Transcript Returns to Capital in Sri Lanka

May 23, 2012
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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
1.
2.
questions:
Can business training (alone or with a grant) raise
the incomes of low-earning women;
Can it allow women outside the labor force to
start new businesses.
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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.
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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.
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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 posttraining: increases power + look at trajectories.
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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
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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
•
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.
◦ 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
◦ 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)
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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.
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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
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As a result of randomization, treatment and control
groups balanced on baseline characteristics.
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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.
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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.
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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.
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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
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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, capitalstock
◦ Business practices
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On current enterprises
◦ On business practices
◦ On business outcomes
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On potential enterprise owners
◦ On whether they start-up a business
◦ On how well these businesses do
Business Practices Score for Current Firms Over Time
Number of Practices Implemented
12
10
8
6
Control
Training only
4
Training + Cash
2
0
0
5
10
15
20
Months Since Training
25
30
Real Profits for Current Firms over Time
12000
Real Monthly Profits
10000
8000
Control
6000
Training only
Training + Cash
4000
2000
0
0
10
20
Months Since Intervention
30
1
.8
.6
0
.2
.4
4 months after training
+ grant
0
20000
40000
60000
Real Monthly Profits in Round 2
Control
Training only
80000
Cash
100000
1
.8
.6
0
.2
.4
25 months after
training and grant
0
20000
40000
60000
Real Monthly Profits in Round 5
Control
Training only
Cash
80000
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
Assigned to Training only
Panel C: Capital Stock
ITT Effects
Assigned to Cash if finish Training
Assigned to Training only
5,171
(4,686)
-2,941
(4,422)
4,436
(3,500)
-1,786
(3,512)
0.143
(0.0932)
-0.0414
(0.0967)
6,818*
(4,020)
-1,718
(3,845)
3,284
(5,366)
-1,519
(5,386)
3,079
(6,534)
-3,884
(5,993)
2,129
(6,482)
-2,248
(7,177)
17,221** 10,379*** 0.155**
(7,815) (3,583) (0.0691)
-700.2
-490.7 -0.0671
(5,616) (3,338) (0.0629)
9,535*
(4,893)
-3,476
(4,192)
7,270
(4,932)
-278.1
(4,596)
12,195*
(6,379)
-4,452
(5,921)
11,374**
(5,760)
3,389
(6,474)
Proportion owning a business by survey
round
0.70
0.60
Proportion
0.50
0.40
0.30
0.20
0.10
0.00
4 months
Control
8 months
Training Only
16 months
25 months
Training + Grant
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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.
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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
.8
.7
.6
.5
.4
0
2
4
Baseline Raven test score
Cash+Training
Control group
6
Training only
8
.7
.6
.5
.4
-2
0
Baseline Wealth Index
Cash+Training
Control group
2
Training only
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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.
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
Firms
p-value for testing treatment equality
Control group mean
1,175
601
0.920
3516
1,119
585
0.327
4940
615
359
0.398
5001
675
393
0.165
5209
676
394
0.819
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
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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
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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.
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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.
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Results show the importance of tracing out the
trajectory of impacts
◦ Single follow-up survey would miss much of the story.
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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.
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Issue of content when comparing evaluations
◦ “business training” varies a lot in curricula, cost, number
of hours, etc. across studies, making difficult to
compare.