Are Movers More Egalitarian than Stayers? An Intergenerational Perspective on Intra-Household Financial Decision-Making

Abstract

This study seeks to investigate the role of international migration in shaping the financial decision-making behaviors of married couples through a comparison of three generations of Turkish migrants to Europe (i.e., movers) with their counterparts who remained in Turkey (i.e., stayers). The data are drawn from a subset of personal data from the 2000 Families Survey, involving 4,215 interviews performed randomly with married individuals nested within 1,713 families. The results suggest that international migration increases the tendency for spouses to jointly decide on their finances by (1) weakening the intergenerational transmission of traditional financial decision-making behaviors and gender ideologies and (2) enabling more intense acculturation of younger generations within “less patriarchal” contexts. With its unique, intergenerational, and multisite perspective, the study provides particular insight into the understudied relationship between migration and intra-household decision-making and its benefits for gender equality.

Introduction

How married or co-habiting couples organize their finances has attracted considerable research attention since the 1980s (e.g., Edwards 1981; Pahl 1989; Fleming 1997; Elizabeth 2001; Vogler, Lyonette, and Wiggins 2008). Studies have investigated the objective and subjective factors potentially influencing the financial decision-making behaviors of married or co-habiting couples and their outcomes for poverty and inequality (e.g., Vogler and Pahl 1994; Goode et al. 1998; Eroğlu 2009; Evertsson and Nyman 2014). However, little is known about the role of international migration in shaping intra-household (financial) decision-making behaviors, the underlying gender ideologies, and their transmission across generations.

This study is an attempt to bridge these research gaps by drawing comparisons between three generations of married couples who moved from Turkey to Europe and their stayer counterparts who remained behind. The migration history of these groups dates back to the guest worker years of 1961 to 1974, when many Western European countries pursued active labor recruitment policies to tackle the major labor shortages they faced (Akgündüz 2008). About one million people moved from Turkey to Europe at the time, becoming the largest guest worker group in the continent (ibid.). Turkish migration to Europe has continued since then, through family formation/reunification, employment, education, and political asylum. Today, people from Turkey comprise one of the largest diasporas in Europe (Güveli et al. 2016). About five million people of Turkish descent are estimated to live in Europe, with significant numbers in Germany, France, the Netherlands, and Austria (ibid.). Our focus on a large minority group with a long history in Europe presents a perfect opportunity to explore international migration’s possible effects on financial decision-making behaviors of couples from an intergenerational perspective.

Theoretical and Empirical Background

Two closely linked bodies of literature frame this study: one concerned with intra-household distribution (or allocation) of resources and the other with the wider processes of household decision-making. In the qualitative and quantitative branches of the first literature, the objects of allocation (or distribution) studied under the rubric of “resources” range from income to assets, from consumption goods to services (e.g., Messer 1997; Phipps and Woolley 2006; Grabka, Marcus, and Sierminska 2013). A substantial part of this body of work, however, examines income allocation, mostly based upon the distinction between the concepts of “financial control” and “financial (or money) management” (Edwards 1981; Pahl 1983). Financial control involves making important decisions concerning how income will be allocated and how responsibilities for different areas of spending will be shared, whereas financial (or money) management concerns the day-to-day implementation of these decisions in practice (ibid.).

Questions remain concerning the extent to which the conceptual distinction between financial control and management can be maintained (Bennett 2013), given the blurry line between them in relation to situations such as women’s use of covert mechanisms like “secret kitties” to subvert male authority (Eroğlu 2009) or potential sense of empowerment from managing money or applying their financial skills (Pahl 1989; Iversen 2003). Nonetheless, the distinction remains of significance to understanding both the balance of power between couples and their position within “the hierarchy of financial responsibility” (Morris 1990, 106), even if the bulk of existing work on this theme focuses on money management (e.g., Roman and Vogler 1999; Elizabeth 2001; Burgoyne et al. 2007; Lott 2016).

Within the smaller literature focused on financial control, three main streams can be identified. One explores how responsibility for financial control is organized and/or linked with money management (Land 1969; Pahl 1983, 1989; Burgoyne and Lewis 1994; Rake and Jayatilaka 2002; Eroğlu 2009, 2011; Cantillon 2013). A second stream investigates the implications of financial control for household poverty and inequality in terms of differences in couples’ access to power; (personal spending) money; consumption items; and, to a lesser extent, living standards (Wilson 1987; Blumberg 1988; Pahl 1989; Burgoyne 1990; Vogler and Pahl 1994; Lister 1998; Goode, Callender, and Vogler 1998; Nyman 1999; Bradbury 2004; Vogler, Lyonette, and Wiggins 2008; Eroğlu 2009, 2011; Cantillon 2013).

The third stream is of particular relevance to this study, given its focus upon the predictors of financial control. One frequently documented predictor concerns partners’ relative contributions to household income, indicated by their employment status or earning levels (e.g., Fleming 1997; Woolley 2000; Kenney 2006; Bertocchi, Brunetti, and Toricelli 2014). These works show that women have a greater say in financial matters especially when they generate a considerable portion of household income or when their earnings approach or exceed that of the men. Other key predictors of financial control include partners’ age and educational status. For instance, Bertocchi, Brunetti, and Toricelli (2014) demonstrate that women’s responsibility for financial control is higher among couples that are closer in age and hold similar educational status. Further, Woolley (2000) documents a greater tendency for younger couples to share responsibility for financial control.

A less frequently reported predictor of financial control relates to race and ethnicity (Fleming 1997; Kenney 2006). Fleming’s qualitative study of couples in New Zealand, for example, shows that ethnicity matters, given cultural differences in the value ethnic groups attach to control of money as an expression of power. The potential influence of (international) migration within this overall body of scholarship remains little explored, although existing research provides some evidence of its redistributive effects upon financial decision-making power and household resources. For example, Antman’s study (2015) shows that within households, migration increases the daughters’ share of resources by allowing female partners to gain greater control over financial decision-making in the absence of the migrant male head.

