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Aspirational District Programme
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AN ASSESSMENT OF
ASPIRATIONAL
DISTRICTS
PROGRAMME
ASPIRATIONAL
DISTRICTS
PROGRAMME
Michael Green
CEO, Social Progress Imperative
Dr. Amit Kapoor
Chair, Institute for Competitiveness
& Visiting Scholar, Stanford University
Michael E. Porter
Professor, Harvard Business School
Foreword By
Scott Stern
Professor, MIT
Authors ASPIRATIONAL
DISTRICTS
PROGRAMME
AN ASSESSMENT OF 04
Amit Kapoor
Chair
Institute for Competitiveness
Michael Green
CEO
Social Progress Imperative
All Images are representative
Authors
Designed By Aspirational Districts Program Foreword
India is at a crossroads. A rising focus on competitiveness has
produced a record of positive economic growth and pockets of
prosperity. India now stands as the fifth-largest economy in the
world. However, the uneven distribution of economic gains across
regions and individual citizens has only served to highlight the
need for a broader agenda aimed at inclusive growth and social
progress. Income growth has been concentrated in a small number
of individuals and regions. And, despite significant investments in
infrastructure and social services, India stands in the 102
nd
position
among 149 countries in the 2019 Social Progress Index. Going
forward, India’s progress should not be measured simply by its
achievement of a certain level of economic growth, but whether
India can realize its extraordinary potential when growth is shared
across the widest number of individuals, and addressing India’s
most pressing social progress challenges.
True success requires the integration of improving competitiveness
and social progress, which is the combination that unlocks
inclusive economic growth.
THE 2018 LAUNCH OF THE
“ASPIRATIONAL DISTRICTS”
PROGRAM (ADP) HAS BEEN
A BOLD AND PROMISING
STRATEGIC STEP TOWARDS
THIS NEW AGENDA. THERE
HAS BEEN A LONGSTANDING
FOCUS IN INDIA ON THE LEAST
DEVELOPED REGIONS ACROSS
THE COUNTRY.
Yet, ADP marks an important shift from pursuing economic growth
per se to focusing on achieving meaningful social progress ADP
benchmarks in 112 less developed Indian districts, and enables
partnerships among states in driving success. The program 06
focuses on practical and measurable
social progress outcomes, including
Health and Nutrition, Education,
Agriculture and Water Resources,
Financial Inclusion, Skill Development,
and Basic Infrastructure. Each of
these are critical to expanding shared
prosperity among all citizens.
By targeting a set of important but
practical areas for improvement at the
district level, ADP brings the promise
of both inclusive development and a
reduction in regional disparity. And,
the focus on enhancing each of these
critical areas offers the opportunity for
these regions to contribute to India’s
broader economic development as a
whole, while raising economic growth
itself over the long run.
The significant promise of the ADP
depends on identifying the most
leveraged areas for improvement, and
developing a broad set of practical
tools for enhancing India’s overall
development agenda.
This report, An Assessment of the
Aspirational Districts Program, offers
a timely yet systematic evaluation
of the ADP and the gains realized
to date. The report focuses on the
most significant economic and
social progress challenges facing
the ADP districts, and evaluates the
progress in these districts over the
first two years of the program. The
report also examines the role of the
stakeholder-oriented model, in which
public awareness, engaged public-
private partnerships, and cooperation
among multiple levels of government
is utilized to enhance the success of
individual initiatives.
Though still at an early stage, the
finding are highly encouraging.
Almost all districts included in the
ADP program have made progress
on key development parameters as
compared to the baseline, and are
performing significantly better today
than they were before the programme
was initiated. Particularly notable are
gains in Health and Wellness, and
Basic Infrastructure. The ADP seems
to not have simply maintained the
districts along a pre-existing trajectory
but materially improved the rate of
improvement.
A striking finding is the impact
of governance. Relative to a
conventional top-down approach, the
ADP supports active collaborations
among multiple levels of governance
within each ADP district, and the
use of public-private partnerships.
This stakeholder-oriented approach
is driven by a shared understanding
among the partners, and the use of
a common language of outcome-
oriented metrics and data. This study
builds on this data collection and
offers an interactive visualization
tool that can be used by the various
stakeholders, based on their own
priorities and resources to make
informed ADP strategy choices.
To date, the ADP focus on both
local economic development as well
as social progress improvement is
yielding positive gains. These early
achievement will catalyse broader
future gains, and accelerate Indian Aspirational Districts Program Prof. Michael E. Porter
Harvard Business School
Prof. Scott Stern
Massachusetts Institute of Technology
THIS REPORT NOT ONLY PROVIDES AN EARLY
ASSESSMENT OF THE ADP, BUT ALSO HAS THE
POTENTIAL TO CATALYSE ACTION THROUGHOUT INDIA.
BY FOCUSING ON “WHAT WORKS” IN ADVANCING
INCLUSIVE GROWTH AND SOCIAL PROGRESS, ADP HAS
THE POTENTIAL TO SERVE AS A MODEL FOR INDIA’S
FUTURE ECONOMIC AND SOCIAL DEVELOPMENT
STRATEGY.
progress towards meeting the Sustainable Development Goals.
The experience of the ADP initiative to date also offers key lessons that can
help galvanise and sustain the ADP program over time. Regional teams
are guided by collecting streamlined outcome data in a timely way, and are
structured so that leadership changes do not disrupt the successful execution of
the program.
Partnerships across districts maximize the spread of key interventions, and can
be expanded. Districts can sharpen their focus on the areas of greatest need,
and work to formalize mechanisms to collaborate and learn from peers and
better performing districts.
As the world continues to grapple with the fallout from the COVID-19 public
health crisis, the importance of resilient, shared economic development
combined with social progress have come into even sharper relief. This study
offers a timely and insightful guide into how and why the ADP program is
beginning to realize this promise in the neediest regions. 08
Executive
Summary
The Government of India
launched the Aspirational
Districts Programme
(ADP) in January 2018 to
accelerate improvement
in the socio-economic
indicators of the most
underdeveloped districts
of the country. Currently,
the programme has been
implemented in
112 OF INDIA’S 739
DISTRICTS, SPREAD
ACROSS THE COUNTRY. Aspirational Districts Program The ADP is a collective
effort. At the Central
level, NITI Aayog
is anchoring the
programme and
individual Ministries
have assumed
responsibilities to
drive the progress of
the districts. Yet it is
the state governments
that are the main
drivers of change.
Each state has formed
a committee under
their respective
Chief Secretaries
to implement as
well as track the
programme. Moreover,
for each district, a
central Prabhari
Officer of the rank of
Additional Secretary/
Joint Secretary has
been appointed to
provide feedback and
recommendations
based on their local
level findings. 10
The research in this study
documents the social development
outcomes in some of the most
challenging regions of India. It
examines institutional best practices,
coordination frameworks across
government bodies and other
partners, and governance and
leadership initiatives at the district
level which can be used to replicate
the success of this initiative not only
in other districts of India, but also in
other countries facing similar socio-
economic challenges.
by measuring the current state of various social parameters and
highlighting the most pressing issues, the programme recognises
that focusing solely on economic parameters will not lead to inclusive
development in India. Moreover, these social challenges might hamper
future economic growth as well.
by focusing on underdeveloped pockets of India it will help in addressing
the issue of regional disparities.
by embedding partners within the institutional rubric of the government
and encouraging them to integrate with the district administration
instead of them functioning as external practitioners of development, the
programme adopts a unique approach that can lead to maximum social
and human development.
The assessment of the programme
reveals insights that can provide
direction to the programme leaders
and implementing agencies about
future focus areas; it can help
in unlocking the full potential of
the programme and can provide
guidance for replicating the
programme across different
geographies.
FIRST,
SECOND,
THIRD,
We find that there are several ways the project contributes to
enhancing the social progress of the region. Aspirational Districts Program • Health and Education are the sectors
in which the districts are closest to
achieving their targets. In health, the
maximum distance of districts away from
their targets is about 30 percent.
• Agriculture and Financial Inclusion are
the main areas of concern for most
aspirational districts as their average
scores lie farthest away from the frontier.
Most of the districts are 40-90 percent
away from their targets.ADP COVERS
5 SECTORS:
Disparities across
sectors are high
HEALTH AND
NUTRITION
FINANCIAL
INCLUSION
AND SKILL
DEVELOPMENT
BASIC
INFRASTRUCTURE
EDUCATION
AGRICULTURE
AND WATER
RESOURCES
Distance to Frontier (Lower the better)
Agriculture and
Water Resources
0
10
20
Figure 1: Average Distance to Frontier across Sectors
30
40
50
60
70
80
90
Health and
Nutrition
Skill
Development
Financial
Inclusion
Education
Basic
Infrastructure
This analysis suggests that areas such as
Agriculture and Water Resources, Financial
Inclusion, and Skill Development require
greater attention in the ADP programme
going forward. 12
The disparities can be also be
seen by looking at a particular
district. Figure 2 below shows the
performance of Dahod district
across sectors. It has overachieved
its target in Health and Nutrition but
lags behind its targets by significant
margins in Agriculture and Water
Resources, Skill Development and
Financial Inclusion. These results
suggest that there are no clear
achievers or laggards across all
sectors.
Three key areas of best practice
have emerged from the ADP
programme:
a) Awareness: several districts have
used awareness campaigns
to reach out to populations
which have been detached
from the development process.
Awareness raising campaigns
help create a common platform
for engagement, thereby helping
with the integration of actors and
beneficiaries.
b) Collaboration: ADP incentivises
collaboration between tiers and
agencies of government and
with the private and civil society
sectors. By leveraging assets
and networks in a collective
effort, ADP enhances the
outreach capacity of the district
administration in integrating the
population.
c) Data-based interventions: the
use of data to measure impact,
locate nodes for improvement,
as well as to identify policies and
interventions that are driving
the most change is critical to the
success of ADP.
Figure 2. Disparities in the performance of Dahod across Sectors
Concrete best practices are
emerging from the programme
Distance to Frontier (How far are the
districts from achieving their target
Agriculture &
Water Resource
Dahod
Dahod
Dahod
Dahod
Tier
14
DahodDahod
Achievement of Target
Basic
Infrastructure
Financial
Inclusion
Health &
Nutrition
Skill
Development
Education
Basic
Infrastructure
(Electricity, internet,
roads, latrines,
water, CSCs, and
pucca houses
80
70
60
50
40
30
20
10
0
-10 This study also sheds light on the economic
benefits that the country can derive by addressing
social challenges. In Health and Nutrition, for
example, the economic impact of reducing Severe
Acute Malnutrition (SAM) among children is felt
through the effects on productivity and lifetime
learning. The overall economic impact for all the
states (only looking at Aspirational Districts) of
reducing SAM is estimated to be a mammoth
Similarly, the impact of
providing household
latrines is around
These economic
benefits can provide
a strong rationale
for the government
in investing in
programmes directed
towards social
benefits.
ADP is generating economic
as well as social impact
1.43 LAKH CR.
INR 400 CR.
Aspirational Districts Program 14
There is significant diversity among
the districts covered by ADP.
The indicators of the programme
also range from inputs through
to outcomes. This suggests two
opportunities to enhance data
collection and analysis:
a) Survey methods should be
adjusted to reflect the fact that
not all ADP indicators show
change at similar frequency.
Output and outcome indicators
that show change over the long-
run should be assessed on an
annual basis, while short-run
input indicators can continue to
be assessed on a quarterly basis.
This would also improve survey
reliability. Moreover, it would help
ADP leaders to streamline the
chosen group of indicators that
form the basis of competition
among the aspirational districts.
For example, indicators like
percentage of pregnant women
taking nutrition and those
having severe anaemia treated
are heavily correlated (0.89); it
would be ideal to resolve such
duplication of assessment.
b) The study shows that districts
that are at different levels
progress at different rates. For
example, districts at a lower level
that are catching up will be able
to progress faster than the most
advanced districts. Therefore, it
is suggested that districts are
divided into peer groups based
on their level of development, to
facilitate relevant lesson sharing.
Streamlining data collection and
ensuring effective feedback loop to
update programmes based on relevant
data insights is critical Aspirational Districts Program 16 Contents Foreward
Executive Summary
Introduction
Understanding the
Aspirational Districts
Programme (ADP)
Literature Review:
Impact Evaluation of Public
Programmes
Methodology:
Assessing the Aspirational
Districts Programme
Results
Discussion of Results
Impact of ADP:
Beating Secular Trends?
Impact of ADP:
Attaining the SDGs
Learnings:
Leveraging the Partner
Ecosystem
Recommendations
Appendix
05
08
22
30
44
50
58
104
122
132
140
160
166 18
LIST OF FIGURES
Figure 1 District Level Social Progress Index
Figure 1.1 The Key Focus Areas of ADP
Figure 1.2 Transformation of Partner Ecosystem
Figure 4.1 Distance to Frontier Analysis: Health and Nutrition
Figure 4.2 Mobility Matrix for Health and Nutrition
Figure 4.3 Future Engagements in Health and Nutrition
Figure 4.4 Top ten districts with the most improvement in SAM in 2019
Figure 4.5 State-wise impact of total potential savings
Figure 4.6 Distance to Frontier Analysis: Education
Figure 4.7 Mobility Matrix: Education
Figure 4.8 Future Engagements in Education
Figure 4.9 Distance to Frontier Analysis: Financial Inclusion
Figure 4.10 Mobility Matrix: Financial Inclusion
Figure 4.11 Future Engagements in Financial Inclusion
Figure 4.12 Distance to Frontier Analysis: Agriculture and Water Resources
Figure 4.13 Mobility Matrix: Agriculture and Water Resources
Figure 4.14 Future Engagements in Agriculture and Water Resources
Figure 4.15 Distance to Frontier Analysis: Skill Development
Figure 4.16 Mobility Matrix: Skill Development
Figure 4.17 Future Engagements in Skill Development
Figure 4.18 Potential Economic Gains due to Skill Development in INR Crores
Figure 4.19 Distance to Frontier Analysis: Basic Infrastructure
Figure 4.20 Mobility Matrix: Basic Infrastructure
Figure 4.21 Future Engagements in Basic Infrastructure
Figure 4.22 Coverage Status of IHHL across all States
Figure 4.23 Number of deaths due to Diarrhoeal diseases (0-4 Years) in
India (2013-17)
Figure 4.24 Actual Scores for 2019 (Difference between Current Scores and
Baseline Scores)
Figure 4.25 State-wise economic savings due to IHHL based on incremental
progress during 2018-2019
Figure 4.26 Actual Scores for 2019 (Difference between Current Scores and
Baseline Scores)
18 Aspirational Districts Program LIST OF TABLES
Figure 4.27 State-wise economic savings due to potable water based on
incremental progress during 2018-2019
Figure 4.28 Savings over costs for the Top 10 States in 2019
Figure 5.1 Relationship between rate of change (2018-2020) and baseline
scores
Figure 5.2 State-wise change in mean scores
Figure 5.3 Performance of Districts across parameters
Figure 5.4 Performance of Districts in the Healthcare Ecosystem
Figure 5.5 Comparison of Mean Scores for Short-Term, Medium-Term and
Long-Term Indicators
Figure 5.6 Comparison of mean score for impact and performance
indicators
Figure 6.1 Percentage of Institutional Deliveries to Total Deliveries (2015-
2016)
Figure 6.2 Percentage of Schools with functional Drinking Water (2015-
2016)
Figure 7.1 SDG Target Achievement for Health
Figure 7.2 SDG Target Achievement for Education
Figure 7.3 SDG Target Achievement for Basic Infrastructure
Figure 8.1 The 6-point Engagement Framework
Figure 8.2 The first step of the framework
Figure 8.4 The third step of the framework
Figure 8.5 The fourth step of the framework
Figure 8.6 The fifth step of the framework
Figure 8.7 The sixth step of the framework
Aspirational Districts Program
Table 1.1 Framework used for selection of Aspirational Districts LIST OF ABBREVIATIONS
3Cs Convergence, Collaboration and Competition
ADAspirational District
ADP Aspirational District Programme
APY Atal Pension Yojana
ASHA Accredited Social Health Activist
BMGF Bill and Melinda Gates Foundation
CAG Comptroller and Auditor General
CRC Citizens’ Report Cards
DALY Death-Adjusted Life Year
DBT Direct Benefit Transfer
DCs District Collectors
DDU-GKY Deen Dayal Upadhyaya Grameen Kaushalya Yojana
DFIC District Financial Inclusion Co-ordinator
DMs District Magistrates
DTF Distance to Frontier
EIA Environment Impact Assessment
HMIS Health Management Information System
HWCs Health and Wellness Centres
ICDS Integrated Child Development Service
ICT Information and Communications Technology
IFC Institute for Competitiveness
IHHL Individual Household Latrines
LDM Lead District Manager
LWE Left Wing Extremism
MAM Moderate Acute Malnutrition
20 MHA Ministry of Home Affairs
MoHFW Ministry of Health and Family Welfare
NRDWP National Rural Drinking Water Programme
PHCs Public Health Centres
PMGSY Pradhan Mantri Gram Sadak Yojana
PMJDY Pradhan Mantri Jan Dhan Yojana
PMJJBY Pradhan Mantri Jeevan Jyoti Bima Yojana
PMKVY Pradhan Mantri Kaushal Vikas Yojana
PMSBY Pradhan Mantri Suraksha Bima Yojana
PWDs Persons with Disabilities
RFD Results-Framework Document
RTE Right to Education Act
SAM Severe Acute Malnutrition
SAUBHAGYA Pradhan Mantri Sahaj Bijli Har Ghar Yojana
SDGs Sustainable Development Goals
SMCs School Management Committees
TBTuberculosis
UDISE Unified District Information System for Education
Aspirational Districts Program Introduction
On several counts, India can
be mistaken for a continent.
Most notably these include
the size of the land and
the diversity of her people.
Upon taking a closer look,
such characteristics become
evident in more granular
aspects as well. The vast
disparities in regional
development across Indian
states that stand at different
stages of economic and
social development is one
such glaring trend that
showcases its curious
heterogeneity.
The economic contribution
of the peninsular states
is higher than that of
hinterland states creating
a north-south divide. For
instance, the population of
Maharashtra is almost half
as that of Uttar Pradesh
but the size of its gross
domestic product (GDP) is
almost twice as much. The
gap is also widening over
time. The per capita income
of the richest five states,
which was 145 percent
higher than that of the
poorest five states at the
beginning of the millennium
has risen to over 400
percent in 2018-19.
1
These trends point to
the fallacy of looking at
development solely through
the lens of economic growth
and average statistical
barometers like GDP or
even per capita GDP. Such
averages hide the deep
inequities that are prevalent
in the Indian life. The realities
of one corner this continent-
sized nation and nation-
sized states are typically
very different from another
corner of the landmass.
1
Data retrieved from Ministry of Statistics and Programme Implementation
(MoSPI), Government of India. Aspirational Districts Program 2
The list of the 112 Aspirational Districts is
provided in the Appendix.
Clearly, India’s high growth over
the last few decades has been slow
to reach across all geographies.
In order to set this skewed
path of development aright, the
government has launched the
‘Transformation of Aspirational
Districts’ Programme across the
most backward districts of India
in January 2018. The programme
effectively aims to bring in
expeditious improvements in the
socio-economic status of 112
2
of
the most backward districts in the
country, including 35 Left Wing
Extremism (LWE) affected regions.
The idea has been to focus on the
regions that have faced challenges
in bettering socio-economic
outcomes and in narrowing the gap
on key development parameters
with the rest of the country. Once
the seeds of development are sown
in the least developed regions
of the country, the country itself
will witness rapid development
in a more inclusive manner. As
the COVID-19 pandemic ravages
across the world and its effects
are felt for decades to come on the
socio-economic well-being of the
people, the programme can help
to address the regional inequality
in development gains before they
exacerbate and become cemented
in time. NEED FOR THE PROGRAMME
The Transformation of
Aspirational Districts
programme is an effort to
take the conversation on
development beyond the
narrow domain of economic
advancement. Over the years,
countries have relied heavily
on traditional measures of
economic development like
the GDP to define success.
India’s development has also
been celebrated on being able
to drive its per capita income
numbers by almost four times
between 1988 and 2018.
However, India has not been
able to fully transform its
remarkable economic success
into social development.
According to Social Progress
Imperative, India’s rank
on Social Progress Index
remained constant from 2014
to 2018 at 103rd position with
a marginal increase of 2.1 in
its score. In 2019, India was
able to move up the ladder
by one rank. Similarly, if one
looks at HDI India was able to
improve its score from 0.640
to 0.647 in 2019. However,
when its discounted for
inequality HDI score falls by
26.3 percent to 0.477. This
fall is slightly higher than the
average loss due to inequality
in “Medium HDI Countries”.
On some social parameters,
India fares poorly compared
to its neighbours. The infant
mortality rate for India,
which stands at 37.9, is not
only higher than the world
average but also than its
low-income neighbors Nepal
and Bangladesh. A baby
born is India is nearly 1.2
times as likely to die during
the first year of life as one
born in Nepal. These social
challenges might hamper
India’s economic growth in
future as well. For instance, an
unhealthy workforce would
mean that the country is
less productive compared to
other nations. It is therefore
important that we focus
on social parameters along
with traditional measures of
progress.
Moving Beyond Economic
Measures of Success
The Transformation of Aspirational Districts programme is driven by the following ideas
that signal a shift in the approach of the government towards policy and governance:
24 Aspirational Districts Program
THEREFORE, EVEN THOUGH ECONOMIC MEASURES ARE USEFUL
GUIDES OF PROGRESS, THEY DO NOT ADEQUATELY REFLECT THE
QUALITY OF LIFE OF THE PEOPLE. THE TRANSFORMATION OF
ASPIRATIONAL DISTRICTS PROGRAMME MAKES AN ATTEMPT TO
ADDRESS THIS SHORTCOMING BY MONITORING PERFORMANCE
ON THE ESSENTIAL ELEMENTS THAT DEFINE A GOOD SOCIETY LIKE
HEALTH, EDUCATION, AND BASIC INFRASTRUCTURE. India is well known for its diversity.
It presents endless varieties of
physical features, cultural patterns,
religions, languages etc. However,
this diversity is not only limited to
the physical characteristics of the
country but is also highlighted in
the development parameters. For
instance, the maternal mortality
ratio is 46 per 1,00,000 live births in
Kerala vs 237 per 1,00,00 live births
in Assam
3
.
Figure 1:
District
Level Social
Progress
Index
26
Enabling Equitable Regional
Development
Measure Values
0100
3
Data retrieved from NITI Aayog, Government of India. Aspirational Districts Program
This disparity does not only exist
across states but percolates down
to the lowest level of geographies.
A recent Lancet study showed
that among the 723 districts of
India in 2017, the prevalence of
stunting ranged from 16.4 percent
to 62.8 percent, wasting ranged
from 5.5 percent to 30 percent,
and underweight children ranged
from 11 percent to 51 percent.
4
The district level social progress
index (presented in Figure 1) that
measures the performance of
districts across 12 facets of social
progress including healthcare,
education, personal rights etc clearly
highlights this disparity that exists
within Indian districts. The scores
range from 28.6 to 76.8 on a scale
of 0-100. Even states with high per
capita GDP such as Maharashtra
have some districts in the bottom
tier, implying that having a high GDP
doesn’t translate into high social
progress.
Therefore, if India must achieve
comprehensive social and human
development it has to ensure that
its most under-developed pockets
socially progress.
THE TRANSFORMATION OF ASPIRATIONAL DISTRICTS
PROGRAMME IS A SIGNIFICANT STEP TOWARDS
ADDRESSING THE REGIONAL DISPARITIES ACROSS THE
INDIAN LANDSCAPE.
4
Hemalatha, R., Pandey, A., Kinyoki, D., Ramji, S., Lodha, R., Kumar, G. A., ... & Laxmaiah, A. (2020).
Mapping of variations in child stunting, wasting and underweight within the states of India: The Global
Burden of Disease Study 2000–2017. EClinicalMedicine, 100317. 28
The Aspirational Districts
programme is a key governance
initiative that is being driven in
the spirit of driving development
changes through the spirit of
competitive federalism among
geographies. The states are the
main drivers of the programme
where they work with the central
government to identify and target
development goals for these
districts. The District Magistrates
are the pillars on which the
programme rests. The competition
among different districts motivates
them to outperform their peers and
also learn from in the process.
The objective of imbibing a spirit of
competitive federalism at all levels
of governance is to not just about
competition but also to work in
partnership with the least developed
regions of the country and help them
transform, which is encapsulated in
the idea of cooperative federalism.
The combination of competition and
cooperation across different levels of
geographies and governance fuels
the Transformation of Aspirational
Districts programme.
Driving Change through Cooperative
and Competitive Federalism
THE TRANSFORMATION OF ASPIRATIONAL DISTRICTS
PROGRAMME IS DRIVEN BY A SPIRIT OF COMPETITIVE
FEDERALISM TO ENCOURAGE DIFFERENT GEOGRAPHIES
TO WORK TOWARDS A COMMON GOAL OF
DEVELOPMENT Aspirational Districts Program
The Transformation of Aspirational
Districts Programme has been
running for over two years across
112 districts. Over this period,
the programme has generated
an impact at the ground level
on the set of socio-economic
parameters upon which it focuses.
The study is being undertaken
to develop an assessment of
these transformations. The broad
objectives of the study are to:
1. Conduct a holistic assessment
of the programme and the
performance of the districts in
improving the lives of citizens.
2. Assess whether the programme
has accelerated the socio-
economic development of these
districts in comparison to their
trends before the programme was
implemented.
3. Documentation of the institutional
best practices of the initiatives
taken by the districts to draw
learnings for the programme.
4. Analyse the vertical and
horizontal coordination
frameworks between government
bodies and the partners engaged
with the programme.
5. Develop actionable
recommendations to enable the
future transition roadmap for the
initiative and help India progress
towards its goals for social
development.
The study will give a sense of how
the aspirational districts have
performed under the programme
and what are the challenges and
opportunities it presents moving
forward. It will also provide learnings
for countries that intend to replicate
such interventions. Moreover, it can
also help the Indian government in
case the program is extended to
other districts.
MOTIVE OF THE STUDY:
ASSESSING THE IMPACT 30
UNDERSTANDING THE
ASPIRATIONAL
DISTRICTS
PROGRAMME (ADP)
01
ADP WAS IMPLEMENTED WITH A STRATEGY
TO RAPIDLY TRANSFORM DISTRICTS WITH
RELATIVELY LOW SOCIAL AND HUMAN
DEVELOPMENT TO BOOST THE OVERALL
HUMAN DEVELOPMENT OF THE COUNTRY. Aspirational Districts Program ADP ADP began with the selection of
the least developed districts in the
country. The selection of the districts
was based on a composite index
consisting of challenges faced by
the districts in terms of the poverty
of their citizens, relatively poor
health and nutritional outcomes,
educational status, and deficient
infrastructure
5
. Table 1.1 shows the
list of indicators and the weightages
used to calculate the index.
SELECTION OF THE DISTRICTS
5
Transformation of Aspirational Districts, A New India by 2022, Page 2
Landless
households
dependent on
Manual labour
(SECC D7)
Ante-natal
care (NHFS-4)
Institutional
delivery
(NHFS-4)
Stunting of
children below 5
years (NHFS-4)
Wasting
in children
below
5 years
(NHFS-4)
Elementary drop-
out rate (U-DISE
2015-16)
Adverse
pupil teacher
ratio (U-DISE
2015-16)
Un-electrified
households
(Ministry)
Households
without individual
toilets (Ministry)
Un-connected
PMGSY village
(Ministry)
Rural Household
without access to
water (Ministry)
25%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
HEALTH
A
N
D
N
U
T
R
IT
IO
N
E
D
U
C
A
T
I
O
N
IN
F
R
A
S
T
R
U
C
T
U
R
E
D
E
P
R
I
V
A
T
I
O
N
Table 1.1.
Framework
Used for
Selection of
Aspirational
Districts
32 The results of the index were
analysed and after deliberations
with all the key stakeholders, it was
decided that at least one district
should be included from every state
keeping in line with the spirit of
competitive federalism. Initially, 117
districts from 27 states and 1 Union
Territory (J&K) were selected to be
a part of the programme. However,
five districts of West Bengal did not
join the programme and now the
programme comprises 112 districts
from 26 states and 1 Union Territory.
Aspirational Districts Program 34
The programme is based on
three core principles, which are
encapsulated in the 3Cs Approach
– Convergence (of Central and State
schemes), Collaboration (among
citizens and functionaries of Central
& State Governments including
district teams), and Competition
(among districts). The 3Cs are
themselves interconnected with
each other. The programme aims
to create a convergence between
the central and state government
schemes and initiatives directed
towards similar policy goals by,
first, improving collaboration
between the civil society and the
functionaries of the state and
central government, including the
Prabhari Officers and, second, by
developing a spirit of competition
among the districts using the
monitoring dashboard and the
monthly ranking system.
THE 3C
APPROACH
Create convergence among State and Central
Government initiatives at the district level to
overcome constraints
CONVERGENCE
COMPETITION
COLLABORATION
Promote competition among states and districts
using the “Champions of Change” monitoring
dashboard
This implies forging of cooperation between the
civil society and the functionaries of Central & State
Governments including district government bodies.) Aspirational Districts Program The programme is a collective
effort of the Central and State
governments; however, States
are the main drivers of change.
The States have either formed a
committee under their respective
Chief Secretaries or appointed a
nodal officer to implement as well
as to track the programme. At the
Central level, NITI Aayog is steering
the implementation of this initiative.
Additionally, individual Ministries
have assumed responsibilities to
drive the progress of the districts.
The structure of the programme is
classified further into:
1. For each district, a Central
Prabhari Officer of the rank
of Additional Secretary/ Joint
Secretary, and a similar State
Prabhari Officer at the level
of the State Government has
been nominated to create policy
convergence and promote
collaboration across all levels of
the government.
2. An Empowered Committee
which has been set up under the
chairmanship of the CEO, NITI
Aayog is expected to ensure
convergence in schemes and
address specific issues and
challenges that are raised by the
Prabhari Officers nominated for
each district.
The structure of the programme has
allowed for decentralisation that
has enabled local experimentation
in the selected districts based on a
firm appreciation of ground realities.
The local government institutions,
working in collaboration with the
Central and State government, are
in a position to ensure that different
measures are undertaken to bring
in socio-economic changes at
the ground level. And this greater
participation of the local and state
governments is an essential driver
of change in the ADP.
The structure of the programme is
reflective of cooperative federalism,
wherein the local, state and the
central governments are working
together to attain growth at a
micro-level. The idea being that the
programme aspires to harness the
uniqueness of each district in terms
of the strengths they possess as
well as the challenges they face to
enhance better human development
for its citizens through competition,
convergence, and collaboration.
BASIC STRUCTURE OF THE
PROGRAMME 36
ADP focuses on five main
themes – Health & Nutrition,
Education, Agriculture & Water
Resources, Financial Inclusion
& Skill Development, and Basic
Infrastructure. These five identified
thematic areas are further broken
down into 49 indicators. The
distribution of these indicators is
shown in Figure 1.1.
The reason why the programme
includes these particular themes is
that they directly impact the quality
of life as well as the economic
productivity of citizens. The salient
feature of this programme is that
NITI Aayog in collaboration with the
Planning Department, Government
of Andhra Pradesh has created an
accessible dashboard, where 81
data-points are tracked regularly.
THE PROGRAMME METRICS
Figure 1.1.
The Key
Focus Areas
of ADP
Aspirational Districts
Programme Focus Areas
ADP MONITORS 81 DATA
POINTS FOR 49 INDICATORS
Monitoring Indicators
30
10
30
55
20
Education
Basic
Infrastructure
Health &
Nutrition
Skill
Development
Financial
Inclusion
Agriculture
and Water
Resources
8 Indicators
14 Data Points
7 Indicators
8 Data Points
13 Indicators
31 Data Points
5 Indicators
10 Data Points
10 Indicators
12 Data Points
6 Indicators
6 Data Points Broadly, dashboards are expected
to display data integrated from
multiple sources and exhibit the
same in an easy-to-comprehend
manner. This allows any individual
to understand complex information
in less time than it would take to
read through an entire report. At
the same time, dashboards are
self-contained in explanation. For
example, in the context of ADP, the
dashboard tracks key indicators
with real-time visibility of how the
districts are performing and the
distance of them from their targets.
The districts have been responsible
for entering the data since April
1, 2018. It should be kept in mind
that districts only fill the data for
the indicators that are collected by
them locally. They play no role in
entering some indicators such as
the ones in Financial Inclusion.
Based upon their entry, they are ranked based on progress made
on a real-time basis. There are two types of ranking that emerge
from this database:
The dynamic system of ranking
acts as a tool that is enabling
the districts to identify indicator
specific challenges and help them
to immediately take corrective
measures. The entire process of
an incremental ranking system is
expected to inculcate a sense of
positive competition among the
districts in their endeavour to not
only become the best within their
state but also within the nation.
This is an endeavour to create
an atmosphere of competitive
federalism.
• DELTA-RANKING – WHICH CAPTURES THE CHANGE
IN DISTRICT RANKINGS OVER TIME AND ARE SHOWN
ON THE DASHBOARD AND ARE PUBLISHED AS
REGULAR REPORTS BY NITI AAYOG
• BASELINE RANKING – WHICH CAPTURES THE
DISTRICT PERFORMANCE COMPARED TO THE
BASELINE YEAR AND WAS PUBLISHED AS A
COMPREHENSIVE REPORT BY NITI AAYOG.
Aspirational Districts Program 38
Furthermore, the dashboard is
available to the public to monitor the
progress of the aspirational districts.
This is particularly important when we
view it from the point of accountability
as well as maintaining transparency
to the public. Such efforts have been a
highlight of the current administration
as exemplified in the implementation
of programmes like Direct Benefit
Transfer and Jan Dhan-Aadhar-Mobile
(JAM). The idea, which perpetuates
from the ADP dashboard initiative,
is that such platforms allow the
public to participate in the process
of governance, aside from ensuring
accountability and transparency.
Hence, the creation of the dashboard
to track the progress of the
programme as well as to disseminate
data grounded in evidence has been
an important step.
The uniqueness of the program is
reflected in two ways
7
1. The programme has effectively
managed to shift the focus from
outputs to outcomes, such as
evaluation of socio-economic
measures of malnutrition, skilling
and learning, among others. An
outcome-based evaluation is
expected to answer essential
questions such as, “What is the
extent to which the programme
has achieved its intended
result?”, “What difference did the
programme make?” and “How
did the participant benefit from
the programme?”. ADP provides
the opportunity to assess the
programme in terms of these
questions because they have
managed to disseminate data
effectively. This leaves scope for
impact evaluation to assume an
important role in the context of
ADP.
The monitoring of the data has
further provided an incentive to
government officials to deliver
results in a timely and expert
manner. Performance evaluation
of the programme is sure to
act as a motivation to the local
government officials to improve
their performances.
2. The programme has managed to
actively encourage collaborations
with international development
AT ITS CORE,ADP SEEMS TO HAVE PRIORITISED
PROMOTING A CULTURE OF PRODUCING RELIABLE
AND ACTIONABLE DATA POINTS AND ENSURING AN
INCREASE IN THE USE OF DATA TO CLOSELY MONITOR
THE PERFORMANCES OF THE DISTRICTS.
7
Hemalatha, R., Pandey, A., Kinyoki, D., Ramji, S., Lodha, R., Kumar, G. A., ... & Laxmaiah, A. (2020).
Mapping of variations in child stunting, wasting and underweight within the states of India: The Global
Burden of Disease Study 2000–2017. EClinicalMedicine, 100317. organisations and civil
society to create a better
impact. The knowledge
partner of NITI Aayog,
Bill and Melinda Gates
Foundation (BMGF)
in partnership with ID
Insights and Tata Trusts
has carried out three
rounds of household
surveys in all the
Aspirational Districts
beginning in June 2018
and covering more than
1,00,000 households.
These surveys were
used to validate 20
self-reported data-
points and estimate nine
further data-points for
which district-level data
is usually not readily
available at regular
intervals.
Each of these initiatives
has been a significant step
away from the existing state
of affairs in governance
today, or in other words, a
step away from the status
quo. The programme has
created an opportunity
to ensure sustained
institutional processes of
impact evaluation by easing
access to data and creating
the ability to accurately
measure the performance of
the programme. Therefore,
it is critical to carefully
document and to learn
from the experiences of this
programme. This report is an
attempt towards ensuring
the same.
Aspirational Districts Program 40
ADP, by design of its policy
framework, does not recognise
the development partner as an
external funder or an agency that
“supplements and complements”
the work of the government in
isolation. The development partner
is predominantly identified as
an external knowledge resource
integrated within the state
institutions to bridge critical gaps
in governance or citizen service
delivery that may arise owing to
niche and/or structural challenges
that are prominent in some of the
most under-developed regions
of the country. The partners are
expected to improve the quality of
governance at the grassroots and
also to augment the capacity of the
district administration to deliver
citizen services by overcoming any
structural challenges prevalent in
the district. This is achieved either
by creating capacity in personnel
(such as partner initiatives to
training government officials)
or by creating innovative policy
interventions in collaboration with
the district administration (such as
establishing community kitchens
to improve access to nutrition for
children in a predominantly tribal
district of Maharashtra).
LEVERAGING THE
PARTNER ECOSYSTEM
ADP Approach to Partner Ecosystem
UNLIKE TRADITIONAL PARTNER ENGAGEMENT
APPROACHES, THE GOVT HAS INTEGRATED PARTNERS
INTO THE ADP FRAMEWORK
Traditional Engagement of Development Partners
Government
Citizens
Development
Organisations+NGOs/
NPOs/Donor Agencies
Figure 1.2.
Aspirational
Districts
Programme
has been
able to
effectively
integrate the
development
partners
within the
institutional
rubric of the
government. Aspirational Districts Program In the initial phase, the perceived
role of development partners was
primarily restricted to the 3
rd
C of
the 3C model under ADP. They were
expected to collaborate with the
respective district administrators to
promote efficiency and innovation in
public service delivery systems, as
indicated by one of the stakeholders
interviewed within the scope of this
research.
The other critical role being played
by the partner ecosystem relates
to the aspect of data validation.
The data validation partners,
who conduct field surveys to
check the quality of reported data
under ADP, ensure performance
management and accountability,
which promotes “competition”
amongst districts. The aspect of
social audit of public policy or
other government programmes is
Under the Aspirational District
Programme, the development
organisations and NGOs/NPOs
have been embedded within the
institutional apparatus of the
government to:
1. Bridge the critical knowledge
and resource gaps to expand
the scale and scope of citizen
services through convergence
and collaboration;
2. To facilitate open performance
management by validating the
achieved social outcomes; and
3. Promote policy innovation at the
grassroots to overcome niche
challenges in districts that leads
to exclusion of citizens from
public services.
Partner Ecosystem under ADP
Government
Citizens
Development
Organisations+NGOs/
NPOs/Donor Agencies not a new phenomenon. However,
the integration of the validation
partner within the policy design
of a programme is a progressive
policy move that is seen within
this programme. Very few policies
or programmes show such an
integrated design feature.
Gradually, the assimilation of the
partner organisations within the
broader institutional framework of
the programme also enabled some
informal and organic connections to
develop between the administration
and the partners. For instance,
in the interviews conducted, one
partner revealed that the district
administration connected with their
young professionals to brainstorm
on issues that are not within the
direct scope of the organisation.
This indicated that the partner
ecosystem was also able to create
informal and organic knowledge
networks within the administration.
These knowledge networks
of young fellows or personnel
present within the office of
District Collectors (DCs) or District
Magistrates (DMs) enable them to
create innovative policy actions
to overcome niche challenges by
“convergence”. Effectively, the
partner ecosystem does not only
cater to 3
rd
C but all the 3Cs of this
programme. It drives collaboration.
The data validation partners help in
promoting competition. The informal
knowledge networks created
between the young professionals
of the partner ecosystem and the
district administration promotes
convergence to overcome niche
challenges wherever applicable.
Furthermore, the “new” knowledge
brought in by the partners allows
the district administration to expand
its capacity in areas that were
traditionally catered to by other
public institutions. For instance,
banking-related institutions
traditionally catered to financial
inclusion in any district as the DC/
DM Offices did not have experts
or line-officials to drive financial
inclusion. The Lead District Manager
(LDM) of the banks and some other
institutions providing relevant
microfinance services primarily
did this. However, under ADP,
several districts have partnered
with development partners
who have domain expertise in
microfinance services and financial
inclusion. This has enabled the
district administration to expand
its capacity in an area which was
traditionally not within their scope
but was crucial to their work as
most of the citizen services and
benefits are gradually coming
under the framework of Direct
Benefits Transfer (DBT) which
makes financial inclusion critical for
delivering citizen services.
To sum up, the partner ecosystem
under ADP considers development
partners or development
organisations as external
knowledge resources that help the
state to bridge critical gaps. Instead
42 of being outside the institutional
rubric of the state, this has emerged
as one of the very few programmes
where the development partners
have been integrated within the
district administration. This has led
to several development partners to
establish representatives working
in the office of the district and block
administration in an Aspirational
District. Instead of supplementing
and complementing the work of the
government, these organisations
are now actively enhancing the
impact of government policy by
improving governance and creating
state capacity at the grassroots.
Aspirational Districts Program LITERATURE REVIEW
IMPACT EVALUATION OF
PUBLIC PROGRAMMES
02LITERATURE REVIEW 8
Blomquist, John. 2003. Impact evaluation of social
programs: a policy perspective, Washington, DC:
World Bank. http://documents.worldbank.org/curated/
en/386851468140967391/Impact-evaluation-of-social-
programs-a-policy-perspective
WHAT ARE IMPACT
EVALUATIONS?
Impact evaluations measure the impact
of direct participation in a programme
or intervention
8
on its participants (for
instance, districts in case of ADP). The role
of an impact evaluation study is not only
limited to quantifying the programme’s
impact. The study moves on to explain
why they occurred (or did not), and the
policy implications that arise from the
evaluation. An impact evaluation does
more than merely detect programme
effects – it also examines the programme
process, reasons for observed outcomes,
and cost-effectiveness. The process of
a good impact evaluation, therefore,
helps to clarify the programme plans,
improving communication among partners,
and gathering the necessary feedback
needed to improve and be accountable for
programme effectiveness.LITERATURE REVIEW 46
The first and foremost objective of an impact evaluation
study is to understand the effect of the government
program and interventions.
Detect Program Effects
It also helps to clarify the program
plans, improving communication
among partners, and gather the
necessary feedback for improvement.
Examine the Program Process
A proper impact evaluation is
supposed to include not only the
quantitative estimates, of pragram
impacts, but also is expected to
explain why they occured, and the
policy implication that arise from
the evaluation
Evaluate the reason
for observed outcomes
The examination of cost helps in designing
future developement aimed at fostering
similiar outcomes of interest.
Evaluate cost-effectiveness
Figure 2.1:
Role of Impact
Evaluation Aspirational Districts Program THE FIRST
is accountability to ensure that the development
programmes or interventions lead to development
outcomes.
THE SECOND
that evaluation serves is learning. This mainly aims to
suggest an evidence base for choosing and designing
development interventions that are likely to be effective
in fostering similar outcomes of interest
9
.
However, there are undoubtedly
significant considerations to
be taken into account before
conducting an impact evaluation of
a particular programme
10
. The first
one involves selecting a specialised
evaluator, preferably someone
external to the government or any
other implementing agency. This
preference is to ensure objectivity
and independence. Additionally,
the World Bank mentions that
specialised skills and expertise are
necessary to conduct a quantitative
impact evaluation.
The second one involves selecting
an appropriate quantitative method
to estimate impacts. There are
two kinds of designs available
for the same – experimental and
non-experimental. Experimental
estimates compare the outcomes
of the participants with those that
arise from a randomly assigned
control group. The control group
is otherwise eligible for the
programme and similar to the
participants or the treatment
group but did not receive program
benefits. If we were to contextualise
this for ADP, it would imply taking
into consideration the districts
that have been selected under this
programme and comparing them
with a control group of districts who
are eligible but did not make it to
the programme. An experimental
design is usually preferred on
methodological grounds. This
IMPACT EVALUATION PRIMARILY
SERVES TWO PURPOSES.
9
Impact Evaluation of Development Interventions: A Practical Guide, H. White, David A. Raitzer, ADB, 2017
10
Blomquist, John. 2003, Impact evaluation of social programs: A policy perspective, Washington, World
Bank, http://documents.worldbank.org/curated/en/386851468140967391/Impact-evaluation-of-social-
programs-a-policy-perspective 48
minimises the effects of pre-existing
differences that exist between
the participants (or, the treatment
group), and the comparison group
that can be, otherwise, confounded
with the impacts of program
participation (or, selection bias). In
case a random assignment is not
being taken into consideration, it
may still be possible to estimate
impacts reliably using non-
experimental methods. Multivariate
regression models, matched-
comparison methods, double-
difference, and instrumental-
variables methods can attempt to
control statistically for sources of
selection bias.
Most recent impact evaluations in
developing countries have relied
upon non-experimental methods
due to cost constraints and
data availability considerations.
Therefore, it has become
increasingly crucial to integrate
qualitative methods and permit
a grounded analysis of the
underlying causes of outcomes.
They allow a deeper understanding
of the programme processes,
external conditions, and individual
behaviours. The methods are open-
ended, relying on semi-structured
interviews in an individual or group
setting and on the interviewer
observations.
The availability, as well as the
quality of the data, is the most
critical factor affecting the quality
of impact evaluations. New
surveys are frequently required to
retrieve substantial information on
programme participants, including
baseline and follow-up surveys. Aspirational Districts Program Governments around the world
introduce many programs and
interventions to address different
developmental challenges within
their countries. But, how do we
know that the programme is
working the way it was intended
to since its conception
11
? If the
interventions are not effective,
and even if they are, how can they
be improved upon to make them?
All of this has led to a growing
trend towards the better use of
impact evaluation to understand
and improve the practice of using
the same. Evaluating government
programs and interventions to
understand their impact and
developing the prerequisite
infrastructure to support a
sustained level of high-quality
evaluations should, therefore, be
a priority. The systematic use of
evaluation may lead to solving
of the problems posed by the
aforementioned questions and help
governments identify the challenges
and scopes of their programmes.
IN GENERAL, AN IMPACT EVALUATION SEEKS TO ASK QUESTIONS AROUND THE
FOLLOWING:
1. Implementation: Are the activities of the
programme put into place as originally
intended?
2. Effectiveness: Is the programme
attaining the goals and objectives that it
was intended to accomplish?
3. Efficiency: Are the activities of the
programme being produced with optimal
use of resources, which include budget
as well as staff-time?
4. Cost-Effectiveness: Is the benefit of
attaining the goals and objectives of the
programme significantly higher than the
cost of producing the same?
5. Attribution: Can the success of
achieving the goals and objectives be
related to the programme, or assigned to
other interventions that are in place at
the same time?
All of these questions are asked to
document programme progress,
demonstrating accountability to
funders, policymakers and the civil
society or identifying ways to make
the programme better. It can also
depict how those outcomes differ
among different populations and
what factors are responsible for
those outcomes.
11
“Recommended Framework for Program Evaluation in Public Health Practice,” B. Milstein, Scott Wetterhall,
and the CDC Evaluation Working Group.
