Intimate Partner Violence: The Influence of Job Opportunities for Men and Women

Abstract

This study examines the association of unemployment variation with intimate partner violence using representative data from thirty-one developing countries, from 2005 to 2016. It finds that a 1 percent increase in the male unemployment rate is associated with an increase in the incidence of physical violence against women by 0.50 percentage points, or 2.75 percent. This is consistent with financial and psychological stress generated by unemployment. Female unemployment rates have the opposite effect, a 1 percent decrease being associated with an increase in the probability of victimization of 0.52 percentage points, or 2.87 percent. That an improvement in women's employment opportunities is associated with increased violence is consistent with male backlash. The study finds that this pattern of behaviors emerges entirely from countries in which women have more limited access to divorce than men.

1. Introduction

Intimate partner violence (IPV) is pervasive, with about one in three women in richer as well as poorer countries reporting abuse over their lifetime (Devries et al. 2013). It is increasingly being recognized as an important part of the development agenda (WHO 2014; Michau et al. 2015; UN Women 2015a). While there were no targets for violence against women in the Millennium Development Goals, the new Sustainable Development Goals explicitly call for the “elimination of all forms of violence against women and girls” (UN Women 2015a). IPV tends to be higher in low-income countries, being 65.64 percent in Central Sub-Saharan Africa and 41.73 percent in South Asia, compared to 27.85 percent and 21.32 percent in Central Europe and North America, respectively (Devries et al. 2013). It not only harms the physical and mental health of women, it also harms children (Ellsberg et al. 2008; Aizer 2011; Rawlings and Siddique 2018). In the last decade, many countries have implemented laws criminalizing IPV, but the extent to which such laws are upheld varies hugely (OECD Development Centre 2014).

This paper considers how IPV varies with macroeconomic conditions, in particular, male and female unemployment rates, using comparable data for 31 developing countries. It considers male and female unemployment shocks, each conditional upon the other. Since these are correlated with one another but may have different impacts on violence, omitting either one will tend to bias the coefficient on the other. This study confirms that this is the case.¹ Of particular interest is how violence against individual women is associated with improved aggregate employment prospects for women. This is important because many interventions in developing countries, for example, microcredit schemes and skills training programs, are designed to increase women's employment. The direction of any association is unclear unless it is assumed that improved outside options can be leveraged to the woman's advantage. On the one hand, increases in women's employment opportunities may be expected to empower them and thus lower violence while, on the other, this may challenge gender norms leading to increased violence.

This study finds that a 1 percent increase in the male unemployment rate is associated with an increase in the incidence of physical violence against women by 0.50 percentage points (or 2.75 percent) while a 1 percent increase in female unemployment rates is associated with a reduction in the incidence of violence by 0.52 percentage points (or 2.87 percent). The pooled (male plus female) unemployment rate has no significant association with IPV.² The results are robust to a number of checks, including different measures of business cycle variation, and a leave-one-out analysis. Although the study avoids using this as the main specification, if the unemployment rate is replaced with the individual (un)employment status of the woman, a similar result is found, namely, that the employment of the individual woman is predictive of IPV. The study investigates whether these associations vary with whether there are restrictions on women's access to divorce and find that the results emerge entirely from countries in which women face greater legal and social barriers to divorce than men.³ In countries where women and men have equal access to divorce, the results are reversed, in line with recent results for the United Kingdom (Anderberg et al. 2016) and the United States (Aizer 2010).

A contribution of this study is that it paints a broad-brush picture for a large sample of developing countries. A further contribution is that it examines how the association of violence with male and female unemployment rates varies with the cultural and legal accessibility of divorce for women relative to men. The study shows a striking reversal of results by whether or not access is equal. However, it is not possible to obtain causal identification of the relationships of interest in this large and diverse sample.⁴ Earlier studies have tended to focus on the experience of individual countries, and often on responses of IPV to an individual woman working (e.g., Bowlus and Seitz 2006; Chin 2012; Tertilt and van den Berg 2015), and these studies are mostly set in developed countries.⁵ In contrast, this study considers macroeconomic shocks in a cross-section of countries over time.^6,7