The other relevant body of literature is concerned with wider processes of household decision-making, considered to depend upon the balance of power between spouses. Most studies from this literature endeavor to ascertain the causes of power differentials between partners, theoretically or empirically. Many relevant theories here come from economics and sociology (see Nyman and Dema 2007; Bennett 2013; and Himmelweit et al. 2013 for extended reviews). Drawn from sociology, the Resource Theory of Marital Power proposes that spouses’ control over household decision-making depends primarily upon the income and status they obtain through paid work (e.g., Blood and Wolfe 1960). This theory has, however, been criticized for ignoring the role of factors such as ideology and culture. Blumberg (1988), for instance, using the notion of ideological discount rate, argues that women’s contributions to income tend to be viewed as being of secondary importance regardless of the size or proportion of their earnings, due to powerful assumptions about breadwinning being a male role. Subsequent theories, including Exchange Theory and the Theory of Marital Dependence, draw attention to other influences and respectively emphasize the role of a range of alternatives open to spouses outside marriage and their access to resources (e.g., Katz 1997, cited in Bennett 2013).

As for economic theories of household decision-making, these move from the unitary to bargaining and other collective models. Unitary models treat the household as a single decision-making body and investigate the conditions under which this assumption holds (e.g., Becker 1981), while bargaining models recognize the household’s collective and conflictive nature that leads to differences in members’ interests and preferences (e.g., Sen 1990). Collective models represent a generalized version of the collective bargaining models, where spouses are assumed to co-operate for an efficient solution (e.g., Chiappori 1997). Broadly speaking, these models link power in decision-making with the consequences of a potential breakdown in co-operation (Bennett 2013).

The empirical literature on household decision-making provides substantial support for the resource theory of marital power and confirms prevailing findings about the predictors of financial control by demonstrating the significance of couple’s income, employment, education, and/or health status for understanding the power (im)balance within households (e.g., Friedberg and Webb 2006; Lührmann and Maurer 2007). Especially for women, the acquisition of power over decision-making is shown to depend upon their educational and employment status (ibid.).

The role of contexts is also explored, though to a lesser extent. A study by Lührmann and Maurer (2007), for example, reveals significant differences in the distribution of power between rural and urban couples. Furthermore, reflecting upon results from comparative research, Nyman, Reinikainen, and Stocks (2013) emphasize the importance of contextual factors in shaping intra-household income allocation. They assert that the gender ideologies underpinning the meanings attached to money not only influence welfare regimes but also are influenced by them. According to the regime approach advanced by Esping Andersen (1990), there is a dominant ideology underpinning the way states design and deliver welfare, and variation between them can be captured under three regime types (i.e., liberal, conservative, or social democratic). It follows from this argument that a government’s approach to welfare in areas concerning women may differ across regimes and is likely to shape public attitudes to gender (in)equality, as well as being shaped by it. Thus, the type of welfare regime prevalent within a given context can affect couples’ attitudes to gender and their sharing of financial decisions.

Beyond the role of context, subjective factors, such as couples’ perceptions about ownership of money and contributions to income, are also claimed to influence intra-household income allocation by virtue of their role in determining the entitlement to dictate how money is used (e.g., Elizabeth 2001; Himmelweit and Santos 2009; Evertsson and Nyman 2014). Such perceptions are, of course, associated with the gender ideologies to which couples subscribe. Vogler (1998), for example, speaks about two conflicting gender ideologies: one that relates to discourses of equality, suggesting that marriage should require sharing resources equally regardless of each spouse’s relative contributions to the household; and one that involves the discourse of breadwinning/earner entitlement, which gives the main breadwinner the legitimacy to exercise more financial power and have greater access to personal spending money. Gender ideologies have been shown to be as important an influence as partners’ relative contributions in determining how egalitarian couples are in their handling of money (e.g., Roman and Vogler 1999).

Before concluding this section, it should be noted that the existing literature offers little understanding of the nature or extent of change in patterns of income allocation within the household. Quantitative studies with a temporal dimension are particularly rare and tend to focus on money management (Vogler and Pahl 1993; Laurie and Gershuny 2000; Lott 2016). Of these works, some find more evidence of continuity over time (Laurie and Gershuny 2000), while others document change across unrelated generations. Lewis’s (2001, 167) study of younger and older couples in the United Kingdom, for instance, shows that younger couples are more likely than older ones to have a “joint approach to money” and at the same time expect to control their “own” money. Studies, mostly from a qualitative perspective demonstrate how major life events such as marriage, childbirth, or sickness can alter the ways in which money is managed or controlled (e.g., Fleming 1997; Burgoyne et al. 2007; Nyman and Reinikainen 2007; Bisdee, Daly, and Price 2013; Lott 2016). However, the potential impact of a major life-changing process such as international migration remains unexplored. The present study is an attempt to bridge this gap.

Migration and Intra-Household Financial Decision-Making

As shown above, the relationship between international migration and intra-household financial decision-making is established neither theoretically nor empirically. What is, however, widely acknowledged is that spouses’ access to resources and the gender ideologies to which they subscribe are key to understanding how (financial) power is distributed and exercised within the household. This idea can be taken as a basis for explaining international migration’s influence. However, first one needs to be clear about the meaning of the term “resource” and its boundaries and place it within a wider framework that captures the range of micro- to macro-level factors potentially impacting spouses’ resources and financial decision-making behaviors. The resource-based perspectives used extensively within poverty and livelihoods literatures (e.g., Swift 1989; Moser 1998; Eroğlu 2013) have more recently been applied to understanding migrant adaptation/assimilation and subjective well-being (Alba and Nee 2003; Ryan, Dooley, and Benson 2008) and are particularly useful for this purpose. Of the existing variants, this study draws upon the framework developed by Eroğlu (2011, 2013) to explain household responses to poverty, including their intra-household allocation of income.

According to this framework, resources imply capacities that can be mobilized in their own right or in combination with others to generate material or immaterial benefits from various sources, such as the market, state, and household. Spouses are understood to have individual or joint access to a range of resources, including time, labor resources, economic capital (i.e., financial and non-financial assets); cultural capital (i.e., educational qualifications and skills); social capital (i.e., relatively durable relations established in and outside the markets); and institutional entitlements granted by governmental and non-governmental institutions to regulate access to various monetary and non-monetary benefits (e.g., cash, assets, goods, and services). These resources are deployable in a range of market- and non-market-based activities for income generation, consumption, investment, and borrowing purposes, which then define spouses’ employment, income, and wealth status. Along with their gender ideologies and educational attainment levels (or cultural capital accumulations), spouses’ relative income, employment, and wealth status are critical to the ways (financial) power is distributed and exercised within the household.

