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Hidden gender dimensions of the brain drain: the case of Turkey

Published online by Cambridge University Press:  26 June 2019

Adem Yavuz Elveren
Affiliation:
Fitchburg State University, MA, US, aelveren@fitchburgstate.edu
Gülay Toksöz
Affiliation:
Ankara University, Ankara, Turkey, gulay.toksoz@gmail.com
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Abstract

This study examines the gender dimension of the brain drain in Turkey, drawing on the results of an online survey to argue that the gender inequality present in sending countries can serve as a push factor in women's decisions to migrate and return or not return. The results indicate that the gender gap in the labor market in Turkey is an important factor in shaping the return intentions of female Turkish professionals and students living abroad. The findings reveal a gender gap in return intentions independent of other main factors, such as age, field of study/occupation, or duration of stay.

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Articles
Copyright
© New Perspectives on Turkey and Cambridge University Press 2019 

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Introduction

The international literature on the gender dimension of the migration of highly skilled women is rather sparse. Existing studies show that there has been a steady increase in the number of highly skilled female migrants in countries of the Organization for Economic Cooperation and Development (OECD), which is explained by the rise in the rate of women’s schooling and an increasing tendency to move.Footnote 1 According to one recent study, the number of highly skilled women migrants in OECD countries increased from 5.7 million to 14.4 million between 1990 and 2010, ultimately surpassing the number of highly skilled men migrants.Footnote 2 Docquier et al. claim that educated women are better able than uneducated women to escape from sexual discrimination in their countries of origin.Footnote 3 Gender sensitive literature argues that gender disparities in education, labor force participation rates, and income levels in the origin country are all important push factors for skilled female migrants.Footnote 4

There are only a few studies on this topic as it relates to Turkey, and even these only focus on the issue partially. However, considering the fact that gender inequality is increasing in Turkey—partly due to a shift over the last decade toward a more authoritarian regime with Islamic roots—it is especially important to investigate Turkey’s brain drain with a particular focus on the gender dimension. The main question is whether there are differences between highly skilled women and men migrants regarding their decisions to emigrate and work abroad, and, if so, whether they mention different push and pull factors.

To this end, this study will quantitatively analyze the return intentions of students and professionals living abroad in order to provide a comprehensive picture of gender inequality in Turkey. We will show that the push factors emphasized by women respondents, on the one hand, and gender disparities in Turkey’s labor market, on the other, in fact mirror one another. We will examine the gender dimension of the brain drain by using survey data from 200 Turkish students and professionals living abroad who responded to two comprehensive online questionnaires conducted between late 2015 and early 2016. It is worth noting that the initial purpose of the survey was to analyze the brain drain in general, not its gender dimension specifically. However, when we found a remarkable gender gap in connection with return intentions, it encouraged us to further research the brain drain with a special focus on the gender dimension.

Our findings support most of the previous findings in the literature,Footnote 5 and suggest that some of these have become more significant over time. For instance, political instability, lack of a long-term science and research policy, and lack of academic freedom have become more dominant push factors than others.Footnote 6 The key finding of our work, however, is that Turkish women have a higher tendency than men to emigrate and remain abroad, and that this tendency results more from push factors than pull factors. One particularly significant hidden push factor in the migration decisions of these highly skilled women might be the high level of gender disparity in Turkey, which disadvantages women in the education and labor markets. It is this hidden dimension of the brain drain from Turkey that this study specifically investigates.

The following section will review the international literature on the gender dimension of brain drain along with empirical studies of the brain drain in Turkey and its gender dimension. The third section will discuss gender inequality in Turkey as a background for the quantitative analysis, whose results will be discussed with reference to these inequalities. Finally, the last section will summarize our findings.

The gender dimension of brain drain

As noted above, in recent decades, the number of highly skilled women migrants has come to surpass that of men. Analyses of the causes of this development have investigated both push and pull factors, with some scholars emphasizing gender inequality as an important push factor for women.Footnote 7 We will briefly review this literature insofar as it seems relevant in evaluating the corresponding situation in Turkey. Among the push factors, the gender gap in education plays an important role in that the strong growth exhibited toward the end of the twentieth century in terms of the proportion of more highly skilled women emigrants to the total number of skilled migrants is considered to be related primarily to the rise in the level of women’s schooling and to their increasing tendency to move. Newer data from Docquier et al. on the numbers of emigrants and rates of emigration show that highly skilled women are emigrating at a higher rate than men.Footnote 8 More specifically, the average migration rate of females with post-secondary education is both 17 percent higher than that of males and strongly correlated with the gender gap in the educational attainment of the source population, reflecting unequal access to education. Docquier et al. conclude that educated women are better able than uneducated women to escape gender discrimination in their country of origin.

Bang and Mitra reached similar conclusions regarding the role of access to education in relation to the brain drain for men and women in OECD countries.Footnote 9 Looking at gender bias in access to education, as well as in outcomes like labor force participation rates and income levels, they found that bias in access to educational opportunities and higher female fertility rates both serve as important push factors. In countries where women have more equal access to education and lower fertility rates, female brain drain rates are lower, while they are higher in countries with a wider gender gap in education and higher fertility rates. Finally, they also found that the quality of political institutions affects the brain drain of both genders similarly. However, critical approaches to brain drain discourse from a feminist perspective argue that, even when political conditions are considered as a factor that influences the decision-making process, neither gender differences in the experience of political, social, and cultural conditions nor the career aspirations of highly skilled women have been adequately taken into account.Footnote 10

To fill the gap in the gender-specific aspects of the brain drain literature, Nejad looked at the effects of women’s rights on the gender gap in highly skilled migration.Footnote 11 She argued that, although women in countries with very low levels of women’s rights lack the freedom to migrate, just a small increase in a country’s women’s rights index increases the female brain drain rate. Nejad and Young then explored women’s rights as a determinant of the female brain drain rate relative to that of men, using women’s economic, social, and political rights indices from the Cingranelli and Richards (CIRI) Human Rights Dataset, as well as migration flows across OECD and non-OECD countries.Footnote 12 They concluded that when women’s rights levels are higher in the destination country than in the origin country, highly skilled women are more likely to migrate than men.

The influence of women’s rights in both origin and destination countries on women’s migration decisions is not limited to highly skilled female migrants. Using Gallup World Polls conducted between 2009 and 2013, and measuring gender discrimination in terms of the proportion of female respondents who stated that women in their country were not treated with respect and dignity, coupled with the respondents’ desire to migrate, Ruyssen and Salomone claim that “[o]verall we find that women who do not feel treated with respect and dignity in their country have a stronger desire to move out. Perceived gender discrimination hence positively affects the size of potential female migration.”Footnote 13 However, highly skilled, employed, and secular women are more likely to actually turn their desires and plans into action.Footnote 14 One concrete example of this is the case of Iran. After Ayatollah Ruhollah Khomeini and the Islamic government took power in Iran, the number of individuals with tertiary education and special skills emigrating from Iran increased enormously, with a large proportion being women escaping religious and ideological restrictions and gender-based discrimination.Footnote 15

