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Turkish Studies
ISSN: 1468-3849 (Print) 1743-9663 (Online) Journal homepage: https://www.tandfonline.com/loi/ftur20
Does migration contribute to women’s
empowerment? Portrait of urban Turkey and
Istanbul
Değer Eryar, Hasan Tekgüç & Sule Toktas
To cite this article: Değer Eryar, Hasan Tekgüç & Sule Toktas (2019) Does migration contribute
to women’s empowerment? Portrait of urban Turkey and Istanbul, Turkish Studies, 20:2, 200-221,
DOI: 10.1080/14683849.2018.1495566
To link to this article: https://doi.org/10.1080/14683849.2018.1495566
Published online: 11 Jul 2018.
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Does migration contribute to women’s
empowerment? Portrait of urban Turkey and Istanbul
Değer Eryar
a
, Hasan Tekgüç
b
and Sule Toktas
c
a
Department of Economics, İzmir University of Economics, Izmir, Turkey;
b
Department of
Economics, Kadir Has University, Istanbul, Turkey;
c
Department of Political Science and Public
Administration, Kadir Has University, Istanbul, Turkey
ABSTRACT
This article empirically investigates the impact of internal migration on women’s
empowerment in urban areas of Turkey. Based on data from a nationally
representative household survey, we find that migration exerts a positive
impact in urban settings through improvements in educational attainment
and labor market outcomes. Migration contributes to women’s empowerment
by raising their education levels and lowering the gap in schooling between
men and women. Migration also allows migrants, both men and women and
particularly those with tertiary education, to access jobs and occupations in
high wage regions like Istanbul. However, unlike in education, a gender wage
gap persists even after migration.
ARTICLE HISTORY Received 12 January 2018; Accepted 19 April 2018
KEYWORDS Migration; women; immigrants; empowerment; Istanbul
Introduction
Empowerment in its simplest term is expansion in personal ability to make
and implement significant decisions affecting one’s own life and the lives of
others in a context where this ability was previously denied to him/her.
1
Increase in assets and capabilities produces control over resources and
decisions and at the same time enhances freedom of choice and action.
2
Empowerment occurs at individual and collective levels as well as in the
public and the private spheres with interrelated socio-economic, political, cul-
tural, legal, psychological and legal dimensions.
3
On account of the many
faces of gender inequality, empowerment of women refers to multivariate
situations of increased power in accessing education, work, health and
decision-making processes in the household. Thus, the process of empower-
ment entails women’s individual consciousness for freedom and well-being
that gets operationalized through mobility,
4
wage labor, a strong role in the
© 2018 Informa UK Limited, trading as Taylor & Francis Group
CONTACT Sule Toktas suletoktas@yahoo.com; sule@khas.edu.tr Department of Political Science
and Public Administration, Kadir Has University, Cibali, 34083 Istanbul, Turkey
TURKISH STUDIES
2019, VOL. 20, NO. 2, 200–221
https://doi.org/10.1080/14683849.2018.1495566
household and eventually a meaningful participation in the wider
community.
5
This article focuses on the impact of internal migration on women’s
empowerment through changes in women’s educational attainment and
their labor market outcomes such as employment rate, occupational choices
and wage income. With migration, women can have more access to a
variety of education and employment opportunities, which directly or
indirectly help reduce inequality and poverty.
6
Migration might also
expand the opportunities of women’s economic, social and inter-personal
relations. What’s more, the migration of women from rural-to-urban areas
can proliferate economic and social empowerment and economic attainment
through trading, independence and networking to find better economic
opportunities.
7
Yet, factors like low education levels, prior non-working
status and rural background negatively correlate with empowering outcomes
for women due to migration.
8
Most of the studies on internal migration in Turkey are overwhelmingly
field studies employing qualitative methods based on data from migrant
enclaves that present a multi-dimensional picture of rural-to-urban and gen-
erally less educated migrant experience. The current study, however, utilizing
a nationally representative survey, allows for an investigation of often over-
looked groups of migrants, such as urban-to-urban and better-educated
migrants, living outside the enclaves. Incorporating the gender aspect to the
processes of internal migration, the article discusses the relationship
between migration and women’s involvement in education and labor force
by comparing the related figures to those of men as well as to those of non-
migrants.
The main results of this study present us sufficient empirical evidence for
the positive correlation between internal migration and empowerment of
women observed mostly through improvements in women’s educational
attainment and in their labor market outcomes. The analysis indicates that
migration provides both migrants and their children with better education
opportunities, which themselves can lead to better-paid occupations,
especially for those with tertiary education. This link is much more pro-
nounced for women as much as migration is positively associated not only
with higher levels of education for women, but also with a narrowed gap
between men’s and women’s educational attainment. Apart from enabling
women to acquire more education and to have them better equipped for
the labor market, migration tends to offer them more job opportunities
which do not necessarily become available immediately after arrival in a
new setting.
Turkey is a country that has nearly completed its urbanization process.
According to the latest national figures in 2016,
9
the majority of the popu-
lation lives in urban settings with 92.3 percent of population residing in
TURKISH STUDIES 201
provincial and district centers, and only 7.7 percent of the population lives in
towns and villages.
