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Higher education expansion and women’s access to higher education and the labor market: quasi-experimental evidence from Turkey

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Abstract

We study the 1992 higher education expansion reform in Turkey and examine how the expansion program changed higher education attainment and labor market access, particularly for women, who are disadvantaged on both accounts. We use the 2011 Population and Housing Census and employ a difference-in-differences estimation strategy. We find that the establishment of universities in localities where universities did not exist before increases the higher education attainment of women by 12–13% and their labor force participation by 4%. In contrast, we do not find a program effect for men for either of the two outcomes. That the program did not affect high school graduation suggests that the improvement for women stems from the change in the behavior of the same pool of high school graduates due to reduced monetary and psychic costs. The absence of a program effect for men further suggests that the reduction in schooling costs was not high enough to overcome the lower benefit of having to attend a less reputable local university. As a result of the expansion policy, the gender gap in higher education attainment and labor force participation shrinks. A battery of robustness checks that include an IV estimation supports our findings.

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Fig. 1

Source: CoHE, 2022

Fig. 2

Source: CoHE, 2022

Fig. 3
Fig. 4

Source: authors’ calculations based on Higher Education Student Quotas books published by the Student Selection and Placement Center (OSYM)

Fig. 5

Source: authors’ calculations based on the 2011 Population and Housing Census

Fig. 6

Source: authors’ calculations based on the 2011 Population and Housing Census

Fig. 7
Fig. 8

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Data Availability

The micro data used in this study are available with permission from the Turkish Statistical Institute (TurkStat) and can only be accessed at TurkStat premises.

Notes

  1. Calculated as total enrollment in tertiary education (regardless of the age of the participant) divided by youth population in the 5-year age group immediately following upper secondary school graduation age (http://uis.unesco.org/en/glossary-term/gross-enrolment-ratio-tertiary-education-sex).

  2. Years refer to the beginning of the academic year. For example, the 1992–1993 academic year is referred to as 1992 throughout the paper.

  3. In 1997, compulsory schooling was increased from 5 to 8 years so that children born in 1987 and later were required to stay in school longer. Kırdar et al. (2016) show spillover effects of this reform on high school. The 1987 cohort would have graduated from high school around the same time that university seats were increased in 2006. In 2007, the so-called “headscarf ban” that prevented women wearing a headscarf from entering university campuses was lifted. Furthermore, the number of private universities increased at a much faster pace around this time so that the supply of private university seats also changed.

  4. Authors’ calculations based on 2019 household labor force survey micro data.

  5. The corresponding figures for men for the same year was 75.9% and 85.8%, respectively.

  6. In Fig. 4, the number of seats available in 1995 looks quite high. This might be a data anomaly. Since we construct our measure of intensity by comparing 1996 to 1991, our estimates are not affected.

  7. Another piece of evidence of the role of politics in program placement can be found in the choice of campus locations and staff recruitment. Özoğlu et al. (2016) in their qualitative study on the challenges faced by newly established universities report that the rectors of these universities were frustrated by the interference of local authorities in where the university campus would be located and the hiring of the university staff.

  8. The reference period for labor market outcomes is the last week of September 2011.

  9. The census does not provide information on why individuals migrate. Migration becomes a concern for our study if, for instance, it is more likely for youth in treatment provinces to migrate to get an education as compared to those in control provinces. To see if there is any divergence in the propensity to migrate for education purposes, we turn to another dataset, the Turkish Demographic Health Survey (DHS), that in some years provides information on the reasons for migration among ever-married women. Using the 1998 DHS, we calculate that 30% of 17–25-year-old women do not live where they were born. This figure is lower among youth born in treatment provinces at 24.7% as compared to youth born in control provinces at 36.1%. When we examine the reasons for the move, only 7.6% of the moves turn out to be schooling related. (Note that the move might have taken place at any age until the age we observe our target group in the DHS.) Comparing treatment and control groups, we calculate that only 2.4% of 17–25-year-old women have changed residence for education purposes in the treatment provinces as compared to 1.7% in control provinces. The difference between the two sets of provinces is quite small and is not likely to affect our results.

  10. In the 1990s, the examinees submitted their university/program preferences before they took the exam.

  11. This group might be affected if their high school graduation is delayed due to grade repetition.

  12. We also estimate a model where treatment is a binary variable, with the treated provinces taking the value of 1 and others, 0. Our results are robust to this re-definition. Results are given in Table 9.

  13. Appendix Table A1 shows the results of a regression analysis of the net increase in the number of seats available at the provincial level on the number of young adults of university age (17–25) and high school graduates. The results suggest that the university-age population is positively related to the net increase in seats. When we also control for the number of high school graduates, the R-squared (0.23) does not change. The coefficient of this variable is not statistically significant at conventional levels though it has the expected sign.