The gender dimension of the migration decision has been noted in other studies as well. Nowak, for instance, argued that worsening socioeconomic conditions in Ghana led to flexibility in gender norms toward migration among female nurses.Footnote 16 Zweig and Changgui, focusing on scientists, engineers, and students, showed that Chinese women are less likely to want to return from the United States to China, as they have more opportunities for career advancement in the former.Footnote 17 Murakami also notes a similar situation in the case of Japan, in line with Ono and Piper.Footnote 18 Spadavechhia claims that women from sub-Saharan Africa move to Europe to escape an environment shaped by strict gender roles that confine them to the household and restrict their access to credit, land, and means of production.Footnote 19 A very similar situation is noted by Reynolds for professional women in Nigeria.Footnote 20 Klüsener et al., using a 2011 data set prepared by Statistics Lithuania and covering Lithuania’s entire population, made a connection with emigration data to find that persistent gender inequality is one possible factor why highly educated women are more likely to emigrate than their male peers.Footnote 21 Finally, Alberts and Hazen report the effect of differing gender roles between the United States and the home countries of international students in relation to their return intentions or lack thereof.Footnote 22

Some researchers, however, argue that gender inequality is not a significant push factor. Based on original indices for gender inequality in labor markets and migration data provided by Docquier et al. and covering the years 1991–2001, Baudassé and Bazillier did not confirm the theory that gender inequality in origin countries is a push factor for women.Footnote 23 Similarly, based on data obtained from Botswanan students in their final year in tertiary education between October 2002 and January 2003, Campbell found no significant gender differences in connection with the intention to emigrate.Footnote 24 The study also found that men are more likely to prefer to migrate alone. Bartolini, Gropas, and Triandafyllidou, based on a survey conducted in 2013, also failed to find any general gender differences in migration decisions.Footnote 25 Finally, Rangelova showed that, although there are no noticeable differences between men and women in terms of the purpose of migrating, women are more likely to resettle abroad than men.Footnote 26 The same study also found that Turkish women are more likely to migrate than other ethnicities, specifically women from the Bulgarian and Roma communities.

Overall, the above brief literature review reveals opposing views on whether gender inequality is a possible push factor for women migrants. This is hardly unexpected considering that the studies focus on different countries, for different time periods, and using various data and methods, all of which prevents a direct comparison of the results. In fact, this situation only encourages further research investigating the existence of such a causality for other countries. Thus, in the following sections, we will examine this issue in the case of Turkey.

During the 1960s, Turkey was a sending country for western European labor markets, especially Germany, in order to fulfil these markets’ demand for low-skill manual workers. The general characteristics of this migration can be explained in terms of traditional push and pull factors,Footnote 27 with the migrant workers’ dominant feature being their low skill levels. More specifically, according to Docquier et al., of the top 30 migrant-sending countries, Turkey was the fifth largest in 2000 yet fourth to last in terms of the proportion of skilled emigrants.Footnote 28 Skilled workers made up only 9 percent of Turkey’s total emigrants, and of these, only 36.5 percent were women—the lowest rate of all 30 countries. Turkey also had one of the lowest figures when considering migratory movements in terms of country of origin and destination, with only 6.3 percent of Turkish migrants in Germany in 2000 being highly skilled, of which 45.8 percent were women.Footnote 29 Of the OECD countries, which are the preferred destination countries for highly skilled migrants, the US, United Kingdom, Canada, and Australia received 70 percent in 2010, with the US alone taking 41 percent.Footnote 30 The US is also the most preferred destination country for highly skilled migrants from Turkey. According to data from the International Institute of Education (IIE), there were 10,691 Turkish students in the US during the 2015/2016 academic year, making Turkey the thirteenth largest source country,Footnote 31 while 469 Turkish students on temporary visas took doctorate degrees in 2015 (387 in science and engineering, 82 in other fields), which had risen from 390 in 2005, making Turkey sixth after China, India, South Korea, Iran, and Taiwan.

Despite the sizable literature on Turkey’s migration issue, few studies have focused on the brain drain specifically, including empirical research that investigates the migration of highly skilled workers. Empirical studies provide a detailed picture of the brain drain in Turkey.Footnote 32 Early studies from the late 1960s and early 1970s found that the key reason for the intention to migrate or remain abroad was low wages in Turkey, although greater opportunities to specialize, as well as hierarchical authority and political pressures in Turkey, were also mentioned.Footnote 33 During the 2000s, new research provided a more comprehensive analysis, dealing with various aspects of migration and applying statistical methods. In addition to low wages and career concerns,Footnote 34 participants often mentioned lack of respect for science and academics in Turkey, lack of freedom of expression, workplace dissatisfaction, and political instability as main push factors.Footnote 35

Finally, over the last decade, while wage differentials between resident countries and Turkey specifically and life standards in general have become secondary factors, political instability and lack of academic freedom, or else dissatisfaction with general science policy or Turkey’s higher education system, have become major push factors in emigrants’ decisions to remain abroad. Esen, for example, reports that those who stay value research opportunities more than their wages, especially given that Turkey’s private universities currently provide a better deal once salary and fringe benefits are considered.Footnote 36 For non-returners, lack of academic freedom, fewer academic opportunities, and political instability outweigh Turkey’s recent economic growth.Footnote 37

Although none of these studies offer a gender perspective on the brain drain, a few nevertheless provide important contrasting findings on gender differences in relation to migration and/or return decisions. For example, Akman found that male students are more likely to intend to work and settle abroad;Footnote 38 Mollahaliloğlu et al. reported that male physicians are 1.5 times more likely to wish to live abroad;Footnote 39 and finally, Öztürk found that female students were not significantly more likely than male students to return to Turkey after graduating.Footnote 40 According to Güngör and Tansel, women students show less tendency to return to Turkey than men, perhaps due to the gender gap in Turkey’s labor market and less freedom in social life.Footnote 41 Two other studies by the same authors showed that females are more likely to report their intention to stay abroad than males.Footnote 42 Based on the same data set used in these three studies, Güngör showed that women are more likely to migrate due to greater opportunities for advanced training and work, as well as because they have concerns about the possibility of advancing in their jobs in the home country.Footnote 43 Güngör also underscores how women are more likely to migrate and not return because they are more affected by economic decline and the lack of social security in Turkey.Footnote 44 She also showed, however, that “political discord, bureaucracy, and lack of financial resources to conduct business in Turkey” is a “more important push factors for male respondents”.Footnote 45 Finally, Güngör noted that women are more dependent on men in their migration decisions. This small number of studies yields seemingly contrasting results on the gender dimension of migration in Turkey. However, considering the coverage and methodology of this research, by especially emphasizing Güngör and Tansel’s comprehensive studies, it is safe to argue for the existence of the gender gap in migration decisions in Turkey.

The gender gap and gender inequality in Turkey and its impact on female brain drain

In this section, we explain, with reference to the survey results, how gender inequality in Turkey serves as a major push factor for women in Turkey regarding their decisions to emigrate and not return once they are abroad. The survey was based on two comprehensive online questionnaires conducted between late 2015 and early 2016 and responded to by 200 Turkish students and professionals living abroad. We argue that gender disparity in the education and labor market in Turkey constitutes a significant hidden push factor in the migration decisions of highly skilled women in Turkey.Footnote 46 The following section reports on this hidden dimension of the brain drain from Turkey, which has not been directly addressed as a factor of the migration or non-return decisions of high-skill women in Turkey.

