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Book cover for Towards Gender Equity in Development Towards Gender Equity in Development

Civil conflicts and wars have many dire consequences, including forcing people to flee their homes. By the end of 2014, 59.5 million people had been displaced due to conflict, persecution, or human rights violations (UNHCR 2015). Among them, a large share (38.2 million) were internally displaced persons (IDPs) who had moved away from their homes but remained in their country of citizenship. Although forced migration affects millions of people, its effects are relatively understudied (Ruiz and Vargas-Silva 2013). In particular, we know little about the effects of conflict-induced displacement on gender norms and attitudes.

In this chapter, I explore the long-term consequences of internal forced migration for women’s attitudes towards domestic violence in Turkey. According to official figures, between 1984 and 1999 around one million people1 were internally displaced due to the conflict between the Turkish state and the Kurdistan Workers’ Party (PKK) (HÜNEE 2005). Many of the migrants were Kurdish, lived in rural areas, and had to move to urban centres in the region or in the western parts of the country. As of 2009, fewer than 20 per cent of IDPs had returned to their original residence (IDMC 2013).

Theoretically, forced migration may affect women’s attitudes to domestic violence through a number of mechanisms. Household bargaining models predict that a change in women’s access to economic opportunities may affect domestic violence. Forced migrants may lack necessary skills or networks to obtain employment at their destination. If such resources are rarer for women or it is more important for them to gain access to economic opportunities in the urban sector, it is likely that forced migration from rural to urban areas will reduce their bargaining power in the household. In Turkey, employment opportunities for low-skilled women are rarer in the urban sector than in the rural, while for men the difference is not as large (Aran et al. 2009; Tunali 2003). Therefore forced rural-to-urban migration may have led to a fall in women’s intra-household bargaining power, which may have increased the incidence and acceptability of domestic violence. Alternatively, being forced to move from rural to urban areas may forcibly expose migrants to different cultural norms. Traditional gender roles may come into conflict with the cultural norms at the destination, causing conflict within the household. Moreover, the psychological and social consequences of being forced to migrate may increase the incidence of domestic violence and affect attitudes towards it. Ultimately, whether forced migration affects domestic violence, and if so through what mechanisms, are empirical questions.

To examine whether women who were forced to migrate during the conflict have different attitudes towards domestic violence, I use two different data sources. First, I use the 2008 and 2013 waves of the Turkish Demographic and Health Survey (TDHS). These surveys were targeted at a representative sample of women2 and collected information on their health outcomes and basic socio-economic characteristics. In addition, information was recorded on their attitudes towards domestic violence and their migration histories. This enables me to test whether women who migrated due to the conflict have different attitudes towards domestic violence. In particular, I estimate a triple-difference model, exploiting differences in ethnicity (Turkish vs Kurdish women), region of birth/childhood (the conflict region vs the rest of the country), and timing of migration (whether they migrated during the conflict period (1984–99) or not). I find that Kurdish women who migrated from their homes during the conflict are more likely to believe that a husband is justified in beating his wife in at least one of the scenarios they were asked about. Controlling for observable characteristics such as age, family background, parental education, and birthplace, I find that women who were forced to migrate are 16 percentage points more inclined to believe domestic violence is acceptable. Examining the possible mechanisms behind this effect, I find some evidence consistent with the bargaining power hypothesis: forced migration increased the likelihood that the respondent’s husband was working while she was not. Moreover, spouses of migrant women were more likely to have tried to control their wives by, for example, limiting their movements or social interactions. This may be in line with the idea that forced migration threatens the traditional male gender role more than the female role, and causes conflict in the household.

As another, suggestive, piece of evidence, I use a novel database that was compiled by one of the largest NGOs working to support women affected by domestic violence in eastern Turkey.3 The data contains information on all women who applied to the NGO for help in dealing with domestic violence between October 2009 and December 2011. In the sample, there are more than 2,278 Kurdish applicants who were subjected to physical or sexual intrafamily violence. Among them, about 15 per cent reported that they had been forced to migrate due to security concerns, and there is a robust relationship between being a forced migrant and the duration as well as the extent of the domestic violence they experienced before seeking help from the NGO. In particular, women who were forced migrants were more likely to report that the abusive relationship had been going on for more than ten years and that the abuse had started at the beginning of the relationship. They were also less likely to have sought legal aid or alternative help, to have been forced to have sex against their will, and to have had a miscarriage due to domestic violence.4 These findings suggest that women who had been forced to migrate had suffered domestic violence for longer and possibly of greater severity before deciding to seek help from the NGO (and were no more likely to have sought help elsewhere).

Taken together, the findings from the TDHS and the applicants’ data imply that forced migration ensuing from the Kurdish-Turkish conflict changed women’s attitudes towards domestic violence, making them more tolerant of it. Further research is needed to fully understand the mechanisms driving the effects of forced migration on attitudes towards and the incidence of domestic violence.

The forced migration studied in this chapter was caused by the conflict between Turkey and Kurdish insurgent groups, mainly the PKK. The PKK was founded in 1978 under the leadership of Abdullah Öcalan, and transformed into a paramilitary group in 1984. They started a guerrilla war, benefiting from the difficult terrain in the region for cover. In the ensuing fighting, Turkey both used its army and recruited local Kurdish villagers to create a paramilitary organization named ‘village guards’ (Ozar et al. 2013). Between 1984 and the late 1990s, an estimated 40,000 people lost their lives, and many villages were evacuated and/or destroyed in the largely Kurdish eastern and south-eastern parts of the country (Beriker-Atiyas 1997). The intensity of the fighting diminished with the capture of Öcalan in 1999, and in September 1999 a ceasefire was declared. The focus of this chapter will be on the forced migrations that took place in this period. The fighting resumed after 2004, and continued with lower intensity than in the 1990s until its re-escalation in 2015.

