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Business Training and Female Enterprise Start-up and Growth in Sri Lanka Suresh de Mel, University of Peradeniya David McKenzie, World Bank and Chris Woodruff,

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Presentation on theme: "Business Training and Female Enterprise Start-up and Growth in Sri Lanka Suresh de Mel, University of Peradeniya David McKenzie, World Bank and Chris Woodruff,"— Presentation transcript:

1 Business Training and Female Enterprise Start-up and Growth in Sri Lanka Suresh de Mel, University of Peradeniya David McKenzie, World Bank and Chris Woodruff, Univ of Warwick World Bank Conference on “New Ideas in Business Growth: Financial Literacy, Firm Dynamics and Entrepreneurial Environment” March 2011

2 Motivation: Previous work in SL Randomized experiment where we provide SLR 10K or 20K (US$100 or 200) in equipment or cash grants to micro-enterprises to create exogenous variation in capital stock (QJE, Nov 2008) Selected 618 firms in three districts in southern Sri Lanka (Kalutara, Galle, Matara) with less than SLR 100K (US$1000) in capital (excluding land and buildings). Surveyed first in March 2005, then quarterly for two years, semi-annually for a third year (11 waves) Profits increased on avg by 5.9% per month. The surprising result: males generated 7.8% increase in profits but females generated -0.8% return. We explore several possible explanations (AEJ Applied, July 2009) – Intra-household bargaining / capture by spouse – Sector of activity

3 Motivation: Other recent work We look at the impact of business training on a general population of female business owners – not just on MF clients. The current study focuses on 2 groups – current enterprises and potential enterprises Content of the business training is a standardized training package (ILO’s SIYB training program). Useful to know its impact. Difficult to compare content across customized training programs offered by MFIs. We measure outcomes at 3 different points in time post- training. Able to achieve more power than is possible with a single follow-up survey. And able to examine the growth trajectory over time. We use business training + capital grants as interventions. Can examine impact of training only vs training + grants

4 Follow-on project in Sri Lanka Identify two groups of women in 7 districts in and around Colombo and Kandy. Listing in 142 GNs in 10 DS divisions. – Age yrs – Current enterprises: > 20 hrs per wk in self employment, sector other than seasonal agri/fisheries, monthly profits =< SLR 5000 ($43). – Potential enterprises: planned to enter SE in next yr, able to identify the nature of the proposed business, unmarried/married with no kids/married with kids > 5 yrs of age/if < 5 yrs of age had someone to look after the kids. Selected sample of 628 current enterprises and 628 potential enterprises equally distributed across 10 DS divisions.

5 Interventions Provide business training – ILO’s Start and Improve Your Business (SIYB) program. Implemented in 95 countries. Estimated global outreach of 1.5 million trainees. Teaching materials customized to local language and context. Potential Ents: 3 day Generate Your Business Idea (GYB) + 5 day Start Your Business (SYB). Current Ents: 1 day Refresher GYB (RGYB) + 5 day Improve Your Business (IYB) Both groups got 1 day technical training – exposure to, and training in, some relatively high rtn sectors which are socially acceptable for women. 2-3 options available at each training location. Cash grants of SLR 15,000 (~$125) for half, conditional on completing training Attendance payment of Rs 400 per day – transport, lunch, opp cost. At each DS location, training offer to 40 current and 40 potentials. Half of those who completed qualified for the 15K grants.

6 Sample: Summary Statistics Current Enterprises Potential Enterprises TrainingTraining + TrainingTraining + ControlonlyCash ControlonlyCash Variables stratified on Total Monthly Profits (Rs.) Have no children or have someone to look after them Colombo district Kandy district Has taken concrete steps to opening business Has never worked before Variables not stratified on Age Married Number of children under Years of Education Risk-seeking score Digitspan Recall Raven test score Total household income from all sources Household has a fridge Household has a sewing machine Household has an oven Household has a gas cooker Age of Firm (years) Ever had a loan from financial institution Total Monthly Sales (Rs.) Capital Stock excluding land and buildings (Rs.) Truncated Capital Stock (Rs.) Business Practices Score Number of Firms

7 Sample Typical current enterprise: – 36 years old, married, with 10 yrs of education, running the business for 6.5 yrs. – Mean monthly business income SLR 4000 (US$34). – This is about 1/4 th of HH income – Low business practices score at baseline (mean is 4.6 out of 29). – Only 18% have done any business related training – and of this mainly technical training