10
Although migration from rural to the urban settings has
dominated the recent history of urbanization in Turkey since the 1950s, which
resulted in the emergence of shanty towns (commonly known as the ‘gece-
kondu’phenomenon) in the cities,
11
changing socio-economic dynamics
have produced urbanization which over time came to be dominated more
by urban-urban migrations and less by rural-to-urban migrations.
12
Especially after 1990s and in 2000s, critical shifts in housing policies in
addition to several other national and global socio-economic factors provoked
intra-city as well as inter-city mobility. Both the central and municipal gov-
ernments shifted their stance on squatter housing from tacit approval to
proactive rehabilitation of existing ones coupled with prevention of new
ones.
13
This shift in policy probably increased the housing costs of
newcomers.
The migration process was accompanied by the transformation of big cities
into metropolitan settlements and in the case of Istanbul changing the city
into a ‘mega city’comparable to Bangkok, Buenos Aires, Cairo, and Mexico
City, and the like in the global South. Nowadays, these megacities attract
highly educated, ambitious and skilled migrants to fill the jobs in corporate
headquarters, bureaucracy, and in high-paying sectors like finance and tech-
nology. They also attract low-skilled migrants to fill in jobs like construction
workers, domestic cleaners, and other low-skilled and manual service sector
jobs. Therefore, both the educational composition and the wage structure of
migrants in Istanbul are probably different from the national averages.
Thus, although the current article focuses on the impact of internal migration
on women’s empowerment in urban areas of Turkey, a specific focus on the
case of Istanbul that entails a comparison to be drawn between this ‘mega city’
and national overview is inevitable. Thus, the paper, after presenting the data
source and methods, discusses the empirical findings not only with reference
to previous empirical studies but also comparatively of the different tabula-
tions pulled out of the data set. The results of the quantitative research are dis-
cussed in connection with women’s empowerment in the last section.
The study: data source and methods
This study uses the Household Labor Force Survey from 2013 (HLFS) which
is provided by the Turkish Statistical Institute (TurkStat) as open data. The
HLFS is the most recent nationally representative micro data set that contains
comprehensive information regarding all the variables relevant for our analy-
sis where we investigate the impact of internal migration on female empow-
erment. It has a large sample size with a rich micro data set of around 380,000
working-age individuals (15 years of age and above) in a nationally represen-
tative sample along with a very high response rate (around 91 percent).
202 D. ERYAR ET AL.
In addition to demographic questions, the presence of unique set of questions
in the 2013 HLFS on different aspects of labor market experience of individ-
uals provides a rich set of information. Some of these questions shed light on
the labor market status (employed, unemployed or outside the labor force),
occupational position (e.g. managers, service and sale workers, etc.),
working hours and wage income. The questions on the educational history
of individuals along with their labor market outcome across gender dimen-
sion within the same data set allow for an analysis of female empowerment
as a combination of education and labor market outcome. Especially the
responses given to the questions of ‘Have you been living permanently in
this province since you were born?’or ‘From which year do you live in this
province?’help identify and distinguish immigrants.
14
We limit our main
analysis to those individuals who were born between 1960 and 1989 in
order to focus more on prime working-age population. Given the importance
of having tertiary education for labor market outcome, especially for women,
we did not focus on those individuals who were younger than 24 years of age
in 2013 during the year of survey.
Most recent migrants need some time in order to adapt themselves to new
local conditions in terms of labor market conditions, acquisition of new skills,
and networking.
15
Hence, instead of pooling all migrants into the same cat-
egory we further divided them into three groups according to their arrival
date in order to investigate the degree of assimilation over time. The most
recent group consists of migrants who arrived in the last five years (2009–
2013) prior to the survey (most recent); the second group contains all
migrants who moved between 2004 and 2008 (in-transit); and the last
group covers the migrants who came to their current residences before
2004 (settled-down). Moreover, those individuals who never migrated in
their lifetime became our control group. The urban-rural division as an essen-
tial dimension of internal migration
16
underlines the significance of the 2013
HLFS since it is the last HLFS that contains information about the urban-rural
divide in a nationally representative survey. We took urban areas as the main
migration destination and excluded rural-to-rural and urban-to-rural
migration movements in our main analysis given that almost 95 percent of
all migrants in our sample chose urban areas as their destination.
According to economic perspectives in explaining migration among
various other theories of migration, most migrants, at least if migrating volun-
tarily, are motivated by the search for better living conditions in locations
other than their current location.
17
The expectation for a better life may be
linked to higher expected earnings for all members of the family and better
access to improved conditions in terms of living standards for present and
future.
18
If migration depends on the comparison between expected lifetime
earnings in the current and alternative regions of residence, then the relation-
ship between migration and education as one of the key determinants of
TURKISH STUDIES 203
expected earnings comes to forefront. Human capital theory is one of the most
frequently used approaches in order to account for the impact of education on
the expected earnings of individuals.
19
In this research, we explore the role of migration on the educational attain-
ment of individuals moving to urban destinations. There are different chan-
nels where the positive correlation between migration and education can be
detected.
20
Accordingly, the prospect of migration can result in more acqui-
sition of education as long as there are more job opportunities with higher
returns to education in new destinations. Therefore, individuals are expected
to invest more in education before migrating.