During the height of the conflict, a state of emergency was declared by the Turkish state in eleven provinces in the east and south-east of the country. These provinces were Bingöl, Diyarbakır, Elazığ, Hakkari, Mardin, Siirt, Tunceli, and Van, and the neighbouring provinces of Adıyaman, Bitlis, and Muş. The state of emergency came to be known as OHAL (from olağanüstü hal (extraordinary state) in Turkish), and the region came to be known as the OHAL region. Most of the forced migration took place within this area as inhabitants of many rural settlements were evicted.5 While most of the displaced were from rural areas, there was also forced migration from some towns (e.g., Lice, Kulp, Cizre, and Şırnak) to other urban areas, and the majority of the displaced population was Kurdish (Kurban et al. 2007). A report by the Turkish Parliament Investigation Commission in 1998 highlighted three main reasons for the displacement: (1) the collapse of agriculture and animal husbandry due to the clashes; (2) the PKK’s eviction of villagers who were cooperating with the state (i.e. becoming village guards); (3) the eviction by the security forces of villagers who refused to become village guards. Many of the migrants settled in urban centres in the region and some moved to western parts of the country. As of 2009, fewer than 20 per cent of IDPs had returned to their original residence (IDMC 2013).

For a long time the number of people forced to migrate during the conflict was disputed. Official government reports put this number at around 300,000, while many NGOs claimed it was as high as three million (IDMC 2013). In 2005 the Turkish government commissioned a comprehensive study to estimate the correct number. According to this report (HÜNEE 2005), between 925,000 and 1.2 million people were internally displaced due to the conflict. The same study showed that forced migrants on average had low socio-economic status and low schooling, and the majority (94 per cent) of them were either not employed or working in the informal sector (i.e. in jobs with no social security).

The forced migration that was caused by the Turkish-Kurdish conflict may have affected migrants’ attitudes towards domestic violence through a number of mechanisms.

In theoretical models of household bargaining, spousal violence can be a means to increase the abuser’s bargaining power. An improvement in women’s access to economic opportunities (such as employment or earnings) may decrease or increase the incidence of domestic violence, depending on the initial allocation of bargaining power within the couple and whether the reservation utility of the woman or her spouse is binding (Anderson and Genicot 2015; Bloch and Rao 2002; Eswaran and Malhotra 2011; Tauchen et al. 1991). This implies that a change in the economic opportunities of women relative to their spouses is likely to affect the incidence of domestic violence. Empirical literature testing these predictions has studied how women’s employment or earning opportunities can influence the incidence of domestic violence across a variety of settings (e.g. Aizer 2010; Alesina et al. 2016; Amaral et al. 2015; Andenberg et al. 2016; Angelucci 2008; Bobonis et al. 2013; Chin 2012; Heath 2014; Heise and Kotsadam 2015; Hidrobo and Fernald 2013; van den Berg and Tertilt 2015). Broadly speaking, the evidence suggests that an increase in women’s bargaining power reduces domestic violence in high-income settings, while it leads to an increase in domestic violence in low-income settings. If forced migration affects women’s access to economic opportunities (relative to men’s), it may change the likelihood of domestic violence and conflict within the family, which may in turn affect attitudes towards it.6 In the context of the Turkish-Kurdish conflict, the forced migration occurred in the poorest parts of the country, among households that had limited income and education.7 Moreover, in Turkey, women with low education typically have fewer employment opportunities in the urban sector relative to the rural sector, while for men the reverse is true on average (Aran et al. 2009; cf. evidence presented in Table A4). Thus forced migration in Turkey may have reduced the economic opportunities of women relative to men.

Another mechanism through which forced migration may affect attitudes is the migrants’ exposure to different cultural norms. In the Turkish context, many forced migrants had to move from rural to urban areas, which on average have more progressive gender norms.8 This may have brought traditional gender norms into conflict with more modern norms. Threats to the traditional male gender role may have led to an increase in the incidence of domestic violence (Atkinson et al. 2005). On the other hand, if migrants over time adopt the norms of their destinations, they may have lower tolerance of domestic violence compared with individuals from similar ex ante backgrounds who were not forced to migrate.9

Another alternative mechanism might be related to the long-run psychological consequences of being exposed to conflict. In psychology, social cognition theories propose that exposure to community violence may culminate in the normalization of the use of aggressive behaviours (e.g., Fowler et al. 2009). In economics, empirical studies have demonstrated a positive association between exposure to conflict and individuals’ propensity to commit violent or criminal acts later on (Couttenier et al. 2016; Miguel et al. 2011; Rohlfs 2010), and the long-run psychological consequences have been highlighted as one of the potential mechanisms behind such effects.10

Last but not least, forced migration may result in the breaking apart of existing social ties and the loss of social capital. Without the support of their family and friends, women may have difficulty in leaving abusive relationships, which may increase the incidence and acceptability of violence.

The data used in this study comes from two sources: (1) the TDHS; (2) data on applicants to one of the largest NGOs in Turkey providing support for women affected by domestic violence (henceforth referred to as ‘applicant data’).

