Public provisioning of basic facilities such as health and education, remains crucial for marginalised populations. In the context of the decentralised structure of governance and fund allocation in India, Guha, Jyotishi and Hatekar assess public provisioning at the disaggregated levels, and the gaps therein. Leveraging the Mission Antyodaya dataset, they create a ‘Rural Deprivation Index’ which can be used to examine the status of provisioning across blocks, villages, districts and states. 

The recent NITI Aayog Report on the ‘National Multidimensional Poverty Index’ (NMPI) has rekindled the discussion on poverty. The latest poverty figures indicate that public provisioning of social infrastructure and human capital development facilities is crucial for a large proportion of the population, which remains marginalised. Such public provisioning can enhance capabilities of individuals and address ‘unfreedoms’ (Sen 1999), create social safety nets for vulnerable groups, reduce poverty, and ultimately raise economic growth.

Given the decentralised structure of governance and fund allocation in India, we assess public provisioning at the disaggregated levels, and the gaps therein. For this purpose, we create an index called the Rural Deprivation Index (RDI), which highlights the status of provisioning of basic infrastructural, education and health services – mapped across blocks, villages, districts, and states.

The data

The RDI is created using the Mission Antyodaya dataset, comprising information on public provisioning and related outcomes at the village and Gram Panchayat (GP) levels¹. Adopted in the Union Budget 2017-18, Mission Antyodaya is a State-led initiative of creating a framework of convergence and accountability at the GP level, to monitor the use and management of resources allocated by 27 ministries/departments of the Government of India under various programmes for rural development (National Institute of Rural Development and Panchayati Raj, 2018). An annual survey of GPs across the country is an important aspect of the Mission Antyodaya framework. It is carried out coterminous with the People’s Plan Campaign (PPC) of the Ministry of Panchayat Raj. The purpose of the Mission Antyodaya survey is to lend support to the process of participatory planning for the Gram Panchayat Development Plans (GPDP). The Mission Antyodaya Portal, which is publicly accessible, has data for 267,205 GPs (out of a total of 269,943), covering 648,358 of 667,933 villages in the country. The currently available dataset refers to the year 2019-20.

Provisioning versus outcomes

For creating this index, we exclusively analysed provisioning, and not outcomes, for two reasons. First, we envisage the index to measure provisioning in ‘quantitative’ terms. Examining outcomes relating to health, education etc. will require the additional evaluation of the quality of provisioning. The policy tools required for setting up a school, for instance, are different from those needed to ensure that the school is running well. By focusing solely on the provisioning aspect, we can develop insights into the first-order matter of how budgets allocated at the district level are utilised at the GP or block level for specific purposes².

Secondly, unlike the provisioning variable, the data on outcome variables are likely to have a substantial degree of error and dynamicity – even though these are collected through rigorous surveys. To take an example from within the Mission Antyodaya dataset, the number of out-of-school children in a village is likely to be highly dynamic and hard to measure. On the other hand, data on basic provision, like whether there is a primary school in the village, or whether the village is connected to an all-weather road, is less problematic. This data does not have to be gathered from any records but is starkly visible to the surveyor and well-known to everyone in the village. During our ‘ground truthing’ exercise, we learned that provisioning data supplied directly from the village by the Gram Pradhan or Panchayat Secretary through the Panchayat office or line departmental functionaries (for example, teachers) who are directly engaged at the village level, are much more likely to be correct compared to data that have to be obtained from records computed from scratch. Although outcome variables are important indicators of welfare and well-being, provisioning remains a prerequisite to achieve any desirable outcome – this led us to focus on provisioning indicators.

Creating the Rural Deprivation Index

The first step in our analysis is to identify the indicators of basic deprivation; we select 22 parameters for the purpose (Table 1).