ROLE OF IMPACT EVALUATION IN
PUBLIC PROGRAMMES: 50
Performance measurement is an approach that
incorporates the monitoring and showcasing of
accomplishments under a particular programme,
with respect to the progress toward pre-
established goals
12
. The role of performance
measurement is to provide a descriptive picture
of the “participants” under a given programme
and their intermediate outcomes. However,
this process does not draw any causal links
pertaining to the findings/outcomes. Performance
measurement is followed with a non-
experimental design to assess the impact of the
programme in the following sections.
METHODOLOGYMETHODOLOGY
ASSESSING THE ASPIRATIONAL
DISTRICTS PROGRAMME
03
19
Executive Office of the PresidentCouncil of Economic
Advisers. (2014). Economic Report of the President (2014). Aspirational Districts Program Performance measurement, as a concept, in
most of the developed nations is attached
with budgetary procedures. However, in
both developed and developing economies,
it has been gaining ground in the domain
of public policy. There are three key
reasons why such a measurement has
become essential for comprehensive public
management
13
:
• To efficiently utilise limited
resources,
• To improve the decision-
making process and to
reduce the information
asymmetry across various
levels of administration; and
• To promote accountability
and transparency. METHODOLOGY
13
Delorme, P., & Chatelain, O. (2011). Policy Steering-The Role
and Use of Performance Measurement Indicators. Aid Deliv.
Methods Program. 52
Indian policymaking has also
adopted such performance
measuring procedures to accurately
assess the progress of programmes
while maintaining transparency
across various tiers of stakeholders.
In 2014-15 the Performance
Management Division under the
Cabinet Secretariat issued the
notice to prepare a department-
level Results-Framework Document
(RFD)
14
. This document served two
key purposes. The first purpose was
to shift the focus of all departments
from process-orientation to result-
orientation. Second, to provide an
objective and fair basis to appraise
a department’s overall performance
at the end of the year.
Similar policies were also observed
across other lower-rungs of
policymaking. For instance, a
Citizens’ Report Cards (CRC) was
introduced by many Municipal
Councils and Ward Committees
to measure the satisfaction of
the concerned public group with
the performance of the service
providers
15
. CRC led to an open
discussion on service provision
and the limitations attached to
it. This helped the policymakers
to visualise the objectives and
targets to address such challenges.
It also acted as a good public
accountability mechanism
16
.
IN THIS STUDY, WE
UTILISE THE “DISTANCE
TO FRONTIER” (DTF)
ANALYSIS TO CAPTURE
THE PERFORMANCE OF
DISTRICTS UNDER THE
ASPIRATIONAL DISTRICTS
PROGRAMME.
Given the real-time updated data
available through the Aspirational
Districts dashboard and the targets
set by districts at the beginning
of the programme, Performance
Measurement can shed light on the
progress of the programme.
14
Guidelines for Results-Framework Document (RFD) 2014-2015
15
Nallathiga, R. (2007). Performance Measurement as a Tool for Public Accountability: A Review of
Experiments with the Report Cards in Indian Cities. Indian Journal of Public Administration, 53(1),
1-20.
16
ibid. Aspirational Districts Program The distance implies the current
position of an Aspirational District
vis-à-vis its benchmark or the best
performing district in the respective
State. There are two ways
prescribed under the Champions
of Change Dashboard that
successfully tracks the Distance to
Frontier for Aspirational Districts:
BENCHMARK TARGETS
These targets intend to maximise the growth potential
under each indicator for Aspirational Districts.
Generally, the highest possible target for districts is
100% (i.e. completion of the desired objective under an
indicator).
BEST IN STATE
The dashboard, along with depicting the district level
data, also presents the annual scores for the best
performing district within a particular state for each
indicator. The objective of such scores is to create
competition at the State, District, and even the block
level.
The Distance to Frontier (DTF) is measured at the district level for all the
six sectors of the Aspirational Districts Programme. For district-level
assessment, the average scores are deducted from the Benchmark Targets
assigned for each district.
Distance to Frontier = Benchmark Target – Average Score
id
Where, i represents the indicator and d represents the district.
If the difference is zero, then the districts have achieved their respective
benchmark. In other words, when the difference is zero, it means that the
districts have achieved saturation in that particular indicator/sector with
respect to these pre-determined targets. If the difference is positive, the
districts are lagging in their targets and if the difference is negative, it
implies that districts have overachieved. The Distance to Frontier analysis shows how far are the districts from
their set target. This is illustrated in the figure below for the indicator
percentage of schools with separate toilet for girls. The indicator value
for a district can lie anywhere between 0-100 (since it is in percentage
terms).
0
Current Value
for the district
Target for the
District*
100
70
(Minimum Value
Possible)
Target – Current Value shows the “Distance to Frontier”In this case, 100-70=30. The district is 30 percent away from achieving its target.
PERCENTAGE OF SCHOOLS WITH SEPARATE TOILET FOR GIRLS
54 Distance to Frontier can take three possible values: positive, negative
and zero. The box below represents the meaning of the three values by
using the indicator: Transition rate from upper primary to secondary
TRANSITION RATE FROM UPPER PRIMARY TO SECONDARY
03090100
(Minimum Value Possible)
Value for District X
(Target ValuePossible)
Value for District Z
Value for District Y
Distance to Frontier for District X: 90-30= 60. Implying that it is 60 units away from the target.
Distance to Frontier for District Y: 90-90= 0.
Implying that it has achieved the target.
Distance to Frontier for District Z: 90-100= -10.
Implying that has over achieved the target by 10 units.
Aspirational Districts Program 56
Based on the DTF analysis, districts
are divided into four tiers using
quartiles. This helps in identifying
the leaders and laggards across
various sectors. In this study, state-
level representation in the different
quartiles/tiers is emphasised upon
as this gives a better understanding
of stronger policy convergence and
collaboration in closing the gap with
the benchmark targets.
The DTF analysis provides static
analysis of the districts in terms of
measuring their progress vis-à-vis
the targets. While the results from
the analysis are meaningful for
drawing policy recommendations by
looking at the areas where districts
are lagging, they do not provide any
insights about the improvements
that the districts have made.
Therefore, to understand the
improvements made across all the
sectors in terms of progress, it is
crucial to pick out two comparable
time points. For this study, two
specific points have been taken. The
first-time point is the baseline value
from the year 2018 (presented
under the column “Data As on
31/03/2018” in the Champions of
Change Dashboard). The second
time point comes from the quarterly
average for the calendar year 2019.
The DTF is calculated for these two-
time points and districts are divided
in Tiers for both the periods.
THE RESULTS ARE
PRESENTED IN THE FORM
OF A “MOBILITY MATRIX”.
It goes beyond the DTF analysis by
taking into account the progress of
the districts over time. While DTF is
a static representation of the district
performance, the mobility matrix
represents their dynamic movement. Aspirational Districts Program • The more the districts will be
shifting from lower tiers to
upper tiers between Timepoint
1 (baseline) and Time Point 2
(average for 2019); the better
the improvement that has been
observed in that particular pillar.
• The green portion in the figure
signifies positive movement of
districts from lower to higher
tiers over the tested period of
time.
• The portion in red will show the
number of districts that have
shown regressive movement
with time across tiers.
• The grey cells show a lack of
movement across tiers.
• Each cell will carry the number
of districts.
HOW TO READ THE MOBILITY
MATRIX?
Time Point 2
Time Point 1
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4 58
RESULTS
04
The Health and Nutrition sector
covers indicators related to
maternal care such as provision
of antenatal care, availability
of supplementary nutrition
under the Integrated Child
Development Services (ICDS)
programme etc.; aspects of
childcare such as presence
of Severe Acute Malnutrition
(SAM); availability of healthcare
infrastructure such as First
Referral Units, anganwadis
with buildings, etc. and health
outcomes such as sex ratio. RESULTS
HEALTH AND NUTRITION Aspirational Districts Program RESULTS In the DTF analysis,
Health and
Nutrition have
delivered some
impressive results
as around 10%
of districts have
managed to meet
their respective
benchmark targets.
This sets the right
precedence for the
rest of the districts
as health is one of
the most important
sectors under
the programme
and commands
30% weightage.
Hence closing the
gap with their
benchmark targets
would reflect in the
districts’ enhanced
monthly scores and
rankings. 60
The mean distance between the
frontier targets and the average
achievement of the districts in 2019 is
only 10.23 percentage points across
the sector. This is the lowest average
gap across the sectors between the
targets and the achievements making
Health & Nutrition probably the best
performing sector within the ambit of
the programme.
Districts such as Dahod (Gujarat),
Baramulla (Jammu and Kashmir),
Gadchiroli (Maharashtra), Raichur
(Karnataka), Bijapur (Karnataka),
Bastar (Chhattisgarh), Yadgir
(Karnataka) have been able to
exceed their set targets. Bastar,
Chattisgarh has been offering free
health check-ups, free medicine, and
free nutritious food and counselling
of malnourished children under the
‘Suposhit Bastar Abiyaan’. The first
health and wellness centre was
launched in Bijapur, Chattisgarh,
and was inaugurated by the Prime
Minister. Since then, 15000 health
and wellness centres have been
launched to facilitate comprehensive
healthcare. These initiatives based on
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
How to read the figure?
Figure 4.1:
Distance
to Frontier
Analysis:
Health and
Nutrition
Y.S.R
-5
0
5
10
15
20
25
30
Mohasamund
Visakhapatnam
Average
Achievement of Tragets
Sheikhpura
Firozpur
Jaisalmer
Kandharnal
KaraputMoga
Karauli
Dholpur
West District
Virudhunagar
Ramanathapuram
Chandauli
Bhoopalapalli (Warangal)
Bhadradri-Kothagudern
Asifbad (Adilbad)
Haridwar
Shrawasti
Balrampur
Chamba
Ranchi
Giridih
Gumla
Bokaro
KupwaraDumko
Osmanabad
Godchiroli
Barwani
Ribhoi
Kiphire
Mamit
Wayanad
Nandurbar
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu & Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Vidisha
Guna
Khandwa (East Nimar)
Washim
Damoh
Bastar
Barpeta
Darrang
Jamui
Namsai
Khagaria
Udalguri
Banka
Mewat
Korba
Kotihar
Yadgir
Raichur
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
Tier 1 Tier 2 Tier 3 Tier 4 Aspirational Districts Program Figure 4.2:
Mobility
Matrix for
Health and
Nutrition
data driven policies help in bringing
significant change in the remote
areas.
Andhra Pradesh (3 Aspirational
Districts), Gujarat (2 Aspirational
Districts), Jammu and Kashmir (2
Aspirational Districts), Karnataka
(2 Aspirational Districts) and Sikkim
(1 Aspirational District) have 100%
representation in the first tier implying
that districts have either achieved the
targets or are close to achieving it.
This depicts a holistic improvement in
their health-related statistics.
Kiphire (Nagaland), Ribhoi
(Meghalaya), Mewat (Haryana),
Banka (Bihar), Udalguri (Assam)
are the bottom five districts.
Districts of Bihar and some of the
North-East States mainly form the
bottom tier. States that have 100%
representation in the bottom tier (4th
quartile) include Manipur, Meghalaya,
Mizoram, Nagaland and Arunachal
Pradesh. Therefore, there is a long
way to go for them to meet their
benchmark targets. On the other
hand, Assam has districts in Tier I,
Tier III as well as Tier IV. The bottom
tier districts of Assam as well as
other North-East states can draw
learnings from Hailakandi (the top
tier district in Assam). It has been
innovative in addressing the nutrition
concerns, promoting biodiversity, as
well as securing education through
the awareness campaign. The
practice involves gifting 5 saplings
(coconut, litchi, assam lemon, guava,
amla) to the parents of a new born
girl child. The rationale being that
the fruit from the trees can be used
to feed the child, which would help
in building immunity and warding off
malnutrition. The sale of the produce
could also be invested in educating
the child.
The mobility matrix shows that most
of the districts (71 percent i.e. 20 out
of 28) that were in the first tier during
the baseline have retained their
position while 29 percent of them slid
down to Tier 2. Similarly, 17 out of 28
districts in the bottom tier maintained
their position while 10 of them moved
up one tier.
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
20800
27109
61282
0110 17 Most of the changes have been
observed within the second and
the third tier. Two districts namely,
Adilabad and Darrang moved down
from Tier 2 to Tier 4. Both of them
have moved away from achieving
their targets and thus require
immediate attention. On the other
hand, Kupwara and Sheikhpura
showed remarkable change in their
health scenario and moved two tiers
up.
In a nutshell, the results help us
in identifying the districts that are
close to achieving their targets
and also highlight how the bottom
tier districts can draw learning
from them. These results can
also be utilised by the partners to
identify the districts that require
engagements in the health
domain. The table below shows
the districts requiring interventions
categorisation on the basis of scope
and scale of partners.
These improvements in healthcare
outcomes are crucial as ill-health
harms productivity and adversely
effects human capital. It also
impacts the job prospects of people
and their lifetime earnings. To
understand the repercussions, the
study will analyse the economic
impact arising from the diminishing
rates of Severe Acute Malnutrition
amongst children aged between 6
months and 6 years.
Figure 4.3:
Future
Engagements
in Health and
Nutrition
62
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Kiphire Rajgarh Hazaribagh Chhatarpur
Ribhoi Nandurbar Garhwa Khunti
Mewat Balrampur Latehar Purbi Singhbhum
Banka Begusarai Guna West District
Araria Wayanad Katihar Sheikhpura Aspirational Districts Program SAM is a critical indicator to evaluate
the wellbeing of a child. Improving
maternal health and decreasing child
mortality are heavily linked with the
rates of malnutrition. Malnutrition is
responsible directly or indirectly for
35% of deaths among the children
aged 5 or below
17
.
Therefore, ADP through its strict
monitoring and evaluation nudges
the districts to bring down the rates
of both Severe Acute Malnutrition
(SAM) and Moderate Acute
Malnutrition (MAM). As per the WHO
guidelines, SAM is defined by very
low weight for height (subject to
prescribed median and standard
deviation) of a child below the age of
5 years.
India has shown a high prevalence
of SAM and surprisingly, the
National Family Health Survey-4
reported a higher rate of severe
wasting (7.5%) compared to its
previous iteration (6.4%)
18
. Such
a significant rate of malnutrition
amongst children has prompted a
large number of studies that have
tried to evaluate sample sizes across
the nation. Studies from states such
as Uttar Pradesh
19
and Bihar
20
have
shown significantly higher rates of
severe wasting amongst children.
Thus, the role of ADP becomes
bigger than ever in addressing these
challenges. While malnutrition can
have fatal implications, it also leads
to arrested mental and physical
growth in the long run, which
diminishes the overall productivity
of the concerned person. Given
SAM accounts for malnutrition
amongst children aged between 6
months and 6 years; a quicker and
efficient intervention could easily
help in reducing these rates. WHO
guidelines have also highlighted
that the case-fatality rates for SAM
can be reduced by 55% in hospital
settings and other community
measures such as provisioning of
ready-to-use therapeutic foods
21
can
also bring down these rates.
Indicator: Percentage of Severe
Acute Malnutrition
17
www.who.int/nutrition/topics/malnutrition/en/
18
IIPS, I. (2015). National Family Health Survey (NFHS-4).
19
Singh, K., Badgaiyan, N., Ranjan, A., Dixit, H. O., Kaushik, A., Kushwaha, K. P., & Aguayo, V. M. (2014).
Management of children with severe acute malnutrition: experience of Nutrition Rehabilitation Centers in
Uttar Pradesh, India. Indian pediatrics, 51(1), 21-25.
20
Burza, S., Mahajan, R., Marino, E., Sunyoto, T., Shandilya, C., Tabrez, M., ... & Mishra, K. N. (2015).
Community-based management of severe acute malnutrition in India: new evidence from Bihar. The
American journal of clinical nutrition, 101(4), 847-859.
21
Briend, A., Akomo, P., Bahwere, P., De Pee, S., Dibari, F., Golden, M. H., ... & Ryan, K. (2015). Developing
food supplements for moderately malnourished children: lessons learned from ready-to-use therapeutic
foods. Food and nutrition bulletin, 36(1_suppl1), S53-S58. Although no ‘Benchmark Target’
has been prescribed under the
Champions of Change dashboard, it
is quite clear that the districts would
aim to reduce the malnutrition rates
(both SAM & MAM) down to 0 per
cent.
To accurately assess the performance
of the districts, indicator values for
the year 2019 were compared with
their respective baseline values. In the
last calendar year, i.e. from January
2019 to December 2019, around
58% of the districts have managed to
reduce the SAM rate significantly.
The above graph shows the long and tremendous leap these districts have taken in reducing the SAM rates since their baseline values were recorded.
Impact Measured Across
Aspirational Districts
Improvement in reducing SAM (%) for 2019
Figure 4.4:
Top ten
districts with
the most
improvement
in SAM in
2019
ARARIA, A DISTRICT FROM BIHAR
BEING THE OBVIOUS LEADER IN
REDUCING SAM HAS RECORDED AN
IMPRESSIVE 68% CHANGE WHEN
COMPARED TO ITS CORRESPONDING
BASELINE FIGURE.
64
Chhatarpur
Chandauli
Guna
Rajgarh
Namsai
Pashchimi Singh bhum
Darrang
Sheikhpura
Asifabad (Adilabad)
Araria
0 10 20 30 40 50 60 However, it is a major concern that
states such as Rajasthan, Punjab
& Uttarakhand have zero districts
that have shown any positive
change. Since their baseline values
were recorded, all the districts
in these states have regressed
during the concerned period. Thus,
a holistic approach is required in
such a case, where the Anganwadi
Centres (responsible for recoding
the information and supplying
the appropriate nutrients),
district government and the state
government need to focus on
successful policy convergence and
collaboration.
The subnational-level analysis shows that many states with two or more
Aspirational Districts have recorded significant positive changes since their
baseline position.
have a healthy representation for Aspirational Districts with this positive
change.
8070
6366.67
Chhattisgarh
Andhra Pradesh
Odisha
Jharkhand
Aspirational Districts Program 66
To measure the economic impact,
it was crucial to consider the long-
term implications of SAM on children.
As mentioned above, malnutrition of
any form has long-lasting effects on
mental and physical well-being that
ultimately reduces the productivity
levels of an individual. The objective
of this impact evaluation is to
measure the lifetime economic gains
that can be made by averting any
kind of disability or death pertaining
to malnutrition.
While it is difficult to assign any
particular value for gain in lifetime
economic gains owing to lower
malnutrition, policymakers across
the world go for the “rule of thumb”.
This rule is based on valuations of
health investment made by nations
under specific income categories
22,23
.
Therefore, for lower-income nations
generally, value is quoted to be
$1000/Death-Adjusted Life Year
(DALY) and for middle to higher-
income nations it close to $5000/
DALY
24
. Therefore, the potential
economic gains that can be made
by reducing the rates of SAM are
always going to be massive which
incorporates its long-term benefits.
Another crucial factor that has been
taken into account is for the loss of
productivity. According to a Lancet
study from India, malnutrition has
a strong influence in reducing the
productivity of an individual. The
study suggested that a person could
lose approximately 17.3 years of
his healthy life due to long-term
implications of malnutrition
25
. Hence,
the economic impact that has
been computed also measures the
prevented loss in the healthy life of
an individual.
The overall economic impact for
all the states comes out to be a
mammoth 1.43 Lakh crores. This
is the impact that ensures that not
only there is a significant fall in the
SAM rates but it also leads towards
healthy and productive lifetime
earnings. The possible number of
beneficiaries for such an impact was
1.2 crore children enrolled in the
Anganwadi Centres across the 112
districts.
Illustrative Economic Impact
through Health and Nutrition
22
Mill, A. and S. Shillcut, 2004. Communicable Disease. In B. Lomborg (ed.) Global
crises, global solutions. Cambridge University Press, Cambridge.
23
Stokley, N., 2004. Expert Comments. In Bjorn Lomborg (ed.) Global crises, global
solutions. Cambridge University Press, Cambridge.
24
Horton, S., Alderman, H., & Rivera, J. A. (2008). The challenge of hunger and malnutrition. Copenhagen
Consensus, 3-4.
25
Swaminathan, S., Hemalatha, R., Pandey, A., Kassebaum, N. J., Laxmaiah, A., Longvah, T., ... & Gupta, S.
S. (2019). The burden of child and maternal malnutrition and trends in its indicators in the states of India:
the Global Burden of Disease Study 1990–2017. The Lancet Child & Adolescent Health, 3(12), 855-870. Aspirational Districts Program Apart from the obvious reason
of percentage of prevailing SAM,
other factors could influence the
overall impact values for the States/
Districts:
• Number of Aspirational Districts:
As seen above, those states
that have more Aspirational
Districts would tend to enjoy
more cumulated economic gains.
Thus, states such as Bihar (13
districts), Madhya Pradesh (8),
UP (8) have such high numbers.
Yet, there are states such as
Haryana, Manipur, Tripura and
Arunachal Pradesh that have
one Aspirational District each but
also have managed to oversee
a sizable reduction in SAM rates
along with strong potential
economic gains.
• However, it was observed that
Rajasthan is an exception. The
state has 5 districts yet all of
them regressed in terms of the
prevalence of SAM since its
baseline values were recorded.
This means that even if the state
has more districts, its cumulative
impact will be lower than those
with fewer districts and those
with lower prevailing SAM rates.
• Number of Children enrolled
in an Anganwadi Centre: This
indicator targets children aged
between 6 months and 6 years,
which is a big pool of possible
beneficiaries. As a result, the
base for computing economic
impact favours those states that
have more children enrolled in
Anganwadi Centres. However,
one interesting case can be
observed in Maharashtra,
where it has the fourth-highest
average number of children
enrolled under the Anganwadi
centres. Yet, due to its regressing
SAM rates since the baseline
period, the state has witnessed
a potential economic loss.
Thus, this factor only positively
influences those cases where
SAM cases have been low.
Figure 4.5:
State Wise
Impact
Total Potential
Savings..
-7,756 65,669 68
The overall economic gain arising
from lowering the SAM rates is
so high that it should be a signal
for all the stakeholders. Better
coordination between Anganwadi,
district and state-level stakeholders
could not only prevent fatality
amongst children but could
potentially pave the way for them to
lead a healthy and productive life.
As far as lifetime earnings are
concerned, the above figure is
only computed for the progress
made by the districts in the year
2019 and how it compares with
their baseline values. However,
for better and even more accurate
valuation, longitudinal studies are
required which could further shed
light on the nature of education
received, training acquired, and
the professional route taken by the
beneficiaries. This could reform
the way stakeholders can plan the
social development of an individual
by positively influencing their
lifetime earnings. Aspirational Districts Program The education sector focuses on
learning outcomes (transition rate
from primary to upper primary,
and subsequently to secondary
schooling, average scores in
mathematics and languages and
so on) as well as infrastructural
(toilet access for girls, electricity
supply, drinking water, etc.) and
institutional indicators (pupil-
teacher ratio, timely delivery of
textbooks, etc.). Considering the
importance of education in enabling
development, it commands a
weightage of 30 percent – similar to
that of health.
Unlike health, none of the districts
have managed to achieve their
set targets on an average in the
education sector. All of the Tier
1 districts, however, were merely
5 to 10 percent away from their
respective targets over the last
year. The States of Andhra Pradesh,
Himachal Pradesh, Punjab, Sikkim,
and Tamil Nadu have all of their
districts in the top tier.
EDUCATION
How to read the figure?
Figure 4.6:
Distance
to Frontier
Analysis:
Education
0
5
10
15
20
25
35
30
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu & Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Y.S.R
Rajnandgaon
ViziangaranBegusarai
Uttar Bastar Kanker
Dahod
Jaisalmer
Rayagada
Kalahandi
Malakangiri
Moga
Dahal
West District
Ramanathapuram
Virudhunagar
Udham Singh Nagar
Chitrakoot
Bhadradri-Kothagudern
Asifbad (Adilbad)
Haridwar
Shrawasti
Bahraich
Latehar Chandel
Pakur
Yadgir
Baramula
Singrauli
Chhatarpur
Dhenkanal
Barwani
Ribhoi
Kiphire
Mamit
Wayanad
Nandurbar
Vidisha
Guna
Balangir
Washim
Damoh
Bastar
Namsal
Katihar
Sukma
Banka
Sitamarhi
Sahibganj
Lohardaga
Mewat
Goalpara
Darrang
Muzaffarpur
Average
Achievement of Tragets
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 70
The districts in this tier have
been undertaking some unique
interventions to improve education
among the children. Rajnandgaon
in Chattisgarh has ensured access
to sanitation facilities for every
girl child, for which toilets were
installed in schools. This helped
in reducing the drop-out rate
of girls enrolled in government
schools. Similarly, in Dantewada,
Chattisgarh, the government
schools adopted ICT models to
boost the quality of education.
Meanwhile, in Baran, Rajasthan,
volunteer generation campaign was
organised to strengthen student-
learning outcomes in schools, and a
capacity building workshop for 617
volunteers was conducted.
Banka in Bihar has launched a
programme, ‘Unnayan Banka
– Reinventing Education using
Technology’, which is an effort to
leverage technology to improve the
learning environment. The Prime
Minister has even presented an
award to the district administration
for the initiative. In another instance
in Sharavasti, Uttar Pradesh,
School Management Committees
were formed in 1289 schools
for a tenure of 2 years. These
SMCs with collaboration from
Education Department make school
development plans and look after
building capacity.
One of the striking features of this
sector is the intra-state outliers
that emerge across some of the
states. For instance, Sahibganj
district in Jharkhand appears to be
significantly lagging as compared to
the rest of the districts in the State
when it comes to performance in
the domain of education. Similarly,
Sukma districts in Chhattisgarh is
the only district in the state that
appears to be in the bottom tier
while all the other districts are in
the top 3 tiers of the sector. Ribhoi
in Meghalaya appears to lag behind
even when compared to other
districts in the North East and
may need critical partner support
moving forward.
On average, across all aspirational districts, the DTF on education remains
at 15 percent. Evidently, the distribution of districts in the bottom tier is
more spread out when compared to the top three tiers.
But it must be noted that some of the districts that lie in this tier and
are, thus, farthest from achieving their targets have been putting in
considerable efforts to climb up the ladder.
STATES LIKE BIHAR, ODISHA, TELANGANA, MANIPUR,
MEGHALAYA, AND NAGALAND HAVE SUBSTANTIAL
VISIBILITY IN THE BOTTOM TIER. Aspirational Districts Program However, five districts – Garhwa
(Jharkhand), Hailakandi (Assam),
Kupwara (Jammu & Kashmir),
Rajgarh (Madhya Pradesh), and
Singrauli (Madhya Pradesh) – have
moved from the bottom-most tier
in the baseline year to Tier-2 over
the last year. A unique initiative
undertaken by Singrauli to bring
about such progress over this time
was a four week-long attendance
campaign, which resulted in a 10%
increase in student attendance
across three clusters.
The analysis presented here shows
how the aspirational districts have
performed with respect to education
and the outcome seems mixed. It
shows that there remains immense
scope for further intervention on
this front. None of the districts
have been able to achieve their
targets but appear to be on course
to achieve/ mostly achieve them by
2022. Partner interventions in this
sector can again be guided by the
logic of converging scale and scope
of the partner engagements and the
needs of the district as highlighted
in the DTF analysis. Their preferred
engagements depending on the
scope, scale, and the agenda of the
respective partner organisation can
be chosen from Table X, which is
mapped to the bottom five districts
from each Tier.
While the DTF analysis delineates
the static position of the districts
based on their averages across
the last year, the mobility matrix
highlights the movement of districts
across tiers over time. Surprisingly,
more districts (32 over 26)
have slipped to lower tiers
with time on the education
parameter than have
improved during the same
period.
Figure 4.7:
Mobility
Matrix:
Education
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
20710
36811
510 121
05716 72
Figure 4.8:
Future
Engagements
in Education
FOCUSED INTERVENTIONS WITH HIGHER DEGREES OF
INTENSITY ARE REQUIRED IN THE NORTH EASTERN
PART OF THE COUNTRY OWING TO ITS SPECIFIC
NICHE CHALLENGES. EVEN WITHIN STATES THAT ARE
PERFORMING RELATIVELY WELL, DISTRICTS THAT
ARE LAGGING BEHIND BY SOME DISTANCE SHOULD
BE GIVEN EXTRA ATTENTION TO ENSURE THAT NO
DICHOTOMIES EMERGE IN THE OVERALL PERFORMANCE
OF THE STATE UNDER THE PROGRAMME.
Some of these districts, as seen
in the case of Health & Nutrition,
do face niche challenges ranging
from a lack of school infrastructure
to extremist violence, which
may impede the functioning of
educational institutions in these
regions reflecting the relatively
poorer performance compared to
other districts in the same state.
Digital tools, especially mobile-
based solutions, could emerge as
possible measures of bridging the
gap between isolated districts and
the rest of the state.
Therefore, education remains a
sector that can be a focal point
of higher engagement by all
stakeholders in the programme
given its scope for improvement and
its vitality for development.
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Ribhoi MewatBastar Vizianagaram
Asifabad
(Adilabad)
Namsai Bijapur Ramgarh
Sahibganj Pakur Nandurbar Sirohi
Bhadradri-
Kothagudem
WayanadGiridih Washim
Sitamarhi Dumka NuapadaBaran Aspirational Districts Program The Financial Inclusion domain covers
the availability of bank accounts
through government schemes such
as Pradhan Mantri Jan Dhan Yojana
(PMJDY); pension beneficiaries through
Atal Pension Yojana; and affordable
and easy access to financial loans
disbursements through Mudra. It is an
important area of this programme as
indicators under this sector ensure the
self-dependence of the beneficiaries.
Having a bank account and enjoying
social safety nets such as insurance
and pension are crucial factors for
the subsistence of normal life and
thus protects the beneficiaries from
potential risks.
In the DTF analysis, it is evident that
the potential for improvement remains
high despite the best efforts of the
government over the last few years.
The district closest to the target i.e.
Mahasamund from Chhattisgarh is 42
percent away from achieving the goals
set for the financial inclusion sector
while the farthest away is Ribhoi from
Meghalaya that is 87 percent away.
This range (42-87 percent) within
which all the districts fall reflects India
still has to put in a lot of effort to climb
the financial inclusion ladder.
FINANCIAL INCLUSION
How to read the figure?
Figure 4.9:
Distance
to Frontier
Analysis:
Financial
Inclusion
Rajnandgaon
Narayanpur
Viziangaran
Dahod
JaisalmerMalakangiri
Naupada
Moga
West District
Udham Singh Nagar
Siddharthanagar
Haridwar
Bahraich
Dahal
Chandel
Yadgir
Singrauli
Chhatarpur
Sitamarhi
Dhenkanal
RibhoiKiphire
Mamit
Namsal
Sukma
Baksa
Mewat
Dhubri
Simdega
Visakhapatnam
Kupwara
Baramula
NarmadaChamba
Wayanad
0
40
30
20
10
50
60
70
90
80
Andhra
Pradesh
Arunachal
Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya
Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal
Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu &
Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Average
Achievement of Tragets
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 74
The two states that have shown
encouraging performance relative to
other regions are Andhra Pradesh
and Chhattisgarh. In Andhra
Pradesh, two out of three districts
are in the top tier while the third one
is in Tier II. In Chhattisgarh, nine out
of ten are in the first tier.
The results also clearly depict
disparities within states. States
such as Odisha, Rajasthan,
Chhattisgarh, Madhya Pradesh
have representation in almost
all tiers. For instance, Dhenkanal
(Odisha) is in Tier I with 50 percent
distance from the target while in
Malkangiri (Odisha) the distance
between the target and the current
value is 74 percent. Moreover, there
are no states in this sector that
have achieved 100% representation
in the top tier.
The trend is similar to the Health
and Education sectors where one
can see the North Eastern states
lag in comparison to the rest of the
country. Topographic challenges
and lack of quality internet
connectivity have emerged as two
main constraints in driving financial
inclusion in the North East. Tripura
has emerged as the only state in the
North East to have its district in the
top 2 tiers of the cohort.
The Mobility Matrix shows the
majority of the districts in the first
tier have remained in the same tier
for 2019 as well. In the second tier,
Yadgir (Karnataka) has worsened
its performance and moved to Tier
IV in 2019. During the baseline data
collection, it was 58 percent away
from achieving its target while in
2019 it is 71 percent away. While
21 out of 28 districts retain their
position in the bottom tier, two
districts, namely Nuapada (Odisha)
and Bhadradri-Kothagudem
(Telangana) have made a major
improvement to jump to the top tier
for the year 2019.
Figure 4.10:
Mobility
Matrix:
Financial
Inclusion
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
20810
06166
61471
25521 Aspirational Districts Program However, there are a lot of steps being
taken by the districts currently that
can help them in providing access
to financial services to their citizens.
Sonbhadra in Uttar Pradesh organised
Financial Literacy camps which
resulted in 650 enrolments for PMJDY
and other Social Security Schemes
such as PMSBY, PMJJBY and APY from
46 villages in the district. Another
step comes from Gajapati, Odisha.
The district is tribal-dominated and
was devastated by the cyclone Titli
in October 2018. What started as
challenges in transferring direct
benefits to beneficiaries in remote
places due to lack of bank branches,
laid the foundation for opening mini
banks under Odisha Livelihood
Mission. To facilitate this, an MoU was
signed with the State Bank of India
and Utkal Grameen Bank. The banks
opened mini banks in panchayats
that did not have banking facilities.
These mini banks also functioned
as common service centres. Quick
enough, 15 banks started functioning
in the district, and bank accounts of
27,463 SHG members were opened,
while 23000 were linked with Adhere.
However, the results show that
these steps are not enough, and the
government will have put in a lot of
other steps for enhancing the financial
services in these regions.
The fact that there is only one partner
– Microsave – that is currently working
in the domain of Financial Inclusion,
shows there is immense potential for
partners to engage with the districts
in this particular sector. Before the
engagement of the development
partner Microsave India, the district
administration had no nodal officer
in the domain of financial inclusion.
This often meant that the district
administration was heavily dependent
on external banking and micro-
finance institutions to drive financial
inclusion and access to the credit in
the districts. Under the framework of
ADP, Microsave India along with NITI
Aayog has been able to place District
Financial Inclusion Coordinators (DFIC)
at the designated districts driving the
agenda of financial inclusion from
within the district administration.
Figure 4.11:
Future
Engagements
in Financial
Inclusion
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Ribhoi Baramula Aurangabad Khunti
Kiphire
Gajapati Sirohi Pakur
Baksa Dhaulpur Jamui Sahibganj
Dhubri Kandhamal Rayagada Wayanad
Chandel Osmanabad Purbi Singhbhum Nuapada It was crucial to incorporate data
points assessing the state of
agriculture and water resources
because the sector forms a critical
aspect of development, especially
among the aspirational districts.
It has a weightage of 20 percent
and focuses on output (yield, price
realisation, etc.), inputs (soil health
cards, quality seed distribution,
etc.), and institutional support (crop
insurance, animal vaccination,
electronic markets, etc.).
Agriculture is a sector where the
districts are the farthest away from
the set targets so much so that it is
difficult to draw a clear distinction
between leaders and laggards. This
is also driven by the fact that the
elements of its indicators have a
longer time frame for improvement.
The results show that there is
immense scope for improvement as
the average distance from frontier
is 80 percent. The potential gains
from interventions in this sector are
exceedingly high.
AGRICULTURE AND WATER RESOURCES
How to read the figure?
Figure 4.12:
Distance
to Frontier
Analysis:
Agriculture
and Water
Resources
76
Aurangabad
Y.S.R
Muzaffarpur
Viziangaran
Fatehpur
Yadgir
Kiphire
Dhaulpur
Osmanabad
Gadchiroli
Sheikhpura
Sahibganj
Ribhoi
Mamit
Dhalal
Namsai
Bokaro
Gaya
Mewat
Washim
Barwani
Visakhapatnam
Kupwara
Baramula
Narmada
Chamba
Wayanad
Average
Dhenkanal
Kalahandi
Balangir
Gajapati
Bhoopapalapalli(Warangal)
Ramanathapuram
Asifabad (Adilabad)
Bhadradri-Kothagudem
Dakshin Bastar Dantewada
Haridwar
Baran
0
40
30
20
10
50
60
70
90
80
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu & Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Achievement of Tragets
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 Unlike most sectors, the tier-1
districts in agriculture are the most
spread out as seen in Figure 4.12.
Andhra Pradesh and Kerala are
the only states that have all of
their aspirational districts in the
top-most tier. On the other hand,
Punjab and Himachal Pradesh are
states that have all of their districts
in the lowest tier. However,
considering the distance of all
districts from the frontier, there is
immense scope for improvement
across all tiers.
Kupwara in Jammu and Kashmir, which is one of the districts
in the top tier introduced high density farming to improve
agricultural productivity and make optimum utilisation of
resources. The traditional seedling-based orchards were
converted into high density orchards. This gave the producers
success in cultivation of crops such as apples and walnuts and
increased the harvest by up to three times. Such efforts by
districts can substantially improve the state of agriculture and
water resources across aspirational districts.
Aspirational Districts Program 78
Another notable story comes from
the district Virudhunagar, Tamil
Nadu. The farmers in Virudhunagar
have adopted cost-effective water
harvesting techniques such as
micro irrigation, drip irrigation,
water trenches, and reservoirs,
thereby overcoming water
deficiency. This was in response
to the Prime Minister’s call of ‘Per
Drop More Crop’. Innovation has
brought to the district concepts like
‘Apni Mandi’ where the farmers
come and sell their produce directly
to the consumers. The farmers
have also embraced processing of
harvest such as drying agricultural
produce using solar energy, and
poly-house cultivation. These have
enabled the farmers to have a
stable income.
Meanwhile, the mobility matrix
of the sector shows that there
has been considerable movement
across tiers over time. In fact,
among all sectors, the agriculture
and water resources sector has
recorded the most changes in the
position of the districts across tiers.
Figure 4.13 shows
42 DISTRICTS THAT
HAVE SEEN AN UPWARD
MOVEMENT AND HAVE
BEEN ABLE TO GET
CLOSER TO THEIR
TARGETS AT A FASTER
RATE THAN THEIR PEERS.
On the other hand, 40 districts
have either moved further away
from their targets than they
were during the baseline period
(2018) or have recorded smaller
improvements compared to other
Aspirational Districts.
Figure 4.13:
Mobility
Matrix:
Agriculture
and Water
Resources
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
8686
51166
7777
8479 Aspirational Districts Program Bihar and Assam have used
targeted measures for the
conservation of environment.
Goalpara, Assam has taken an
exemplary step by using green
technologies for construction of
all-weather roads. And in Bihar
the ‘green army’ of school students
were encouraged to judiciously use
water resources.
In conclusion, it can be said that
there remains immense scope for
improvement on this front. The
partners can choose to intervene
to improve the state of agriculture
and water resources in aspirational
districts to reap the maximum
developmental gains. Based on
their level of engagements and
choice of region, the possible
locations for investment are
depicted in Figure 4.14.
THE 8 DISTRICTS THAT MOVED FROM
TIER IV TO TIER I BELONG TO BIHAR,
ASSAM AND CHHATTISGARH.
Figure 4.14:
Future
Engagements
in Agriculture
and Water
Resources
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Kiphire Balrampur Kondagaon Rajnandgaon
Barpeta Malkangiri Karauli Bijapur
Dakshin Bastar
Dantewada
Sirohi Dhubri Giridih
Firozpur Koraput West District Mahasamund
Purnia Ramgarh
Khandwa (East
Nimar)
Kalahandi 80
Approximately 70 million additional
individuals of working age (15-59
years) are expected to enter the
country’s labour force by 2023 and
by the same estimation model, it is
also predicted that the total workforce
will include approximately 404.15
million people
26
. The rising workforce
in India and the low employability of
the current population
27
requires the
country to focus on improving the skill
set of its population. The government
has launched a lot of programmes in
this domain such as Pradhan Mantri
Kaushal Vikas Yojana (PMKVY) that
aim to not only provide relevant skills to
the workforce but also help them with
employment opportunities.
A note of caution needs to be added for
the data related to skill development.
The programme only captures skill
formation but does not effectively
track employment or improvement in
earnings. This can be improved within
the programme moving forward.
The DTF analysis results shows that
skill development is a unique sector as
it has clear leaders at both district and
state-levels. However, it is difficult to
pick laggards as the average scores
in the third and fourth quartile have
limited divergence.
SKILL DEVELOPMENT
Figure 4.15:
Distance
to Frontier
(DTF): Skill
Development
How to read the figure?
26
The 3
challenges to skill
development in
India and how to
tackle them, WEF
(2019)
27
India Skills
Report, CII (2019)
Average
0
40
30
20
10
50
60
70
90
80
Andhra
Pradesh
Arunachal
Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya
Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal
Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu &
Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Achievement of Tragets
Khagarta
Y.S.R
Darrang
Virudhunagar
Chitrakoot
Yadgir
Raichur
Kiphire
Dhaulpur
Osmanabad
Malkangiri
Mahasamund
Hazaribagh
Garhwa
Ribhoi
Mamit
Sirohi
Namsai
Bokaro
Latehar
Godda
Begusarai
Mewat
Singrauli
Baran
Visakhapatnam
Kupwara
Udaiguri
Purnia
NawadaBaksa
Baramula
Narmada
Banka
Sitamarhi
Chamba
Dahod
Wayanad
Dhenkanal
Kalahandi
Kandhamal
Nandurbar
Chhatarpur
Gadchiroli
Ramgarh
Bhoopapalapalli(Warangal)
Bhadradri-Kothagudem
Sukma
Nabarangapur
Asifabad (Adilabad)
Haridwar
Distance to Frontier: How far are you from your target?0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 Aspirational Districts Program Karnataka and Sikkim are the
best performing states with 100%
representation in the 1st quartile.
While Bihar, Jharkhand, Madhya
Pradesh, Tamil Nadu and Odisha are
the states in which the performance
of some districts is commendable.
Giridh and Ramgarh, two districts
from Jharkhand have even achieved
saturation in this sector with an
impressive average score.
The bottom quartile is mainly formed
by some districts of Chhattisgarh
– Sukma, Bijapur, Bastar, Korba,
Kondagoan; two districts from
Bihar – Sitamarhi and Banka; two
districts from Jharkhand- Gumla and
Garwa; all the Aspirational districts
from Arunachal Pradesh, Jammu
and Kashmir, Manipur, Meghalaya,
Mizoram, Gujarat and Nagaland.
It is observed from the Mobility
Matrix that similar to Agriculture
and Natural Resource sector, Skill
Development has also witnessed
drastic changes in the position
of districts within the two time
periods. 50 districts have seen an
upward movement and have been
able to get closer to their targets
at a faster rate than their peers.
One of the districts – Gajapati that
moved from Tier IV to Tier II had
started enrolment of people for skill
development under Deen Dayal
Upadhyaya Grameen Kaushalya
Yojana (DDU-GKY) after the Titli
cyclone hit the district. As a result
of the efforts, 11,600 candidates
were mobilised, and over 450 were
trained in different crafts. Some of
the candidates have got placements,
which reflect the effectiveness of the
initiative.
On the other hand, 45 districts have
either moved further away from
Figure 4.16:
Mobility
Matrix: Skill
Development
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
410 122
76510
9838
82108 their targets than they were during
the baseline period (2018) or have
recorded smaller improvements
compared to other Aspirational
Districts.
In terms of partner engagement,
even though the programme
encourages skilling of Persons with
Disabilities (PWDs), there are no
partners currently engaged in this
domain. The district administration
could take steps to reach out to
partners to bridge critical gaps in
skilling PWDs. It would enhance
and support the districts to not
only achieve the targets stipulated
under the programme but also allow
districts to positively impact the
socio-economic welfare of PWDs
in some of the most challenging
geographies of the country.
82 In skill development programmes it
is not only important to look at the
skills imparted by the government
under these programmes but is
also critical to study whether these
skills have enabled people to obtain
new jobs and how these new job
opportunities have impacted their
income. In this study we analyse
the indicator “Number of certified
youth employed/ number of youths
trained under short-term and long-
term training”. This is arguably
the most important indicator as it
evaluates the final performance of
the training programmes. The higher
the possibility of employability of the
candidates, the better the training
programmes are.
The competitive labour and job
markets have made it even more
difficult for individuals to find
their preferred option of jobs/
career options. As a result, skill
development becomes a viable
option that could help in addressing
these problems.
India has been riddled by the
problem of “Skill and Job Mismatch”.
This means that India faces a dual
challenge where:
• The workers suffer from skill-
deficit, which leaves them
unemployed.
• The workers might be over-
skilled and with limited suitable
jobs available
Figure 4.17:
Future
Engagements
in Skill
Development
Illustrative Economic Impact
through Skill Development
Indicator: “Number of certified youth employed/ number of
youths trained under short-term and long-term training”
Aspirational Districts Program
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Kiphire Dhubri Vidisha West District
NarmadaPakurGunaKatihar
Sukma Purbi Singhbhum Nawada Muzaffarpur
Baramula
Bhadradri-Ko-
thagudem
Jamui Raichur
GumlaBarpeta MogaSirohi 84
In such a case, those who are over-
skilled reach for those jobs, which
need lower levels of education or skill.
This leads to overcrowding for the
already limited number of jobs and
further reduces the chances for those
workers who are untrained/unskilled.
Skill development, thus, can address
at least half of the abovementioned
challenges.
ADP has compiled a comprehensive
list of indicators that could monitor
the progress made by the districts
to train the workers. By monitoring
the rate of skilled candidates, each
district can produce a pool of workers
that will be prepared for future-
oriented jobs.
Recent efforts by the Government
have ensured that a wide variety of
training programmes are available
that would help in skilling the young
members of the workforce. Especially,
Pradhan Mantri Kaushal Vikas Yojana
(PMKVY) has been a major guiding
force in creating an emerging batch of
the workforce that would be prepared
for the challenges that the labour
market could throw in the future.
There are definite economic
benefits attached to the skilling of
the workforce. It has been noted
that employment post-training
programmes often lead to a significant
jump in the wage and hence, positions
the beneficiaries in an advantageous
situation in the labour market. This
has been backed by a recent World
Bank Study, which shows that
the acquisition of new skills could
potentially boost income by 21 per
cent and training programmes can
spur the employment rate for women
more than men
28
.
For impact evaluation, the increase
in income will be computed for three
months of employment, going by the
assumption that the candidates will
be employed for a minimum of 66
working days
29
. For monthly income,
we refer to the most updated monthly
per capita income for India in Rupees
30
.
Impact Measured Across
the Aspirational Districts
Assumptions and
Methodology
28
economictimes.indiatimes.com/news/economy/policy/skill-development-programmes-can-boost-
income-by-21-but-not-all-of-them-beneficial-world-bank/articleshow/48106307.cms?from=mdr
29
One working month= 22 working days
30
www.business-standard.com/article/economy-policy/india-s-per-capita-income-rises-6-8-to-rs-11-
254-a-month-in-fy20-120010701269_1.html Aspirational Districts Program The results of the analysis show
a positive result. Ten districts
covering around 45,000 candidates
have already managed to achieve
saturation, thus showing the rapid
pace that progress could be made for
this indicator.
The above graph represents the
potential economic gains made by
seven out of the aforementioned
ten districts (data for those districts
with 1000+ candidates). Successful
implementation of relevant central
skill development schemes has
ensured that candidates in these
districts will not only be employed
but will also find themselves in an
advantageous position as compared
to other workers who might be either
unskilled or semi-skilled.