I use data from the 2008 and 2013 waves of the TDHS. In the 2008 wave, a representative sample of women aged 15–50 who had been married at least once was surveyed. In TDHS 2013, all women were sampled, regardless of their marriage history.11 In addition to the respondents’ basic demographic and socio-economic characteristics, the surveys collected information on their migration history and domestic violence attitudes. For migration, respondents were asked to report their birth province, the place where they had grown up (their main residence until age 12), and every location they had lived in for at least six months after the age of 12. If they had moved from one place to another, the timing of migration was recorded. On the basis of this information one can identify whether a respondent is from an OHAL province and if she migrated from there (or within the province from one location to another) during the conflict years (1984–99). Of the 16,216 women in the data, 2,860 were born and/or grew up in one of the OHAL provinces. Among them, 752 migrated from an OHAL province during the conflict period, and 2,108 did not. Respondents were asked to report whether they thought that a husband was justified in beating his wife if she (1) neglected their children’s needs, (2) argued with her husband, (3) refused to have sex with him, (4) burned the food, (5) wasted money, (6) did not cook, or (7) neglected household chores.12 On the basis of these, I define three summary indices: first, a dummy variable equal to one if the respondent thought it was acceptable for a husband to beat his wife in any one of these scenarios; second, the fraction of cases in which the respondent thought domestic violence was justified; and third, the first principal component of responses to the individual scenarios. On average, 20 per cent of respondents thought men were justified in beating their wives in at least one of the scenarios. For detailed descriptive statistics on these and background characteristics of the respondents, see Gulesci (2017: Table 1).

The second data set was collected by one of the main NGOs offering support to women who are victims of violence in eastern and south-eastern Turkey—the provinces affected by the conflict. Depending on their needs, the NGO may offer the women legal, medical, psychological, or economic (e.g. in finding a job) assistance, as well as a chance to meet and forge bonds with other women who have been victims of violence.13 The data contains information on all women who applied to the NGO for assistance between October 2009 and December 2011. Upon application (prior to receiving any support from the NGO) they were asked to complete a brief questionnaire about why they were applying, what type of abuse they had faced, and some information on their background (e.g., their age, education level, and work status). Importantly for the analysis, the survey contained questions on the applicant’s migration status, which enables me to identify whether the applicant was forced to migrate due to the conflict.

I limit the sample to women who applied to the NGO seeking help because they were subject to physical or sexual domestic (intrahousehold) violence. This is clearly a selected sample. It only contains women who chose to report and seek help for any violence they experienced. I use this data to provide suggestive evidence about forced migrants’ attitudes towards domestic violence relative to other applicants. In particular, I test whether forced migrants endured more domestic violence, in terms of duration or severity, before deciding to seek help. There are 3,582 cases in total of women who applied to the NGO to seek assistance in dealing with physical or sexual domestic violence. Of these, 2,278 were Kurdish and 349 had been forced to migrate.14 The average woman in the sample is 37 years old, but there is a lot of age variation among them (the youngest applicant in the sample is 15, and the oldest 80 years old). I study the correlation between being a forced migrant and indicators of the duration and extent of the domestic violence experienced by the applicants, and any assistance they may have sought prior to their application to the NGO. For detailed descriptive statistics on this dataset, see Gulesci (2017: Table 2).

To identify the effects of forced migration on women’s attitudes towards domestic violence in the TDHS, I estimate the following model:

[1]

where yipt is the domestic violence attitude of respondent i from province p whose migration status was revealed in period t; Ki and Cp are dummy variables for whether respondent i is Kurdish and from a conflict province respectively; Mit is a dummy variable if respondent i migrated during the conflict period (1984–99); Xi is a matrix of control variables;15 θp and St are province of birth and survey wave fixed effects respectively. Standard errors are clustered by birth province to account for the fact that women born in the same province will have correlated outcomes. The parameter of interest is λ, which gives the triple difference between women from the conflict region (vs the rest of the country), who migrated during the conflict period (vs did not migrate in this period), who are Kurdish (vs Turkish). The key identifying assumption is that, conditional on the control variables, this triple difference should pick up the effect of being forced to migrate because of the conflict. On the basis of the discussion of the historical and political context in Section 2, it is reasonable to assume that Kurdish women who moved from the conflict provinces during this period were most likely forced to do so because of the conflict.

In the applicant data, I estimate:

[2]

where yip is the outcome of interest for applicant i from province p; Fi is a dummy variable equal to one if the respondent is a forced migrant; Xi is a vector of demographic and socio-economic controls;16 and θp is the province of application fixed effects. Standard errors are clustered by province. The parameter of interest is σ, the difference between forced migrants and the rest of the applicants, controlling for other observable characteristics (including whether the respondent is a migrant in general).

Table 5.1 presents the results of estimating the triple-difference specification in [1] on women’s attitudes towards domestic violence in the TDHS data.17 In Column (1), the dependent variable is an indicator for whether the respondent thought a man was justified in beating his wife in any of the scenarios she was asked about. The estimates imply that Kurdish women from the conflict region who migrated during the conflict are 16 percentage points more likely to think that domestic violence is justified in at least one of these scenarios. This is a very large effect, both compared to the sample mean (20 per cent) and relative to the subsample of Kurdish women who did not migrate during the conflict (32 per cent). In Column (2), the dependent variable is the fraction of scenarios in which the respondent thought domestic violence was acceptable. The outcome is higher by 0.06 for Kurdish women who were forced to migrate during the conflict, which is a large effect relative to the sample mean (0.08) or compared to Kurdish women who did not migrate during the conflict (0.15). Finally, Column (3) shows the finding is robust to aggregating the responses using an alternative way—the first principal component of the individual questions on domestic violence. Overall, results in Table 5.3 imply that more than twenty years after the beginning and ten years after the end of the conflict in question, forced migrant women were more likely to find physical domestic violence justified.18

Table 5.1.
Forced migration and women’s attitudes towards domestic violence
Domestic violence is justified in any scenarioFraction of scenarios in which domestic violence is justifiedFirst principal component
(1)(2)(3)

From conflict region x Migrated during conflict x Kurdish

0.163***

0.064***

0.504**

(0.035)

(0.021)

(0.213)

Joint p-value

0.000

Mean level of outcome (full sample)

0.203

0.080

−.008

Mean level of outcome (subsample)

0.321

0.145

0.622

Adjusted R-squared

0.088

0.097

0.077

Number of observations

16197

16197

15762

Domestic violence is justified in any scenarioFraction of scenarios in which domestic violence is justifiedFirst principal component
(1)(2)(3)

From conflict region x Migrated during conflict x Kurdish

0.163***

0.064***

0.504**

(0.035)

(0.021)

(0.213)

Joint p-value

0.000

Mean level of outcome (full sample)

0.203

0.080

−.008

Mean level of outcome (subsample)

0.321

0.145

0.622

Adjusted R-squared

0.088

0.097

0.077

Number of observations

16197

16197

15762

Source: Author’s calculations based on data from the 2008 and 2013 Turkish Demographic and Health Surveys.

