1. Women’s Tertiary Education Masks Labor Market Discrimination; the Gender Wage Gap in Turkey
Hasan Tekgüç (MAÜ), Değer Eryar (İEÜ) & Dilek Cindoğlu (MAÜ)
24th IAFFE Annual Conference, July 16-18, 2015
Berlin School of Economics and Law

2. Motivation Gender wage gap is widely studied, including Turkey.
IAFFE 2015 presentation
Motivation
Gender wage gap is widely studied, including Turkey.
However, we believe that the empirical findings may not be reliable for Turkey, b/c
The gender discrepancy of labor force participation.
Exception to discrepancy is women with higher education.
Disaggregating only by gender leads to misleading findings.
We further disaggregate by education level when estimating wage gap and taking into account selection bias problem.

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Motivation
Cindoğlu & Toktaş (2002): «reserve power» :Tertiary education enables access to respectable/clean jobs such that women working in these jobs are conferred higher status. But also:
More say about «if, with whom and when» to marry
Ability to terminate bad marriages and not to marry in case of widowhood.
Successfully resist demands for more housework from their husbands and children.
Status enables them to receive help from their mothers or mother-in-laws for childcare.
Royalty (1998) and Theoddossiou & Zangelidis (2009) study job mobility by disaggregating both for gender and education level.
Unobserved characteristics (omitted variable problem)
Mobility behavior differs by education

4. Education and Female Labor Force Participation
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Education and Female Labor Force Participation

5. Empirical Literature on Turkey
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Empirical Literature on Turkey
Dayıoğlu and Kasnakoğlu (1997)
female-to-male monthly wage ratio 96 % (1987 survey)
Only human capital characteristics
Dayıoğlu and Tunalı (2004)
female to male wage ratio of 98 % (1988) survey & 85 % (1994) (corrected for selection bias).
Human capital + some workplace characteristics such as firm size & industry
Tansel (2004)
Female to male wage ratio is 73% in private sector, 78% in SEEs and almost nonexistent in the public sector according to 1994 Household Expenditure Survey (corrected for selection bias)
Discrimination is mostly observed in private sector
The key factors are returns to education and experience

6. Empirical literature on Turkey
IAFFE 2015 presentation
Empirical literature on Turkey
İlkkaracan and Selim (2007)
No correction for selection bias
Female male wage ratio is around 70 % (1994: employment and Wage Structure Survey)
Mostly manufacturing, electricity, gas, and mining
Detailed workplace characteristics drop the unexplained part of the gap
All the above results are based on Blinder-Oaxaca composition (mean wage differential)
Aktaş and Uysal (2012)
Almost no gap at the bottom of the distribution and higher wages for women at the top (2006: employment and Wage Structure Survey)
Different returns to education is crucial in explaining the gap rather than the workplace characteristics

7. Method Step 1 - selection model: Step 2 - Wage estimation:
IAFFE 2015 presentation
Method
Step 1 - selection model:
LFP = marital status + urban + NUTS2 + age + # young child + others’ income + education (if necessary)
Step 2 - Wage estimation:
Ln(wage_hour) = marital status + urban + metro + NUTS1 + age + major + tenure + tenure2 + public + firm-size + occupation + admin + inv. Mills ratio [population weights]
Step 3 - Wage decomposition:
𝑅 = 𝑌 𝑀 − 𝑌 𝑊 =( 𝑋 𝑀 − 𝑋 𝑊 )′ 𝛽 𝑀 + 𝑋 𝑊 ′ 𝛽 𝑀 − 𝛽 𝑊
Endowment
Discrimination
If ln M – ln W =  ln (M/W)=0.222  (M/W)=e0.222=1.25. i.e. on average men earn 25 percent more than women or equivalently women to men earning ratio (W/M) is 80 percent.

8. Dependent Variable: Monthly Wage
IAFFE 2015 presentation
Dependent Variable: Monthly Wage

9. 2-step procedure results
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2-step procedure results

10. Selection or not? Disaggregation or not? HLFS, 2011
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Selection or not? Disaggregation or not? HLFS, 2011

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Private versus public

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2004 versus 2011

13. Summary: Gender discrimination exists and it is increasing
IAFFE 2015 presentation
Summary: Gender discrimination exists and it is increasing
Both correcting for selection and disaggregating for education levels lead to more reliable results.
Both for tertiary (15 %) and less educated (21 %) women endowment explains only a minor part (1 %) of observed differences.
Tertiary education:
Excluding women working part-time and in informal sector reduce wage gap.
Controlling for more detailed major/subject do not reduce wage gap!
Controlling for occupation and admin. tasks reduce wage gap.
2011 sub-groups:
Total wage gap is the same both for the public and private sector, however, discrimination is worse in the public sector for women with tertiary education.
Increasing wage gap between 2004 and 2011 has been mostly due to discrimination
Glass Ceiling exists.

14. Why 20-54? Household Labor Force Survey (HLFS) 2004 & 2011
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Why 20-54? Household Labor Force Survey (HLFS) 2004 & 2011

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Wage according to education level, HLFS 2004 & 2011 (20 – 54 years old)

16. Labor Force participation, HLFS 2011 (20 – 54)
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Labor Force participation, HLFS 2011 (20 – 54)

17. Does the observed discrimination really exist?
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Does the observed discrimination really exist?

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Glass Ceiling:

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Other MENA countries:

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