Closely related to our approach are two recent studies, set in the United States and the United Kingdom respectively, which consider how macroeconomic changes in relative male and female economic opportunities influence IPV.⁸ Using demand-driven variation in female relative to male wages at the county level in the United States, Aizer (2010) shows that IPV is decreasing in women's relative wages. Anderberg et al. (2016) similarly find that improvements in the relative employment rates of women in the United Kingdom are associated with lower rates of IPV, and that male unemployment acts to inhibit IPV.⁹ These findings can be rationalized with reference to a household bargaining model in which better labor market prospects for women relative to men increase their bargaining power by improving their outside options. The higher the threat point of women, the more averse men are to committing violence that may enhance the risk of marital dissolution (Farmer and Tiefenthaler 1997). This study is able to replicate this pattern of results in this sample but only for the small fraction of countries in which women and men are similarly placed to access divorce (as is the case in the United Kingdom and United States).

The main findings contrast sharply with the results for the United Kingdom and the United States and can be explained by women in many low- and middle-income countries having weak outside options on account of social norms and embedded economic and political disadvantage (Bloch and Rao 2002; Anderson and Eswaran 2009). For many of the countries in the sample, woman lack equal access to divorce relative to men (table S1.1 in the supplementary online appendix, available with this article at The World Bank Economic Review website). This limits the extent to which divorce can act as a margin of adjustment and leaves women within marriage in a more vulnerable position even when economic opportunities for them improve.

As a result, improved job opportunities for women may not increase the probability that they exit marriage. Instead, outside job opportunities for women may act to threaten gender stereotypes and prime male identity, leading to male backlash (Macmillan and Gartner 1999).¹⁰ Some previous studies have documented evidence of backlash whereby men react negatively to higher earnings of women or to women performing nontraditional roles (Schuler et al. 1996; Luke and Munshi 2011; Mani 2011; Gagliarducci and Paserman 2012; Bertrand, Kamenica, and Pan 2015; Gangadharan et al. 2016). The coefficient on the male unemployment rate flips in developing countries for a similar reason. If divorce initiated by the woman is not a real threat, then male unemployment rates will not tame men but, instead, create psychological and financial stress that can lead to higher IPV (Angelucci 2008). The psychological stress is possibly greater than in richer countries because of male-breadwinner stereotypes being stronger, and the financial stress is probably greater because the family relies primarily on male income and there is limited state income support. Male unemployment may also raise IPV by reducing the opportunity cost of men's time (Blattman and Miguel 2010),¹¹ and increasing exposure of the woman to the man if he spends more time at home (Chin 2012).¹²

Similarly to this paper, but using Spanish data, Alonso-Borrego and Carrasco (2017) and Tur-Prats (2017) find that improved female employment opportunities increase violence against women for some (although not all) women.¹³Alonso-Borrego and Carrasco (2017) find that female employment reduces violence only if the female's partner is employed as well. Tur-Prats (2017) finds that in Spanish territories with a historical nuclear family tradition a decrease in female unemployment relative to male unemployment increases IPV due to cultural norms pertaining to gender.¹⁴ This study shows the critical role of women's access to divorce in explaining this relationship across a number of developing countries covering a wide geographical area. It may be that access to divorce is itself influenced by historical cultural norms pertaining to gender. However, given the wide geographical scope of our study, it is not possible to use consistent controls for such historical cultural norms, so the study cannot tease out the separate influence of gendered norms vs. access to divorce in this study.

Section 2 describes the data and section 3 the methodology. Section 4 provides the estimation results, section 5 the robustness checks, and section 6 provides a discussion and conclusions.

2. Data

The study uses individual data from the Demographic and Health Surveys (DHS), which are large-scale, repeated cross-sectional household surveys that use standardized questionnaires that are comparable across countries.

Intimate Partner Violence

Since 1998 the DHS has included a standardized domestic violence module that asks women if they have ever experienced specific acts of physical, emotional, or sexual abuse. Since 2005, the DHS has also asked women if they have experienced any of these three forms of violence in the twelve months preceding the survey date. The study analyses reports of abuse in the last twelve months so as to exploit the timing of unemployment shocks. A potential concern with self-reported measures of IPV is that women may systematically underreport its incidence (Kishor and Johnson 2004). The DHS surveys attempt to minimize this through methods of women selection, interviewer training, and interview technique. Specifically, only one eligible woman per household is selected for the domestic violence module so as to reduce the likelihood that others in the household are aware of the nature of the questions. Women are asked the questions only toward the end of the interview so that a rapport has been built up between interviewer and respondent before the questions are posed; questions on IPV are only asked if absolute privacy is ensured, and translators are avoided to ensure privacy. Finally, interviewers are provided with extensive training regarding the appropriate way to ask questions of such a sensitive nature.¹⁵