Each column provides the result of estimating specification [1] on respondents’ attitudes towards domestic violence. For brevity, only the estimate for λ, the coefficient of the triple-interaction term, is reported. Estimates of other parameters of the model are reported in Gulesci (2017: Table B1). In 2008, respondents were asked to state if they thought domestic violence by a husband towards his wife was justified in seven different scenarios, while in the 2013 TDHS only five of these scenarios were used. In Column (1), the outcome variable is a dummy variable =1 if the respondent said she thought a husband was justified in beating his wife in any of the seven scenarios that were described to her. In Column (2) the outcome is the proportion of cases (out of the seven (five) scenarios read to her in the 2008 (2013) TDHS) in which the respondent said she thought a husband was justified in beating his wife. In Column (3) the dependent variable is the first principal component of seven (five) dummy variables each equal to 1 if the respondent stated she found domestic violence justified in the given scenario in the 2008 (2013) TDHS. ‘From conflict region’ is a dummy variable =1 if the respondent was born and/or grew up in one of the conflict provinces (Adiyaman, Agri, Batman, Bingol, Bitlis, Diyarbakir, Elazig, Hakkari, Mardin, Mus, Siirt, Sirnak, Tunceli, and Van). ‘Migrated during conflict’ is a dummy variable =1 if the respondent migrated at least once during the conflict years (1984–99). ‘Kurdish’ is a dummy variable =1 if the first language of either the mother or the father of the respondent was Kurdish. ‘From conflict region x Migrated during conflict x Kurdish’ is the triple-interaction term that identifies the effect of being forced to migrate due to the conflict. All regressions control for the following covariates: a dummy variable =1 if the respondent’s mother ever went to school; a dummy variable =1 if the respondent’s father completed primary school; a dummy variable =1 if the respondent’s father graduated from secondary school or above; a dummy variable =1 if the respondent’s parents were related by blood; province of birth and TDHS wave fixed effects. The reported ‘joint p-value’ is from a test for joint significance of estimates for ‘From conflict region x Migrated during conflict x Kurdish’ using seemingly unrelated regressions for Columns (1)–(3). The row ‘mean level of outcome (subsample)’ gives the mean of the outcome among Kurdish women from the conflict region who did not migrate during conflict. Robust standard errors are clustered by birth province.

*** (**) (*) indicates significance at the 1% (5%) (10%) level.

Table 5.3.
Effects on controlling behaviours of the spouse
If respondent’s current or last husband ever:Aggregate indices
Prevented her from seeing her friendsLimited her contact with her familyInsisted on knowing where she was at all timesDistrusted her with moneyAccused her of being unfaithfulRespondent experienced any of the situations in (1)–(5)Principal component
(1)(2)(3)(4)(5)(6)(7)

From conflict region x Migrated during conflict x Kurdish

0.089***

0.034

0.103*

0.035

0.024

0.098**

0.404**

(0.030)

(0.025)

(0.056)

(0.041)

(0.028)

(0.049)

(0.154)

Joint p-value

0.000

Mean level of outcome (full sample)

0.098

0.068

0.374

0.058

0.040

0.432

–0.003

Mean level of outcome (subsample)

0.124

0.095

0.437

0.059

0.030

0.506

0.115

Adjusted R-squared

0.012

0.006

0.032

0.002

0.004

0.032

0.014

Number of observations

14019

14017

14010

14008

14008

14025

13965

If respondent’s current or last husband ever:Aggregate indices
Prevented her from seeing her friendsLimited her contact with her familyInsisted on knowing where she was at all timesDistrusted her with moneyAccused her of being unfaithfulRespondent experienced any of the situations in (1)–(5)Principal component
(1)(2)(3)(4)(5)(6)(7)

From conflict region x Migrated during conflict x Kurdish

0.089***

0.034

0.103*

0.035

0.024

0.098**

0.404**

(0.030)

(0.025)

(0.056)

(0.041)

(0.028)

(0.049)

(0.154)

Joint p-value

0.000

Mean level of outcome (full sample)

0.098

0.068

0.374

0.058

0.040

0.432

–0.003

Mean level of outcome (subsample)

0.124

0.095

0.437

0.059

0.030

0.506

0.115

Adjusted R-squared

0.012

0.006

0.032

0.002

0.004

0.032

0.014

Number of observations

14019

14017

14010

14008

14008

14025

13965

Source: Author’s calculations based on data from the 2008 and 2013 Turkish Demographic and Health Surveys.