  14. The information on the number of 17–25-year-olds by province comes from the 1990 General Population Census. We obtain the number of high school graduates by province from the 1990–1991 Education Statistics Yearbook of the Ministry of Education.

  15. We use a linear probability model for computational efficiency. We also repeat our main results using a logit model. Our results, which are available on request, are robust to using a nonlinear binary model.

  16. Provinces with higher education attainment for a given birth cohort are likely to have a similarly high achievement for the next cohort as well. The cross-correlation among the error terms in a given province may bias the standard errors (Bertrand et al., 2004; Moulton, 1986). Thus, we cluster standard errors at the birth province level.

  17. We also estimate Eq. (2) for men but we do not observe statistically significant effects. Results are available from the authors upon request.

  18. We implemented the De Chaisemartin and D’Haultfoeuille (2020) estimator using did_multiplegt Stata packages.

References

  • Aytac, I. A., & Rankin, B. H. (2004). Modernity, traditionality, and junior high school attainment in Turkey. Social Indicators Research, 66, 267–282.

    Article  Google Scholar 

  • Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. Columbia University Press.

    Google Scholar 

  • Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How much should we trust differences-in-differences estimates? The Quarterly Journal of Economics, 119(1), 249–275.

    Article  Google Scholar 

  • Besley, T., & Case, A. (2000). Unnatural experiments estimating the incidence of endogenous policies. The Economic Journal, 110(467), 672–694.

    Article  Google Scholar 

  • Blanden, J., & Machin, S. (2004). Educational inequality and the expansion of UK higher education. Scottish Journal of Political Economy, 51(2), 230–249.

    Article  Google Scholar 

  • Borusyak, K., Jaravel, X. & Spiess, J. (2021). Revisiting event study designs: Robust and efficient estimation. Working Paper. Available at SSRN: https://ssrn.com/abstract=2826228 or https://doi.org/10.2139/ssrn.2826228

  • Bratti, M., Checchi, D., & de Blasio, G. (2008). Does the expansion of higher education increase the equality of educational opportunities? Evidence from Italy. Labour, 22(Special Issue), 53–88.

    Article  Google Scholar 

  • Breen, R., Luijkx, R., Muller, W., & Pollak, P. (2010). Long-term trends in educational inequality in Europe: Class inequalities and gender differences. European Sociological Review, 26(1), 31–48.

    Article  Google Scholar 

  • Buchman, C., & DiPrete, T. A. (2006). The growing female advantage in college completion: The role of family background and academic achievement. American Sociological Review, 71(4), 515–541.

    Article  Google Scholar 

  • Callaway, B., Goodman-Bacon, A., & Sant’Anna, P. H. C. (2021). Difference-in-differences with a continuous treatment. arXiv:2107.02637 [econ.EM].

  • Caner, A., Guven, C., Ökten, C., & Sakalli, C. O. (2016). Gender roles and the education gender gap in Turkey. Social Indicators Research, 129, 1231–1254.

    Article  Google Scholar 

  • Caner, A., Demirel, M., & Ökten, C. (2019). Attainment and gender equality in higher education: Evidence from a large scale expansion. IZA Discussion Paper No. 12711. Institute of Labor Economics (IZA).

  • Card, D. (1995). Using geographic variation in college proximity to estimate the return to schooling. In L. Christofides, E. Grant, Kenneth, Swidinsky, R. (Eds.), Aspects of labor market behavior: Essays in honor of John Vanderkamp (pp. 201–222). University of Toronto Press, Toronto.

  • Çetinsaya, G. (2014). Büyüme, kalite, uluslararasılaşma: Türkiye yükseköğretimi için bir yol haritası. Yükseköğretim Kurulu, Ankara.

  • Chang, D. (2018). Effects of higher education expansion on gender parity: A 65-year trajectory in Taiwan. Higher Education, 76(1), 449–466.

    Article  Google Scholar 

  • Chesters, J., & Watson, L. (2013). Understanding the persistence of inequality in higher education: Evidence from Australia. Journal of Education Policy, 28(2), 198–215.

    Article  Google Scholar 

  • Cin, F. M., Gümüş, S., & Weiss, F. (2021). Women’s empowerment in the period of the rapid expansion of higher education in Turkey: Developments and paradoxes of gender equality in the labor market. Higher Education, 81, 31–50.

    Article  Google Scholar 

  • Colclough, C., Rose, P., & Tembon, M. (2000). Gender inequalities in primary schooling: The roles of poverty and adverse cultural practice. International Journal of Educational Development, 20(1), 5–27.

    Article  Google Scholar 

  • Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94(Supplement), S95–S120.

    Article  Google Scholar 

  • Council of Higher Education (CoHE) (1996). Recent developments in the Turkish higher education system. CoHE, Ankara.

  • Council of Higher Education (CoHE) (2007). Higher education strategy of Turkey. CoHE, Ankara.