Another possible concern is that reporting behavior changes endogenously with male vs. female empowerment. It seems plausible that secular (permanent) changes in relative unemployment rates will empower or disempower women to report violence. However, it is less plausible that reporting would change in response to transitory deviations from trend. This concern is also mitigated by the fact that reporting in the DHS is not observable by husbands, due to measures taken by the DHS surveyors to ensure privacy and confidentiality, described above.¹⁶Anderberg et al. (2016) use data from a crime survey that, in principle, has the same issues as the data used in this study. Other studies have used more institutionalized data, which have different limitations. For instance, Aizer (2010) uses hospitalization data, but only severe cases of IPV are hospitalized. Mani et al. (2012) use police reports, but many women are reluctant to report IPV to the police for fear that their husbands will either exercise backlash or be arrested and taken away (e.g., Iyengar 2009; Amaral et al. 2019).

The estimation sample includes 31 and 26 countries, respectively, for which physical and sexual violence data from the DHS are available for 2005–2016 (see table S1.2).¹⁷ Estimates are reported for each of physical and sexual violence and their sum. The study does not use emotional abuse as it is a more subjective measure of abuse. There is substantial variation in the incidence of physical and sexual violence across countries; see figs. 1(a) and (b).¹⁸

Unemployment Rate Shocks

Data on male and female unemployment rates are obtained from the World Development Indicators (WDI), sourced from the ILOSTAT database.¹⁹ Although violence measures are only available for 2005–2016, the study uses a longer time series going back to 1991 to model the trend in unemployment rates and, thereby, to extract the cyclical component of unemployment using a Hodrick-Prescott filter (Hodrick and Prescott 1997).²⁰ The study also shows results with an alternative measure, the annual change in the logarithm of the unemployment rate.

Figure S1.1(a) shows a plot of the cyclical male unemployment vs. cyclical female unemployment in the sample with a 45° line imposed on top. This shows that the unemployment shocks are positively correlated, although there is variation around the 45° line. Figure S1.1(b) displays the pooled (across countries) mean of cyclical and log-differenced male and female unemployment over time for the country-years in our sample. Although shocks to male and female unemployment are positively correlated (fig. S1.1(a)),²¹ shocks to female unemployment are larger, and there is considerable variation in the relative size of each over time, as shown by the ratio and difference between the male and female cyclical unemployment (figs. S1.1(c) and (d)).

Figure S1.2(a) and (b) plot the unconditional association between country-year cyclical male and female unemployment and spousal physical violence rates. At the aggregate level, no clear pattern emerges from the data, particularly for female unemployment, though this unconditional association does not account for country fixed effects, which the regression analysis shows it is important to account for (section 4).

3. Methodology

Baseline Specification

The dependent variable, |$IP{V_{ij\,t}}\ $|is an indicator for whether a woman |${i}$| in country |${j}$| in interview year |${t}$| experienced intimate partner violence in the last twelve months. The variables of interest are |$\ln {{{U}}^{{f}}}_{{{j\,t}} - 1}$| and |$\ln {{{U}}^{{m}}}_{{{j\,t}} - 1}$|⁠, which are detrended log female and male unemployment in country |${j}$| in the previous year, respectively.²² In a robustness check, the study investigates replacing the detrended rates with the first-difference of the rate.

The control variables |${{{X}}_{{{ij\,t}}}}$| in equation (1) include the education of the woman and her partner, her age, and an indicator for whether she resides in an urban location. For the sample for which it is available, religion is also controlled for.²³ Country (⁠|${{\rm{\gamma }}_{{j}}}$|⁠) and year (⁠|${{\rm{\gamma }}_{{t}}}$|⁠) fixed effects are included to purge country-level unobservables and common shocks respectively. The study does not include country-specific trends in the main specification since unemployment is already detrended. However, the study checks robustness of the results to the inclusion of country-specific trends. Standard errors are robust to arbitrary forms of heteroscedasticity and are clustered at the country level. The study estimates linear probability models using ordinary least squares (OLS).

