2. Self-employment accounts for a large share of
female employment in most developing countries
But:
◦ Most female-owned firms are very small in scale, with low
earnings
◦ In much of South Asia and the Middle East, the majority of
women are not even employed at all.
⇒ Key questions:
4. Can business training (alone or with a grant) raise
the incomes of low-earning women;
5. Can it allow women outside the labor force to start
new businesses.
3. A lot of emphasis has been on capital as the
constraint to female microenterprise growth;
hence the attention given to microfinance.
But:
◦ In recent experiments in Sri Lanka and Ghana,
we’ve found physical capital alone has not been
enough to raise incomes of subsistence-level
female-owned businesses.
◦ Recent microfinance experiments also shown very
modest results in this regard – although have had
some success in getting new businesses started.
4. Conduct randomized experiments in Sri Lanka to
test impact of business training on 2 different
groups of women:
◦ Self-employed with low levels of income
◦ Out of the labor force but interested in entering.
Use the ILO’s SIYB training program, which is the
most commonly used worldwide.
Look at impact of training alone, as well as
training + grants.
Measure outcomes at 4 points in time post-
training: increases power + look at trajectories.
5. Last couple of years have seen a number of
randomized experiments on business training in
developing countries
Most are with microfinance clients, focus on existing
business owners, are often with customized training
programs, and have only single snapshot follow-up.
Karlan and Valdivia – Peru – improvements in business practices, no sig.
improvements in sales, profits or employment; maybe higher sales in bad months.
Drexler et al. – Dominican Republic – compare two programs. Find simpler “rules
of thumb” program improved practices and sales in bad months, no sig. impact on
average sales, and profits not looked at.
Berge et al – Tanzania – for females weak improvements in business practices, no
impact on business outcomes (males they get improvements).
Bruhn and Zia – Bosnia – improvements in business practices, but no increases in
business profits or survival rates.
Gine and Mansuri – Pakistan – women improve business knowledge, but show no
improvements in outcomes
6. Urban labor force participation rate for 20-40
year old women only 38% (vs >90% for men)
28% of those in paid work are self-employed
◦ Median profits only 5000 Rs (US$43)/month
◦ Only 5% have any paid workers
7. • Identify two groups of women in districts in and
around Colombo and Kandy. Listing in 142 GNs
in 10 DS divisions.
– Age 25-45 yrs
– Current enterprises: > 20 hrs per week in self
employment, sector other than seasonal
agriculture/fisheries, monthly profits =< 5000 Rs ($43).
– Potential enterprises: planned to enter self-
employment in next year, 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.
8. ◦ Typical industries are tea shops, beauty shops, bag and
mat manufacturing, tailoring, sewing, fruit & vegetable
sales, making and selling lunch packets.
◦ 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 17% keep written records, only 4% done any advertising
in last 6 months, only 9% have sales target fro next year,
only 3% have budget of what costs for next year likely to be.
◦ Only 18% have done any business related training – and
of this mainly technical training
9.
10.
11. ◦ 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 group, but
otherwise similar in terms of education, digitspan
recall, raven tests, attitudes towards risk, and
number of children.
◦ Monthly HH income about Rs 1100 less than current.
◦ Less likely to own fridge or sewing machine (assets
that have business potential)
12. Randomly selected 400/628 in each group to be
offered business training
◦ Half of these were also selected to receive a grant of
15,000 Rs (US$129) conditional on finishing the training.
◦ At the time of being offered training, individuals were told
that half of those who completed the training would be
randomly chosen to receive a grant of this size.
Randomization stratified on D.S., and other key
variables.
◦ Current enterprises: children to look after; baseline profits
◦ Potential enterprises: taken steps to opening business;
whether had ever worked before
As a result of randomization, treatment and control
groups balanced on baseline characteristics.