At the other end, there could be
two major reasons, as to why
districts are not able to maximise
the economic gains arising from skill
development. First, districts have
been unable to make any progress
under this indicator during 2019. This
is evident from Namsai’s (Arunachal
Pradesh) and Kiphire’s (Nagaland)
performance, as both have achieved
0 as their annual average. The
second reason could be attributed
to the fact that there are not many
candidates that either avail or have
been enrolled under specific skill
development schemes. This is notable
for two districts Sheikhpura (Bihar)
and Malkangiri (Odisha). Both these
districts have achieved 100 per cent
success under the given indicator;
however, both also have less than
100 candidates available to train. As
a result, while the implementation
has been strong in this case, due to
the beneficiary base being small, the
overall economic gains also fall short.
Analysis
Figure 4.18: Potential Economic Gains due to Skill Development in INR Crores Aurangabad
Virudhunagar
Bokaro
Jamui
Muzzaffarpur
Hardwar
Darrang
0 2 4 6 8 10 12 86
Skill development is an interesting
sector under the ADP. It is probably
one of the few components that
not only can monitor an individual’s
skills, but can also trace the trends
that exist in the present-day labour
and job markets. More priority
could be given to those training
programmes that command a
higher share of labour demand
and similarly, help in revising those
programmes that are on their way to
redundancy.
This study is a basic economic
impact for trained candidates in
the Aspirational Districts. While
some common factors have been
incorporated to simplify the analysis;
there is a massive scope to study the
longitudinal impacts arising from this
sector. Subject to data availability,
the analysis can be broken down
into specific schemes, which will lay
out district-level trends. Furthermore,
the progress of the previous
batch of candidates can help in
tracing back the success of the
programmes at the disaggregated
level, which would better prepare
the stakeholders in formulating the
training course for future batches.
Looking
Forward Aspirational Districts Program Since basic infrastructure is the
minimum necessary condition
that needs to be satisfied to
enable development, it was crucial
to incorporate indicators that
provide a sense of infrastructural
conditions. These include availability
of individual household latrines,
drinking water, electricity, and
road connectivity. The districts
are also tracked for the number of
Gram Panchayats connected to
the internet, and panchayats with
Common Service Centres.
Apart from health and nutrition,
basic infrastructure is the only
sector where there are multiple
cases of saturation and with the
average scores skewing towards the
benchmark point.
BASIC INFRASTRUCTURE
THE STATES OF GUJARAT AND KERALA EMERGE AS THE
TOP-PERFORMING STATES WITH A 100% REPRESENTATION
IN THE TOP TIER. THEY ARE CLOSELY FOLLOWED BY
MADHYA PRADESH (5 OUT OF 8).
CURRENTLY, 6 DISTRICTS
HAVE MET OR EXCEEDED
THEIR PROGRAMME
TARGETS AS OF 2019.
KHANDWA (MADHYA
PRADESH) HAS
EMERGED AS THE BEST
PERFORMER AND BIJAPUR,
CHHATTISGARH IS
FARTHEST FROM ACHIEVING
ITS PROGRAMME TARGETS. 88
It is encouraging to see the first
quartile formed by a mix of states,
geographically and economically,
representing that districts in most of
the states have made considerable
improvements. In fact, on the whole
the districts are 20 percent away
from their targets on an average.
Meanwhile, Telangana and the North
East states (except Assam) have full
representation in Tier 4, the bottom
tier. The aspirational districts in
these states need focused attention
under basic infrastructure.
Figure 4.19:
Distance
to Frontier:
Basic
Infrastructure
How to read the figure?
One reason for districts exceeding, achieving, or nearly achieving
their targets in the Basic Infrastructure sector stems from the fact
that some of the indicators – such as Individual Household Latrines
(IHHL) and household electrification – were driven by mission mode
schemes such as Swachcha Bharat and SAUBHAGYA.
0
40
30
20
10
50
60
70
-10
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu & Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Achievement of Tragets
Hailakandi
Begusarai
Kondagaon
Rajnandgaon
Darrang
Virudhunagar
Yadgir
Kiphire
Sirohi
Osmanabad
Chhatarpur
Simdega
Chandel
Ribhoi
MamitNamsai
Washim
Bastar
Mewat
Singrauli
Nandurbar
Vidisha
Barwani
Visakhapatnam
VizianagaramKupwara
Ramgarh
Khunti
Raichur
Wayanad
Katihar
Dhubri
Araria
Banka
Barpeta
Bijapur
Chamba
Baramula
Palamu
Sonbhadra
Chandauli
Dhalal
Kalahandi
Firozpur
Gadchiroli
Khandwa (East Nimar)
Sheikhpura
Uttar Bastar Kanker
Ramanathapuram
Udham Singh Nagar
Bhadradri-Kothagudem
Nabarangapur
Asifabad (Adilabad)
Haridwar
Average
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 Aspirational Districts Program Among the districts in the top tier,
in Kupwara, Jammu and Kashmir,
a network of 176 water-harvesting
tanks was strengthened. It has
yielded double benefit, as it also
aided in enhancing farmers income
through water conservation.
In Dahod districts of Gujarat,
a hundred households across
five villages benefitted from the
installation of solar powered
community tube wells. The initiative
was led by the Collector, Dahod,
and helped in facilitating the
availability of water at low cost for
drinking as well as for irrigational
purposes.
Since districts in a lot of states
have achieved saturation in this
sector, the Mobility Matrix shows
considerable shift in the position of
districts within tiers as expected. It
can be seen in Figure 4.20 that two
districts have fallen from the first
tier in the baseline to the bottom tier
in the latest year. These are Chatra
in Jharkhand and Khagaria in Bihar.
On the other hand, four districts
from two states have climbed from
the bottom tier in the baseline to
Tier 2 in the latest year. These
include Baksa (Assam), Dhubri
(Assam), Giridih (Jharkhand), and
Latehar (Jharkhand).
The dominant presence of partners
in basic infrastructure is in the
domain of potable drinking water
with Piramal Water, being the
partner engaged in supporting the
initiative. Sanitation has emerged
as another area of engagement by
partners across geographies.
This therefore leaves immense
scope for other partners to
engage in this domain to support
different kinds of infrastructure
requirements – such as internet
connectivity for rural panchayats
– which form an essential part of
this sector.
Figure 4.20:
Mobility
Matrix: Basic
Infrastructure
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
14842
4410 10
101251
04915 90
Figure 4.21:
Future
Engagements
in Basic
Infrastructure
Even though the partners are
actively engaged across the
aspirational districts in this sector,
Figure 4.21 shows the areas where
further interventions can be made
based on specific requirements.
To measure socioeconomic impact,
two indicators namely in-house toilet
construction and delivery of potable
water have been selected. The
objective here is to assess the role
of water-availability and sanitation
in improving the overall health of
the beneficiaries. Previous studies
have shown that sanitation and
water are two of the key non-health
factors that have a strong influence
in determining the healthy lifestyle
of an individual
31
. Inadequate water
and sanitation have strong adverse
effects on a healthy life such as:
• Premature mortality: Poor
sanitation has had a direct
impact on lost lives, especially
those of children. India shares
some of the highest-burden of
disease caused by diarrhoea,
which has led to a massive loss
of DALYs in children under 5
years
32
.
Illustrative Economic Impact
through Basic Infrastructure
31
Sanctuary, Mark & Tropp, Hakan. (2004). Making Water a Part of Economic Development: The
Economic Benefits of Improved Water Management and Services.
32
hgamapserver.who.int/gho/interactive_charts/phe/wsh_mbd/atlas.html
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Bijapur Kalahandi Latehar Muzaffarpur
Kiphire Baramula Bahraich Kondagaon
Bhadradri-Ko-
thagudem
Garhwa Dhubri
Udham Singh
Nagar
Narayanpur DumkaSirohi Virudhunagar
Sukma Chandauli Gumla Kupwara Aspirational Districts Program • Additional Costs: Lack of
infrastructure to support water
and sanitation provisions often
lead to higher healthcare costs
for individuals. The cumulative
effect of such costs incurred
also hurts the national economic
prospect as it was reported in
2016, that poor sanitation cost
India about 5.2% of its GDP
33
.
• Productivity losses: This refers to
the productive time lost due to
illness and mortality. Productivity
loss also includes productive time
lost to look after the ill by the
caregivers.
Thus, the following analysis intends
to measure the savings made by
the Aspirational Districts under
each state by preventing loss of
healthy lives through successful
implementation of relevant central
schemes. These central schemes
include Swachh Bharat Mission
(Gramin) and National Rural Drinking
Water Programme (NRDWP).
Prevention of the loss of healthy
lives is key for any governing body.
Hence, curbing the cumulative
DALYs must be a priority for the
local governing bodies. From a
policymaking point of view, it is
crucial to understand DALYs as
34
:
• It highlights the aid required
for setting health service (both
curative and preventive) priorities
and further, establishing health
research priorities.
• It supports categorising
disadvantaged groups and
targeting of necessary health
interventions.
• Delivers a comparable measure
of intervention-based output.
Plenty of studies in the past have
highlighted the importance of
reducing the loss of healthy lives by
ensuring the consistent provision of
water and by implementing simple
sanitary measures. Preservation
of healthy lives in a defined region
raises the productivity levels, which
in turn boosts the economic potential
that can be derived from that same
region
35
. Hence, the same discourse
could be replicated in the ADP. This
could be attained by monitoring the
progress made by the districts in
terms of the annual rate of in-house
toilet construction and delivery of
potable water.
33
LIXIL, WaterAid, Oxford Economics. (2016). The True Cost of Poor Sanitation.
34
Murray, C. J. (1994). Quantifying the burden of disease: the technical basis for disability-adjusted life
years. Bulletin of the World health Organization, 72(3), 429.
35
Cylus, J., Permanand, G., & Smith, P. C. (2018). Making the economic case for investing in health
systems: What is the evidence that health systems advance economic and fiscal objectives? 92
Under the Swachh Bharat Mission
(Gramin), construction of household
latrines has been a crucial
component. Construction of in-house
toilets is one of the first steps taken
under this mission to undertake
intensive behaviour change across
the grassroots level.
The mission has also underlined
the urgent need for such a drastic
behavioural change as the costs
incurred due to poor sanitation
are huge and have long-lasting
consequences on public health,
environment and the economy:
Impact on Public Health: For this
study, major emphasis will be given
to the impact of poor sanitation on
public health. Open and untreated
human excreta can often interact
with food through soil, water and
crops. This creates a dangerous
chain of the faecal-oral route. And
according to a study conducted by
the UNICEF, one gram of faeces
can contain 10,000,000 viruses,
1,000,000 bacteria, 1,000 parasite
cysts and 100 parasite eggs
36
.
Furthermore, poor sanitation leaves
children under the age of five highly
susceptible to dangerous diseases
due to their relatively weaker
immunity. As mentioned before,
under-5 child mortality based on
diarrheal cases has crossed 1.9
million in developing nations
37
.
Role of the Mission and
Aspirational Districts: Thus, as
a part of Swachh Bharat Mission,
one of the major objectives was
to break the oral-faecal route by
constructing toilets across all the
rural households. This would be
supported by other policy measures
such as
38
:
• Encouraging communities and
Panchayati Raj institutions
to adopt other sustainable
sanitation practices.
• Developing community-
managed solid and liquid waste
management systems.
Indicator: Percentage of households with
Individual Household Latrines (IHHL)
36
UNICEF. (2000). Sanitation for All: Promoting dignity and human rights.
37
Vijaya Shankari, A., Kalpana, S., & Srinivas, G. (2019). Diarrhoeal Disease Among Under Five Children
in India: A Brief Review. University Journal of Medicine and Medical Specialities, 5(4).
38
www.prsindia.org/theprsblog/swachh-bharat-mission-gramin Aspirational Districts Program IHHL does create an induced impact
in terms of fall in diarrhoeal cases
39
.
This has been observed in India
as well where the most vulnerable
demographic group, i.e. 0-4 years;
have seen a consistent decline in
the cases for deaths arising from
diarrhoeal diseases. Thus, IHHL
has certainly played a major part in
curbing these deaths across India
with other factors such as public
awareness programmes, delivery
of safe drinking water and strict
tracking of progress made under the
Swachh Bharat Mission (both rural
and urban).
And the results witnessed under the mission have been impressive. All the
states have managed to achieve a 100% IHHL.
(Source: Swachh Bharat Mission)
(Source: Global Health Observatory Data, World Health Organization)
39
UNICEF. (2018). Evidence Review Potential Impact of Sanitation on Health and Wellbeing. Final Report.
Figure 4.22. Coverage Status of IHHL across all States
Figure 4.23.
Number of
deaths due
to Diarrhoeal
diseases (0-4
Years) in India
(2013-17)
20132014201520162017
20,000
0
40,000
60,000
80,000
10,0000
12,0000
14,0000
124175
112854
106367
98197
91270
Oct-14
38.7
50.84
64.91
84.18
98.28
100
0
20
40
60
80
100
120
2015-2016 2016-2017 2017-2018 2018-2019 2019-2020 94
Thus, over the last few years, there has been
a consistent fall in diarrhoeal related death
cases amongst children as the Swachh
Bharat Mission accomplished its objective of
100% IHHL in all the states. While National-
level impact evaluation of the Mission is a
must to understand the overall economic
benefits; this study would like to present the
situation at a disaggregated level through
Aspirational Districts.
According to a study conducted by the World
Bank
40
; successful policy interventions can
bring in drastic socio-economic benefits in
terms of costs per DALY saved. This includes
hygiene behaviour change, which accounts
for a savings of 26.42 USD
41
per DALY. IHHL
falls under the ambit of Hygiene behaviour
change as prescribed under the Swachh
Bharat Mission. Thus, by assessing the rate
at which the toilet has been constructed, a
fair assessment can be made both at the
state and the district levels to measure the
potential socio-economic savings.
Savings on DALY is a crucial component of
socio-economic savings. DALY includes the
unit of time lost due to disability or premature
mortality. And at the national level, it has
been witnessed that the diarrhoeal related
death cases are falling. Hence, it is fair to
expect that more individuals will get the
opportunity to live a healthy life, free from
any insanitary-related disability or even
premature death. This should translate into a
more productive life where eventually these
individuals will be able to contribute to the
economy owing to their good health.
40
Lvovsky, K. (2001). Health and environment (Vol. 1). World
Bank, Environment Department.
41
The value has been inflation-adjusted for the year 2019 (i.e.
the year of impact analysis) Aspirational Districts Program 96
According to the Champions
of Change Dashboard, most of
the Aspirational Districts have
tremendously managed to achieve
100% IHHL as early as December
2018. And by the end of the year
2019, all the districts have now
accomplished the same objective.
The above ten districts have ensured
maximum difference between their
current scores and their respective
baseline scores. This shows the
rapid progress that has taken place
in just a year. Interestingly, seven
out of ten districts here are from
Bihar, thus highlighting a strong
case for possible policy collaboration
between the state and the district
level stakeholders.
Following Bihar’s example, a state-
level analysis presents an interesting
picture.
Potential Economic Savings from IHHL: Findings
Figure 4.24.
Actual Scores
for 2019
(Difference
between
Current
Scores and
Baseline
Scores)
MANY STATES HAD ALREADY ACHIEVED CLOSE TO
SATURATION LEVELS OF SCORES WHEN THEIR BASELINE
VALUES WERE RECORDED. AS A RESULT, THEIR ACTUAL
SCORES NOW COME OUT TO BE MINIMAL. WHILE IT MAY
LEAD TO LOWER ECONOMIC SAVINGS, THIS IS A TESTAMENT
TO THEIR STRONG POLICY IMPLEMENTATION IN IHHL EVEN
BEFORE THE ASPIRATIONAL DISTRICTS PROGRAMME WAS
IMPLEMENTED.
Balangir
Katihar
Purnia
Banka
Muzaffarpur
Jamui
Godda
Aurangabad
Araria
Bhadradri-
Kothagudem
96.58
69.75
69.65
68.92
62.88
60.61
59.23
58.95
58.45
58.27 Aspirational Districts Program The above map shows that for the
year 2019, it was the Central and
the Eastern states that made most
of the progress. Most of the North
East States and the Western States
such as Rajasthan and Maharashtra
had already achieved saturation
during the baseline period. On the
other hand, Bihar, Uttar Pradesh
and Jharkhand were the biggest
achievers in the year 2019 and as a
result, managed to potentially make
the biggest savings assigned with
hygiene behaviour change.
These savings can be varied from
state to state due to two important
factors:
i. The number of Aspirational
Districts present in these States.
For instance, Jharkhand with
its 19 Aspirational Districts
will report higher savings as
compared to Kerala that has only
one Aspirational District.
ii. The number of beneficiaries
present in each Aspirational
District. Highly populated
states will report more savings
as compared to less populated
states. For instance, both Katihar
(Bihar) and Balangir (Odisha)
have similar scores for the year
2019, however, the former’s
population is twice the latter’s;
thus, contributing more to the
potential savings.
Figure 4.25.
State-wise
economic
savings
due to IHHL
based on
incremental
progress
during 2018-
2019
Total Potential
State-Wise
0.0 65.3 98
AFTER CONSIDERING ALL THE
ABOVE FACTORS, THE OVERALL
SAVINGS THAT THE DISTRICTS
COULD ACCUMULATE WAS ABOUT
INR 400 CRORES.
Way
Forward
The indicator data for the year 2019
shows that the Aspirational Districts
have taken major strides to bring
consistent improvement. More than
half of the districts have above 90%
annual average for the calendar
year. This implies that strong
potable water delivery services are
available in these districts and soon
will establish a proper network,
which would ensure that all the
beneficiaries receive an adequate
amount of potable water. The rest of
the districts are also not far behind
as the overall average for all the
112 districts come out to be 78.62%,
which is a tremendous achievement.
Compared to this, according to a
Comptroller and Auditor General
(CAG) report in 2017, it was found
that less than half of the target
was met at a national level under
the National Rural Drinking Water
Programme (NRDWP)
42
. That
To further this study, a district-level
assessment must be carried out
that could measure the longitudinal
impacts of construction of IHHL. This
could be corroborated by a monthly
change in child death rates owing
to diarrhoeal deaths. Along with
a health assessment, there must
be a simultaneous Environmental
Impact Assessment (EIA) that
could scrutinise the frequency of
untreated sewage mixing into local
water bodies for all the districts.
Finally, the scope of the study
must be expanded to other sectors
including Education, Tourism, etc.
that could highlight the economic
impacts owing to the presence of
conventional sanitation measures
such as IHHL.
Indicator: Percentage of Rural Habitations with
Access to Adequate Quantity of Potable Water
42
www.bloombergquint.com/law-and-policy/national-rural-drinking-water-programme-failed-
to-achieve-targets-government-auditor-heres-why Aspirational Districts Program Potential Economic Savings due to
Potable Water: Findings
very audit report specified “poor
execution” and “weak contract
management” as two major reasons
for the failure of the programme
to meet its objectives. Thus, the
progress made by Aspirational
Districts has overcome those barriers
and presents another example of
successful policy convergence and
collaboration across various tiers of
stakeholders.
Similar to the IHHL, many districts
were closer to saturation during
the beeline period. However, the
scope for improvement under this
indicator is much bigger. As a result,
some of the districts have shown a
tremendous jump and as a result,
have increased their corresponding
potential savings.
Unlike what was observed with the
IHHL scores, districts from various
States have made tremendous
progress to ensure that potable
water is made available for all. It
was also interesting to note that
North East districts such as Chandel
(Manipur) and Ribhoi (Meghalaya)
have improved significantly.
Figure 4.26
Actual Scores
for 2019
(Difference
between
Current
Scores and
Baseline
Scores)
Ranchi
Nabarangapur
Lohardaga
Balangir
Ribhoi
Yadgir
Dhubri
Virudhunagar
Chandel
Bhadradri-
Kothagudem
9.98
13.53
14.69
20.02
21.79
26.90
28.20
30.78
34.22
74.27 100
THE TOTAL SAVINGS, BASED ON THE ABOVE IMPROVEMENTS,
THAT THE 112 DISTRICTS COULD MAKE CAME OUT TO BE A
MASSIVE AMOUNT OF INR 1443 CRORES.
This figure accounts for the savings, all the districts can make by reducing the
disability and fatality caused by delivery of unsafe water.
Figure 4.27:
State-wise
economic
savings due
to potable
water
based on
incremental
progress
during 2018-
2019
The above map shows that state-
level savings vary significantly. Most
of the Eastern and Southern states
have ensured high savings whereas
Central and Western states have
struggled to achieve the same.
Districts from both Madhya Pradesh
and Maharashtra were not able
to create a distance between their
actual scores for 2019 and their
baseline values. This is an alarming
sign, given that both the states suffer
from severe water pollution
43
and
most importantly, water deficiency
44
.
43
www.downtoearth.org.in/blog/water/can-ministry-of-jal-shakti-save-indian-rivers--65197
44
indianexpress.com/article/explained/simply-put-5000-dry-villages-in-maharashtra-6500-
tankers-5777789/
Total State-
Wise Potential
-103.1 293 Aspirational Districts Program Savings by costs analysis, delivered
some very surprising results.
The state with the biggest return
on costs was Manipur. Its only
Aspirational District, Chandel, has
been one of the biggest improvers
in the year 2019 with respect to
delivery of potable water. As a
result, the district over-delivered
by not just accomplishing its target
for the calendar year but also by
potentially providing better returns
on the costs incurred for provisioning
potable water.
Similarly, Tamil Nadu also with
its two districts has given strong
returns over the associated costs.
This exercise goes to show that
there is so much potential economic
gains/ savings that can be made
from selected districts, that they
can help the state in overcoming the
existing liabilities.
As far as the best performers are
concerned; Odisha, Telangana,
Bihar are some of the states with
more than two Aspirational Districts
that have recorded huge potential
economic savings. Most of the
districts in these states have a
healthy gap between their current
scores and their baseline values,
thus paving the way for major
improvement.
To further evaluate the efficacy of
such savings, this study also looked
at the funds that were allocated to
the states by the Ministry of Jal Shakti
for the financial year of 2019-2020.
The assumption here is that all these
funds will be used by the states
to meet the costs for the National
Rural Drinking Water Programme
(NRDWP).
Saving/ Expenditure (%) for 2019Figure 4.28:
Savings Over
Costs for the
Top 10 States
in 2019
1468.33
313.15
234.06
177.73
154.54126.86
74.64
57.3743.28
Manipur
Tamil
Nadu
Jharkhand
Telangana
Odisha
Chhattisgarh
Andhra
Pradesh
Bihar
Assam The above potential savings
can be further strengthened
for the majority of the
districts and states, as they
are yet to achieve 100%
potable water supply.
Hence, all the relevant
stakeholders need to focus
on meeting this target given
the impending challenge of
water shortage that would
affect the world soon.
For future assessment
processes, new parameters
must be brought in regarding
water management in
Aspirational Districts. Along
with successful water
delivery, modes of water
treatment must also be
studied. This would ensure
complete coverage of water
provisioning both in terms of
quantity and quality.
Furthermore, policy
convergence observed
across all the districts must
cover the anecdotes on
innovative means of water
conservation.
Efficient utilisation would
reduce the burden on our
depleting water-sources.
Thus, new and unique
methods must be showcased
that have positively affected
the water supply at local
levels. For instance, in the
YSR Kadapa district in
Andhra Pradesh, water
conservation process has
been a success through the
construction of subsurface
dams. These subsurface
dams cost one-tenth of
traditional dams and have
benefited around 36 villages
in the district area
45
.
45
niti.gov.in/sites/default/files/2019-08/4_Presentation-for-
PrincipalSecretariesPlanning.pdf
102 Aspirational Districts Program 104
DISCUSSION
OF RESULTSDISCUSSION OF RESULT
05 Aspirational Districts Program The above section presented the
improvements that districts have across
sectors. The performance measurement
of the aspirational districts depicts
varied impacts across parameters. The
observations for the Health and Nutrition
sector suggest that 10 percent of the
districts have already achieved their
targets, whereas 90 percent of the districts
have covered almost 3/4th distance to
their respective targets. On the contrary,
the observations for the Financial Inclusion
sector suggests that none of the aspiration
districts are close to their aspirational
targets. All the districts are approximately
40 to 90 percent far from their targets. DISCUSSION OF RESULT 106
In order to understand the reasons
for such varied performance
of sectors across districts, the
observed outcomes were further
examined in the following manner:
The identification of the indicators
on the basis of who directly controls
them drives this process. While
we may qualify, that all data
points are affected to a varying
a degree by the effort of district
administration, a few of them are
directly affected. This could impact
the decision-making capacities
and the anticipated outcomes
under the programme. Aiyar (2018)
pointed out
46
the limited flexibility
in such a decision-making structure
could affect the implementation
capacity of District Magistrates/
District Collectors. Therefore,
indicators falling directly under the
control of the District Magistrate/
District Collector were isolated, and
the trajectories of the indicators
were assessed on those specific
parameters in this segment of the
report.
47
This allowed the analysis
to control those indicators outside
the ambit of the District Magistrate/
District Collector and effectively
gauge how well the programme has
been able to impact the ability of
the district administration to drive
social impact.
By isolating indicators, the analysis
is able to:
• Isolate the impact of other
national/state schemes.
These indicators reflect the
improved governance of
the district administration
stimulated by competition,
collaboration, and convergence
under the Aspirational Districts
Programme.
• Inform the district
administration about the
development trajectories of
certain indicators – which
indicators need short-term
policy intervention strategies
and which indicators require
longer intervention periods to
show results – allowing them
to create more effective
intervention strategies in the
medium to long term.
46
Aiyar, Y. (2018, May 15). Why the Aspirational Districts Programme may not change anything
on ground. Retrieved from Hindustan Times: https://www.hindustantimes.com/columns/
why-the-aspirational-districts-programme-may-not-change-anything-on-ground/story-
Tnb22h2rMLWUI16MxmZ83J.html Aspirational Districts Program By taking into account only the
indicators that can be impacted by
the DMs, the study reflects on two
things. First, the assessment intends
to highlight if there has been a
tangible change within the districts
as compared to their position at the
baseline of the analysis. Secondly,
it intends to understand which are
the districts that have been able to
drive the maximum change. It must
be recalled here, as mentioned in the
prior sections of this report, one of
the major thematic ideas guiding this
programme is to help the districts
which have emerged as laggards in
social development to the forefront
improving India’s overall human
development. Therefore, the following
analysis sheds light on whether the
districts that lagged behind the most
during the baseline survey have
been able to catch-up to the leaders,
or if the dichotomy among districts
remains constant.
ASSESSING THE RESULTS:
OVERALL PERFORMANCE
Figure 5.1.
Relationship
between
rate of
change
(2018-2020)
and baseline
scores
For the ease of comprehension, the
districts have also been divided
into four categories based on their
baseline scores. The quartiles are
directly proportional to the baseline
scores of the districts. Districts with
the top 25 percent scores in 2018
have been categorised in the Fourth
Quartile. Similarly, districts with the
bottom 25 percent scores in 2018
have been categorised in the First
Quartile within the ambit of this
analysis.
20
20
15
45
45 55 65
10
40
40 50 60
5
35
35
0
30
30
-5
25
25
-10
Score for 2018
Lower
QuartileMedian
Upper
Quartile
Rate of Change
(2018-2019)
Tier
1.0 4.0
• The graphs shows a negative relationship between
the rate of change and baseline scores with a strong
correlation of -0.66.
• This indicates that districts in the bottom tier are
catching up rapidly with the high ranking districts.
• The average rate of growth of fourth quartile (Tier 1)
districts is 8.2 percent while that of first quartile (Tier
2) districts is 25 percent. 108
THE PROGRAMME HAS
THEREFORE NOT ONLY BEEN
SUCCESSFUL IN DRIVING
SOCIAL IMPACT BUT ALSO
IN DRIVING SOCIAL JUSTICE
BY ENSURING THAT THE
MAXIMUM BENEFITS OF THE
PROGRAMME GO TO THOSE
WHO NEEDED IT THE MOST.
In Figure 5.1., it can be seen that the average
growth rate for the districts visible in the First
Quartile is 25 percent. Similarly, the average
growth rate for the districts in the Fourth
Quartile is only 8 percent. This indicates that
the districts that were initially lagging behind
have been able to drive the maximum change
under the programme. Districts which were
initially leading, have also been able to drive
change but at a much slower rate owing to
their proximity to saturation. This means,
under the Aspirational Districts Programme,
districts that were initially lagging in social
and human development indicators have
been able to drive the maximum change
and catch-up to the leaders. This is further
bolstered by the strong correlation of -0.66
between the rate of change scores from 2018
to 2020 and the baseline score from 2018.
Using the above analysis, it can be depicted
with clarity that the Aspirational Districts
Programme has been able to create a
positive social impact by improving social
and human development indicators within
a district. Furthermore, the effective
performance management under the
programme has facilitated those districts the
most that were most deprived in social and
human development at the initiation of the
programme. Aspirational Districts Program The performance of the
states is analysed to assess
any emerging patterns
that may better inform
the policy design aspects
moving ahead. In other
words, if any particular
state has shown marked
improvements or appears to
lag across the parameters
of the programme, special
focus can be given to those
Aspirational Districts to
create more regional equity.
It would ultimately lead
to the overall success of
the programme across the
country.
The state performance
analysis involves depiction
of the change in mean
scores of the Aspirational
Districts within each state
from 2018 to 2020. In Figure
5.2, the states have been
portrayed on the basis of
their performance in the
current year of assessment,
i.e. 2020.
The states highlighted
in red (Figure 5.2) mark
a dip in the current year
of assessment. States
registering lower mean
scores should be given
special focus moving
forward to create better
regional equity within the
ambit of the programme.
The discourse guiding
the programme is one of
regional equity. Regularly
identifying states and
districts that appear to
fall behind would be a
crucial step to ensure that
the programme does not
create a dichotomy of
winners and losers but
actually contribute to the
overall regional equity
within the country leading
to better social and human
development. Currently,
Aspirational Districts in
states with more visible
white spaces – such as
Bihar, Madhya Pradesh, and
Telangana would require
more focus moving forward
compared to the rest of the
country.
ASSESSING THE RESULTS:
STATE WISE*
The results and recommendations from the state wise analysis must be
understood very carefully keeping in mind the limitations of conducting a state
wise analysis. The limitations arise as the number of districts in each state under
the program varies. 110
Figure 5.2: State-wise change in
mean scores on the Aspirational
Districts framework
Haryana
Rajasthan
Delhi
Madhya Pradesh
Gujarat
Maharashtra
Goa
2018
010305070
2019
2020
Uttarakhand
2018
010305070
2019
2020
2018
010305070
2019
2020
2018
010305070
20192020
Punjab
2018
010305070
20192020
70
2018
0103050
20192020
2018
010305070
20192020
2018
010305070
20192020
Chhatisgarh
2018
010305070
20192020
2018
010305070
20192020
Karnataka
2018
010305070
20192020
Kerela
2018
010305070
20192020
Tamil Nadu
2018
010305070
20192020
Andhra Pradesh
2018
010305070
20192020
Himachal Pradesh
2018
010305070
20192020
Uttar Pradesh
2018
010305070
20192020
Arunachal Pradesh
2018
010305070
20192020
Bihar
2018
010305070
20192020
Telangana
2018
010305070
20192020
Meghalaya
2018
010305070
20192020
Jharkhand
2018
010305070
20192020
Sikkim
2018
010305070
20192020
West Bengal
2018
010305070
20192020
Assam
2018
010305070
20192020
Tripura
2018
010305070
20192020
Mizoram
2018
010305070
20192020
Manipur
2018
010305070
20192020
Nagaland
2018
010305070
20192020
Jammu & Kashmir
2018
010305070
20192020
Odisha
2018
010305070
20192020
Note: Red indicates states where mean scores have fallen in the last year.
Blue indicates a general upward trend. Aspirational Districts Program Figure 5.3:
Performance
of Districts
across
parameters
Figure 5.3 portrays that the
Aspirational Districts have shown
the biggest improvement in the
Education sector. The disparity
among the districts has fallen the
most in the Education Sector. On
the contrary, Agriculture and Water
Resources Sector indicates a lot of
scope for improvement. The districts
have also been able to reduce their
respective disparities across the
sectors of Health and Nutrition,
Skill Development, and Basic
Infrastructure.
ASSESSING THE RESULTS:
ACROSS PARAMETERS
Among all the sectors considered
within the ambit of the programme,
the Health and Nutrition sector
is noted to house the maximum
number of indicators. Therefore, it
has been separately analysed in
Figure 5.4.
20
15
10
5
0
-5
-10
Health &
Nutrition
Education
Change in Mean
Change in Std. Dev.
Agriculture
and Water
Resources
Skill
Development
Basic Infra 112
The total number of indicators
under the Health and Nutrition
sector accounts for 31 individual
data-points. This is significantly
high as it represents around 36%
of the total number of data-points
across the sectors. The data-points
have been thematically categorised
and subsequently analysed in
Figure 5.4 to assess the key
movements within this particular
domain.
The detailed assessment of
the Health & Nutrition sector
showcases some interesting trends
in policy impact. The maximum
improvement in the domain of
Health and Nutrition has happened
within the Health Infrastructure
domain. Disparities within districts
have reduced the most under Child
Care, which could be a result of
focused policy initiatives to support
child immunisation and Integrated
Child Development Services (ICDS)
across the country. Similar is the
trajectory for aspects related to
maternal care, which are often
related. It must be noted here that
the most encouraging inference
from the analysis stems from the
fact that all parameters across
the sector have shown marked
improvement. It must also be noted
here that driving change in aspects
of health care under any policy
intervention is no mean feat that
can be easily achieved. Often, these
interventions require sustaining
behavioural changes – like regular
access to nutritious food for
pregnant women – which may come
with its socio-cultural baggage in
the context of South Asia. The fact
that the programme, along with its
digital performance management
mechanisms, has been able to
achieve this change is in itself a
positive social impact.
Figure 5.4:
Performance
of Districts
in the
Healthcare
Ecosystem
Changes in the Healthcare Ecosystem
20
15
10
5
0
-5
-10
Maternal Care
Child Care
Health Outcomes
Heath Infrastructure
Change in MeanChange in Std. Dev. The indicators which can be most
influenced by the District Magistrate
have further been categorised
into two additional aspects. In the
first segment, the indicators are
collated based on their ease of
implementation. On the basis of
secondary research and extensive
field engagements undertaken
within the scope of this research with
district administrators, the indicators
which can be most influenced by
the district administration have
been categorised into short-term
indicators, medium-term indicators,
and long-term indicators under the
programme. This analysis is expected
to help the district administration
develop effective timeframes for policy
interventions under the Aspirational
Districts Programme, and reduce
incorrect target setting exercises such
as expecting to achieve targets of the
long-term indicator within a short-
term of policy intervention.
In the subsequent section, the
indicators are further classified into
impact and performance indicators.
Such a classification based on the
type and nature of the indicators
enables the report to highlight
whether the Aspirational Districts
Programme has been able to drive
any tangible change at the ground
level or have been restricted in
showing improvements across input
intervention. It must be noted here
that improvement in performance is
often harder to achieve as compared
to inputs since performance indicators
can also demand behavioural change.
If the programme has been able to
generate a positive impact on the
performance indicators, along with
the impact indicators, it can be an
indication of the positive behavioural
change that is being driven within the
districts by the Aspirational Districts
Programme.
UNDERSTANDING THE
INDICATORS IN MORE DETAIL
Aspirational Districts Program Ease of
Implementation
The nature of indicators across
sectors varies, and their outcomes
may be visible across different
points of time. While some
indicators are comparatively
easier to move owing to their
implementation processes, other
indicators may be more complex
to administer by the District
Magistrate/District Collector.
Similarly, some indicators can
be improved within a short time
such as the indicator measuring
the provision of textbooks under
the Education sector. Others
would require more time to
reflect improvement and need
interventions for longer durations.
For instance, indicators measuring
improvement in institutional
deliveries under the Health and
Nutrition sector would take more
time to move owing to its scope and
nature as compared to the previous
example of textbooks.
114 Therefore, to address the varying nature and ease of achievability of the
indicators, they have been categorised into three groups:
Short Term – comprising of indicators whose impact can be tracked in the
short-term after any related policy intervention.
Medium Term – comprising of indicators whose impact can be tracked in
the medium-term after any related policy intervention.
Long Term – comprising of indicators that require a long gestation period
to show impact after any related policy intervention.
The analysis intends to study the rate of change for the indicators across
these three categories.
This analysis will be particularly
useful for the district authorities to
determine the “low hanging fruit”
under the ambit of the programme,
or the indicators that they may
focus upon to see immediate gains.
Furthermore, it will help the district
administration better strategise
their interventions with more
information on the nature of the
indicators, allowing them to come
up with more effective timelines
to achieve the determined targets
under the ambit of the programme.
THE HYPOTHESIS FOR THE ANALYSIS IS THAT THE RATE
OF CHANGE OF SHORT-TERM INDICATORS WILL BE THE
HIGHEST AMONG THE THREE. THE RATE OF CHANGE
OF MEDIUM-TERM AND LONG-TERM INDICATORS WILL
FOLLOW A SIMILAR TREND, THEREBY, REFLECTING
THAT THE RATE OF CHANGE FOR ANY INDICATORS IS
RELATIVE TO ITS EASE OF ACHIEVABILITY OVER TIME.
Aspirational Districts Program 116
Figure 5.5: Comparison of Mean
Scores for Short-Term, Medium-
Term and Long-Term Indicators
16
16
202020
16
16
16
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12
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101010
8
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555
4
4
4
4
0
0
000
0
0
0
0
Categorization of Indicators by Ease of Achievement
Indicators achieavable in Short Term
2018 Scores
2018 Scores
2018 Scores
2019 Scores
2019 Scores
2019 Scores
2020 Scores
2020 Scores
2020 Scores
Indicators achieavable in Medium Term
Indicators achieavable in Long Term
FrequencyFrequencyFrequency While short-run indicators were already at
a high mean score in 2018, their dispersion
has reduced over time. The medium-term
indicators had the lowest mean in 2018
but have shown the most improvement
across the three years. Their dispersion is
also the highest in 2020 across all levels.
The long-run indicators were stickier across
time, which is expected since the time-span
assessed here is too short.
• The short-term indicators have been
able to significantly converge around its
high mean scores – that is to indicate
that those districts which were lagging
in 2018, have been able to catch-up with
their peer districts.
• Though the medium-term indicators
show the highest dispersion among the
districts, they have been able to achieve
the maximum change within the scope of
the programme as the analysis; and,
• As believed, the long-term indicators
have recorded little variation over
time owing to the “sticky” nature of
these indicators. They would require a
sustained gestation period before related
policy interventions can show traceable
impact in these domains.
The key learning is that the districts
should develop goal posts based on the
ease of achievement of the indicators.
KEY INFERENCES
Aspirational Districts Program Type of Indicator
Along with the ease of
implementation analysis that will
facilitate the districts to determine
robust timeframes to achieving
targets under the Aspirational
Districts Programme, the report
also expands the analysis to the
nature of the indicators. By further
categorising indicators into impact
and performance indicators and
studying their trajectories of
change, the analysis would further
help the districts to better strategise
interventions within the programme
leading to better social and human
development in the districts.
This classification, relating to
the type of the indicator, has
been based on the defining
characteristics of the sectors
within the Aspirational Districts
Programme. Indicators under
each sector have been classified
either as “impact indicators” or as
“performance indicators” depending
on its nature and scope of their
effect. In other words, indicators
that are predominantly dependent
on input factors – such as provision
of text-books – have been classified
as impact indicators. Similarly,
indicators that are more dependent
on outcome factors – such as the
prevalence of institutional deliveries
within a district – have been
classified as performance indicators
within the scope of this analysis.
118 In other words, based on their
distinct types, the indicators have
been grouped as:
Impact indicators – Impact
indicators measure a region’s
policies that are believed to create
an impact on the outcomes. These
may include indicators pertaining to
infrastructure, such as the number
of hospitals, schools, etc.
Performance indicators –
Performance Output indicators
directly measure the outcome
of policies. For instance, a
performance indicator may measure
the quality of the infrastructure in
place.
THE HYPOTHESIS
UNDERLYING THIS
CLASSIFICATION IS THAT
THE RATE OF CHANGE
REFLECTED BY THE IMPACT
INDICATORS WILL BE
HIGHER THAN THE RATE
OF CHANGE DEPICTED
BY PERFORMANCE
INDICATORS.
The analysis of indicators based
on their nature of achievement is
similar to the analysis previously
done for ease of achievement. The
analysis highlights the following
inferences within the scope of this
report.
The distribution of aggregate mean
scores for the impact indicators
has improved across the three
years. However, the extent of
improvement varies from the
performance indicators. One of the
probable reasons could be that the
required infrastructure to achieve
improvement across indicators was
available. The sufficiency of these
infrastructural or policy provisions
can be gauged from the depiction
of improvement in performance
indicators over time.
Aspirational Districts Program 120
The improvement in aggregate
mean scores can be seen in the
distribution for performance
indicators in Figure 5.6. The
dispersion has also reduced
across the years. The performance
indicators have shown a visibly
superior outcome over the impact
indicators. This can verify the
previous assumption and imply
that the districts had the inputs in
place. Therefore, social challenges
could be addressed during the term.
The monitoring mechanism of the
programme could have incentivised
the district administrations towards
improving their performance
parameters.
Figure 5.6: Comparison of mean score for
impact and performance indicators
1616
202020
16
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0
0
0
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0
FrequencyFrequency
2018 Scores
2018 Scores
2019 Scores
2019 Scores
2020 Scores
2020 Scores
Categorization of Indicators by Year
Impact Indicators
Performance Indicators KEY INFERENCES
• The impact-indicators have shown
improvement, but owing to the work
already done in the districts under
the various missions and schemes
of the government vis-å-vis input
infrastructure, the change in these
indicators appears to be somewhat
subdued when compared to the
performance indicators.
• The improvement in mean scores of the
performance-indicators in the analysis is
more vivid over time. This can somewhat
vindicate the previous inference. Since
the input infrastructure was already
present in the districts, the competition,
collaboration, and effective monitoring
undertaken by the Aspirational Districts
Programme have probably enabled the
districts to achieve positive outcome vis-
å-vis the performance indicators.
Aspirational Districts Program The analysis in the report until this section highlighted
the performance of the Aspirational Districts Programme
since its implementation in March 2018. In other words,
the three previous sections – the DTF Analysis, the
Mobility Matrix, and the prior section assessing the impact
of governance across different districts focus on the
transformations and social impact that has been created
under the Aspirational District Programme from the
baseline condition.
IMPACT OF ADP
BEATING SECULAR
TRENDS?
06 Each section highlights its distinct
findings and showcases the impact
that the programme has been able
to create across different sectors
and their respective indicators. To
briefly sum up the programme has
undoubtedly created some positive
impact across the sectors even
though the scale of the impact has
been severely varied. It is generally
observed across the analysis that
sectors that have received a higher
weight within the design of the
programme, such as Health and
Nutrition and Education, have shown
comparatively more impact than
other sectors
SECTORS SUCH AS BASIC
INFRASTRUCTURE THAT
ARE BEING DRIVEN
BY MISSION MODE
PROGRAMMES SUCH
AS SWACHH BHARAT
AND SAUBHAGYA, HAVE
ALSO SEEN SIGNIFICANT
IMPROVEMENT IN THE
ASPIRATIONAL DISTRICTS
OF THE COUNTRY.
Based on these inferences, it is
becoming obvious to investigate if
the Aspirational Districts Programme
does add any additional value as a
policy intervention across the sectors
or would the districts showcase very
similar development trajectories even
in the absence of the programme. If it
can be comprehensively determined,
using a statistical technique that the
Aspirational Districts Programme
does positively influence the
growth trajectories of the indicators
compared to their secular trends then
the research can definitively attribute
the social impact to the Aspirational
Districts Programme itself. To
achieve this, the research analyses
indicators from the domain of Health
and Nutrition and Education –
which comprise of 60% of the total
weight given to the sectors under
the programme – to check if the
programme has been able to create
tangible impact within its scope by
enabling these indicators to beat their
respective secular trends. 124
In order to do this, existing public databases such as Health Management
Information System (HMIS) (for Health and Nutrition indicators) and UDISE
(for Education indicators) are used. In this, indicator level data for common
indicators, that are indicators, which are present in the aforementioned
public databases and within the scope of the Aspirational Districts
Programme, are compared for two phases with similar time-period. It means
that the changes in the common indicators over equal intervals of time are
compared before and after the implementation of the Aspirational Districts
Programme.
A two-tailed z test is used because there can be a worsening of district
performance post-ADP. For accuracy, time-periods immediately before
and immediately after the implementation of the Aspirational Districts
Programme have been used as per the latest available data for the
indicators.
SINCE THIS IS AN INDICATIVE
ANALYSIS, ONLY THOSE DATA-POINTS
THAT ARE PUBLICLY AVAILABLE HAVE
BEEN USED TO ENSURE THE EXERCISE
IS EASILY REPLICABLE TO CHECK FOR
STATISTICAL VALIDITY. ONCE THE
CHANGE IS CALCULATED BEFORE AND
AFTER THE IMPLEMENTATION OF THE
PROGRAMME, A TWO-TAILED Z-TEST IS
CONDUCTED TO DETERMINE IF THERE
IS ANY STATISTICALLY SIGNIFICANT
DIFFERENCE THAT HAS BEEN
ACHIEVED UNDER THE ASPIRATIONAL
DISTRICTS PROGRAMME. Aspirational Districts Program The use of a two-tailed Z-test is of
relative significance here. A Z-test is a
well-established statistical technique
used to test hypotheses of any
experiment. In order to use the Z-test
in the scope of this research, the
report hypothesises that the annual
increment in indicator performance
before the aspirational districts
programme is equal to the annual
increment under the programme. As
discussed in the previous paragraph,
the annual increment immediately
before the implementation of the
programme and immediately
after the implementation of the
programme has been considered
for select indicators. This data has
been collated for all 112 Aspirational
Districts within the scope of the
programme.
Once the data for all the districts are
collated, the mean and the standard
deviation of the given sample is
calculated, and a decision rule is
established. A decision rule, in simple
terms, refers to the choice of the test
statistic and the confidence interval
within which the hypothesis needs
to be tested. Following this, a Z-test
is run on a pre-determined level of
statistical significance.
It must be mentioned here that
for sample sizes less than 30, the
convention dictates that a t-statistic
test is used instead of a z-statistic
test. Since the sample size, or the
number of data points, is greater than
30 in this research – a z-statistic test
is being used. Also, as there are two
possible outcomes that one may
observe after the implementation
of the Aspirational District
Programme, a two-tail Z-test is
being used instead of a one-tail
Z-test. A two-tail Z-test informs if a
particular parameter being tested
has shown any change – either
increase or decrease – thereby
enabling a researcher to reject the
null hypotheses or the hypotheses
that were created before the test
was conducted. Apart from a two-
tail Z-test, a Z-test can also be
of two other types. An upper-tail
Z-test and a lower-tail Z-test. An
upper-tail Z-test is usually used
when an increase is hypothesised.
Similarly, a lower-tail Z-test is used
when a decrease is hypothesised.
The reason for this report to use the
two-tail Z-test instead is because
the research neither hypothesises
an increase nor a decrease, but
it simply hypothesises a change
which can either be increasing or
decreasing in nature. It is effective
to test the indicators in such a
manner as with the implementation
of a new policy intervention
programme, all three observations
– an increasing, a decreasing, or
an unchanged – trajectory of the
indicators are possible. Using a
two-tailed Z-test not only allows
the identification of change but
would also allow the identification
of the trajectory of change – if any –
that has been brought about by this
programme 126
In the scope of this analysis, the Z-test is conducted at a 5 percent level
of significance, which indicates that the test would be able to state with
95% confidence whether the programme has shown any change from the
secular trends of the tested indicators. The test would reject the hypothesis
if |Z| < Zα /2. Thereby, it would be able to determine if the difference in
the incremental change under the Aspirational Districts Programme is
statistically significant or not.
