Presentation on theme: "Targeting Efficiency: How well can we identify the poor? IFMR:CMF Seminar May 5, 2008 Jyoti Prasad Mukhopadhyay Abhijit Banerjee, Esther Duflo, Raghabendra."— Presentation transcript:
Targeting Efficiency: How well can we identify the poor? IFMR:CMF Seminar May 5, 2008 Jyoti Prasad Mukhopadhyay Abhijit Banerjee, Esther Duflo, Raghabendra Chattopadhyay and Jeremy Shapiro
Motivation Nearly all poverty alleviation programs target a particular sub-population –Thus, accurate targeting is crucial to program success Evidence that targeting is often sub-optimal –National Sample Survey Organization finds that 18% of the wealthiest 20% of rural population (ranked by monthly per capita expenditure) held Below Poverty Line (BPL) rationing cards. Which targeting methods work? Which don’t?
This Study Evaluates the targeting efficiency of... –various government anti-poverty programs –Targeting the Ultra Poor, operated by Bandhan (a Kolkata MFI) –Participatory Rural Appraisals (PRAs)
Preview of Results Government targeting –Does not identify the poorest of the poor In our sample, eligible households appear no worse off than ineligible households Bandhan’s targeting –Identifies a group which is disadvantaged in some respects Own less land and fewer assets; lack credit access Per capita expenditure does not appear lower PRA –Generates wealth ranking of participants which accords with various measures of poverty
Overview of Bandhan’s Program Name of the program: Targeting Hard-core Poor (THP) Background: Benefits of microfinance do not accrue to the poorest of the poor (Morduch 1999, Rabbani et al 2006). Microfinance Institutions (MFIs) are in general reluctant to lend to the poor. Reasons: ultra-poor households tend to use loan for meeting consumption needs Productive investment of loan is unlikely Ultra-poor households are extremely vulnerable to shocks and hence more prone to default Murdoch (1999) aptly commented, “poorer households should be served by other interventions than credit.” Objective of the program: To provide income generating assets: livestock, inventory etc. as grant to help ultra poor households secure a regular source of income. Also imparting training and other assistance required for starting a small scale enterprise so as to graduate them to potential microfinance clients.
Area of intervention: Murshidabad district, West Bengal Why Murshidabad district? This is one of the poorest districts of West Bengal. district level statistics: HDI Ranking (2004) -15 (out of 17 districts) Targeted no. of beneficiaries: 300 To date, the identification process has occurred in 60 villages, with an average of 15 households identified as Ultra Poor in each village and 300 beneficiaries have received assets so far. Overview of Bandhan’s Program
Identification of Ultra-poor households(Potential beneficiaries) Half of the identified beneficiaries are randomly chosen for asset distribution Enterprise Selection Training Asset distribution Weekly Follow-up and monitoring Key Phases of the Program
The Identification Process Identifying the poorest villages and hamlets of the district Conducting PRAs in the identified hamlets (Social mapping) Identifying ultra-poor households through wealth-ranking during PRA First verification of the identified ultra-poor households: household survey Second verification: by the THP program coordinator Final selection
What is Wealth Ranking? Wealth ranking is done after the completion of social mapping in PRA. It is an effective way of classifying households into different categories based on household’s occupation, assets, land holdings and general economic well being. Each household is given a rank in a scale of 1-6 corresponding to each category where lower ranks corresponds to relatively better-off households. Lively discussion among villagers generate the most precise definition of (relative) poverty and facilitate accurate wealth ranking.
The Second and Final Verification The second and final verification is done by THP program coordinator. During verification, the program coordinator observes economic condition, educational attainment and nutritional status of the women and children of the households. Some mandatory requirements to be eligible for obtaining grants are as follows: The household must have at least one active woman capable of undertaking some enterprise the household must not be associated with any MFI (in keeping with the aim of targeting those who lack credit access) or receive sufficient support through a government aid program primary source of income should be informal labor or begging land holdings below 20 decimals no ownership of productive assets other than land no able bodied male in the household and having school-aged children working rather than attending school
Data Collection At Bandhan’s request, we interviewed households identified as Ultra Poor by Bandhan and other poor households –Conducted economic census (similar to that used for government targeting) in 5 villages where Bandhan operates Ultra Poor program –Identified poorer population from census –From this population, interviewed 170 random households not identified by Bandhan as Ultra Poor –Also interviewed 92 Ultra Poor households
The Dataset: Summary Statistics
Targeting Efficiency of Government Programs Targeting for many government programs is based on BPL census –Concern that census incorrectly classifies households (Jalan and Murgai, 2007) –Speculation that lists of BPL households are manipulated to include non-poor households (Mukherjee, 2005) To assess these concerns, we compare recipient and non-recipient households –For various programs: BPL and Antodaya rationing, Indira housing and employment generating schemes –Compare according to: expenditure measures, land holdings, whether members eat two meals a day, access to credit and an index of asset holdings
Government Targeting Results
Overview of Bandhan’s Targeting the Ultra Poor Program Identification –To identify the Ultra Poor, Bandhan... Conducts PRA’s Conducts follow up survey among those ranked most poor (rank 5 or 6) in the PRA Identified households receive a final verification visit from the Ultra Poor Project coordinator
PRA Process Social Mapping –Location of each household in hamlet demarcated on map –Name of household head recorded on index card Wealth Ranking –Residents define what constitutes poverty in their community –Index cards sorted into piles corresponding to socio-economic status Sorting of households into ranked piles (richest to poorest) based on participatory discussion by hamlet residents Concern that PRA may not generate accurate ranking –May not be sufficient participation (too few people present) –May be that influential hamlet members dominate process Could manipulate ranking in the expectation that highest (poorest) ranked households will receive aid Our study assesses reliability of ranking
Evaluation of the PRA Process
Evaluation of the PRA Process cont’d
Determinates of PRA Rank In addition to evaluating whether PRA wealth rankings accord with statistical measures of poverty, we assess what determines whether households are considered poor by their peers
Evaluation of Bandhan’s Verification Process Generally, PRA and Bandhan’s process identify similar sub-populations –Those ranked poor in PRA and those identified as Ultra Poor by Bandhan have less land, fewer assets, less education and lack formal credit access What does Bandhan’s verification process add above and beyond the PRA ranking? –How does it further narrow the targeted population?
Evaluation of Bandhan’s Verification Process cont’d
Expenditure Puzzle cont’d
Conclusion Effective targeting of a particular sub-population depends crucially on the identification mechanism used –Censuses, similar to those used for targeting of government aid, do not appear to identify the most disadvantaged population –Peer wealth rankings gathered in PRAs can provide statistically reliable information about which households are most poor –More detailed household interviews, as used by Bandhan, provide a way to further narrow the identified population and target more precisely