13. ILO Start and Improve Your Business (SIYB) program
◦ Designed to meet needs of small-scale entrepreneurs in
developing countries
◦ Started in Eastern Africa in 1977
◦ Global outreach of 1.5 million trainees, implemented in
over 95 countries
◦ Use three packages:
Generate Your Business (GYB) – 3 days on generating idea for
business
Start Your Business (SYB) – 5 days on main aspects needed to
start a business – what to sell, pricing, organizing staff,
equipment and inputs, legal form, etc.
Improve Your Business (IYB) – 5 day course which helps existing
business owners develop their business – modules on
marketing, buying, costing, stock control, record-keeping, and
financial planning.
14. • Potentials: 3 day GYB + 5 day SYB.
• Currents: 1 day Refresher GYB + 5 day IYB
• Both groups got 1 day technical training – exposure to,
and training in, some relatively high return sectors
which are socially acceptable for women. 2-3 options
available at each training location.
• Training provided by SLBDC, which has 8 years of
experience delivering this content to local market &
university-educated trainers.
• Cost to us of training was around $130 per individual
trained.
• Course was offered to participants for free + attendance
payment of 400 Rs per day to cover transport and
opportunity cost of training.
15.
16.
17. Current: 279 (69.8%) of the 400 offered
treatment attended training and 268 (67%)
completed training.
◦ Married, more educated women running young firms
more likely to attend.
◦ Opportunity cost of time matters – less likely to attend
if more profitable, work more hours, have more
wealth.
Potentials: 282 (70.5%) of the 400 offered
treatment attended training and 261 (65.3%)
completed.
◦ More able, older women more likely to attend
◦ Take-up lower in Colombo than elsewhere
18.
19. Follow-up surveys are at 3-4 months; 7-8
months; 15-16 months; and 24-25 months after
training.
Attrition rates low – getting 580-590 out of 624
in follow-up rounds (92-94%). Attrition unrelated
to treatment status in current enterprises,
slightly lower for trained in potential sample but
results robust to this
Measure:
◦ Business outcomes, including profits, sales, capital-
stock
◦ Business practices
20.
21.
22. On current enterprises
◦ On business practices
◦ On business outcomes
On potential enterprise owners
◦ On whether they start-up a business
◦ On how well these businesses do
23.
24.
25. 1 .8
Cumulative Distribution
.6
4 months after training
+ grant
.2 .4 0
0 20000 40000 60000 80000 100000
Real Monthly Profits in Round 2
Control Cash
Training only
26. 1 .8
Cumulative Distribution
.6
25 months after
training and grant
.2 .4 0
0 20000 40000 60000 80000
Real Monthly Profits in Round 5
Control Cash
Training only
27. Table 4: Impact on Firm Performance for Current Enterprises
All rounds pooled Round 2 Round 3 Round 4 Round 5
Truncated Truncated Truncated Truncated Truncated
Levels Levels Logs Levels Levels Levels Levels
Panel A: Monthly Profits
ITT Effects
Assigned to Cash if finish Training 724.9 1,207** 0.168** 1,758* 1,910** 432.5 169.9
(839.9) (593.0) (0.0716) (932.6) (898.5) (1,123) (1,099)
Assigned to Training only -695.7 -171.3 0.0240 11.75 -76.47 -460.3 -760.6
(920.7) (626.2) (0.0752) (889.5) (912.4) (1,148) (1,241)
Panel B: Monthly Sales
ITT Effects
Assigned to Cash if finish Training 5,171 4,436 0.143 6,818* 3,284 3,079 2,129
(4,686) (3,500) (0.0932) (4,020) (5,366) (6,534) (6,482)
Assigned to Training only -2,941 -1,786 -0.0414 -1,718 -1,519 -3,884 -2,248
(4,422) (3,512) (0.0967) (3,845) (5,386) (5,993) (7,177)
Panel C: Capital Stock
ITT Effects
Assigned to Cash if finish Training 17,221** 10,379*** 0.155** 9,535* 7,270 12,195* 11,374**
(7,815) (3,583) (0.0691) (4,893) (4,932) (6,379) (5,760)
Assigned to Training only -700.2 -490.7 -0.0671 -3,476 -278.1 -4,452 3,389
(5,616) (3,338) (0.0629) (4,192) (4,596) (5,921) (6,474)
28.