The gender gap and discrimination against women in Turkey

Gender inequality is a particularly striking aspect of the economic, social, and political structure in Turkey. According to the United Nations’ Human Development Index (HDI), in 2016 Turkey ranked 71st, with an index value of 0.767 (0.724 for females and 0.797 for males), among 188 countries with high human development. Besides gender differences in expected and mean years of schooling, there is also a major gap in the estimated gross national income per capita (in 2011 PPP US dollars) of 10,648 dollars for females and 27,035 dollars for males, a result of the low labor force participation rate of women.Footnote 47 On the Gender Inequality Index, Turkey had a value of 0.328 in 2015, placing it 69th among 159 countries. More specifically, whereas only 43.5 percent of females in Turkey have at least some secondary education, 64.8 percent of males do, while the labor force participation rate is 30.4 percent for females but 71.4 percent for males. This huge gender disparity in terms of labor force participation helps explain the massive gender gap in gross national income per capita mentioned above.

Because Turkey’s potential European Union (EU) candidacy requires harmonization with the EU acquis during the accession period starting in 2004, Turkey’s government has revised legislation from the perspective of gender equality so as to remove almost every discriminatory aspect from laws and directives. Nevertheless, discriminatory mentalities and practices continue.Footnote 48 As such, indices dealing with gender inequalities need to go beyond legal regulations in order to capture the real dimensions of inequalities. According to the country scores and sub-indices of the OECD’s 2014 Social Institutions and Gender Index Synthesis Report, Turkey has a low level of discrimination in regard to discriminatory family codes, restricted physical integrity, and restricted resources and assets, but a high level of discrimination against daughters along with restricted civil liberties.Footnote 49

The report also notes how challenges remain across OECD countries in connection with unpaid care work. On average, women spend more than twice as much time as men on such work, but in Japan, Korea, and Turkey, this increases to five times more.Footnote 50 The unequal distribution of paid and unpaid work between men and women in Turkey is the leading injustice in the country’s social structure and has both economic and political consequences that are manifested in low female employment, a large gender wage gap, and low female political representation.

In the Gallup and International Labour Organization (ILO) survey on women and work, differences in the answers given by men and women to various questions show men’s conservative, gender-based perceptions of the division of labor regarding women’s employment in Turkey.Footnote 51 While 34 percent of Turkish women wanted to work in a paid job, 12 percent wanted to stay at home and 53 percent said they wanted both. In contrast, only 28 percent of men preferred that the women in their family work in a paid job, while 32 percent preferred that they stay at home and 34 percent preferred both. Even 18 percent of men with tertiary education wanted women in their family to stay at home. These values place Turkey as one of the countries with the largest gender gaps in terms of opinions about women’s work. Whereas the percentages of women who would like to have paid jobs or both do paid work and care for the home are 70 percent globally and 87 percent for women in Turkey, for men they are 66 percent globally and 62 percent for men in Turkey, revealing a gap of 25 percent.

According to the Polity IV Index,Footnote 52 Turkey is characterized by open anocracy, which means a regime of partial democracy and partial autocracy. The regime in Turkey has shifted further toward authoritarianism since the constitutional referendum on April 16, 2017, which was accepted by 51.4 percent of voters but took place under a state of emergency. According to the Venice Commission, the constitutional amendments will excessively concentrate executive power in the hands of the president, weaken parliamentary control of that power, and curtail the independence of the judiciary vis-à-vis the president. The Venice Commission’s concern over the concentration of power proved fully justified with the elections of June 2018. Such political developments as these may also increase the brain drain from Turkey inasmuch as educated people generally prefer to live in more democratic and politically stable environments, as well as to have freer, “Westernized” lifestyles, both individually and socially.Footnote 53

The international indicators regarding women’s rights and gender equalities mentioned above highlight gender disparities in Turkey that disadvantage women in education and labor markets and serve as important factors in the migration decisions of highly skilled females. As Ruyssen and Salomone argue, perceived gender discrimination may increase the size of potential female migration.Footnote 54 To deal with this issue in a more comprehensive manner, we will first look at our general survey results in order to evaluate them within the framework of detailed comparative statistics on tertiary education and professional occupations for men and women in Turkey.

Findings of the survey on the brain drain in Turkey

Our data was collected using two online questionnaires, accessible for about five months from late 2015 to early 2016: a 46-item questionnaire in English for professionals, and a 53-item questionnaire in both Turkish and English for students. For comparison purposes, the questionnaires were based mainly on Güngör.Footnote 55 Detailed descriptive statistics and questionnaire responses for the 116 students and 84 professionals who replied to all questions in the relevant survey are presented below so as to measure their intentions to return or not return. The questionnaires were distributed through social media and emailed to relevant social and professional email groups for about five months, based on referral and snowball sampling methods.

Both groups of emigrants are relatively young, with 82 percent of the students younger than 30 years old and 77.4 percent of the professionals younger than 40 years old. There is a relatively equal gender distribution: 41.4 (58.6) percent of the students and 33.3 (66.7) percent of the professionals are female (male), with 38 percent of all participants being female and 62 percent male. This reasonably balanced distribution enabled us to investigate further possible differentiations.

While 63 percent of the professionals come from İstanbul, Ankara, or İzmir, only about 40 percent of the students were born in these three cities, which are the largest in Turkey. The rest (about 60 percent) of the students come from 46 different provinces across the country. A significant percentage of both the students (86.1 percent) and professionals (82.1 percent) reside in the US, followed by the UK, Canada, and major European countries.

Considering the available statistics and the basic characteristics of the samples of other major studies—such as those of Güngör and Tansel, as well as Esen—these basic descriptive statistics suggest that our sample is a robust representation of the target population.Footnote 56 The distribution of origin cities in Turkey, the most popular host country (i.e., the US), and the fields of study and work are all in line with the general characteristics of Turkish students and professionals living abroad. It is worth noting, however, that our sample may be biased in terms of the age of the professionals, as they are relatively young. Nevertheless, it is justifiable to argue that this downward bias in terms of age does not lessen the validity of our results. Indeed, since our findings suggest that there is a positive association between the duration of stay and the intention not to return, it is safe to conclude that the results would be more likely to suggest a stronger intention not to return in an older group of professionals.

Regarding qualifications, 42.2 percent of the students’ highest degrees are master’s degrees, while 30.2 percent hold a bachelor’s degree and 18.1 percent a Ph.D. degree. Only 8.3 percent of the professionals hold a bachelor’s degree, while 61.9 percent have a Ph.D. and 26.2 percent a master’s degree. Of the professionals, 41.7 percent hold academic positions while 58.3 percent have non-academic positions. Only 17.9 percent of the professionals received their highest degree from an institution in Turkey, with 73.8 percent obtaining their highest degree in the US. Conversely, 64.7 percent of students earned their highest degree in Turkey, compared to 26.7 percent from the US.

The respondents were drawn from both the natural sciences and the social sciences, and are not restricted to only a few occupational categories, like doctors or engineers. While 56.4 percent of students are in the natural sciences, 43.6 percent are in social sciences. For the professionals, these ratios are 60.7 percent and 39.3 percent respectively. This relatively balanced distribution allowed us to investigate possible differentiations between these two broad fields.