Each column provides the result of estimating specification [1]. For brevity, only the estimate for λ, the coefficient of the triple-interaction term, is reported. Estimates of other parameters of the model are reported in Gulesci (2017: Table B4). In Columns (1)–(5), the dependent variables are dummy variables =1 if the respondent’s current or (if divorced or widowed) last husband sometimes or often behaved in the stated manner. They are defined on the basis of the question: ‘Can you please tell me how often you experience(d) such situations in your relationship with your (last) husband? Often, sometimes, or never?’ I combine the responses ‘often’ and ‘sometimes’, so the reference category is ‘never’. The specific situations are: in Column (1), preventing her from seeing her female friends; in Column (2), limiting her contact with her family; in Column (3), insisting on knowing where she was at all times; in Column (4), distrusting her with money; in Column (5), accusing her of being unfaithful. In Column (6) the dependent variable is a dummy variable =1 if any of the dummy variables in Columns (1–5) is equal to 1. In Column (7) the dependent variable is the first principal component of the five dummy variables in Columns (1–5). ‘From conflict region’ is a dummy variable =1 if the respondent was born and/or grew up in one of the conflict provinces (Adiyaman, Agri, Batman, Bingol, Bitlis, Diyarbakir, Elazig, Hakkari, Mardin, Mus, Siirt, Sirnak, Tunceli, and Van). ‘Migrated during conflict’ is a dummy variable =1 if the respondent migrated at least once during the conflict years (1984–99). ‘Kurdish’ is a dummy variable =1 if the first language of either the mother or the father of the respondent was Kurdish. ‘From conflict region x Migrated during conflict x Kurdish’ is the triple-interaction term that identifies the effect of being forced to migrate due to the conflict. All regressions control for the following covariates: a dummy variable =1 if the respondent’s mother ever went to school; a dummy variable =1 if the respondent’s father completed primary school; a dummy variable =1 if the respondent’s father graduated from secondary school or above; a dummy variable =1 if the respondent’s parents were related by blood; province of birth and TDHS wave fixed effects. The reported ‘joint p-value’ is from a test for joint significance of estimates for ‘From conflict region x Migrated during conflict x Kurdish’ using seemingly unrelated regressions for Columns (1)–(7). The row ‘mean level of outcome (subsample)’ gives the mean of the outcome among Kurdish women from the conflict region who did not migrate during the conflict. Robust standard errors are clustered by birth province. *** (**) (*) indicates significance at the 1% (5%) (10%) level.

In order to assess the robustness of the estimates and the validity of the identification strategy, I explore two approaches. First, I conduct a placebo test where I estimate the triple-difference specification in [1] for women who migrated before the conflict period (i.e. prior to 1984). In other words, I substitute the dummy variable Mit with one that is equal to one if respondent i migrated before the conflict period. If the findings are driven by the forced migration ensuing from the conflict, then I should not find any significant differences in the domestic violence attitudes of Kurdish women who migrated before the conflict relative to those who did not and relative to Turkish women. The results are reported in Gulesci (2017: Table A1). The coefficient estimates for the triple-interaction term (λ) are negative and insignificant for all outcome variables, which builds confidence that the effects demonstrated before were driven by the forced migration and not by any other underlying differences across the comparison groups.

Second, as an alternative specification, I restrict the sample to Kurdish respondents and estimate the difference-in-difference between those who are from the OHAL provinces and those who migrated during the conflict period. Formally, I estimate:

[3]

In this specification, the coefficient of interest is τ, the difference-in-difference between Kurdish women who were from the OHAL provinces versus the rest of the country, and those who migrated during the conflict relative to those who did not. The results are reported in Gulesci (2017: Tables A2 and A3). The estimated effects are qualitatively similar to the triple-difference approach in specification [1], but due to the smaller sample size some of the estimates lose precision. For example, in Table A2, the estimate for τ is not precise for the first principal component (Column (3)), but it is positive and significant for the other two indicators.

To return to the discussion in Section 3, a potential mechanism behind this change in women’s attitudes might be that forced migration lowers the bargaining power of women relative to men and thus makes domestic violence more expected and acceptable in their households. To test this mechanism explicitly, I estimate specification [1] on the employment and schooling level of women and their husbands (thus limiting the sample to married women only). Results in Table 5.2 show that while forced migration did not have a significant effect on the employment probability of women in the long run (Column (1)), it did widen the gap between them and their husbands in terms of employment probability. Column (3) shows that Kurdish women who migrated during the conflict are 11 percentage points more likely to be in a relationship where their spouse is working while they themselves are not. They are also 12 percentage points less likely to be classified as above middle-wealth class according to the wealth ranking provided by the TDHS. These effects are in line with forced migration leading to a change in intrahousehold bargaining power that favours the men in the family. In Turkey, on average, women’s labour force participation is higher in the rural sector compared with the urban sector (Aran et al. 2009; Tunali 2003). Moreover, Tunali (2003) shows that women’s unemployment rate is higher in the urban sector, which suggests that employment rates are even lower.19 Given these patterns, forced migration in this context is likely to have widened the gap in employment opportunities of women relative to men, lowering their bargaining position. While this is in line with the bargaining power mechanism discussed in Section 3, it does not imply that this is the only mechanism that may be at work.

Table 5.2.
Effects on employment and wealth
Respondent is employed at the time of interviewRespondent’s spouse is employedRespondent is not employed but her spouse isAbove middle-wealth class
(1)(2)(3)(4)

From conflict region x Migrated during conflict x Kurdish

−0.014

0.078

0.112*

−0.117**

(0.058)

(0.051)

(0.067)

(0.054)

Mean level of outcome (full sample)

0.304

0.900

0.592

0.372

Mean level of outcome (subsample)

0.129

0.842

0.708

0.081

Adjusted R-squared

0.093

0.065

0.082

0.233

Number of observations

13721

13036

13733

13733

Respondent is employed at the time of interviewRespondent’s spouse is employedRespondent is not employed but her spouse isAbove middle-wealth class
(1)(2)(3)(4)

From conflict region x Migrated during conflict x Kurdish

−0.014

0.078

0.112*

−0.117**

(0.058)

(0.051)

(0.067)

(0.054)

Mean level of outcome (full sample)

0.304

0.900

0.592

0.372

Mean level of outcome (subsample)

0.129

0.842

0.708

0.081

Adjusted R-squared

0.093

0.065

0.082

0.233

Number of observations

13721

13036

13733

13733

Source: Author’s calculations based on data from the 2008 and 2013 Turkish Demographic and Health Surveys.