21
Due to the significance of
additional skills acquisition through further education and training after
arriving at the new residence,
22
acquisition of education may also be the
main reason for migration.
23
This can be especially important for increasing
investment in the education of migrants’children in response to changes in
socio-economic and cultural environment in which children grow up.
Taking into consideration these factors, we first compute the average years
of education according to two new categories (those who migrated after com-
pleting their education and those who migrated before completing their edu-
cation). Comparing these two categories with non-migrants according to
average years of education enables us to explore the following questions:
a. Is migration important as a prospect for acquiring more education even
before migrating?
b. Does migration provide an opportunity of getting more education for
people after migrating?
We repeat the same comparison for three migrant groups (most recent, in-
transit, settled-down) and across gender division as well. Therefore, we are
able to inspect the possible gender differences regarding the extent of the
above correlations between migration and education for each subgroup of
migrants.
Although educational attainment turns out to be one of the main determi-
nants of wage, occupational categories also seem to play a crucial role in deter-
mining the expected earnings of individuals. Yet, both the probability of being
employed and choosing a particular occupational position strongly depends
on education as well.
24
It is in this context that the correlation between
migration and occupation should not be carried out independently of edu-
cational categories. Our aim is to find out whether being employed is differ-
ently correlated with migrants than with non-migrants for individual
educational categories. Another related question arises as to whether the
same correlation varies across gender dimension.
Apart from being employed, the choice of occupational position is also cor-
related with migration and educational attainment.
25
We are interested in
204 D. ERYAR ET AL.
whether there is a higher probability of better-educated migrants to find
themselves in less-skilled occupations during the initial years of their
migration due to possible constraints such as discrimination or lack of
required social networks. Therefore, we also check the possibility of down-
grading of better-educated migrants.
26
For example, if the majority of
college graduates are not employed in skilled non-manual occupational pos-
itions, such as professionals, then this observation indicates the possibility of
downgrading. We discuss the degree of assimilation of men and women
migrants by exploring both the presence of downgrading and whether it
fades away over time when migrants adapt themselves to new conditions.
In due course, we explore the impact of being migrant on average wage
income by focusing on the correlation between these two factors in a multi-
variate framework.
27
In order to single out the relationship between being
migrant and wages, all other observable relevant factors are controlled for
in the same analysis. These factors consist of human capital (educational
attainment, tenure in the work place), occupational position, age cohort
effect, public employee, marital status and regions. Only after taking into
account all possible correlations between wage and control factors, we can
appropriately focus on the partial correlation between wage and being
migrant. This multivariate analysis is carried out first for the whole sample
where gender is used as another control factor. Then, the same analysis is con-
ducted separately for men and women in order to find out whether the cor-
relation between being migrant and wages is different for either of the genders.
As of 2013, migrants compose of 38 percent of all working-age population
which are more than the share of urban or rural non-migrants. The situation
is much more extreme in Istanbul; almost 70 percent of prime working-age
population in Istanbul are migrants. On the one hand, Istanbul is currently
hosting the headquarters of overwhelming majority of large corporations
and high-paying technology and finance sectors. On the other hand, it has
been a destination city for migrants like low-skilled workers for a long-
time. As a result, we suspect that the national averages may not be represen-
tative for Istanbul. Therefore, we analyze Istanbul as a separate unit in
addition to Turkey in our framework.
With respect to limitations of the study, it has to be noted that our analysis
depends on the evidence provided by the 2013 HLFS which does not contain
certain questions that might help for a more detailed inquiry. There are at
least three data limitations. First, we do not know the reason for migration.
Due to restrictions of the data set that make it impossible to identify
between voluntary and involuntary migration, our definition of migrants
cannot distinguish between migrants who were motivated mostly for econ-
omic reasons and forced migrants, who leave their current location due to
natural disaster or socio-political crisis. Second, we do not know the complete
migration history of individuals as there might have been multiple migration
TURKISH STUDIES 205
(s) of an individual migrant. Last but not least, we do not know the origin
region of migrants. Other household level datasets that contain these infor-
mation (migration reason, region of birth, migration history) such as
Turkish Demographic and Health Surveys, unfortunately lack detailed infor-
mation on labor force outcomes (employment, occupation and wages).
Findings: women’s empowerment and internal migration
In Turkey, 32 percent of all people are first generation migrants (i.e. they live
in a different province than their place of birth) whereas the same figure is
slightly above 50 percent in Istanbul. The share of migrants turns out to be
higher in the sample used in the analysis, 44 and 68 percent, in Turkey and
Istanbul, respectively. Table 1 reports the share of migrants and non-migrants
by internal migration status. It further shows that the overwhelming majority
of migrants are destined to urban areas in both Turkey and Istanbul.
Regarding average years of education by arrival time, our key finding is that
the educational attainment of migrants (9.4 years for men and 7.8 years for
women) turns out to be higher than that of non-migrants (8.7 years for
men and 7.3 years for women) in Turkey as measured by the average years
of schooling. Moreover, this difference becomes much more significant for
those migrants who migrated before completing their education than those
who migrated after completing their education. Both men and women in
the first group of migrants have higher average years of schooling (10 years
for both men and women) compared to the latter group of migrants (9.1
years for men and 7.1 years for women). This result shows that individuals
utilize migration more as an opportunity of having better access to schools
in their new destinations rather than as an endeavor that might increase
Table 1. Distribution of migrants by origin and destination.
