1. 1 Does Microcredit Matter? Evidence from India Supriya Garikipati University of Liverpool

2. 2 Microcredit Programs  They lend small sums of money to individuals as members of group  They rely on group liability to ensure repayment  They subsidise administrative costs rather than interest rates  Loans are repaid in weekly instalments GRAMEEN BANK

3. 3 The Microcredit Debate Does Microcredit Make a Difference?  1980s: Repayment Rates  1990s: Poverty Alleviation  2000s: Empowerment and Sustainability This paper evaluates vulnerability reducing and empowering potential of one such prog

4. 4 Microcredit in India More or less on lines of Grameen model Groups are larger (average 15 members) Various sources of finance (Banks, Commercial Institutions and NGO) Started in early 1990s As of 2002 there are 12 million members Sponsor led evaluation studies (Motivation)

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6. 6 Method  Household Survey: 302 Households 2001 and 2002 Client-Control Group  Client Survey: 397 Clients 2002 Understand the Findings  Key Informants: 38 Women 2002 and 2003

7. 7 Classify Households (302) Destitute (50% PL) Very Poor (51 to 80%) Mod Poor (81 to 120%) Non Poor (121% or >) Client 31 Client 28Client 31 Control 41Control 42Control 39Control 49

8. 8 Measuring Household Vulnerability Diversity1.Mean % of household income from non-agricultural sources 2.Households with access to such a source Entrepreneurial behaviour 1.Mean exp on fertiliser & pesticide 2.% Employing labour 3.Mean number of labour days employed Investment in phy, human, & social capital 1.Mean value of physical assets 2.Mean value of human capital index 3.Mean value of social capital index

9. 9 DestituteVery Poor Mod Poor Non Poor Diversity1. 2. Higher *** Entrepreneu rship 1. 2. 3.Higher *** Higher *** Higher ** Higher *** Higher *** P, H & S capital 1. 2. 3. Higher ** Higher *** Higher ** Percentages and Means of Study Variables of Client and Control Group Households (sig at 10% or better)

10. 10 Measuring Empowerment Constructing indices that reflect women position in and outside the household and impacts on her welfare Asset1.% with a positive index value 2.Mean rank of the index ProcessesSimilar as above OutcomesSimilar as above CompositeSimilar as above Time UseNon-waged work - Waged work – Reproductive work

11. 11 Percentages and Means of Empowerment Indices of Client and Control Group Women DestituteVery PoorMod PoorNon poor Assets1. 2.Lower *** Higher ** Processes1. 2. Lower * Lower ** Outcomes1. 2. Lower ** Lower *** Composite1. 2. Lower * Lower ** Lower *

12. 12 Percentages and Means of Time-Use of Client and Control Group Women DestituteVery Poor Mod Poor Non poor Non-wage work % doing it Mean timeHigher *** Wage work* % doing it Mean days Lower ** Lower *** Reproductive * Mean timeHigher ***

13. 13 Personal testimonies Change in attitude own capability and worth (own perception and others) Confidence in a network (emergencies and risk sharing) Change in standard of living Improved bargaining position

14. 14 Classify Clients (397) DestituteVery PoorMod PoorNon Poor 106 (26.7%) 99 (24.9%) 91 (22.9%) 101 (25.4%) Explaining the ‘Great Divide’

15. 15 Primary Loan Usage by Income Group (% of Women) Primary UseDestituteVery Poor Mod Poor Non poor Total Own Business4.72.031.945.520.7 Family Venture66.077.836.346.557.2 Asset Creation3.85.126.46.910.1 Consumption25.515.25.51.012.1 N of Cases1069991101397 Loan Usage

16. 16 Some Indications Most use loans on family ventures but For the poor consumption is important For the non-poor own business is important Non-poor more empowered and also more likely to use loans on own business

17. 17 Determinants of Loan Usage: Logistic Models (N = 386) RegressorOwn Business Family Venture Asset Creation Consume Constant -17.0 ( 6.8)* 2.3 (7.7)* -1.1 (-2.7)** 0.1 (0.6) Per Cap Income 0.0 (1.8)*** 0.0 (2.3)** 0.0 (0.3) -0.0 (-3.0)* Wealth 0.0 ( 1.8)*** 0.0 (2.3)** 0.0 (0.7) -0.0 (-0.5) Loan Control 0.3 (6.2)* -0.1 (-6.6)* -0.0 (-3.6)* -0.0 (-1.7) Group Decision 2.3 (2.3)** -0.4 (-1.6) 0.4 (1.1) -0.4 (-0.9) Years Member 0.0 (0.74) -0.0 (-0.4) -0.0 (-1.5) 0.0 (1.8)* Log-likelihood -27.9-420.51 -246.27-236.47

18. 18 The Main Findings Non-poor clients who control loans Non-poor clients who do not control Poor clients irrespective of control Followed up by personal testimonies If loans used for consumption and non-productive asset creation then how do clients manage repayments?

19. 19 Repayments Major source of repayment by loan usage (%) Use Repay Own Busines s Family Venture Asset Creation ConsumeTotal Own Business Income 85.4___14.0 Family Farm/ Business Income 13.49.317.54.217.0 Waged Work1.290.782.595.868.0 N of cases822274048397

20. 20 Plus Personal Testimonies Own-business Repay from source but only those women investing together make profit Others Repayment is difficult, work for wages or sell assets Challenging existing women’s intra-household position Decision on allocation of her labour Say over sale of assets

21. 21 Policy Interventions Poor Protection against risk Non-Poor Variety and Flexibility