Table 1. Dimensions of deprivation

No.	Parameter	Indicator	Dimension
1	Irrigation	All cultivated land is rain fed	Infrastructure
2	Roads	The village is not connected to an all-weather road
3	Internal Roads	Village is not covered with internal pucca road
4	Public Transport	No form of public transport (bus/van/auto) is available
5	Electricity	No electricity in the village
6	Bank	Brick and mortar bank branch is farther than 10 kilometres
7	ATM	Nearest ATM is farther than 10 kilometres
8	Telephone	No mobile or landline facility is available in the village
9	Broadband	Broadband not available in the village
10	Market	Nearest market (mandi/regular market/weekly market) is farther than 10 kilometres
11	Ration Shop	Nearest Ration shop is farther than 10 kilometres
12	Health Facilities	Primary health centre/Sub-centre/Community health centre is farther than 10 kilometres	Health
13	Drainage	Lack of any drainage facilities
14	Anganwadi	Non-availability of anganwadi (childcare) centre in the village
15	Mother and Child Health	Nearest mother and child health facilities is farther than 10 kilometres
16	Toilets	Village has home/homes without sanitary toilets
17	Piped Water	Village has no households with piped water
18	Primary School	Nearest primary school is farther than 10 kilometres	Education
19	Middle school	Nearest Middle School is farther than 10 kilometres
20	High School	Nearest High School is farther than 10 kilometres
21	SSC School	Nearest SSC School is farther than 10 kilometres
22	Vocational Training	Nearest vocational training centre/polytechnic/Industrial Training Institute/Rural Self Employment Training Institute/Deen Dayal Upadhyaya Grameen Kaushal Yojana centre is farther than 10 kilometres

Note: Primary schools are generally up to grade 5, middle schools are from grade 6 to grade 8, high schools consist of grades 9 and 10, and SSC (Secondary School Certificate) schools include grades 11 and 12. However, since education is a concurrent subject there are minor variations across the states and union territories.

Next, we classify the indicators into three dimensions namely infrastructure, education, and healthcare. A value of one is assigned if the village is deprived on that particular indicator, zero otherwise. We then calculate the deprivation score for each dimension (proportion of indicators that hold true), and average across the three dimension to get the composite deprivation score for each village. At this point, we  categorise villages into those that are deprived (composite score of 0.23 or more, or deprived of at least five of 22 indicators) and those that are not. It is noteworthy that the chosen deprivation parameters represent ‘deep deprivations’ as they pertain to the most basic provisioning. Hence ‘deprived’ villages are in fact deeply deprived.

Table 2 presents the deprived village count across states, that is, the proportion of villages in the state that are deprived. We also calculate the intensity of deprivation of states, which is the average deprivation among the deprived villages of a state. Finally, we compute a state RDI, defined as the average deprivation score across all villages of a state.

Table 2. State-level deprivation

State	Deprived Village Count	Intensity of Deprivation	RDI	Rank
Kerala	0.009	0.003	0.000	1
Haryana	0.143	0.042	0.006	2
Dadra and Nagar Haveli and Daman and Diu	0.186	0.050	0.009	3
Gujarat	0.172	0.056	0.010	4
Punjab	0.198	0.060	0.012	5
Tripura	0.219	0.079	0.017	6
Tamil Nadu	0.265	0.083	0.022	7
West Bengal	0.314	0.097	0.030	8
Goa	0.299	0.115	0.034	9
Andaman and Nicobar Islands	0.317	0.118	0.037	10
Uttar Pradesh	0.349	0.111	0.039	11
Telangana	0.347	0.122	0.042	12
Jammu and Kashmir	0.355	0.129	0.046	13
Karnataka	0.378	0.133	0.050	14
Bihar	0.455	0.157	0.072	15
Sikkim	0.463	0.165	0.076	16
Andhra Pradesh	0.453	0.184	0.083	17
Rajasthan	0.499	0.184	0.092	18
Chhattisgarh	0.487	0.195	0.095	19
Himachal Pradesh	0.510	0.188	0.096	20
Maharashtra	0.526	0.206	0.109	21
Uttarakhand	0.602	0.213	0.128	22
Madhya Pradesh	0.608	0.227	0.138	23
Odisha	0.665	0.266	0.177	24
Mizoram	0.644	0.282	0.182	25
Jharkhand	0.758	0.299	0.227	26
Assam	0.773	0.311	0.240	27
Ladakh	0.849	0.351	0.298	28
Manipur	0.769	0.405	0.312	29
Nagaland	0.842	0.416	0.350	30
Meghalaya	0.859	0.433	0.372	31
Arunachal Pradesh	0.892	0.537	0.479	32

As can be seen from Table 2, Kerala is the best performing Indian state, with the lowest rural deprivation. Interestingly, Maharashtra defies the usual expectation and is ranked 21, behind Uttar Pradesh, Bihar, and Rajasthan of the erstwhile “BIMARU” (Bihar, Madhya Pradesh, Rajasthan and Uttar Pradesh) states.  The positioning of North-eastern and hilly states to an extent can be attributed to the terrain and topography.

