Abstract
This paper investigates the relation between female activity in the labor market and gender wage gaps using regional data from Turkey. Labor force participation of women in Turkey significantly lags behind the developed countries but is increasing. At the same time, raw gender wage gap is quite low in international standards but also increasing. I use the regional variation to analyze the relation between female labor force participation and wage gaps in two steps. First, I estimate the unexplained wage gap, which filters out the gender differences in productivity characteristics for each region and each year between 2009 and 2018, using Household Labor Force Survey data. Then I analyze the relation between gender gap with female labor force participation and other regional characteristics in a panel data regression. The results of the paper suggest that female labor force participation is positively related with both raw and unexplained wage gap. This positive relation partially stems from the fact that women with less unobservable skills or career motivation enter into labor force in the process of increase in female employment rate.
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Notes
Source: OECD Employment Database, http://www.oecd.org/employment/emp/onlineoecdemploymentdatabase.htm, retrieved 11/21/2019.
11th development plan can be reached at http://www.sbb.gov.tr/kalkinma-planlari/
Bhalotra and Fernandez (2018) provides a simple and intuitive mathematical formulation of the model.
Gender segregation can be separated into two components; vertical and horizontal. Horizontal segregation can be broadly defined as the concentration of men and women in different occupations or industries. Vertical segregation denotes the situation whereby opportunities for career progression for a particular gender within a company or sector are limited. In that respect, Ilkkaracan and Sevim (2007) analyzes the relationship between the gender wage gap and horizontal segregation. However, there is no study that analyzes the relation between vertical segregation and gender wage gap in the Turkish labor market. For a detailed discussion of the definitions, see https://www.eurofound.europa.eu/observatories/eurwork/industrial-relations-dictionary/segregation.
I use the psmatch2 module in Stata for the matching analysis. For technical ils see Leuven and Sianesi (2003).
The reason for choosing 2 years of lag is that the data for school enrollment is available only after 2007.
Illiterate workers are assumed to have 0 years of education and illiterate workers without any diploma are assumed to have 3 years of education. Years of education is approximated as 5 years for primary school graduates, 8 years for secondary school graduates, 11 years for graduates, and 15 years for higher education graduates.
https://biruni.tuik.gov.tr/bolgeselistatistik/, retrieved 5/12/2019.
The instrument is strongly correlated with the female employment rate. The F-test of significance in the first-stage regression is approximately 594.
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Aldan, A. Rising Female Labor Force Participation and Gender Wage Gap: Evidence From Turkey. Soc Indic Res 155, 865–884 (2021). https://doi.org/10.1007/s11205-021-02631-9
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DOI: https://doi.org/10.1007/s11205-021-02631-9