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Education, political discontent, and emigration intentions: evidence from a natural experiment in Turkey

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Abstract

We exploit the 1997 school reform that prolonged compulsory schooling from 5 to 8 years to investigate the causal effect of education on emigration intentions. Our IV estimates indicate that an additional year of schooling increases the probability of reporting the intention to emigrate by 24% points. Moreover, we provide evidence that the identified effect of education on emigration intentions does not operate through financial dissatisfaction, but rather through displeasure at a bleak political environment that better educated people are more keenly aware of.

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Notes

  1. See Cesur and Mocan (2013) for a detailed discussion of the political developments leading to the enactment of the 1997 education reform.

  2. Turkey is divided into 12 main regions and 26 sub-regions. In our empirical analysis, the geographic variables are measured at the sub-regional level. We merged, however, six small sub-regions with neighboring larger sub-regions to arrive at a minimum of 50 observations per sub-region. Our 20 sub-regions are Istanbul, West Marmara, Izmir, Aydin, Manisa, East Marmara, Ankara, Konya, Antalya, Adana, Hatay, Central Anatolia, Zonguldak and Kastamonu, Samsun, East Black Sea, Northeast Anatolia, Malatya, Van, Gaziantep, Sanliurfa and Mardin.

  3. For example, during 1997–2000, the enrollment rate in the sub-region with the lowest pre-reform enrollment rate (Van) rose by 37%, while the enrollment rate in the sub-region with the highest pre-reform enrollment rate (Ankara) increased by 7%. The difference between the enrollment rates of the two sub-regions declined from 20 to 7% points over the same period.

  4. The gross primary school enrollment rate in grades 6–8 is defined as the ratio of the number of students enrolled in grades 6–8 to the population of children aged 11–13.

  5. In the 2004 Implementation Completion Report (ICR) of the World Bank, the Basic Education Program is, for example, evaluated as “unsatisfactory” in meeting the objective of “training of teachers, principals and inspectors” (p. 7) (retrieved from http://documents.worldbank.org/curated/en/2004/06/4653454/turkey-basic-education-program-project).

  6. See for information on KONDA’s media coverage http://www.konda.com.tr/tr/uluslararasi_basin.php.

  7. The surveys typically interview 1800 to 3600 individuals aged 18 or older. Interviews are conducted face-to-face in the respondents’ homes.

  8. Children of primary school age are 6–13 years old.

  9. National Education Statistics and Population Censuses are provided by the Turkish Statistical Institute.

  10. In the survey, the respondents are asked to report their religious affiliations as one of the following: Sunni Muslim, Alevi Muslim and Other.

  11. The question on ethnicity lists the following possible responses: Turkish, Kurdish, Arabic and Other.

  12. Using data from the German Socio-Economic Panel, Jaeger et al. (2010) examine the relationship between migration and risk attitudes. They find that less risk-averse individuals are more likely to migrate internally.

  13. Duflo (2001) capitalizes on a primary school construction program in Indonesia to investigate the causal effect of education on wages. Exploiting regional differences in program intensity, measured by the number of new schools constructed per primary school aged child, Duflo (2001) uses the interaction between the year of birth and program intensity as an instrumental variable for education. Other studies use similar identification strategies to estimate the causal effect of education on a range of outcomes, including fertility, infant and child health, and women's empowerment (Chou et al. 2010; Dincer et al. 2014; Gunes 2015; Osili and Long 2008).

  14. This law was published in the Official Gazette of the Republic of Turkey (# 21308) on 7 August 1992.

  15. We form the treatment and control groups under the assumption that students started the first grade at the age of six and did not experience grade retention until the fifth grade. It is quite possible that some individuals who were at the fourth grade in summer 1996 may have repeated that grade and ended up being at the fourth grade in summer 1997 and thus were exposed to the reform. Given the fact that we incorrectly assign those individuals to the control group, grade retention potentially leads to a downward bias in the estimated effect of education.

  16. Using the same education reform as a source of exogenous variation in education, Dincer et al. (2014) and Gunes (2015) also exploit geographic differences in the intensity of reform to investigate the causal effects of education on several outcomes. Dincer et al. (2014) use the variation in the number of primary school teachers across regions to capture reform intensity, while Gunes (2015) uses the variation in the number of primary school classrooms across provinces for the same purpose.

  17. To be more specific, consider two individuals who were born in the same region in 1987 and 1988, respectively. Child A, born in 1987, is matched with the 1998 value of the reform-intensity measure in her region of birth, while child B, born in 1988, is matched with the respective 1999 value.

