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Abstract
It is widely acknowledged that top-down support is essential for bottom-up participatory projects to be effectively implemented at scale. However, which level of government, national or sub-national, should be given the responsibility to implement such projects is an open question, with wide variations in practice. This paper analyses qualitative and quantitative data from a natural experiment of a large participatory project in the state of Rajasthan in India comparing central management and state-level management. We find that locally managed facilitators formed groups that were more likely to engage in collective action and be politically active, with higher savings and greater access to subsidised loans.
Acknowledgments
The authors are indebted to Radha Khan for supervising the qualitative fieldwork, Ritwik Sircar and Anirvan Chowdhury for outstanding research assistance, SRI-IMRB for collecting the quantitative data for this study, the Government of Rajasthan for sharing valuable data, PRADAN for valuable initial conversations, and the staff of PRADAN, PEDO, SERP and the Rajasthan SHG federations for their support. We are grateful to Georgetown University and the South Asia Food and Nutrition Security Initiative for their financial support. For excellent comments and conversations, we thank the two anonymous referees, Radha Khan, Sanjay Sharma, Irfan Nooruddin, Milan Vaishnav, Anders Olofsgard and participants of the India Politics Workshop in Washington, DC. This paper reflects the individual views of the authors and does not in any way represent the official position of the World Bank or its member countries.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. Devolution is typically defined as a process of transfer of political, administrative and fiscal management powers between central government and lower levels of government, primarily operating at city and region levels (Potter, Citation2001).
2. Mansuri and Rao (Citation2012) review the literature on facilitation, documenting its central role in community driven projects. Perry et al. (Citation2014) review the history of community health care worker programmes in low-, medium- and high-income countries. They argue that in the past three decades, community health workers have played a critical role in helping health systems achieve their potential, regardless of a country’s level of development.
3. The programme has been modified considerably over the last five years and now gives states considerable leeway in how it is managed.
4. The National Rural Livelihoods Mission is funded by a $1 billion loan from the Government of India, and a $4.1 billion budget from the Government of India. The World Bank funded component of the project is focused on India’s poorest states (including Rajasthan) and is known as the National Rural Livelihoods Project (NRLP). For the sake of brevity we will refer to the project as the NRLM in this paper, though our focus is technically on the NRLP.
5. Headed by Bunker Roy, the SWRC was established in Rajasthan in 1972. It began with a focus on water and irrigation but its mission soon expanded to empowerment and sustainability. It rose to prominence in the 1990s. Roy has been named one of the 100 most influential people in the world by TIME magazine.
6. As of March 2013, Pradan worked with 18,736 SHG’s across seven states, representing a total membership of 252,070 rural poor women. These SHG’s have mobilised a total savings of 1230 Million Rupees.
7. The official Implementation Status and Results Report, written in February 2013, classifies the ‘Overall Risk Rating’ of the project as ‘Substantial’ and mentions that the RRLP was at least a year behind schedule and had only spent 0.54 per cent of its allocated funds in the first 16 months of its operation (India – Rajasthan Rural Livelihoods Project [RRLP]: P102329 – Implementation Status Results Report: Sequence 05, World Bank, 2013).
8. In the 1st phase, SERP deployed 20 PRPs on 23 February 2013 and 20 CRP teams on 9 March 2013. These have been deployed in five blocks of five RRLP districts, namely Baran, Churu, Jhalawar, Kota, Tonk. The rotation was to last until 7 April 2013. The next batch of 22 teams of CRPs and PRPs was deployed by the SERP in the month of May 2013 and would include blocks in Dungarpur as well as Udaipur districts.
9. The blocks were Bari and Bashedi of Dholpur district, Dausa block of Dausa district, Taranagar of Churu district, Simalwada block of Dungarpur district, Kolayat of Bikaner district, and Sarada of Udaipur district.
10. The National Mission Management Unit (NMMU) of the NRLM had planned in 2012 to create 100 community managed and community driven intensive Resource Blocks across the country. The goal was to develop, through an intensive social mobilisation process, a few blocks (two to six blocks in NRLP/NRLM states) as role models.
11. We chose these four blocks because this is where the key organisations were scaling up their efforts at that particular time. Balance tests of these areas suggest that they were similar to each other, and also similar to other RRLP districts of the state.
12. This was done in a two-step process. In July 2013, the authors and the research team prepared preliminary questions in a structured questionnaire for facilitators with open-ended responses possible for many questions. The interview transcripts were read, analysed and compiled into a report that was circulated for deliberation within the research team. This was then used to refine and revise the survey questionnaire, which was then translated into Hindi and Telugu by the survey firm. In March 2014, the questionnaire was pretested by the authors on facilitators from SERP as well as PRADAN.
13. We originally sent survey enumerators to Andhra Pradesh to interview all the SERP facilitators in the entire state of Rajasthan. The head of the organisation, however, denied our surveyors access and refused to allow any surveys in the state of Andhra Pradesh. We were able to complete our surveys only when the women went back to Rajasthan to be deployed for the RRLP where the Government of Rajasthan gave us permission for the interviews. Our sample is a census of all SERP facilitators in our selected blocks. Approximately 10 women did not participate in the survey due to limitations of their schedules.
14. 2914 control households in six villages sampled per block in each of the 19 non-RRLP blocks in the same districts as the treatment villages were also surveyed, but we do not analyse the control data in this paper.
15. We directly observed that SERP facilitators had access to a set of training materials and methods brought with them from Andhra Pradesh.
16. The question was worded as follows: ‘Provide any example of an SHG woman engaging in collective action?’
17. Official data were collected by a strong team led by a statistician, Mr. Hardeep Chopra.
18. The survey was conducted by government officials who manage the project at the block level.
19. Due to the constraints of the data (which was anonymised to preserve respondent privacy), we are unable to match specific SHGs to specific facilitators.
20. This is known as the ‘panchsutra’ in the RRLP manual.
21. This method attempts to reduce small-sample bias in standard logistic regression. The method has been shown to produce finite, consistent estimates of regression parameters in the case where the maximum likelihood estimates do not exist (Firth, Citation1993). This is needed because some of our outcomes (such as the dummy variable that measures ‘following RRLP rules’) occurs rarely in only specific groups of the population, which are included as controls. The penalised likelihood estimator, implemented in STATA as ‘firthlogit’, addresses this issue.
22. Note that we omit district-level fixed-effects from the regressions on participation in entitlement programmes because these programmes are implemented at the district and block level. Given that our key explanatory variable also varies at the block level, there is insufficient variation in the sample to produce unbiased and reliable estimates.