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Does Microcredit Matter? Evidence from India

Supriya Garikipati

University of Liverpool

 

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Microcredit Programs They lend small sums of money to individuals

as members of groupThey rely on group liability to ensure

repaymentThey subsidise administrative costs rather than

interest ratesLoans are repaid in weekly instalments

GRAMEEN BANK

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The Microcredit DebateDoes Microcredit Make a Difference?

1980s: Repayment Rates1990s: Poverty Alleviation2000s: Empowerment and

Sustainability

• This paper evaluates vulnerability reducing and empowering potential of one such prog

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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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MethodHousehold Survey: 302 Households

2001 and 2002

Client-Control Group Client Survey: 397 Clients

2002

Understand the Findings Key Informants: 38 Women

2002 and 2003

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Classify Households (302)

Destitute

(50% PL)

Very Poor(51 to 80%)

Mod Poor(81 to 120%)

Non Poor (121% or >)

Client 31

Client 31

Client 28

Client 31

Control 41

Control 42

Control 39

Control 49

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Measuring Household VulnerabilityDiversity 1. 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

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Destitute

Very Poor

Mod Poor

Non Poor

Diversity

1.

2.

Higher***

Higher***

Entrepreneurship

1.

2.

3. Higher***

Higher***

Higher**

Higher*** Higher***

P, H & S capital

1.

2.

3.

Higher**

Higher**

Higher***

Higher***

Higher***

Higher**

Percentages and Means of Study Variables of Client and Control Group Households (sig at 10% or better)

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Measuring EmpowermentConstructing indices that reflect women position in and

outside the household and impacts on her welfare

Asset 1. % with a positive index value

2. Mean rank of the index

Processes Similar as above

Outcomes Similar as above

Composite Similar as above

Time Use Non-waged work - Waged work –

Reproductive work

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Percentages and Means of Empowerment Indices of Client and Control Group Women

Destitute Very Poor Mod Poor Non poor

Assets 1.

2. Lower***

Higher**

Processes 1.

2.

Lower*

Lower**

Lower**

Lower**

Outcomes 1.

2.

Lower**

Lower***

Lower***

Composite 1.

2.

Lower*

Lower**

Lower*

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Percentages and Means of Time-Use of Client and Control Group WomenDestitute Very

PoorMod Poor

Non poor

Non-wage work• % doing it• Mean time Higher***

Higher***

Wage work*• % doing it• Mean days

Lower**

Lower**

Lower***

Reproductive *• Mean time Higher***

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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

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Classify Clients (397)

Destitute

Very Poor

Mod Poor Non Poor

106(26.7%)

99

(24.9%)

91(22.9%)

101(25.4%)

Explaining the ‘Great Divide’

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Primary Loan Usage by Income Group (% of Women)

Primary Use Destitute Very Poor

Mod Poor

Non poor

Total

Own Business 4.7 2.0 31.9 45.5 20.7

Family Venture 66.0 77.8 36.3 46.5 57.2

Asset Creation 3.8 5.1 26.4 6.9 10.1

Consumption 25.5 15.2 5.5 1.0 12.1

N of Cases 106 99 91 101 397

Loan Usage

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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

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Determinants of Loan Usage: Logistic Models (N = 386)

Regressor Own 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

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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?

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RepaymentsMajor source of repayment by loan usage (%)

Use Repay

Own Business

Family Venture

Asset Creation

Consume Total

Own Business Income

85.4 _ _ _ 14.0

Family Farm/ Business Income

13.4 9.3 17.5 4.2 17.0

Waged Work 1.2 90.7 82.5 95.8 68.0

N of cases 82 227 40 48 397

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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

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Policy Interventions

• Poor Protection against risk

• Non-Poor Variety and Flexibility