8 Sample Typical potential enterprise: – Only 18% have never worked before, but only 8% have previously been in SE – 50% have taken some concrete steps towards opening a business in the past year. – 2 yrs younger in age than current grp, but otherwise similar in terms of education, digitspan recall, raven tests, attitudes towards risk, and no of children. – Monthly HH income about Rs 1100 less than current. – Less likely to own fridge or sewing machine (assets that have business potential)

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14 Timeline Jan 2009 April/May 2009 Screening and Baseline survey Screening and Baseline survey June 2009 Sept 2009 Jan 2010 Notification / Training Notification / Training Grants delivered First follow-up survey First follow-up survey Second follow-up survey Second follow-up survey Sept 2010 Third follow-up survey Third follow-up survey

15 Treatment Takeup Current: 279 (69.8%) of the 400 offered treatment attended training and 268 (67%) completed training. Potentials: 282 (70.5%) of the 400 offered treatment attended training and 261 (65.3%) completed. Common reasons for not taking up training: – Family member was sick – No one to look after the business in their absence – No one to look after their children

16 Who is likely to take-up training? CURRENT – Married, more educated women, running younger firms, more likely to attend training. – Having no children or having someone to look after children not significantly associated with takeup – Manufacturing firms more likely to attend training – Opp cost of time seems to matter: women running higher profit earning enterprises are less likely to attend, women working more than 40 hrs per wk are less likely to attend. – Firms in Colombo are less likely to attend

17 Who is likely to take-up training? POTENTIALS – Take-up increases with age of woman and raven score. – Colombo potentials are less likely to attend. – Having no children or having someone to look after children, yrs of education, previous work experience, having taken steps to open a business, spouse’s income not significantly associated with takeup

18 Takeup: Current Ents Table 2A: Determinants of Training Take-up Among Current Enterprises Marginal effects from Probit estimation of Attending Training among those offered (1)(2)(3) Has no children or has someone to look after children (0.0469)(0.0472)(0.0494) Log of monthly profits * (0.0405)(0.0391)(0.0428) Age ( )( )( ) Married0.121*0.164**0.144** (0.0654)(0.0676)(0.0687) Years of Education0.0197** ( )(0.0102)(0.0107) Firm is younger than 5 years old0.0838*0.131**0.128** (0.0495)(0.0521)(0.0525) Baseline Business Practices Score ( )( )( ) Risk-seeking Attitude (0.0135)(0.0134)(0.0140) Digit-span Recall (0.0201)(0.0199)(0.0214) Firm is in Manufacturing0.158**0.146**0.149** (0.0646)(0.0681)(0.0691) Firm is in Retail Trade (0.0652)(0.0718)(0.0732) Works more than 40 hours a week at baseline * * (0.0485)(0.0497)(0.0495) Says would pay 500 Rs or more for a training course (0.0494)(0.0528)(0.0537) Colombo District *** (0.0672) Kandy District (0.0628) D.S. (locality) fixed effectsNo Yes Number of firms400 Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

19 Takeup: Potential Ents

20 Current Ent: Impact on Business Practices Measured at baseline (R1) and short-term (R2: 4 months after training) and medium term (R4: 16 months after training) Business Practices usage has increased in both the short term and medium term for both training only grp and training + cash grp Magnitude of increase large relative to baseline. Training also significantly improved the components – marketing, stock control, financial planning, and record keeping.

21 Current Ent: Impact on Business Practices

22 Current Ent: Impact on Firm Performance Impact of the treatments on monthly profits (also on sales and capital stock). Examined in levels, truncated at 99 th percentile and in logs. Training alone does not increase profits. But significant impact of training + cash on profits Magnitudes of impact on profits is also high. Eg. TOT shows that truncated profits increase by 2236 relative to baseline mean of Increase in profits occur in R2 and R3 (4 months + 8 months post training) but falls off by round 4 (16 months post training).