  18. The reform's intensity is measured with error if the region of birth is different from the region of education. To alleviate that measurement error, we exclude in a robustness test all individuals who did not live in the region where they were born at the time of the survey. The results from that robustness check are presented in column E of Table 3.

  19. The gross primary school enrollment rate is the ratio of the number of students enrolled in grades 1–8 to the number of children aged between 6 and 13 in the region of birth.

  20. As a rule of thumb, in the case of a single endogenous regressor, the instrument is considered to be weak if the first-stage F-statistic is less than 10 (Staiger and Stock 1997).

  21. Estimation results based on Eq. (3) are available upon request.

  22. The reference categories for the educational attainments “s” are as follows: illiterate (i.e., people who cannot write and read), less than elementary education (i.e., less than 5 years of schooling), elementary education (i.e., 5 years of schooling), middle school diploma (i.e., 8 years of schooling), high school diploma, and college education.

  23. Several explanations are possible for why the IV estimate exceeds the OLS estimate. First, unobserved factors that have (1) a negative effect on the intention to migrate and are (2) positively correlated with education would result in a downward bias in the OLS estimate. The literature on the relationship between subjective well-being and the intention to migrate indicates, for example, that people who are satisfied with their lives are less likely to consider emigration (Otrachshenko and Popova 2014; Chindarkar 2014; Cai et al. 2014), and several studies suggest a positive and statistically significant association between education and self-reported life satisfaction (e.g., Blanchflower and Oswald 2004; Easterlin 2001; Ferrer-i-Carbonell 2005; Graham and Pettinato 2002). Second, classical measurement error in schooling exerts a downward bias on the OLS estimate. Third, in the presence of heterogeneous treatment effects, the IV estimator may identify the average effect of education for the subpopulation of individuals who completed more schooling because of the reform, i.e., the IV estimate may well capture the average effect of the additional three years of schooling among children who would not have completed those extra three years of schooling in the absence of the reform. The effect of primary school completion on the probability of reporting emigration intentions is likely to be larger for the subpopulation at the lower end of the education distribution than for the entire population.

  24. In Turkey, Kurdish people mostly live in the south-eastern provinces where PKK’s terrorist activities mainly have been concentrated. When we exclude respondents who live in south-eastern provinces from the analysis, the estimated effect of education on the probability of reporting emigration intentions remains statistically significant at the 10% level, but shrinks somewhat in magnitude.

  25. Among 145 countries, Turkey is stuck at rank 130 in the 2015 Global Gender Gap Report published by the World Economic Forum WEF (2015).

  26. Ivlevs (2015), who likewise examines emigration intentions, finds a similar result for a similar sample (post-socialist and selected Western European countries).

  27. Most studies find that education is causally linked to health, but not all do so. Dursun et al. (2018) also exploit the 1997 education reform in Turkey to examine the causal effect of education on several health outcomes. They find that education has no statistically significant effect on men’s self-reported health status while education increases the probability of reporting excellent health for women. Cutler and Lleras-Muney (2012) provide a review of the literature.

  28. Using the Household Labor Force Survey conducted by the Turkish Statistical Institute and also exploiting the 1997 education reform to examine the effect of education on labor market outcomes, Torun (2018) demonstrates that extending primary schooling does not have a statistically significant effect on the wages of males, while the effect is positive and statistically significant for females. He also finds that the 1997 education reform does not affect the probability of being employed for both males and females. Our dataset does not contain information on the respondents’ earnings, but observes household incomes. We investigate the causal effect of education on household income. The results indicate that the causal effect of education on household income is not statistically significant at conventional levels; in that empirical analysis, the number of observations declines to 1354 owing to missing data on household income.

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Acknowledgements

We thank Bekir Ağırdır for providing us with the data and Eren Pultar who answered our numerous survey-related questions with admirable patience. We also thank two anonymous reviewers, the guest editor, Arye Hillman, and the editor-in-chief, William F. Shughart II, for helpful comments.

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Authors and Affiliations

  1. Católica Porto Business School and CEGE, Universidade Católica Portuguesa, R. de Diogo Botelho 1327, 4169-005, Porto, Portugal

    Z. Eylem Gevrek

  2. Department of Economics, University of Konstanz, Box 138, 78457, Constance, Germany

    Pinar Kunt & Heinrich W. Ursprung

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  1. Z. Eylem Gevrek
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  2. Pinar Kunt
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  3. Heinrich W. Ursprung
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Correspondence to Z. Eylem Gevrek.

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Gevrek, Z.E., Kunt, P. & Ursprung, H.W. Education, political discontent, and emigration intentions: evidence from a natural experiment in Turkey. Public Choice 186, 563–585 (2021). https://doi.org/10.1007/s11127-019-00724-1

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