1. BANGLADESH Population: 143.8 million Urban 23.9 million HDI Rank: 138 Adult illiteracy 58.9% Population < $1 36.0 million Largest Microfinance Programs ’98: Grameen, BRAC, RD-12 Serving the landless rural poor

2. Pitt and Khandker (1998) Attempt to measure the impact of microfinance participation, by gender on: - boys’ and girls’ schooling - household expenditures (consumption) - accumulation on non – land assets - women’s and men’s labor supply

3. Cross – Section Data: 1,798 households in 87 villages were surveyed in 1992 905 households were under a microfinance program← treatment 893 households were not ← control Results: Relative to credit provided to men, credit provided to women: (a) ↑Schooling (both boys and girls) (b) ↑Household expenditures (consumption) (c) ↑Non-land assets held by women (d) ↓Labor supply of men and women

4. Basic insight

5. Problem: How to address the biases? Find an IV: a variable that explains levels of credit received but has no direct relationship with the outcomes of interest In this case: Schooling, Household Expenditures, Non Land Assets, Labor supply “An eligibility rule: only “functionally landless” households (with < ½ of land) can have access to microfinance” The fact that there ineligible households (260) within villages with programs → there is another “control” group which helps to alleviate the bias

6. An improved estimation strategy Compare: (a)Treatment with ineligible households living in the same village (b)Ineligible with “would be” eligible → households with access to microfinance are doing better than their ineligible neighbors relative to the difference in outcomes between functionally landless households in control villages versus their ineligible neighbors

7. Yij = Xij α + Vj β+ Eij γ + (Tij Eij) δ’ + ηij,(8.5) Disappointing results w/r to impact on household consumption But: Microfinance helps to diversify income streams so that consumption is less variable across seasons Also: Landholdings may not be “exogenous” On the other hand Successful borrowers were buying land → may explain why no impact on household consumption ☺ Moreover, debate over ineligible households that participated (25%). But Pitt- Khandker (1999) acknowledged the problem, made robustness checks and show that their results change very little ☺

8. Note that: Yij = Xij α + Vj β+ Eij γ + Cij δ” + ηij,(8.6) Where: δ” captures credit “access” Now, by expanding the set of instruments to Xij Tij Eij → there are as many instruments as there are X (education….) → δ” takes advantage of variation of how much credit households receive

9. Now, when comparing groups of men with groups of women Pitt-Khandker (1998) most cited result: For every 100 taka lent to a woman consumption ↑ 18 taka For every 100 taka lent to a man consumption ↑11 taka Now, another round of data was collected in 1998 – 1999 And Khandker (2003) to see the trends

10. 20 per cent poverty decline both participants and nonparticipants Pessimists: decline would have happened even without microfinance Optimists: impact of microfinance has had positive spillovers to nonparticipants

11. Khandker’s (2003) econometric estimates show that: Microfinance contributed to roughly ½ of the 20 percentage points decline in poverty For every 100 taka lent to a woman consumption ↑8 taka Ideally, another round of data collection should help Problem: microfinance in Bangladesh has spread far and wide → No more control groups!!! Have a great weekend and good luck on the midterm☺ → Next Class: DR, Chap 8 and the article by Coate