All population Born between 1960 and 1989
Men Women All Men Women All
Origin-to-destination
Rural-to-rural 1 1 1 1 1 1
Urban-to-rural 4 3 4 5 4 4
Rural-to-urban 8 8 8 11 11 11
Urban-to-urban 19 20 19 27 27 27
Rural non-migrant 27 27 27 22 22 22
Urban non-migrant 41 41 41 34 34 34
Total 100 100 100 100 100 100
Destination Istanbul
Rural-to-rural 0 0 0 0 1 1
Urban-to-rural 0 0 0 0 0 0
Rural-to-urban 24 23 23 32 30 31
Urban-to-urban 26 28 27 34 38 36
Rural non-migrant 1 1 1 1 1 1
Urban non-migrant 48 47 47 32 30 31
Total 100 100 100 100 100 100
206 D. ERYAR ET AL.
their migrant chance. In some cases, acquiring education itself can be an
important motivation for migration as is clearly presented for inter-state
mobility in India.
28
In some other cases, migration can provide better edu-
cation opportunities for the children of migrants, whereas the same channel
strongly depends on the socio-economic status of migrant parents.
29
Additionally, community-wide interactions and peer effects also significantly
contribute to the impact of migration on children’s education by changing
parents’incentives to educate their children in their new residence.
30
These
findings are illustrated in Table 2 which shows average years of education
by arrival time.
Internal migration has a direct positive impact on women’s empowerment
by providing an opportunity for improving educational gender inequality as
well. Although we observe gender gap of schooling for both migrants and
non-migrants, the same gender gap of average years of schooling does not
exist anymore for those migrants who moved to their new destinations
before completing their education. This result again emphasizes the role of
internal migration in terms of generating better opportunities of acquiring
education and/or staying in the educational system, particularly for young
women. Apart from lower costs of attaining education and higher returns
to education, migration to urban areas also exposes both parents and children
to more non-traditional gender norms about working women.
31
When con-
ducting the same analysis only for Istanbul, some of our general findings
do not seem to hold. Unlike Turkey, there is no positive correlation
between being migrant and educational attainment in this city. In terms of
average years of schooling, non-migrants perform better than migrants do
for both men and women. One partial explanation is the relatively smaller
share of public employees in the overall migrant group moving to Istanbul,
who, on average, are highly educated, and might keep the average educational
Table 2. Average years of Education, born between 1960 and 1989.
Migrated after
Migrated
before
Share (%)
Education completed Average
Men Women Men Women Men Women
Urban
Non-migrant 8.7 7.3 47
Arrived before 2004 7.8 5.9 9.7 9.5 8.6 7.1 36
Arrived between 2004 and 2008 10.0 7.9 14.0 14.1 10.4 8.4 9
Arrived between 2009 and 2013 11.3 9.7 15.0 15.0 11.4 9.9 9
Average 9.1 7.1 10.0 10.0 9.0 7.5 100
Istanbul
Non-migrant 9.9 9.8 32
Arrived before 2004 6.9 5.5 9.2 9.1 7.9 6.7 53
Arrived between 2004 and 2008 9.1 7.2 13.6 13.9 9.7 7.8 9
Arrived between 2009 and 2013 10.8 9.2 15.0 15.0 10.9 9.4 6
Average 7.8 6.2 9.5 9.4 8.9 7.9 100
TURKISH STUDIES 207
attainment of migrants to Istanbul below that of Turkey. Moreover, relatively
high share of rural-urban migration in total urban migration in Istanbul com-
pared to Turkey (46 percent in Istanbul against 29 percent in Turkey) can also
negatively contribute to the low levels of average years schooling of migrants
especially due to the ones coming to Istanbul after finishing their education
from places with already low average years of schooling. Historically,
eastern and southeastern regions of Turkey received less public education
spending,
32
hence, migrants from these regions probably arrive in big cities
with lower education level.
Our findings shed light on the impact of internal migration on the labor
market outcomes of individuals. As is discussed in data source and method
sections, the analysis of the correlation between migration and the labor
market outcomes such as employment, occupation and wages have been
carried out by controlling for different levels of education as well. Although
one can observe the expected positive correlation between educational attain-
ment and probability of employment (see Figure 1), there is a need to single
out the very strong correlation between university education and employment
of women. Therefore, both the rise in average years of schooling and the fall in
gender gap regarding educational attainment particularly for those migrants
moving to their new destinations before completing their education reflect
Figure 1. Education and employment. LTHS: Less than High School; HS: High School.
208 D. ERYAR ET AL.
the positive effect of internal migration especially on women’s probability of
employment.
Following Figure 1, we do not distinguish between unemployed and out-of-
labor force but combine them under non-employed category. We create three
sub-categories for the employed: skilled non-manual, skilled manual, and
unskilled manual.
33
While migration might raise the probability of employ-
ment by exerting its influence on the educational attainment of individuals,
it is also correlated with the occupational positions in the labor market as
long as the occupational positions are attained mostly due to appropriate
human capital investment. Moreover, migration can affect the probability
of employment and occupational choices by creating some barriers during
the assimilation process. We also explore the possibility of downgrading of
better-educated migrants as is relevant in the literature on international
migration.