  • Council of Higher Education (CoHE) (2022). Higher education information management system. Ankara. https://istatistik.yok.gov.tr/. Accessed Jan 2022

  • Dayıoğlu, M., Kırdar, M. G., & Tansel, A. (2009). The impact of sibship size, birth order, and sex composition on school enrollment in urban Turkey. Oxford Bulletin of Economics and Statistics, 71(3), 399–426.

    Article  Google Scholar 

  • Dayıoğlu, M., & Kırdar, M. G. (2010). Determinants of and trends in labor force participation of women in Turkey. T.R. Prime Ministry, State Planning Organization and World Bank Working Paper Number 5, World Bank, Ankara.

  • de Chaisemartin, C., & D’Haultfœuille, X. (2018). Fuzzy differences-in-differences. The Review of Economic Studies, 85(2), 999–1028.

    Article  Google Scholar 

  • de Chaisemartin, C., & D’Haultfœuille, X. (2020). Two-way fixed effects estimators with heterogeneous treatment effects. American Economic Review, 110(9), 2964–2996.

    Article  Google Scholar 

  • Denzler, S., & Walter, S. C. (2011). Too far to go? Does distance determine study choices? IZA Discussion Paper no. 5712. Institute of Labor Economics (IZA).

  • Dildar, Y. (2015). Patriarchal norms, religion, and female labor supply: Evidence from Turkey. World Development, 76, 40–61.

    Article  Google Scholar 

  • Dominitz, J., Fischhoff, B., & Manski, C. F. (2001). Who are youth at-risk? Expectations evidence in the NLSY-97. In R. T. Michael (Ed.), Social awakenings: Adolescent’ behavior as adulthood approaches. Russell Sage Publications. https://www.jstor.org/stable/10.7758/9781610443951

  • Duflo, E. (2001). Schooling and labor market consequences of school construction in Indonesia: Evidence from an unusual policy experiment. The American Economic Review, 91(4), 795–813.

    Article  Google Scholar 

  • Duflo, E. (2004). The medium run effects of educational expansion: Evidence from a large school construction program in Indonesia. Journal of Development Economics, 74, 163–197.

    Article  Google Scholar 

  • Flashman, J. (2013). A cohort perspective on gender gaps in college attendance and completion. Research in Higher Education, 54, 545–570.

    Article  Google Scholar 

  • Frenette, M. (2006). Too far to go on? Distance to school and university participation. Education Economics, 14(1), 31–58.

    Article  Google Scholar 

  • Glick, P. (2008). What policies will reduce gender schooling gaps in developing countries: Evidence and interpretation. World Development, 36(9), 1623–1646.

    Article  Google Scholar 

  • Göksel, I. (2013). Female labor force participation in Turkey: The role of conservatism. Women’s Studies International Forum, 41(1), 45–54.

    Article  Google Scholar 

  • Goldin, C., Katz, L. F., & Kuziemko, I. (2006). The homecoming of American college women: The reversal of the college gender gap. The Journal of Economic Perspectives, 20(4), 133–156.

    Article  Google Scholar 

  • Goodman-Bacon, A. (2021). Difference-in-differences with variation in treatment timing. Journal of Econometrics, 225(2), 254–277.

    Article  Google Scholar 

  • Gündüz-Hosgör, A., & Smits, J. (2008). Variation in labor market participation of married women in Turkey. Women’s Studies International Forum, 31(2), 104–117.

    Article  Google Scholar 

  • Jacob, B. A. (2001). Where the boys aren’t: Non-cognitive skills, returns to school and the gender gap in higher education. Economics of Education Review, 21, 589–598.

    Article  Google Scholar 

  • Jensen, R. (2012). The (perceived) returns to education and the demand for schooling. Quarterly Journal of Economics, 125(2), 515–548.

    Article  Google Scholar 

  • Kirdar, G. M., Dayioglu, M., & Koc, I. (2016). Does longer compulsory education equalize schooling by gender and rural/urban residence? World Bank Economic Review, 30(3), 549–579.

    Article  Google Scholar 

  • Mincer, J. (1974). Schooling, experience, and earnings. Columbia University Press.

    Google Scholar 

  • Ministry of National Education (MoNE) and Council of Higher Education (CoHE) (1991). Higher education development plan (1992–2012). MoNE, Ankara.

  • Moulton, B. R. (1986). Random group effects and the precision of regression estimates. Journal of Econometrics, 32, 385–397.

    Article  Google Scholar 

  • Öniş, Z. (1999). Turkey, Europe, and paradoxes of identity: Perspectives on the international context of democratization. Mediterranean Quarterly, 10, 107–136.

    Google Scholar 

  • Oppedisano, V. (2011). The (adverse) effects of expanding higher education: Evidence from Italy. Economics of Education Review, 30(5), 997–1008.