In the scope of this report, nine indicators from the Health and Nutrition
sector and five indicators from the Education sector were tested to
determine if the Aspirational District Programme has been able to break the
secular trends in these domains.
HYPOTHESIS
H0 : µ = µ
0
H
A
: µ ≠ µ
0
We reject H0 at significance
level a if|Z| <
Z
α/2
TEST STATISTIC
DECISION
ACCEPTANCE
REGION (A.R) AND
REJECTION REGION
(R.R) OF H
0
a/2a/2
A.R. of H0
R.R
Of H0
R.R
Of H0
1 - a
Ζ
a/2
Ζ
1- a/2 = -Ζ
a/2
Calculate the value of :Ζ ∼ N(0,1)=
-Χµ
0
/σ√n Aspirational Districts Program In the Health and Nutrition sector, it is evident that five out of nine indicators tested
have registered significantly higher improvements during the Aspirational Districts
programme as compared to their secular trends. Three of the indicators considered did
not show any significant change in their trend. It must be noted here that it does not mean
that the indicators have not improved; it simply means that the rate of improvement
under the programme has not been faster than the secular trajectories. One indicator
tested, the percentage of live babies weighed at birth, showed a positive change at the 10%
significance level but not at the 5 percent significance level.
Indicator
0.0000.0001.000Yes
0.0001.0000.000Yes
0.0000.0001.000Yes
0.0000.0001.000Yes
0.4080.7960.204No
0.0580.0290.970No
0.7140.3570.643No
0.0010.0050.9995Yes
0.0020.0010.999Yes
Percentage of ANC registered
within the first trimester
Percentage of deliveries at
home attended by SBAs
Percentage of new-borns
breastfed within one hour of
birth
Percentage of low birth weight
babies (less than 2500g)
Percentage of live
babies weighed at birth
Percentage of children
fully immunised
Sex Ratio at birth
Percentage of Pregnant
women having severe anaemia
treated
Percentage of
institutional deliveries
Based on Ζ test
(at 5 % level of
significance)
p-valueAcceptance
Is there significant
difference due to the
programme?
µ1 ≠ µ0µ1 > µ0µ1 < µ0
p-valueAcceptance
Incremental
improvement under
programme is higher
p-valueAcceptance
Incremental
improvement before
AD was highe
r
Health and
Nutrition 128
It is important to note that one
of the nine indicators tested has
shown a curious trend wherein the
development under the Aspirational
Districts Programme has appeared
to be significantly lower than the
secular trend. The percentage
of institutional deliveries has
registered a slower growth under
the Aspirational Districts Programme
than before. However, this could
be an outcome of the fact that this
particular indicator had almost
reached saturation around 2015-16
itself, as depicted in Figure 6.1. As
witnessed in the previous section of
this report, the closer an indicator
gets to saturation its rate of change
gradually reduces. This could be a
possible explanation for the indicator
to effectively show a slower rate of
change under the programme than
under its secular trend.
Araria
Asifabad (Adilabad)
Aurangabad
Bahraich
Baksa
Balangir
Balrampur
Banka
Baramula
Baran
Barpeta
Barwani
Bastar
Begusarai
Bijapur
Bokaro
Chamba
Chandauli
Chandel
Chatra
Chhatarpur
Chitrakoot
Dakshin Bastar Dantewada
Damoh
Darrang
Dhalai
Dhaulpur
Dhenkanal
Dhubri
Dohad
Dumka
Fatehpur
Firozpur
Gadchiroli
Gajapati
Garhwa
Gaya
Giridih
Goalpara
Godda
Gumla
Guna
Hailakandi
Hardwar
Hazaribagh
Jaisalmer
Jamui
Kalahandi
Kandhamal
Karauli
Katihar
Khagar
ia
Khandwa (East Nimar)
Khunti
Kiphire
Kondagaon
Koraput
Korba
Kupwara
Latehar
Lohardaga
Mahasamund
Malkangiri
Mamit
Mewat
Moga
Muzaffarpur
Nabarangapur
Namsai
Nandurbar
Narayanpur
Narmada
Nawada
Nuapada
Osmanabad
Pakur
Palamu
Pashchimi Singhbhum
Purbi Singhbhum
Purnia
Raichur
Rajgarh
Rajnandgaon
Ramanathapuram
Ramgarh
Ranchi
Rayagada
Ribhoi
Sahibganj
Sheikhpura
Shrawasti
Siddharthnagar
Simdega
Singrauli
Sirohi
Sitamarhi
Sonbhadra
Sukma
Udalgu
ri
Udham Singh Nagar
Uttar Bastar Kanker
Vidisha
Virudhunagar
Visakhapatnam
Vizianagaram
Washim
Wayanad
West District
Y.S.R.
Yadgir
100
0
Figure 6.1. Percentage of Institutional Deliveries had almost reached saturation across most Aspirational Districts by 2015-16.
Percentage of Institutional Deliveries to Total Deliveries
(2015-2016)
WITH FIVE OUT OF NINE INDICATORS POSITIVELY BEATING THE SECULAR
TREND TO REGISTER IMPROVED GROWTH TRAJECTORIES AT 5% SIGNIFICANCE
LEVELS, IT CAN BE STATED THAT THE ASPIRATIONAL DISTRICTS PROGRAMME
HAS INDEED BEEN ABLE TO BEAT THE SECULAR TREND IN IMPROVING HEALTH
AND NUTRITION IN SOME OF THE MOST CHALLENGING AND UNDERDEVELOPED
REGIONS OF THE COUNTRY. Aspirational Districts Program
Education
LIKE HEALTH AND NUTRITION, THE INDICATORS IN EDUCATION ALSO
SHOW POSITIVE IMPROVEMENTS UNDER THE ASPIRATIONAL DISTRICT
PROGRAMMES BEATING THEIR SECULAR TREND OF GROWTH.
FOUR OUT OF FIVE INDICATORS TESTED SHOW A STATISTICALLY
SIGNIFICANT IMPROVEMENT IN THE DOMAIN OF EDUCATION UNDER
THE ASPIRATIONAL DISTRICTS PROGRAMME
.
Indicator
0.0150.007Yes
Yes
0.4680.000
0.234
No
0.0000.0051.000
1.000
1.000
0.993
0.766
Yes
0.000
0.000
0.001Yes
Percentage of schools with
functional drinking water facility
Percentage of schools with
electricity facility (secondary)
Transition Rate (Upper Primary
to Secondary
Transition Rate (Primary to
Upper Primary)
Percentage of schools with
functional girls’ toilets
Based on Ζ test
(at 5 % level of
significance)
p-valueAcceptance
Is there significant
difference due to the
programme?
µ1 ≠ µ0µ1 > µ0µ1 < µ0
p-valueAcceptance
Incremental
improvement under
programme is higher
p-valueAcceptance
Incremental
improvement before
AD was highe
r
Only one indicator, the percentage
of schools with functional drinking
water facility, shows a slower rate of
growth under the programme than
the secular trend. Similar to the trend
observed in the Health and Nutrition
indicator, this particular indicator
too was almost near saturation
during 2015-16 across the districts.
It could be one of the reasons for the
indicator registering a slower rate
of change under the programme as
compared to its secular trend. Visakhapatnam
Vizianagaram
Y.S.R.
Namsai
Baksa
Barpeta
Darrang
Dhubri
Goalpara
Hailakandi
Udalguri
Araria
Aurangabad
Banka
Begusarai
Gaya
Jamui
Ka�har
Khagaria
Muzaffarpur
Nawada
Purnia
Sheikhpura
Sitamarhi
Bastar
Bijapur
Dakshin Bastar Dantewada
Kondagaon
Korba
Mahasamund
Narayanpur
Rajnandgaon
Sukma
U�ar Bastar Kanker
Dohad
Narmada
Mewat
Chamba
Baramula
Kupwara
Bokaro
Chatra
Dumka
Garhwa
Giridih
Godda
Gumla
Hazaribagh
Khun�
Latehar
Lohardaga
Paku
r
Palamu
Pashchimi Singhbhum
Purbi Singhbhum
Ramgarh
Ranchi
Sahibganj
Simdega
Raichur
Yadgir
Wayanad
Barwani
Chhatarpur
Damoh
Guna
Khandwa (East Nimar)
Rajgarh
Singrauli
Vidisha
Gadchiroli
Nandurbar
Osmanabad
Washim
Chandel
Ribhoi
Mamit
Kiphire
Balangir
Dhenkanal
Gajapa�
Kalahandi
Kandhamal
Koraput
Malkangiri
Nabarangapur
Nuapada
Rayagada
Firozpur
Moga
Baran
Dhaulpur
Jaisalmer
Karauli
Sirohi
West District
Ramanathapuram
Virudhunagar
Asifabad (
Adilabad)
Bhoopalapalli (Warangal)
Bhadradri-Kothagudem
Dhalai
Hardwar
Udham Singh Nagar
Bahraich
Balrampur
Chandauli
Chitrakoot
Fatehpur
Shrawas�
Siddharthnagar
Sonbhadra
100
0
Figure 6.2. Percentage of Schools with Functional Drinking Water (2015-2016).
The indicator Percentage
of Schools with Functional
Drinking Water, like
Percentage of Institutional
Deliveries, had almost
reached saturation across
most Aspirational Districts
by 2015-16. This reason
could have possibly led to
a slower rate of change
under the programme as
compared to its secular
trend. With four out of five
indicators, positively beating
the secular trend, to register
improved growth trajectories
at 5 percent significance
levels, it can be stated that
the Aspirational Districts
Programme has also been
able to beat the secular trend
in improving Education and
its related indicators in the
Aspirational Districts.
130 Aspirational Districts Program
To sum up, the use of the Z-test
enabled the research to identify
if the improvements under the
Aspirational Districts Programme
were statistically significant or were
broadly in tune with the secular
trends that had existed before the
implementation of the programme.
In order to check this, select
indicators from the domain of Health
& Nutrition and Education were
chosen to check the secular trend
trajectories on the basis of publicly
available data to make the exercise
replicable. In this regard, matching
indicators from HMIS and UDISE
were chosen to test for secular
trends.
It emerged that 9/14 indicators
tested showed a statistically
significant improvement, i.e. they
were able to beat the secular growth
trajectories under the Aspirational
Districts Programme.
This could be an extremely
encouraging sign for the programme
as it is not only able to generate
significant improvements within
a very short span of time but is
also doing so faster than the prior
secular trend. One limitation of
this analysis is that it is conducted
for only 14 data points within the
programme owing to constraints of
data availability. Future research can
further explore this aspect across
more indicators of the programme
to comprehensively identify the
areas in which the programme has
been able to beat the secular trends,
thereby creating a significantly
positive impact in some of the
most challenging geographies of
the country. Finally, the fact that
competition, collaboration, and
convergence can actually determine
better policy outcomes compared
to secular trends further testifies to
the effectiveness of the fundamental
discourse of this programme.
It validates the belief that improving
the quality of governance can
produce better social and human
development outcomes – an
idea that has the potential to be
replicated globally. The Aspirational Districts Programme (ADP)
and Sustainable Development Goals (SDGs)
both emphasise on the provisioning of basic
services through sustainable means to the
most marginalised communities and people.
As discussed earlier, the focus of ADP
revolves around six domains:
• Health
• Education
• Agriculture and Water Resources
• Skill Development
• Financial Inclusion
• Basic Infrastructure
IMPACT OF ADP
ATTAINING THE
SDGs
07 134
These domains cover a wide range
of socio-economic issues that
subnational policymaking has to
deal with regularly. The original
objective of ADP is to bring holistic
development to the relatively
backward 112 districts across India
through Policy convergence and
collaboration and by promoting
competition amongst the districts.
This objective aligns with the
spirit of SDG 10 to reduce various
forms of inequalities
48
. Aligning the
objectives of ADP with that of SDGs
is crucial to establish a time-bound
assessment framework.
In the last two years, NITI Aayog has released the SDG India Index that assesses the progress made at the state level concerning the completion of all the seventeen Goals. Thus, a similar framework must be created to assess the same level of progress at the district-level. There are multiple ways in which such a framework could benefit the subnational policymaking:
• By tracking the SDG completion
for aspirational districts, the
State Government could assess
the policy convergence at both
state and district levels. This
would further guide the States in
pinpointing the areas where the
progress of aspirational districts
successfully aligns with that of
its own.
• Evaluation of the above policy
convergence/divergence; it could
promote State-District level
policy collaboration. Therefore,
this would streamline the
policymaking from sub-national
to the next disaggregated level.
Studies also reflect how strong
collaboration results in the
successful execution of policies,
thus attributing to holistic
regional development
49
.
• Adherence to the framework
could also prompt successful
competitive federalism as
envisioned by NITI Aayog
amongst the Aspirational
Districts. Healthy competition
amongst the districts could
result in large-scale regional
development with long-term
economic and social multipliers
benefiting the most vulnerable
sections of that region.
• Finally, states such as Bihar
and Jharkhand, that did not fare
well in the latest NITI India SDG
Index could use this framework
to nudge their Aspirational
districts in improving their SDG-
related indicators that in turn
could improve their state-level
performance.
Need for a
Framework
48
NITI Aayog. (2019). SDG India Index 2019.
49
OECD. (2010). The Interface Between Subnational and National Levels of Government. Aspirational Districts Program The objective of this framework is to
identify the key indicators common
between the ADP and the SDGs.
While all the indicators under both
the programmes may not align,
NITI Aayog has identified six SDGs
(namely SDG 3, 4, 6, 8, 9, 10) that
could be aligned perfectly with the
indicators prescribed under the
Aspirational Districts
50
.
Thus, a list of indicators has been
compiled to assess the progress
of a district made under the ADP.
This progress could then be linked
with the rate of completion of
SDGs for all such districts. For this
framework, NITI Aayog’s metadata
has been referred to which finds the
closest-possible SDG indicator that
could be linked with an Aspirational
District indicator
51
.
Methodology
50
NITI Aayog. (2019). SDG India Index 2019.
51
NITI Aayog. (2018). Transformation of Aspirational Districts; National Workshop on Real-Time
Monitoring Dashboard.
THE ANALYSIS FOR SDGS IS ONLY DONE FOR INDICATORS THAT CAN BE
MAPPED TO THE SDGS, CAN INTUITIVELY BE PROJECTED, AND WHERE
SUFFICIENT DATA IS AVAILABLE.
Using the data for these indicators from the dashboard, projections are made
to identify the year in which saturation will be achieved or districts will reach
the SDG target. These projections are made using moving average point
change to capture the changes between the rate of growth of districts that
start with a higher value and the districts that start with a low value. It has
been observed in the above analysis that districts that start at a lower value
tend to grow faster as they have both, a lot of scope for success as well as
learnings from other districts.
ADP SectorNumber of Overall Indicators
Basic
Infrastructure
Education
Health7
Total=13
3
3 136
Results
In the graphs below we present the time taken for the
mean scores of the districts on each of the indicators to
reach their target, categorised by sectors.
PLEASE NOTE THAT THESE
INDICATORS DO NOT
SPECIFICALLY FALL UNDER
SDGS BUT HELP IMPROVE
DEVELOPMENT INDICATORS
THAT HAVE A ONE-TO-ONE
MAPPING WITH SDGS. Aspirational Districts Program
Health
There are seven indicators under the
Health sector that can be mapped
to the SDG goals. Most of them
will be achieved within the target
date of 2030 and will significantly
contribute to helping India reach
the set goals. One area of concern
is the burden of tuberculosis (TB
cases. India has a low notification
rate for TB cases despite it being
mandated for all patients. As per
our projections, the notification rate
will reach 100 percent for these
districts only in 2038.
Percentage of Anganwadis centres/Urban
PHCs to have conducted at least one Health
Sanitation & Nutrition day
Proportion of Sub centres/ PHCs converted
into Health & Wellness Centres (HWCs)
TB Treatment success rate among notified TB
patients (public and private)
Tuberculosis (TB) case notification rate
(Public and Private Institutions) against
estimated cases
Percentage of children fully immunized (9-11
months) (BCG+ DPT3 + OPV3 + Measles1)
Percentage of institutional deliveries out of
total estimated deliveries
Percentage of Pregnant women having
severe anaemia treated against PW having
sever anaemia tested cases
2021
2021
2021
2020 2025 2030 2035 2040
2022
2026
2023
2038
Figure 7.1. SDG Target Achievement for Health
Years of SDG Achievement In the Education sector, we look at
three indicators – the Percentage
of elementary schools complying
with RTE specified Pupil-Teacher
Ratio, the Transition rate from upper
primary to secondary school level,
and Transition rate from primary
to upper primary school level. The
transition rate from upper primary
to secondary schools is very low in
the country indicating that children
drop out after class 8. The target for
this indicator will only be achieved
by 2031.
Education
Pupil Teacher Ratio
(RTE Compliant)
Transition Rate
(Upper Primary to Secondary)
Transition Rate
(Primary to Upper Primary)
2026
2027
2024
2022
2026
2028
2030
2032
2031
Figure 7.2.
SDG Target
Achievement
for
Education
Years of SDG Achievement
138 All indicators that can be mapped
with SDGs will be achieved even
before 2025. The progress over
the last few years on road building
and electricity penetration by the
government has yielded positive
results. Meanwhile, the push for
digital connectivity and falling
internet prices have driven internet
penetration into the aspirational
districts as well.
Basic Infrastructure
Percentage of habitations
with access to all weather
roads under PMGSY
Percentage of Gram
panchayat with internet
connection
Percentage of households
with electricity connection
2023
2020
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2024
Figure 7.3.
SDG Target
Achievement
for Basic
Infrastructure
Years of SDG Achievement
Aspirational Districts Program 140
LEARNINGSLEARNINGS
LEVERAGING THE
PARTNER ECOSYSTEM
08 Aspirational Districts Program Based on the field interviews and
the engagements undertaken
by the team within the scope
of this research, the report
recommends a six-point partner
engagement framework to
leverage maximum social and
human development outcomes
from partner engagements. This
framework recommends the key
guiding principles and maps it
to the identified challenges or
best practices shared by the key
stakeholders interviewed during
the research. LEARNINGS
WHAT WORKS?
FRAMEWORK FOR FUTURE
PARTNER ENGAGEMENTS IN
ASPIRATIONAL DISTRICTS L
if
e
C
y
c
le
o
f
a
p
a
r
t
n
e
r
e
n
g
a
g
e
m
e
n
t
Figure 8.1.
The 6-point
Engagement
Framework
COLLABORATE
ENGAGE
FACILITATE
MONITOR
PROMOTE
IDENTIFY
Initiation
Execution
Sustainable
Completion
142 Aspirational Districts Program Figure 8.2. The first step of the framework helps partners accurately
identify their domain, region, and point of intervention.
The framework is designed keeping
the entire lifecycle of partner
engagement in mind. In the first
stage of the framework, the
challenge of identifying the right
district based on the Aspirational
District data is addressed. Often,
as discussed in the previous
sections of this report, choosing the
incorrect district to engage leads
to the problem of either “too much”
or “too little” for the partners. This
may lead to undesirable social and
human development outcomes.
Whenever a partner intends to
engage or expand their geographic
scope within the Aspirational
District Programme, the use of
evidence-driven tools such as
Institute of Competitiveness (IFC)
Partner Connect, or any other
tool on similar principles, would
enable partners to choose points of
intervention appropriately allowing
them to leverage maximum social
and human development outcomes
within the scope and scale of their
intervention. Finally, this also allows
NITI Aayog to clearly define
the role of the partner once the
engagement is identified thereby
avoiding any mismatch in the goals
of the partner and the goals of the
district where the partner is going
to intervene.
Identify
Action Utilize evidence based analysis such as DTF to identify the domain, region, and
point of intervention. Assess if needs of the district are implementation oriented
or innovation model oriented. Avoid problems of engagement mismatch.
Time Frame At the initiation of the project.
Key Insights
Incorporated
Dual nature of existing development partner engagements within the
ecosystem – (i) program implementation engagements; and (ii) policy innovation
engagements.
Challenges
Addressed
1. Mismatch between the nature of engagement and the demands of the district.
2. Concentration of partners in some regions – ignoring others.
Risks May not be possible to effectively gauge niche challenges within districts using
CoC data – leading to incorrect assessment and incorrect identification.
Step 144
The framework is designed keeping
the entire lifecycle of partner
engagement in mind. framework
devices best practices for
generating collaboration with
the district administration. In
the scope of this research, it can
be stated on the basis of the field
engagements that partners are
most effective in collaborating
with district authorities when
they are embedded into the
institutionalised structure of the
district administration; and, have
subsequently been able to position
a human resource within the office
of the district administration. In this
regard, the framework recommends
that the partners – after identifying
the appropriate district for
engagement – collaborate with the
nodal ministry or NITI Aayog to
facilitate the institutionalisation of
the partner organisation within the
district administration.
Secondly, the framework
recommends that wherever
possible, the partners should
facilitate the presence of a human
resource within the district
administration. However, not
all partners need to position a
human resource within the district
administration if the scale and
the scope of the engagement are
limited. In case of high-intensity
engagements over medium to
long-term, the presence of a
human resource within the district
administration or collaborating with
other partners who already have
positioned a human resource within
the district administration office is
recommended.
Step
Collaborate
Figure 8.3. The second step of the framework highlights effective
collaboration strategies to overcome bureaucratic resistance.
Action Collaborate with the nodal ministry or NITI Aayog to facilitate the institutionalization of the partner organization within the district administration. Seek possible convergence/overlaps with other partner activities in districts.
Time Frame After identification of districts.
Key Insights Incorporated
1. Institutional engagement reduces bureaucratic hindrances.2. Convergence of partner activities lead to improved engagement outcomes and prevents crowding-in or overlaps.
Challenges Addressed
1. Resistance from district officials and line-departments to incorporate engagements within the practices of the district administration.2. Avoids concentration of partners and re-experimenting in similar engagement practices.
Risks Different nodal agencies – example NITI Aayog and MoHFW – allocate partners working in overlapping domains (Health). Difficult to collaborate unless such forums exists at national levels as recommended in the research. Aspirational Districts Program Moving forward, the engagement
strategy of the development
partner should not be restricted
to the district leadership but
also percolate to the secondary
and tertiary levels of officials,
preferably percolating to
the block/panchayat level.
This is another area where a
representative present within the
district administration encourages
better results from the perspective
of the partners as well as district
officials. The comprehensive
engagement with the district and
not just the District Collector/
District Magistrate allows better
continuity and prioritisation of
the program even in the case of
leadership change. This is critical,
as it has also been highlighted in
the previous section of the report
that the transition in leadership can
often adversely affect the continuity
of partner engagements in a given
district.
MOREOVER, THE GRANULAR ENGAGEMENT AT THE
BLOCK/PANCHAYAT LEVEL FURTHER ALLOWS THE
PARTNERS TO LEVERAGE BETTER SOCIAL AND HUMAN
DEVELOPMENT OUTCOMES BY BREAKING DOWN
NICHE CHALLENGES AT A SMALLER SCALE WHICH ARE
RELATIVELY EASIER TO MANAGE, ESPECIALLY FOR VERY
LARGE GEOGRAPHIC DISTRICTS.
Step
Furthermore, engaging directly
with front-line workers allows
the partners to have a robust
understanding of the capacity of
the human resources responsible for
delivering the partner engagement
services once the resources of
the partner are retracted from
the district at the closure of
engagement. Necessary strategies
to create capacity – especially in
districts facing the challenge of
vacant human resources at the
front lines – can be developed
by the partners at this stage to
ensure sustainable transition
and institutionalisation of the
engagement practices within the
district administration.
Engage 146
Figure 8.4. The third step of the framework highlights effective strategies
for partners to create engagement throughout the district administration
to help programme continuity and effective implementation of engagement
objectives by front line workers.
Action Allocate human resources within the district administration wherever possible.
Ensure clear communication of engagement goals to front-line workers and intra-
district functionaries. Get the buy-in of second-line district officials and Prabhari
Officers.
Time Frame On establishing collaboration and presence in district.
Key Insights
Incorporated
1. Young professionals improve motivation of district administration.
2. Second-line officials facilitate continuity in cases of leadership change.
Challenges
Addressed
1. Discontinued prioritization of engagement activities owing to leadership change in
districts.
2. Low understanding of indicators and end goals among front-line workers.
Risks Creating stakeholder engagement at the district level may be hindered by cultural
differences, time-line commitments of an engagement, and lack of enthusiasm for
partner priorities (as experienced in the case of some low weight indicators).
Aspirational Districts Program Facilitate
Figure 8.5. Facilitating the incorporation of engagement activities within
the district administration ensures that positive engagement activities
continue even after the closure of the partner engagement.
Here, the partners are expected to
tweak and innovate on the existing
solution to address district-specific
niche challenges. This would
further help in the adoption of the
evolved policy practices within the
government institutions across all
levels of the district. The role of the
partner in this stage is expected to
mostly be one of managing change
and overcoming institutional
resistance across the levels of the
district administration. Again, the
presence of a representative in the
district may be helpful in navigating
the change management aspects of
the engagement across the district.
Once the partners have established
a robust engagement across the
district administration and have
successfully operationalised
solutions to bridge critical gaps
within the districts.
The role of the partner can
focus more on facilitating the
operational changes using
knowledge support to the district
administration across levels.
Action Map engagement activities with roles of officials within a district – such as
encouraging ASHA workers to promote nutritious diet plans – and facilitate the
incorporation of engagement activities within the district administration.
Time Frame On successful engagement with all stakeholders within a district.
Key Insights
Incorporated
Creating sustainable engagement practices would require the enthusiastic
participation of the district administration and front-line workers.
Challenges
Addressed
Possible discontinuity of positive engagement activities at the closure of partner
engagements or the program.
Risks Some critical activities – such as financial inclusion – cannot be mapped to
existing roles as no such line-official exists within the district administration. Such
activities are mostly conducted by banks/financial institutions in the districts.
Step 148
Figure 8.6. Mapping partner engagement activities to existing roles/
institutions and monitoring them effectively can create lasting behavioural
change in the district administration.
Embedding the engagement
within the district administration,
the partner can further roll back
into the role of monitoring the
changed practices across the
districts intervening only when
there are hurdles or when
operational feedbacks are needed
by the district administration.
This allows the administration
to gradually imbibe the changed
policy operations and reduces the
dependency on the resources of the
partner.
This approach promotes the
creation of behavioural change
within the district administration by
effectively establishing a positive
feedback loop. Thus, the processes
get disseminated throughout the
district administration. Furthermore,
incorporating monitoring within
the engagement framework allows
partners to overcome the issue of
vacant supervisory positions within
districts. These roles can now be
bridged by the partner engagement
leading to sustainable assimilation
of the activities within the district
administration.
Monitor
Action Once mapped to existing roles/institutions at the district level, actively monitor
the engagement activities performed by the district administration with proper
feedback loops to institutionalize the processes and practices across the board.
Time Frame On successful mapping and facilitation of engagement activities to line-officials in
a district. Strategy should be in place at the initiation of the project itself.
Key Insights
Incorporated
Creating sustainable engagement practices would require the enthusiastic
participation of the district administration and front-line workers.
Challenges
Addressed
Inability to create behavioural change within the district administration to make
partner engagement practices sustainable.
Risks Imbibing practices of partner engagement may take additional time or capacity
building mechanisms for line-officials as low capacity of officials have been
identified as a challenge for partners.
Step Aspirational Districts Program Figure 8.7. By promoting successful engagement practices new
knowledge resources get created which help other districts overcome
similar niche development challenges.
Finally, when a district completely
imbibes and institutionalises
the policy operations that help
them bridge the capacity and
governance gaps within the district,
the partners may promote the
practice as a “proof of concept”
or “best practice” across districts
where similar strategies can then be
imbibed and scaled up.
This would facilitate the reduction
of intra-regional and inter-regional
disparities in partner engagements
as other districts – where the
partner may not be engaging – can
also replicate the best practices
and achieve similar social and
human development outcomes.
Furthermore, it would prevent
the loss of several key informal
learnings from the district that
can be applicable to regions
facing similar niche challenges.
The success stories also act as
inspiration for other districts by
creating a stronger resolve to drive
change. This additional motivation
can also bear a positive impact
on driving change within the
Aspirational Districts.
Promote
Action Publish and disseminate the learnings from engagements to other districts and
partners to induce similar best practices in other districts and global regions.
Time Frame On successful institutionalization of engagement practices within the institutional
structure of the district administration
Key Insights
Incorporated
Scaling-up of partner activities by disseminating innovative models of intervention
or best practices of policy implementation.
Challenges
Addressed
Intra-regional and inter-regional disparities in partner engagements. Loss of
knowledge resources that can promote change in regions facing similar policy
challenges.
Risks Some engagement practices can be context and institution specific within a given
state/district holding little external relevance.
Step Choose the correct domain, region,
and point of intervention by matching
partner and district foals and
orientation using data-driven insights
as indicated by IFC Partner Connect.
Approach partner engagements
with a framework to institutionalise
engagement activities within the
district administration so that the
positive impact continues even
after the closure of the particular
engagement initiative.
Create information symmetries within
the ecosystem to magnify the effects
of the engagements by convergence,
peer to peer learning, and scale-up
best-practices within India, as well as
at a global scale.
Promote the presence of human
and knowledge resources at
the districts to strengthen the
information structure and capacity
of the district officials to facilitate
better performance management,
competition, and convergence.
Engage local youth wherever
possible.
KEY INFERENCES:
HOW TO EFFECTIVELY
ENGAGE?
150 Aspirational Districts Program In this section, the report identifies
the top 10 districts that have been
able to drive the maximum change
from their baseline position till the
end of 2019 and highlight their
corresponding domain partners
facilitating this change. In order to
measure the change, the difference
between the relative positions of
districts vis-å-vis their targets
from their baseline position and
2019 have been considered. This
change has been transformed
into a relative score of 100 for all
the districts to better highlight
the relative improvements per
district from their baseline position.
This means the district that has
travelled the maximum distance
towards its target from its base-
line position has been given a score
of 100. The other districts have
been relatively scored according to
the movement of this district.
A lower score indicates that the
districts have been able to drive
a lower degree of change. One
limitation of such an analysis stems
from the fact that districts that
were closer to meeting their targets
at the baseline would record
lower scores as compared to the
districts that were much further
away, as the scope of movement is
restricted for districts closer to their
respective targets. However, the
niche challenges for the districts
which were further away from
their targets at the baseline would
conversely be steeper making it
harder for them to achieve change.
Once the districts have been
scored, their development partners
working in these domains have
been identified.
Again, this is not a metric to gauge
the relative performance of a
partner organisation. This exercise
is merely indicative of partners
who have been engaged in districts
that were able to drive maximum
change within the given time frame
under the programme. Since the
partners have the advantage of
tracking the field-level happenings
in these change-making districts,
they would eventually be better
positioned to inform the whole
ecosystem about the successful
strategies employed by these
districts to overcome challenges.
TOP CHANGE-MAKERS:
WHICH DISTRICTS HAVE BEEN ABLE TO DRIVE
THE MAXIMUM CHANGE WITH THE HELP OF
PARTNERS? Health &
Nutrition
In the Health and Nutrition sector,
the top 10 districts that have been
able to drive the maximum change
have all been effectively supported
by the presence of development
partners within the districts. Five
of the ten districts in the top 10
have registered the presence of
more than one partner in the
Health and Nutrition sector.
One partner has been facilitated
by the Ministry of Health and
Family Welfare (MoHFW) and the
other partner has been facilitated
either by Ministry of Home Affairs
(MHA) for LWE districts or NITI
Aayog. Since it has already been
mentioned that the Health and
Nutrition sector has seen the best
performance across all districts, it
can be indicated with some degree
of confidence that the partner
ecosystem has been particularly
effective in supporting the district
administration in this sector. It is
also perhaps relevant to note
here that almost 40% of all
partner engagements within the
Aspirational Districts Programme
are related to the sector of
Health and Nutrition.
District ScoreDomain Partners Engaged
Ranchi100USAID/IPE Global, Tata Trust
Sukma90.10Tata Trust
Nuapada 83.38UNFPA
Balrampur 80.24Piramal Swasthya, UNICEF
Wayanad 79.72UNICEF
Sheikhpura 79.52BMGF, Piramal Swasthya
Barwani 76.69Piramal Swasthya, Tata Trust
Siddharthnagar 75.73BMGF, Plan International
Firozpur 72.75USAID/IPE Global
Kupwara 72.45NIPI
Sector
152 Education
In the domain of Education, eight of
the top 10 districts that have been
able to drive the maximum change
are supported by development
partners working in the same domain.
Four of these districts (Garhwa,
Ranchi, Rajgarh, and Palamau)
are LWE districts from the state
of Jharkhand that have made their
place in the top 10 change-making
districts in the domain of education.
All these districts are partnered by
Tata Trusts that operates across
multiple domains in these districts,
including education. The other four
districts are mentored by Piramal
Foundation. Moving forward, more
partner engagement in the domain of
education is desirable as the sector
is given 30% overall weightage
within the programme but accounts
for only 10% partner engagements.
However, it must also be stated here
that several partners working within
multiple domains – such as Tata
Trusts and Lupin Foundation – are
also engaging with the districts in the
domain of education. Some of the
best case studies documented in the
field of education within the scope
of this research come from the LWE
districts of Jharkhand, where Tata
Trusts has been executing innovative
education initiatives such as “Project
Smart Shala” and “Project Angan”.
District Score Domain Partners Engaged
Jaisalmer 100Piramal Foundation (Education)
Hailakandi 89.68 No Domain Partner
Balrampur 88.38 Piramal Foundation (Education)
Sonebhadra 87.52 Piramal Foundation (Education)
Singrauli 85.44 Piramal Foundation (Education)
Rajgarh 84.67 Tata Trust*
Garhwa 82.24 Tata Trust*
Ranchi 81.65 Tata Trust*
Kupwara 79.14 No Domain Partner
Palamu 74.96 Tata Trust*
Sector
Aspirational Districts Program Only two out of the top 10
districts that have been able
to drive change in the domain
of Agriculture and Water
Resources have been supported
by a development partner
organisation. The significant
improvement of Andhra
Pradesh is also visible in this
analysis, as two out of its
three Aspirational Districts
have made it to the list. On
the whole, this indicates that
there are a lot of opportunities
for partners to engage in this
particular domain as districts
would require significant
handholding to achieve their
programme targets within this
particular sector.
District Score Domain Partners Engaged
Y.S.R. 100No Domain Partner
Bahraich 78.18 ITC Ltd
Vizianagaram 77.92 No Domain Partner
Fatehpur 75.75 No Domain Partner
Wayanad 75.50 No Domain Partner
Kupwara 73.71 No Domain Partner
Khunti 73.38 No Domain Partner
Siddharthnagar71.82 No Domain Partner
Baran 70.12 ITC Ltd
Bokaro 69.70 No Domain Partner
Agriculture
& Water
Resources
Sector
154 Financial Inclusion is another
sector where there is significant
scope for new partners to
engage and for existing partners
to expand their engagements
with districts. As discussed
within the scope of the DTF
Analysis and the Key Insights
section above, owing to its
low weightage (5%) in the
programme, Financial Inclusion
is often not prioritised either
by the district administration
or by the partner ecosystem.
Only one development partner
organisation is currently working
in this domain. Odisha and
Chhattisgarh have emerged
as two states that have been
able to drive the maximum
change in the domain of
Financial Inclusion compared
to all the other districts under
the programme. The top 10
change-makers in the domain
of Financial Inclusion are as
follows:
District Score Domain Partners Engaged
Nuapada 100 No Domain Partner
Bhadradri-
Kothagudem
95.37 No Domain Partner
Nawarangpur 73.72 No Domain Partner
Mahasamund 50.45 No Domain Partner
Dhenkanal 46.34 No Domain Partner
Rajnandgaon 41.17 No Domain Partner
Kanker 39.78 No Domain Partner
Wayanad 35.04 No Domain Partner
Moga34.99 No Domain Partner
Bastar 33.96 No Domain Partner
Financial
Inclusion
Sector
Aspirational Districts Program Like Financial Inclusion, several
districts in the domain of Skill
Development have a broad gap
from their programme targets
giving scope for more partners
to engage in this domain.
Districts supported by CII have
done well under this sector.
Four out of the 10 districts in
the top 10 are supported by
CII. However, it is important to
note that the only two districts
that have been able to achieve
or exceed their programme
targets in the country, Giridih
and Ramgarh from Jharkhand,
currently have no development
partners attached to them. The
top 10 change-makers in the
domain of Skill Development
are as follows:
DistrictScore Domain Partners Engaged
Giridih100 No Domain Partner
Ramgarh89.04 No Domain Partner
Sheikhpura82.38 CII
Ramanathapuram 81.09 No Domain Partner
Khagaria80.18 No Domain Partner
Baran75.59 Fuel, L&T, and CII
Malkangiri72.84 No Domain Partner
Latehar71.73 No Domain Partner
Barwani71.65 CII
Damoh69.85 CII
Skill
Development
Sector
156 Five out of the top 10
districts are supported by
development partners for
Basic infrastructure. Of these,
only one district is supported
by a development partner
dedicated to the domain of
Basic Infrastructure, while the
other four districts are LWE
districts that are supported
by Tata Trusts. Existing
government missions – such
as SAUBHAGYA and Swachh
Bharat – have addressed this
sector effectively. Moving
forward, partner engagement
in domains such as internet
connectivity in panchayats
and the creation of capacity
among local youth to establish
common services centres
at the panchayat level can
be considered. The top 10
districts that have been able
to drive the maximum change
under the programme are as
follows:
District Score Domain Partners Engaged
Khunti 100Tata Trust*
Baksa98.68 No Domain Partner
Bhopapalli 97.72 No Domain Partner
Sukma92.17 Tata Trust*
Giridih 91.99 Tata Trust*
Khandwa 91.06 Piramal Water
Godda90.02 No Domain Partner
Rajgarh 89.78 Tata Trust*
Ribhoi 88.94 No Domain Partner
Sheikhpura 87.94 No Domain Partner
Basic
Infrastructure
Sector
Aspirational Districts Program The influence of partners is seen most
significantly in the domain of Health
& Nutrition.
Financial Inclusion, Skill Development,
and Agriculture & Water resources
remain the most challenging sectors
to drive change.
Partners intending to support and
expand can select some of the
change-making districts which
currently lack external support to
further enhance their performance.
The analysis in this report and the IFC
Partner Connect tool can be useful in
this case.
The ability of the districts to drive
change irrespective of the support
from external partner organisations
in some cases may indicate that
the competition, convergence, and
collaboration within Aspirational
Districts Programme is able to drive
change in some cases irrespective
of the support from the partner
ecosystem. Partners can consider
moving into such districts for short
to medium term engagement in
order to help these districts achieve
saturation.
KEY INFERENCES:
TOP CHANGE-MAKERS
158 Aspirational Districts Program 160
RECOMMENDATIONS
09 Aspirational Districts Program RECOMMENDATIONS 162
STREAMLINING THE SURVEY
AND COLLECTION MECHANISMS
UPDATING PLAN OF ACTION
BASED ON NEW LEARNINGS
Recommendation Detailed Steps
Narrow Pool of Indicators
There is immense scope of streamlining the chosen group of indicators that form the basis of competition among the aspirational districts. For instance, indicators like the percentage of pregnant women taking nutrition and those having severe anaemia, treated are heavily correlated (0.89). It might be ideal to resolve such duplication of assessment.
Adjust frequency of data collection based on type
Not all indicators show change at a similar frequency as seen in the study. So, taking this into account, survey methods should be adjusted accordingly. Indicators that present change over the long-run should be assessed on an annual basis while the short-run indicators can continue to be assessed quarterly. This would also improve survey reliability.
Digitalisation of data mechanisms
The districts would benefit from a more real-time mechanism of data collection and dissemination. Currently, there is a gap of a few months between survey collection and accessibility of the data by districts. This can be improved if the process is digitised and districts can access the data with a minimal lag.
Recommendation Detailed Steps
Peer Group Comparison
Districts can assess where they stand on different parameters and in which sectors have they achieved their targets. Based on that, they can plan their future course of action. By assessing which tier group do they lie in they can draw learnings from their tiers and those above them.
Relative Movement across Regions
An assessment presented in the Mobility Matrix provides them with the data on whether they have improved, worsened or retained status quo. These achievements/failures can be traced back to the policies to understand What Works.
Best Practices of Leaders
The study is supplemented with case studies on some of the best practices for the leading districts across sectors. The districts can modify the learnings made from these practices based on their local requirements across different parameters.
The following recommendations are indicative of the way forward for the programme and includes several steps that are already being addressed, especially with the building of a new dynamic dashboard . Aspirational Districts Program DRIVING TARGETED INVESTMENT
THROUGH PARTNER ECOSYSTEM
LEVERAGING DATA TO DESIGN
EFFECTIVE EVALUATION SYSTEMS
Recommendation Detailed Steps
Defining investment
intensity through Distance to Frontier analysis
The partners should define their geography of investment based on their intensity of engagement. The appropriate geography can depend upon the length of their engagement. For instance, the partners that plan to engage for a longer period can choose districts that are farthest away from their targets based on the Distance to Frontier analysis.
Building partner engagement based on the 6 Point Framework
The study has developed a Six Point Framework across three major phases of partner engagement that can create better engagement outcomes for partners. The framework is targeted to be utilised by the development partners to leverage better engagement outcomes and promote institutionalisation of partner activities within the district administration.
Leveraging the IFC Partner Connect to drive engagement
Data visualisation and analytics can be utilised to create interactive dashboards, that can help in facilitating partner engagements and CSR in Aspirational Districts. IFC Partner Connect is one such interactive dashboard where partners can identify the domain, the region, and the point of engagement as per the requirement of the engagement profile. It also enables partners present in a district to identify potential areas of expanding their engagements.
Recommendation Detailed Steps
Defining Peer Groups
Assessment of districts should be done based on the standing of comparative peer groups. It has been seen that districts that start at a relatively low level on the development parameters show more rapid improvement over time since they have more opportunity to grow and also draw lessons from ideas that have been implemented elsewhere.
Conducting and Leveraging a Baseline Study
While extending the programme or replicating it across different geographies, it is instructive to conduct a baseline study and choose indicators that have scope for improvement. The study shows that indicators that had already attained near-saturation before the start of the aspirational districts programme show no significant boost in incremental change on introduction of the programme.
Examining the nature of indicators
While building evaluation mechanisms for projects like Aspirational Districts, the nature of the indicators should be kept in mind. The study shows that all the indicators do not grow at the same rate by using two categorisations: Ease of Implementation and Type of Indicators. It is observed that long-term indicators have low rate of growth compared to medium- and short-term indicators. Also, impact indicators are easier to implement as compared to outcomes. 164
ENGAGING IN CUSTOMISED
LOCAL LEVEL INTERVENTIONS
Recommendation Detailed Steps
Awareness Campaigns
It is observed that in many cases there is not enough demand for basic health and education infrastructure, or benefits of government programmes don’t reach the actual targeted groups due to lack of knowledge. In such cases, awareness campaigns are useful as they aid in reaching out to the populations that have stayed aloof from the development process. They also facilitate a common platform for engagement, thereby, helping in integration of actors and beneficiaries.
Involving young professionals within grass-root administration
Given one of the major problems is continuity in leadership, it is important that many young professionals are engaged that work directly at the local level and act as a common link between the partners and local government administration. It not only promotes continuity of engagements but also improves the motivation of bureaucrats leading to higher social and economic development.
Collaborating with locals
Collaboration with the individual functionaries helps in leveraging the social network and enhances the outreach capacity of the district administration in integrating the population. It also opens the door for the introduction of community-based intervention models, which facilitates stakeholder participation. For instance, women-driven institutions such as Self-Help Groups and Anganwadis have been particularly crucial in the delivery of schemes. Aspirational Districts Program APPENDIX
LIST OF ASPIRATIONAL DISTRICTS
StateDistricts
Andhra Pradesh Visakhapatnam, Vizianagaram, Y.S.R.
Arunachal Pradesh Namsai
AssamBaksa, Barpeta, Darrang, Dhubri, Goalpara, Hailakandi, Udalguri
BiharAraria, Aurangabad, Banka, Begusarai, Gaya, Jamui, Katihar,
Khagaria, Muzaffarpur, Nawada, Purnia, Sheikhpura, Sitamarhi
Chhattisgarh Bastar, Bijapur, Dakshin Bastar Dantewada, Kondagaon, Korba,
Mahasamund, Narayanpur, Rajnandgaon, Sukma, Uttar Bastar
Kanker
GujaratDahod, Narmada
HaryanaMewat
Himachal Pradesh Chamba
Jammu & Kashmir Baramula, Kupwara
Jharkhand Bokaro, Chatra, Dumka, Garhwa, Giridih, Godda, Gumla, Hazaribagh,
Khunti, Latehar, Lohardaga, Pakur, Palamu, Pashchimi Singhbhum,
Purbi Singhbhum, Ramgarh, Ranchi, Sahibganj, Simdega
Karnataka Raichur, Yadgir
KeralaWayanad
Madhya Pradesh Barwani, Chhatarpur, Damoh, Guna, Khandwa (East Nimar), Rajgarh,
Singrauli, Vidisha
Maharashtra Gadchiroli, Nandurbar, Osmanabad, Washim
ManipurChandel
Meghalaya Ribhoi
MizoramMamit
Nagaland Kiphire
OdishaBalangir, Dhenkanal, Gajapati, Kalahandi, Kandhamal, Koraput,
Malkangiri, Nabarangapur , Nuapada, Rayagada
PunjabFirozpur, Moga
Rajasthan Baran, Dhaulpur, Jaisalmer, Karauli, Sirohi
SikkimWest District
Tamil Nadu Ramanathapuram, Virudhunagar
Telangana Asifabad (Adilabad), Bhoopalapalli (Warangal), Khammam
TripuraDhalai
Uttar Pradesh Bahraich, Balrampur, Chandauli, Chitrakoot, Fatehpur, Shrawasti,
Siddharthnagar, Sonbhadra
Uttarakhand Hardwar, Udham Singh Nagar Institute for Competitiveness, India is the Indian knot in the global network of the
Institute for Strategy and Competitiveness at Harvard Business School. Institute for
Competitiveness, India is an international initiative centered in India, dedicated to
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Institute for Competitiveness, India conducts & supports indigenous research;
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implications for company strategy; the competitiveness of nations, regions & cities
and thus generate guidelines for businesses and those in governance; and suggests
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ASPIRATIONAL
DISTRICTS
PROGRAMME
ASPIRATIONAL
DISTRICTS
PROGRAMME
Michael Green
CEO, Social Progress Imperative
Dr. Amit Kapoor
Chair, Institute for Competitiveness
& Visiting Scholar, Stanford University
Michael E. Porter
Professor, Harvard Business School
Foreword By
Scott Stern
Professor, MIT
Authors ASPIRATIONAL
DISTRICTS
PROGRAMME
AN ASSESSMENT OF 04
Amit Kapoor
Chair
Institute for Competitiveness
Michael Green
CEO
Social Progress Imperative
All Images are representative
Authors
Designed By Aspirational Districts Program Foreword
India is at a crossroads. A rising focus on competitiveness has
produced a record of positive economic growth and pockets of
prosperity. India now stands as the fifth-largest economy in the
world. However, the uneven distribution of economic gains across
regions and individual citizens has only served to highlight the
need for a broader agenda aimed at inclusive growth and social
progress. Income growth has been concentrated in a small number
of individuals and regions. And, despite significant investments in
infrastructure and social services, India stands in the 102
nd
position
among 149 countries in the 2019 Social Progress Index. Going
forward, India’s progress should not be measured simply by its
achievement of a certain level of economic growth, but whether
India can realize its extraordinary potential when growth is shared
across the widest number of individuals, and addressing India’s
most pressing social progress challenges.
