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Detailed summary notes for week 5 readings eg mobarak and heath paper includes 3 papers
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Manufacturing growth and the lives of Bangladeshi women Heath Mobarak 2015Aim Analyses effect of garments industry growth on Bangladeshi women
Context Setting: Bangladesh: Ready made garment had growth rate of 17% & first Sector to provide female employment
education is rewarded in garment factories
10 and 23 years old (critical age group at risk for early marriage in Bangladesh)
Motivati Manufacturing expansion typically associated w/ incr in female labor force participation But
on evidence gap - Little understanding of welfare effects; usually anecdotes ab negative effects of hazardous
working conditions.
Important for policy-makers in Bangladesh where infamous garment factory collapses called for boycotts
need to fill this evidence gap to understand the implications otherwise unintended consequences on
welfare of Bangladeshi women
Identific compare outcomes of women in garment-proximate village to 3 sources of identifying variation: (a) girls in non-
ation garment proximate sub-districts (b) earlier years before factories arrive and (c) the girls' male siblings
- Outcome: marriage, childbearing, school enrollment and labour force partipation
labor force participation diff- in-diff: compare probability of girl working exposed to extra year of garment jobs
compared to girl in a garment-proximate village with less exposure when at critical ages for joining the labor force or
getting married
Marriage and childbearing discrete time hazard model: effects on probability girl marries or childbearing from
extra year of exposure to garments job, using years of exposure to garment jobs as explanatory variable
Educational attainment (δ2) effect of garment industry on years of education completed by girls in garment
village relative to brothers (boys as control group for girls)
- δ1 + δ2 = effect of girls in garment-proximate village compared to girls in non-garment
School Enrollment: effect of factory on girl's enrolment decision relative to brother in garment-proximate village
(δ1) and girls in non-garment (δ1 + δ2)
- How enrolment relative to brothers effect varies w/ age (δ3)
- how enrolment relative to girls in non-garment villages varies w/ age (δ3 + δ4)
identification assumption: exposure to garment sector is localized: garment industry effects are concentrated on
girls growing up in villages within commuting distance of garment factories
Identific Reverse causality: girls' schooling or marriage decisions (dependent variables) influence arrival of garment jobs
ation OVB: non-random arrival of garment factories eg factory location based on new roads built nearby
concern - factory location influenced by use family-owned buildings & proximity to infrastructure
s - largest effects are seen in younger girls contradicts infrastructure improvements near factories explaining
results, as children in Bangladesh travel further for secondary school than primary school
Data o Baseline HH surveys 2009 - Schooling (years, timing), marriage, childbearing history of all offspring
o Garment manufacturer's association categorizes garment-proximate villages and non-garment villages
o Survey knowledgeable person - supplemental data on start dates of garment factories opening
Results Result 2: marriage and childbirth (welfare indicators) at early ages (12–18) drops sharply for girls exposed to
garment sector, where early marriage most harmful to girls development Table 4:
o col 1: girls living in garment-proximate villages where factories operating for 6.4 years have (6.4 × 0.00048) =
0.3 pp lower probability of getting married relative to girls in control villages
o Col 2: effects is large, statistically significant at youngest ages(12-18) (fig 6 shows
this too)
o Col 3: girls living in garment-proximate villages with 6.4 years of exposure are
(6.4 × 0.00036) = 0.23 pp less likely to given birth relative to control villages
Result 1: Garment industry induced more women to work outside the home: exposure
to garment jobs at critical age increases working outside home by 13pp. Table 3:
, o col 1: girls in garment-proximate villages are 15 pp more likely to worked outside the home than girls in
control villages.
o Col 2: strongest effects among girls for whom factory presence coincided with their life-cycle
o Col 3: girls exposed to factory jobs at critical age are 13 pp more likely to have done wage work outside the
home than girls in control
Result 3: Garment exposure increase in girls' educational attainment and school enrolment effects – Table 6
- Additional year of garment exposure= increase 0.26 yrs of boys education & 0.22 yrs effect on girls.
o gender gap in educational attainment closes by 1.5 years
o Fig 7: large positive effects on younger girls (8 yrs old) is 13 pp more likely to be in school, after women in
her village work in the garment industry, relative to girl in a non-garment proximate village. After 11, effects
begin to decrease some drop-outs among older girls
Garment industry explains reduced gender gap in schooling, earlier marriages and fertility in Bangladesh, rather
than cash transfer program (female school stipend program” (FSP): paid girls to remain in school, conditional on
remaining unmarried)
Effects of (FSP); no evidence that girls remained in school after 1994 (Table 9) & no evidence of marriage and the
childbearing reducing (table 10)
Mechan Access to factory jobs significantly lowers the risk of early marriage and childbirth for girls:
ism o younger children stay in school longer to invest in their education bc its rewarded in factories(requires
numeracy/literacy higher education enrolment = delay early marriage+ lower childbirth hazard
o garment jobs increases opportunity cost of being married/ having children = older children may be induced
to get factory jobs, instead of marriage + families postpone their daughter's marriage = reduce early
childbirth
Policy Manufacturing growth has a larger effect in improving female educational than Cash transfer (supplyside)
implicati - promoting export-led manufacturing and increasing returns to skill is the more effective path to human
ons capital accumulation
- garment factory arrival increase gender participation & equality in workforce - policy-relevant, as Bangladesh
has surpassed the third Millennium Development Goal of gender equity in enrollments before deadline
External Accelerating gender equity in education + Growth in export-oriented sector applicable to low-skill manufacturing
validity jobs in developing world
Labor Rationing (excess labour supply)
Aim examining the effects of experimental hiring shock on local wages and employment -> excess labor supply
Context Setting: Rural labor markets in Odisha, India. Represents a casual labor market:
agricultural, non-agricultural jobs, Self-employment workers owning land
Seasonal labour demand: Employment higher in peak and lower in lean months
Experiment: temporary hiring shocks in villages by offering jobs outside village randomising hiring intensity across
villages
Treatment: give jobs to 24% male labor force & control villages: no hiring shock
uses local labor market response to learn about the equilibrium that existed in the absence of our shock
Worker is rationed if:
Worker wants to supply labor at current market wage, but unable to find employment (worker is not on her
labor supply curve)
Worker is employable at that wage (i. her marginal product > current wage).
rationed worker may be involuntarily unemployed, or engaged in self-employment.
Motivati In developing countries, rural wage employment rates hover around 50%, but interpretation remains unclear
on - Some suggest that it reflects high involuntary unemployment, indicating significant distortions, while others:
low wage work reflect well-functioning labor markets where workers choose other activities like self-
employment = implications for labor market equilibrium
Identific Revealed Preference test: when job slots open up through the hiring shock, workers reveal they prefer jobs at wage
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