1. Paper prepared for the World Bank conference on Access to Finance
RETURNS TO CAPITAL IN MICROENTERPRISES: EVIDENCE FROM A FIELD EXPERIMENT Christopher Woodruff, UCSD (With Bob Cull and David McKenzie)
Paper prepared for the World Bank conference on Access to Finance
March 15-16, 2007

2. The project
We estimate returns to capital for a set of very small household enterprises.
No paid employees, capital of less than $US 1000 (~two-thirds of the income distribution in Mexico)

3. Returns to capital in microenterprises --Why do we care?
Large portion of urban labor market is self-employed. About one-quarter in Mexico
What is the potential for growth of these enterprises?
Financial market imperfections can result in large inefficiencies, underinvestment

4. Why might returns be high or low?
Low returns:
Several influential theory papers posit some minimum scale of investment / non-convex production sets (Banerjee and Newman 1993; Aghion and Bolton 1997)
High returns:
Capital constraints
Risk / uncertainty

5. Evidence on returns to capital in enterprises
Among others:
Banerjee and Duflo 2003 (74%-100%)
Bigsten et al (30%)
Udry and Anogol 2006 (60%-250%)
De Mel, McKenzie and Woodruff 2007 (60%)
McKenzie and Woodruff 2006
(10%/month)

6. Returns from ENAMIN data

7. What is wrong with existing evidence?
Some from cross section: Worry about conflating ability and capital investment
Some from loan programs: Measure only for the self-selected sample that applies for credit
McKenzie and Woodruff suggests that returns are high in the broad sample of firms, yet take up rates for loan programs are low

8. The Experiment
Randomized experiment where we provide grants to enterprises to create exogenous variation in capital stock
Selected 207 retail firms in Leon, Guanajuato
Sample drawn from block-to-block survey of households in selected UPMs
Surveyed first in November 2005, then quarterly through November 2006 (5 waves)

11. Capital shock
After the first and third round of the survey, randomly selected firms were given capital shock
~$140, in cash or equipment
33% of mean baseline capital stock, 50% of mean monthly earnings
Use grants rather than loans because we want to measure the full spectrum of firms

12. What part of the population?

13. Random Assignment to treatment

14. Attrition something to address

15. Returns to capital

16. Returns to capital

17. Attrition: Lower Lee bounds

18. Heterogeneity of returns

19. High returns to MFIs making small loans

20. Conclusions
Use random shocks to capital stock to estimate returns to capital
Data noisy, but suggest monthly returns in the 20%-35% range
Returns in the constrained firms
These returns are even higher than the returns we find from cross-sectional OLS data (attenuation?)