Spouses’ resources, however, do not exist in a vacuum. Various micro- and macro-level factors enhance or constrain the availability, control/management, and benefit-delivery capacity of their resource portfolios. Of particular importance to this study are spouses’ personal features (e.g., age, generational position, family migration background); family endowments inherited from other generations (or intergenerational family transmissions or transfers) in the form of resources, behaviors, values, and beliefs; and the contextual influences to which they are exposed at the local, national, and global levels (e.g., public attitudes to gender). The last two sets of factors are likely to influence the gender ideologies to which they subscribe.

So where does migration come into play in this framework? International migration is viewed here as a life-changing process that fundamentally (re)shapes the resource portfolio and gender ideologies of migrant couples and their descendants by altering (1) the local and national contexts within which they operate and (2) the nature and extent of intergenerational family transfers. Through migration, people become exposed to a new context where gender relations are “more” or “less” patriarchal than in their origin country, and they acculturate within this context to varying extents.

Migration can also increase or reduce the extent of intergenerational family transmissions and/or change their character. There is a substantial amount of research within the international migration literature focused specifically on the transmission of (grand)parental resources, beliefs, values/attitudes, and behaviors. This literature is wide ranging in scope and explores the potential influence of intergenerational family transmissions on the availability of cultural and social capital resources (e.g., Nauck 2001); personal values or attitudes concerning gender roles, collectivism, achievement, and partner choice/intermarriage (Phalet and Schönpflug 2001; Ideama and Phalet 2007; Carol 2014; Spierings 2015; Kretschmer 2017); and behavioral patterns such as marriage arrangements and self-employment (Güveli et al. 2015; Baykara-Krumme 2017; Eroğlu 2018). Some of these studies target migrant families only, while others compare migrant families with “natives” or “stayers” in the origin country. For example, while Kretschmer (2017) finds a strong transmission of traditional gender attitudes among migrants as opposed to “natives,” Spierings’s (2015) migrant-stayer comparisons suggest a reduced influence of parental gender attitudes, especially upon those who grew up in Europe. Overall, evidence on the strength of intergenerational transmissions among migrants is rather mixed and dependent on the object of transmission and group(s) studied. Of particular relevance to this study are works with a specific focus on resources and gender-related roles, attitudes, and behaviors and their findings indicate the weakening effect of migration on their transmission across generations (e.g., Nauck 2001; Spierings 2015; Baykara-Krumme 2017).

Consequently, especially through changing both the context in which one lives and acculturates and the family endowments one receives from earlier generations, (international) migration plays a potentially crucial role in (re)shaping the relative income, employment, and wealth status of spouses and their gender ideologies, which in turn affects how (financial) power is distributed and exercised within the household. However, in disentangling migration-related effects, one should take into account potential issues arising from migrant selectivity. As pointed out by Chiswick (1986), migrants can form a distinct group with some observed or unobserved characteristics in terms of values, skills, and motivation that may systematically distinguish them from those who “choose” not to migrate. For example, in the case at hand, it is theoretically possible that movers were more open-minded about living in a “less patriarchal” society and held more egalitarian gender ideologies than stayers, even before they went to Europe. Among migrants, both those who settle in the destination country and those who return to their origins may potentially be self-selected, yet it could also be that returnees are less able to adapt to a new context where gender relations operate differently. The overall conclusion from these considerations is that researchers must carefully assess the potential bias that might result from migrant selectivity before drawing any causal inferences about migration’s role.

Research Design and Method

This study compares three generations of Turkish migrants to Europe (i.e., movers) with their counterparts who remained in the origin country (i.e., stayers) to answer the following research questions:

Do significant differences exist between movers and stayers in the ways they control their finances and make big financial decisions?

(a) Is there generational change in how finances are controlled within the household? (b) Do observed generational trends differ significantly between movers and stayers?

(a) To what extent do parents transmit their financial decision-making behaviors (and underlying gender ideologies) to their children? (b) Does the extent of transmission differ significantly between movers and stayers?

Data were drawn from the 2000 Families Survey that adopted an innovative technique of screening five high-migrant-sending regions in Turkey (Acıpayam, Akçaabat, Emirdağ, Kulu, and Şarkışla) to identify migrant and non-migrant families and obtain their contact details (Güveli et al. 2016). The selected regions represent rural and semi-urban parts of Turkey inhabited predominantly by Turks from a Sünni religious background, with only Şarkışla having a sizable Alevi minority and Kulu a small Kurdish population (for more information on the regions, see Güveli et al. 2015). Selection criteria for migrant families involved having a male ancestor who (1) might be alive or dead, (2) was or would have been between the ages of 65 and 90, (3) grew up in the region, (4) moved to Europe between 1960 and 1974, and (5) stayed there for at least five years. The same criteria were applied to their non-migrant comparators with one difference: their male ancestor must have stayed in Turkey instead of moving to Europe. A sampling quota of 80 percent migrant and 20 percent non-migrant was imposed on each region.

In screening families, a clustered probability sample was drawn for each region. The Turkish Statistical Institute’s (TÜİK) address register was used to obtain 100 primary sampling units with a random starting point. Each unit’s size was proportional to the estimated population size of the randomly chosen locality. From the primary sampling point onwards, the sample was selected through random walk. This approach involved going to the random starting point and knocking on every door if the locality included fewer than 1,000 households and on every other door if the number of inhabitants was 1,000 or above. Four migrant families were sampled for every non-migrant. The random walk ended when 60 households were screened or when eight families were recruited.

Screenings were carried out in two stages. First, a pilot study was performed in Şarkışla in Summer 2010. Second, the remaining four regions were screened in Summer 2011, when approximately 21,000 addresses were visited to achieve the target sample of 400 families per region. The strike rate (i.e., the proportion of eligible families) was around one in every 12 households, yielding 1,992 participating families in total. Of these, 1,580 were migrant, and 412 were non-migrant by background.

The survey charted members of both migrant and non-migrant families across Europe and Turkey up to the fourth generation. Descendants nested within migrant families are not necessarily movers themselves. Neither are those from non-migrant families entirely composed of stayers in Turkey. Given its specific focus on the large Turkish labor migration to Western Europe that occurred between 1961 and 1974, the survey’s migrant population was restricted to the first labor migrants (typically male), their descendants who migrated during or after the guest-worker years or were born in Europe, and those from non-migrant families who moved subsequently. Therefore, the survey cannot speak to the entire Turkish diaspora in Europe. Nonetheless, by sampling male ancestors from the Turkish regions that displayed high rates of migration to Europe over the given period, it captures the typical features of guest workers from Turkey and their descendants spanning multiple generations while providing partial coverage of those who migrated after 1974, thereby representing a substantial portion of the existing Turkish population in Europe.