True success requires the integration of improving competitiveness
and social progress, which is the combination that unlocks
inclusive economic growth.
THE 2018 LAUNCH OF THE
“ASPIRATIONAL DISTRICTS”
PROGRAM (ADP) HAS BEEN
A BOLD AND PROMISING
STRATEGIC STEP TOWARDS
THIS NEW AGENDA. THERE
HAS BEEN A LONGSTANDING
FOCUS IN INDIA ON THE LEAST
DEVELOPED REGIONS ACROSS
THE COUNTRY.
Yet, ADP marks an important shift from pursuing economic growth
per se to focusing on achieving meaningful social progress ADP
benchmarks in 112 less developed Indian districts, and enables
partnerships among states in driving success. The program 06
focuses on practical and measurable
social progress outcomes, including
Health and Nutrition, Education,
Agriculture and Water Resources,
Financial Inclusion, Skill Development,
and Basic Infrastructure. Each of
these are critical to expanding shared
prosperity among all citizens.
By targeting a set of important but
practical areas for improvement at the
district level, ADP brings the promise
of both inclusive development and a
reduction in regional disparity. And,
the focus on enhancing each of these
critical areas offers the opportunity for
these regions to contribute to India’s
broader economic development as a
whole, while raising economic growth
itself over the long run.
The significant promise of the ADP
depends on identifying the most
leveraged areas for improvement, and
developing a broad set of practical
tools for enhancing India’s overall
development agenda.
This report, An Assessment of the
Aspirational Districts Program, offers
a timely yet systematic evaluation
of the ADP and the gains realized
to date. The report focuses on the
most significant economic and
social progress challenges facing
the ADP districts, and evaluates the
progress in these districts over the
first two years of the program. The
report also examines the role of the
stakeholder-oriented model, in which
public awareness, engaged public-
private partnerships, and cooperation
among multiple levels of government
is utilized to enhance the success of
individual initiatives.
Though still at an early stage, the
finding are highly encouraging.
Almost all districts included in the
ADP program have made progress
on key development parameters as
compared to the baseline, and are
performing significantly better today
than they were before the programme
was initiated. Particularly notable are
gains in Health and Wellness, and
Basic Infrastructure. The ADP seems
to not have simply maintained the
districts along a pre-existing trajectory
but materially improved the rate of
improvement.
A striking finding is the impact
of governance. Relative to a
conventional top-down approach, the
ADP supports active collaborations
among multiple levels of governance
within each ADP district, and the
use of public-private partnerships.
This stakeholder-oriented approach
is driven by a shared understanding
among the partners, and the use of
a common language of outcome-
oriented metrics and data. This study
builds on this data collection and
offers an interactive visualization
tool that can be used by the various
stakeholders, based on their own
priorities and resources to make
informed ADP strategy choices.
To date, the ADP focus on both
local economic development as well
as social progress improvement is
yielding positive gains. These early
achievement will catalyse broader
future gains, and accelerate Indian Aspirational Districts Program Prof. Michael E. Porter
Harvard Business School
Prof. Scott Stern
Massachusetts Institute of Technology
THIS REPORT NOT ONLY PROVIDES AN EARLY
ASSESSMENT OF THE ADP, BUT ALSO HAS THE
POTENTIAL TO CATALYSE ACTION THROUGHOUT INDIA.
BY FOCUSING ON “WHAT WORKS” IN ADVANCING
INCLUSIVE GROWTH AND SOCIAL PROGRESS, ADP HAS
THE POTENTIAL TO SERVE AS A MODEL FOR INDIA’S
FUTURE ECONOMIC AND SOCIAL DEVELOPMENT
STRATEGY.
progress towards meeting the Sustainable Development Goals.
The experience of the ADP initiative to date also offers key lessons that can
help galvanise and sustain the ADP program over time. Regional teams
are guided by collecting streamlined outcome data in a timely way, and are
structured so that leadership changes do not disrupt the successful execution of
the program.
Partnerships across districts maximize the spread of key interventions, and can
be expanded. Districts can sharpen their focus on the areas of greatest need,
and work to formalize mechanisms to collaborate and learn from peers and
better performing districts.
As the world continues to grapple with the fallout from the COVID-19 public
health crisis, the importance of resilient, shared economic development
combined with social progress have come into even sharper relief. This study
offers a timely and insightful guide into how and why the ADP program is
beginning to realize this promise in the neediest regions. 08
Executive
Summary
The Government of India
launched the Aspirational
Districts Programme
(ADP) in January 2018 to
accelerate improvement
in the socio-economic
indicators of the most
underdeveloped districts
of the country. Currently,
the programme has been
implemented in
112 OF INDIA’S 739
DISTRICTS, SPREAD
ACROSS THE COUNTRY. Aspirational Districts Program The ADP is a collective
effort. At the Central
level, NITI Aayog
is anchoring the
programme and
individual Ministries
have assumed
responsibilities to
drive the progress of
the districts. Yet it is
the state governments
that are the main
drivers of change.
Each state has formed
a committee under
their respective
Chief Secretaries
to implement as
well as track the
programme. Moreover,
for each district, a
central Prabhari
Officer of the rank of
Additional Secretary/
Joint Secretary has
been appointed to
provide feedback and
recommendations
based on their local
level findings. 10
The research in this study
documents the social development
outcomes in some of the most
challenging regions of India. It
examines institutional best practices,
coordination frameworks across
government bodies and other
partners, and governance and
leadership initiatives at the district
level which can be used to replicate
the success of this initiative not only
in other districts of India, but also in
other countries facing similar socio-
economic challenges.
by measuring the current state of various social parameters and
highlighting the most pressing issues, the programme recognises
that focusing solely on economic parameters will not lead to inclusive
development in India. Moreover, these social challenges might hamper
future economic growth as well.
by focusing on underdeveloped pockets of India it will help in addressing
the issue of regional disparities.
by embedding partners within the institutional rubric of the government
and encouraging them to integrate with the district administration
instead of them functioning as external practitioners of development, the
programme adopts a unique approach that can lead to maximum social
and human development.
The assessment of the programme
reveals insights that can provide
direction to the programme leaders
and implementing agencies about
future focus areas; it can help
in unlocking the full potential of
the programme and can provide
guidance for replicating the
programme across different
geographies.
FIRST,
SECOND,
THIRD,
We find that there are several ways the project contributes to
enhancing the social progress of the region. Aspirational Districts Program • Health and Education are the sectors
in which the districts are closest to
achieving their targets. In health, the
maximum distance of districts away from
their targets is about 30 percent.
• Agriculture and Financial Inclusion are
the main areas of concern for most
aspirational districts as their average
scores lie farthest away from the frontier.
Most of the districts are 40-90 percent
away from their targets.ADP COVERS
5 SECTORS:
Disparities across
sectors are high
HEALTH AND
NUTRITION
FINANCIAL
INCLUSION
AND SKILL
DEVELOPMENT
BASIC
INFRASTRUCTURE
EDUCATION
AGRICULTURE
AND WATER
RESOURCES
Distance to Frontier (Lower the better)
Agriculture and
Water Resources
0
10
20
Figure 1: Average Distance to Frontier across Sectors
30
40
50
60
70
80
90
Health and
Nutrition
Skill
Development
Financial
Inclusion
Education
Basic
Infrastructure
This analysis suggests that areas such as
Agriculture and Water Resources, Financial
Inclusion, and Skill Development require
greater attention in the ADP programme
going forward. 12
The disparities can be also be
seen by looking at a particular
district. Figure 2 below shows the
performance of Dahod district
across sectors. It has overachieved
its target in Health and Nutrition but
lags behind its targets by significant
margins in Agriculture and Water
Resources, Skill Development and
Financial Inclusion. These results
suggest that there are no clear
achievers or laggards across all
sectors.
Three key areas of best practice
have emerged from the ADP
programme:
a) Awareness: several districts have
used awareness campaigns
to reach out to populations
which have been detached
from the development process.
Awareness raising campaigns
help create a common platform
for engagement, thereby helping
with the integration of actors and
beneficiaries.
b) Collaboration: ADP incentivises
collaboration between tiers and
agencies of government and
with the private and civil society
sectors. By leveraging assets
and networks in a collective
effort, ADP enhances the
outreach capacity of the district
administration in integrating the
population.
c) Data-based interventions: the
use of data to measure impact,
locate nodes for improvement,
as well as to identify policies and
interventions that are driving
the most change is critical to the
success of ADP.
Figure 2. Disparities in the performance of Dahod across Sectors
Concrete best practices are
emerging from the programme
Distance to Frontier (How far are the
districts from achieving their target
Agriculture &
Water Resource
Dahod
Dahod
Dahod
Dahod
Tier
14
DahodDahod
Achievement of Target
Basic
Infrastructure
Financial
Inclusion
Health &
Nutrition
Skill
Development
Education
Basic
Infrastructure
(Electricity, internet,
roads, latrines,
water, CSCs, and
pucca houses
80
70
60
50
40
30
20
10
0
-10 This study also sheds light on the economic
benefits that the country can derive by addressing
social challenges. In Health and Nutrition, for
example, the economic impact of reducing Severe
Acute Malnutrition (SAM) among children is felt
through the effects on productivity and lifetime
learning. The overall economic impact for all the
states (only looking at Aspirational Districts) of
reducing SAM is estimated to be a mammoth
Similarly, the impact of
providing household
latrines is around
These economic
benefits can provide
a strong rationale
for the government
in investing in
programmes directed
towards social
benefits.
ADP is generating economic
as well as social impact
1.43 LAKH CR.
INR 400 CR.
Aspirational Districts Program 14
There is significant diversity among
the districts covered by ADP.
The indicators of the programme
also range from inputs through
to outcomes. This suggests two
opportunities to enhance data
collection and analysis:
a) Survey methods should be
adjusted to reflect the fact that
not all ADP indicators show
change at similar frequency.
Output and outcome indicators
that show change over the long-
run should be assessed on an
annual basis, while short-run
input indicators can continue to
be assessed on a quarterly basis.
This would also improve survey
reliability. Moreover, it would help
ADP leaders to streamline the
chosen group of indicators that
form the basis of competition
among the aspirational districts.
For example, indicators like
percentage of pregnant women
taking nutrition and those
having severe anaemia treated
are heavily correlated (0.89); it
would be ideal to resolve such
duplication of assessment.
b) The study shows that districts
that are at different levels
progress at different rates. For
example, districts at a lower level
that are catching up will be able
to progress faster than the most
advanced districts. Therefore, it
is suggested that districts are
divided into peer groups based
on their level of development, to
facilitate relevant lesson sharing.
Streamlining data collection and
ensuring effective feedback loop to
update programmes based on relevant
data insights is critical Aspirational Districts Program 16 Contents Foreward
Executive Summary
Introduction
Understanding the
Aspirational Districts
Programme (ADP)
Literature Review:
Impact Evaluation of Public
Programmes
Methodology:
Assessing the Aspirational
Districts Programme
Results
Discussion of Results
Impact of ADP:
Beating Secular Trends?
Impact of ADP:
Attaining the SDGs
Learnings:
Leveraging the Partner
Ecosystem
Recommendations
Appendix
05
08
22
30
44
50
58
104
122
132
140
160
166 18
LIST OF FIGURES
Figure 1 District Level Social Progress Index
Figure 1.1 The Key Focus Areas of ADP
Figure 1.2 Transformation of Partner Ecosystem
Figure 4.1 Distance to Frontier Analysis: Health and Nutrition
Figure 4.2 Mobility Matrix for Health and Nutrition
Figure 4.3 Future Engagements in Health and Nutrition
Figure 4.4 Top ten districts with the most improvement in SAM in 2019
Figure 4.5 State-wise impact of total potential savings
Figure 4.6 Distance to Frontier Analysis: Education
Figure 4.7 Mobility Matrix: Education
Figure 4.8 Future Engagements in Education
Figure 4.9 Distance to Frontier Analysis: Financial Inclusion
Figure 4.10 Mobility Matrix: Financial Inclusion
Figure 4.11 Future Engagements in Financial Inclusion
Figure 4.12 Distance to Frontier Analysis: Agriculture and Water Resources
Figure 4.13 Mobility Matrix: Agriculture and Water Resources
Figure 4.14 Future Engagements in Agriculture and Water Resources
Figure 4.15 Distance to Frontier Analysis: Skill Development
Figure 4.16 Mobility Matrix: Skill Development
Figure 4.17 Future Engagements in Skill Development
Figure 4.18 Potential Economic Gains due to Skill Development in INR Crores
Figure 4.19 Distance to Frontier Analysis: Basic Infrastructure
Figure 4.20 Mobility Matrix: Basic Infrastructure
Figure 4.21 Future Engagements in Basic Infrastructure
Figure 4.22 Coverage Status of IHHL across all States
Figure 4.23 Number of deaths due to Diarrhoeal diseases (0-4 Years) in
India (2013-17)
Figure 4.24 Actual Scores for 2019 (Difference between Current Scores and
Baseline Scores)
Figure 4.25 State-wise economic savings due to IHHL based on incremental
progress during 2018-2019
Figure 4.26 Actual Scores for 2019 (Difference between Current Scores and
Baseline Scores)
18 Aspirational Districts Program LIST OF TABLES
Figure 4.27 State-wise economic savings due to potable water based on
incremental progress during 2018-2019
Figure 4.28 Savings over costs for the Top 10 States in 2019
Figure 5.1 Relationship between rate of change (2018-2020) and baseline
scores
Figure 5.2 State-wise change in mean scores
Figure 5.3 Performance of Districts across parameters
Figure 5.4 Performance of Districts in the Healthcare Ecosystem
Figure 5.5 Comparison of Mean Scores for Short-Term, Medium-Term and
Long-Term Indicators
Figure 5.6 Comparison of mean score for impact and performance
indicators
Figure 6.1 Percentage of Institutional Deliveries to Total Deliveries (2015-
2016)
Figure 6.2 Percentage of Schools with functional Drinking Water (2015-
2016)
Figure 7.1 SDG Target Achievement for Health
Figure 7.2 SDG Target Achievement for Education
Figure 7.3 SDG Target Achievement for Basic Infrastructure
Figure 8.1 The 6-point Engagement Framework
Figure 8.2 The first step of the framework
Figure 8.4 The third step of the framework
Figure 8.5 The fourth step of the framework
Figure 8.6 The fifth step of the framework
Figure 8.7 The sixth step of the framework
Aspirational Districts Program
Table 1.1 Framework used for selection of Aspirational Districts LIST OF ABBREVIATIONS
3Cs Convergence, Collaboration and Competition
ADAspirational District
ADP Aspirational District Programme
APY Atal Pension Yojana
ASHA Accredited Social Health Activist
BMGF Bill and Melinda Gates Foundation
CAG Comptroller and Auditor General
CRC Citizens’ Report Cards
DALY Death-Adjusted Life Year
DBT Direct Benefit Transfer
DCs District Collectors
DDU-GKY Deen Dayal Upadhyaya Grameen Kaushalya Yojana
DFIC District Financial Inclusion Co-ordinator
DMs District Magistrates
DTF Distance to Frontier
EIA Environment Impact Assessment
HMIS Health Management Information System
HWCs Health and Wellness Centres
ICDS Integrated Child Development Service
ICT Information and Communications Technology
IFC Institute for Competitiveness
IHHL Individual Household Latrines
LDM Lead District Manager
LWE Left Wing Extremism
MAM Moderate Acute Malnutrition
20 MHA Ministry of Home Affairs
MoHFW Ministry of Health and Family Welfare
NRDWP National Rural Drinking Water Programme
PHCs Public Health Centres
PMGSY Pradhan Mantri Gram Sadak Yojana
PMJDY Pradhan Mantri Jan Dhan Yojana
PMJJBY Pradhan Mantri Jeevan Jyoti Bima Yojana
PMKVY Pradhan Mantri Kaushal Vikas Yojana
PMSBY Pradhan Mantri Suraksha Bima Yojana
PWDs Persons with Disabilities
RFD Results-Framework Document
RTE Right to Education Act
SAM Severe Acute Malnutrition
SAUBHAGYA Pradhan Mantri Sahaj Bijli Har Ghar Yojana
SDGs Sustainable Development Goals
SMCs School Management Committees
TBTuberculosis
UDISE Unified District Information System for Education
Aspirational Districts Program Introduction
On several counts, India can
be mistaken for a continent.
Most notably these include
the size of the land and
the diversity of her people.
Upon taking a closer look,
such characteristics become
evident in more granular
aspects as well. The vast
disparities in regional
development across Indian
states that stand at different
stages of economic and
social development is one
such glaring trend that
showcases its curious
heterogeneity.
The economic contribution
of the peninsular states
is higher than that of
hinterland states creating
a north-south divide. For
instance, the population of
Maharashtra is almost half
as that of Uttar Pradesh
but the size of its gross
domestic product (GDP) is
almost twice as much. The
gap is also widening over
time. The per capita income
of the richest five states,
which was 145 percent
higher than that of the
poorest five states at the
beginning of the millennium
has risen to over 400
percent in 2018-19.
1
These trends point to
the fallacy of looking at
development solely through
the lens of economic growth
and average statistical
barometers like GDP or
even per capita GDP. Such
averages hide the deep
inequities that are prevalent
in the Indian life. The realities
of one corner this continent-
sized nation and nation-
sized states are typically
very different from another
corner of the landmass.
1
Data retrieved from Ministry of Statistics and Programme Implementation
(MoSPI), Government of India. Aspirational Districts Program 2
The list of the 112 Aspirational Districts is
provided in the Appendix.
Clearly, India’s high growth over
the last few decades has been slow
to reach across all geographies.
In order to set this skewed
path of development aright, the
government has launched the
‘Transformation of Aspirational
Districts’ Programme across the
most backward districts of India
in January 2018. The programme
effectively aims to bring in
expeditious improvements in the
socio-economic status of 112
2
of
the most backward districts in the
country, including 35 Left Wing
Extremism (LWE) affected regions.
The idea has been to focus on the
regions that have faced challenges
in bettering socio-economic
outcomes and in narrowing the gap
on key development parameters
with the rest of the country. Once
the seeds of development are sown
in the least developed regions
of the country, the country itself
will witness rapid development
in a more inclusive manner. As
the COVID-19 pandemic ravages
across the world and its effects
are felt for decades to come on the
socio-economic well-being of the
people, the programme can help
to address the regional inequality
in development gains before they
exacerbate and become cemented
in time. NEED FOR THE PROGRAMME
The Transformation of
Aspirational Districts
programme is an effort to
take the conversation on
development beyond the
narrow domain of economic
advancement. Over the years,
countries have relied heavily
on traditional measures of
economic development like
the GDP to define success.
India’s development has also
been celebrated on being able
to drive its per capita income
numbers by almost four times
between 1988 and 2018.
However, India has not been
able to fully transform its
remarkable economic success
into social development.
According to Social Progress
Imperative, India’s rank
on Social Progress Index
remained constant from 2014
to 2018 at 103rd position with
a marginal increase of 2.1 in
its score. In 2019, India was
able to move up the ladder
by one rank. Similarly, if one
looks at HDI India was able to
improve its score from 0.640
to 0.647 in 2019. However,
when its discounted for
inequality HDI score falls by
26.3 percent to 0.477. This
fall is slightly higher than the
average loss due to inequality
in “Medium HDI Countries”.
On some social parameters,
India fares poorly compared
to its neighbours. The infant
mortality rate for India,
which stands at 37.9, is not
only higher than the world
average but also than its
low-income neighbors Nepal
and Bangladesh. A baby
born is India is nearly 1.2
times as likely to die during
the first year of life as one
born in Nepal. These social
challenges might hamper
India’s economic growth in
future as well. For instance, an
unhealthy workforce would
mean that the country is
less productive compared to
other nations. It is therefore
important that we focus
on social parameters along
with traditional measures of
progress.
Moving Beyond Economic
Measures of Success
The Transformation of Aspirational Districts programme is driven by the following ideas
that signal a shift in the approach of the government towards policy and governance:
24 Aspirational Districts Program
THEREFORE, EVEN THOUGH ECONOMIC MEASURES ARE USEFUL
GUIDES OF PROGRESS, THEY DO NOT ADEQUATELY REFLECT THE
QUALITY OF LIFE OF THE PEOPLE. THE TRANSFORMATION OF
ASPIRATIONAL DISTRICTS PROGRAMME MAKES AN ATTEMPT TO
ADDRESS THIS SHORTCOMING BY MONITORING PERFORMANCE
ON THE ESSENTIAL ELEMENTS THAT DEFINE A GOOD SOCIETY LIKE
HEALTH, EDUCATION, AND BASIC INFRASTRUCTURE. India is well known for its diversity.
It presents endless varieties of
physical features, cultural patterns,
religions, languages etc. However,
this diversity is not only limited to
the physical characteristics of the
country but is also highlighted in
the development parameters. For
instance, the maternal mortality
ratio is 46 per 1,00,000 live births in
Kerala vs 237 per 1,00,00 live births
in Assam
3
.
Figure 1:
District
Level Social
Progress
Index
26
Enabling Equitable Regional
Development
Measure Values
0100
3
Data retrieved from NITI Aayog, Government of India. Aspirational Districts Program
This disparity does not only exist
across states but percolates down
to the lowest level of geographies.
A recent Lancet study showed
that among the 723 districts of
India in 2017, the prevalence of
stunting ranged from 16.4 percent
to 62.8 percent, wasting ranged
from 5.5 percent to 30 percent,
and underweight children ranged
from 11 percent to 51 percent.
4
The district level social progress
index (presented in Figure 1) that
measures the performance of
districts across 12 facets of social
progress including healthcare,
education, personal rights etc clearly
highlights this disparity that exists
within Indian districts. The scores
range from 28.6 to 76.8 on a scale
of 0-100. Even states with high per
capita GDP such as Maharashtra
have some districts in the bottom
tier, implying that having a high GDP
doesn’t translate into high social
progress.
Therefore, if India must achieve
comprehensive social and human
development it has to ensure that
its most under-developed pockets
socially progress.
THE TRANSFORMATION OF ASPIRATIONAL DISTRICTS
PROGRAMME IS A SIGNIFICANT STEP TOWARDS
ADDRESSING THE REGIONAL DISPARITIES ACROSS THE
INDIAN LANDSCAPE.
4
Hemalatha, R., Pandey, A., Kinyoki, D., Ramji, S., Lodha, R., Kumar, G. A., ... & Laxmaiah, A. (2020).
Mapping of variations in child stunting, wasting and underweight within the states of India: The Global
Burden of Disease Study 2000–2017. EClinicalMedicine, 100317. 28
The Aspirational Districts
programme is a key governance
initiative that is being driven in
the spirit of driving development
changes through the spirit of
competitive federalism among
geographies. The states are the
main drivers of the programme
where they work with the central
government to identify and target
development goals for these
districts. The District Magistrates
are the pillars on which the
programme rests. The competition
among different districts motivates
them to outperform their peers and
also learn from in the process.
The objective of imbibing a spirit of
competitive federalism at all levels
of governance is to not just about
competition but also to work in
partnership with the least developed
regions of the country and help them
transform, which is encapsulated in
the idea of cooperative federalism.
The combination of competition and
cooperation across different levels of
geographies and governance fuels
the Transformation of Aspirational
Districts programme.
Driving Change through Cooperative
and Competitive Federalism
THE TRANSFORMATION OF ASPIRATIONAL DISTRICTS
PROGRAMME IS DRIVEN BY A SPIRIT OF COMPETITIVE
FEDERALISM TO ENCOURAGE DIFFERENT GEOGRAPHIES
TO WORK TOWARDS A COMMON GOAL OF
DEVELOPMENT Aspirational Districts Program
The Transformation of Aspirational
Districts Programme has been
running for over two years across
112 districts. Over this period,
the programme has generated
an impact at the ground level
on the set of socio-economic
parameters upon which it focuses.
The study is being undertaken
to develop an assessment of
these transformations. The broad
objectives of the study are to:
1. Conduct a holistic assessment
of the programme and the
performance of the districts in
improving the lives of citizens.
2. Assess whether the programme
has accelerated the socio-
economic development of these
districts in comparison to their
trends before the programme was
implemented.
3. Documentation of the institutional
best practices of the initiatives
taken by the districts to draw
learnings for the programme.
4. Analyse the vertical and
horizontal coordination
frameworks between government
bodies and the partners engaged
with the programme.
5. Develop actionable
recommendations to enable the
future transition roadmap for the
initiative and help India progress
towards its goals for social
development.
The study will give a sense of how
the aspirational districts have
performed under the programme
and what are the challenges and
opportunities it presents moving
forward. It will also provide learnings
for countries that intend to replicate
such interventions. Moreover, it can
also help the Indian government in
case the program is extended to
other districts.
MOTIVE OF THE STUDY:
ASSESSING THE IMPACT 30
UNDERSTANDING THE
ASPIRATIONAL
DISTRICTS
PROGRAMME (ADP)
01
ADP WAS IMPLEMENTED WITH A STRATEGY
TO RAPIDLY TRANSFORM DISTRICTS WITH
RELATIVELY LOW SOCIAL AND HUMAN
DEVELOPMENT TO BOOST THE OVERALL
HUMAN DEVELOPMENT OF THE COUNTRY. Aspirational Districts Program ADP ADP began with the selection of
the least developed districts in the
country. The selection of the districts
was based on a composite index
consisting of challenges faced by
the districts in terms of the poverty
of their citizens, relatively poor
health and nutritional outcomes,
educational status, and deficient
infrastructure
5
. Table 1.1 shows the
list of indicators and the weightages
used to calculate the index.
SELECTION OF THE DISTRICTS
5
Transformation of Aspirational Districts, A New India by 2022, Page 2
Landless
households
dependent on
Manual labour
(SECC D7)
Ante-natal
care (NHFS-4)
Institutional
delivery
(NHFS-4)
Stunting of
children below 5
years (NHFS-4)
Wasting
in children
below
5 years
(NHFS-4)
Elementary drop-
out rate (U-DISE
2015-16)
Adverse
pupil teacher
ratio (U-DISE
2015-16)
Un-electrified
households
(Ministry)
Households
without individual
toilets (Ministry)
Un-connected
PMGSY village
(Ministry)
Rural Household
without access to
water (Ministry)
25%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
7.5%
HEALTH
A
N
D
N
U
T
R
IT
IO
N
E
D
U
C
A
T
I
O
N
IN
F
R
A
S
T
R
U
C
T
U
R
E
D
E
P
R
I
V
A
T
I
O
N
Table 1.1.
Framework
Used for
Selection of
Aspirational
Districts
32 The results of the index were
analysed and after deliberations
with all the key stakeholders, it was
decided that at least one district
should be included from every state
keeping in line with the spirit of
competitive federalism. Initially, 117
districts from 27 states and 1 Union
Territory (J&K) were selected to be
a part of the programme. However,
five districts of West Bengal did not
join the programme and now the
programme comprises 112 districts
from 26 states and 1 Union Territory.
Aspirational Districts Program 34
The programme is based on
three core principles, which are
encapsulated in the 3Cs Approach
– Convergence (of Central and State
schemes), Collaboration (among
citizens and functionaries of Central
& State Governments including
district teams), and Competition
(among districts). The 3Cs are
themselves interconnected with
each other. The programme aims
to create a convergence between
the central and state government
schemes and initiatives directed
towards similar policy goals by,
first, improving collaboration
between the civil society and the
functionaries of the state and
central government, including the
Prabhari Officers and, second, by
developing a spirit of competition
among the districts using the
monitoring dashboard and the
monthly ranking system.
THE 3C
APPROACH
Create convergence among State and Central
Government initiatives at the district level to
overcome constraints
CONVERGENCE
COMPETITION
COLLABORATION
Promote competition among states and districts
using the “Champions of Change” monitoring
dashboard
This implies forging of cooperation between the
civil society and the functionaries of Central & State
Governments including district government bodies.) Aspirational Districts Program The programme is a collective
effort of the Central and State
governments; however, States
are the main drivers of change.
The States have either formed a
committee under their respective
Chief Secretaries or appointed a
nodal officer to implement as well
as to track the programme. At the
Central level, NITI Aayog is steering
the implementation of this initiative.
Additionally, individual Ministries
have assumed responsibilities to
drive the progress of the districts.
The structure of the programme is
classified further into:
1. For each district, a Central
Prabhari Officer of the rank
of Additional Secretary/ Joint
Secretary, and a similar State
Prabhari Officer at the level
of the State Government has
been nominated to create policy
convergence and promote
collaboration across all levels of
the government.
2. An Empowered Committee
which has been set up under the
chairmanship of the CEO, NITI
Aayog is expected to ensure
convergence in schemes and
address specific issues and
challenges that are raised by the
Prabhari Officers nominated for
each district.
The structure of the programme has
allowed for decentralisation that
has enabled local experimentation
in the selected districts based on a
firm appreciation of ground realities.
The local government institutions,
working in collaboration with the
Central and State government, are
in a position to ensure that different
measures are undertaken to bring
in socio-economic changes at
the ground level. And this greater
participation of the local and state
governments is an essential driver
of change in the ADP.
The structure of the programme is
reflective of cooperative federalism,
wherein the local, state and the
central governments are working
together to attain growth at a
micro-level. The idea being that the
programme aspires to harness the
uniqueness of each district in terms
of the strengths they possess as
well as the challenges they face to
enhance better human development
for its citizens through competition,
convergence, and collaboration.
BASIC STRUCTURE OF THE
PROGRAMME 36
ADP focuses on five main
themes – Health & Nutrition,
Education, Agriculture & Water
Resources, Financial Inclusion
& Skill Development, and Basic
Infrastructure. These five identified
thematic areas are further broken
down into 49 indicators. The
distribution of these indicators is
shown in Figure 1.1.
The reason why the programme
includes these particular themes is
that they directly impact the quality
of life as well as the economic
productivity of citizens. The salient
feature of this programme is that
NITI Aayog in collaboration with the
Planning Department, Government
of Andhra Pradesh has created an
accessible dashboard, where 81
data-points are tracked regularly.
THE PROGRAMME METRICS
Figure 1.1.
The Key
Focus Areas
of ADP
Aspirational Districts
Programme Focus Areas
ADP MONITORS 81 DATA
POINTS FOR 49 INDICATORS
Monitoring Indicators
30
10
30
55
20
Education
Basic
Infrastructure
Health &
Nutrition
Skill
Development
Financial
Inclusion
Agriculture
and Water
Resources
8 Indicators
14 Data Points
7 Indicators
8 Data Points
13 Indicators
31 Data Points
5 Indicators
10 Data Points
10 Indicators
12 Data Points
6 Indicators
6 Data Points Broadly, dashboards are expected
to display data integrated from
multiple sources and exhibit the
same in an easy-to-comprehend
manner. This allows any individual
to understand complex information
in less time than it would take to
read through an entire report. At
the same time, dashboards are
self-contained in explanation. For
example, in the context of ADP, the
dashboard tracks key indicators
with real-time visibility of how the
districts are performing and the
distance of them from their targets.
The districts have been responsible
for entering the data since April
1, 2018. It should be kept in mind
that districts only fill the data for
the indicators that are collected by
them locally. They play no role in
entering some indicators such as
the ones in Financial Inclusion.
Based upon their entry, they are ranked based on progress made
on a real-time basis. There are two types of ranking that emerge
from this database:
The dynamic system of ranking
acts as a tool that is enabling
the districts to identify indicator
specific challenges and help them
to immediately take corrective
measures. The entire process of
an incremental ranking system is
expected to inculcate a sense of
positive competition among the
districts in their endeavour to not
only become the best within their
state but also within the nation.
This is an endeavour to create
an atmosphere of competitive
federalism.
• DELTA-RANKING – WHICH CAPTURES THE CHANGE
IN DISTRICT RANKINGS OVER TIME AND ARE SHOWN
ON THE DASHBOARD AND ARE PUBLISHED AS
REGULAR REPORTS BY NITI AAYOG
• BASELINE RANKING – WHICH CAPTURES THE
DISTRICT PERFORMANCE COMPARED TO THE
BASELINE YEAR AND WAS PUBLISHED AS A
COMPREHENSIVE REPORT BY NITI AAYOG.
Aspirational Districts Program 38
Furthermore, the dashboard is
available to the public to monitor the
progress of the aspirational districts.
This is particularly important when we
view it from the point of accountability
as well as maintaining transparency
to the public. Such efforts have been a
highlight of the current administration
as exemplified in the implementation
of programmes like Direct Benefit
Transfer and Jan Dhan-Aadhar-Mobile
(JAM). The idea, which perpetuates
from the ADP dashboard initiative,
is that such platforms allow the
public to participate in the process
of governance, aside from ensuring
accountability and transparency.
Hence, the creation of the dashboard
to track the progress of the
programme as well as to disseminate
data grounded in evidence has been
an important step.
The uniqueness of the program is
reflected in two ways
7
1. The programme has effectively
managed to shift the focus from
outputs to outcomes, such as
evaluation of socio-economic
measures of malnutrition, skilling
and learning, among others. An
outcome-based evaluation is
expected to answer essential
questions such as, “What is the
extent to which the programme
has achieved its intended
result?”, “What difference did the
programme make?” and “How
did the participant benefit from
the programme?”. ADP provides
the opportunity to assess the
programme in terms of these
questions because they have
managed to disseminate data
effectively. This leaves scope for
impact evaluation to assume an
important role in the context of
ADP.
The monitoring of the data has
further provided an incentive to
government officials to deliver
results in a timely and expert
manner. Performance evaluation
of the programme is sure to
act as a motivation to the local
government officials to improve
their performances.
2. The programme has managed to
actively encourage collaborations
with international development
AT ITS CORE,ADP SEEMS TO HAVE PRIORITISED
PROMOTING A CULTURE OF PRODUCING RELIABLE
AND ACTIONABLE DATA POINTS AND ENSURING AN
INCREASE IN THE USE OF DATA TO CLOSELY MONITOR
THE PERFORMANCES OF THE DISTRICTS.
7
Hemalatha, R., Pandey, A., Kinyoki, D., Ramji, S., Lodha, R., Kumar, G. A., ... & Laxmaiah, A. (2020).
Mapping of variations in child stunting, wasting and underweight within the states of India: The Global
Burden of Disease Study 2000–2017. EClinicalMedicine, 100317. organisations and civil
society to create a better
impact. The knowledge
partner of NITI Aayog,
Bill and Melinda Gates
Foundation (BMGF)
in partnership with ID
Insights and Tata Trusts
has carried out three
rounds of household
surveys in all the
Aspirational Districts
beginning in June 2018
and covering more than
1,00,000 households.
These surveys were
used to validate 20
self-reported data-
points and estimate nine
further data-points for
which district-level data
is usually not readily
available at regular
intervals.
Each of these initiatives
has been a significant step
away from the existing state
of affairs in governance
today, or in other words, a
step away from the status
quo. The programme has
created an opportunity
to ensure sustained
institutional processes of
impact evaluation by easing
access to data and creating
the ability to accurately
measure the performance of
the programme. Therefore,
it is critical to carefully
document and to learn
from the experiences of this
programme. This report is an
attempt towards ensuring
the same.
Aspirational Districts Program 40
ADP, by design of its policy
framework, does not recognise
the development partner as an
external funder or an agency that
“supplements and complements”
the work of the government in
isolation. The development partner
is predominantly identified as
an external knowledge resource
integrated within the state
institutions to bridge critical gaps
in governance or citizen service
delivery that may arise owing to
niche and/or structural challenges
that are prominent in some of the
most under-developed regions
of the country. The partners are
expected to improve the quality of
governance at the grassroots and
also to augment the capacity of the
district administration to deliver
citizen services by overcoming any
structural challenges prevalent in
the district. This is achieved either
by creating capacity in personnel
(such as partner initiatives to
training government officials)
or by creating innovative policy
interventions in collaboration with
the district administration (such as
establishing community kitchens
to improve access to nutrition for
children in a predominantly tribal
district of Maharashtra).
LEVERAGING THE
PARTNER ECOSYSTEM
ADP Approach to Partner Ecosystem
UNLIKE TRADITIONAL PARTNER ENGAGEMENT
APPROACHES, THE GOVT HAS INTEGRATED PARTNERS
INTO THE ADP FRAMEWORK
Traditional Engagement of Development Partners
Government
Citizens
Development
Organisations+NGOs/
NPOs/Donor Agencies
Figure 1.2.
Aspirational
Districts
Programme
has been
able to
effectively
integrate the
development
partners
within the
institutional
rubric of the
government. Aspirational Districts Program In the initial phase, the perceived
role of development partners was
primarily restricted to the 3
rd
C of
the 3C model under ADP. They were
expected to collaborate with the
respective district administrators to
promote efficiency and innovation in
public service delivery systems, as
indicated by one of the stakeholders
interviewed within the scope of this
research.
The other critical role being played
by the partner ecosystem relates
to the aspect of data validation.
The data validation partners,
who conduct field surveys to
check the quality of reported data
under ADP, ensure performance
management and accountability,
which promotes “competition”
amongst districts. The aspect of
social audit of public policy or
other government programmes is
Under the Aspirational District
Programme, the development
organisations and NGOs/NPOs
have been embedded within the
institutional apparatus of the
government to:
1. Bridge the critical knowledge
and resource gaps to expand
the scale and scope of citizen
services through convergence
and collaboration;
2. To facilitate open performance
management by validating the
achieved social outcomes; and
3. Promote policy innovation at the
grassroots to overcome niche
challenges in districts that leads
to exclusion of citizens from
public services.
Partner Ecosystem under ADP
Government
Citizens
Development
Organisations+NGOs/
NPOs/Donor Agencies not a new phenomenon. However,
the integration of the validation
partner within the policy design
of a programme is a progressive
policy move that is seen within
this programme. Very few policies
or programmes show such an
integrated design feature.
Gradually, the assimilation of the
partner organisations within the
broader institutional framework of
the programme also enabled some
informal and organic connections to
develop between the administration
and the partners. For instance,
in the interviews conducted, one
partner revealed that the district
administration connected with their
young professionals to brainstorm
on issues that are not within the
direct scope of the organisation.
This indicated that the partner
ecosystem was also able to create
informal and organic knowledge
networks within the administration.
These knowledge networks
of young fellows or personnel
present within the office of
District Collectors (DCs) or District
Magistrates (DMs) enable them to
create innovative policy actions
to overcome niche challenges by
“convergence”. Effectively, the
partner ecosystem does not only
cater to 3
rd
C but all the 3Cs of this
programme. It drives collaboration.
The data validation partners help in
promoting competition. The informal
knowledge networks created
between the young professionals
of the partner ecosystem and the
district administration promotes
convergence to overcome niche
challenges wherever applicable.
Furthermore, the “new” knowledge
brought in by the partners allows
the district administration to expand
its capacity in areas that were
traditionally catered to by other
public institutions. For instance,
banking-related institutions
traditionally catered to financial
inclusion in any district as the DC/
DM Offices did not have experts
or line-officials to drive financial
inclusion. The Lead District Manager
(LDM) of the banks and some other
institutions providing relevant
microfinance services primarily
did this. However, under ADP,
several districts have partnered
with development partners
who have domain expertise in
microfinance services and financial
inclusion. This has enabled the
district administration to expand
its capacity in an area which was
traditionally not within their scope
but was crucial to their work as
most of the citizen services and
benefits are gradually coming
under the framework of Direct
Benefits Transfer (DBT) which
makes financial inclusion critical for
delivering citizen services.
To sum up, the partner ecosystem
under ADP considers development
partners or development
organisations as external
knowledge resources that help the
state to bridge critical gaps. Instead
42 of being outside the institutional
rubric of the state, this has emerged
as one of the very few programmes
where the development partners
have been integrated within the
district administration. This has led
to several development partners to
establish representatives working
in the office of the district and block
administration in an Aspirational
District. Instead of supplementing
and complementing the work of the
government, these organisations
are now actively enhancing the
impact of government policy by
improving governance and creating
state capacity at the grassroots.
Aspirational Districts Program LITERATURE REVIEW
IMPACT EVALUATION OF
PUBLIC PROGRAMMES
02LITERATURE REVIEW 8
Blomquist, John. 2003. Impact evaluation of social
programs: a policy perspective, Washington, DC:
World Bank. http://documents.worldbank.org/curated/
en/386851468140967391/Impact-evaluation-of-social-
programs-a-policy-perspective
WHAT ARE IMPACT
EVALUATIONS?
Impact evaluations measure the impact
of direct participation in a programme
or intervention
8
on its participants (for
instance, districts in case of ADP). The role
of an impact evaluation study is not only
limited to quantifying the programme’s
impact. The study moves on to explain
why they occurred (or did not), and the
policy implications that arise from the
evaluation. An impact evaluation does
more than merely detect programme
effects – it also examines the programme
process, reasons for observed outcomes,
and cost-effectiveness. The process of
a good impact evaluation, therefore,
helps to clarify the programme plans,
improving communication among partners,
and gathering the necessary feedback
needed to improve and be accountable for
programme effectiveness.LITERATURE REVIEW 46
The first and foremost objective of an impact evaluation
study is to understand the effect of the government
program and interventions.
Detect Program Effects
It also helps to clarify the program
plans, improving communication
among partners, and gather the
necessary feedback for improvement.
Examine the Program Process
A proper impact evaluation is
supposed to include not only the
quantitative estimates, of pragram
impacts, but also is expected to
explain why they occured, and the
policy implication that arise from
the evaluation
Evaluate the reason
for observed outcomes
The examination of cost helps in designing
future developement aimed at fostering
similiar outcomes of interest.
Evaluate cost-effectiveness
Figure 2.1:
Role of Impact
Evaluation Aspirational Districts Program THE FIRST
is accountability to ensure that the development
programmes or interventions lead to development
outcomes.
THE SECOND
that evaluation serves is learning. This mainly aims to
suggest an evidence base for choosing and designing
development interventions that are likely to be effective
in fostering similar outcomes of interest
9
.
However, there are undoubtedly
significant considerations to
be taken into account before
conducting an impact evaluation of
a particular programme
10
. The first
one involves selecting a specialised
evaluator, preferably someone
external to the government or any
other implementing agency. This
preference is to ensure objectivity
and independence. Additionally,
the World Bank mentions that
specialised skills and expertise are
necessary to conduct a quantitative
impact evaluation.
The second one involves selecting
an appropriate quantitative method
to estimate impacts. There are
two kinds of designs available
for the same – experimental and
non-experimental. Experimental
estimates compare the outcomes
of the participants with those that
arise from a randomly assigned
control group. The control group
is otherwise eligible for the
programme and similar to the
participants or the treatment
group but did not receive program
benefits. If we were to contextualise
this for ADP, it would imply taking
into consideration the districts
that have been selected under this
programme and comparing them
with a control group of districts who
are eligible but did not make it to
the programme. An experimental
design is usually preferred on
methodological grounds. This
IMPACT EVALUATION PRIMARILY
SERVES TWO PURPOSES.
9
Impact Evaluation of Development Interventions: A Practical Guide, H. White, David A. Raitzer, ADB, 2017
10
Blomquist, John. 2003, Impact evaluation of social programs: A policy perspective, Washington, World
Bank, http://documents.worldbank.org/curated/en/386851468140967391/Impact-evaluation-of-social-
programs-a-policy-perspective 48
minimises the effects of pre-existing
differences that exist between
the participants (or, the treatment
group), and the comparison group
that can be, otherwise, confounded
with the impacts of program
participation (or, selection bias). In
case a random assignment is not
being taken into consideration, it
may still be possible to estimate
impacts reliably using non-
experimental methods. Multivariate
regression models, matched-
comparison methods, double-
difference, and instrumental-
variables methods can attempt to
control statistically for sources of
selection bias.
Most recent impact evaluations in
developing countries have relied
upon non-experimental methods
due to cost constraints and
data availability considerations.
Therefore, it has become
increasingly crucial to integrate
qualitative methods and permit
a grounded analysis of the
underlying causes of outcomes.
They allow a deeper understanding
of the programme processes,
external conditions, and individual
behaviours. The methods are open-
ended, relying on semi-structured
interviews in an individual or group
setting and on the interviewer
observations.
The availability, as well as the
quality of the data, is the most
critical factor affecting the quality
of impact evaluations. New
surveys are frequently required to
retrieve substantial information on
programme participants, including
baseline and follow-up surveys. Aspirational Districts Program Governments around the world
introduce many programs and
interventions to address different
developmental challenges within
their countries. But, how do we
know that the programme is
working the way it was intended
to since its conception
11
? If the
interventions are not effective,
and even if they are, how can they
be improved upon to make them?
All of this has led to a growing
trend towards the better use of
impact evaluation to understand
and improve the practice of using
the same. Evaluating government
programs and interventions to
understand their impact and
developing the prerequisite
infrastructure to support a
sustained level of high-quality
evaluations should, therefore, be
a priority. The systematic use of
evaluation may lead to solving
of the problems posed by the
aforementioned questions and help
governments identify the challenges
and scopes of their programmes.
IN GENERAL, AN IMPACT EVALUATION SEEKS TO ASK QUESTIONS AROUND THE
FOLLOWING:
1. Implementation: Are the activities of the
programme put into place as originally
intended?
2. Effectiveness: Is the programme
attaining the goals and objectives that it
was intended to accomplish?
3. Efficiency: Are the activities of the
programme being produced with optimal
use of resources, which include budget
as well as staff-time?
4. Cost-Effectiveness: Is the benefit of
attaining the goals and objectives of the
programme significantly higher than the
cost of producing the same?
5. Attribution: Can the success of
achieving the goals and objectives be
related to the programme, or assigned to
other interventions that are in place at
the same time?
All of these questions are asked to
document programme progress,
demonstrating accountability to
funders, policymakers and the civil
society or identifying ways to make
the programme better. It can also
depict how those outcomes differ
among different populations and
what factors are responsible for
those outcomes.
11
“Recommended Framework for Program Evaluation in Public Health Practice,” B. Milstein, Scott Wetterhall,
and the CDC Evaluation Working Group.
ROLE OF IMPACT EVALUATION IN
PUBLIC PROGRAMMES: 50
Performance measurement is an approach that
incorporates the monitoring and showcasing of
accomplishments under a particular programme,
with respect to the progress toward pre-
established goals
12
. The role of performance
measurement is to provide a descriptive picture
of the “participants” under a given programme
and their intermediate outcomes. However,
this process does not draw any causal links
pertaining to the findings/outcomes. Performance
measurement is followed with a non-
experimental design to assess the impact of the
programme in the following sections.
METHODOLOGYMETHODOLOGY
ASSESSING THE ASPIRATIONAL
DISTRICTS PROGRAMME
03
19
Executive Office of the PresidentCouncil of Economic
Advisers. (2014). Economic Report of the President (2014). Aspirational Districts Program Performance measurement, as a concept, in
most of the developed nations is attached
with budgetary procedures. However, in
both developed and developing economies,
it has been gaining ground in the domain
of public policy. There are three key
reasons why such a measurement has
become essential for comprehensive public
management
13
:
• To efficiently utilise limited
resources,
• To improve the decision-
making process and to
reduce the information
asymmetry across various
levels of administration; and
• To promote accountability
and transparency. METHODOLOGY
13
Delorme, P., & Chatelain, O. (2011). Policy Steering-The Role
and Use of Performance Measurement Indicators. Aid Deliv.