Heterogeneity by Gender Equality in Access to Divorce

The study investigates whether the observed association differs between countries in which women face more legal, financial, customary, or religious barriers in access to divorce than men. It uses the OECD Development Centre's Social Institutions Gender Index (SIGI), produced in 2019, which contains a measure of this. The study estimates the main specifications for subsamples defined by whether or not men and women have the same rights to initiate and finalize divorce (see table S1.1 for details of these samples, as well as comparison with the United Kingdom and United States as the study referred to studies of these countries earlier).^24,25

4. Results

Baseline Specification

The study shows estimates of equation (1) for each indicator of IPV, with controls sequentially added (table 1). The study first presents the unconditional correlation, which is negative for male unemployment and insignificantly small for female unemployment, mirroring the association observed in the raw data in fig. S1.3. The estimates are not sensitive to inclusion of year fixed effects. However, they are sensitive to inclusion of country fixed effects, consistent with time-invariant country-level characteristics being correlated with both IPV and unemployment rates. Once country fixed effects are in, the estimates are not sensitive to covariates.

In the preferred specification, conditional on country and year effects and covariates, an increase in male unemployment rates, holding female unemployment constant, is associated with increases in the incidence of physical violence. In contrast, an increase in female unemployment rates, holding male unemployment constant, is associated with reductions in the incidence of physical violence (column (4) of panel A, table 1). The coefficients for sexual violence are of the same sign but are not statistically significant once the study includes all controls (panel B, table 1). Results for physical and sexual violence (panel C, table 1) are driven by physical violence. An F-test of equality comfortably rejects the null that the coefficients on |$\ln {U^f}\!_{j\,t - 1}$| and |$\ln {U^m}\!_{j\,t - 1}$| are equal.²⁶ There is no robust statistically significant association between the total (male plus female) unemployment rate and IPV (table S1.3), a finding also shown in Anderberg et al. (2016).²⁷

A potential concern is that the estimates for male and female unemployment are driven by multicollinearity. However, the precision of our estimates speaks against multicollinearity.²⁸ In order for the study to mistake the sign on the coefficients of interest, the standard errors would have to be large enough to encompass the “true” effect with the opposite sign. In this setting this is not the case. Still, to investigate this further, the study estimates an alternative specification that includes the total (male plus female) unemployment rate and the ratio of the female to the male unemployment rate. The study finds that it is the ratio rather than common shocks that influence IPV (see section 5 below).

Holding female unemployment rates constant, a rise in male unemployment relative to trend by 1 percent is associated with an increase in the probability that a woman is a victim of physical violence by 0.50 percentage points, or an increase of 50 cases per 10,000 (table 1, panel A, column (4)). This translates to 2.75 percent of the mean prevalence rate of physical violence in the sample. An upswing in female unemployment from trend of 1 percent is associated with the risks of physical violence decreasing by 0.52 percentage points, or a decrease of 52 cases per 10,000 (table 1, panel A, column (4)). This translates to 2.86 percent of the mean prevalence rate of physical violence in the sample. The study find no statistically significant effects for sexual violence.^29,30

The finding that men react adversely to improvements in women's employment prospects conditional upon their own is consistent with models of male-backlash (Macmillan and Gartner 1999; Akerlof and Kranton 2000). When men feel traditional gender roles (male breadwinner) being threatened through elevation of women's relative status, they react negatively, attempting to reassert their authority through violence or other means. Evidence consistent with this has been found in other domains, in studies not concerned with domestic violence (Schuler et al. 1996; Atkinson, Greenstein, and Lang 2005; Mani 2011; Gagliarducci and Paserman 2012; Gangadharan et al. 2016).

The study now considers how the identified effect sizes compare with previous studies. The results for male and female unemployment are very similar in magnitude to those found by Tur-Prats (2017), who finds that a 1 percent increase in female (male) unemployment in Spain is associated with a decrease (increase) in risk of experiencing violence by 0.56 (0.37) percentage points, among provinces in which local historical gender identity norms prescribed men as main contributors to the household income. The effects estimates in this study are larger and, for female employment, of opposite sign to those reported by Anderberg et al. (2016) for the United Kingdom, who find that a 1 percentage point increase in female unemployment (holding male unemployment constant) is associated with an increase in the risk of experiencing IPV of 0.097 percentage points. Like this study they find that male unemployment rates have an effect of similar magnitude but opposite-sign, a 1 ppt increase leading to a decrease in IPV of 0.090 ppt.³¹ As discussed in the Introduction, they motivate their results with a model in which, when women have improved outside options (higher employment prospects), and the possibility of dissolution of the marriage union, men have an incentive to tame any tendency towards violence.³² Below, the study considers whether the observed associations differ between countries in which women can access divorce similarly to men, and countries in which they cannot.