Data were generated through face-to-face interviews with those present in the field and through phone interviews with those who were absent. Additionally, a three-month tracing procedure was put in place to establish contact and conduct interviews with “hard-to-reach” family members, mostly composed of those living in Europe at the time of the survey. Multiple instruments were administered for data collection — family, proxy, and personal questionnaires. This study uses data drawn from personal interviews performed face-to-face and over the phone in the summers of 2010 and 2011 with male ancestors and their randomly selected descendants aged 18 or above. The sample frame for each family included the living male ancestor; his two children; two adult children of these two children (i.e., male ancestors’ grandchildren); and their adult children, if any (i.e., male ancestors’ great grandchildren). For randomization, the adults with initials closest to A and Z were selected. The response rate was high, at 61 percent, amounting to a total of 5,980 personal interviews with individuals spanning three family generations nested within 1,770 families. This figure includes 515 interviewees recruited through additional tracing, which considerably boosted the survey’s coverage of migrant population, given that nearly all respondents interviewed over the tracing period had been settled in Europe and living there for a year or more.

The current study draws on a subset of personal interviews with 4,215 currently married individuals nested within 1,713 families. The proportion of inter-ethnic couples with origins in Turkey and Europe was less than 1 percent (31 out of 4,042). Of currently married respondents, 80 percent (3,379) had a male migrant ancestor, while the remaining 20 percent did not. These respondents did not necessarily have the same migration status as their male ancestors; some were “movers,” whereas others were “stayers.” Movers refer to those who migrated to or were born in Europe and had lived there for at least one year, whereas stayers include those who had not left Turkey for more than a year. Movers is a heterogeneous category, combining “settler” and “return” migrants. Settlers include those who had been living in Europe at the time of data collection for a year or more, whereas return migrants refer to those who went (back) to Turkey after having spent at least a year in Europe. Within the sample of currently married respondents, 39 percent (1,623 out of 4,196) were settlers, 19 percent (779) were returnees, and the remaining 42 percent (1,794) were stayers in Turkey.

As for data analysis, the study estimated probit functions of financial control. Table 1 summarizes the dependent and independent variables specified for these models. The binary dependent variable was derived from the following question: “People have different arrangements for organizing their family finances. In your family, who has the responsibility for making big financial decisions? 1. Self or more self than partner/spouse 2. Partner/spouse or more partner/spouse than self. 3. Both self and partner/spouse equally. 4. Other.” Based on the respondent’s sex, a new variable was created with four categories specifying whether finances are male dominated, female dominated, jointly controlled, or other. This variable was then collapsed into a binary variable of whether household finances are jointly controlled.

Table 1.

Dependent and Independent Variables.

Dependent Variable		Descriptives
Financial control	1 jointly controlled0 not jointly controlled	40%60%
Independent Variables
Family migration background	1 male ancestor is a migrant0 male ancestor is a non-migrant (REF)	80%20%
Individual migration status	1 mover to Europe0 stayer in Turkey (REF)	49% (pooled models)51%
Family generations	1 first generation: G1-male ancestor2 second generation: G2 (REF)3 third generation: G3	23%56%21%
Male spouse’s education	Highest qualification achieved (1, 5)	(Mean = 2.96; SD = 1.16)
Female spouse’s education	Highest qualification achieved (1, 5)	(Mean = 2.78; SD = 1.14)
Spousal earner status	1 dual earner (REF)2 male earner3 female earner	24%75%1%
Parental financial control	1 Parents jointly control finances0 Parents not jointly control finances	31% (dyadic models)69%

The independent variables were specified to ascertain the role of migration and intergenerational family transfers and to track change across generations. They represent core elements of the resource-based framework that are of particular relevance to this study. Of those variables that capture respondents’ personal features, “family migration background” and “individual migration status” are included to measure migration-related effects and “family generations” and “age” to identify generational trends. The latter variable was included within the early models to disentangle generational effects. Of the three robustness checks performed for this purpose, the first incorporated all but the age variable, revealing significant differences between the first and second generations (G1 = –0.195, p < 0.05; G3 = 0.007, p = 0.917). The second excluded generations but yielded no significant age effects (Age = –0.004, p = 0.099). The third controlled for age, indicating insignificant results for both age and generations (Age = –0.001, p = 0.787; G1 = –0.162, p = 0.195; G3 = –0.003, p = 0.972). The generation effects may have been cancelled out due to possible multicollinearity between age and generation variables (r = –0.870, p < 0.001). To circumvent this problem, the age variable, shown to have no statistically significant effect, was omitted from the final analyses.

The “parental financial control” variable signifying the financial decision-making behaviors adopted by respondents’ parents was employed to determine the likely effects of intergenerational family transfers (e.g., of relevant values, beliefs, resources, and behaviors). This variable establishes a direct link (i.e., dyad) between the married child and his or her parent (who can be a member of the first or second generation) and indicates whether the respondent’s own parents jointly controlled their finances (or whether they made big financial decisions jointly or one party had a greater say). It was incorporated into the analyses to determine the extent to which married children displayed the same financial decision-making behaviors as their parents and thereby to draw inferences about the nature and significance of intergenerational family transfers. The contextual influences have been explored on the basis of a distinction between Turkey and Western Europe, as reflected within the “individual migration status” variable. Dividing the sample in this way is considered meaningful and adequate since none of the Western European countries can be deemed “less patriarchal” than Turkey.

The other two co-variates (“spousal earner status” and “male and female spouses’ educational status”) represent spouses’ labor resources and cultural capital stocks, as well as their employment/relative income status. They comprise the key objective predictors of financial control that are frequently referenced within the existing literature (e.g., Fleming 1997; Woolley 2000; Kenney 2006; Bertocchi, Brunetti, and Toricelli 2014). The former variable, denoting whether male, female, or both spouses were in work, was employed as a proxy for their relative contributions to income. The ideal would have been to construct a variable capturing the relative size of their earnings, but the 2000 Families Survey contains earnings and work hours information only for the respondent, not for his or her spouse. Thus, the “spousal earner status” variable remains the best proxy one can obtain, given the data.

The economic capital stocks and wealth status of spouses are also considered of critical theoretical significance, but their possible effects could not be examined empirically due to the lack of gender-disaggregated data on asset ownership. For the same reasons, it was not possible to explore the likely influence of social capital and institutional entitlement type resources. Citizenship status could not be used as a proxy for the latter, as it varies only amongst movers. Despite such data limitations, the specified probit models represent a close approximation of the resource-based framework, capturing a great many of its elements that are of central importance to understanding (financial) power differentials between spouses.