Our study confirms previous general findings on intentions to migrate and decisions to return. Table 1 shows several correlations tests for initial and current (non-)return intentions. One of the most significant results is the positive relationship between initial and current return decisions, which confirms the findings of both Gökbayrak and Güngör and Tansel.Footnote 57

Table 1. Pearson correlation test results

Note: *, **, and *** refer to significance at the 10%, 5%, and 1% levels respectively. Spearman and Kendall correlation tests yielded very similar results, but in the interests of space are not presented here.

As Table 1 shows, there is a significant positive relationship between current and initial return intentions for all occupation groups and genders according to the Pearson test. “Initial return intention” refers to respondents’ intention to return at the time they left the country or in their early years in the resident country. However, although there is a positive correlation between “stay duration (abroad)” and “initial non-return intention” for students and females, that relationship, as expected, is more significant between “stay duration” and “current non-return intention” for all groups. This highly significant result demonstrates the impact of time spend abroad on non-return decisions, supporting Güngör and Tansel.Footnote 58

Age and initial non-return decisions are not significantly correlated. We used four main age categories: < 26, 26–30, 31–40, and > 40. However, for all groups except professionals, age is positively associated with the current non-return decision, which is also in line with Güngör and Tansel,Footnote 59 presumably because the costs of migration may be higher for older people, as argued by Güngör.Footnote 60

Both students and professionals who received their degree from a foreign university are also more likely to not intend to return, which also supports Güngör and Tansel,Footnote 61 although this is not true for initial return intentions. Moreover, social science graduates (both students and professionals) are more likely than natural science graduates to intend to return.Footnote 62

Finally, there is a highly significant negative correlation between the length of experience abroad and the current return intention. That is, those who have spent more time abroad are less likely to intend to return; those who initially decided to stay abroad are likely to intend to stay currently as well, and this decision only becomes more entrenched over time.

Our study also reveals some significant gender differentiations. One of these is that current non-return intentions are significantly higher than initial non-return intentions for women. Table 2 shows the differences between initial and current stay intentions by gender. While the proportion of males intending to stay increased by about 82 percent (from 22 to 40), it increased by as much as 158 percent for females (from 12 to 31). It thus seems reasonable to argue that women are more likely to appreciate living abroad due to the greater opportunities there (or, conversely, the lack of opportunities in their home country).

Table 2. Initial and current return intentions (Number of respondents)

The second finding in relation to gender is that females are more likely to go abroad again. Those who reported their intention to return were also asked if they planned to return abroad again, and Table 3 presents the answers to this question by gender.

Table 3. Plan to go abroad again by occupation and gender (%)

Note: Students: Chi Squared (2) = 3.744; Professionals: Chi Squared (2) = 4.169; Total: Chi Squared (2) = 5.163*, where * refers to significance at the 10% level.

Table 4. Push and pull factors rated as “important” or “very important” (%)

Note: *, **, and *** refer to significance at the 10%, 5%, and 1% levels respectively.

Notably, a higher proportion of students (31.8 percent) than professionals (13.2 percent) intend to go abroad again. For both students and professionals, there is also a significant difference between genders in this regard. While 24.5 percent of male students plan to return abroad, 43.8 percent female students do. Similarly, nearly twice as many female professionals as male professionals (20.0 versus 10.7 percent) plan to go abroad again.

To understand the reasons why women have higher non-return intentions and are more likely to go abroad again as compared to men, we need to look at the education and labor market opportunities for women in Turkey, which will be examined in the following section.

Education

The gender gap in education in Turkey is manifested in the TurkStat gender indicators that follow.Footnote 63 In 2015, for the population aged 25 years and older, for every 100 female elementary school graduates there were 76 men, for every 100 female high school graduates there were 151 men, and for every 100 female higher education graduates there were 136 men. That is to say, fewer women than men were able to attend secondary and tertiary education. However, since the adoption of 8-year compulsory schooling in 1997 and 12-year compulsory schooling in 2012, the enrollment rates of female students have started to increase.

Although females make up 45.9 percent of all higher education students, their enrollment rate overtook that of males in 2015, with 42.6 percent versus 39.2 percent, and thus a gender balance in the number of higher education students can be expected in the coming years. Unsurprisingly, however, higher education fields themselves are gendered. Whereas there are 57 men for every 100 women in the areas of language and literature, there are 237 men for every 100 women in the technical sciences. At the same time, however, though women are unsurprisingly concentrated in the health sciences, social sciences, and arts, it is interesting to see that female students outnumber male students in mathematics and the natural sciences in Turkey, with 100 women for every 72 men. Another interesting statistic is the share of female students in the fields of engineering, manufacturing, and construction (29.4 percent) and medicine (49.4 percent), as these areas tend to be rather difficult of access for female students in many countries. Similarly, 30.8 percent of master’s students in engineering, manufacturing, and construction are currently women.Footnote 64 This phenomenon has deep historical roots in Turkey due to the ideological approach of successive governments following the foundation of the republic in 1923, who believed that improving women’s social and political status and supporting their rights in higher education and professional employment was integral to Turkey’s Westernization process. Adopting a rationalist, positivist worldview, these governments promoted the natural and technical sciences and thereby influenced women from middle- and upper-class families in their choices of these fields of study.Footnote 65

The current education data for Turkey is consistent with the literature on the female brain drain, pointing to factors like the gender gap in educational attainment and the rise in women’s levels of schooling, especially in tertiary education. For instance, Dumont et al. and Docquier et al. show that the strong growth in the proportion of more highly skilled women emigrants among the total number of skilled migrants toward the end of the twentieth century is related mainly to the rise in women’s levels of schooling and their increasing tendency to move.Footnote 66 In Turkey, the existing gender gap has only encouraged the rather limited number of highly skilled women to migrate, and we can expect this tendency to strengthen with the increasing enrollment of female students in higher education. Conditions conducive to women’s choices in the natural and technical sciences facilitate the actualization of their migration intentions. Thus, in line with Dumont et al. and Docquier et al., we argue that educated women are better able than uneducated women to escape gender discrimination in Turkey.Footnote 67

The survey data in this study are also consistent with the distribution of female students’ study fields, with engineering and the technical sciences taking the lion’s share among both professional women and men. Given the demand of developed countries for professionals in engineering and related disciplines, being educated in these fields encourages women to emigrate from Turkey. We can therefore assume that this may well be the main source of the female brain drain in Turkey, particularly if these women are frustrated with career opportunities in Turkey due to various forms of gender discrimination in the country’s labor market.

The labor market

As mentioned above, women’s labor force participation (LFP) rate is very low in Turkey in comparison to OECD countries, despite increasing from 23.3 percent in 2004 to 32.5 percent in 2016. This is a manifestation of a rigid gender-based division of labor in which women tend to be responsible for household and care activities whereas men earn the family’s income. However, the LFP rate in Turkey increases with level of education, being 27.2 percent for women with less than secondary education, 33.7 percent for secondary school graduates, and 71.3 percent for tertiary education graduates.Footnote 68 The differences between these rates relate to women’s abilities to reconcile family and work responsibilities in Turkey: whereas women with more education earn relatively high wages as compared to those with less education, thus enabling them to hire care workers or pay for private kindergartens, women with less education and low wages usually have to quit their jobs once they have children owing to Turkey’s lack of affordable public childcare facilities.Footnote 69

However, this increase in the average LFP rate corresponding to level of education is also closely related to higher female unemployment rates, which are particularly high for educated women, resulting in a huge gender gap. In 2016, Turkey’s unemployment rate for high school graduates was 10.5 percent for males but 21.1 percent for females, while for higher education graduates it was 8.8 percent for males and 16.9 percent for females. In other words, women’s unemployment rates are almost double those of men. Furthermore, between 2004 and 2016 the number of unemployed women increased by 113 percent, whereas the rise was only 14 percent for men.Footnote 70 Such high unemployment rates for educated women, which represent possible career frustration, may well have an influence on their decision to migrate.

