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Gender and Microfinance


									Gender and Microfinance

   Jonathan Morduch
   World Bank
   April 30th, 2007
   Reaching Women
   Why Women
   Evaluating Impact
   Beyond Credit
   Looking Forward
Reaching Women
   10.3 million in 1999  69 million in
   570% increase
   84.2% of total clients

Source: Daley-Harris, Sam (2006). “State of the Microcredit Summit Campaign Report 2006”.
Women Served

Source: Daley-Harris, Sam (2006). “State of the Microcredit Summit Campaign Report 2006”.
Why Women?
   Women make up a large and growing
    segment of the informal-sector
   Women tend to be more credit constrained
   Commercial banks focus on men because
    men form a larger portion of the formal sector
                                     Percentage of non-
                                agricultural labor force that
                                 is in the informal sector,        Women’s share of the
                                         1991/1997              informal sector in the non-
                                                                  agricultural labor force,
                                  Women              Men                 1991/1997
                Benin                97               83                    62
                Chad                 97               59                    53
                Guinea               84               61                    37
                Kenya                83               59                    60
                Mali                 96               91                    59
                South Africa         30               14                    61
                Tunisia              39               52                    18
                Latin America
                Bolivia              74               55                    51
                Brazil               67               55                    47
                Chile                44               31                    46
                Colombia             44               42                    50
                Costa Rica           48               46                    40
                El Salvador          69               47                    58
                Honduras             65               51                    56
                Mexico               55               44                    44
                Panama               41               35                    44
                Venezuela            47               47                    38
                India                91               70                    23
                Indonesia            88               69                    43
                Philippines          64               66                    46
                Thailand             54               49                    47

Source: The United Nations, 2000. The World’s Women 2000: Trends and Statistics. Chart 5.13, p. 122
Financial Impact: Targeting women customers
          can improve repayment rates
Financial Impact
   Women are better customers
       Higher repayment rates
           Conservative in investment strategy – more risk
           More vulnerable to peer pressure and threat of
            public humiliation
           Less access to credit which reduces risk of moral
               Hossain (1988): 81% of women had no repayment
                problems versus 74% of men.
               Khandker et al., (1995): 15.3 % of male borrowers
                were “struggling” in 1991 versus 1.4% of female
                (missing some payments before the final due date)
Financial Impact
   Women are better customers
       Less mobile
           Reduces monitoring costs – for bank as well as peer
           Enables women to attend repayment meetings (if
       Less argumentative
   Lower staff costs
       Institutions can hire more female staff
Financial Impact: But institutions targeting
 women have tended to be less profitable as
     loan sizes remain relatively small
Evaluating Financial Impact
   As MFI’s scale, the % of women clients
       Small scale – 75.3% women borrowers
       Medium scale – 64.5% women borrowers
       Large scale – 55.2% women borrowers
   For-Profit institutions tend to serve fewer
    women clients
       Not for Profit – 71.9% women borrowers
       For Profit – 54.5% women borrowers
Source: MicroBanking Bulletin, Issue No. 12, April 2006
Development Impact: Targeting women has a
    greater impact on social and economic
Development Impact
   Women are poorer
       UNDP Human Development Report (1996): 70% of
        the world’s poor, about 900 million women
   Women spend on household consumption as
    opposed to personal consumption
       Pitt and Khandker (1998): Empirical studies have
        shown that women are more likely than men to direct
        additional income to household consumption
   Working women contribute to economic growth
Empowerment Impact
   Increases women’s decision-making power
       Pitt et al., (2006): Women’s participation in credit
        programs leads to women having greater role in
        household decisions, social networks, and greater
        freedom of mobility. Increase spousal communication
        about family planning and parenting concerns.
   Improvement in domestic interactions
       Third party scrutiny of household abuse
       Intervention with Microfinance for AIDS and Gender
        Equity (IMAGE) study demonstrated reductions in
        levels of intimate-partner violence in participants.
Empowering Women with Micro Finance:
Evidence from Bangladesh
- Mark Pitt, Shahidur Khandker, Jennifer

• Study estimates the impact of participation in micro credit
program on an index of empowerment
• Uses data from household survey from 1998-99
• Uses qualitative, self-reported responses to questions
around women autonomy and gender relations in
Study Design
   Original 1991-92 survey
       1,789 households -1,538 target (59% participated
        in program) and 260 nontarget
       40 program villages
           22 female-only groups
           10 male-only groups
   1998-99 follow-up empowerment survey
       2,074 households with married couples
       80% of question were asked only to wives
Study Design
   10 Empowerment Factors
       Purchasing
       Resource
       Finance
       Transaction Management
       Mobility and Networks
       Activism
       Household Attitudes
       Husband’s Bahavior
       Fertility and Parenting
       All Variables
Study Results
   Female credit produces statistically significant
    improvements in –
     Autonomy with purchasing households assets

     Access to and control over economic resources
     Ability to raise emergency funds
     Role in deciding and implementing household
     Power to oversee and conduct major household
      economic transactions
     Mobility and networking
     Awareness and activism

     Discussions around family planning and parenting
Study Results
   Female credit does not increase husband’s
    opinions and actions
   Male credit effects on women’s
    empowerments were largely negative –
    specifically on women’s control of resources,
    finance, freedom of movement and fertility
    and parenting decisions
Tying Odysseus to the Mast:
Evidence from a Commitment Savings Product
in the Philippines
- Dean S. Karlan, Nava Ashraf, Wesley Yin