The study estimated both pooled and separate probit functions of financial control. The former aggregated the data on movers and stayers whereas in the latter, the data were divided along the two groups. Two pooled models were specified. Model 1 was designed to identify possible migration effects and track generational trends in aggregate terms (RQ.1 and RQ.2a). As for RQ2.b, auxiliary probit analyses were performed separately for movers and stayers to see whether significant generational differences emerge between the two groups, but these yielded the same results as Model 1. Thus, to avoid repetition and provide greater detail on the generational distribution of financial control patterns across movers and stayers, cross-tabulations were presented instead. Model 2 was devised to determine the overall influence of direct family transfers from parents to their own children (RQ.3a), based on dyadic data that link the members of the second and third generations to their fathers/mothers. Of the 1,521 parent-child dyads established among currently married respondents, 256 were between the first (G1) and second (G2), and 1,265 were between the second (G2) and third generations (G3). Since the personal interview data contain no information about the financial control mechanisms adopted by the male ancestors’ parents, dyads could not be established between them and their parents.

Moreover, the dyads had to be formed using the respondent information only, as the survey did not ask about the parents of the respondent’s partner. However, sole reliance on respondent information for establishing dyads is unlikely to have caused a systematic bias, given the random distribution of male and female respondents to the mover and stayer categories. Additionally, separate models had to be estimated to understand whether intergenerational family transfers affect the financial decision-making behaviors of movers and stayers differently and thereby to answer RQ3.b. These between-group analyses also drew on dyadic data that provide information about direct family transfers from parents to their own children, allowing causal inferences to be drawn about migration’s possible role in shaping the extent of intergenerational family transfers.

It should be acknowledged here that the comparison of probit/logit coefficients across groups is a contentious issue. Among others, Mood (2010) infamously argues that neither of these coefficients can be meaningfully compared since effect sizes depend upon unobserved heterogeneity, which varies across samples, groups, and points in time. However, Buis (2015, 10) contends that the presence of such an effect in group comparisons is, in fact, not a problem but a desirable feature of logit — if one is to consider the dependent variable, the probability, as ‘an assessment of how likely it is that an event occurs.’ He goes on to suggest that

within groups…we are more certain the predicted probabilities can get closer to zero or one, so there is more room for a variable to have an effect. Logistic regression coefficients have exactly this property, [and] this property of logistic regression ensures that a comparison of odds ratios give an accurate description of the difference in effects across groups. (Ibid.)

This study follows Buis’s position, which extends to the comparisons of probit coefficients across groups, as these estimates of probability are an artefact of another binary response model similar to logit/logistic regression. Marginal effects need not be calculated here because group comparisons were based on whether the effects are significant, not on their magnitude. Finally, given the survey data’s nested nature, all models estimated here had to be cluster corrected to account for within-family association.

Results

This section summarizes the results obtained from the probit estimations, starting with the pooled models presented in Table 2. Model 1 reveals that unlike respondents’ family migration background, that is, having a male migrant ancestor in the family, respondents’ own migration status makes a significant difference to the ways couples control their finances. It appears from our results that movers were significantly more likely than stayers to control their finances jointly. An auxiliary probit estimation of the migration effects for settlers, returnees, and stayers reveals that settlers were significantly more likely than stayers to control their finances jointly (coefficients for settlers = 0.168, p < 0.01; and for returnees = 0.138, p = 0.106; stayers as the baseline). As for returnees, their financial decision-making behavior was not found to differ significantly either from that of settlers or stayers. (coefficients for settlers = 0.030, p = 0.715; for stayers = –0.138, p = 0.106; returnees as the baseline). The heterogeneity of returnees can thus be claimed to be driving down the strength of the association observed between financial control and individual migration status.

Table 2.

Pooled Probit Models of Financial Decision-Making amongst Married Couples.

Independent Variables	Model 1	Model 2
Family migration background^a
Migrant ancestor	0.038 (0.071)	0.044 (0.999)
Individual migration status^b
Mover	0.136* (0.056)	0.090 (0.745)
Family generations^c
G1	–0.195* (0.087)	Not applicable
G3	0.007 (0.064)	–0.110 (0.079)
Male spouse’s education	0.051 (0.027)	–0.029 (0.036)
Female spouse’s education	0.144*** (0.028)	–0.172*** (0.036)
Spouses’ earner status^d
Male earner	–0.507*** (0.060)	–0.454*** (0.077)
Female earner	–0.885*** (0.208)	–0.767** (0.265)
Parental financial control	Not applicable	0.283*** (0.077)
Constant	–0.427*** (0.121)	–0.487** (0.168)
Observations	2,752	1,479
Pseudo R ²	0.063	0.067

Note. Standard errors in parentheses.

Source: 2000 Families Survey, personal data.

^a Baseline: non-migrant ancestor. ^b Baseline: stayer. ^c Baseline: G2 second generation. ^d Baseline: dual earner.

*p < 0.05. **p < 0.01. ***p < 0.001.

Regarding generational differences, Model 1 shows that members of the first generation (male ancestors) were significantly less likely than those of the second generation to make big financial decisions together with their spouses. However, the model demonstrates no significant differences between members of the second and third generations. The observed generational trends apply to both movers and stayers, which can be seen more clearly from Table 3. The cross-tabulations presented here indicate that the propensity for first-generation men to adopt the joint mechanism of financial control was low for both groups, but it was 7% lower for their stayer counterparts. They also confirm that the tendency to use this mechanism is significantly greater for the younger generations, regardless of whether they moved to Europe. It might be 10% lower for the second generation of stayers than their mover counterparts but reaches similar levels for both movers and stayers in the third generation.

Table 3.

Financial Decision-Making Behaviors of Three Generations of Movers and Stayers.

	Movers to Europe			Stayers in Turkey
	G1	G2	G3	G1	G2	G3	Row Total
Jointly controlled	27%(201)	49%(500)	48%(96)	20%(28)	39%(486)	47%(297)	40%(1,608)
Not jointly controlled	73%(554)	51%(512)	52%(104)	80%(111)	61%(765)	53%(330)	60%(2,376)
Column total	100%(755)	100%(1,012)	100%(200)	100%(139)	100%(1,251)	100%(627)	100%(3,984)
Chi-square	98.3109, p < 0.001			37.6084, p < 0.001

Note. Ns in parentheses.