The occupational distribution of employment coincides with the LFP characteristics of women. Given the economic, political, and cultural obstacles facing little educated and unskilled women, their LFP rate is low, as discussed above. As more highly educated women began to join the labor market at a much higher rate, 15.4 percent of all women were in professional occupations by 2016, as compared to 8 percent of men. Consequently, women represented 45.9 percent of all employees in professional occupations, which matches the percentage of female university students. However, only 15.1 percent of managers are women, indicating that educated women face serious obstacles in terms of career advancement, a factor that may also influence women’s migration decisions.Footnote 71

Another indicator of gender inequality is the gender gap in earnings in Turkey. In 2015, this was 20.8 percent in total earnings in favor of men, varying according to job status. The female-to-male income ratio was 54.9 percent for self-employed workers, 72.1 percent for employers, and 86.8 percent for wage workers. Women in Turkey also earn less than men at all levels of education, with the average annual earnings of women with higher education being 76.7 percent of men’s.Footnote 72 According to data from a household budget survey of 2003, 40 percent of the gender wage gap for female university graduates was due to discrimination.Footnote 73

In Turkey, a conservative religious party, the Justice and Development Party (Adalet ve Kalkınma Partisi, AKP), has been in power since 2002. A critical assessment of the AKP government’s female employment policies indicates that it has replaced a previous egalitarian rhetoric with a focus on the importance of the family for social continuity, giving women the responsibility to maintain and protect the family.Footnote 74 Accordingly, in order to preserve a gender-based division of labor, the government has proposed flexible work options for women, such as part-time work and female entrepreneurship, which result in precarious forms of employment.

The role of gender inequalities as push factors

Within this unequal socioeconomic environment, we can assert that our most significant finding is the difference in the emphasis that female and male students put on push factors. Tables 4 and 5 highlight two important points in this regard. First, while there are no statistically significant differences between the push and pull factors reported by male and female professionals (except for three cases), there are highly significant gender differences for students. Second, the differentiation is far clearer for push factors than for pull factors, particularly for students.

The findings in Tables 4 and 5 deserve a closer look, as there is a clear overlap between the factors that women emphasize statistically significantly more than men and the gender gap in Turkey’s labor market, particularly regarding the categories of “few opportunities for advancement in occupation,” “limited job opportunities in specialty,” “no opportunity for advanced training,” “less satisfying social/cultural life,” “political pressures, discord,” and “economic instability, uncertainty.” Among these factors, “few opportunities for advancement in occupation,” “limited job opportunities in specialty,” and “no opportunity for advanced training” clearly reflect the gender gap in Turkey’s labor market. Women earn less than men at all levels of education, and there are limited opportunities for women to advance in their career. Women with higher education earn 76.7 percent of what men earn, only 15.1 percent of managers are women, and educated women are twice as likely as men to be unemployed. These serious obstacles for women may well be key factors behind the gender gap indicated in the table.

In addition to socioeconomic disparities, one common finding of earlier studies was the lack of respect for science and academics in Turkey, as noted above. Table 5 shows that a “better work environment”—which refers to all aspects of the work atmosphere, rather than just better physical conditions—is significantly more important as a pull factor for women than for men. This indirectly shows that a lack of respect in the work environment is a more serious issue for women. In this regard, the recent purges in academia in Turkey are a highly relevant issue. Although our study does not cover these owing to the timing of the survey, it is important to note that academia in Turkey has been exposed to steadily worsening conditions. For example, academics who signed the peace declaration published in January 2016 have been subjected to multiple forms of repression by government authorities.Footnote 75 This has added tremendously to the ongoing brain drain, making it perhaps the most severe instance thereof in the country’s historyFootnote 76. The most deplorable aspect of this is the violation of the right to movement of these academics and their families. The impact of such a detrimental academic environment has both contributed to a flight of academics from the country and discouraged young Ph.D.s from returning home.Footnote 77

Table 5. Push and pull factors rated as “important” or “very important” (%) (Students and professionals)

Note: *, **, and *** refer to significance at the 10%, 5%, and 1% levels respectively.

It is also striking—though perhaps not unexpected—that while “better educational opportunities for children” is an important pull factor for only 25.8 percent of male students, it is considered important by 60 percent of female students.

Finally, we used an ordered logit regression analysis to test whether being female affected return intentions after controlling for previously examined variables, such as age, initial return decision, stay duration, professional status, and family support. The results, presented in Table 6, suggest that being female does increase the likelihood of an intention not to return, thereby confirming the findings presented in Table 2. That is to say, initially expressing an intention to stay, being initially undecided, and having support (e.g., emotional support) from one’s family all increase the likelihood of intending not to return to Turkey. Similarly, being professional, being female, staying abroad for a longer period, and being in an older age group also increase the intention not to return.

Table 6. Regression analysis of non-return intentions

Note: *, **, and *** refer to significance at the 10%, 5%, and 1% levels respectively.

Conclusion

This study has examined the return intentions of emigrant Turkish students and professionals, with a special focus on gender, a factor that has not received sufficient attention in either Turkish or international studies. Our study’s findings, based on data from 116 students and 84 professionals who responded to two comprehensive questionnaires, support most of the previous findings in the literature, while also providing some new results. Not surprisingly, this study has clarified how economic and professional factors, together with political instability in Turkey, are key determinants of respondents’ decision to return or not return.

This study contributes to the relatively limited literature on migration arguing that gender inequality in the country of origin may be a push factor for women. We have shown that this argument holds in the case of Turkey, with women’s higher tendency to migrate or not return overlapping with the gender gap and gender inequality present in Turkey’s economic and social life. However, as noted earlier, some studies have found no difference between men and women in terms of the motivation to migrate. These conflicting findings in the literature suggest that further research is needed in order to better understand the gender dimension of migration, since the migration decision is a particularly complicated one, being influenced by several factors, among them marital status, parenthood status, income level, education level, age, ethnicity, and religion.

As has been mentioned, although the brain drain in general is a popular topic for scholars from Turkey, very few studies have focused specifically on gender. The recent literature on the brain drain in Turkey, reviewed above, suggests that political instability has become the key push factor. Only a very small part of this literature has a gender aspect, but even this shows that women have a higher tendency than men not to return to Turkey. This study helps to fill this gap in the literature by dealing directly with the gender dimension of the brain drain from Turkey.

We have also discussed the strong link between the gender gap and gender inequality on the one hand and the female brain drain from Turkey on the other. Our research confirms some basic, and unsurprising, early findings in the literature, such as the positive relationships between initial and current return decisions, initial return intention and stay duration, current return intention and stay duration, and current return intention and age.