The study also compares its estimates with estimates from studies of domestic violence that investigate other causes. For instance, it is estimated that availability of alcohol raises intimate partner violence by 5 percentage points in India (Luca, Owens and Sharma 2019), that public transfers (Mexico's Opportunidades program) lower incidence of IPV by 8.2 percentage points (Bobonis, González-Brenes, and Castro 2013), and that a one standard deviation in civil conflict intensity in a respondent's place of residence raises physical IPV by 5.07 percentage points in Rwanda (La Mattina 2017).

Heterogeneity by an Indicator of Gender Equality in Access to Divorce

The estimates show a striking separation, showing that the associations observed in table 1 are driven entirely by the sample in which women do not have equal access to divorce. For this sample, the estimates are remarkably similar to those in table 1: A rise in male unemployment relative to trend of one percent is associated with an increase in the probability that a woman is a victim of physical violence of 0.56 percentage points, or an increase of 56 cases per 10,000 (table 2, panel A, column (4)). An upswing in female unemployment from trend of 1 percent is associated with the risks of physical violence decreasing by 0.52 percentage points, or a decrease of 52 cases per 10,000 (table 2, panel A, column (4)). In contrast, in countries in which women have equal access to divorce (such as the United States and the United Kingdom), the study finds the opposite signed effects. Results for these countries align with those in Anderberg et al. (2016) for the United Kingdom.

5. Robustness Checks

Here, the study discusses robustness of its results to the inclusion of country-specific trends, alternate specifications in which it replaces the cyclical component of the logarithm of the two gender-specific unemployment rates with the first difference in the logarithms of these rates, and a specification that includes the total unemployment rate alongside the ratio of male and female unemployment rather than the two rates independently. The study also considers robustness of its results to sample composition, and alternative measurements of IPV.

The results point in the same direction (see table 4). Increases in male unemployment are associated with increased physical violence against women and increases in female unemployment with decreases.

The results, in table 5, suggest no statistically significant association between total cyclical unemployment and IPV, for which the study finds a very small estimated coefficient close to zero. However, an increase in the ratio of the male to the female unemployment rate of 1 percent is associated with a rise in the risk of physical violence of 0.50 percentage points.

The study checked whether sample composition drives the results in two ways. Since the preferred specification in table 1 (column (5)) identifies the relationship from the 21 countries for which the study has multiple years of data, it re-estimates equation (1) on the subsample of countries for which it observes women in at least two years. The results are almost identical (table S1.4). Second, since 23.3 percent of the sample of women are Indian and 20.4 percent Colombian, one concern might be that these countries are driving the observed effects. In fact, the study finds this is not the case. Figures 2(a), (b), and S1.4, generalize this, showing the estimated coefficients when the study drops one country at a time from the sample, and re-estimates. Overall the estimates are robust to changes in sample composition.

The main specification measures IPV as dummy variables, taking the value of 1 if the woman has ever faced i) physical, ii) sexual, or iii) any other form of violence from her partner. As an alternative, the study aggregates information from the underlying questions on specific acts of IPV into summary indices, since this aggregation can improve statistical power to detect effects that go in the same direction within a domain (Kling, Liebman, and Katz 2007). The study first converts answers to individual physical violence and sexual violence questions to z-scores by subtracting the country-specific mean and dividing by the country-specific standard deviation, for each of the individual questions on physical and sexual violence. The study then averages over these z-scores to create an index for i) physical violence and ii) sexual violence, as in Erten and Keskin (2018). Finally, it creates an index for iii) any violence, which is the arithmetic mean of the physical and sexual violence indices. Results in table S1.5 show that the results are robust to using indices of violence, and gain statistical significance when considering sexual violence (panel B), which now becomes statistically significant. Overall, the results are qualitatively similar and confirm the main analysis.