Source: 2000 Families Survey, personal data.

Returning to Table 2, Model 1 reveals that not the men’s, but the women’s educational status was strongly associated with financial control, meaning that where female spouses were better educated, couples tended to make big financial decisions together. The model also shows that in households where the male or female spouse was the only earner, couples were significantly less likely to control household finances jointly. It remains unknown exactly who controls the finances in single-earner households, but as can be seen from the cross-tabulations presented in Table 4, the assumption that the person who brings in the money makes the decision seems to work more for men than for women. This appears to be particularly the case with movers. In 55 percent of stayer families where women were the sole earners, women controlled the household finances whereas the percentage for movers was only 20 percent. Moreover, in 44 percent of mover families with sole female earners, household finances remained under men’s control.

Table 4.

Financial Decision-Making Behaviors of Movers and Stayers by Earner Status.

	Movers to Europe			Stayers in Turkey
	Dual Earner	Male Earner	Female Earner	Dual Earner	Male Earner	Female Earner
Male control	31%(136)	59%(753)	44%(11)	29%(116)	58%(743)	25%(5)
Female control	10%(45)	7%(84)	20%(5)	7%(29)	7%(94)	55%(11)
Joint control	59%(260)	34%(431)	36%(9)	64%(262)	35%(449)	20%(4)
Total	100%(441)	100%(1,268)	100%(25)	100%(407)	100%(1,286)	100%(20)
Fisher’s exact	0.000			0.000

Note. Ns in parentheses.

Source: 2000 Families Survey, personal data.

Model 2 confirms Model 1’s findings that no significant difference exists between members of the second and third generations after controlling for their individual migration status. This means couples from both generations, regardless of whether they moved to Europe, display an increased tendency toward joint financial control (see also Table 3). Model 2 also demonstrates a very strong positive relationship between the financial control mechanisms adopted by parents and their children, controlling for individual migration status. The strength of this association indicates that independently of whether they are movers and stayers, married children are significantly likely to display the same financial decision-making behaviors as their parents. This is equal to suggesting that those children whose parents adopt the joint mechanism of financial control are more likely to make financial decisions jointly with their spouses than those whose parents do not, and vice versa.

However, rather strikingly, the separate analyses presented in Table 5 demonstrate that the probit estimates for parental financial control are significant only for stayers. The cross-tabulations and chi-square test results presented in Table 6 also confirm this picture. From these results, it can be inferred that stayers are more likely than movers to display the same behavioral patterns as their parents or equally that stayers’ parents are more likely than those of movers to transfer their financial decision-making behaviors and underpinning gender ideologies. As discussed in detail below, the observed differences between movers and stayers may be attributable to migration and its particular role in hampering the transmission of relevant behaviors and values across family generations.¹

Table 5.

Separate Probit Models of Financial Decision-Making for Movers and Stayers (Dyadic).

Independent Variables	Movers	Stayers
Family migration background^a
Migrant ancestor	–0.069 (0.204)	0.044 (0.999)
Family generations^b
G1	Not applicable	Not applicable
G3	–1.777 (0.145)	–0.110 (0.079)
Male spouse’s education	0.083 (0.057)	–0.029 (0.036)
Female spouse’s education	0.110* (0.056)	–0.172*** (0.036)
Spouses’ earner status^c
Male earner	–0.352** (0.114)	–0.454*** (0.077)
Female earner	–0.798* (0.348)	–0.767** (0.265)
Parental financial control	–0.178 (0.123)	0.283*** (0.077)
Constant	–0.303*** (0.287)	–0.487** (0.168)
Observations	556	923
Pseudo R ²	0.038	0.067

Note. Standard errors in parentheses.

Source: 2000 Families Survey, personal data.

^a Baseline: non-migrant ancestor. ^b Baseline: G2 second generation. ^c Baseline: dual earner.

*p < 0.05. **p < 0.01. ***p < 0.001.

Table 6.

Financial Decision-Making Behaviors of Movers’ and Stayers’ Own Parents.

	Movers to Europe		Stayers in Turkey
	Joint	Not Joint	Joint	Not Joint	Row Total
Parents jointly controlled	57%(117)	50%(235)	57%(202)	40%(296)	100%(850)
Parents not jointly controlled	43%(89)	50%(237)	43%(152)	60%(451)	100%(929)
Column total	100%(206)	100%(472)	100%(354)	100%(747)	100%(1,779)
Chi Square	2.821, p = 0.093		29.4786, p < 0.001

Note. Ns in parentheses.

Source: 2000 Families Survey, personal data.

Discussion

What do the above findings tell us about migration’s role in shaping the financial decision-making behaviors of married couples? They suggest that having a migrant male ancestor as a father or grandfather makes no significant difference to the ways in which finances are controlled within the household. As is elaborated below, this might be due to the interference of international migration with the intergeneration transmission of financial decision-making behaviors and underlying gender ideologies. The migration background of one’s family may not matter, but one’s own migration status does seem to. Movers to Europe appear more inclined than stayers to adopt joint mechanisms of financial control. The tendency was found to be stronger for those movers currently settled in Europe than for returnees to Turkey. Can we infer from the evidence, then, that there is a migration effect?

It may be suggested that the observed differences cannot be attributed to migration due to possible self-selection bias. As discussed earlier, one might suggest that movers form a distinctly more progressive group that hold equalitarian gender ideologies, as compared with stayers, even before they migrated to Europe. Such positive self-selection remains theoretically possible but is rather unlikely, given the survey’s concerted sampling strategy to match the characteristics of the migrant (or mover) male ancestors with those of their non-migrant (stayer) comparators, ensuring that both sub-groups of men were born and grew up in one of the five regions that represent some of the most conservative and religious parts of rural/semi-urban Turkey. Therefore, both migrant and non-migrant men are very likely to have held traditional gender ideologies prior to labor migration to Europe, and their low propensity for joint financial control lends some support to this (see Table 3). Among movers, a minority of male ancestors might have been more egalitarian in their approach to gender pre-migration, which may have contributed to the observed difference between the first generation of movers and stayers (see Table 4). However, it is very unlikely that they constitute a large enough group to systematically bias the results. That said, one potential group of migrants where the self-selection argument might apply is the descendants of stayer male ancestors who subsequently moved to Europe, but with 19 percent (182 out of 981), they represent a small portion of the sample.

