World Bank Conference on “New Ideas in Business Growth: Financial Literacy, Firm Dynamics and Entrepreneurial Environment” March 2011

Business Training and Female Enterprise Start-up and Growth in Sri

Lanka

Suresh de Mel, University of Peradeniya David McKenzie, World Bank andChris Woodruff, Univ of Warwick

World Bank Conference on “New Ideas in Business Growth: Financial Literacy, Firm Dynamics and Entrepreneurial Environment”

March 2011

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

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

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 25-45 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.

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.

Sample: Summary Statistics Current Enterprises Potential Enterprises Training Training + Training Training + Control only Cash Control only CashVariables stratified on Total Monthly Profits (Rs.) 3987 3981 4001 Have no children or have someone to look after them 0.55 0.54 0.55 Colombo district 0.20 0.20 0.20 0.19 0.20 0.21Kandy district 0.21 0.20 0.20 0.20 0.20 0.20Has taken concrete steps to opening business 0.51 0.50 0.51Has never worked before 0.18 0.17 0.19 Variables not stratified on Age 35.94 37.71 36.58 34.38 34.05 33.72Married 0.89 0.86 0.80 0.84 0.91 0.89Number of children under 18 1.55 1.47 1.40 1.40 1.47 1.59Years of Education 10.16 10.34 10.51 10.51 10.56 10.53Risk-seeking score 6.81 6.87 6.53 6.73 6.82 6.75Digitspan Recall 6.00 6.04 6.01 6.03 5.93 6.06Raven test score 2.58 2.75 2.68 2.76 2.59 2.81Total household income from all sources 17192 18245 17595 16422 16690 16393Household has a fridge 0.45 0.53 0.51 0.39 0.41 0.43Household has a sewing machine 0.56 0.60 0.60 0.51 0.54 0.55Household has an oven 0.08 0.08 0.12 0.09 0.05 0.08Household has a gas cooker 0.25 0.23 0.30 0.28 0.24 0.24Age of Firm (years) 6.47 6.88 6.35 Ever had a loan from financial institution 0.23 0.18 0.20 Total Monthly Sales (Rs.) 12523 12485 12640 Capital Stock excluding land and buildings (Rs.) 28649 27418 35187 Truncated Capital Stock (Rs.) 28649 27418 34997 Business Practices Score 4.59 4.99 4.98 Number of Firms 224 200 200 228 200 200

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 1/4th 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

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)

Timeline

Jan 2009

April/May 2009

Screening andBaseline survey

June 2009

Sept 2009

Jan 2010

Notification / Training

Grants delivered

First follow-upsurvey

Second follow-upsurvey

Sept 2010

Third follow-upsurvey

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

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

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

Takeup: Current EntsTable 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 0.0164 -0.0452 -0.0117 (0.0469) (0.0472) (0.0494)Log of monthly profits -0.0700* 0.0259 0.0112 (0.0405) (0.0391) (0.0428)Age 0.00621 0.00627 0.00452 (0.00403) (0.00408) (0.00419)Married 0.121* 0.164** 0.144** (0.0654) (0.0676) (0.0687)Years of Education 0.0197** 0.0101 0.00742 (0.00985) (0.0102) (0.0107)Firm is younger than 5 years old 0.0838* 0.131** 0.128** (0.0495) (0.0521) (0.0525)Baseline Business Practices Score 0.00152 0.00380 0.00761 (0.00643) (0.00690) (0.00759)Risk-seeking Attitude -0.0215 -0.0111 -0.0104 (0.0135) (0.0134) (0.0140)Digit-span Recall -0.00911 0.00918 0.00915 (0.0201) (0.0199) (0.0214)Firm is in Manufacturing 0.158** 0.146** 0.149** (0.0646) (0.0681) (0.0691)Firm is in Retail Trade 0.0826 0.0488 0.0502 (0.0652) (0.0718) (0.0732)Works more than 40 hours a week at baseline -0.0878* -0.0879* -0.0705 (0.0485) (0.0497) (0.0495)Says would pay 500 Rs or more for a training course -0.0149 -0.0265 -0.0508 (0.0494) (0.0528) (0.0537)Colombo District -0.454*** (0.0672) Kandy District 0.0730 (0.0628) D.S. (locality) fixed effects No No Yes Number of firms 400 400 400Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

Takeup: Potential Ents

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.