Each column provides the result of estimating specification [1]. For brevity, only the estimate for λ, the coefficient of the triple-interaction term, is reported. Estimates of other parameters of the model are reported in Gulesci (2017: Table B3). The sample is restricted to married women only. The dependent variable in Column (1) is a dummy variable =1 if the respondent is working at an income-generating activity at the time of the survey; in Column (2) it is a dummy variable =1 if the respondent’s husband is working at an income-generating activity; in Column (3) it is a dummy variable =1 if the respondent’s husband is working but the respondent is not working at an income-generating activity at the time of the survey. In Column (4) the outcome is a dummy variable =1 if the respondent’s household is classified as in class 4 or 5 in the TDHS wealth index, which is based on their asset ownership and ranges from 1 (poorest) to 5 (richest). ‘From conflict region’ is a dummy variable =1 if the respondent was born and/or grew up in one of the conflict provinces (Adiyaman, Agri, Batman, Bingol, Bitlis, Diyarbakir, Elazig, Hakkari, Mardin, Mus, Siirt, Sirnak, Tunceli, and Van). ‘Migrated during conflict’ is a dummy variable =1 if the respondent migrated at least once during the conflict years (1984–99). ‘Kurdish’ is a dummy variable =1 if the first language of either the mother or the father of the respondent was Kurdish. ‘From conflict region x Migrated during conflict x Kurdish’ is the triple-interaction term that identifies the effect of being forced to migrate due to the conflict. All regressions control for the following covariates: a dummy variable =1 if the respondent’s mother ever went to school; a dummy variable =1 if the respondent’s father completed primary school; a dummy variable =1 if the respondent’s father graduated from secondary school or above; a dummy variable =1 if the respondent’s parents were related by blood; province of birth and TDHS wave fixed effects. The row ‘mean level of outcome (subsample)’ gives the mean of the outcome variable among Kurdish women from the conflict region who did not migrate during the conflict. Robust standard errors are clustered by birth province. *** (**) (*) indicates significance at the 1% (5%) (10%) level.

Finally, I explore whether forced migration increased the likelihood of the respondent’s spouse behaving in a controlling manner. In the TDHS, every respondent who was (or had been) married was asked if her current or (if divorced or widowed) last partner had ever tried to prevent her from seeing her friends, limited her contact with her family, insisted on knowing where she was at all times, distrusted her with money, or accused her of being unfaithful. Table 5.3 shows the effect of forced migration on respondents’ likelihood of having experienced such behaviours. Forced migration is associated with a 10 percentage point increase in the likelihood that respondents’ husbands exhibited at least one of these behaviours (Column (6)). This effect is mainly driven by an increase in their partners’ likelihood of insisting on knowing where she was at all times and preventing her from seeing her friends. This increase in men’s attempts to control women’s actions may be in line with a number of mechanisms that were discussed in Section 3. For example, forced migration may have brought traditional male gender roles into conflict with more modern roles, which may have induced men to become more controlling. Further research and more detailed data are needed to fully understand the key mechanisms driving the effect of forced migration on domestic violence attitudes.

As an additional, suggestive piece of evidence, I explore the differences between forced migrant women and others who sought help from the shelter NGO in dealing with the consequences of domestic violence. Table 5.4 presents the results of estimating specification [2] on the duration of domestic violence experienced by each applicant and previous help sought prior to applying to the NGO. The estimates in Column (1) show that among Kurdish women who applied to the NGO for assistance, forced migrants—with controls for being a migrant in general—were seven percentage points more likely to have been in a relationship for over ten years and experienced domestic violence since the beginning of this relationship. This finding is robust to controlling for age at marriage, being forced into the marriage, housing conditions, and literacy level of the applicants (Column (2)). This suggests that forced migrant women suffered domestic violence for a longer period before deciding to seek assistance from the NGO. The rest of the table shows that forced migrants are also less likely to have sought any treatment or filed a legal complaint, and no more likely to have complained to other institutions or people, prior to seeking help from the shelter. This rules out the possibility that the reason why forced migrant women applied later was that they were receiving assistance from alternative institutions or people.

Table 5.4.
Duration of domestic violence and previous support sought
Violence has been going on since the start of a 10+-year relationshipReceived medical or psychological treatmentFiled a legal complaintComplained to police, court, family, or friends
(1)(2)(3)(4)(5)(6)(7)(8)

Forced migrant

0.069**

0.069**

−0.048**

−0.044**

−0.025*

−0.029**

−0.023

−0.027

(0.029)

(0.029)

(0.019)

(0.019)

(0.013)

(0.014)

(0.030)

(0.030)

Basic controls

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Additional controls

No

Yes

No

Yes

No

Yes

No

Yes

Mean level of outcome

0.304

0.129

0.060

0.597

Adjusted R-squared

0.204

0.217

0.255

0.264

0.036

0.041

0.269

0.275

Number of observations

2278

2278

2272

2272

2276

2276

2278

2278

Violence has been going on since the start of a 10+-year relationshipReceived medical or psychological treatmentFiled a legal complaintComplained to police, court, family, or friends
(1)(2)(3)(4)(5)(6)(7)(8)

Forced migrant

0.069**

0.069**

−0.048**

−0.044**

−0.025*

−0.029**

−0.023

−0.027

(0.029)

(0.029)

(0.019)

(0.019)

(0.013)

(0.014)

(0.030)

(0.030)

Basic controls

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Additional controls

No

Yes

No

Yes

No

Yes

No

Yes

Mean level of outcome

0.304

0.129

0.060

0.597

Adjusted R-squared

0.204

0.217

0.255

0.264

0.036

0.041

0.269

0.275

Number of observations

2278

2278

2272

2272

2276

2276

2278

2278

Source: Author’s calculations based on applications to the shelter NGO.