Methods Program. 52
Indian policymaking has also
adopted such performance
measuring procedures to accurately
assess the progress of programmes
while maintaining transparency
across various tiers of stakeholders.
In 2014-15 the Performance
Management Division under the
Cabinet Secretariat issued the
notice to prepare a department-
level Results-Framework Document
(RFD)
14
. This document served two
key purposes. The first purpose was
to shift the focus of all departments
from process-orientation to result-
orientation. Second, to provide an
objective and fair basis to appraise
a department’s overall performance
at the end of the year.
Similar policies were also observed
across other lower-rungs of
policymaking. For instance, a
Citizens’ Report Cards (CRC) was
introduced by many Municipal
Councils and Ward Committees
to measure the satisfaction of
the concerned public group with
the performance of the service
providers
15
. CRC led to an open
discussion on service provision
and the limitations attached to
it. This helped the policymakers
to visualise the objectives and
targets to address such challenges.
It also acted as a good public
accountability mechanism
16
.
IN THIS STUDY, WE
UTILISE THE “DISTANCE
TO FRONTIER” (DTF)
ANALYSIS TO CAPTURE
THE PERFORMANCE OF
DISTRICTS UNDER THE
ASPIRATIONAL DISTRICTS
PROGRAMME.
Given the real-time updated data
available through the Aspirational
Districts dashboard and the targets
set by districts at the beginning
of the programme, Performance
Measurement can shed light on the
progress of the programme.
14
Guidelines for Results-Framework Document (RFD) 2014-2015
15
Nallathiga, R. (2007). Performance Measurement as a Tool for Public Accountability: A Review of
Experiments with the Report Cards in Indian Cities. Indian Journal of Public Administration, 53(1),
1-20.
16
ibid. Aspirational Districts Program The distance implies the current
position of an Aspirational District
vis-à-vis its benchmark or the best
performing district in the respective
State. There are two ways
prescribed under the Champions
of Change Dashboard that
successfully tracks the Distance to
Frontier for Aspirational Districts:
BENCHMARK TARGETS
These targets intend to maximise the growth potential
under each indicator for Aspirational Districts.
Generally, the highest possible target for districts is
100% (i.e. completion of the desired objective under an
indicator).
BEST IN STATE
The dashboard, along with depicting the district level
data, also presents the annual scores for the best
performing district within a particular state for each
indicator. The objective of such scores is to create
competition at the State, District, and even the block
level.
The Distance to Frontier (DTF) is measured at the district level for all the
six sectors of the Aspirational Districts Programme. For district-level
assessment, the average scores are deducted from the Benchmark Targets
assigned for each district.
Distance to Frontier = Benchmark Target – Average Score
id
Where, i represents the indicator and d represents the district.
If the difference is zero, then the districts have achieved their respective
benchmark. In other words, when the difference is zero, it means that the
districts have achieved saturation in that particular indicator/sector with
respect to these pre-determined targets. If the difference is positive, the
districts are lagging in their targets and if the difference is negative, it
implies that districts have overachieved. The Distance to Frontier analysis shows how far are the districts from
their set target. This is illustrated in the figure below for the indicator
percentage of schools with separate toilet for girls. The indicator value
for a district can lie anywhere between 0-100 (since it is in percentage
terms).
0
Current Value
for the district
Target for the
District*
100
70
(Minimum Value
Possible)
Target – Current Value shows the “Distance to Frontier”In this case, 100-70=30. The district is 30 percent away from achieving its target.
PERCENTAGE OF SCHOOLS WITH SEPARATE TOILET FOR GIRLS
54 Distance to Frontier can take three possible values: positive, negative
and zero. The box below represents the meaning of the three values by
using the indicator: Transition rate from upper primary to secondary
TRANSITION RATE FROM UPPER PRIMARY TO SECONDARY
03090100
(Minimum Value Possible)
Value for District X
(Target ValuePossible)
Value for District Z
Value for District Y
Distance to Frontier for District X: 90-30= 60. Implying that it is 60 units away from the target.
Distance to Frontier for District Y: 90-90= 0.
Implying that it has achieved the target.
Distance to Frontier for District Z: 90-100= -10.
Implying that has over achieved the target by 10 units.
Aspirational Districts Program 56
Based on the DTF analysis, districts
are divided into four tiers using
quartiles. This helps in identifying
the leaders and laggards across
various sectors. In this study, state-
level representation in the different
quartiles/tiers is emphasised upon
as this gives a better understanding
of stronger policy convergence and
collaboration in closing the gap with
the benchmark targets.
The DTF analysis provides static
analysis of the districts in terms of
measuring their progress vis-à-vis
the targets. While the results from
the analysis are meaningful for
drawing policy recommendations by
looking at the areas where districts
are lagging, they do not provide any
insights about the improvements
that the districts have made.
Therefore, to understand the
improvements made across all the
sectors in terms of progress, it is
crucial to pick out two comparable
time points. For this study, two
specific points have been taken. The
first-time point is the baseline value
from the year 2018 (presented
under the column “Data As on
31/03/2018” in the Champions of
Change Dashboard). The second
time point comes from the quarterly
average for the calendar year 2019.
The DTF is calculated for these two-
time points and districts are divided
in Tiers for both the periods.
THE RESULTS ARE
PRESENTED IN THE FORM
OF A “MOBILITY MATRIX”.
It goes beyond the DTF analysis by
taking into account the progress of
the districts over time. While DTF is
a static representation of the district
performance, the mobility matrix
represents their dynamic movement. Aspirational Districts Program • The more the districts will be
shifting from lower tiers to
upper tiers between Timepoint
1 (baseline) and Time Point 2
(average for 2019); the better
the improvement that has been
observed in that particular pillar.
• The green portion in the figure
signifies positive movement of
districts from lower to higher
tiers over the tested period of
time.
• The portion in red will show the
number of districts that have
shown regressive movement
with time across tiers.
• The grey cells show a lack of
movement across tiers.
• Each cell will carry the number
of districts.
HOW TO READ THE MOBILITY
MATRIX?
Time Point 2
Time Point 1
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4 58
RESULTS
04
The Health and Nutrition sector
covers indicators related to
maternal care such as provision
of antenatal care, availability
of supplementary nutrition
under the Integrated Child
Development Services (ICDS)
programme etc.; aspects of
childcare such as presence
of Severe Acute Malnutrition
(SAM); availability of healthcare
infrastructure such as First
Referral Units, anganwadis
with buildings, etc. and health
outcomes such as sex ratio. RESULTS
HEALTH AND NUTRITION Aspirational Districts Program RESULTS In the DTF analysis,
Health and
Nutrition have
delivered some
impressive results
as around 10%
of districts have
managed to meet
their respective
benchmark targets.
This sets the right
precedence for the
rest of the districts
as health is one of
the most important
sectors under
the programme
and commands
30% weightage.
Hence closing the
gap with their
benchmark targets
would reflect in the
districts’ enhanced
monthly scores and
rankings. 60
The mean distance between the
frontier targets and the average
achievement of the districts in 2019 is
only 10.23 percentage points across
the sector. This is the lowest average
gap across the sectors between the
targets and the achievements making
Health & Nutrition probably the best
performing sector within the ambit of
the programme.
Districts such as Dahod (Gujarat),
Baramulla (Jammu and Kashmir),
Gadchiroli (Maharashtra), Raichur
(Karnataka), Bijapur (Karnataka),
Bastar (Chhattisgarh), Yadgir
(Karnataka) have been able to
exceed their set targets. Bastar,
Chattisgarh has been offering free
health check-ups, free medicine, and
free nutritious food and counselling
of malnourished children under the
‘Suposhit Bastar Abiyaan’. The first
health and wellness centre was
launched in Bijapur, Chattisgarh,
and was inaugurated by the Prime
Minister. Since then, 15000 health
and wellness centres have been
launched to facilitate comprehensive
healthcare. These initiatives based on
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
How to read the figure?
Figure 4.1:
Distance
to Frontier
Analysis:
Health and
Nutrition
Y.S.R
-5
0
5
10
15
20
25
30
Mohasamund
Visakhapatnam
Average
Achievement of Tragets
Sheikhpura
Firozpur
Jaisalmer
Kandharnal
KaraputMoga
Karauli
Dholpur
West District
Virudhunagar
Ramanathapuram
Chandauli
Bhoopalapalli (Warangal)
Bhadradri-Kothagudern
Asifbad (Adilbad)
Haridwar
Shrawasti
Balrampur
Chamba
Ranchi
Giridih
Gumla
Bokaro
KupwaraDumko
Osmanabad
Godchiroli
Barwani
Ribhoi
Kiphire
Mamit
Wayanad
Nandurbar
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu & Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Vidisha
Guna
Khandwa (East Nimar)
Washim
Damoh
Bastar
Barpeta
Darrang
Jamui
Namsai
Khagaria
Udalguri
Banka
Mewat
Korba
Kotihar
Yadgir
Raichur
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
Tier 1 Tier 2 Tier 3 Tier 4 Aspirational Districts Program Figure 4.2:
Mobility
Matrix for
Health and
Nutrition
data driven policies help in bringing
significant change in the remote
areas.
Andhra Pradesh (3 Aspirational
Districts), Gujarat (2 Aspirational
Districts), Jammu and Kashmir (2
Aspirational Districts), Karnataka
(2 Aspirational Districts) and Sikkim
(1 Aspirational District) have 100%
representation in the first tier implying
that districts have either achieved the
targets or are close to achieving it.
This depicts a holistic improvement in
their health-related statistics.
Kiphire (Nagaland), Ribhoi
(Meghalaya), Mewat (Haryana),
Banka (Bihar), Udalguri (Assam)
are the bottom five districts.
Districts of Bihar and some of the
North-East States mainly form the
bottom tier. States that have 100%
representation in the bottom tier (4th
quartile) include Manipur, Meghalaya,
Mizoram, Nagaland and Arunachal
Pradesh. Therefore, there is a long
way to go for them to meet their
benchmark targets. On the other
hand, Assam has districts in Tier I,
Tier III as well as Tier IV. The bottom
tier districts of Assam as well as
other North-East states can draw
learnings from Hailakandi (the top
tier district in Assam). It has been
innovative in addressing the nutrition
concerns, promoting biodiversity, as
well as securing education through
the awareness campaign. The
practice involves gifting 5 saplings
(coconut, litchi, assam lemon, guava,
amla) to the parents of a new born
girl child. The rationale being that
the fruit from the trees can be used
to feed the child, which would help
in building immunity and warding off
malnutrition. The sale of the produce
could also be invested in educating
the child.
The mobility matrix shows that most
of the districts (71 percent i.e. 20 out
of 28) that were in the first tier during
the baseline have retained their
position while 29 percent of them slid
down to Tier 2. Similarly, 17 out of 28
districts in the bottom tier maintained
their position while 10 of them moved
up one tier.
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
20800
27109
61282
0110 17 Most of the changes have been
observed within the second and
the third tier. Two districts namely,
Adilabad and Darrang moved down
from Tier 2 to Tier 4. Both of them
have moved away from achieving
their targets and thus require
immediate attention. On the other
hand, Kupwara and Sheikhpura
showed remarkable change in their
health scenario and moved two tiers
up.
In a nutshell, the results help us
in identifying the districts that are
close to achieving their targets
and also highlight how the bottom
tier districts can draw learning
from them. These results can
also be utilised by the partners to
identify the districts that require
engagements in the health
domain. The table below shows
the districts requiring interventions
categorisation on the basis of scope
and scale of partners.
These improvements in healthcare
outcomes are crucial as ill-health
harms productivity and adversely
effects human capital. It also
impacts the job prospects of people
and their lifetime earnings. To
understand the repercussions, the
study will analyse the economic
impact arising from the diminishing
rates of Severe Acute Malnutrition
amongst children aged between 6
months and 6 years.
Figure 4.3:
Future
Engagements
in Health and
Nutrition
62
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Kiphire Rajgarh Hazaribagh Chhatarpur
Ribhoi Nandurbar Garhwa Khunti
Mewat Balrampur Latehar Purbi Singhbhum
Banka Begusarai Guna West District
Araria Wayanad Katihar Sheikhpura Aspirational Districts Program SAM is a critical indicator to evaluate
the wellbeing of a child. Improving
maternal health and decreasing child
mortality are heavily linked with the
rates of malnutrition. Malnutrition is
responsible directly or indirectly for
35% of deaths among the children
aged 5 or below
17
.
Therefore, ADP through its strict
monitoring and evaluation nudges
the districts to bring down the rates
of both Severe Acute Malnutrition
(SAM) and Moderate Acute
Malnutrition (MAM). As per the WHO
guidelines, SAM is defined by very
low weight for height (subject to
prescribed median and standard
deviation) of a child below the age of
5 years.
India has shown a high prevalence
of SAM and surprisingly, the
National Family Health Survey-4
reported a higher rate of severe
wasting (7.5%) compared to its
previous iteration (6.4%)
18
. Such
a significant rate of malnutrition
amongst children has prompted a
large number of studies that have
tried to evaluate sample sizes across
the nation. Studies from states such
as Uttar Pradesh
19
and Bihar
20
have
shown significantly higher rates of
severe wasting amongst children.
Thus, the role of ADP becomes
bigger than ever in addressing these
challenges. While malnutrition can
have fatal implications, it also leads
to arrested mental and physical
growth in the long run, which
diminishes the overall productivity
of the concerned person. Given
SAM accounts for malnutrition
amongst children aged between 6
months and 6 years; a quicker and
efficient intervention could easily
help in reducing these rates. WHO
guidelines have also highlighted
that the case-fatality rates for SAM
can be reduced by 55% in hospital
settings and other community
measures such as provisioning of
ready-to-use therapeutic foods
21
can
also bring down these rates.
Indicator: Percentage of Severe
Acute Malnutrition
17
www.who.int/nutrition/topics/malnutrition/en/
18
IIPS, I. (2015). National Family Health Survey (NFHS-4).
19
Singh, K., Badgaiyan, N., Ranjan, A., Dixit, H. O., Kaushik, A., Kushwaha, K. P., & Aguayo, V. M. (2014).
Management of children with severe acute malnutrition: experience of Nutrition Rehabilitation Centers in
Uttar Pradesh, India. Indian pediatrics, 51(1), 21-25.
20
Burza, S., Mahajan, R., Marino, E., Sunyoto, T., Shandilya, C., Tabrez, M., ... & Mishra, K. N. (2015).
Community-based management of severe acute malnutrition in India: new evidence from Bihar. The
American journal of clinical nutrition, 101(4), 847-859.
21
Briend, A., Akomo, P., Bahwere, P., De Pee, S., Dibari, F., Golden, M. H., ... & Ryan, K. (2015). Developing
food supplements for moderately malnourished children: lessons learned from ready-to-use therapeutic
foods. Food and nutrition bulletin, 36(1_suppl1), S53-S58. Although no ‘Benchmark Target’
has been prescribed under the
Champions of Change dashboard, it
is quite clear that the districts would
aim to reduce the malnutrition rates
(both SAM & MAM) down to 0 per
cent.
To accurately assess the performance
of the districts, indicator values for
the year 2019 were compared with
their respective baseline values. In the
last calendar year, i.e. from January
2019 to December 2019, around
58% of the districts have managed to
reduce the SAM rate significantly.
The above graph shows the long and tremendous leap these districts have taken in reducing the SAM rates since their baseline values were recorded.
Impact Measured Across
Aspirational Districts
Improvement in reducing SAM (%) for 2019
Figure 4.4:
Top ten
districts with
the most
improvement
in SAM in
2019
ARARIA, A DISTRICT FROM BIHAR
BEING THE OBVIOUS LEADER IN
REDUCING SAM HAS RECORDED AN
IMPRESSIVE 68% CHANGE WHEN
COMPARED TO ITS CORRESPONDING
BASELINE FIGURE.
64
Chhatarpur
Chandauli
Guna
Rajgarh
Namsai
Pashchimi Singh bhum
Darrang
Sheikhpura
Asifabad (Adilabad)
Araria
0 10 20 30 40 50 60 However, it is a major concern that
states such as Rajasthan, Punjab
& Uttarakhand have zero districts
that have shown any positive
change. Since their baseline values
were recorded, all the districts
in these states have regressed
during the concerned period. Thus,
a holistic approach is required in
such a case, where the Anganwadi
Centres (responsible for recoding
the information and supplying
the appropriate nutrients),
district government and the state
government need to focus on
successful policy convergence and
collaboration.
The subnational-level analysis shows that many states with two or more
Aspirational Districts have recorded significant positive changes since their
baseline position.
have a healthy representation for Aspirational Districts with this positive
change.
8070
6366.67
Chhattisgarh
Andhra Pradesh
Odisha
Jharkhand
Aspirational Districts Program 66
To measure the economic impact,
it was crucial to consider the long-
term implications of SAM on children.
As mentioned above, malnutrition of
any form has long-lasting effects on
mental and physical well-being that
ultimately reduces the productivity
levels of an individual. The objective
of this impact evaluation is to
measure the lifetime economic gains
that can be made by averting any
kind of disability or death pertaining
to malnutrition.
While it is difficult to assign any
particular value for gain in lifetime
economic gains owing to lower
malnutrition, policymakers across
the world go for the “rule of thumb”.
This rule is based on valuations of
health investment made by nations
under specific income categories
22,23
.
Therefore, for lower-income nations
generally, value is quoted to be
$1000/Death-Adjusted Life Year
(DALY) and for middle to higher-
income nations it close to $5000/
DALY
24
. Therefore, the potential
economic gains that can be made
by reducing the rates of SAM are
always going to be massive which
incorporates its long-term benefits.
Another crucial factor that has been
taken into account is for the loss of
productivity. According to a Lancet
study from India, malnutrition has
a strong influence in reducing the
productivity of an individual. The
study suggested that a person could
lose approximately 17.3 years of
his healthy life due to long-term
implications of malnutrition
25
. Hence,
the economic impact that has
been computed also measures the
prevented loss in the healthy life of
an individual.
The overall economic impact for
all the states comes out to be a
mammoth 1.43 Lakh crores. This
is the impact that ensures that not
only there is a significant fall in the
SAM rates but it also leads towards
healthy and productive lifetime
earnings. The possible number of
beneficiaries for such an impact was
1.2 crore children enrolled in the
Anganwadi Centres across the 112
districts.
Illustrative Economic Impact
through Health and Nutrition
22
Mill, A. and S. Shillcut, 2004. Communicable Disease. In B. Lomborg (ed.) Global
crises, global solutions. Cambridge University Press, Cambridge.
23
Stokley, N., 2004. Expert Comments. In Bjorn Lomborg (ed.) Global crises, global
solutions. Cambridge University Press, Cambridge.
24
Horton, S., Alderman, H., & Rivera, J. A. (2008). The challenge of hunger and malnutrition. Copenhagen
Consensus, 3-4.
25
Swaminathan, S., Hemalatha, R., Pandey, A., Kassebaum, N. J., Laxmaiah, A., Longvah, T., ... & Gupta, S.
S. (2019). The burden of child and maternal malnutrition and trends in its indicators in the states of India:
the Global Burden of Disease Study 1990–2017. The Lancet Child & Adolescent Health, 3(12), 855-870. Aspirational Districts Program Apart from the obvious reason
of percentage of prevailing SAM,
other factors could influence the
overall impact values for the States/
Districts:
• Number of Aspirational Districts:
As seen above, those states
that have more Aspirational
Districts would tend to enjoy
more cumulated economic gains.
Thus, states such as Bihar (13
districts), Madhya Pradesh (8),
UP (8) have such high numbers.
Yet, there are states such as
Haryana, Manipur, Tripura and
Arunachal Pradesh that have
one Aspirational District each but
also have managed to oversee
a sizable reduction in SAM rates
along with strong potential
economic gains.
• However, it was observed that
Rajasthan is an exception. The
state has 5 districts yet all of
them regressed in terms of the
prevalence of SAM since its
baseline values were recorded.
This means that even if the state
has more districts, its cumulative
impact will be lower than those
with fewer districts and those
with lower prevailing SAM rates.
• Number of Children enrolled
in an Anganwadi Centre: This
indicator targets children aged
between 6 months and 6 years,
which is a big pool of possible
beneficiaries. As a result, the
base for computing economic
impact favours those states that
have more children enrolled in
Anganwadi Centres. However,
one interesting case can be
observed in Maharashtra,
where it has the fourth-highest
average number of children
enrolled under the Anganwadi
centres. Yet, due to its regressing
SAM rates since the baseline
period, the state has witnessed
a potential economic loss.
Thus, this factor only positively
influences those cases where
SAM cases have been low.
Figure 4.5:
State Wise
Impact
Total Potential
Savings..
-7,756 65,669 68
The overall economic gain arising
from lowering the SAM rates is
so high that it should be a signal
for all the stakeholders. Better
coordination between Anganwadi,
district and state-level stakeholders
could not only prevent fatality
amongst children but could
potentially pave the way for them to
lead a healthy and productive life.
As far as lifetime earnings are
concerned, the above figure is
only computed for the progress
made by the districts in the year
2019 and how it compares with
their baseline values. However,
for better and even more accurate
valuation, longitudinal studies are
required which could further shed
light on the nature of education
received, training acquired, and
the professional route taken by the
beneficiaries. This could reform
the way stakeholders can plan the
social development of an individual
by positively influencing their
lifetime earnings. Aspirational Districts Program The education sector focuses on
learning outcomes (transition rate
from primary to upper primary,
and subsequently to secondary
schooling, average scores in
mathematics and languages and
so on) as well as infrastructural
(toilet access for girls, electricity
supply, drinking water, etc.) and
institutional indicators (pupil-
teacher ratio, timely delivery of
textbooks, etc.). Considering the
importance of education in enabling
development, it commands a
weightage of 30 percent – similar to
that of health.
Unlike health, none of the districts
have managed to achieve their
set targets on an average in the
education sector. All of the Tier
1 districts, however, were merely
5 to 10 percent away from their
respective targets over the last
year. The States of Andhra Pradesh,
Himachal Pradesh, Punjab, Sikkim,
and Tamil Nadu have all of their
districts in the top tier.
EDUCATION
How to read the figure?
Figure 4.6:
Distance
to Frontier
Analysis:
Education
0
5
10
15
20
25
35
30
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu & Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Y.S.R
Rajnandgaon
ViziangaranBegusarai
Uttar Bastar Kanker
Dahod
Jaisalmer
Rayagada
Kalahandi
Malakangiri
Moga
Dahal
West District
Ramanathapuram
Virudhunagar
Udham Singh Nagar
Chitrakoot
Bhadradri-Kothagudern
Asifbad (Adilbad)
Haridwar
Shrawasti
Bahraich
Latehar Chandel
Pakur
Yadgir
Baramula
Singrauli
Chhatarpur
Dhenkanal
Barwani
Ribhoi
Kiphire
Mamit
Wayanad
Nandurbar
Vidisha
Guna
Balangir
Washim
Damoh
Bastar
Namsal
Katihar
Sukma
Banka
Sitamarhi
Sahibganj
Lohardaga
Mewat
Goalpara
Darrang
Muzaffarpur
Average
Achievement of Tragets
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 70
The districts in this tier have
been undertaking some unique
interventions to improve education
among the children. Rajnandgaon
in Chattisgarh has ensured access
to sanitation facilities for every
girl child, for which toilets were
installed in schools. This helped
in reducing the drop-out rate
of girls enrolled in government
schools. Similarly, in Dantewada,
Chattisgarh, the government
schools adopted ICT models to
boost the quality of education.
Meanwhile, in Baran, Rajasthan,
volunteer generation campaign was
organised to strengthen student-
learning outcomes in schools, and a
capacity building workshop for 617
volunteers was conducted.
Banka in Bihar has launched a
programme, ‘Unnayan Banka
– Reinventing Education using
Technology’, which is an effort to
leverage technology to improve the
learning environment. The Prime
Minister has even presented an
award to the district administration
for the initiative. In another instance
in Sharavasti, Uttar Pradesh,
School Management Committees
were formed in 1289 schools
for a tenure of 2 years. These
SMCs with collaboration from
Education Department make school
development plans and look after
building capacity.
One of the striking features of this
sector is the intra-state outliers
that emerge across some of the
states. For instance, Sahibganj
district in Jharkhand appears to be
significantly lagging as compared to
the rest of the districts in the State
when it comes to performance in
the domain of education. Similarly,
Sukma districts in Chhattisgarh is
the only district in the state that
appears to be in the bottom tier
while all the other districts are in
the top 3 tiers of the sector. Ribhoi
in Meghalaya appears to lag behind
even when compared to other
districts in the North East and
may need critical partner support
moving forward.
On average, across all aspirational districts, the DTF on education remains
at 15 percent. Evidently, the distribution of districts in the bottom tier is
more spread out when compared to the top three tiers.
But it must be noted that some of the districts that lie in this tier and
are, thus, farthest from achieving their targets have been putting in
considerable efforts to climb up the ladder.
STATES LIKE BIHAR, ODISHA, TELANGANA, MANIPUR,
MEGHALAYA, AND NAGALAND HAVE SUBSTANTIAL
VISIBILITY IN THE BOTTOM TIER. Aspirational Districts Program However, five districts – Garhwa
(Jharkhand), Hailakandi (Assam),
Kupwara (Jammu & Kashmir),
Rajgarh (Madhya Pradesh), and
Singrauli (Madhya Pradesh) – have
moved from the bottom-most tier
in the baseline year to Tier-2 over
the last year. A unique initiative
undertaken by Singrauli to bring
about such progress over this time
was a four week-long attendance
campaign, which resulted in a 10%
increase in student attendance
across three clusters.
The analysis presented here shows
how the aspirational districts have
performed with respect to education
and the outcome seems mixed. It
shows that there remains immense
scope for further intervention on
this front. None of the districts
have been able to achieve their
targets but appear to be on course
to achieve/ mostly achieve them by
2022. Partner interventions in this
sector can again be guided by the
logic of converging scale and scope
of the partner engagements and the
needs of the district as highlighted
in the DTF analysis. Their preferred
engagements depending on the
scope, scale, and the agenda of the
respective partner organisation can
be chosen from Table X, which is
mapped to the bottom five districts
from each Tier.
While the DTF analysis delineates
the static position of the districts
based on their averages across
the last year, the mobility matrix
highlights the movement of districts
across tiers over time. Surprisingly,
more districts (32 over 26)
have slipped to lower tiers
with time on the education
parameter than have
improved during the same
period.
Figure 4.7:
Mobility
Matrix:
Education
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
20710
36811
510 121
05716 72
Figure 4.8:
Future
Engagements
in Education
FOCUSED INTERVENTIONS WITH HIGHER DEGREES OF
INTENSITY ARE REQUIRED IN THE NORTH EASTERN
PART OF THE COUNTRY OWING TO ITS SPECIFIC
NICHE CHALLENGES. EVEN WITHIN STATES THAT ARE
PERFORMING RELATIVELY WELL, DISTRICTS THAT
ARE LAGGING BEHIND BY SOME DISTANCE SHOULD
BE GIVEN EXTRA ATTENTION TO ENSURE THAT NO
DICHOTOMIES EMERGE IN THE OVERALL PERFORMANCE
OF THE STATE UNDER THE PROGRAMME.
Some of these districts, as seen
in the case of Health & Nutrition,
do face niche challenges ranging
from a lack of school infrastructure
to extremist violence, which
may impede the functioning of
educational institutions in these
regions reflecting the relatively
poorer performance compared to
other districts in the same state.
Digital tools, especially mobile-
based solutions, could emerge as
possible measures of bridging the
gap between isolated districts and
the rest of the state.
Therefore, education remains a
sector that can be a focal point
of higher engagement by all
stakeholders in the programme
given its scope for improvement and
its vitality for development.
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Ribhoi MewatBastar Vizianagaram
Asifabad
(Adilabad)
Namsai Bijapur Ramgarh
Sahibganj Pakur Nandurbar Sirohi
Bhadradri-
Kothagudem
WayanadGiridih Washim
Sitamarhi Dumka NuapadaBaran Aspirational Districts Program The Financial Inclusion domain covers
the availability of bank accounts
through government schemes such
as Pradhan Mantri Jan Dhan Yojana
(PMJDY); pension beneficiaries through
Atal Pension Yojana; and affordable
and easy access to financial loans
disbursements through Mudra. It is an
important area of this programme as
indicators under this sector ensure the
self-dependence of the beneficiaries.
Having a bank account and enjoying
social safety nets such as insurance
and pension are crucial factors for
the subsistence of normal life and
thus protects the beneficiaries from
potential risks.
In the DTF analysis, it is evident that
the potential for improvement remains
high despite the best efforts of the
government over the last few years.
The district closest to the target i.e.
Mahasamund from Chhattisgarh is 42
percent away from achieving the goals
set for the financial inclusion sector
while the farthest away is Ribhoi from
Meghalaya that is 87 percent away.
This range (42-87 percent) within
which all the districts fall reflects India
still has to put in a lot of effort to climb
the financial inclusion ladder.
FINANCIAL INCLUSION
How to read the figure?
Figure 4.9:
Distance
to Frontier
Analysis:
Financial
Inclusion
Rajnandgaon
Narayanpur
Viziangaran
Dahod
JaisalmerMalakangiri
Naupada
Moga
West District
Udham Singh Nagar
Siddharthanagar
Haridwar
Bahraich
Dahal
Chandel
Yadgir
Singrauli
Chhatarpur
Sitamarhi
Dhenkanal
RibhoiKiphire
Mamit
Namsal
Sukma
Baksa
Mewat
Dhubri
Simdega
Visakhapatnam
Kupwara
Baramula
NarmadaChamba
Wayanad
0
40
30
20
10
50
60
70
90
80
Andhra
Pradesh
Arunachal
Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya
Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal
Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu &
Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Average
Achievement of Tragets
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 74
The two states that have shown
encouraging performance relative to
other regions are Andhra Pradesh
and Chhattisgarh. In Andhra
Pradesh, two out of three districts
are in the top tier while the third one
is in Tier II. In Chhattisgarh, nine out
of ten are in the first tier.
The results also clearly depict
disparities within states. States
such as Odisha, Rajasthan,
Chhattisgarh, Madhya Pradesh
have representation in almost
all tiers. For instance, Dhenkanal
(Odisha) is in Tier I with 50 percent
distance from the target while in
Malkangiri (Odisha) the distance
between the target and the current
value is 74 percent. Moreover, there
are no states in this sector that
have achieved 100% representation
in the top tier.
The trend is similar to the Health
and Education sectors where one
can see the North Eastern states
lag in comparison to the rest of the
country. Topographic challenges
and lack of quality internet
connectivity have emerged as two
main constraints in driving financial
inclusion in the North East. Tripura
has emerged as the only state in the
North East to have its district in the
top 2 tiers of the cohort.
The Mobility Matrix shows the
majority of the districts in the first
tier have remained in the same tier
for 2019 as well. In the second tier,
Yadgir (Karnataka) has worsened
its performance and moved to Tier
IV in 2019. During the baseline data
collection, it was 58 percent away
from achieving its target while in
2019 it is 71 percent away. While
21 out of 28 districts retain their
position in the bottom tier, two
districts, namely Nuapada (Odisha)
and Bhadradri-Kothagudem
(Telangana) have made a major
improvement to jump to the top tier
for the year 2019.
Figure 4.10:
Mobility
Matrix:
Financial
Inclusion
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
20810
06166
61471
25521 Aspirational Districts Program However, there are a lot of steps being
taken by the districts currently that
can help them in providing access
to financial services to their citizens.
Sonbhadra in Uttar Pradesh organised
Financial Literacy camps which
resulted in 650 enrolments for PMJDY
and other Social Security Schemes
such as PMSBY, PMJJBY and APY from
46 villages in the district. Another
step comes from Gajapati, Odisha.
The district is tribal-dominated and
was devastated by the cyclone Titli
in October 2018. What started as
challenges in transferring direct
benefits to beneficiaries in remote
places due to lack of bank branches,
laid the foundation for opening mini
banks under Odisha Livelihood
Mission. To facilitate this, an MoU was
signed with the State Bank of India
and Utkal Grameen Bank. The banks
opened mini banks in panchayats
that did not have banking facilities.
These mini banks also functioned
as common service centres. Quick
enough, 15 banks started functioning
in the district, and bank accounts of
27,463 SHG members were opened,
while 23000 were linked with Adhere.
However, the results show that
these steps are not enough, and the
government will have put in a lot of
other steps for enhancing the financial
services in these regions.
The fact that there is only one partner
– Microsave – that is currently working
in the domain of Financial Inclusion,
shows there is immense potential for
partners to engage with the districts
in this particular sector. Before the
engagement of the development
partner Microsave India, the district
administration had no nodal officer
in the domain of financial inclusion.
This often meant that the district
administration was heavily dependent
on external banking and micro-
finance institutions to drive financial
inclusion and access to the credit in
the districts. Under the framework of
ADP, Microsave India along with NITI
Aayog has been able to place District
Financial Inclusion Coordinators (DFIC)
at the designated districts driving the
agenda of financial inclusion from
within the district administration.
Figure 4.11:
Future
Engagements
in Financial
Inclusion
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Ribhoi Baramula Aurangabad Khunti
Kiphire
Gajapati Sirohi Pakur
Baksa Dhaulpur Jamui Sahibganj
Dhubri Kandhamal Rayagada Wayanad
Chandel Osmanabad Purbi Singhbhum Nuapada It was crucial to incorporate data
points assessing the state of
agriculture and water resources
because the sector forms a critical
aspect of development, especially
among the aspirational districts.
It has a weightage of 20 percent
and focuses on output (yield, price
realisation, etc.), inputs (soil health
cards, quality seed distribution,
etc.), and institutional support (crop
insurance, animal vaccination,
electronic markets, etc.).
Agriculture is a sector where the
districts are the farthest away from
the set targets so much so that it is
difficult to draw a clear distinction
between leaders and laggards. This
is also driven by the fact that the
elements of its indicators have a
longer time frame for improvement.
The results show that there is
immense scope for improvement as
the average distance from frontier
is 80 percent. The potential gains
from interventions in this sector are
exceedingly high.
AGRICULTURE AND WATER RESOURCES
How to read the figure?
Figure 4.12:
Distance
to Frontier
Analysis:
Agriculture
and Water
Resources
76
Aurangabad
Y.S.R
Muzaffarpur
Viziangaran
Fatehpur
Yadgir
Kiphire
Dhaulpur
Osmanabad
Gadchiroli
Sheikhpura
Sahibganj
Ribhoi
Mamit
Dhalal
Namsai
Bokaro
Gaya
Mewat
Washim
Barwani
Visakhapatnam
Kupwara
Baramula
Narmada
Chamba
Wayanad
Average
Dhenkanal
Kalahandi
Balangir
Gajapati
Bhoopapalapalli(Warangal)
Ramanathapuram
Asifabad (Adilabad)
Bhadradri-Kothagudem
Dakshin Bastar Dantewada
Haridwar
Baran
0
40
30
20
10
50
60
70
90
80
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu & Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Achievement of Tragets
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 Unlike most sectors, the tier-1
districts in agriculture are the most
spread out as seen in Figure 4.12.
Andhra Pradesh and Kerala are
the only states that have all of
their aspirational districts in the
top-most tier. On the other hand,
Punjab and Himachal Pradesh are
states that have all of their districts
in the lowest tier. However,
considering the distance of all
districts from the frontier, there is
immense scope for improvement
across all tiers.
Kupwara in Jammu and Kashmir, which is one of the districts
in the top tier introduced high density farming to improve
agricultural productivity and make optimum utilisation of
resources. The traditional seedling-based orchards were
converted into high density orchards. This gave the producers
success in cultivation of crops such as apples and walnuts and
increased the harvest by up to three times. Such efforts by
districts can substantially improve the state of agriculture and
water resources across aspirational districts.
Aspirational Districts Program 78
Another notable story comes from
the district Virudhunagar, Tamil
Nadu. The farmers in Virudhunagar
have adopted cost-effective water
harvesting techniques such as
micro irrigation, drip irrigation,
water trenches, and reservoirs,
thereby overcoming water
deficiency. This was in response
to the Prime Minister’s call of ‘Per
Drop More Crop’. Innovation has
brought to the district concepts like
‘Apni Mandi’ where the farmers
come and sell their produce directly
to the consumers. The farmers
have also embraced processing of
harvest such as drying agricultural
produce using solar energy, and
poly-house cultivation. These have
enabled the farmers to have a
stable income.
Meanwhile, the mobility matrix
of the sector shows that there
has been considerable movement
across tiers over time. In fact,
among all sectors, the agriculture
and water resources sector has
recorded the most changes in the
position of the districts across tiers.
Figure 4.13 shows
42 DISTRICTS THAT
HAVE SEEN AN UPWARD
MOVEMENT AND HAVE
BEEN ABLE TO GET
CLOSER TO THEIR
TARGETS AT A FASTER
RATE THAN THEIR PEERS.
On the other hand, 40 districts
have either moved further away
from their targets than they
were during the baseline period
(2018) or have recorded smaller
improvements compared to other
Aspirational Districts.
Figure 4.13:
Mobility
Matrix:
Agriculture
and Water
Resources
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
8686
51166
7777
8479 Aspirational Districts Program Bihar and Assam have used
targeted measures for the
conservation of environment.
Goalpara, Assam has taken an
exemplary step by using green
technologies for construction of
all-weather roads. And in Bihar
the ‘green army’ of school students
were encouraged to judiciously use
water resources.
In conclusion, it can be said that
there remains immense scope for
improvement on this front. The
partners can choose to intervene
to improve the state of agriculture
and water resources in aspirational
districts to reap the maximum
developmental gains. Based on
their level of engagements and
choice of region, the possible
locations for investment are
depicted in Figure 4.14.
THE 8 DISTRICTS THAT MOVED FROM
TIER IV TO TIER I BELONG TO BIHAR,
ASSAM AND CHHATTISGARH.
Figure 4.14:
Future
Engagements
in Agriculture
and Water
Resources
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Kiphire Balrampur Kondagaon Rajnandgaon
Barpeta Malkangiri Karauli Bijapur
Dakshin Bastar
Dantewada
Sirohi Dhubri Giridih
Firozpur Koraput West District Mahasamund
Purnia Ramgarh
Khandwa (East
Nimar)
Kalahandi 80
Approximately 70 million additional
individuals of working age (15-59
years) are expected to enter the
country’s labour force by 2023 and
by the same estimation model, it is
also predicted that the total workforce
will include approximately 404.15
million people
26
. The rising workforce
in India and the low employability of
the current population
27
requires the
country to focus on improving the skill
set of its population. The government
has launched a lot of programmes in
this domain such as Pradhan Mantri
Kaushal Vikas Yojana (PMKVY) that
aim to not only provide relevant skills to
the workforce but also help them with
employment opportunities.
A note of caution needs to be added for
the data related to skill development.
The programme only captures skill
formation but does not effectively
track employment or improvement in
earnings. This can be improved within
the programme moving forward.
The DTF analysis results shows that
skill development is a unique sector as
it has clear leaders at both district and
state-levels. However, it is difficult to
pick laggards as the average scores
in the third and fourth quartile have
limited divergence.
SKILL DEVELOPMENT
Figure 4.15:
Distance
to Frontier
(DTF): Skill
Development
How to read the figure?
26
The 3
challenges to skill
development in
India and how to
tackle them, WEF
(2019)
27
India Skills
Report, CII (2019)
Average
0
40
30
20
10
50
60
70
90
80
Andhra
Pradesh
Arunachal
Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya
Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal
Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu &
Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Achievement of Tragets
Khagarta
Y.S.R
Darrang
Virudhunagar
Chitrakoot
Yadgir
Raichur
Kiphire
Dhaulpur
Osmanabad
Malkangiri
Mahasamund
Hazaribagh
Garhwa
Ribhoi
Mamit
Sirohi
Namsai
Bokaro
Latehar
Godda
Begusarai
Mewat
Singrauli
Baran
Visakhapatnam
Kupwara
Udaiguri
Purnia
NawadaBaksa
Baramula
Narmada
Banka
Sitamarhi
Chamba
Dahod
Wayanad
Dhenkanal
Kalahandi
Kandhamal
Nandurbar
Chhatarpur
Gadchiroli
Ramgarh
Bhoopapalapalli(Warangal)
Bhadradri-Kothagudem
Sukma
Nabarangapur
Asifabad (Adilabad)
Haridwar
Distance to Frontier: How far are you from your target?0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 Aspirational Districts Program Karnataka and Sikkim are the
best performing states with 100%
representation in the 1st quartile.
While Bihar, Jharkhand, Madhya
Pradesh, Tamil Nadu and Odisha are
the states in which the performance
of some districts is commendable.
Giridh and Ramgarh, two districts
from Jharkhand have even achieved
saturation in this sector with an
impressive average score.
The bottom quartile is mainly formed
by some districts of Chhattisgarh
– Sukma, Bijapur, Bastar, Korba,
Kondagoan; two districts from
Bihar – Sitamarhi and Banka; two
districts from Jharkhand- Gumla and
Garwa; all the Aspirational districts
from Arunachal Pradesh, Jammu
and Kashmir, Manipur, Meghalaya,
Mizoram, Gujarat and Nagaland.
It is observed from the Mobility
Matrix that similar to Agriculture
and Natural Resource sector, Skill
Development has also witnessed
drastic changes in the position
of districts within the two time
periods. 50 districts have seen an
upward movement and have been
able to get closer to their targets
at a faster rate than their peers.
One of the districts – Gajapati that
moved from Tier IV to Tier II had
started enrolment of people for skill
development under Deen Dayal
Upadhyaya Grameen Kaushalya
Yojana (DDU-GKY) after the Titli
cyclone hit the district. As a result
of the efforts, 11,600 candidates
were mobilised, and over 450 were
trained in different crafts. Some of
the candidates have got placements,
which reflect the effectiveness of the
initiative.
On the other hand, 45 districts have
either moved further away from
Figure 4.16:
Mobility
Matrix: Skill
Development
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
410 122
76510
9838
82108 their targets than they were during
the baseline period (2018) or have
recorded smaller improvements
compared to other Aspirational
Districts.
In terms of partner engagement,
even though the programme
encourages skilling of Persons with
Disabilities (PWDs), there are no
partners currently engaged in this
domain. The district administration
could take steps to reach out to
partners to bridge critical gaps in
skilling PWDs. It would enhance
and support the districts to not
only achieve the targets stipulated
under the programme but also allow
districts to positively impact the
socio-economic welfare of PWDs
in some of the most challenging
geographies of the country.
82 In skill development programmes it
is not only important to look at the
skills imparted by the government
under these programmes but is
also critical to study whether these
skills have enabled people to obtain
new jobs and how these new job
opportunities have impacted their
income. In this study we analyse
the indicator “Number of certified
youth employed/ number of youths
trained under short-term and long-
term training”. This is arguably
the most important indicator as it
evaluates the final performance of
the training programmes. The higher
the possibility of employability of the
candidates, the better the training
programmes are.
The competitive labour and job
markets have made it even more
difficult for individuals to find
their preferred option of jobs/
career options. As a result, skill
development becomes a viable
option that could help in addressing
these problems.
India has been riddled by the
problem of “Skill and Job Mismatch”.
This means that India faces a dual
challenge where:
• The workers suffer from skill-
deficit, which leaves them
unemployed.
• The workers might be over-
skilled and with limited suitable
jobs available
Figure 4.17:
Future
Engagements
in Skill
Development
Illustrative Economic Impact
through Skill Development
Indicator: “Number of certified youth employed/ number of
youths trained under short-term and long-term training”
Aspirational Districts Program
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Kiphire Dhubri Vidisha West District
NarmadaPakurGunaKatihar
Sukma Purbi Singhbhum Nawada Muzaffarpur
Baramula
Bhadradri-Ko-
thagudem
Jamui Raichur
GumlaBarpeta MogaSirohi 84
In such a case, those who are over-
skilled reach for those jobs, which
need lower levels of education or skill.
This leads to overcrowding for the
already limited number of jobs and
further reduces the chances for those
workers who are untrained/unskilled.
Skill development, thus, can address
at least half of the abovementioned
challenges.
ADP has compiled a comprehensive
list of indicators that could monitor
the progress made by the districts
to train the workers. By monitoring
the rate of skilled candidates, each
district can produce a pool of workers
that will be prepared for future-
oriented jobs.
Recent efforts by the Government
have ensured that a wide variety of
training programmes are available
that would help in skilling the young
members of the workforce. Especially,
Pradhan Mantri Kaushal Vikas Yojana
(PMKVY) has been a major guiding
force in creating an emerging batch of
the workforce that would be prepared
for the challenges that the labour
market could throw in the future.
There are definite economic
benefits attached to the skilling of
the workforce. It has been noted
that employment post-training
programmes often lead to a significant
jump in the wage and hence, positions
the beneficiaries in an advantageous
situation in the labour market. This
has been backed by a recent World
Bank Study, which shows that
the acquisition of new skills could
potentially boost income by 21 per
cent and training programmes can
spur the employment rate for women
more than men
28
.
For impact evaluation, the increase
in income will be computed for three
months of employment, going by the
assumption that the candidates will
be employed for a minimum of 66
working days
29
. For monthly income,
we refer to the most updated monthly
per capita income for India in Rupees
30
.
Impact Measured Across
the Aspirational Districts
Assumptions and
Methodology
28
economictimes.indiatimes.com/news/economy/policy/skill-development-programmes-can-boost-
income-by-21-but-not-all-of-them-beneficial-world-bank/articleshow/48106307.cms?from=mdr
29
One working month= 22 working days
30
www.business-standard.com/article/economy-policy/india-s-per-capita-income-rises-6-8-to-rs-11-
254-a-month-in-fy20-120010701269_1.html Aspirational Districts Program The results of the analysis show
a positive result. Ten districts
covering around 45,000 candidates
have already managed to achieve
saturation, thus showing the rapid
pace that progress could be made for
this indicator.
The above graph represents the
potential economic gains made by
seven out of the aforementioned
ten districts (data for those districts
with 1000+ candidates). Successful
implementation of relevant central
skill development schemes has
ensured that candidates in these
districts will not only be employed
but will also find themselves in an
advantageous position as compared
to other workers who might be either
unskilled or semi-skilled.
At the other end, there could be
two major reasons, as to why
districts are not able to maximise
the economic gains arising from skill
development. First, districts have
been unable to make any progress
under this indicator during 2019. This
is evident from Namsai’s (Arunachal
Pradesh) and Kiphire’s (Nagaland)
performance, as both have achieved
0 as their annual average. The
second reason could be attributed
to the fact that there are not many
candidates that either avail or have
been enrolled under specific skill
development schemes. This is notable
for two districts Sheikhpura (Bihar)
and Malkangiri (Odisha). Both these
districts have achieved 100 per cent
success under the given indicator;
however, both also have less than
100 candidates available to train. As
a result, while the implementation
has been strong in this case, due to
the beneficiary base being small, the
overall economic gains also fall short.
Analysis
Figure 4.18: Potential Economic Gains due to Skill Development in INR Crores Aurangabad
Virudhunagar
Bokaro
Jamui
Muzzaffarpur
Hardwar
Darrang
0 2 4 6 8 10 12 86
Skill development is an interesting
sector under the ADP. It is probably
one of the few components that
not only can monitor an individual’s
skills, but can also trace the trends
that exist in the present-day labour
and job markets. More priority
could be given to those training
programmes that command a
higher share of labour demand
and similarly, help in revising those
programmes that are on their way to
redundancy.