34
Especially, there is a higher probability of better-educated
migrants to find themselves in low-paid occupations during the initial years
of their migration. Table 3 shows the cross tabulation of education and occu-
pation as follows:
Our results indicate the presence of occupational downgrading especially
for migrant men. The better-educated part of the more recent migrants
(those who arrived between 2009 and 2013) are under-represented in high
paid occupations such as skilled non-manual jobs compared to those migrants
who arrived before 2004 (Table 3). This observation can partly be accounted
by the difficulties in accessing to the appropriate networks necessary for best-
matched jobs.
35
This problem of downgrading is more visible in Istanbul (not
presented here due to space limitations but available from authors) where
most of the job opportunities for better-educated people consist of private
sector jobs rather than public sector jobs like in many other parts of Turkey.
The same analysis presented in Table 3 above depicts a different picture for
women. Although college-educated most recent migrant women (who arrived
between 2009 and 2013) have a smaller share in better-paid jobs than the
migrant women who arrived before 2004, the reason seems to be associated
more with being unemployed or out of the labor force at the earlier stage of
migration rather than downgrading as is observed for men. A gradual rise
in the rate of labor force participation after the first phase of migration is
detected for the other migrant women as well; however, it is much stronger
for women with a high-school diploma. The share of women with no job in
this educational category (who are either out of the labor force or unem-
ployed) is 80 percent for the most recent migrant group, whereas the same
share drops down to 64 percent for those migrant women who arrived
before 2004. These results point to the positive impact of internal migration
on women’s labor market outcomes through different channels. One of
them seems to be the gradual adjustment of migrant women to labor
market conditions in view of the lack of formal networks similar to the case
TURKISH STUDIES 209
Table 3. Education and employment, born between 1960 and 1989.
Non-migrant Arrived before 2004 Arrived between 2004 and 2008 Arrived between 2009 and 2013
LTHS HS Tertiary Aver. LTHS HS Tertiary Aver. LTHS HS Tertiary Aver. LTHS HS Tertiary Aver.
Urban men
Non-employed 21 13 15 18 19 14 9 16 14 15 8 12 23 19 11 16
Unskilled manual 13 7 2 9 13 6 1 9 16 5 1 7 15 6 1 6
Skilled manual 59 52 19 50 59 50 15 48 65 54 21 45 55 41 21 35
Skilled non-manual 8 28 65 23 9 30 75 27 6 26 70 35 6 34 67 42
Urban women
Non-employed 80 66 34 71 79 64 29 68 83 74 28 68 84 80 36 65
Unskilled manual 6 3 0 5 8 5 0 6 6 2 0 4 5 2 0 3
Skilled manual 13 15 6 12 12 15 4 11 10 10 4 9 10 9 4 7
Skilled non-manual 1 17 60 12 1 16 67 14 1 13 68 20 1 9 60 25
Note: LTHS: Less than high school; HS: high school.
210 D. ERYAR ET AL.
of better-educated men. However, the more significant increase in the share of
employed women who have less than tertiary education over time emphasizes
the possibility of women’s exposition to non-traditional gender norms in new
destinations regarding the status of women in the labor market. Lastly, it is
also likely that those migrant women with lower education levels tend to
work outside home out of economic necessity.
36
Most of these women are
more likely to have a husband along with similar educational attainment or
live in a household where the other members also have lower educational
attainment and therefore been employed in low-paid occupations.
Given the limitations in our data set on the ethnicity and the region of
origin, we are in no position to claim that ethnic discrimination does not
play a role in accounting for variations in terms of employment rates
among migrants. This can be especially important regarding the wave of
the Kurdish migration in the 1990s that has been usually associated with invo-
luntary migration.
37
The migrants from Southeastern and Eastern parts of
Turkey, who are predominantly Kurdish, tend to be less educated on
average than the migrants do from other regions. Hence, without controls
for the region of origin or ethnicity, education variable is probably picking
up some of the effect of the ethnicity.
Regarding the impact of migration on the wages of individuals, Figure 2
shows the average monthly wages for migrant groups according to edu-
cational categories and gender (see below). During 2013, net minimum
wage was 773 TL for the first half and 804 TL for the second half of the
year. Wage data excludes self-employed and entrepreneurs. Most self-
employed in urban areas are small-scale craftsmen with modest incomes,
but self-employed category also includes some high earning professionals
(lawyers, doctors, architects). The over-representation of these professionals
and entrepreneurs among non-migrants might result underestimation of
average wages for individuals with tertiary education especially in Istanbul.
The overall comparison indicates higher wages for all migrant groups than
non-migrant group in Turkey across all education categories for both men
and women. However, the same result does not necessarily hold for the
lower educated migrants in Istanbul. Many people along with less than
high-school diploma migrate to Istanbul in order to exploit job opportunities
that are not available in their original area of residence although many of these
jobs are low-paid positions in the informal sector.
38
The raw wage gap
between migrants and non-migrants is pronounced most significantly for
individuals with tertiary education level.