The table reports the results of estimating specification [2]. For brevity, only the estimate for σ, the coefficient of ‘forced migrant’, is reported. Estimates of other parameters of the model are reported in Gulesci (2017: Table B5). The sample includes Kurdish women who applied to the women’s shelter between October 2009 and December 2011 to seek assistance in relation to physical or sexual domestic (intrahousehold) violence. In Columns (1)–(2) the dependent variable is a dummy variable =1 if the relationship in which the applicant has experienced domestic violence started 10 or more years ago and she reports that the violence has been going on since the beginning of the relationship. In Columns (3)–(4) the dependent variable is a dummy variable =1 if the applicant reports having received medical, psychological, or other treatment due to the domestic violence she has experienced. In Columns (5)–(6) the dependent variable is a dummy variable =1 if the applicant has a legal document issued by the police or courts proving that she experienced domestic violence. In Columns (7)–(8) the dependent variable is a dummy variable =1 if the applicant says she complained about the domestic violence she experienced to anyone (e.g. friends, family, police, courts, etc.). ‘Forced migrant’ is a dummy variable =1 if the respondent reports that she was forced to migrate from her residence due to security concerns more than 10 years ago. ‘Migrant’ is a dummy variable =1 if the applicant ever migrated for any reason. ‘Housing: gecekondu’ is a dummy variable =1 if the applicant lives in a gecekondu, a makeshift dwelling put up quickly without legal permission, often by squatters. ‘Household size’ is the number of people living in the applicant’s household. ‘Literate’ is a dummy variable =1 if the applicant reports that she is able to read and write. ‘Age at marriage 15 or younger’ is a dummy variable =1 if the applicant first married when she was younger than 16 years old. ‘Age at marriage 16–17’ is a dummy variable =1 if the applicant first married while she was 16 or 17. ‘Forced to marry against her will’ is a dummy variable =1 if the applicant reports that she was forced into the marriage she is currently in. ‘Has independent source of income’ is a dummy variable =1 if the applicant reports that she has an income source that is not dependent on her husband or other men in her family. All regressions control for province, month, and year of application fixed effects. Standard errors are clustered by province. *** (**) (*) indicates significance at the 1% (5%) (10%) level.

Table 5.5 shows the association between forced migration and some indicators of the extent of domestic violence experienced by the applicants. The first two columns show that forced migrants were five to six percentage points more likely to have been forced to have sex against their will—significant only when controls are added in Column (2). This corresponds to an increase of 12 per cent in the outcome relative to the sample mean. In Columns (3–4), the dependent variable is whether the applicant reported having had a miscarriage caused by the domestic violence she experienced. This likelihood is four percentage points higher among forced migrants, a large effect considering that in the entire sample only 8 per cent of women reported having had a miscarriage due to domestic violence. Taken together, the findings suggest that forced migrant women had endured domestic violence for longer and of greater severity before deciding to seek help from the NGO.

Table 5.5.
Extent of domestic violence
Forced to have sex against her willHad a miscarriage due to the violence
(1)(2)(3)(4)

Forced migrant

0.048

0.060*

0.041**

0.035**

(0.031)

(0.032)

(0.017)

(0.017)

Basic controls

Yes

Yes

Yes

Yes

Additional controls

No

Yes

No

Yes

Mean level of outcome

0.494

0.083

Adjusted R-squared

0.261

0.267

0.199

0.205

Number of observations

2093

2093

2274

2274

Forced to have sex against her willHad a miscarriage due to the violence
(1)(2)(3)(4)

Forced migrant

0.048

0.060*

0.041**

0.035**

(0.031)

(0.032)

(0.017)

(0.017)

Basic controls

Yes

Yes

Yes

Yes

Additional controls

No

Yes

No

Yes

Mean level of outcome

0.494

0.083

Adjusted R-squared

0.261

0.267

0.199

0.205

Number of observations

2093

2093

2274

2274

Source: Author’s calculations based on applications to the shelter NGO.

The table reports results of estimating specification [2]. For brevity, only the estimate for σ, the coefficient of ‘forced migrant’, is reported. Estimates of other parameters of the model are reported in Gulesci (2017: Table B6). The sample includes Kurdish women who applied to the women’s shelter between October 2009 and December 2011 to seek assistance in relation to physical or sexual domestic (intrahousehold) violence. In Columns (1)–(2) the dependent variable is a dummy variable =1 if the applicant reports that she was forced to have sex unwillingly. In Columns (3)–(4) the dependent variable is a dummy variable =1 if the applicant reported having had a miscarriage caused mainly by the domestic violence she had experienced. ‘Forced migrant’ is a dummy variable =1 if the respondent reported that she was forced to migrate from her residence due to security concerns more than 10 years ago. ‘Migrant’ is a dummy variable =1 if the applicant ever migrated. ‘Housing: gecekondu’ is a dummy variable =1 if the applicant lives in a gecekondu, a makeshift dwelling put up quickly without legal permission, often by squatters. ‘Household size’ is the number of people living in the applicant’s household. ‘Literate’ is a dummy variable =1 if the applicant reported that she was able to read and write. ‘Age at marriage 15 or younger’ is a dummy variable =1 if the applicant first married when she was younger than 16 years old. ‘Age at marriage 16–17’ is a dummy variable =1 if the applicant first married while she was 16 or 17. ‘Forced to marry against her will’ is a dummy variable =1 if the applicant reported that she was forced into the marriage she was currently in. ‘Has independent source of income’ is a dummy variable =1 if the applicant reported that she had an income source that was not dependent on her husband or other men in her family. All regressions control for province, month, and year of application fixed effects. Standard errors are clustered by province. *** (**) (*) indicates significance at the 1% (5%) (10%) level.

