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May 23, 2012
   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.
   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.
   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.
   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
   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)
   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.
   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.
•   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.
   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
   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
   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
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
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
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)
   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
.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
Proportion owning a business in Round 5
.4            .5          .6          .7




                                            -2                0                             2
                                                    Baseline Wealth Index

                                                 Cash+Training              Training only
                                                 Control group
   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                                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
   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.
   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.
   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.

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Gender and Business Training

  • 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.