We investigate the correlation between being migrant and average wage
income in a multivariate framework where all other relevant factors are con-
trolled (see Table 4 below). These control factors include educational attain-
ment (including programs finished for tertiary graduates), occupational
positions, experience in the workplace, public sector, cohort effects, marital
TURKISH STUDIES 211
status, the presence of small children, and current region of residence. The
results show overall a positive correlation between migrants and wages. In
other words, migrants are likely to earn more than non-migrants, when we
compare migrants and non-migrants with similar observable characteristics.
The dependent variable is the natural logarithm of self-reported positive
wage and hence coefficient estimates correspond to percentage change.
Accordingly, a wage-employed migrant who arrived between 2009 and
2013 is expected to earn on average about 12 percent more than a non-
migrant along with similar observable characteristics such as same edu-
cational attainment, same work place experience, same age group and etc.
This effect becomes much more significant when we carry out the same analy-
sis only for those migrants with tertiary education where the most recent
migrants earn almost 22 percent more than non-migrants do on average.
This wage premium is highest for the most recent migrants whereas it falls
down to 7 percent for those migrants arrived between 2004 and 2008, and
to 2 percent for those migrants arrived before 2004. Returning migrants
Figure 2. Average wages, born between 1960 and 1989. During 2013, net minimum
wage was 773 TL for the first half and 804 TL for the second half of the year (average
= 788 TL).
212 D. ERYAR ET AL.
can partly account for the above wage dynamics of migrants.
39
Hence, it is
possible that migrants who are unsuccessful in landing jobs tend to return
to original place earlier than successful ones as long as their decisions are
related to their earnings. This can lead to overestimation of the positive
impact of migration on wages in the earlier phase of migration. The ones
who quickly find a good job upon their arrival might decide to stay and
their success can be the outcome of possessing above average ability, having
pre-migration network connections, or just pure luck.
Overall women earn less than men on average independently of being
migrant or not in every sub-group. However, when we explore the impact
of being migrant on wages separately for men and women, our results indicate
again the positive impact of being migrant on average wages within the same
sex category after taking all other observable factors into account. Similar to
the results for the whole sample, the impact of migration on women’s wages is
also particularly high and significant for the most recent migrant group and
university graduates.
Does all these mean that migration is bad for non-migrants? Not necess-
arily, Istanbul is the number one destination for migration in Turkey for
the last 70 years and after receiving millions of migrants, wages are still at
least 20 percent higher than the rest of Turkey. In other words, the
Table 4. Wage differences by migration and gender (dependent variable: log wages).
Urban wages
Istanbul
wages
Urban and
university
Istanbul and
university
Arrived before 2004 0.020 *** 0.002 0.063 *** 0.028
Arrived between 2004 and 2008 0.073 *** 0.076 *** 0.154 *** 0.202 ***
Arrived between 2009 and 2013 0.122 *** 0.071 *** 0.216 *** 0.198 ***
Women −0.247 *** −0.195 *** −0.160 *** −0.149 ***
R-squared 0.512 0.464 0.344 0.280
N67,945 11,239 22,039 3424
Men only
Arrived before 2004 0.018 *** −0.011 0.081 *** 0.024
Arrived between 2004 and 2008 0.080 *** 0.080 *** 0.183 *** 0.265 ***
Arrived between 2009 and 2013 0.130 *** 0.070 *** 0.241 *** 0.250 ***
R-squared 0.51 0.459 0.364 0.316
N48,891 7776 13,296 1856
Women only
Arrived before 2004 0.043 *** 0.040 ** 0.043 *** 0.041
Arrived between 2004 and 2008 0.068 *** 0.052 * 0.096 *** 0.093 **
Arrived between 2009 and 2013 0.119 *** 0.078 ** 0.156 *** 0.127 ***
R-squared 0.527 0.485 0.294 0.224
N19,054 3463 8743 1568
Controls
Age, five-year cohorts Y Y Y Y
Occupation, three sub-groups Y Y Y Y
Married, tenure, public Y Y Y Y
Education, three sub-groups Y Y
Major, five sub-groups Y Y
NUTS1 regions Y Y
***p< .01; **p< .05; *p< .10.
TURKISH STUDIES 213
agglomeration of high-skilled and highly motivated migrants creates such a
dynamism that it leads to higher overall wages in Istanbul including non-
migrants.
Conclusion
The current study confirms that migration contributes to women’s empower-
ment in the case of Turkey. The empirical evidence obtained in the current
research suggests for a positive correlation between internal migration and
empowerment of women mostly through improvements in women’s edu-
cational attainment and to a certain extent in their labor market outcomes.
Migration provides both migrants and their children with better education
opportunities that open the path for better-paid occupations. For women
migrants, such a link is clearer not only because of the positive association
between migration and higher levels of education for women but also due to
the gap between men’s and women’s educational attainment narrowing
down with migration. However, the current research also indicates that
unlike the case of education, migration does not lead to a narrower wage gap
between men and women. With respect to the labor market and wage differen-
tials, a rather different and complicated picture is at stake. Findings pinpoint
various dimensions to question of empowerment and internal migration.
First, according to the research results, it is significant that women in
Turkey obtain more education in the course of migration that equips them
better for the labor market, and present them more job opportunities. Yet,
these job opportunities do not necessarily become available immediately
after the arrival. Migrant women seem to need some time in order to adapt
themselves to the new socio-economic environment by acquiring new skills
through education, getting familiar with new social networks, and being
exposed to non-traditional social norms about women working outside home.