    Article  Google Scholar 

  • Orazem, P. F. & King, E. M. (2008). Schooling in developing countries: The roles of supply, demand and government policy. In Handbook of Development Economics (pp. 3475–559). Elsevier. https://doi.org/10.1016/S1573-4471(07)04107-1

  • Ou, D., & Zhao, Z. (2016). Higher education expansion and labor market outcomes for young college graduates. IZA Discussion Paper no. 9643. Institute of Labor Economics (IZA).

  • Ou, D., & Hou, Y. (2019). Bigger pie, bigger slice? The impact of higher education expansion on educational opportunity in China. Research in Higher Education, 60, 358–391.

    Article  Google Scholar 

  • Özoğlu, M., Gür, B. S., & Gümüş, S. (2016). Rapid expansion of higher education in Turkey: The challenges of recently established public universities (2006–2013). Higher Education Policy, 29, 21–39.

    Article  Google Scholar 

  • Polat, S. (2017). The expansion of higher education in Turkey: Access, equality and regional returns to education. Structural Change and Economic Dynamics, 43, 1–14.

    Article  Google Scholar 

  • Psacharopoulos, G., & Tzannatos, Z. (1989). Female labor force participation: An international perspective. The World Bank Research Observer, 4(2), 187–201.

    Article  Google Scholar 

  • Reimer, D., & Pollak, R. (2010). Educational expansion and its consequences for vertical and horizontal inequalities in access to higher education in West Germany. European Sociological Review, 26(4), 415–430.

    Article  Google Scholar 

  • Rosenzweig, M. R., & Wolpin, K. I. (1986). Evaluating the effects of optimally distributed public programs: Child health and family planning interventions. American Economic Review, 76(3), 470–482.

    Google Scholar 

  • Smits, J., & Hoşgör, A. G. (2006). Effects of family background characteristics on educational participation in Turkey. International Journal of Educational Development, 26, 545–560.

    Article  Google Scholar 

  • Spiess, C. K., & Wrohlich, K. (2010). Does distance determine who attends a university in Germany? Economics of Education Review, 29(3), 470–479.

  • SPO & World Bank (2009). Female labor force participation in Turkey: Trends, determinants and policy framework. T.R. Prime Ministry, State Planning Organization and World Bank, Ankara.

  • Tunalı, I., Kırdar, G. M., & Dayıoğlu, M. (2021). Down and up the “U” - A synthetic cohort (panel) analysis of female labor force participation in Turkey, 1988–2013. World Development, 146. https://doi.org/10.1016/j.worlddev.2021.105609

  • Turkish Statistical Institute (TurkStat) (1995). National education statistics formal education 1992–1993. TurkStat, Ankara.

  • Turkish Statistical Institute (TurkStat) (2023). Data portal for statistics. https://data.tuik.gov.tr/. Accessed Jan 2023

  • UNESCO (United Nations Educational, Scientific and Cultural Organization). (2022). Institute for statistics (UIS), UIS.Stat Database. http://data.uis.unesco.org/. Accessed Jan 2022

  • Valero, A., & Van Reenen, J. (2019). The economic impact of universities: Evidence from across the globe. Economics of Education Review, 68, 53–67.

    Article  Google Scholar 

  • Wu, X., & Zhang, Z. (2010). Changes in educational inequality in China, 1990–2005: Evidence from the population census data. Research in Sociology of Education, 17, 123–152.

    Article  Google Scholar 

  • Wu, L., Yan, K., & Zhang, Y. (2020). Higher education expansion and inequality in educational opportunities in China. Higher Education, 80, 549–570.

    Article  Google Scholar 

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Acknowledgements

We would like to thank the editor, Brendan Cantwell, and two anonymous referees for their valuable comments and suggestions. The usual disclaimer holds.

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Authors and Affiliations

  1. Statistical, Economic and Social Research and Training Centre for Islamic Countries (SESRIC), Ankara, 06800, Turkey

    Ahmet Öztürk

  2. Department of Economics, TED University, Ankara, 06420, Turkey

    Meltem Dayıoğlu

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  1. Ahmet Öztürk
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Appendix

Appendix

Fig. A1

figure 9

Source:TurkStat, 2023

Real GDP and population growth (%). 

Table A1

Determinants of number of seats available in higher education programs

 

Dependent variable: the net increase in the number of seats available in higher education institutions from 1991 to 1996

Number of young adults aged 17–25 (*10−3)

9.43 (2.10)***

6.69 (3.38)*

Number of high school graduates (*10−3)

 

102.27 (127.16)

R-squared

0.23

0.23

# of observations

54

54

  1. Note: robust standard errors are in parentheses.

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Öztürk, A., Dayıoğlu, M. Higher education expansion and women’s access to higher education and the labor market: quasi-experimental evidence from Turkey. High Educ (2023). https://doi.org/10.1007/s10734-023-01122-9

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