   “…but you must bind me hard and fast, so that I
    cannot stir from the spot where you will stand
    me… and if I beg you to release me, you must
    tighten and add to my bonds.”
    -- The Odyssey
   Developed new “commitment” savings product for
    Philippine small, semi-rural, for-profit bank
   Randomized control evaluation design
   Developed survey methodology to identify “hyperbolic”
    individuals using hypothetical time preference questions
   Developed follow-up survey to measure impact on
    female decision-making power and household outcomes
   Sample frame: poor but “banked” (prior clients) of the
A Commitment Savings Product
   Withdrawal restriction
     Either time-based (140) or amount-based (62)

     Decided entirely by client

   Deposit incentive
     Ganansiya box – 167 out of 202 tookup 

     Automatic transfer – 2 tookup 

   Same interest rate as regular savings account
     Hence, loss of liquidity is uncompensated

   Note: Given combination of account features, not possible
    establish causal link of any one feature to impact
   Note: Features could work for self-control OR spousal-control
The Commitment Savings Product
Randomized Experimental Design

                      1,777 Clients of
                    Green Bank Surveyed
                     by Research Team

                       25%: Provided
50%: Offered SEED                           25%: Control group:
                    intensified marketing
  (Of those, 28%                             no further contact
                      of normal savings
    accepted)                                 beyond survey.
                                             Measuring Impact
                                           Figure 2: Changes in Overall Savings Balances
                                                            (12 months)

                                                                                           Treatment: SEED
                             2000                                                          Takeup
Change in Philippine Pesos

                                                                                           Treatment:No SEED
                             1500                                                          Takeup
                                                                                           Marketing Group

                              500                                                          Control Group

                                     0.1   0.2   0.3   0.4   0.5   0.6   0.7   0.8   0.9

                                           Decies of Change in Savings Balances
Magnitude in Real Dollars
   Doctor’s visit: 150 pesos
   Public school fees are 150 pesos/year,
    plus ~200 pesos/month for special
   1 month supply of rice for a family of 5:
    1000 pesos
Follow-Up Survey: Female Empowerment
   Conducted one-year after experiment date
   Nine decision categories such as family
    planning, financial and consumption
   Record whether principle decision-maker is
    respondents, the spouse or both for each
   Reponses assigned values of two, zero and
    one respectively
Measuring Impact: Self-Reporting
   Constructed two decision making indices
       Equally-weighted mean of each response - 0.14
        standard deviation increase for treatment group
       Linear combination of individual responses to
        each question – 0.25 standard deviation increase
        for treatment group
   Average effect is largely driven by increase in
    decision-making ability for women below the
    median (initially less empowered)
Measuring Impact: Observing Purchases
   Three categories for expenditures
       House Repair, Female-oriented Durables (washing
        machine, kitchen appliances etc), Other Durables
   Women below median
       Increase in items purchased and total expenditures of
        consumer durables associated with female use
       No increase in other non-female specific durables
       Indicates that women were able to use their power in
        households to purchase goods that were beneficial to them
   Women above median
       Increase in items purchased is smaller and not statistically
Study Results
   Average savings increases by 85% for those
    who took-up
   Average savings increases by 24% for those
    who were offered
   ~34% of SEED clients actively using the
   Female empowerment through increase in
    female decision-making power
       Increase in self-reporting by women
       Increase in women oriented durable purchases
Evaluating Finance, Development and
         Empowerment Impact:
        Critical Perspectives
Evaluating Development Impact
   Women do not control all loans
       Goetz and Sen Gupta (1996): 40% of
        women have little or no control over their
   Difficulty in scaling businesses due to
    limited resources (including skills and
   Difficulty in scaling businesses due to
    greater risk and debt aversion
Evaluating Development Impact
   Income generation responsibility may
    lead to heavier workload and more
       Mayoux (1999): Lack of substitute care for
        children and elderly leads to added
Evaluating Empowerment Impact
   Pressure to pay back loans can lead to
    domestic pressure and violence
       Contrary to the IMAGE study, per
        Rahman’s study 70% of women expressed
        increase in violence (based on one village)
   Limited empowerment outside the
       Mayoux (1999): Less evidence of socio-
        political empowerment due to presence of
        inflexible social norms and traditions
Evaluating Empowerment Impact
   Unclear evidence on endogeneity of
    empowerment and microfinance
       Are women involved in microfinance
        already empowered?
Beyond Credit: Toward cost-effective ways
      to enhance development and
     empowerment impact on women
Beyond Credit
   Johnson (2000): Mainstreaming and
    institutionalizing gender
       Incorporate gender issues in normal service delivery
       Equality of women’s access to services and mechanisms
       Require asset registration in woman’s name
       Equal employment opportunity for women as staff
   Products and programs that respond to women’s
    needs and demand
       Commitment Savings Product
           Karlan et al., (2006): Access to commitment savings product
            in Philippines had positive impact on female decision-making
            power within household
Beyond Credit
   Education and consciousness-raising programs
       Pro Mujer - Health Education
       BRAC Bangladesh – Integrated Training
       Support collective group learning for both men and women
       RADAR IMAGE Collaboration in South Africa

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