23 Current Ent: Impact on Firm Performance Table 4: Impact on Firm Performance for Current Enterprises All rounds pooledRound 2Round 3Round 4 (1)(2)(3)(4)(5)(6) Truncated Levels LogsLevels Panel A: Monthly Profits ITT Effects Assigned to Cash if finish Training1,1951,520**0.213***1,801*1,955**441.4 (884.1)(645.9)(0.0755)(945.6)(929.7)(1,191) Assigned to Training only (908.7)(661.1)(0.0797)(904.7)(952.1)(1,223) TOT Effects Received Training & Cash1,7652,236**0.312***2,587**2,885***656.7 (1,203)(882.3)(0.103)(1,046)(1,058)(1,307) Received Training Only (1,105)(804.9)(0.0978)(897.6)(964.3)(1,215) Baseline Mean: Observations1,592 1, Firms Notes: Robust standard errors in parentheses clustered at the firm level when all rounds used, *** p<0.01, ** p<0.05, * p<0.1 All specifications also include survey round dummies, baseline outcome value, and controls for randomization strata. Truncated levels truncate at the 99th percentile.

24 Potential Ent: Entry into SE Training + grant leads to a 13 percentage point increase in prob that a woman enters into SE. Training alone has a smaller effect which is not statistically significant. However in R2 (4 months post training), training only leads to a 12 percentage point increase and training + grant leads to a 22 percentage point increase. By R4 (16 months post training), the difference between treatment and control groups have disappeared. On avg, training + grant leads to a 9.5 percentage point increase in likelihood of being ever SE

25 Potential Ent: Entry into SE Table 6: Impact on Entry into Self Employment Probability of being Self EmployedEver SE (1)(2)(3)(4)(5) VARIABLESAll wavesR2R3R4 Assigned to Training only ** (0.043)(0.053)(0.050)(0.051)(0.047) Assigned to Training and Cash Grant0.1306***0.2211***0.1521*** ** (0.042)(0.050)(0.049)(0.051)(0.046) Observations1, Notes: R2 through R4 denote survey rounds Robust standard errors in parentheses clustered at the firm level, *** p<0.01, ** p<0.05, * p<0.1 All specifications also include survey round dummies and controls for randomization strata.

26 Potential Ent: Impact on Business Practices Impact on business practices is much less compared to current ent. Trtmnt raised overall score by only just over 1 point – but this is statistically significant only for the training + cash grp. Impact of the trtmnt is positive in each of the sub- components but significance indicated only for marketing among the training + cash grp and record keeping for the training grp

27 Potential Ent: Impact on Business Practices Table 7: Impact on Business Practices of Current Enterprises Overall ScoreMarketing Stock Control Record keeping Financial Planning (3)(4)(5)(6)(7) Ruond 4 Intent-to-Treat Effects Assigned to Training Plus Cash Grant1.334**0.648*** (0.663)(0.214)(0.129)(0.324)(0.296) Assigned to Training only *0.158 (0.734)(0.237)(0.131)(0.322)(0.297) Observations335 R-squared Robust standard errors in parentheses clustered at the firm level when all rounds used, *** p<0.01, ** p<0.05, * p<0.1 All specifications also include survey round dummies, baseline outcome value, and controls for randomization strata.

28 Potential Ent: Impact on Firm Performance We find positive but insignificant effects of both treatments In R2 and R3 we find negative effects on profits for those who rcvd training + grants (but not statistically significant) By R4, large positive effect on profits for those who rcvd training only. Positive but not significant effect for those who rcvd training+grant. Recall that in R2 and R3 we had significantly higher rates of SE in training + grants grp. Could it be that with the training + grants there has been more entry by women with lower potential profits and less entry by women with higher potential profits?

29 Potential Ent: Impact on Firm Performance Table 8: Impact on Firm Performance for Potential Enterprises All wavesR2R3R4 (1)(2)(3)(4) Panel A: Monthly Profits ITT Effects Assigned to Training Plus Cash Grant ,532 (844)(866)(1,248)(1,135) Assigned to Training only1, ,632** (900)(899)(1,379)(1,230) Observations Notes: Robust standard errors in parentheses clustered at the firm level when all rounds used, *** p<0.01, ** p<0.05, * p<0.1 All specifications also include survey round dummies, baseline outcome value, and controls for randomization strata. Truncated levels truncate at the 99th percentile (columns 5-8)

30 Conclusions Examined impact of training and training + cash grant among current and potential female enterprises. CURRENTS: – Significant improvements in business practices. Effects are only slightly smaller even 16 months after training. – Training only does not affect profits. But training +grants has significant positive impact on profits. POTENTIALS: – Both training only and training + grant has speeded up entry into SE, but not the ultimate rate of entry. – Some evidence that profits are higher among the treatment grps by R4.


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