29.
30. TOT impacts:
◦ Cash + Training: 29 p.p. increase at R2, 2 p.p. in R4 and
R5
◦ Training only: 12.2 p.p. increase at R2, -2 p.p. in R5.
Have sped up entry – so impact evaluations which
looked only in the first year would think big
impact on business start-up, but by 25 months
no significant impact on levels of start-up.
What about who runs a business?
◦ Model predicts we should see selection on ability and
wealth
31. .8
Proportion owning a business in Round 5
.4 .5 .6 .7
0 2 4 6 8
Baseline Raven test score
Cash+Training Training only
Control group
32. Proportion owning a business in Round 5
.4 .5 .6 .7
-2 0 2
Baseline Wealth Index
Cash+Training Training only
Control group
33. So even though levels of business ownership
are the same, interventions have changed
who owns a business – which makes
evaluating the impact of the training and
grants on the business less straightforward.
Two approaches:
◦ Naïve experimental approach – estimate impacts via
OLS – since selection seems to be that interventions
bring in poorer and less analytically able, this might
be argued to be lower bound.
◦ Use generalized propensity score and run weighted
regression to compare like with like.
34. Table 7: Impacts on Total Work Income and Business Outcomes for Potential Group
Business outcomes
Total Work Income Profits Business Practices
R2 and R3 R4 and R5 R2 and R3 R4 and R5 R4 and R5
Panel A: Experimental ITT Estimates
Assigned to Cash if finish Training 266.7 696.7 -161.0 804.7 0.999**
(556.5) (728.5) (741.7) (830.2) (0.489)
Assigned to Training only 211.5 1,494* 484.9 2,244** 0.870
(545.4) (773.9) (785.3) (975.9) (0.559)
Observations 1,175 1,119 615 675 676
Firms 601 585 359 393 394
p-value for testing treatment equality 0.920 0.327 0.398 0.165 0.819
Control group mean 3516 4940 5001 5209 8.33
Panel B: Generalized Propensity Score Reweighted Estimates to account for selection into who operates a business
Assigned to Cash if finish Training 59.12 767.2 1.173**
(692.6) (846.0) (0.502)
Assigned to Training only 374.3 2,171** 0.971*
(772.0) (1,072) (0.567)
Observations 590 651 652
Firms 345 380 381
p-value for testing treatment equality 0.6702 0.2127 0.7282
35. Training alone not enough to get subsistence
businesses run by women to grow
◦ Consistent with results from other business training
studies
◦ Also consistent with work on capital grants
◦ Adding capital gives temporary boost in profitability, but
appears to be relatively short-lived
⇒Really hard to get these subsistence-level firms to grow
⇒ Policy options:
⇒More intensive one-on-one mentoring e.g. Valdivia –
but expensive.
⇒Address constraints to participation in wage work, with
labor market failures potentially reason these women
operating business in the first place.
36. Potential enterprises
◦ Results more encouraging for ability of business
training to help women start businesses more
quickly, and make these businesses more profitable
This is a group existing business training studies
haven’t focused on
Consistent with microfinance studies which have found
some impact on business start-up
=> Easier to get women to start-up
subsistence businesses than it is to get these
businesses to grow.
37. Results show the importance of tracing out the
trajectory of impacts
◦ Single follow-up survey would miss much of the story.
Importance of looking at impacts on different
subgroups of interest
◦ Potential vs Current firm samples
◦ Arguably learn more about firm growth constraints by
taking a sample of general population than by taking
microfinance clients.
Issue of content when comparing evaluations
◦ “business training” varies a lot in curricula, cost, number
of hours, etc. across studies, making difficult to
compare.