The key finding in this study is that more women than men currently prefer to stay abroad, and this more because of push factors than pull factors.Footnote 78 We conclude that this is a clear reflection of how Turkey’s current socioeconomic and political climate strongly influences women’s decisions to migrate and not return. The increasing gender disparities in Turkey, which disadvantage women in education and the labor market, serve as significant push factors in the migration decisions of highly skilled females. We also conclude that increasing authoritarianism and Islamization in Turkey will perpetuate this tendency, causing an increasingly massive brain drain from the country.

By shedding some light on the hidden gender dimension of the brain drain in Turkey, this paper will hopefully encourage further studies to address the gender aspects of Turkey’s brain drain in a more systematic manner. In this regard, first, it is essential that questionnaires be prepared specifically so as to address the gender dimension of brain drain; this will allow for a clearer investigation of the difference between women’s and men’s decisions to migrate. Second, as noted earlier, it must be remembered that migration decisions are not made solely by individuals, but are socially bounded; in this sense, it is important to analyze, when the sample size allows, the decisions of women with respect to their social strata. And finally, it is essential to use qualitative methods alongside quantitative methods, because such a comprehensive approach will allow for a better understanding of the dynamics of the decision-making process and the motivations behind migrating and not returning.

Footnotes

1 Jean-Christophe Dumont, John P. Martin, and Gilles Spielvogel, “Women on the Move: The Neglected Gender Dimension of the Brain Drain,” IZA Discussion Paper No. 2920 (Bonn: IZA, July Reference Docquier, Lowell and Marfouk2007); Frédéric Docquier, B. Lindsay Lowell, and Abdeslam Marfouk, “A Gendered Assessment of the Brain Drain,” IZA Discussion Paper No. 3235 (Bonn: IZA, December Reference Docquier, Lowell and Marfouk2007); and Frédéric Docquier, Abdeslam Marfouk, Sara Salomone, and Khalid Sekkat, “Are Skilled Women More Migratory than Skilled Men?” World Development 40, no. 2 (February Reference Docquier, Marfouk, Salomone and Sekkat2012): 251–265.

2 Sari Pekkala Kerr, William Kerr, Caglar Özden, and Christopher Parsons, “Global Talent Flows,” NBER Working Paper No. 22715 (October Reference Pekkala, Kerr, Özden and Parsons2016), 5.

3 Frédéric Docquier, B. Lindsay Lowell, and Abdeslam Marfouk, “A Gendered Assessment of Highly Skilled Emigration,” Population and Development Review 35, no. 2 (June Reference Dirican, Taylor, Kurt and Parsons2009): 297–321.

4 Parvati Raghuram, “Situating Women in the Brain Drain Discourse: Discursive Challenges and Opportunities,” in Gender and Migration in 21st century Europe, ed. Helen Stalford, Samantha Currie, and Samantha Velluti (Oxford and New York: Routledge, Reference Raghuram, Stalford, Currie and Velluti2009): 85–106; Maryam Naghsh Nejad, “Institutionalized Inequality and Brain Drain: An Empirical Study of the Effects of Women’s Rights on the Gender Gap in High-Skilled Migration,” IZA Discussion Paper No. 7864 (Bonn: IZA, December Reference Nejad2013); Hiroshi Ono and Nicola Piper, “Japanese Women Studying Abroad: The Case of the United States,” Women’s Studies International Forum 27, no. 2 (Reference Ono and Piper2004): 101–118; and Ilse Ruyssen and Sara Salomone, “Female Migration: A Way out of Discrimination?” Journal of Development Economics 130 (January Reference Ruyssen and Salomone2018), 225.

5 Nil Demet Güngör and Aysit Tansel, “Brain Drain from Turkey: An Investigation of Students’ Return Intention,” Applied Economics 40, no. 23 (Reference Güngör and Tansel2008): 3069–3087; Nil Demet Güngör and Aysit Tansel, “Brain Drain from Turkey: The Case of Professionals Abroad,” International Journal of Manpower 29, no. 4 (Reference Estukyan and İlkkaracan2008): 323–347; and Nil Demet Güngör and Aysit Tansel, “Brain Drain from Turkey: Return Intentions of Skilled Migrants,” International Migration 52, no. 5 (Reference Estukyan and İlkkaracan2014): 208–226.

6 Eyyup Esen, “Going and Coming: Why U.S.-Educated Turkish PhD Holders Stay in the U.S. or Return to Turkey?” (Ph.D. dissertation, University of Kansas, 2014) and Adem Y. Elveren and Gülay Toksöz, “Türkiye’de Beyin Göçü Yazını ve Bir Alan Araştırması,” in Gürhan Fişek’in İzinde Ortak Emek Ortak Eylem, ed. E. Karadoğan, G. Yenimahalleli Yaşar, N. Dertli, Ö. Millioğulları, K. Sebiha Kablay, and T. Akpınar (Ankara: Siyasal Kitabevi, Reference Elveren, Toksöz, Karadoğan, Yenimahalleli Yaşar, Dertli, Millioğulları, Sebiha Kablay and Akpınar2018): 191–214.

7 Docquier et al., “A Gendered Assessment of Highly Skilled Emigration”; James T. Bang and Aniruddha Mitra, “Gender Bias and the Female Brain Drain,” Applied Economics Letters 18, no. 9 (Reference Bang and Mitra2011): 829–833; Raghuram, “Situating Women in the Brain Drain Discourse”; Nejad, “Institutionalized Inequality”; Ruyssen and Salomone, “Female Migration: A Way out of Discrimination?”; Mohammed A. Chaichian, “The New Phase of Globalization and Brain Drain: Migration of Educated and Skilled Iranians to the United States,” International Journal of Social Economics 39, no. 1–2 (Reference Chaichian2011): 18–38; Joanne Nowak, “Gendered Perceptions of Migration among Skilled Female Ghanaian Nurses,” Gender & Development 17, no. 2 (Reference Nowak2009): 269–280; David Zweig and Chen Changgui, China’s Brain Drain to the United States: Views of Overseas Chinese Students and Scholars in the 1990s (Berkeley: Institute of East Asian Studies, University of California, Reference Zweig and Changgui1995); Yukiko Murakami, “Incentives for International Migration of Scientists and Engineers to Japan,” International Migration 47, no. 4 (Reference Gökbayrak2009): 67–91; Ono and Piper, “Japanese Women Studying Abroad”; Camilla Spadavecchia, “Migration of Women from Sub-Saharan Africa to Europe: The Role of Highly Skilled Women,” Sociología y tecnociencia /Sociology and Technoscience 3, no. 3 (Reference Spadavecchia2013): 96–116; Rachel R. Reynolds, “Professional Nigerian Women, Household Economy, and Immigration Decisions,” International Migration 44, no. 5 (Reference Reynolds2006): 167–188; Sebastian Klüsener, Vlada Stankuniene, Pavel Grigoriev, and Domantas Jasilionis, “The Mass Emigration Context of Lithuania: Patterns and Policy Options,” International Migration 53, no. 5 (Reference Klüsener, Stankuniene, Grigoriev and Jasilionis2015): 179–193; Eugene K. Campbell, “Brain Drain Potential in Botswana,” International Migration 45, no. 5 (Reference Campbell2007): 115–145; and Laura Bartolini, Ruby Gropas, and Anna Triandafyllidou, “Drivers of Highly Skilled Mobility from Southern Europe: Escaping the Crisis and Emancipating Oneself,” Journal of Ethnic and Migration Studies 43, no. 4 (Reference Bartolini, Gropas and Triandafyllidou2017): 652–673.