Second, research results show that migration is associated with higher
wages particularly for recent migrants with university education; yet a causal-
ity cannot be claimed. The evidence gathered in the research for the national
outlook of Turkey does not suggest that migration causes wages to be higher
for migrants on average than non-migrants. However, it is significant that
migration definitely contributes to higher wages by providing the migrants
with opportunities for improving their wage-enhancing characteristics such
as education and occupational choices, which might not have been possible
had they not migrated in the first place. The positive wage premium that
exists among those individuals even with similar observable characteristics
can be explained by higher ability/motivations of individuals, the possibility
of participating in social networks, or a combination of these factors that
might affect the decision to migrate and cannot be captured by the available
data in this study.
214 D. ERYAR ET AL.
Third, specifically for women migrants, although the above universal
outlook is valid, that is women migrants would have had earned less had
they stayed in their settlements of origin, gender seems to continue to serve
as a blockade. When compared with male migrants, women migrants earn
less. The wage gap does not seem to close down between men and
women,
40
even with the utilization of the opportunity of migration. Despite
the significant correlation of internal migration with higher wages, gender
barrier seems to remain strong for women to surpass to obtain equal wages
with men.
41
Fourth, although most of the results of this study are generalizable to the
whole country, migration dynamics for Istanbul seem to be working differ-
ently in certain aspects. Apart from providing the best labor market and edu-
cational opportunities, Istanbul, like other mega cities in the global South, also
attracts lower educated people from other parts of Turkey by offering them
better jobs than those available in their original areas of residence. Yet, the
relatively lower wages for those migrants compared to similar non-migrants
in Istanbul indicate that most of those migrants are employed in low-paid
and informal jobs.
Gender is a critical factor in identifying the motivations, outcomes, and
barriers to migration and what’s more, migration flows and their outcomes
are strongly gendered. As part of selection bias, women on the move might
also be those who have been empowered to a certain extent in the previous
pre-migration situation so that they were able to utilize the opportunity of
migration.
42
It has to be noted that migration not only opens the gate for
opportunities, it is an opportunity in itself especially if occurring voluntarily.
To be able to move, one needs to have certain social and material capital.
Thus, migration can be both a cause and consequence of female empower-
ment.
43
Women migrate for different purposes and under different circum-
stances, as there are various types of migration voluntary or involuntary in
nature. A large part of female migration is for marriage purpose or because
the husband is migrating, however, there are also other migrations like for
education, for family re-unification, for work or for forced situations. Yet,
the same physical mobility brings by social mobility with increased education
levels, enhanced job opportunities as well as elevated wages in most of the
cases.
There are many different types of empowerment but in this analysis, we
focused on socio-economic empowerment in the spheres of education and
labor market. In a complicated manner, migration has both empowering
and disempowering effects for women.
44
Empowerment or disempowerment
of women through migration heavily depends on the context in which the
migration occurs, the type of movement, and the characteristics of the
female migrants. It is very common that women migrants receive lower
wages than male migrants in similar situations and, therefore, terms of
TURKISH STUDIES 215
employment and enclave employment might limit the benefit for women
migrants.
45
Migration does not bring about a complete transformation in
intra-household power relations, too. Women’s increased access to household
resources including income by way of entering labor market does not necess-
arily give rise to a comparable or proportionate increase in absolute control
over those resources.
46
Migrant women’s involvement in the labor market do
not pinpoint to an innate transformation for an increased bargaining power
within the home, an equal distribution of household duties like cleaning and
cooking and a greater male-female cooperation. An overemphasis on wage
labor as a means to migrant women’s liberation also runs the risk of making
assumptions that homogenize women’s experiences and perceptions.
47
In the context of Turkey, patriarchal societal structure confines women to
the domain of domesticity irrespective of improvements experienced in both
educational attainment and labor market outcomes.
48
Although economic
participation is supposed to be a key contribution to the empowerment
process of women,
49
this expected gain is constrained by a solid patriarchal
culture imposed upon migrant women mostly by their husbands and other
family members in different sites such as workplaces. Women’s work either
paid or unpaid is devalued and unrecognized as long as women are identified
primarily as wives and mothers rather than labor market participants like
their male counterparts.
50
Women, even with higher education levels,
encounter problems like inner conflicts between being working women and
caring mom that negatively affects their attachment to the labor force.
51
The prevalence of traditional gender norms in the society and their impact
on social policies (e.g. inadequate provision of childcare services) are some
of the key factors that reinforce the inner conflict for working women even
with tertiary education.
Notes
1. Kabeer, “Resources, Agency, Achievements”; Narayan, “Conceptual Frame-
work”; and Sinha, Jha and Negi, “Migration and Empowerment.”
2. Kabeer, “Discussing Women’s Empowerment,”and Narayan, Empowerment.
3. Malhotra, “Measuring Empowerment.”
4. Sen, “Introduction: The Many Faces.”
5. Schuler and Hahemi, “Defining and Studying.”
6. Momsen, Domestic Service.
7. Bello-Bravo, “Rural-urban Migration.”
8. Narazani et al., “Policy Brief on Migration.”
9. The Turkish Statistical Institute, “The Results.”
10. Accordingly with the Law No. 6360 on metropolitan municipalities enacted in
2012, TurkStat significantly altered the definition of the rural area and discon-
tinued releasing data about the urban-rural divide after the revision. According
to one of the last available data from a Labor Force Survey, the share of urban
population is 77.3 percent and rural population is 22.7 percent.