Reflections

The RDI based on the Mission Antyodaya database can prove to be a valuable tool for objective measurement of the implementation of developmental initiatives at the grassroots level in India. Given that the Mission Antyodaya database is updated every year following annual surveys, it may be used in decentralised planning and assessment of convergence in the country’s village-level amenities. The research community in India and outside has just begun to appreciate the vast opportunities opened up by the public availability of such a massive granular database (seem for example, work by Gharat et al. (2024) and Chathukulam et al. (2021)).

Our methodology allows us to dig down to the village and GP level. Starting with the state level, we can extract the contribution of various sub-regional levels to overall multidimensional deprivation. This not only helps us to identify the deeply deprived villages, but also the dimensions of deprivation in need of most policy attention. Thus, this index can aid in precisely identifying the dimensions and regions in which to plan targeted interventions at the GP, block, district and state levels.

To cite an example, Rajasthan is ranked 18 on the RDI in Table 2. However, some of the state’s districts, like Jaisalmer, Barmer, Jodhpur and Bikaner, have considerably high deprivation levels, as compared to neighbouring districts (Figure 1). This highlights the across-district variations within a state with respect to deprivation levels.

Figure 1. District-wise Rural Deprivation Index 

The variation in derivation can also be explored at the village level. Figure 2 shows the percentage of villages deprived in each of the districts in India. Going back to the example of Rajasthan, we observe that in the four districts mentioned above, over 90% of villages are multidimensionally deprived.

Figure 2. Percentages of deprived villages across districts in India 

Another deep dive is possible by analysing the extent (intensity) of deprivation. Figure 3 provides the intensity of deprivation of villages across all districts. For the same four districts of Rajasthan, we observe that for Jaisalmer and Bikaner the deprivation intensity is 40-50%, while for Jodhpur and Barmer it is between 30-40%. In other words, the deprived villages in Jaisalmer and Bikaner are deprived on 10-11 parameters, while that of latter the villages are deprived on 6-8 parameters.

Figures 3. Intensity of rural deprivation 

In conclusion, with such detailed understanding of deprivation on parameters at a village or district level, more directed interventions can be planned to address the needs and help overcome deprivation.

This analysis is part of Development Dialogue with Data Initiative at the School of Development, Azim Premji University. The content and opinions expressed are of the authors and are not necessarily endorsed by/reflect the views of Azim Premji University or the I4I Editorial Board.

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Notes:

1. Under the Panchayati Raj system, a Gram Panchayat is responsible for the governance of a village. A village may be further divided into smaller units called wards. A group of villages constitute a block, which in turn is a sub-division of a district.
2. Based on the recommendation of the Finance Commission, the Ministry of Finance prepares operational guideline for the transfer of funds to the rural local bodies (RLB). Further details are available here.

Further Reading

• Chathukulam, Jos, Manasi Joseph, Rekha V, CV Balamurali and TV Thilakan (2021), “Mission Antyodaya: Well Envisioned but Poorly Understood”, Gandhi Marg Quarterly, 43(2): 151-186. Available here.
• Gharat Sanket, Prasanna Surathkal, Puja Guha, Amalendu Jyotishi and Neeraj Hatekar (2024), Multidimensional Deprivation Index and Spatial Clustering, Economic and Political Weekly, 59(3).
• Khosla, R, S Hasan, J Samuels and B Mulyawan (2002), ‘Removing unfreedoms: Citizens as agents of change’, United Nations Habitat Program Liaison Office, Brussels, Background Support Project Document. Available here.
• Sen, A (1999), Development as Freedom, Oxford University Press, New York.