Moreover, the effect size for migration is likely to have been affected by possible bias arising from the strategy of sampling from origins, which led to under-representation of families who broke links with Turkey and, probably, over-representation of returnees. It is likely that these respectively represent the more- and less-adapted migrant groups, so should they have been proportionately sampled, the migration effect might have been of greater size. Consequently, it seems that the observed differences between movers and stayers cannot simply be explained away as self-selection. Migration to Europe appears to have an independent effect upon the financial decision-making behaviors of married Turkish couples, so let us now try to understand how.

To begin, the international migration process can be said to have exposed these couples to new, “less patriarchal” contexts where gender relations are less unequal and gender equality is widely promoted as an institutional goal. Their acculturation in such contexts is likely to have led them to adopt more egalitarian gender ideologies and mechanisms of financial control. It would be naïve to think that all people they encounter would be progressive in their attitudes to gender and the sharing of financial decision-making or that the institutions with which they come in contact would actively pursue the goal of gender equality. Yet it remains that movers are more likely to come across such people and institutional ideas in Europe than their stayer counterparts in Turkey, and this applies to all three generations. However, it should be acknowledged that the male ancestors who moved from Turkey in the 1960s and 1970s arrived in a more unequal Europe in terms of gender relations than did subsequent generations (see UN Women’s Progress of World’s Women 2010–2016 reports for evaluation of the progress made in reducing gender inequality since the 1990s).

The timing of migration to Europe may partly explain the lower propensity for the first generation of movers to adopt the joint mechanism of financial control than their second- and third-generation counterparts, or vice versa (see Table 3). However, the intensity of their acculturation also matters. Thus, the observed generational tendencies could also mean that the process has been rather moderate for the male ancestors. This finding holds even when currently married movers are examined separately as settlers and returnees, both of whom display a similarly low propensity to adopt the joint mechanism of financial control at 28 percent and 26 percent, respectively. On average, the first generation of movers had spent 29 years in Europe (SD = 14.45). The average duration of stay was around 42 years (SD = 3.86) for the first generation of settlers and 19 years (SD = 11.36) for their returnee counterparts. Thus, the majority of settler and returnee migrants can be said to have spent a long enough time in Europe for acculturation to potentially occur. The question then arises as to why the process of acculturation was not so intense for the first generation.

A full exploration of this question is beyond the scope of this study, but multiple tentative explanations can be offered. One such explanation relates to the age at migration. The studied male ancestors were selected from those who spent at least 16 years of their lives in Turkey. Their average age at arrival in Europe was around 30 (SD = 5.57). Given that these men spent their formative years in some of Turkey’s most conservative parts, they are likely to have arrived in Europe with set traditional ideas about gender, which may have made behavioral change more difficult.

A second reason concerns their initial migrant status. These men went to Europe in the 1960s and 1970s as guest workers without the expectation of staying indefinitely. From personal field observations, it became clear that one common plan shared among the migrant male ancestors was to return to Turkey after having made enough money to buy agricultural land and equipment. Indeed, while many ultimately stayed in Europe, they did so as sojourners with the aim of making and saving money. They might therefore have been more focused on working (mostly in heavy industries dominated by men) and, thus, participated less in the destination society’s mainstream social and cultural life. Berger and Mohr’s (1975/2010) vivid depictions of guest workers’ living and working conditions lend some support to this claim. Such workers from the first generation may hence be self-excluded to a degree, but it also remains probable that they were socially excluded by “natives.”

The possibility for social exclusion takes us to a third explanation, which has to do with negative public attitudes toward migrants, racism, and prejudice. It is difficult to find evidence that fully captures the nature and extent of public hostility suffered by Turkish migrants who moved to Western Europe in the 1960s and 1970s, yet Berger and Mohr’s reporting of guest-workers’ skepticism about the workers unions’ willingness or ability to defend their interests provides some justification for the social exclusion argument, given its implications for a negative context of reception where migrants felt excluded even from those circles duty-bound to protect their rights as workers.

A fourth explanation relates to language barriers. Indeed, the levels of oral and written proficiency in the country language are much lower for the first generation of movers than for their second- and third-generation counterparts. On a scale of 0 to 6, these men scored on average 2.49 (SD = 1.29), whereas the respective scores for the second and third generation of movers were 3.69 (SD = 1.37) and 3.59 (SD = 1.54), respectively. Whatever the reason, many initial movers appear to have had little opportunity to mix with “natives” outside the workplace. As a matter of interest, the proportion of first-generation movers with almost all their friends from Turkey or of Turkish origin was 67 percent. The respective figures were 40 percent and 32 percent for the second and third generations (chi-square = 147.4103, p < 0.001). The evidence tells us nothing about the intensity of their friendships (the first generation of movers might well have formed a few but very strong relationships with “natives”), but it at least suggests that intense acculturation was less likely for this group of men than for the younger generations.

As for the younger generations of movers, the majority appear to have stayed in Europe long enough for the acculturation process to take effect (mean duration of stay for G2 = 25.87, SD = 12:75; mean for G3 = 14.39, SD = 10.22). They arrived in Europe at a younger age than their first-generation counterparts (mean age at migration for G2 = 14.19, SD = 9.67; mean for G3 = 14, SD = 9.06), with 11 percent (458 out of 4,197) born there. As shown above, younger generations attained higher levels of proficiency in the receiving country’s oral and written language. This fact is unsurprising, given that more of them were schooled in Europe (proportion of married movers with completed or continued education in the receiving country for G1 = 0.2%; G2 = 41%; G3 = 35%).

All these factors likely helped younger generations pass through a relatively more intense process of acculturation. However, this study empirically demonstrates the significance of one key factor — the intergenerational transmission of financial decision-making behaviors (and underlying gender ideologies). The extent of such transmissions turned out to be much smaller for movers than for stayers (see Tables 5 and 6), and this difference could be due to international migration. How migration actually weakens intergenerational family transmissions is a question requiring further exploration. Some tentative explanations may nevertheless be offered. The loss of physical proximity between mover parents and their children could be one. Another reason might be that a new, relatively “less patriarchal” context where gender attitudes and relations take different forms than those at home may be more attractive to younger people who spent their years of identity formation in Europe. Migration can hence be said to be weakening the influence of family and interfering with the transmission of parental financial behaviors and underlying gender ideologies to their children, thereby making it more possible for younger generations to acculturate more intensely.