This study is a basic economic
impact for trained candidates in
the Aspirational Districts. While
some common factors have been
incorporated to simplify the analysis;
there is a massive scope to study the
longitudinal impacts arising from this
sector. Subject to data availability,
the analysis can be broken down
into specific schemes, which will lay
out district-level trends. Furthermore,
the progress of the previous
batch of candidates can help in
tracing back the success of the
programmes at the disaggregated
level, which would better prepare
the stakeholders in formulating the
training course for future batches.
Looking
Forward Aspirational Districts Program Since basic infrastructure is the
minimum necessary condition
that needs to be satisfied to
enable development, it was crucial
to incorporate indicators that
provide a sense of infrastructural
conditions. These include availability
of individual household latrines,
drinking water, electricity, and
road connectivity. The districts
are also tracked for the number of
Gram Panchayats connected to
the internet, and panchayats with
Common Service Centres.
Apart from health and nutrition,
basic infrastructure is the only
sector where there are multiple
cases of saturation and with the
average scores skewing towards the
benchmark point.
BASIC INFRASTRUCTURE
THE STATES OF GUJARAT AND KERALA EMERGE AS THE
TOP-PERFORMING STATES WITH A 100% REPRESENTATION
IN THE TOP TIER. THEY ARE CLOSELY FOLLOWED BY
MADHYA PRADESH (5 OUT OF 8).
CURRENTLY, 6 DISTRICTS
HAVE MET OR EXCEEDED
THEIR PROGRAMME
TARGETS AS OF 2019.
KHANDWA (MADHYA
PRADESH) HAS
EMERGED AS THE BEST
PERFORMER AND BIJAPUR,
CHHATTISGARH IS
FARTHEST FROM ACHIEVING
ITS PROGRAMME TARGETS. 88
It is encouraging to see the first
quartile formed by a mix of states,
geographically and economically,
representing that districts in most of
the states have made considerable
improvements. In fact, on the whole
the districts are 20 percent away
from their targets on an average.
Meanwhile, Telangana and the North
East states (except Assam) have full
representation in Tier 4, the bottom
tier. The aspirational districts in
these states need focused attention
under basic infrastructure.
Figure 4.19:
Distance
to Frontier:
Basic
Infrastructure
How to read the figure?
One reason for districts exceeding, achieving, or nearly achieving
their targets in the Basic Infrastructure sector stems from the fact
that some of the indicators – such as Individual Household Latrines
(IHHL) and household electrification – were driven by mission mode
schemes such as Swachcha Bharat and SAUBHAGYA.
0
40
30
20
10
50
60
70
-10
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chhatisgarh
Gujrat
Haryana
Madhya Pradesh
Odisha
Jharkhand
Meghalaya
Sikkim
Tripura
Himachal Pradesh
Maharashtra
Punjab
Karnataka
Mizoram
Tamilnadu
Uttar Pradesh
Jammu & Kashmir
Manipur
Rajasthan
Kerela
Nagaland
Telangana
Uttarakhand
Achievement of Tragets
Hailakandi
Begusarai
Kondagaon
Rajnandgaon
Darrang
Virudhunagar
Yadgir
Kiphire
Sirohi
Osmanabad
Chhatarpur
Simdega
Chandel
Ribhoi
MamitNamsai
Washim
Bastar
Mewat
Singrauli
Nandurbar
Vidisha
Barwani
Visakhapatnam
VizianagaramKupwara
Ramgarh
Khunti
Raichur
Wayanad
Katihar
Dhubri
Araria
Banka
Barpeta
Bijapur
Chamba
Baramula
Palamu
Sonbhadra
Chandauli
Dhalal
Kalahandi
Firozpur
Gadchiroli
Khandwa (East Nimar)
Sheikhpura
Uttar Bastar Kanker
Ramanathapuram
Udham Singh Nagar
Bhadradri-Kothagudem
Nabarangapur
Asifabad (Adilabad)
Haridwar
Average
Distance to Frontier: How far are you from your target?
0: Achieved ; Positive: Further away; Negative: Over achieved
The dark green colour represents Tier I districts i.e. the districts that have either achieved their target (with zero value or
negative) or are close to achieving it (0.5 percent away from the target).
The light green colour represents Tier II districts that mostly lie in the range of 5-10 percent, depicting that they are only
5-10 percent away from their target and a small intervention can help. Most of these districts be in Jharkhand, Odisha and
Rajasthan. The yellow colour represents the Tier III districts that are 11-15 percent away from their target.
The red colour represents Tier IV districts that are 15-30 percent away from their set goals. They require immediate
attention by the government.
Tier 1 Tier 2 Tier 3 Tier 4 Aspirational Districts Program Among the districts in the top tier,
in Kupwara, Jammu and Kashmir,
a network of 176 water-harvesting
tanks was strengthened. It has
yielded double benefit, as it also
aided in enhancing farmers income
through water conservation.
In Dahod districts of Gujarat,
a hundred households across
five villages benefitted from the
installation of solar powered
community tube wells. The initiative
was led by the Collector, Dahod,
and helped in facilitating the
availability of water at low cost for
drinking as well as for irrigational
purposes.
Since districts in a lot of states
have achieved saturation in this
sector, the Mobility Matrix shows
considerable shift in the position of
districts within tiers as expected. It
can be seen in Figure 4.20 that two
districts have fallen from the first
tier in the baseline to the bottom tier
in the latest year. These are Chatra
in Jharkhand and Khagaria in Bihar.
On the other hand, four districts
from two states have climbed from
the bottom tier in the baseline to
Tier 2 in the latest year. These
include Baksa (Assam), Dhubri
(Assam), Giridih (Jharkhand), and
Latehar (Jharkhand).
The dominant presence of partners
in basic infrastructure is in the
domain of potable drinking water
with Piramal Water, being the
partner engaged in supporting the
initiative. Sanitation has emerged
as another area of engagement by
partners across geographies.
This therefore leaves immense
scope for other partners to
engage in this domain to support
different kinds of infrastructure
requirements – such as internet
connectivity for rural panchayats
– which form an essential part of
this sector.
Figure 4.20:
Mobility
Matrix: Basic
Infrastructure
Data for 2019
Baseline data
Tier 1
Tier 1 Tier 2 Tier 3 Tier 4
Tier 3
Tier 2
Tier 4
14842
4410 10
101251
04915 90
Figure 4.21:
Future
Engagements
in Basic
Infrastructure
Even though the partners are
actively engaged across the
aspirational districts in this sector,
Figure 4.21 shows the areas where
further interventions can be made
based on specific requirements.
To measure socioeconomic impact,
two indicators namely in-house toilet
construction and delivery of potable
water have been selected. The
objective here is to assess the role
of water-availability and sanitation
in improving the overall health of
the beneficiaries. Previous studies
have shown that sanitation and
water are two of the key non-health
factors that have a strong influence
in determining the healthy lifestyle
of an individual
31
. Inadequate water
and sanitation have strong adverse
effects on a healthy life such as:
• Premature mortality: Poor
sanitation has had a direct
impact on lost lives, especially
those of children. India shares
some of the highest-burden of
disease caused by diarrhoea,
which has led to a massive loss
of DALYs in children under 5
years
32
.
Illustrative Economic Impact
through Basic Infrastructure
31
Sanctuary, Mark & Tropp, Hakan. (2004). Making Water a Part of Economic Development: The
Economic Benefits of Improved Water Management and Services.
32
hgamapserver.who.int/gho/interactive_charts/phe/wsh_mbd/atlas.html
Very High Intensity
Engagements
High Intensity
Engagements
Moderate Intensity
Engagements
Low Intensity
Engagements
Bijapur Kalahandi Latehar Muzaffarpur
Kiphire Baramula Bahraich Kondagaon
Bhadradri-Ko-
thagudem
Garhwa Dhubri
Udham Singh
Nagar
Narayanpur DumkaSirohi Virudhunagar
Sukma Chandauli Gumla Kupwara Aspirational Districts Program • Additional Costs: Lack of
infrastructure to support water
and sanitation provisions often
lead to higher healthcare costs
for individuals. The cumulative
effect of such costs incurred
also hurts the national economic
prospect as it was reported in
2016, that poor sanitation cost
India about 5.2% of its GDP
33
.
• Productivity losses: This refers to
the productive time lost due to
illness and mortality. Productivity
loss also includes productive time
lost to look after the ill by the
caregivers.
Thus, the following analysis intends
to measure the savings made by
the Aspirational Districts under
each state by preventing loss of
healthy lives through successful
implementation of relevant central
schemes. These central schemes
include Swachh Bharat Mission
(Gramin) and National Rural Drinking
Water Programme (NRDWP).
Prevention of the loss of healthy
lives is key for any governing body.
Hence, curbing the cumulative
DALYs must be a priority for the
local governing bodies. From a
policymaking point of view, it is
crucial to understand DALYs as
34
:
• It highlights the aid required
for setting health service (both
curative and preventive) priorities
and further, establishing health
research priorities.
• It supports categorising
disadvantaged groups and
targeting of necessary health
interventions.
• Delivers a comparable measure
of intervention-based output.
Plenty of studies in the past have
highlighted the importance of
reducing the loss of healthy lives by
ensuring the consistent provision of
water and by implementing simple
sanitary measures. Preservation
of healthy lives in a defined region
raises the productivity levels, which
in turn boosts the economic potential
that can be derived from that same
region
35
. Hence, the same discourse
could be replicated in the ADP. This
could be attained by monitoring the
progress made by the districts in
terms of the annual rate of in-house
toilet construction and delivery of
potable water.
33
LIXIL, WaterAid, Oxford Economics. (2016). The True Cost of Poor Sanitation.
34
Murray, C. J. (1994). Quantifying the burden of disease: the technical basis for disability-adjusted life
years. Bulletin of the World health Organization, 72(3), 429.
35
Cylus, J., Permanand, G., & Smith, P. C. (2018). Making the economic case for investing in health
systems: What is the evidence that health systems advance economic and fiscal objectives? 92
Under the Swachh Bharat Mission
(Gramin), construction of household
latrines has been a crucial
component. Construction of in-house
toilets is one of the first steps taken
under this mission to undertake
intensive behaviour change across
the grassroots level.
The mission has also underlined
the urgent need for such a drastic
behavioural change as the costs
incurred due to poor sanitation
are huge and have long-lasting
consequences on public health,
environment and the economy:
Impact on Public Health: For this
study, major emphasis will be given
to the impact of poor sanitation on
public health. Open and untreated
human excreta can often interact
with food through soil, water and
crops. This creates a dangerous
chain of the faecal-oral route. And
according to a study conducted by
the UNICEF, one gram of faeces
can contain 10,000,000 viruses,
1,000,000 bacteria, 1,000 parasite
cysts and 100 parasite eggs
36
.
Furthermore, poor sanitation leaves
children under the age of five highly
susceptible to dangerous diseases
due to their relatively weaker
immunity. As mentioned before,
under-5 child mortality based on
diarrheal cases has crossed 1.9
million in developing nations
37
.
Role of the Mission and
Aspirational Districts: Thus, as
a part of Swachh Bharat Mission,
one of the major objectives was
to break the oral-faecal route by
constructing toilets across all the
rural households. This would be
supported by other policy measures
such as
38
:
• Encouraging communities and
Panchayati Raj institutions
to adopt other sustainable
sanitation practices.
• Developing community-
managed solid and liquid waste
management systems.
Indicator: Percentage of households with
Individual Household Latrines (IHHL)
36
UNICEF. (2000). Sanitation for All: Promoting dignity and human rights.
37
Vijaya Shankari, A., Kalpana, S., & Srinivas, G. (2019). Diarrhoeal Disease Among Under Five Children
in India: A Brief Review. University Journal of Medicine and Medical Specialities, 5(4).
38
www.prsindia.org/theprsblog/swachh-bharat-mission-gramin Aspirational Districts Program IHHL does create an induced impact
in terms of fall in diarrhoeal cases
39
.
This has been observed in India
as well where the most vulnerable
demographic group, i.e. 0-4 years;
have seen a consistent decline in
the cases for deaths arising from
diarrhoeal diseases. Thus, IHHL
has certainly played a major part in
curbing these deaths across India
with other factors such as public
awareness programmes, delivery
of safe drinking water and strict
tracking of progress made under the
Swachh Bharat Mission (both rural
and urban).
And the results witnessed under the mission have been impressive. All the
states have managed to achieve a 100% IHHL.
(Source: Swachh Bharat Mission)
(Source: Global Health Observatory Data, World Health Organization)
39
UNICEF. (2018). Evidence Review Potential Impact of Sanitation on Health and Wellbeing. Final Report.
Figure 4.22. Coverage Status of IHHL across all States
Figure 4.23.
Number of
deaths due
to Diarrhoeal
diseases (0-4
Years) in India
(2013-17)
20132014201520162017
20,000
0
40,000
60,000
80,000
10,0000
12,0000
14,0000
124175
112854
106367
98197
91270
Oct-14
38.7
50.84
64.91
84.18
98.28
100
0
20
40
60
80
100
120
2015-2016 2016-2017 2017-2018 2018-2019 2019-2020 94
Thus, over the last few years, there has been
a consistent fall in diarrhoeal related death
cases amongst children as the Swachh
Bharat Mission accomplished its objective of
100% IHHL in all the states. While National-
level impact evaluation of the Mission is a
must to understand the overall economic
benefits; this study would like to present the
situation at a disaggregated level through
Aspirational Districts.
According to a study conducted by the World
Bank
40
; successful policy interventions can
bring in drastic socio-economic benefits in
terms of costs per DALY saved. This includes
hygiene behaviour change, which accounts
for a savings of 26.42 USD
41
per DALY. IHHL
falls under the ambit of Hygiene behaviour
change as prescribed under the Swachh
Bharat Mission. Thus, by assessing the rate
at which the toilet has been constructed, a
fair assessment can be made both at the
state and the district levels to measure the
potential socio-economic savings.
Savings on DALY is a crucial component of
socio-economic savings. DALY includes the
unit of time lost due to disability or premature
mortality. And at the national level, it has
been witnessed that the diarrhoeal related
death cases are falling. Hence, it is fair to
expect that more individuals will get the
opportunity to live a healthy life, free from
any insanitary-related disability or even
premature death. This should translate into a
more productive life where eventually these
individuals will be able to contribute to the
economy owing to their good health.
40
Lvovsky, K. (2001). Health and environment (Vol. 1). World
Bank, Environment Department.
41
The value has been inflation-adjusted for the year 2019 (i.e.
the year of impact analysis) Aspirational Districts Program 96
According to the Champions
of Change Dashboard, most of
the Aspirational Districts have
tremendously managed to achieve
100% IHHL as early as December
2018. And by the end of the year
2019, all the districts have now
accomplished the same objective.
The above ten districts have ensured
maximum difference between their
current scores and their respective
baseline scores. This shows the
rapid progress that has taken place
in just a year. Interestingly, seven
out of ten districts here are from
Bihar, thus highlighting a strong
case for possible policy collaboration
between the state and the district
level stakeholders.
Following Bihar’s example, a state-
level analysis presents an interesting
picture.
Potential Economic Savings from IHHL: Findings
Figure 4.24.
Actual Scores
for 2019
(Difference
between
Current
Scores and
Baseline
Scores)
MANY STATES HAD ALREADY ACHIEVED CLOSE TO
SATURATION LEVELS OF SCORES WHEN THEIR BASELINE
VALUES WERE RECORDED. AS A RESULT, THEIR ACTUAL
SCORES NOW COME OUT TO BE MINIMAL. WHILE IT MAY
LEAD TO LOWER ECONOMIC SAVINGS, THIS IS A TESTAMENT
TO THEIR STRONG POLICY IMPLEMENTATION IN IHHL EVEN
BEFORE THE ASPIRATIONAL DISTRICTS PROGRAMME WAS
IMPLEMENTED.
Balangir
Katihar
Purnia
Banka
Muzaffarpur
Jamui
Godda
Aurangabad
Araria
Bhadradri-
Kothagudem
96.58
69.75
69.65
68.92
62.88
60.61
59.23
58.95
58.45
58.27 Aspirational Districts Program The above map shows that for the
year 2019, it was the Central and
the Eastern states that made most
of the progress. Most of the North
East States and the Western States
such as Rajasthan and Maharashtra
had already achieved saturation
during the baseline period. On the
other hand, Bihar, Uttar Pradesh
and Jharkhand were the biggest
achievers in the year 2019 and as a
result, managed to potentially make
the biggest savings assigned with
hygiene behaviour change.
These savings can be varied from
state to state due to two important
factors:
i. The number of Aspirational
Districts present in these States.
For instance, Jharkhand with
its 19 Aspirational Districts
will report higher savings as
compared to Kerala that has only
one Aspirational District.
ii. The number of beneficiaries
present in each Aspirational
District. Highly populated
states will report more savings
as compared to less populated
states. For instance, both Katihar
(Bihar) and Balangir (Odisha)
have similar scores for the year
2019, however, the former’s
population is twice the latter’s;
thus, contributing more to the
potential savings.
Figure 4.25.
State-wise
economic
savings
due to IHHL
based on
incremental
progress
during 2018-
2019
Total Potential
State-Wise
0.0 65.3 98
AFTER CONSIDERING ALL THE
ABOVE FACTORS, THE OVERALL
SAVINGS THAT THE DISTRICTS
COULD ACCUMULATE WAS ABOUT
INR 400 CRORES.
Way
Forward
The indicator data for the year 2019
shows that the Aspirational Districts
have taken major strides to bring
consistent improvement. More than
half of the districts have above 90%
annual average for the calendar
year. This implies that strong
potable water delivery services are
available in these districts and soon
will establish a proper network,
which would ensure that all the
beneficiaries receive an adequate
amount of potable water. The rest of
the districts are also not far behind
as the overall average for all the
112 districts come out to be 78.62%,
which is a tremendous achievement.
Compared to this, according to a
Comptroller and Auditor General
(CAG) report in 2017, it was found
that less than half of the target
was met at a national level under
the National Rural Drinking Water
Programme (NRDWP)
42
. That
To further this study, a district-level
assessment must be carried out
that could measure the longitudinal
impacts of construction of IHHL. This
could be corroborated by a monthly
change in child death rates owing
to diarrhoeal deaths. Along with
a health assessment, there must
be a simultaneous Environmental
Impact Assessment (EIA) that
could scrutinise the frequency of
untreated sewage mixing into local
water bodies for all the districts.
Finally, the scope of the study
must be expanded to other sectors
including Education, Tourism, etc.
that could highlight the economic
impacts owing to the presence of
conventional sanitation measures
such as IHHL.
Indicator: Percentage of Rural Habitations with
Access to Adequate Quantity of Potable Water
42
www.bloombergquint.com/law-and-policy/national-rural-drinking-water-programme-failed-
to-achieve-targets-government-auditor-heres-why Aspirational Districts Program Potential Economic Savings due to
Potable Water: Findings
very audit report specified “poor
execution” and “weak contract
management” as two major reasons
for the failure of the programme
to meet its objectives. Thus, the
progress made by Aspirational
Districts has overcome those barriers
and presents another example of
successful policy convergence and
collaboration across various tiers of
stakeholders.
Similar to the IHHL, many districts
were closer to saturation during
the beeline period. However, the
scope for improvement under this
indicator is much bigger. As a result,
some of the districts have shown a
tremendous jump and as a result,
have increased their corresponding
potential savings.
Unlike what was observed with the
IHHL scores, districts from various
States have made tremendous
progress to ensure that potable
water is made available for all. It
was also interesting to note that
North East districts such as Chandel
(Manipur) and Ribhoi (Meghalaya)
have improved significantly.
Figure 4.26
Actual Scores
for 2019
(Difference
between
Current
Scores and
Baseline
Scores)
Ranchi
Nabarangapur
Lohardaga
Balangir
Ribhoi
Yadgir
Dhubri
Virudhunagar
Chandel
Bhadradri-
Kothagudem
9.98
13.53
14.69
20.02
21.79
26.90
28.20
30.78
34.22
74.27 100
THE TOTAL SAVINGS, BASED ON THE ABOVE IMPROVEMENTS,
THAT THE 112 DISTRICTS COULD MAKE CAME OUT TO BE A
MASSIVE AMOUNT OF INR 1443 CRORES.
This figure accounts for the savings, all the districts can make by reducing the
disability and fatality caused by delivery of unsafe water.
Figure 4.27:
State-wise
economic
savings due
to potable
water
based on
incremental
progress
during 2018-
2019
The above map shows that state-
level savings vary significantly. Most
of the Eastern and Southern states
have ensured high savings whereas
Central and Western states have
struggled to achieve the same.
Districts from both Madhya Pradesh
and Maharashtra were not able
to create a distance between their
actual scores for 2019 and their
baseline values. This is an alarming
sign, given that both the states suffer
from severe water pollution
43
and
most importantly, water deficiency
44
.
43
www.downtoearth.org.in/blog/water/can-ministry-of-jal-shakti-save-indian-rivers--65197
44
indianexpress.com/article/explained/simply-put-5000-dry-villages-in-maharashtra-6500-
tankers-5777789/
Total State-
Wise Potential
-103.1 293 Aspirational Districts Program Savings by costs analysis, delivered
some very surprising results.
The state with the biggest return
on costs was Manipur. Its only
Aspirational District, Chandel, has
been one of the biggest improvers
in the year 2019 with respect to
delivery of potable water. As a
result, the district over-delivered
by not just accomplishing its target
for the calendar year but also by
potentially providing better returns
on the costs incurred for provisioning
potable water.
Similarly, Tamil Nadu also with
its two districts has given strong
returns over the associated costs.
This exercise goes to show that
there is so much potential economic
gains/ savings that can be made
from selected districts, that they
can help the state in overcoming the
existing liabilities.
As far as the best performers are
concerned; Odisha, Telangana,
Bihar are some of the states with
more than two Aspirational Districts
that have recorded huge potential
economic savings. Most of the
districts in these states have a
healthy gap between their current
scores and their baseline values,
thus paving the way for major
improvement.
To further evaluate the efficacy of
such savings, this study also looked
at the funds that were allocated to
the states by the Ministry of Jal Shakti
for the financial year of 2019-2020.
The assumption here is that all these
funds will be used by the states
to meet the costs for the National
Rural Drinking Water Programme
(NRDWP).
Saving/ Expenditure (%) for 2019Figure 4.28:
Savings Over
Costs for the
Top 10 States
in 2019
1468.33
313.15
234.06
177.73
154.54126.86
74.64
57.3743.28
Manipur
Tamil
Nadu
Jharkhand
Telangana
Odisha
Chhattisgarh
Andhra
Pradesh
Bihar
Assam The above potential savings
can be further strengthened
for the majority of the
districts and states, as they
are yet to achieve 100%
potable water supply.
Hence, all the relevant
stakeholders need to focus
on meeting this target given
the impending challenge of
water shortage that would
affect the world soon.
For future assessment
processes, new parameters
must be brought in regarding
water management in
Aspirational Districts. Along
with successful water
delivery, modes of water
treatment must also be
studied. This would ensure
complete coverage of water
provisioning both in terms of
quantity and quality.
Furthermore, policy
convergence observed
across all the districts must
cover the anecdotes on
innovative means of water
conservation.
Efficient utilisation would
reduce the burden on our
depleting water-sources.
Thus, new and unique
methods must be showcased
that have positively affected
the water supply at local
levels. For instance, in the
YSR Kadapa district in
Andhra Pradesh, water
conservation process has
been a success through the
construction of subsurface
dams. These subsurface
dams cost one-tenth of
traditional dams and have
benefited around 36 villages
in the district area
45
.
45
niti.gov.in/sites/default/files/2019-08/4_Presentation-for-
PrincipalSecretariesPlanning.pdf
102 Aspirational Districts Program 104
DISCUSSION
OF RESULTSDISCUSSION OF RESULT
05 Aspirational Districts Program The above section presented the
improvements that districts have across
sectors. The performance measurement
of the aspirational districts depicts
varied impacts across parameters. The
observations for the Health and Nutrition
sector suggest that 10 percent of the
districts have already achieved their
targets, whereas 90 percent of the districts
have covered almost 3/4th distance to
their respective targets. On the contrary,
the observations for the Financial Inclusion
sector suggests that none of the aspiration
districts are close to their aspirational
targets. All the districts are approximately
40 to 90 percent far from their targets. DISCUSSION OF RESULT 106
In order to understand the reasons
for such varied performance
of sectors across districts, the
observed outcomes were further
examined in the following manner:
The identification of the indicators
on the basis of who directly controls
them drives this process. While
we may qualify, that all data
points are affected to a varying
a degree by the effort of district
administration, a few of them are
directly affected. This could impact
the decision-making capacities
and the anticipated outcomes
under the programme. Aiyar (2018)
pointed out
46
the limited flexibility
in such a decision-making structure
could affect the implementation
capacity of District Magistrates/
District Collectors. Therefore,
indicators falling directly under the
control of the District Magistrate/
District Collector were isolated, and
the trajectories of the indicators
were assessed on those specific
parameters in this segment of the
report.
47
This allowed the analysis
to control those indicators outside
the ambit of the District Magistrate/
District Collector and effectively
gauge how well the programme has
been able to impact the ability of
the district administration to drive
social impact.
By isolating indicators, the analysis
is able to:
• Isolate the impact of other
national/state schemes.
These indicators reflect the
improved governance of
the district administration
stimulated by competition,
collaboration, and convergence
under the Aspirational Districts
Programme.
• Inform the district
administration about the
development trajectories of
certain indicators – which
indicators need short-term
policy intervention strategies
and which indicators require
longer intervention periods to
show results – allowing them
to create more effective
intervention strategies in the
medium to long term.
46
Aiyar, Y. (2018, May 15). Why the Aspirational Districts Programme may not change anything
on ground. Retrieved from Hindustan Times: https://www.hindustantimes.com/columns/
why-the-aspirational-districts-programme-may-not-change-anything-on-ground/story-
Tnb22h2rMLWUI16MxmZ83J.html Aspirational Districts Program By taking into account only the
indicators that can be impacted by
the DMs, the study reflects on two
things. First, the assessment intends
to highlight if there has been a
tangible change within the districts
as compared to their position at the
baseline of the analysis. Secondly,
it intends to understand which are
the districts that have been able to
drive the maximum change. It must
be recalled here, as mentioned in the
prior sections of this report, one of
the major thematic ideas guiding this
programme is to help the districts
which have emerged as laggards in
social development to the forefront
improving India’s overall human
development. Therefore, the following
analysis sheds light on whether the
districts that lagged behind the most
during the baseline survey have
been able to catch-up to the leaders,
or if the dichotomy among districts
remains constant.
ASSESSING THE RESULTS:
OVERALL PERFORMANCE
Figure 5.1.
Relationship
between
rate of
change
(2018-2020)
and baseline
scores
For the ease of comprehension, the
districts have also been divided
into four categories based on their
baseline scores. The quartiles are
directly proportional to the baseline
scores of the districts. Districts with
the top 25 percent scores in 2018
have been categorised in the Fourth
Quartile. Similarly, districts with the
bottom 25 percent scores in 2018
have been categorised in the First
Quartile within the ambit of this
analysis.
20
20
15
45
45 55 65
10
40
40 50 60
5
35
35
0
30
30
-5
25
25
-10
Score for 2018
Lower
QuartileMedian
Upper
Quartile
Rate of Change
(2018-2019)
Tier
1.0 4.0
• The graphs shows a negative relationship between
the rate of change and baseline scores with a strong
correlation of -0.66.
• This indicates that districts in the bottom tier are
catching up rapidly with the high ranking districts.
• The average rate of growth of fourth quartile (Tier 1)
districts is 8.2 percent while that of first quartile (Tier
2) districts is 25 percent. 108
THE PROGRAMME HAS
THEREFORE NOT ONLY BEEN
SUCCESSFUL IN DRIVING
SOCIAL IMPACT BUT ALSO
IN DRIVING SOCIAL JUSTICE
BY ENSURING THAT THE
MAXIMUM BENEFITS OF THE
PROGRAMME GO TO THOSE
WHO NEEDED IT THE MOST.
In Figure 5.1., it can be seen that the average
growth rate for the districts visible in the First
Quartile is 25 percent. Similarly, the average
growth rate for the districts in the Fourth
Quartile is only 8 percent. This indicates that
the districts that were initially lagging behind
have been able to drive the maximum change
under the programme. Districts which were
initially leading, have also been able to drive
change but at a much slower rate owing to
their proximity to saturation. This means,
under the Aspirational Districts Programme,
districts that were initially lagging in social
and human development indicators have
been able to drive the maximum change
and catch-up to the leaders. This is further
bolstered by the strong correlation of -0.66
between the rate of change scores from 2018
to 2020 and the baseline score from 2018.
Using the above analysis, it can be depicted
with clarity that the Aspirational Districts
Programme has been able to create a
positive social impact by improving social
and human development indicators within
a district. Furthermore, the effective
performance management under the
programme has facilitated those districts the
most that were most deprived in social and
human development at the initiation of the
programme. Aspirational Districts Program The performance of the
states is analysed to assess
any emerging patterns
that may better inform
the policy design aspects
moving ahead. In other
words, if any particular
state has shown marked
improvements or appears to
lag across the parameters
of the programme, special
focus can be given to those
Aspirational Districts to
create more regional equity.
It would ultimately lead
to the overall success of
the programme across the
country.
The state performance
analysis involves depiction
of the change in mean
scores of the Aspirational
Districts within each state
from 2018 to 2020. In Figure
5.2, the states have been
portrayed on the basis of
their performance in the
current year of assessment,
i.e. 2020.
The states highlighted
in red (Figure 5.2) mark
a dip in the current year
of assessment. States
registering lower mean
scores should be given
special focus moving
forward to create better
regional equity within the
ambit of the programme.
The discourse guiding
the programme is one of
regional equity. Regularly
identifying states and
districts that appear to
fall behind would be a
crucial step to ensure that
the programme does not
create a dichotomy of
winners and losers but
actually contribute to the
overall regional equity
within the country leading
to better social and human
development. Currently,
Aspirational Districts in
states with more visible
white spaces – such as
Bihar, Madhya Pradesh, and
Telangana would require
more focus moving forward
compared to the rest of the
country.
ASSESSING THE RESULTS:
STATE WISE*
The results and recommendations from the state wise analysis must be
understood very carefully keeping in mind the limitations of conducting a state
wise analysis. The limitations arise as the number of districts in each state under
the program varies. 110
Figure 5.2: State-wise change in
mean scores on the Aspirational
Districts framework
Haryana
Rajasthan
Delhi
Madhya Pradesh
Gujarat
Maharashtra
Goa
2018
010305070
2019
2020
Uttarakhand
2018
010305070
2019
2020
2018
010305070
2019
2020
2018
010305070
20192020
Punjab
2018
010305070
20192020
70
2018
0103050
20192020
2018
010305070
20192020
2018
010305070
20192020
Chhatisgarh
2018
010305070
20192020
2018
010305070
20192020
Karnataka
2018
010305070
20192020
Kerela
2018
010305070
20192020
Tamil Nadu
2018
010305070
20192020
Andhra Pradesh
2018
010305070
20192020
Himachal Pradesh
2018
010305070
20192020
Uttar Pradesh
2018
010305070
20192020
Arunachal Pradesh
2018
010305070
20192020
Bihar
2018
010305070
20192020
Telangana
2018
010305070
20192020
Meghalaya
2018
010305070
20192020
Jharkhand
2018
010305070
20192020
Sikkim
2018
010305070
20192020
West Bengal
2018
010305070
20192020
Assam
2018
010305070
20192020
Tripura
2018
010305070
20192020
Mizoram
2018
010305070
20192020
Manipur
2018
010305070
20192020
Nagaland
2018
010305070
20192020
Jammu & Kashmir
2018
010305070
20192020
Odisha
2018
010305070
20192020
Note: Red indicates states where mean scores have fallen in the last year.
Blue indicates a general upward trend. Aspirational Districts Program Figure 5.3:
Performance
of Districts
across
parameters
Figure 5.3 portrays that the
Aspirational Districts have shown
the biggest improvement in the
Education sector. The disparity
among the districts has fallen the
most in the Education Sector. On
the contrary, Agriculture and Water
Resources Sector indicates a lot of
scope for improvement. The districts
have also been able to reduce their
respective disparities across the
sectors of Health and Nutrition,
Skill Development, and Basic
Infrastructure.
ASSESSING THE RESULTS:
ACROSS PARAMETERS
Among all the sectors considered
within the ambit of the programme,
the Health and Nutrition sector
is noted to house the maximum
number of indicators. Therefore, it
has been separately analysed in
Figure 5.4.
20
15
10
5
0
-5
-10
Health &
Nutrition
Education
Change in Mean
Change in Std. Dev.
Agriculture
and Water
Resources
Skill
Development
Basic Infra 112
The total number of indicators
under the Health and Nutrition
sector accounts for 31 individual
data-points. This is significantly
high as it represents around 36%
of the total number of data-points
across the sectors. The data-points
have been thematically categorised
and subsequently analysed in
Figure 5.4 to assess the key
movements within this particular
domain.
The detailed assessment of
the Health & Nutrition sector
showcases some interesting trends
in policy impact. The maximum
improvement in the domain of
Health and Nutrition has happened
within the Health Infrastructure
domain. Disparities within districts
have reduced the most under Child
Care, which could be a result of
focused policy initiatives to support
child immunisation and Integrated
Child Development Services (ICDS)
across the country. Similar is the
trajectory for aspects related to
maternal care, which are often
related. It must be noted here that
the most encouraging inference
from the analysis stems from the
fact that all parameters across
the sector have shown marked
improvement. It must also be noted
here that driving change in aspects
of health care under any policy
intervention is no mean feat that
can be easily achieved. Often, these
interventions require sustaining
behavioural changes – like regular
access to nutritious food for
pregnant women – which may come
with its socio-cultural baggage in
the context of South Asia. The fact
that the programme, along with its
digital performance management
mechanisms, has been able to
achieve this change is in itself a
positive social impact.
Figure 5.4:
Performance
of Districts
in the
Healthcare
Ecosystem
Changes in the Healthcare Ecosystem
20
15
10
5
0
-5
-10
Maternal Care
Child Care
Health Outcomes
Heath Infrastructure
Change in MeanChange in Std. Dev. The indicators which can be most
influenced by the District Magistrate
have further been categorised
into two additional aspects. In the
first segment, the indicators are
collated based on their ease of
implementation. On the basis of
secondary research and extensive
field engagements undertaken
within the scope of this research with
district administrators, the indicators
which can be most influenced by
the district administration have
been categorised into short-term
indicators, medium-term indicators,
and long-term indicators under the
programme. This analysis is expected
to help the district administration
develop effective timeframes for policy
interventions under the Aspirational
Districts Programme, and reduce
incorrect target setting exercises such
as expecting to achieve targets of the
long-term indicator within a short-
term of policy intervention.
In the subsequent section, the
indicators are further classified into
impact and performance indicators.
Such a classification based on the
type and nature of the indicators
enables the report to highlight
whether the Aspirational Districts
Programme has been able to drive
any tangible change at the ground
level or have been restricted in
showing improvements across input
intervention. It must be noted here
that improvement in performance is
often harder to achieve as compared
to inputs since performance indicators
can also demand behavioural change.
If the programme has been able to
generate a positive impact on the
performance indicators, along with
the impact indicators, it can be an
indication of the positive behavioural
change that is being driven within the
districts by the Aspirational Districts
Programme.
UNDERSTANDING THE
INDICATORS IN MORE DETAIL
Aspirational Districts Program Ease of
Implementation
The nature of indicators across
sectors varies, and their outcomes
may be visible across different
points of time. While some
indicators are comparatively
easier to move owing to their
implementation processes, other
indicators may be more complex
to administer by the District
Magistrate/District Collector.
Similarly, some indicators can
be improved within a short time
such as the indicator measuring
the provision of textbooks under
the Education sector. Others
would require more time to
reflect improvement and need
interventions for longer durations.
For instance, indicators measuring
improvement in institutional
deliveries under the Health and
Nutrition sector would take more
time to move owing to its scope and
nature as compared to the previous
example of textbooks.
114 Therefore, to address the varying nature and ease of achievability of the
indicators, they have been categorised into three groups:
Short Term – comprising of indicators whose impact can be tracked in the
short-term after any related policy intervention.
Medium Term – comprising of indicators whose impact can be tracked in
the medium-term after any related policy intervention.
Long Term – comprising of indicators that require a long gestation period
to show impact after any related policy intervention.
The analysis intends to study the rate of change for the indicators across
these three categories.
This analysis will be particularly
useful for the district authorities to
determine the “low hanging fruit”
under the ambit of the programme,
or the indicators that they may
focus upon to see immediate gains.
Furthermore, it will help the district
administration better strategise
their interventions with more
information on the nature of the
indicators, allowing them to come
up with more effective timelines
to achieve the determined targets
under the ambit of the programme.
THE HYPOTHESIS FOR THE ANALYSIS IS THAT THE RATE
OF CHANGE OF SHORT-TERM INDICATORS WILL BE THE
HIGHEST AMONG THE THREE. THE RATE OF CHANGE
OF MEDIUM-TERM AND LONG-TERM INDICATORS WILL
FOLLOW A SIMILAR TREND, THEREBY, REFLECTING
THAT THE RATE OF CHANGE FOR ANY INDICATORS IS
RELATIVE TO ITS EASE OF ACHIEVABILITY OVER TIME.
Aspirational Districts Program 116
Figure 5.5: Comparison of Mean
Scores for Short-Term, Medium-
Term and Long-Term Indicators
16
16
202020
16
16
16
16
0
0
0
0
0
0
0
0
0
10
10
10
10
10
10
10
10
10
20
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20
20
20
20
20
20
20
30
30
30
30
30
30
30
30
30
40
40
40
40
40
40
40
40
40
50
50
50
50
50
50
50
50
50
60
60
60
60
60
60
60
60
60
70
70
70
70
70
70
70
70
70
80
80
80
80
80
80
80
80
80
90
90
90
90
90
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90
100
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100
110
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110
110
110
110
12
12
151515
12
12
12
12
8
8
101010
8
8
8
8
4
4
555
4
4
4
4
0
0
000
0
0
0
0
Categorization of Indicators by Ease of Achievement
Indicators achieavable in Short Term
2018 Scores
2018 Scores
2018 Scores
2019 Scores
2019 Scores
2019 Scores
2020 Scores
2020 Scores
2020 Scores
Indicators achieavable in Medium Term
Indicators achieavable in Long Term
FrequencyFrequencyFrequency While short-run indicators were already at
a high mean score in 2018, their dispersion
has reduced over time. The medium-term
indicators had the lowest mean in 2018
but have shown the most improvement
across the three years. Their dispersion is
also the highest in 2020 across all levels.
The long-run indicators were stickier across
time, which is expected since the time-span
assessed here is too short.
• The short-term indicators have been
able to significantly converge around its
high mean scores – that is to indicate
that those districts which were lagging
in 2018, have been able to catch-up with
their peer districts.
• Though the medium-term indicators
show the highest dispersion among the
districts, they have been able to achieve
the maximum change within the scope of
the programme as the analysis; and,
• As believed, the long-term indicators
have recorded little variation over
time owing to the “sticky” nature of
these indicators. They would require a
sustained gestation period before related
policy interventions can show traceable
impact in these domains.
The key learning is that the districts
should develop goal posts based on the
ease of achievement of the indicators.
KEY INFERENCES
Aspirational Districts Program Type of Indicator
Along with the ease of
implementation analysis that will
facilitate the districts to determine
robust timeframes to achieving
targets under the Aspirational
Districts Programme, the report
also expands the analysis to the
nature of the indicators. By further
categorising indicators into impact
and performance indicators and
studying their trajectories of
change, the analysis would further
help the districts to better strategise
interventions within the programme
leading to better social and human
development in the districts.
This classification, relating to
the type of the indicator, has
been based on the defining
characteristics of the sectors
within the Aspirational Districts
Programme. Indicators under
each sector have been classified
either as “impact indicators” or as
“performance indicators” depending
on its nature and scope of their
effect. In other words, indicators
that are predominantly dependent
on input factors – such as provision
of text-books – have been classified
as impact indicators. Similarly,
indicators that are more dependent
on outcome factors – such as the
prevalence of institutional deliveries
within a district – have been
classified as performance indicators
within the scope of this analysis.
118 In other words, based on their
distinct types, the indicators have
been grouped as:
Impact indicators – Impact
indicators measure a region’s
policies that are believed to create
an impact on the outcomes. These
may include indicators pertaining to
infrastructure, such as the number
of hospitals, schools, etc.
Performance indicators –
Performance Output indicators
directly measure the outcome
of policies. For instance, a
performance indicator may measure
the quality of the infrastructure in
place.
THE HYPOTHESIS
UNDERLYING THIS
CLASSIFICATION IS THAT
THE RATE OF CHANGE
REFLECTED BY THE IMPACT
INDICATORS WILL BE
HIGHER THAN THE RATE
OF CHANGE DEPICTED
BY PERFORMANCE
INDICATORS.
The analysis of indicators based
on their nature of achievement is
similar to the analysis previously
done for ease of achievement. The
analysis highlights the following
inferences within the scope of this
report.
The distribution of aggregate mean
scores for the impact indicators
has improved across the three
years. However, the extent of
improvement varies from the
performance indicators. One of the
probable reasons could be that the
required infrastructure to achieve
improvement across indicators was
available. The sufficiency of these
infrastructural or policy provisions
can be gauged from the depiction
of improvement in performance
indicators over time.
Aspirational Districts Program 120
The improvement in aggregate
mean scores can be seen in the
distribution for performance
indicators in Figure 5.6. The
dispersion has also reduced
across the years. The performance
indicators have shown a visibly
superior outcome over the impact
indicators. This can verify the
previous assumption and imply
that the districts had the inputs in
place. Therefore, social challenges
could be addressed during the term.
The monitoring mechanism of the
programme could have incentivised
the district administrations towards
improving their performance
parameters.
Figure 5.6: Comparison of mean score for
impact and performance indicators
1616
202020
16
0
0
0
0
0
0
10
10
10
10
10
10
20
20
20
20
20
20
30
30
30
30
30
30
40
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40
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50
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60
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100
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110
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110
110
110
110
1212
151515
12
88
101010
8
44
555
4
00
000
0
FrequencyFrequency
2018 Scores
2018 Scores
2019 Scores
2019 Scores
2020 Scores
2020 Scores
Categorization of Indicators by Year
Impact Indicators
Performance Indicators KEY INFERENCES
• The impact-indicators have shown
improvement, but owing to the work
already done in the districts under
the various missions and schemes
of the government vis-å-vis input
infrastructure, the change in these
indicators appears to be somewhat
subdued when compared to the
performance indicators.
• The improvement in mean scores of the
performance-indicators in the analysis is
more vivid over time. This can somewhat
vindicate the previous inference. Since
the input infrastructure was already
present in the districts, the competition,
collaboration, and effective monitoring
undertaken by the Aspirational Districts
Programme have probably enabled the
districts to achieve positive outcome vis-
å-vis the performance indicators.
Aspirational Districts Program The analysis in the report until this section highlighted
the performance of the Aspirational Districts Programme
since its implementation in March 2018. In other words,
the three previous sections – the DTF Analysis, the
Mobility Matrix, and the prior section assessing the impact
of governance across different districts focus on the
transformations and social impact that has been created
under the Aspirational District Programme from the
baseline condition.
IMPACT OF ADP
BEATING SECULAR
TRENDS?
06 Each section highlights its distinct
findings and showcases the impact
that the programme has been able
to create across different sectors
and their respective indicators. To
briefly sum up the programme has
undoubtedly created some positive
impact across the sectors even
though the scale of the impact has
been severely varied. It is generally
observed across the analysis that
sectors that have received a higher
weight within the design of the
programme, such as Health and
Nutrition and Education, have shown
comparatively more impact than
other sectors
SECTORS SUCH AS BASIC
INFRASTRUCTURE THAT
ARE BEING DRIVEN
BY MISSION MODE
PROGRAMMES SUCH
AS SWACHH BHARAT
AND SAUBHAGYA, HAVE
ALSO SEEN SIGNIFICANT
IMPROVEMENT IN THE
ASPIRATIONAL DISTRICTS
OF THE COUNTRY.
Based on these inferences, it is
becoming obvious to investigate if
the Aspirational Districts Programme
does add any additional value as a
policy intervention across the sectors
or would the districts showcase very
similar development trajectories even
in the absence of the programme. If it
can be comprehensively determined,
using a statistical technique that the
Aspirational Districts Programme
does positively influence the
growth trajectories of the indicators
compared to their secular trends then
the research can definitively attribute
the social impact to the Aspirational
Districts Programme itself. To
achieve this, the research analyses
indicators from the domain of Health
and Nutrition and Education –
which comprise of 60% of the total
weight given to the sectors under
the programme – to check if the
programme has been able to create
tangible impact within its scope by
enabling these indicators to beat their
respective secular trends. 124
In order to do this, existing public databases such as Health Management
Information System (HMIS) (for Health and Nutrition indicators) and UDISE
(for Education indicators) are used. In this, indicator level data for common
indicators, that are indicators, which are present in the aforementioned
public databases and within the scope of the Aspirational Districts
Programme, are compared for two phases with similar time-period. It means
that the changes in the common indicators over equal intervals of time are
compared before and after the implementation of the Aspirational Districts
Programme.
A two-tailed z test is used because there can be a worsening of district
performance post-ADP. For accuracy, time-periods immediately before
and immediately after the implementation of the Aspirational Districts
Programme have been used as per the latest available data for the
indicators.
SINCE THIS IS AN INDICATIVE
ANALYSIS, ONLY THOSE DATA-POINTS
THAT ARE PUBLICLY AVAILABLE HAVE
BEEN USED TO ENSURE THE EXERCISE
IS EASILY REPLICABLE TO CHECK FOR
STATISTICAL VALIDITY. ONCE THE
CHANGE IS CALCULATED BEFORE AND
AFTER THE IMPLEMENTATION OF THE
PROGRAMME, A TWO-TAILED Z-TEST IS
CONDUCTED TO DETERMINE IF THERE
IS ANY STATISTICALLY SIGNIFICANT
DIFFERENCE THAT HAS BEEN
ACHIEVED UNDER THE ASPIRATIONAL
DISTRICTS PROGRAMME. Aspirational Districts Program The use of a two-tailed Z-test is of
relative significance here. A Z-test is a
well-established statistical technique
used to test hypotheses of any
experiment. In order to use the Z-test
in the scope of this research, the
report hypothesises that the annual
increment in indicator performance
before the aspirational districts
programme is equal to the annual
increment under the programme. As
discussed in the previous paragraph,
the annual increment immediately
before the implementation of the
programme and immediately
after the implementation of the
programme has been considered
for select indicators. This data has
been collated for all 112 Aspirational
Districts within the scope of the
programme.
Once the data for all the districts are
collated, the mean and the standard
deviation of the given sample is
calculated, and a decision rule is
established. A decision rule, in simple
terms, refers to the choice of the test
statistic and the confidence interval
within which the hypothesis needs
to be tested. Following this, a Z-test
is run on a pre-determined level of
statistical significance.
