Microenterprises Gender and Microenterprise Performance A series of projects asking: What are returns to capital in microenterprises? What determines sector of activity, esp for females? Suresh hde Mel, MlPeradeniya Chris Woodruff, Warwick (Based on joint work with David McKenzie, World Bank) GTZ / LMFPA Workshop on Gender and Microenterprise December 2010 The Experiment Randomized experiment where we provide grants to enterprises to create exogenous variation in capital stock Selected 618 firms in three districts in southern Sri Lanka (Kalutara, Galle, Matara) Sample drawn from block to block census in selected GNs Surveyed first in March 2005, then quarterly for two years, semi annually for a third year (11 waves) The Experiment Firms in three zones: 1) Suffered direct damage from tsunami 2) In coastal zone, but no damage 3) Further inland For what we will describe, we exclude the firms directly affected by the tsunami The enterprises All had less than 100,000 SLR ($US1000) in capital (not counting land and buildings) in baseline survey Half in retail, the other half in manufacturing / services (clothing, lace, bamboo, food products) Sl Selected with ihscreening survey (3361 households) h )in GNs with high rates of SE and moderate education levels 1
Sri Lanka: capital shock After the first and third round of the survey, randomly selected firms were given capital shock Rs. 10,000 or Rs. 20,000, in cash or equipment 59% of firms received treatment Larger treatment t tis: About 100% of median (75% mean) capital stock About 6 months of reported earnings Use grants rather than loans because we want to measure the full spectrum of firms Main outcomes About 75% of the grant was invested. Two thirds invested in working capital / inventories Profits increased on average by 5% of the grant per month. Returns to marginal investments of capital Returns by gender Table 4: IV Measuring Return to Capital from Experiment Log Real Real Profits Real Profits Real Profits Profits Real Profits Adjusted (1) Adjusted (2) IV-FE IV-FE 4 Instruments IV-FE IV-FE (1) (2) (3) (4) (5) Capital stock / log Capital Stock 5.85** 0.379*** 5.16** 5.29** 4.59** (excluding land & buildings) (2.34) (0.121) (2.26) (2.28) (2.29) First-stagestage Coefficient on Treatment Amount 0.91*** 0.33*** 0.91*** 0.91*** F-statistic 27.81 49.26 6.79 27.81 27.81 Observations 3101 3101 3101 3101 3101 Number of enterprises 384 384 384 384 384 The surprise Males generated very large increases in income, females did not. This was not expected! We explore several possible explanations (AEJ Applied, July 2009): Intra household bargaining / capture by spouse Sector of activity Intra household cooperation Intra household bargaining / capture by spouse Women invest less in inventories, more in lumpy capital assets Returns appear to be higher for investments in inventories Consumption flows from assets Females in more cooperative households invest more in inventories, have increases in profits 2
Bargaining Sector of activity Some sectors (e.g., repair services) are entirely or mostly males, others (e.g. lace) are entirely or mostly females Returns are higher sectors with more male participants Why are women clustered in certain activities? Social norms? Lack of labor market experience? Lack of capital at time of startup? Joint household production? De Mel et al AEJ Applied July 2009, Table 9 Returns by sector ranked by female ownership Sector of work Marginal profits by % Female Ownership 20 % of treatment investe ed 10 0-10 -20-30 -40 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Female Ownership Female $100 Male $100 Female $200 Male $200 De Mel et al AEJ Applied July 2009, Table 10 Follow on project in Sri Lanka Identify two groups of women in 7 districts around Colombo and Kandy. Listing in 142 GNs in 10 DS divisions Current business owners in low income sectors Women likely to re enter labor force: Had definite idea for business Single, or married w/o children <5,or w/ someone to watch children Provide training 6 8 day ILO program GYB/SYB for re entering, IYB for current 1 day training related to a specific sector chosen by trainers and participants (list from us); 2 3 options offered on same day Cash grants of 15,000 Rs (~$125) for half, conditional on completing training Interventions and timeline Sample of 628 potential re entrants 400 offered training: 200 training only, 200 training + grant. Randomization stratified on: DS; taken steps to open business; very/somewhat confident could run at least 1 of beauty salon, grocery store, tea shop, bakery; some previous labor market experience Among re entering women, 282 (70%) started the training and 261 (65%) completed training. 3
Interventions and timeline Sample of 628 potential re entrants Did training / grants affect start up? Apparently were successful at anticipating startup: Start-up by Treatment Group and Month Jan 2009 Screening and Baseline survey April 2009 June 2009 Notification / begin training Training completed/ Grants delivered Sept 2009 Jan 2010 First follow up survey Second follow up survey % of Sample 14.0% 12.0% 10.0% 8.0% 6.0% 4.0% 2.0% 0.0% January February March April May Month June July August Control Training Training+Grant Did training / grants affect start up? Percentage of women who were employed, self employed by treatment group With other controls Including only stratification controls: Training only shifts some from WW to SE; training plus grants shift some from WW to SE and some from NILF to SE Among other controls, sig effect of extreme risk aversion, no sig effect of age, education, raven, digitspan Household support and norms Asked in baseline: Which of the following businesses is it socially acceptable for women like you to work in? Which would your spouse / family support you doing? Responses: Family support and norms Teashops outside the home splits the sample almost evenly. Teashop is socially acceptable: 66% open a business Teashop not socially acceptable: 57% open a business (p=0.04) 04) Is support from family also correlated with entry? Family supports both grocery and beauty shop: 70% open a business Family does not support at least one of these: 58% open a business (p<0.01) 4
Family support Do training or grants overcome lack of family support? Norms Do training or grants overcome lack of social acceptance? Family support and norms With other controls: Joint production In January 2010, just over a third of women say their spouse / family would not support them running a tea shop outside the home. Why? (A story is that w/ family support, don t need money. W/ social pressure against you, you do need money.) Sector and location Training + grant makes it more likely business will be located outside of home (24% vs. 11%) Sector: Some shift away from retail, and toward food. Sector sector Control Training Train+grant agriculture 5% 15% 14% food manuf 16% 23% 22% retail 29% 16% 19% clothing 35% 27% 29% manuf 5% 4% 4% misc 10% 14% 12% Total 100% 100% 100% Note: Data from September 2009 survey only 5
Conclusions Profits increase on avg by 5% per month. Gender breakdown: Male returns are much higher. Female returns are close to zero. Intra household bargaining issues: females invest more in lumpy assets, less in inventories. More cooperative HHs invest in inventories. Sector issues: Returns higher in male dominated sectors. As % of females increases, returns decrease. Conclusions Training and grants induce higher rates of entry into self employment among women screened on likelihood of re entering LF What relieves constraints on entry among female microentrepreneurs? On going project, but some preliminary evidence for interaction between training / grants and: Support from spouse / family Social norms 6