Turning to the younger generations of stayers, they, like movers, display a greater tendency than their first-generation counterparts to adopt the joint mechanism of financial control. The rate of adoption, however, appears to have been slower for stayers. Only in the third generation do stayers catch up with movers (see Table 3). The generational trends observed for stayers may be gradual in nature but still indicate a significant upward movement. It is hard to say how much of the observed generational trends can be attributed to the concerted government effort to tackle patriarchy, in the absence of longitudinal evidence to track the progress that the Turkish governments have made since the 1960s. Nonetheless, according to the United Nations Development Programme (UNDP; n.d.), in 2010 Turkey scored 0.379 on the Gender Empowerment Measure (GEM), ranking 101 out of 109 countries. It would hence be correct to suggest that the observed generational trends are hardly attributable to the government initiative. The trends may also be explained through the cultural and technological processes of globalization. Such processes are likely to influence young people’s attitudes to gender, for instance, by connecting them more closely with dominant Western cultures where patriarchal relations are not so pervasive.

However, these explanations remain rather conjectural. What this research demonstrates empirically, though, is the persistent role of stayer families in transmitting parental financial decision-making behaviors (hence, the underlying gender ideologies) to younger generations (see Tables 5 and 6). Not having been through a major life-changing process such as international migration, stayer families seem to have continued with such transmissions without serious interruption. This still does not fully account for the significant increase in younger generations’ propensity to adopt more egalitarian mechanisms of financial control. One plausible explanation involves parental education. The outcome of the Spearman’s correlation test indicates that better-educated stayer parents are more likely to make big financial decisions jointly (Spearman’s rho = 0.107, p < 0.001). Hence, this group of parents are likely to be one of the key forces driving the upward generational trends in Turkey. Within a highly patriarchal society that offers more regressive options than the family, it is indeed likely that children will follow in the footsteps of their educated parents rather than adopt traditional gender ideologies.

So far, the discussion has focused on understanding international migration’s role in shaping the ways finances are controlled within the household. Questions, however, remain as to how strong its effect has been relative to other key influences. This study confirms that women’s educational and employment status play more central roles. It seems that men are “entitled” to making big financial decisions together with their spouses regardless of their educational background, whereas women earn this entitlement through education. Likewise, women’s contribution to the household monetary income also seems to help them gain some financial control. When men are not earning, couples are less likely to make joint decisions, but their lack of contribution to household income does not necessarily lead them to lose financial control. Especially, mover men tend to retain it when women are the sole earners, and this finding remains to be explained (Table 4).

Conclusion

Through a comparison of three generations of Turkish migrants who moved to Europe with their counterparts who stayed in Turkey, this study has sought to understand international migration’s influence on the financial decision-making behaviors of married couples. It has also traced generational trends for movers and stayers and explored whether significant differences exist between the two groups in the extent to which they transmitted these behaviors and underlying gender ideologies to their children.

Mover couples were found more likely than stayers to make big financial decisions together. It was concluded that the observed differences could not simply be attributed to migrant self-selection. Migration to another country was shown to have an independent effect by allowing migrants, especially those from younger generations, to acculturate within “less patriarchal” contexts that approach gender differently than at home and/or in the origin country. Migration was also shown to have an effect through weakening the influence of family and hence the transmission of parental financial decision-making behaviors and underlying gender ideologies to children.

Like their mover counterparts, subsequent generations of stayers were found to follow an upward trend toward joint financial control, though at a slower pace. Contrary to the case of movers, the families of stayers were shown to play a persistent role in the intergenerational transmission of relevant behaviors and gender ideologies. Better-educated parents in particular appear to be a key driver of the generational trends observed in Turkey.

International migration’s effect, however, turned out to be less important than other factors that past studies consider as key (i.e., spouses’ relative contributions to income, as indicated by their employment status and educational status). The findings of this study also confirm that women gain some control over household finances through either paid work or education. Congruent with the expectations of the resource power theory, it was shown that women’s contribution to monetary income has a greater influence upon the ways in which financial decisions are made within the household (for similar results, see Fleming 1997; Woolley 2000; Friedberg and Webb 2006; Kenney 2006; Lührmann and Maurer 2007; Bertocchi, Brunetti, and Toricelli 2014). As for men, only their employment status seems to make a difference. When men are not in paid work, financial decisions appear less likely to be made jointly, but, as also shown by previous studies (e.g., Fleming 1997), this does not necessarily lead to women taking control of household finances. Especially in the case of movers, men tend to retain control over household finances.

This research has, however, a number of limitations, mostly resulting from the coverage of the 2000 Families Survey (see Güveli et al. 2016 for a more detailed discussion of the survey’s strengths and weaknesses). The survey focuses on Turkish men who moved to Europe over the guest worker period between 1961 and 1974 and their counterparts who stayed in Turkey and traces their descendants up to the fourth generation, thereby only partially capturing post-1974 migrants. Hence, it is not representative of the entire Turkish diaspora in Europe, largely because the survey was not designed to represent all Turkish migrants who moved to Europe during the guest worker years but instead to focus on the Turkish regions most closely associated with migrants from this period. The sampling from these specific regions might, however, have biased the results, given the likelihood that those migrant families who completely broke links with their regions of origins are under-represented, while returnees are over-represented. If these sources of bias were non-existent, the migration effect could be stronger, since these families possibly represent the more- and less-adapted groups of migrants, respectively. This claim, however, remains to be established.

The study also leaves important questions for future research, one of which relates to acculturation. Several tentative explanations have been offered here to explain why the first generation of movers may be less acculturated than their second- and third-generation counterparts. It would be interesting to explore qualitatively the processes of acculturation for migrants, intergenerational differences in these processes, and the impact of such differences on financial decision-making behaviors and gender ideologies. Another important question for future exploration concerns how international migration weakens the transmission of financial decision-making behaviors and gender ideologies to younger generations. Further questions relate to the role of context. This study explored possible contextual effects based on a division between Turkey and Western Europe. It remains for future research to identify and explain the likely differences between European country contexts. Moreover, from Turkey’s low score on UNDP’s basic gender empowerment measure, it was inferred that the generational trends observed in the country could hardly be explained through government effort. Researchers may wish to validate this claim through a more thorough evaluation of the relevant government policies implemented since the 1960s and their impacts on gender inequalities and women’s empowerment in Turkey.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the NORFACE (New Opportunities for Research Funding Agency Co-operation in Europe) under the grant number 235548.

Notes

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