It must be mentioned here that
for sample sizes less than 30, the
convention dictates that a t-statistic
test is used instead of a z-statistic
test. Since the sample size, or the
number of data points, is greater than
30 in this research – a z-statistic test
is being used. Also, as there are two
possible outcomes that one may
observe after the implementation
of the Aspirational District
Programme, a two-tail Z-test is
being used instead of a one-tail
Z-test. A two-tail Z-test informs if a
particular parameter being tested
has shown any change – either
increase or decrease – thereby
enabling a researcher to reject the
null hypotheses or the hypotheses
that were created before the test
was conducted. Apart from a two-
tail Z-test, a Z-test can also be
of two other types. An upper-tail
Z-test and a lower-tail Z-test. An
upper-tail Z-test is usually used
when an increase is hypothesised.
Similarly, a lower-tail Z-test is used
when a decrease is hypothesised.
The reason for this report to use the
two-tail Z-test instead is because
the research neither hypothesises
an increase nor a decrease, but
it simply hypothesises a change
which can either be increasing or
decreasing in nature. It is effective
to test the indicators in such a
manner as with the implementation
of a new policy intervention
programme, all three observations
– an increasing, a decreasing, or
an unchanged – trajectory of the
indicators are possible. Using a
two-tailed Z-test not only allows
the identification of change but
would also allow the identification
of the trajectory of change – if any –
that has been brought about by this
programme 126
In the scope of this analysis, the Z-test is conducted at a 5 percent level
of significance, which indicates that the test would be able to state with
95% confidence whether the programme has shown any change from the
secular trends of the tested indicators. The test would reject the hypothesis
if |Z| < Zα /2. Thereby, it would be able to determine if the difference in
the incremental change under the Aspirational Districts Programme is
statistically significant or not.
In the scope of this report, nine indicators from the Health and Nutrition
sector and five indicators from the Education sector were tested to
determine if the Aspirational District Programme has been able to break the
secular trends in these domains.
HYPOTHESIS
H0 : µ = µ
0
H
A
: µ ≠ µ
0
We reject H0 at significance
level a if|Z| <
Z
α/2
TEST STATISTIC
DECISION
ACCEPTANCE
REGION (A.R) AND
REJECTION REGION
(R.R) OF H
0
a/2a/2
A.R. of H0
R.R
Of H0
R.R
Of H0
1 - a
Ζ
a/2
Ζ
1- a/2 = -Ζ
a/2
Calculate the value of :Ζ ∼ N(0,1)=
-Χµ
0
/σ√n Aspirational Districts Program In the Health and Nutrition sector, it is evident that five out of nine indicators tested
have registered significantly higher improvements during the Aspirational Districts
programme as compared to their secular trends. Three of the indicators considered did
not show any significant change in their trend. It must be noted here that it does not mean
that the indicators have not improved; it simply means that the rate of improvement
under the programme has not been faster than the secular trajectories. One indicator
tested, the percentage of live babies weighed at birth, showed a positive change at the 10%
significance level but not at the 5 percent significance level.
Indicator
0.0000.0001.000Yes
0.0001.0000.000Yes
0.0000.0001.000Yes
0.0000.0001.000Yes
0.4080.7960.204No
0.0580.0290.970No
0.7140.3570.643No
0.0010.0050.9995Yes
0.0020.0010.999Yes
Percentage of ANC registered
within the first trimester
Percentage of deliveries at
home attended by SBAs
Percentage of new-borns
breastfed within one hour of
birth
Percentage of low birth weight
babies (less than 2500g)
Percentage of live
babies weighed at birth
Percentage of children
fully immunised
Sex Ratio at birth
Percentage of Pregnant
women having severe anaemia
treated
Percentage of
institutional deliveries
Based on Ζ test
(at 5 % level of
significance)
p-valueAcceptance
Is there significant
difference due to the
programme?
µ1 ≠ µ0µ1 > µ0µ1 < µ0
p-valueAcceptance
Incremental
improvement under
programme is higher
p-valueAcceptance
Incremental
improvement before
AD was highe
r
Health and
Nutrition 128
It is important to note that one
of the nine indicators tested has
shown a curious trend wherein the
development under the Aspirational
Districts Programme has appeared
to be significantly lower than the
secular trend. The percentage
of institutional deliveries has
registered a slower growth under
the Aspirational Districts Programme
than before. However, this could
be an outcome of the fact that this
particular indicator had almost
reached saturation around 2015-16
itself, as depicted in Figure 6.1. As
witnessed in the previous section of
this report, the closer an indicator
gets to saturation its rate of change
gradually reduces. This could be a
possible explanation for the indicator
to effectively show a slower rate of
change under the programme than
under its secular trend.
Araria
Asifabad (Adilabad)
Aurangabad
Bahraich
Baksa
Balangir
Balrampur
Banka
Baramula
Baran
Barpeta
Barwani
Bastar
Begusarai
Bijapur
Bokaro
Chamba
Chandauli
Chandel
Chatra
Chhatarpur
Chitrakoot
Dakshin Bastar Dantewada
Damoh
Darrang
Dhalai
Dhaulpur
Dhenkanal
Dhubri
Dohad
Dumka
Fatehpur
Firozpur
Gadchiroli
Gajapati
Garhwa
Gaya
Giridih
Goalpara
Godda
Gumla
Guna
Hailakandi
Hardwar
Hazaribagh
Jaisalmer
Jamui
Kalahandi
Kandhamal
Karauli
Katihar
Khagar
ia
Khandwa (East Nimar)
Khunti
Kiphire
Kondagaon
Koraput
Korba
Kupwara
Latehar
Lohardaga
Mahasamund
Malkangiri
Mamit
Mewat
Moga
Muzaffarpur
Nabarangapur
Namsai
Nandurbar
Narayanpur
Narmada
Nawada
Nuapada
Osmanabad
Pakur
Palamu
Pashchimi Singhbhum
Purbi Singhbhum
Purnia
Raichur
Rajgarh
Rajnandgaon
Ramanathapuram
Ramgarh
Ranchi
Rayagada
Ribhoi
Sahibganj
Sheikhpura
Shrawasti
Siddharthnagar
Simdega
Singrauli
Sirohi
Sitamarhi
Sonbhadra
Sukma
Udalgu
ri
Udham Singh Nagar
Uttar Bastar Kanker
Vidisha
Virudhunagar
Visakhapatnam
Vizianagaram
Washim
Wayanad
West District
Y.S.R.
Yadgir
100
0
Figure 6.1. Percentage of Institutional Deliveries had almost reached saturation across most Aspirational Districts by 2015-16.
Percentage of Institutional Deliveries to Total Deliveries
(2015-2016)
WITH FIVE OUT OF NINE INDICATORS POSITIVELY BEATING THE SECULAR
TREND TO REGISTER IMPROVED GROWTH TRAJECTORIES AT 5% SIGNIFICANCE
LEVELS, IT CAN BE STATED THAT THE ASPIRATIONAL DISTRICTS PROGRAMME
HAS INDEED BEEN ABLE TO BEAT THE SECULAR TREND IN IMPROVING HEALTH
AND NUTRITION IN SOME OF THE MOST CHALLENGING AND UNDERDEVELOPED
REGIONS OF THE COUNTRY. Aspirational Districts Program
Education
LIKE HEALTH AND NUTRITION, THE INDICATORS IN EDUCATION ALSO
SHOW POSITIVE IMPROVEMENTS UNDER THE ASPIRATIONAL DISTRICT
PROGRAMMES BEATING THEIR SECULAR TREND OF GROWTH.
FOUR OUT OF FIVE INDICATORS TESTED SHOW A STATISTICALLY
SIGNIFICANT IMPROVEMENT IN THE DOMAIN OF EDUCATION UNDER
THE ASPIRATIONAL DISTRICTS PROGRAMME
.
Indicator
0.0150.007Yes
Yes
0.4680.000
0.234
No
0.0000.0051.000
1.000
1.000
0.993
0.766
Yes
0.000
0.000
0.001Yes
Percentage of schools with
functional drinking water facility
Percentage of schools with
electricity facility (secondary)
Transition Rate (Upper Primary
to Secondary
Transition Rate (Primary to
Upper Primary)
Percentage of schools with
functional girls’ toilets
Based on Ζ test
(at 5 % level of
significance)
p-valueAcceptance
Is there significant
difference due to the
programme?
µ1 ≠ µ0µ1 > µ0µ1 < µ0
p-valueAcceptance
Incremental
improvement under
programme is higher
p-valueAcceptance
Incremental
improvement before
AD was highe
r
Only one indicator, the percentage
of schools with functional drinking
water facility, shows a slower rate of
growth under the programme than
the secular trend. Similar to the trend
observed in the Health and Nutrition
indicator, this particular indicator
too was almost near saturation
during 2015-16 across the districts.
It could be one of the reasons for the
indicator registering a slower rate
of change under the programme as
compared to its secular trend. Visakhapatnam
Vizianagaram
Y.S.R.
Namsai
Baksa
Barpeta
Darrang
Dhubri
Goalpara
Hailakandi
Udalguri
Araria
Aurangabad
Banka
Begusarai
Gaya
Jamui
Ka�har
Khagaria
Muzaffarpur
Nawada
Purnia
Sheikhpura
Sitamarhi
Bastar
Bijapur
Dakshin Bastar Dantewada
Kondagaon
Korba
Mahasamund
Narayanpur
Rajnandgaon
Sukma
U�ar Bastar Kanker
Dohad
Narmada
Mewat
Chamba
Baramula
Kupwara
Bokaro
Chatra
Dumka
Garhwa
Giridih
Godda
Gumla
Hazaribagh
Khun�
Latehar
Lohardaga
Paku
r
Palamu
Pashchimi Singhbhum
Purbi Singhbhum
Ramgarh
Ranchi
Sahibganj
Simdega
Raichur
Yadgir
Wayanad
Barwani
Chhatarpur
Damoh
Guna
Khandwa (East Nimar)
Rajgarh
Singrauli
Vidisha
Gadchiroli
Nandurbar
Osmanabad
Washim
Chandel
Ribhoi
Mamit
Kiphire
Balangir
Dhenkanal
Gajapa�
Kalahandi
Kandhamal
Koraput
Malkangiri
Nabarangapur
Nuapada
Rayagada
Firozpur
Moga
Baran
Dhaulpur
Jaisalmer
Karauli
Sirohi
West District
Ramanathapuram
Virudhunagar
Asifabad (
Adilabad)
Bhoopalapalli (Warangal)
Bhadradri-Kothagudem
Dhalai
Hardwar
Udham Singh Nagar
Bahraich
Balrampur
Chandauli
Chitrakoot
Fatehpur
Shrawas�
Siddharthnagar
Sonbhadra
100
0
Figure 6.2. Percentage of Schools with Functional Drinking Water (2015-2016).
The indicator Percentage
of Schools with Functional
Drinking Water, like
Percentage of Institutional
Deliveries, had almost
reached saturation across
most Aspirational Districts
by 2015-16. This reason
could have possibly led to
a slower rate of change
under the programme as
compared to its secular
trend. With four out of five
indicators, positively beating
the secular trend, to register
improved growth trajectories
at 5 percent significance
levels, it can be stated that
the Aspirational Districts
Programme has also been
able to beat the secular trend
in improving Education and
its related indicators in the
Aspirational Districts.
130 Aspirational Districts Program
To sum up, the use of the Z-test
enabled the research to identify
if the improvements under the
Aspirational Districts Programme
were statistically significant or were
broadly in tune with the secular
trends that had existed before the
implementation of the programme.
In order to check this, select
indicators from the domain of Health
& Nutrition and Education were
chosen to check the secular trend
trajectories on the basis of publicly
available data to make the exercise
replicable. In this regard, matching
indicators from HMIS and UDISE
were chosen to test for secular
trends.
It emerged that 9/14 indicators
tested showed a statistically
significant improvement, i.e. they
were able to beat the secular growth
trajectories under the Aspirational
Districts Programme.
This could be an extremely
encouraging sign for the programme
as it is not only able to generate
significant improvements within
a very short span of time but is
also doing so faster than the prior
secular trend. One limitation of
this analysis is that it is conducted
for only 14 data points within the
programme owing to constraints of
data availability. Future research can
further explore this aspect across
more indicators of the programme
to comprehensively identify the
areas in which the programme has
been able to beat the secular trends,
thereby creating a significantly
positive impact in some of the
most challenging geographies of
the country. Finally, the fact that
competition, collaboration, and
convergence can actually determine
better policy outcomes compared
to secular trends further testifies to
the effectiveness of the fundamental
discourse of this programme.
It validates the belief that improving
the quality of governance can
produce better social and human
development outcomes – an
idea that has the potential to be
replicated globally. The Aspirational Districts Programme (ADP)
and Sustainable Development Goals (SDGs)
both emphasise on the provisioning of basic
services through sustainable means to the
most marginalised communities and people.
As discussed earlier, the focus of ADP
revolves around six domains:
• Health
• Education
• Agriculture and Water Resources
• Skill Development
• Financial Inclusion
• Basic Infrastructure
IMPACT OF ADP
ATTAINING THE
SDGs
07 134
These domains cover a wide range
of socio-economic issues that
subnational policymaking has to
deal with regularly. The original
objective of ADP is to bring holistic
development to the relatively
backward 112 districts across India
through Policy convergence and
collaboration and by promoting
competition amongst the districts.
This objective aligns with the
spirit of SDG 10 to reduce various
forms of inequalities
48
. Aligning the
objectives of ADP with that of SDGs
is crucial to establish a time-bound
assessment framework.
In the last two years, NITI Aayog has released the SDG India Index that assesses the progress made at the state level concerning the completion of all the seventeen Goals. Thus, a similar framework must be created to assess the same level of progress at the district-level. There are multiple ways in which such a framework could benefit the subnational policymaking:
• By tracking the SDG completion
for aspirational districts, the
State Government could assess
the policy convergence at both
state and district levels. This
would further guide the States in
pinpointing the areas where the
progress of aspirational districts
successfully aligns with that of
its own.
• Evaluation of the above policy
convergence/divergence; it could
promote State-District level
policy collaboration. Therefore,
this would streamline the
policymaking from sub-national
to the next disaggregated level.
Studies also reflect how strong
collaboration results in the
successful execution of policies,
thus attributing to holistic
regional development
49
.
• Adherence to the framework
could also prompt successful
competitive federalism as
envisioned by NITI Aayog
amongst the Aspirational
Districts. Healthy competition
amongst the districts could
result in large-scale regional
development with long-term
economic and social multipliers
benefiting the most vulnerable
sections of that region.
• Finally, states such as Bihar
and Jharkhand, that did not fare
well in the latest NITI India SDG
Index could use this framework
to nudge their Aspirational
districts in improving their SDG-
related indicators that in turn
could improve their state-level
performance.
Need for a
Framework
48
NITI Aayog. (2019). SDG India Index 2019.
49
OECD. (2010). The Interface Between Subnational and National Levels of Government. Aspirational Districts Program The objective of this framework is to
identify the key indicators common
between the ADP and the SDGs.
While all the indicators under both
the programmes may not align,
NITI Aayog has identified six SDGs
(namely SDG 3, 4, 6, 8, 9, 10) that
could be aligned perfectly with the
indicators prescribed under the
Aspirational Districts
50
.
Thus, a list of indicators has been
compiled to assess the progress
of a district made under the ADP.
This progress could then be linked
with the rate of completion of
SDGs for all such districts. For this
framework, NITI Aayog’s metadata
has been referred to which finds the
closest-possible SDG indicator that
could be linked with an Aspirational
District indicator
51
.
Methodology
50
NITI Aayog. (2019). SDG India Index 2019.
51
NITI Aayog. (2018). Transformation of Aspirational Districts; National Workshop on Real-Time
Monitoring Dashboard.
THE ANALYSIS FOR SDGS IS ONLY DONE FOR INDICATORS THAT CAN BE
MAPPED TO THE SDGS, CAN INTUITIVELY BE PROJECTED, AND WHERE
SUFFICIENT DATA IS AVAILABLE.
Using the data for these indicators from the dashboard, projections are made
to identify the year in which saturation will be achieved or districts will reach
the SDG target. These projections are made using moving average point
change to capture the changes between the rate of growth of districts that
start with a higher value and the districts that start with a low value. It has
been observed in the above analysis that districts that start at a lower value
tend to grow faster as they have both, a lot of scope for success as well as
learnings from other districts.
ADP SectorNumber of Overall Indicators
Basic
Infrastructure
Education
Health7
Total=13
3
3 136
Results
In the graphs below we present the time taken for the
mean scores of the districts on each of the indicators to
reach their target, categorised by sectors.
PLEASE NOTE THAT THESE
INDICATORS DO NOT
SPECIFICALLY FALL UNDER
SDGS BUT HELP IMPROVE
DEVELOPMENT INDICATORS
THAT HAVE A ONE-TO-ONE
MAPPING WITH SDGS. Aspirational Districts Program
Health
There are seven indicators under the
Health sector that can be mapped
to the SDG goals. Most of them
will be achieved within the target
date of 2030 and will significantly
contribute to helping India reach
the set goals. One area of concern
is the burden of tuberculosis (TB
cases. India has a low notification
rate for TB cases despite it being
mandated for all patients. As per
our projections, the notification rate
will reach 100 percent for these
districts only in 2038.
Percentage of Anganwadis centres/Urban
PHCs to have conducted at least one Health
Sanitation & Nutrition day
Proportion of Sub centres/ PHCs converted
into Health & Wellness Centres (HWCs)
TB Treatment success rate among notified TB
patients (public and private)
Tuberculosis (TB) case notification rate
(Public and Private Institutions) against
estimated cases
Percentage of children fully immunized (9-11
months) (BCG+ DPT3 + OPV3 + Measles1)
Percentage of institutional deliveries out of
total estimated deliveries
Percentage of Pregnant women having
severe anaemia treated against PW having
sever anaemia tested cases
2021
2021
2021
2020 2025 2030 2035 2040
2022
2026
2023
2038
Figure 7.1. SDG Target Achievement for Health
Years of SDG Achievement In the Education sector, we look at
three indicators – the Percentage
of elementary schools complying
with RTE specified Pupil-Teacher
Ratio, the Transition rate from upper
primary to secondary school level,
and Transition rate from primary
to upper primary school level. The
transition rate from upper primary
to secondary schools is very low in
the country indicating that children
drop out after class 8. The target for
this indicator will only be achieved
by 2031.
Education
Pupil Teacher Ratio
(RTE Compliant)
Transition Rate
(Upper Primary to Secondary)
Transition Rate
(Primary to Upper Primary)
2026
2027
2024
2022
2026
2028
2030
2032
2031
Figure 7.2.
SDG Target
Achievement
for
Education
Years of SDG Achievement
138 All indicators that can be mapped
with SDGs will be achieved even
before 2025. The progress over
the last few years on road building
and electricity penetration by the
government has yielded positive
results. Meanwhile, the push for
digital connectivity and falling
internet prices have driven internet
penetration into the aspirational
districts as well.
Basic Infrastructure
Percentage of habitations
with access to all weather
roads under PMGSY
Percentage of Gram
panchayat with internet
connection
Percentage of households
with electricity connection
2023
2020
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2024
Figure 7.3.
SDG Target
Achievement
for Basic
Infrastructure
Years of SDG Achievement
Aspirational Districts Program 140
LEARNINGSLEARNINGS
LEVERAGING THE
PARTNER ECOSYSTEM
08 Aspirational Districts Program Based on the field interviews and
the engagements undertaken
by the team within the scope
of this research, the report
recommends a six-point partner
engagement framework to
leverage maximum social and
human development outcomes
from partner engagements. This
framework recommends the key
guiding principles and maps it
to the identified challenges or
best practices shared by the key
stakeholders interviewed during
the research. LEARNINGS
WHAT WORKS?
FRAMEWORK FOR FUTURE
PARTNER ENGAGEMENTS IN
ASPIRATIONAL DISTRICTS L
if
e
C
y
c
le
o
f
a
p
a
r
t
n
e
r
e
n
g
a
g
e
m
e
n
t
Figure 8.1.
The 6-point
Engagement
Framework
COLLABORATE
ENGAGE
FACILITATE
MONITOR
PROMOTE
IDENTIFY
Initiation
Execution
Sustainable
Completion
142 Aspirational Districts Program Figure 8.2. The first step of the framework helps partners accurately
identify their domain, region, and point of intervention.
The framework is designed keeping
the entire lifecycle of partner
engagement in mind. In the first
stage of the framework, the
challenge of identifying the right
district based on the Aspirational
District data is addressed. Often,
as discussed in the previous
sections of this report, choosing the
incorrect district to engage leads
to the problem of either “too much”
or “too little” for the partners. This
may lead to undesirable social and
human development outcomes.
Whenever a partner intends to
engage or expand their geographic
scope within the Aspirational
District Programme, the use of
evidence-driven tools such as
Institute of Competitiveness (IFC)
Partner Connect, or any other
tool on similar principles, would
enable partners to choose points of
intervention appropriately allowing
them to leverage maximum social
and human development outcomes
within the scope and scale of their
intervention. Finally, this also allows
NITI Aayog to clearly define
the role of the partner once the
engagement is identified thereby
avoiding any mismatch in the goals
of the partner and the goals of the
district where the partner is going
to intervene.
Identify
Action Utilize evidence based analysis such as DTF to identify the domain, region, and
point of intervention. Assess if needs of the district are implementation oriented
or innovation model oriented. Avoid problems of engagement mismatch.
Time Frame At the initiation of the project.
Key Insights
Incorporated
Dual nature of existing development partner engagements within the
ecosystem – (i) program implementation engagements; and (ii) policy innovation
engagements.
Challenges
Addressed
1. Mismatch between the nature of engagement and the demands of the district.
2. Concentration of partners in some regions – ignoring others.
Risks May not be possible to effectively gauge niche challenges within districts using
CoC data – leading to incorrect assessment and incorrect identification.
Step 144
The framework is designed keeping
the entire lifecycle of partner
engagement in mind. framework
devices best practices for
generating collaboration with
the district administration. In
the scope of this research, it can
be stated on the basis of the field
engagements that partners are
most effective in collaborating
with district authorities when
they are embedded into the
institutionalised structure of the
district administration; and, have
subsequently been able to position
a human resource within the office
of the district administration. In this
regard, the framework recommends
that the partners – after identifying
the appropriate district for
engagement – collaborate with the
nodal ministry or NITI Aayog to
facilitate the institutionalisation of
the partner organisation within the
district administration.
Secondly, the framework
recommends that wherever
possible, the partners should
facilitate the presence of a human
resource within the district
administration. However, not
all partners need to position a
human resource within the district
administration if the scale and
the scope of the engagement are
limited. In case of high-intensity
engagements over medium to
long-term, the presence of a
human resource within the district
administration or collaborating with
other partners who already have
positioned a human resource within
the district administration office is
recommended.
Step
Collaborate
Figure 8.3. The second step of the framework highlights effective
collaboration strategies to overcome bureaucratic resistance.
Action Collaborate with the nodal ministry or NITI Aayog to facilitate the institutionalization of the partner organization within the district administration. Seek possible convergence/overlaps with other partner activities in districts.
Time Frame After identification of districts.
Key Insights Incorporated
1. Institutional engagement reduces bureaucratic hindrances.2. Convergence of partner activities lead to improved engagement outcomes and prevents crowding-in or overlaps.
Challenges Addressed
1. Resistance from district officials and line-departments to incorporate engagements within the practices of the district administration.2. Avoids concentration of partners and re-experimenting in similar engagement practices.
Risks Different nodal agencies – example NITI Aayog and MoHFW – allocate partners working in overlapping domains (Health). Difficult to collaborate unless such forums exists at national levels as recommended in the research. Aspirational Districts Program Moving forward, the engagement
strategy of the development
partner should not be restricted
to the district leadership but
also percolate to the secondary
and tertiary levels of officials,
preferably percolating to
the block/panchayat level.
This is another area where a
representative present within the
district administration encourages
better results from the perspective
of the partners as well as district
officials. The comprehensive
engagement with the district and
not just the District Collector/
District Magistrate allows better
continuity and prioritisation of
the program even in the case of
leadership change. This is critical,
as it has also been highlighted in
the previous section of the report
that the transition in leadership can
often adversely affect the continuity
of partner engagements in a given
district.
MOREOVER, THE GRANULAR ENGAGEMENT AT THE
BLOCK/PANCHAYAT LEVEL FURTHER ALLOWS THE
PARTNERS TO LEVERAGE BETTER SOCIAL AND HUMAN
DEVELOPMENT OUTCOMES BY BREAKING DOWN
NICHE CHALLENGES AT A SMALLER SCALE WHICH ARE
RELATIVELY EASIER TO MANAGE, ESPECIALLY FOR VERY
LARGE GEOGRAPHIC DISTRICTS.
Step
Furthermore, engaging directly
with front-line workers allows
the partners to have a robust
understanding of the capacity of
the human resources responsible for
delivering the partner engagement
services once the resources of
the partner are retracted from
the district at the closure of
engagement. Necessary strategies
to create capacity – especially in
districts facing the challenge of
vacant human resources at the
front lines – can be developed
by the partners at this stage to
ensure sustainable transition
and institutionalisation of the
engagement practices within the
district administration.
Engage 146
Figure 8.4. The third step of the framework highlights effective strategies
for partners to create engagement throughout the district administration
to help programme continuity and effective implementation of engagement
objectives by front line workers.
Action Allocate human resources within the district administration wherever possible.
Ensure clear communication of engagement goals to front-line workers and intra-
district functionaries. Get the buy-in of second-line district officials and Prabhari
Officers.
Time Frame On establishing collaboration and presence in district.
Key Insights
Incorporated
1. Young professionals improve motivation of district administration.
2. Second-line officials facilitate continuity in cases of leadership change.
Challenges
Addressed
1. Discontinued prioritization of engagement activities owing to leadership change in
districts.
2. Low understanding of indicators and end goals among front-line workers.
Risks Creating stakeholder engagement at the district level may be hindered by cultural
differences, time-line commitments of an engagement, and lack of enthusiasm for
partner priorities (as experienced in the case of some low weight indicators).
Aspirational Districts Program Facilitate
Figure 8.5. Facilitating the incorporation of engagement activities within
the district administration ensures that positive engagement activities
continue even after the closure of the partner engagement.
Here, the partners are expected to
tweak and innovate on the existing
solution to address district-specific
niche challenges. This would
further help in the adoption of the
evolved policy practices within the
government institutions across all
levels of the district. The role of the
partner in this stage is expected to
mostly be one of managing change
and overcoming institutional
resistance across the levels of the
district administration. Again, the
presence of a representative in the
district may be helpful in navigating
the change management aspects of
the engagement across the district.
Once the partners have established
a robust engagement across the
district administration and have
successfully operationalised
solutions to bridge critical gaps
within the districts.
The role of the partner can
focus more on facilitating the
operational changes using
knowledge support to the district
administration across levels.
Action Map engagement activities with roles of officials within a district – such as
encouraging ASHA workers to promote nutritious diet plans – and facilitate the
incorporation of engagement activities within the district administration.
Time Frame On successful engagement with all stakeholders within a district.
Key Insights
Incorporated
Creating sustainable engagement practices would require the enthusiastic
participation of the district administration and front-line workers.
Challenges
Addressed
Possible discontinuity of positive engagement activities at the closure of partner
engagements or the program.
Risks Some critical activities – such as financial inclusion – cannot be mapped to
existing roles as no such line-official exists within the district administration. Such
activities are mostly conducted by banks/financial institutions in the districts.
Step 148
Figure 8.6. Mapping partner engagement activities to existing roles/
institutions and monitoring them effectively can create lasting behavioural
change in the district administration.
Embedding the engagement
within the district administration,
the partner can further roll back
into the role of monitoring the
changed practices across the
districts intervening only when
there are hurdles or when
operational feedbacks are needed
by the district administration.
This allows the administration
to gradually imbibe the changed
policy operations and reduces the
dependency on the resources of the
partner.
This approach promotes the
creation of behavioural change
within the district administration by
effectively establishing a positive
feedback loop. Thus, the processes
get disseminated throughout the
district administration. Furthermore,
incorporating monitoring within
the engagement framework allows
partners to overcome the issue of
vacant supervisory positions within
districts. These roles can now be
bridged by the partner engagement
leading to sustainable assimilation
of the activities within the district
administration.
Monitor
Action Once mapped to existing roles/institutions at the district level, actively monitor
the engagement activities performed by the district administration with proper
feedback loops to institutionalize the processes and practices across the board.
Time Frame On successful mapping and facilitation of engagement activities to line-officials in
a district. Strategy should be in place at the initiation of the project itself.
Key Insights
Incorporated
Creating sustainable engagement practices would require the enthusiastic
participation of the district administration and front-line workers.
Challenges
Addressed
Inability to create behavioural change within the district administration to make
partner engagement practices sustainable.
Risks Imbibing practices of partner engagement may take additional time or capacity
building mechanisms for line-officials as low capacity of officials have been
identified as a challenge for partners.
Step Aspirational Districts Program Figure 8.7. By promoting successful engagement practices new
knowledge resources get created which help other districts overcome
similar niche development challenges.
Finally, when a district completely
imbibes and institutionalises
the policy operations that help
them bridge the capacity and
governance gaps within the district,
the partners may promote the
practice as a “proof of concept”
or “best practice” across districts
where similar strategies can then be
imbibed and scaled up.
This would facilitate the reduction
of intra-regional and inter-regional
disparities in partner engagements
as other districts – where the
partner may not be engaging – can
also replicate the best practices
and achieve similar social and
human development outcomes.
Furthermore, it would prevent
the loss of several key informal
learnings from the district that
can be applicable to regions
facing similar niche challenges.
The success stories also act as
inspiration for other districts by
creating a stronger resolve to drive
change. This additional motivation
can also bear a positive impact
on driving change within the
Aspirational Districts.
Promote
Action Publish and disseminate the learnings from engagements to other districts and
partners to induce similar best practices in other districts and global regions.
Time Frame On successful institutionalization of engagement practices within the institutional
structure of the district administration
Key Insights
Incorporated
Scaling-up of partner activities by disseminating innovative models of intervention
or best practices of policy implementation.
Challenges
Addressed
Intra-regional and inter-regional disparities in partner engagements. Loss of
knowledge resources that can promote change in regions facing similar policy
challenges.
Risks Some engagement practices can be context and institution specific within a given
state/district holding little external relevance.
Step Choose the correct domain, region,
and point of intervention by matching
partner and district foals and
orientation using data-driven insights
as indicated by IFC Partner Connect.
Approach partner engagements
with a framework to institutionalise
engagement activities within the
district administration so that the
positive impact continues even
after the closure of the particular
engagement initiative.
Create information symmetries within
the ecosystem to magnify the effects
of the engagements by convergence,
peer to peer learning, and scale-up
best-practices within India, as well as
at a global scale.
Promote the presence of human
and knowledge resources at
the districts to strengthen the
information structure and capacity
of the district officials to facilitate
better performance management,
competition, and convergence.
Engage local youth wherever
possible.
KEY INFERENCES:
HOW TO EFFECTIVELY
ENGAGE?
150 Aspirational Districts Program In this section, the report identifies
the top 10 districts that have been
able to drive the maximum change
from their baseline position till the
end of 2019 and highlight their
corresponding domain partners
facilitating this change. In order to
measure the change, the difference
between the relative positions of
districts vis-å-vis their targets
from their baseline position and
2019 have been considered. This
change has been transformed
into a relative score of 100 for all
the districts to better highlight
the relative improvements per
district from their baseline position.
This means the district that has
travelled the maximum distance
towards its target from its base-
line position has been given a score
of 100. The other districts have
been relatively scored according to
the movement of this district.
A lower score indicates that the
districts have been able to drive
a lower degree of change. One
limitation of such an analysis stems
from the fact that districts that
were closer to meeting their targets
at the baseline would record
lower scores as compared to the
districts that were much further
away, as the scope of movement is
restricted for districts closer to their
respective targets. However, the
niche challenges for the districts
which were further away from
their targets at the baseline would
conversely be steeper making it
harder for them to achieve change.
Once the districts have been
scored, their development partners
working in these domains have
been identified.
Again, this is not a metric to gauge
the relative performance of a
partner organisation. This exercise
is merely indicative of partners
who have been engaged in districts
that were able to drive maximum
change within the given time frame
under the programme. Since the
partners have the advantage of
tracking the field-level happenings
in these change-making districts,
they would eventually be better
positioned to inform the whole
ecosystem about the successful
strategies employed by these
districts to overcome challenges.
TOP CHANGE-MAKERS:
WHICH DISTRICTS HAVE BEEN ABLE TO DRIVE
THE MAXIMUM CHANGE WITH THE HELP OF
PARTNERS? Health &
Nutrition
In the Health and Nutrition sector,
the top 10 districts that have been
able to drive the maximum change
have all been effectively supported
by the presence of development
partners within the districts. Five
of the ten districts in the top 10
have registered the presence of
more than one partner in the
Health and Nutrition sector.
One partner has been facilitated
by the Ministry of Health and
Family Welfare (MoHFW) and the
other partner has been facilitated
either by Ministry of Home Affairs
(MHA) for LWE districts or NITI
Aayog. Since it has already been
mentioned that the Health and
Nutrition sector has seen the best
performance across all districts, it
can be indicated with some degree
of confidence that the partner
ecosystem has been particularly
effective in supporting the district
administration in this sector. It is
also perhaps relevant to note
here that almost 40% of all
partner engagements within the
Aspirational Districts Programme
are related to the sector of
Health and Nutrition.
District ScoreDomain Partners Engaged
Ranchi100USAID/IPE Global, Tata Trust
Sukma90.10Tata Trust
Nuapada 83.38UNFPA
Balrampur 80.24Piramal Swasthya, UNICEF
Wayanad 79.72UNICEF
Sheikhpura 79.52BMGF, Piramal Swasthya
Barwani 76.69Piramal Swasthya, Tata Trust
Siddharthnagar 75.73BMGF, Plan International
Firozpur 72.75USAID/IPE Global
Kupwara 72.45NIPI
Sector
152 Education
In the domain of Education, eight of
the top 10 districts that have been
able to drive the maximum change
are supported by development
partners working in the same domain.
Four of these districts (Garhwa,
Ranchi, Rajgarh, and Palamau)
are LWE districts from the state
of Jharkhand that have made their
place in the top 10 change-making
districts in the domain of education.
All these districts are partnered by
Tata Trusts that operates across
multiple domains in these districts,
including education. The other four
districts are mentored by Piramal
Foundation. Moving forward, more
partner engagement in the domain of
education is desirable as the sector
is given 30% overall weightage
within the programme but accounts
for only 10% partner engagements.
However, it must also be stated here
that several partners working within
multiple domains – such as Tata
Trusts and Lupin Foundation – are
also engaging with the districts in the
domain of education. Some of the
best case studies documented in the
field of education within the scope
of this research come from the LWE
districts of Jharkhand, where Tata
Trusts has been executing innovative
education initiatives such as “Project
Smart Shala” and “Project Angan”.
District Score Domain Partners Engaged
Jaisalmer 100Piramal Foundation (Education)
Hailakandi 89.68 No Domain Partner
Balrampur 88.38 Piramal Foundation (Education)
Sonebhadra 87.52 Piramal Foundation (Education)
Singrauli 85.44 Piramal Foundation (Education)
Rajgarh 84.67 Tata Trust*
Garhwa 82.24 Tata Trust*
Ranchi 81.65 Tata Trust*
Kupwara 79.14 No Domain Partner
Palamu 74.96 Tata Trust*
Sector
Aspirational Districts Program Only two out of the top 10
districts that have been able
to drive change in the domain
of Agriculture and Water
Resources have been supported
by a development partner
organisation. The significant
improvement of Andhra
Pradesh is also visible in this
analysis, as two out of its
three Aspirational Districts
have made it to the list. On
the whole, this indicates that
there are a lot of opportunities
for partners to engage in this
particular domain as districts
would require significant
handholding to achieve their
programme targets within this
particular sector.
District Score Domain Partners Engaged
Y.S.R. 100No Domain Partner
Bahraich 78.18 ITC Ltd
Vizianagaram 77.92 No Domain Partner
Fatehpur 75.75 No Domain Partner
Wayanad 75.50 No Domain Partner
Kupwara 73.71 No Domain Partner
Khunti 73.38 No Domain Partner
Siddharthnagar71.82 No Domain Partner
Baran 70.12 ITC Ltd
Bokaro 69.70 No Domain Partner
Agriculture
& Water
Resources
Sector
154 Financial Inclusion is another
sector where there is significant
scope for new partners to
engage and for existing partners
to expand their engagements
with districts. As discussed
within the scope of the DTF
Analysis and the Key Insights
section above, owing to its
low weightage (5%) in the
programme, Financial Inclusion
is often not prioritised either
by the district administration
or by the partner ecosystem.
Only one development partner
organisation is currently working
in this domain. Odisha and
Chhattisgarh have emerged
as two states that have been
able to drive the maximum
change in the domain of
Financial Inclusion compared
to all the other districts under
the programme. The top 10
change-makers in the domain
of Financial Inclusion are as
follows:
District Score Domain Partners Engaged
Nuapada 100 No Domain Partner
Bhadradri-
Kothagudem
95.37 No Domain Partner
Nawarangpur 73.72 No Domain Partner
Mahasamund 50.45 No Domain Partner
Dhenkanal 46.34 No Domain Partner
Rajnandgaon 41.17 No Domain Partner
Kanker 39.78 No Domain Partner
Wayanad 35.04 No Domain Partner
Moga34.99 No Domain Partner
Bastar 33.96 No Domain Partner
Financial
Inclusion
Sector
Aspirational Districts Program Like Financial Inclusion, several
districts in the domain of Skill
Development have a broad gap
from their programme targets
giving scope for more partners
to engage in this domain.
Districts supported by CII have
done well under this sector.
Four out of the 10 districts in
the top 10 are supported by
CII. However, it is important to
note that the only two districts
that have been able to achieve
or exceed their programme
targets in the country, Giridih
and Ramgarh from Jharkhand,
currently have no development
partners attached to them. The
top 10 change-makers in the
domain of Skill Development
are as follows:
DistrictScore Domain Partners Engaged
Giridih100 No Domain Partner
Ramgarh89.04 No Domain Partner
Sheikhpura82.38 CII
Ramanathapuram 81.09 No Domain Partner
Khagaria80.18 No Domain Partner
Baran75.59 Fuel, L&T, and CII
Malkangiri72.84 No Domain Partner
Latehar71.73 No Domain Partner
Barwani71.65 CII
Damoh69.85 CII
Skill
Development
Sector
156 Five out of the top 10
districts are supported by
development partners for
Basic infrastructure. Of these,
only one district is supported
by a development partner
dedicated to the domain of
Basic Infrastructure, while the
other four districts are LWE
districts that are supported
by Tata Trusts. Existing
government missions – such
as SAUBHAGYA and Swachh
Bharat – have addressed this
sector effectively. Moving
forward, partner engagement
in domains such as internet
connectivity in panchayats
and the creation of capacity
among local youth to establish
common services centres
at the panchayat level can
be considered. The top 10
districts that have been able
to drive the maximum change
under the programme are as
follows:
District Score Domain Partners Engaged
Khunti 100Tata Trust*
Baksa98.68 No Domain Partner
Bhopapalli 97.72 No Domain Partner
Sukma92.17 Tata Trust*
Giridih 91.99 Tata Trust*
Khandwa 91.06 Piramal Water
Godda90.02 No Domain Partner
Rajgarh 89.78 Tata Trust*
Ribhoi 88.94 No Domain Partner
Sheikhpura 87.94 No Domain Partner
Basic
Infrastructure
Sector
Aspirational Districts Program The influence of partners is seen most
significantly in the domain of Health
& Nutrition.
Financial Inclusion, Skill Development,
and Agriculture & Water resources
remain the most challenging sectors
to drive change.
Partners intending to support and
expand can select some of the
change-making districts which
currently lack external support to
further enhance their performance.
The analysis in this report and the IFC
Partner Connect tool can be useful in
this case.
The ability of the districts to drive
change irrespective of the support
from external partner organisations
in some cases may indicate that
the competition, convergence, and
collaboration within Aspirational
Districts Programme is able to drive
change in some cases irrespective
of the support from the partner
ecosystem. Partners can consider
moving into such districts for short
to medium term engagement in
order to help these districts achieve
saturation.
KEY INFERENCES:
TOP CHANGE-MAKERS
158 Aspirational Districts Program 160
RECOMMENDATIONS
09 Aspirational Districts Program RECOMMENDATIONS 162
STREAMLINING THE SURVEY
AND COLLECTION MECHANISMS
UPDATING PLAN OF ACTION
BASED ON NEW LEARNINGS
Recommendation Detailed Steps
Narrow Pool of Indicators
There is immense scope of streamlining the chosen group of indicators that form the basis of competition among the aspirational districts. For instance, indicators like the percentage of pregnant women taking nutrition and those having severe anaemia, treated are heavily correlated (0.89). It might be ideal to resolve such duplication of assessment.
Adjust frequency of data collection based on type
Not all indicators show change at a similar frequency as seen in the study. So, taking this into account, survey methods should be adjusted accordingly. Indicators that present change over the long-run should be assessed on an annual basis while the short-run indicators can continue to be assessed quarterly. This would also improve survey reliability.
Digitalisation of data mechanisms
The districts would benefit from a more real-time mechanism of data collection and dissemination. Currently, there is a gap of a few months between survey collection and accessibility of the data by districts. This can be improved if the process is digitised and districts can access the data with a minimal lag.
Recommendation Detailed Steps
Peer Group Comparison
Districts can assess where they stand on different parameters and in which sectors have they achieved their targets. Based on that, they can plan their future course of action. By assessing which tier group do they lie in they can draw learnings from their tiers and those above them.
Relative Movement across Regions
An assessment presented in the Mobility Matrix provides them with the data on whether they have improved, worsened or retained status quo. These achievements/failures can be traced back to the policies to understand What Works.
Best Practices of Leaders
The study is supplemented with case studies on some of the best practices for the leading districts across sectors. The districts can modify the learnings made from these practices based on their local requirements across different parameters.
The following recommendations are indicative of the way forward for the programme and includes several steps that are already being addressed, especially with the building of a new dynamic dashboard . Aspirational Districts Program DRIVING TARGETED INVESTMENT
THROUGH PARTNER ECOSYSTEM
LEVERAGING DATA TO DESIGN
EFFECTIVE EVALUATION SYSTEMS
Recommendation Detailed Steps
Defining investment
intensity through Distance to Frontier analysis
The partners should define their geography of investment based on their intensity of engagement. The appropriate geography can depend upon the length of their engagement. For instance, the partners that plan to engage for a longer period can choose districts that are farthest away from their targets based on the Distance to Frontier analysis.
Building partner engagement based on the 6 Point Framework
The study has developed a Six Point Framework across three major phases of partner engagement that can create better engagement outcomes for partners. The framework is targeted to be utilised by the development partners to leverage better engagement outcomes and promote institutionalisation of partner activities within the district administration.
Leveraging the IFC Partner Connect to drive engagement
Data visualisation and analytics can be utilised to create interactive dashboards, that can help in facilitating partner engagements and CSR in Aspirational Districts. IFC Partner Connect is one such interactive dashboard where partners can identify the domain, the region, and the point of engagement as per the requirement of the engagement profile. It also enables partners present in a district to identify potential areas of expanding their engagements.
Recommendation Detailed Steps
Defining Peer Groups
Assessment of districts should be done based on the standing of comparative peer groups. It has been seen that districts that start at a relatively low level on the development parameters show more rapid improvement over time since they have more opportunity to grow and also draw lessons from ideas that have been implemented elsewhere.
Conducting and Leveraging a Baseline Study
While extending the programme or replicating it across different geographies, it is instructive to conduct a baseline study and choose indicators that have scope for improvement. The study shows that indicators that had already attained near-saturation before the start of the aspirational districts programme show no significant boost in incremental change on introduction of the programme.
Examining the nature of indicators
While building evaluation mechanisms for projects like Aspirational Districts, the nature of the indicators should be kept in mind. The study shows that all the indicators do not grow at the same rate by using two categorisations: Ease of Implementation and Type of Indicators. It is observed that long-term indicators have low rate of growth compared to medium- and short-term indicators. Also, impact indicators are easier to implement as compared to outcomes. 164
ENGAGING IN CUSTOMISED
LOCAL LEVEL INTERVENTIONS
Recommendation Detailed Steps
Awareness Campaigns
It is observed that in many cases there is not enough demand for basic health and education infrastructure, or benefits of government programmes don’t reach the actual targeted groups due to lack of knowledge. In such cases, awareness campaigns are useful as they aid in reaching out to the populations that have stayed aloof from the development process. They also facilitate a common platform for engagement, thereby, helping in integration of actors and beneficiaries.
Involving young professionals within grass-root administration
Given one of the major problems is continuity in leadership, it is important that many young professionals are engaged that work directly at the local level and act as a common link between the partners and local government administration. It not only promotes continuity of engagements but also improves the motivation of bureaucrats leading to higher social and economic development.
Collaborating with locals
Collaboration with the individual functionaries helps in leveraging the social network and enhances the outreach capacity of the district administration in integrating the population. It also opens the door for the introduction of community-based intervention models, which facilitates stakeholder participation. For instance, women-driven institutions such as Self-Help Groups and Anganwadis have been particularly crucial in the delivery of schemes. Aspirational Districts Program APPENDIX
LIST OF ASPIRATIONAL DISTRICTS
StateDistricts
Andhra Pradesh Visakhapatnam, Vizianagaram, Y.S.R.
Arunachal Pradesh Namsai
AssamBaksa, Barpeta, Darrang, Dhubri, Goalpara, Hailakandi, Udalguri
BiharAraria, Aurangabad, Banka, Begusarai, Gaya, Jamui, Katihar,
Khagaria, Muzaffarpur, Nawada, Purnia, Sheikhpura, Sitamarhi
Chhattisgarh Bastar, Bijapur, Dakshin Bastar Dantewada, Kondagaon, Korba,
Mahasamund, Narayanpur, Rajnandgaon, Sukma, Uttar Bastar
Kanker
GujaratDahod, Narmada
HaryanaMewat
Himachal Pradesh Chamba
Jammu & Kashmir Baramula, Kupwara
Jharkhand Bokaro, Chatra, Dumka, Garhwa, Giridih, Godda, Gumla, Hazaribagh,
Khunti, Latehar, Lohardaga, Pakur, Palamu, Pashchimi Singhbhum,
Purbi Singhbhum, Ramgarh, Ranchi, Sahibganj, Simdega
Karnataka Raichur, Yadgir
KeralaWayanad
Madhya Pradesh Barwani, Chhatarpur, Damoh, Guna, Khandwa (East Nimar), Rajgarh,
Singrauli, Vidisha
Maharashtra Gadchiroli, Nandurbar, Osmanabad, Washim
ManipurChandel
Meghalaya Ribhoi
MizoramMamit
Nagaland Kiphire
OdishaBalangir, Dhenkanal, Gajapati, Kalahandi, Kandhamal, Koraput,
Malkangiri, Nabarangapur , Nuapada, Rayagada
PunjabFirozpur, Moga
Rajasthan Baran, Dhaulpur, Jaisalmer, Karauli, Sirohi
SikkimWest District
Tamil Nadu Ramanathapuram, Virudhunagar
Telangana Asifabad (Adilabad), Bhoopalapalli (Warangal), Khammam
TripuraDhalai
Uttar Pradesh Bahraich, Balrampur, Chandauli, Chitrakoot, Fatehpur, Shrawasti,
Siddharthnagar, Sonbhadra
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