Current Ent: Impact on Business PracticesTable 3: Impact on Business Practices of Current Enterprises

Marketing Stock Control Record keeping Financial Planning(1) (2) (3) (4) (5) (6) (7)

Round 2 Round 4 All rounds All rounds All rounds All rounds All roundsIntent-to-Treat EffectsAssigned to Cash if finish Training 2.530*** 1.936*** 2.071*** 0.395*** 0.236*** 1.000*** 0.566***

(0.555) (0.567) (0.373) (0.130) (0.0690) (0.174) (0.150)Assigned to Training only 1.719*** 1.708*** 1.656*** 0.495*** 0.167** 0.633*** 0.537***

(0.555) (0.560) (0.382) (0.134) (0.0704) (0.161) (0.161)Treatment on the TreatedReceived Training & Cash 3.588*** 2.790*** 2.986*** 0.564*** 0.340*** 1.485*** 0.836***

(0.591) (0.607) (0.462) (0.165) (0.0886) (0.228) (0.194)Received Training Only 2.192*** 2.261*** 2.169*** 0.647*** 0.219*** 0.833*** 0.705***

(0.540) (0.546) (0.431) (0.153) (0.0816) (0.186) (0.187)

Observations 544 513 1,057 1,057 1,057 1,164 1,164Firms 544 513 573 573 573 598 598Baseline Mean: 4.96 5.02 4.96 1.66 0.53 2.10 0.64Robust standard errors in parentheses clustered at the firm level when all rounds used, *** p<0.01, ** p<0.05, * p<0.1All specifications also include survey round dummies, baseline outcome value, and controls for randomization strata.

Total Practices Score

Current Ent: Impact on Firm Performance• Impact of the treatments on monthly profits (also on

sales and capital stock). Examined in levels, truncated at 99th 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 4014.

• Increase in profits occur in R2 and R3 (4 months + 8 months post training) but falls off by round 4 (16 months post training).

Current Ent: Impact on Firm PerformanceTable 4: Impact on Firm Performance for Current Enterprises All rounds pooled Round 2 Round 3 Round 4 (1) (2) (3) (4) (5) (6)

Truncated Truncated Truncated Truncated Levels Levels Logs Levels Levels LevelsPanel A: Monthly Profits ITT Effects Assigned to Cash if finish Training 1,195 1,520** 0.213*** 1,801* 1,955** 441.4 (884.1) (645.9) (0.0755) (945.6) (929.7) (1,191)Assigned to Training only -574.7 -118.0 0.0450 24.92 -79.99 -531.2 (908.7) (661.1) (0.0797) (904.7) (952.1) (1,223)TOT Effects Received Training & Cash 1,765 2,236** 0.312*** 2,587** 2,885*** 656.7 (1,203) (882.3) (0.103) (1,046) (1,058) (1,307)Received Training Only -746.1 -146.4 0.0602 22.99 -90.80 -699.0 (1,105) (804.9) (0.0978) (897.6) (964.3) (1,215) Baseline Mean: 4014 4014 8.14 4004 4023 4016 Observations 1,592 1,592 1,527 538 542 512Firms 577 577 571 538 542 512Notes: Robust standard errors in parentheses clustered at the firm level when all rounds used, *** p<0.01, ** p<0.05, * p<0.1All specifications also include survey round dummies, baseline outcome value, and controls for randomization strata.Truncated levels truncate at the 99th percentile.

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

Potential Ent: Entry into SETable 6: Impact on Entry into Self Employment Probability of being Self Employed Ever SE (1) (2) (3) (4) (5)VARIABLES All waves R2 R3 R4 Assigned to Training only 0.0677 0.1187** 0.0553 0.0311 0.0290 (0.043) (0.053) (0.050) (0.051) (0.047)Assigned to Training and Cash Grant 0.1306*** 0.2211*** 0.1521*** 0.0248 0.0952** (0.042) (0.050) (0.049) (0.051) (0.046) Observations 1,732 588 587 557 588

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.

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

Potential Ent: Impact on Business PracticesTable 7: Impact on Business Practices of Current Enterprises

Overall Score Marketing

Stock Control

Record keeping

Financial Planning

(3) (4) (5) (6) (7) Ruond 4 Ruond 4 Ruond 4 Ruond 4 Ruond 4Intent-to-Treat Effects

Assigned to Training Plus Cash Grant 1.334** 0.648*** 0.117 0.430 0.139 (0.663) (0.214) (0.129) (0.324) (0.296)Assigned to Training only 1.106 0.253 0.132 0.563* 0.158 (0.734) (0.237) (0.131) (0.322) (0.297) Observations 335 335 335 335 335R-squared 0.225 0.214 0.103 0.078 0.285

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.

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?

Potential Ent: Impact on Firm PerformanceTable 8: Impact on Firm Performance for Potential Enterprises All waves R2 R3 R4 (1) (2) (3) (4)Panel A: Monthly Profits ITT Effects Assigned to Training Plus Cash Grant 328 -186 -560 1,532 (844) (866) (1,248) (1,135)Assigned to Training only 1,210 486 239 2,632** (900) (899) (1,379) (1,230) Observations 950 287 329 334Notes:

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)

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.