In this chapter, I studied the effects of forced migration caused by the Turkish-Kurdish conflict from the mid-1980s to the end of the 1990s on migrating women’s attitudes towards domestic violence. Evidence from two separate data sources (the TDHS and a database of applicants to a women’s shelter NGO) suggests that women who were forced to leave their homes due to the conflict are more tolerant towards domestic violence. In the TDHS data, forced migrants were more likely to report that a husband was justified in beating his wife and to have experienced controlling behaviours by their husbands. Moreover, among the applicants to the shelter NGO, forced migrants had endured domestic violence for longer and of greater severity before deciding to seek assistance.

There may be multiple mechanisms that drive the impact of forced migration on attitudes towards domestic violence in this context. One possible mechanism is a fall in the bargaining position of women within the household, and a general worsening of their economic status. Moreover, forced migration increased the incidence of controlling behaviours by men, suggesting that it may have threatened traditional gender roles. Future research is needed on the extent to which other mechanisms—for example, the loss of social networks, or the psychological consequences of conflict exposure—may influence the way in which forced migration shapes migrants’ attitudes towards domestic violence. Understanding the relative importance of these mechanisms across contexts is essential for designing effective policies to address the long-run consequences of forced migration for domestic violence.

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Notes
1

Some NGOs have claimed that this is gravely under-reported, and that the true number of displaced people is as high as three million (IDMC 2013).

2

In the 2008 TDHS, only women who had been married at least once were surveyed, while in 2013 all women (regardless of marital status) were surveyed.

3

Due to the sensitive nature of the data, and in order to protect the anonymity of the respondents, the name of the NGO cannot be revealed.

4

These findings are robust to controls for age, housing conditions, education, age at marriage, whether the applicant was forced into marriage, and whether she had an independent source of income.

5

Although it was never officially declared an OHAL province, a lot of forced migration also took place in the neighbouring province of Ağrı (HÜNEE 2005). I include Ağrı province in the OHAL region for the empirical analysis, but the results are robust to its exclusion.

6

There is little evidence about the interconnection between the incidence of domestic violence and women’s attitudes towards it. García-Moreno et al. (2005) show that the two are positively correlated. Using micro data from a variety of settings, they show that women who experienced domestic violence are more likely to find it acceptable.

7

The literature on the effects of forced migration on the employment and earnings of the migrants is largely limited to refugees in developed countries (Cortes 2004; Khan 1997).

8

Domestic violence is widespread in Turkey. In a nationally representative survey, 42 per cent of women reported being subject to violence (TRPM 2008). While this figure is likely to be under-reported, it is already high enough to place Turkey among the set of countries with the highest rates of domestic violence (Devries et al. 2013; WHO 2013). In terms of cultural tolerance towards domestic violence, the TDHS data used in this chapter shows that 20 per cent of female respondents said it was acceptable for a husband to beat his wife in at least one of the situations they were asked about. The rate was nearly double among respondents who lived in rural areas (31 per cent) compared with those from cities or towns (16 per cent).

9

A burgeoning literature studies how migrating to another country may influence cultural norms, both at the destination and in the source country (see Barsbai et al. (2017) for a recent review), yet evidence on how migration affects the norms and attitudes of the migrants is rare. This is partly because estimates of the impact of migration on the migrants’ attitudes are likely to suffer from selection bias, as people who choose to migrate are likely to have different attitudes from those who stay behind. In the case of forced migration, entire communities are typically uprooted, in a way that is exogenous to their pre-existing cultural norms or attitudes.

10

A number of recent papers have studied the effects of war on domestic violence, and have found that exposure to conflict may increase its incidence (Justino et al. 2015; La Mattina 2017; Noe and Rieckmann 2013). Calderon et al. (2011) show that in Colombia forced migration due to conflict led to higher labour force participation and earnings for women, but also to higher rates of domestic violence.

11

In order to ensure that differences in sampling do not drive the estimates, I control for survey wave fixed effects throughout the empirical analysis.

12

The last two scenarios were included in the 2008 TDHS but not in the 2013 TDHS. When constructing the aggregate indices, I use all available information within each survey wave. Restricting the analysis to the first five scenarios alone does not change the results qualitatively.

13

The data was collected upon application, prior to any action taken by the NGO.

14

The survey contained two questions on migration: whether it had taken place due to security concerns, and whether it had happened recently or more than ten years ago. Since the conflict in question took place between 1984 and 1999, and the data was collected between 2009 and 2011, I define anyone who reported having moved due to security concerns more than ten years before the interview as a forced migrant. While the label ‘security concern’ may seem general, discussions with the NGO workers who recorded the data suggest that this label was applied to identify forced migrants due to civil conflict as opposed to any other type of security concern.

15

The control variables are the age of the respondent, age-squared, respondent’s mother’s and father’s educational levels, and a dummy for whether the respondent’s parents were related.

16

In the baseline specification, the following control variables are included: age of the respondent, age-squared, and whether she is a migrant (forced or otherwise). In a second specification, I also control for whether the respondent has an independent source of income, the number of members living in the respondent’s household, and dummy variables for whether the respondent is literate, lives in a gecekondu (a makeshift dwelling put up quickly without legal permission), was married younger than 15 or aged 16–17 (the reference category being that she married at 18 or older), and was forced to marry against her will.

17

For brevity, the table only reports the coefficient of estimate for λ, the triple difference between women from the conflict region (vs the rest of the country), who migrated during the conflict period (vs did not migrate in this period), who are Kurdish (vs Turkish). The full set of results is reported in Appendix B.

18

Gulesci (2017: Table 2) presents the effects on individual scenarios that the respondents were asked about. The estimates for λ are positive for all and statistically significant for three out of the seven scenarios. Moreover, a test of joint significance of the coefficients is rejected at conventional levels.

19

Gulesci (2017: Table A4) shows the pattern in the TDHS data. On average, 29 per cent of women living in urban areas are employed, while the corresponding rate is 39 per cent in rural areas. The gap is particularly high among women with low schooling. For men, the reverse is true: men in urban regions are more likely on average to have a job relative to those in rural areas.

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