8 Docquier et al., “A Gendered Assessment of Highly Skilled Emigration.”

9 Bang and Mitra, “Gender Bias and the Female Brain Drain.”

10 Raghuram, “Situating Women in the Brain Drain Discourse.”

11 Nejad, “Institutionalized Inequality.”

12 Maryam Naghsh Nejad and Andrew T. Young, “Female Brain Drains and Women’s Rights Gaps: A Gravity Model Analysis of Bilateral Migration Flows,” IZA Discussion Paper No. 8067 (Bonn: IZA, March Reference Nejad and Young2014); David L. Cingranelli and David L. Richards, “The Cingranelli-Richards (CIRI) Human Rights Dataset,” version 2010.05.17 (Reference Cingranelli and Richards2010).

13 Ruyssen and Salomone, “Female Migration: A Way out of Discrimination?”

14 Ibid., 227.

15 Chaichian, “The New Phase.”

16 Nowak, “Gendered Perceptions of Migration.”

17 Zweig and Changgui, China’s Brain Drain to the United States.

18 Murakami, “Incentives for International Migration”; Ono and Piper, “Japanese Women Studying Abroad.”

19 Spadavecchia, “Migration of Women from Sub-Saharan Africa to Europe.”

20 Reynolds, “Professional Nigerian Women.”

21 Klüsener et al., “The Mass Emigration Context of Lithuania.”

22 Heike C. Alberts and Helen D. Hazen, “‘There Are Always Two Voices…’: International Students’ Intentions to Stay in the United States or Return to their Home Countries,” International Migration 43, no. 3 (Reference Alberts and Hazen2005): 131–154.

23 Docquier et al., “A Gendered Assessment of Highly Skilled Emigration”; Thierry Baudassé and Remi Bazillier, “Gender Inequality and Emigration: Push Factor or Selection Process?” International Economics 139 (October Reference Baudassé and Bazillier2014): 19–47.

24 Campbell, “Brain Drain Potential in Botswana.”

25 Bartolini et al., “Drivers of Highly Skilled Mobility.”

26 Rossitsa Rangelova, “Gender Dimension of the New Bulgaria’s Migration: Comments on Empirical Data,” 2006. http://aa.ecn.cz/img_upload/9e9f2072be82f3d69e3265f41fe9f28e/RRangelova_Gender_Dimension.pdf.

27 Philip L. Martin, The Unfinished Story: Turkish Labour Migration to Western Europe, with Special Reference to the Federal Republic of Germany (Geneva: ILO, Reference Martin1991).

28 Docquier et al., “A Gendered Assessment of Highly Skilled Emigration,” 18.

29 Frédéric Docquier, Abdeslam Marfouk, Çağlar Özden, and Christopher Parsons, “Geographic, Gender and Skill Structure of International Migration,” MPRA Paper No. 47917 (Munich: MPRA, Reference Docquier, Marfouk, Özden and Parsons2011).

30 Pekkala Kerr et al., “Global Talent Flows,” 4.

32 See Elveren and Toksöz, “Türkiye’de Beyin Göçü Yazını” and Adem Y. Elveren, Brain Drain and Gender Inequality in Turkey (Palgrave Pivot, Reference Elveren2018).

33 Rahmi Dirican, Carl F. Taylor, and Kurt W. Deushle, Health Manpower Planning in Turkey: An International Research Case Study (Baltimore: Johns Hopkins Press, Reference Dirican, Taylor and Deushle1968); Cevdet Kösemen, A Report Presented to Education and World Affairs Concerning Emigration of Engineers and Architects from Turkey to Foreign Countries for the Project International Migration of Talent (July Reference Kösemen1968); Turhan Oğuzkan, Yurt Dışında Çalışan Doktoralı Türkler: Türkiye’den Başka Ülkelere Yüksek Seviyede Eleman Göçü Üzerinde Bir Araştırma (Ankara: Orta Doğu Teknik Üniversitesi, Reference Oğuzkan1971); Türk Mühendis ve Mimar Odaları Birliği (TMMOB), XVII. Dönem Çalışma Raporu (Ankara: TMMOB, 1972); and Şefik Uysal, Yurt Dışında Yetişen İhtisas Gücü: 1416 Sayılı Kanunun Resmi Öǧrencilerle İlgili Uygulamasına Ait Bir Araştırma (Ankara: Türkiye Bilimsel ve Teknik Araştırma Kurumu, Reference Uysal1973).

34 Mehmet Ali Öztürk, “So Far from Home: Turkish Student Motivation and Access to Overseas Higher Education in the United States” (Ph.D. dissertation, University of Southern California, Los Angeles, 2001); Güngör and Tansel, “Brain Drain from Turkey”; Vedat Akman, “Factors Influencing International Student Migration: A Survey and Evaluation of Turkey’s Case,” Interdisciplinary Journal of Contemporary Research in Business 5, no. 11 (Reference Akman2014): 390–415.

35 Öztürk, “So Far from Home”; Güngör and Tansel, “The Case of Professionals”; Şenay Gökbayrak, “Skilled Labour Migration and Positive Externality: The Case of Turkish Engineers Working Abroad,” International Migration 50, no. s1 (Reference Gökbayrak2009): 132–150; Sevda Figan Pazarcık, “Beyin Göçü Olgusu ve Amerika Birleşik Devletleri Üniversitelerinde Çalışan Türk Sosyal Bilimciler Üzerine Bir Çalışma” (Master’s thesis, Çanakkale Onsekiz Mart University, 2010).

36 Esen, “Going and Coming.”

37 Ibid.

38 Akman, “Factors Influencing International Student Migration.”

39 Salih Mollahaliloğlu, Ülger Çulha, Mustafa Kosdak, and Hasan G. Öncül, “The Migration Preferences of Newly Graduated Physicians in Turkey,” Medical Journal of Islamic World Academy of Sciences 22, no. 2 (Reference Mollahaliloğlu, Çulha, Kosdak and Öncül.2014): 69–75.

40 Öztürk, “So Far from Home.”

41 Güngör and Tansel, “Brain Drain from Turkey,” 3073.

42 Güngör and Tansel, “The Case of Professionals” and Güngör and Tansel, “Return Intentions.”

43 Nil Demet Güngör, “The Gender Dimension of Skilled Migration and Return Intentions: Implications for Home Countries,” in Expert Group Meeting on Harnessing Knowledge on the Migration of Highly Skilled Women: 3–4 April 2014, Geneva (Geneva: IOM, Reference Güngör2014): 117–125.

44 Ibid.

45 Ibid., 118.

46 We acknowledge that social ties are the key aspect of the decision to migrate, both for women and for men. A substantial literature shows that emigration decisions are not solely individual, but rather significantly influenced by social factors; see, e.g., Alejendro Portes, “Social Capital: Its Origins and Applications in Modern Sociology,” Annual Review of Sociology 24 (August Reference Portes1998): 1–24. However, the scope of our survey is the key constraint against extending our discussion so as to address the effect of such basic variables as marital and parenthood status; the limited size of observation simply does not allow us to undertake a more robust analysis.

