Transcript Diploma earning by gender in Colombia ” by J.J.Mora & J.Muro

Development Workshop
14.12.2010
Elisabeth Niendorf and Aleksandra Olszewska
Outline
1) How to estimate returns to education?
2) Simple signalling model
3) Diploma earning differences by gender in Colombia
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General statistics by gender (education, earnings, participation)
Simple signalling model -> Sheepskin effect
Methodology: Pseudo Panel and specification
Findings and Selection Bias
4) Private vs. Social Reutrns
5) Policy Implications
6) Discussion
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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1. Measuring returns to
education
 Mincer (1974):
ln Yit = β0 + β1Eit + β2Xit + γt + εit
 2 types of problems
1) Ability bias
2) Pre-selection into employment
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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2. How the employer can know?
A simple signalling model
Belman & Heywood (1991)
 Assumption: workers have signals of productivity
 imperfectly correlated with their actual productivity
h=a+ ε
, with μ of a = k
and μ of ε = 0
 Firm estimates productivity :
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â = E(a|h)
â = γh + (1- γ)k
Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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2. Simple signalling model cont‘d
 If γ = 1
 perfect information : observing the
signals reveals actual productivity
 If γ = 0
 no information from the signal
 employer must assume productivity = k
Since cost of obtaining a signal is high for minorities 
signal is correlated more closely with productivity for
minorities than for majorities
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Sheepskin effect
 "sheepskin" effect = wage increase
above what would normally be
attributed to the extra year of
education
 A group with higher cost
of obtaining a diploma has lower
expected productivity >> low sheepskin effect
 How to observe empirically?
 wage difference between ‘drop-outs‘ and ‘completers‘
with an equal # of years of education
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Cost of education:
Belman & Heywood (1) vs. Spence (2)
Cost of education
pocket expenses:
- cost of tuition
- living expenses etc.
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opportunity costs:
-monetary
-other costs, including
psychological, time and
effort...
Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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And the benefits ?
Source: OECD, 2009
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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3. Case Study - Colombia
„Diploma earning differences by gender
in Colombia“
J. Mora & J.Muro (2010)
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Labour & returns to education
Labour market participation rate 1981-1998:
 women: 37% >> 51%
 men: 74% (stagnant)
Returns to education:
 women always above men by 2%
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Looking at averages…
Mean variables for males and females:
>> Even if women are more educated, they earn less.
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Pseudo panel data
 Cross-section data in each year but with different individuals at
each time period
 No panel survey statistics on household labor supply in
Colombia
 Use National Housing Survey (NHS) - a time series of
independent and representative cross-sections for the period
1984-2000
 Advantages:
 controls for individual heterogeneity and selection biases
 eliminates attrition problems
 allows for analysing the effect of diplomas on salaries as a result of a
permanent effect of credentials in the labor market and not as a
result of a transitory effect of credentials
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Linear regression and spline
regression
a. Linear regression line
b. Spline regression line
Spline regression is a regression which estimates
different linear slopes for different ranges of the
independent variables.
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Specification
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worker i at time t
Wh – wage/h
S – years of schooling
S-11 – dummy for completing high school
S-16 – dummy for completing university
S11(S-11) and S16(S-16) – cohort variable dummy
exp – potential experience (age-S-6)
ν – cohort effects
μ – idiosyncratic error
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Specification – cont’d
 β0 and β2 – ‘sheepskin effect’ - wages change after
obtaining a high school and university diplomas
 If they are positive and statistically significant, then
there will be a higher wage increase from holding a
diploma than from an additional year of schooling.
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Results
Returns/additional earnings:
 completion of the 10th grade:
 women – 8-9%
 men – 6-7% (confidence interval of 95 percent)
 additional year of experience:
 women – 3-4%
 men – 4-6%
 Sheepskin effect:
 Women holding a high school degrees had higher additional
earnings (12-18%) than men (5-10%)
 Men holding university diplomas had higher additional
earnings (31-68%) than women (16-66%).
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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IV-probit model
 Labour market participation = fn(years of education,
dummies for wealth, martial status, household size,
cohort, city, economic sector)
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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IV-probit model – cont’d
 Selection bias
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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Main findings…
Colombia 1996-2000:
 significant and distinctive effect of high school and
university degrees among men and women
 women holding a high school degree had higher
additional earnings than men
 men holding a university degree obtained higher
additional earnings than women
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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But…
„Even if women are more educated, they earn less.”
 Are women also better educated than men, when
considering only the highest education level?
 Sometimes women choose lower paid jobs (the authors use
averages).
 Different aims at work (high wage, care for the goals, etc.)
 We don’t know too much about the sample
representativeness…
 Unobserved effects? Is there something systematic that
prevents women from labour market participation?
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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But…
 Parents’ education and wealth is also important…
 Education as a normal good: rich families >> more
education for children >> higher future income
 Positive correlation between the parents’ level of education
and one of their children
Attainment of 5 or more
GCSE grades A*-C by
parental NS-SEC, 2002,
Enlgand & Wales
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
Source: www.statistics.gov.uk
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4. Private vs. Social returns to
education
Acemoglu & Angrist (1999)
 Social rate of return to education < sum of individuals‘
private rates of return
 If education is merely a signalling ability without
raising productivity
Stiglitz (1975): „An attempt to eliminate educational screening may just
shift the focus of screening (for example, on-the-job screening), and
make everyone worse off.“
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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4. Private vs. Social returns to
education - cont‘d
 Alternatively: education may have a positive
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externality
Easy to name them, how to measure them?
Vaule-added due to higher education always reflected in
wages?
What we could do: Leigh (2007)
Social return = mean increase in pre-tax earnings
But: what about intergenerational benefits? higher
value-added not included in wages? less tangible
benefits as political participation...?
2015-07-17
Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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5. Policy Implications
 Key challenge: How to allocate scarce resources across types of
education? Will the benefit of a marginal dollar be higher if
invested in schools, technical education or universities?
 If sheepskin effects turn out to be important factors in determining
wage differentials:
 Reconsider the effect of public investment in higher education
 Additional education obtained by individuals of a given
ability -> raises the education needed by the more able, if they
want to signal their higher talent
 Consequence: interventions may raise private cost of education
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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5. Policy Implications cont‘d
Educational expenditure may:
 In the short run: increase inequality and decrease net
national income
 In the long run: benefits for society, result in economic
growth
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Returns to education - A Presentation by
Aleksandra Olszewska & Elisabeth Niendorf
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6. Discussion
 Does education increase wages due to increasing
productivity or due to signalling?
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Education >> skills >> income
Skills >> education >> income
 Why does the gender gap persist?
 Results of psychological studies...
Gender differences in risk-aversion for entering competitive
environment ?
 Confidence in wage negotiation / job interviews?
 (See Pinto, 2010 for a formal model on that issue...)
 Labor market discrimination? .............
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Now
you are free to discuss... 
Returns to education - A Presentation by
2015-07-17
Aleksandra Olszewska & Elisabeth Niendorf
26