216 D. ERYAR ET AL.
11. Erman, “The Politics of Squatter.”
12. The phenomenon of shantytowns in the peripheries of cities especially metro-
politan cities reveal the trends, tendencies and workings of migration from
rural-to-urban settlements. There is also a flow, albeit small in scope and fre-
quency, from urban-to-rural and from rural-to-rural settlements.
13. Icduygu, “Demographic Mobility.”
14. Similar questions for foreign-born Turkish nationals are also available in the
survey.
15. Dustmann and Glitz, “How Do Industries Respond.”
16. Ibid.
17. Castles and Miller, “Theories of Migration,”25.
18. UN, “Human Development Report.”
19. Becker, Human Capital.
20. Dustmann and Glitz, “How Do Industries Respond.”
21. Blunch and Laderchi, “The Winner Takes It All,”and Girsberger, “Migration,
Education and Work.”
22. Dustmann and Glitz, “How Do Industries Respond.”
23. Jha and Kumar, “Socio-economic Determinants.”
24. Chiswick and Miller, “Earnings and Occupational Attainment,”and Maani, Dai
and Inkson, “Occupational Attainment.”
25. Elliot and Lindley, “Immigrant Wage Differentials.”
26. Aleksnyska and Tritah, “Occupation–Education Mismatch.”
27. Eckstein and Weiss, “On the Wage Growth,”and Borjas, “The Slowdown.”
28. Jha and Kumar, “Socio-economic Determinants.”
29. Kusadokoro and Hasegawa, “The Influence.”
30. Gümüş,“The Effects of Community.”
31. Tansel, “Determinants of School Attainment”; Smits and Gündüz-Hoşgör,
“Effects of Family”; and Duman, “Female Education.”
32. Oyvat and Tekgüç, Double Squeeze.
33. International Labour Organization, Global Employment.
34. Aleksnyska and Tritah, “Occupation-Education Mismatch.”
35. Dustmann and Glitz, “How Do Industries Respond.”
36. Erman et al. “Money-Earning Activities.”
37. Bahar, “The Name Says It All.”
38. More than 90 percent of high school and tertiary graduate wage earners are
employed in formal sector. LTHS graduate wage employed women are the
only sub-group where it is almost an even split between formal and informal
wage employment.
39. Bijwaard and Whaba, “Immigrants’Wage Growth.”
40. All the more so in academia where there are high education levels, gender wage
gap persists. See Ucal, O’Neil and Toktaş,“Gender and the Wage Gap.”
41. Tekgüç et al. presents a wage decomposition analysis of gender wage gap and
reports that after controlling for selection tertiary educated women face 8
percent wage discrimination and less educated women face 23 percent wage
discrimination in 2011. See Tekgüç, Eryar and Cindoğlu, “Women’s Tertiary
Education.”
42. Gaye and Shreyasi, “Measuring Women’s Empowerment,”53.
43. Hugo, “Migration and Women’s Empowerment.”
44. Yu, An Empowerment Approach.
45. Ghosh, “Migration and Gender,”30.
TURKISH STUDIES 217
46. Handapangoda, “Transnational Labour Migration.”
47. Zentgraf, “Immigration.”
48. Erman et al. “Money-Earning Activities.”
49. Cindoğlu and Toktaş,“Empowerment and Resistance Strategies of Working
Women.”
50. Dedeoğlu, “Visible Hands.”
51. Paker and Uysal, “Who Takes Care.”
Disclosure statement
No potential conflict of interest was reported by the authors.
Note on contributors
Değer Eryar is an assistant professor in the Department of Economics at Izmir Uni-
versity of Economics. He received his PhD from the University of Massachusetts at
Amherst where he completed his dissertation on the macroeconomic impact of
capital flows in Turkey. His research concentrates on gender and youth dimensions
of the labor market, economic integration and financial crises. His articles have
appeared in journals such as Comparative Economic Studies,Developing Economies
and The Journal of Labor Research.
Hasan Tekgüç received his PhD in Economics from the University of Massachusetts
at Amherst in June 2010. His dissertation focused on consumption behavior of house-
holds and their vulnerability to poverty. Between 2011 and 2015 he held an assistant
professor position at Mardin Artuklu University, and since September 2015 he has
worked at at Kadir Has University. His research interests include competition and
price transmission in animal product markets and gender issues in labor markets
in Turkey. His recent publications have appeared in The Review of Economics of
the Household,Agribusiness,Developing Economies, and The Journal of Labor
Research.
Sule Toktas is a professor of political science in the Department of Political Science
and Public Administration at Kadir Has University in Istanbul. Her research interests
include women’s studies, minority issues and migration. Her publications have
appeared in various journals such as International Migration,Geopolitics,Political
Science Quarterly,Women’s Studies International Forum,European Journal of
Women Studies,Minerva and The Muslim World. She has also co-authored four
books.
ORCID
Sule Toktas http://orcid.org/0000-0002-1332-2039
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