47 United Nations Development Programme, Human Development Report 2016 (New York: UNDP, 2016). http://hdr.undp.org/en/2016-report.

48 Gülay Toksöz, “Transition from ‘Woman’ to ‘Family’: An Analysis of AKP Era Employment Policies from a Gender Perspective,” Journal für Entwicklungspolitik 32, no. 1–2 (Reference Toksöz2016): 64–83 and Simten Coşar and Mesut Yeğenoğlu, “New Grounds for Patriarchy in Turkey? Gender Policy in the Age of AKP,” South European Society and Politics 16, no. 4 (2011): 555–573.

49 OECD Development Centre, “Social Institutions & Gender Index 2014 Synthesis Report” (OECD 2014). https://www.oecd.org/dev/development-gender/BrochureSIGI2015-web.pdf, 62.

50 Ibid., 26.

51 Gallup and ILO, Towards a Better Future for Women and Work: Voices of Women and Men (Gallup and ILO 2017). https://www.ilo.org/wcmsp5/groups/public/@dgreports/@dcomm/@publ/documents/publication/wcms_546256.pdf.

53 Turkey has been experiencing a substantial brain drain since 2016, especially with the (seemingly permanent) state of emergency instituted following the failed military coup attempt of July 15 of that year. The purges in academia and the excessive repression of the signatories of the January 2016 peace declaration are two of the main factors behind this drain. Numerous sources report on the alarming situation of Turkey’s brain drain; see, e.g., Rengin Arslan, “Türkiye’den Akademisyen Göçü: Neden Gidiyorlar?” BBC Türkçe, October 25, 2016. http://www.bbc.com/turkce/haberler-turkiye-37754038; Uzay Bulut and Kasım Cindemir, “Türkiye’den Yurtdışına Beyin Göçü Hızlandı” VOA: Amerika’nın Sesi, August 15, 2016. http://www.amerikaninsesi.com/a/turkiye-den-yurtdisina-beyin-gocu-hizlandi/3464933.html; Vartan Estukyan, “Azınlıkların Gündemi Göç,” AGOS, October 20, 2016. http://www.agos.com.tr/tr/yazi/16791/azinliklarin-gundemi-goc; “İstatistiklerle Beyin Göçü,” Gazete Duvar, February 3, 2017. http://www.gazeteduvar.com.tr/gundem/2017/02/03/istatistiklerle-beyin-gocu/; Can Kamiloğlu, “ABD’ye Yerleşmek İsteyen Türkler’in Sayısında Patlama,” VOA: Amerika’nın Sesi, May 20, 2016. https://www.amerikaninsesi.com/a/abd-ye-yerlesmek-isteyen-turklerin-sayisinda-patlama/3339132.html; Suat Kınıklıoğlu, “Turkey’s Secular Brain Drain,” Al-Monitor, November 5, 2014. https://www.al-monitor.com/pulse/politics/2014/11/turkey-secular-immigration-exodus.html; “Türkiye’den Göçün Sektör ve Ülkelere Göre Dağılımı,” T24, December 22, 2016. http://t24.com.tr/haber/turkiyeden-gocun-sektor-ve-ulkelere-gore-dagilimi,378633; Umur Yedikardeş, “Türkiye’nin Beyin Göçü: Gidenler Nedenlerini Anlatıyor,” Journo, March 2, 2017. https://journo.com.tr/turkiyenin-beyin-gocu.

54 Ruyssen and Salomone, “Female Migration,” 225.

55 Nil Demet Güngör, “Brain Drain from Turkey: An Empirical Investigation of the Determinants of Skilled Migration and Student Non-return” (Ph.D. dissertation, Middle East Technical University, 2003).

56 Güngör and Tansel, “Brain Drain from Turkey”; Güngör and Tansel, “The Case of Professionals”; Güngör and Tansel, “Return Intentions”; and Esen, “Going and Coming.”

57 Güngör and Tansel, “Brain Drain from Turkey”; Güngör and Tansel, “The Case of Professionals”; Güngör and Tansel, “Return Intentions”; and Gökbayrak, “Skilled Labour Migration.”

58 Güngör and Tansel, “Brain Drain from Turkey”; Güngör and Tansel, “The Case of Professionals”; and Güngör and Tansel, “Return Intentions.”

59 Ibid.

60 Güngör, “An Empirical Investigation.”

61 Güngör and Tansel, “Brain Drain from Turkey”; Güngör and Tansel, “The Case of Professionals”; and Güngör and Tansel, “Return Intentions.”

62 In order to save space, we do not present the results regarding the type of university from which the students and professionals graduated, or their fields of study and work. These statistics, however, can be provided upon request.

65 Feride Acar, “Turkish Women in Academia: Roles and Careers,” METU Studies in Development 10, no. 4 (Reference Acar1983): 409–446.

66 Dumont et al., “Women on the Move”; Docquier et al., “A Gendered Assessment.”

67 Ibid.

69 İpek İlkkaracan, “Why So Few Women in the Labor Market in Turkey?” Feminist Economics 18, no. 1 (Reference İlkkaracan2012): 1–37.

71 Ibid.

73 Elisabeth Cudeville and Leman Yonca Gurbuzer, “Gender Wage Discrimination in the Turkish Labor Market: Can Turkey Be Part of Europe?” Comparative Economic Studies 52, no. 3 (September Reference Cudeville and Gurbuzer2010): 429–463.

74 Toksöz, “Transition” and Saniye Dedeoğlu, “Eşitlik mi Ayrımcılık mı? Türkiye’de Sosyal Devlet, Cinsiyet Eşitliği Politikaları ve Kadın İstihdamı,” Çalışma ve Toplum 2, no. 21 (Reference Dedeoğlu2009): 41–54.

77 Elveren, Brain Drain and Gender Inequality in Turkey.

78 We acknowledge that the lack of expansive data is a constraint in our analysis. Retrogressive changes in Turkey in terms of the role of women in society may serve as a push factor for educated women, making them more likely than men to migrate and intend not to return. Ruyssen and Salomone (op. cit.) report that women prefer to migrate when they think that they are not being treated with respect and dignity. Although the problem of violence against women has not yet been explicitly considered in migration studies, it seems reasonable to argue that women’s risk of facing violence in Turkey, along with the sexist rhetoric of public authorities, is likely to reinforce educated women’s desire to emigrate. Therefore, the gender dimension of the brain drain should be examined more systematically by constructing a specific questionnaire that would better integrate the matter of gender inequality. This would allow gender inequality to be specifically tested as a push factor in the context of a more complete explanatory model.

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Figure 0

Table 1. Pearson correlation test results

Figure 1

Table 2. Initial and current return intentions (Number of respondents)

Figure 2

Table 3. Plan to go abroad again by occupation and gender (%)

Figure 3

Table 4. Push and pull factors rated as “important” or “very important” (%)

Figure 4

Table 5. Push and pull factors rated as “important” or “very important” (%) (Students and professionals)

Figure 5

Table 6. Regression analysis of non-return intentions