Finally, the study investigated the association of domestic violence with the (potentially endogenous) individual unemployment status of the woman and her partner, using questions in the DHS that ask whether the individual worked in the last 12 months. This acts as a consistency check on the main analysis. A caveat is that male unemployment is measured poorly in the DHS data—it is collected in only 18 of our 31 countries,³³ and even where it is collected, it is missing in around 67 percent of cases. Still, the pattern of results for individual unemployment mirrors the pattern for unemployment rates (table S1.6). Holding constant the unemployment status of their spouse, female unemployment in the last 12 months is associated with lower incidence of spousal violence. Male (spousal) unemployment is associated with a higher incidence of violence, although this is not statistically significant in every specification.

6. Discussion and Conclusion

The literature has considered alternative explanations for why men perpetrate violence against women partners. Among these are that men gain self-esteem or an enhanced sense of control from committing violence (Farmer and Tiefenthaler 1997); that they have strategic motivations, such as to use violence to extract resources from the woman or her family (Bloch and Rao 2002); and that violence occurs almost inadvertently in response to emotional cues (Card and Dahl 2011). Other studies have highlighted psychological drivers of abuse such as a history of childhood trauma, personality and relationship dysfunctionality (Heise and Kotsadam 2015), or early life exposure to domestic violence (Pollak 2004). Finally, there are studies showing that regional variation in IPV today reflects cultural factors rooted in historical customs (Tur-Prats 2015; Alesina, Brioschi, and Ferrara 2016).

This paper used comparable and representative repeated cross-sections of survey data from up to 31 countries containing women's reports of violence committed against them in the preceding year. It identified a systematic contemporaneous association of unemployment shocks with interpersonal violence. The study finds that changes in male and female unemployment rates have opposing association with IPV; these associations are large, at between 2.75 percent and 2.86 percent of the mean IPV prevalence rates in the sample. However, they are smaller than the estimates obtained by studies on the impact of alcohol on IPV (Luca, Owens, and Sharma 2019). Interpersonal violence is higher when men are more likely to be unemployed, and, holding constant male unemployment rates, it is higher if women face improved employment probabilities.

These findings contrast sharply with recent results for the United States and the United Kingdom (Aizer 2010; Anderberg et al. 2016) where IPV has been seen to be decreasing in the gender wage gap and in increased employment rates of women respectively. These are countries in which women's labor force participation has risen considerably in past decades and stabilized, weakening the male breadwinner norm, and in which women have much more freedom to exit partnerships. When the study separates the sample into those countries where men and women have equal access to divorce and those where women's access is lower, it finds that the results for the former are similar to those obtained by Anderberg et al. (2016) and Aizer (2010). In a majority of developing countries, however, patriarchal norms are much stronger, inequality in access to divorce persists, and women's employment is still on the rise, creating a potential clash between economic changes and norms, which may increase the probability of violence.

In addition to the income effects of male unemployment and female employment, there may also be psychological responses driven by social norms. The finding that increases in male unemployment rates lead to increased violence against women is consistent with the stresses of financial insecurity since unemployment of men challenges income security of the family, and previous research shows that cash transfers reduce IPV (see, e.g., Hidrobo, Peterman, and Heise 2016). It is also consistent with psychic costs of unemployment, this being larger for men who grow up with the expectation that they will be the providers (Tur-Prats 2017). However the finding that women are more likely to be subject to violence from a partner when employment prospects for women improve is almost certainly a psychic response, as established in previous research on backlash (since improved employment chances for women reduce financial stress, the study can reject that the income channel is at play for this result).³⁴ These findings also reject the “exposure reduction” model, which predicts increasing violence in response to both male and female unemployment, explained by unemployment increasing time spent together, which is assumed to increase the potential for conflict (Dugan, Nagin, and Rosenfeld 1999; Chin 2012).

While the evidence in this paper is descriptive, the estimated conditional correlations suggest that the standard bargaining model, which emphasizes how the power balance within the household is sensitive to outside options, may be of more limited empirical significance in poorer countries where the outside option is not readily exercised because of explicit (legal) and implicit (social) constraints. In her seminal analysis of IPV in the United States, Aizer (2010) challenges the backlash hypothesis as being problematic because it “ignores the individual rationality constraints faced by women in abusive relationships . . . as their income increases, women are more likely to end the partnership if transfers decline and abuse continues.” The evidence is that in many developing countries, women do not have the financial means or the social support to end partnerships. Indeed, a stylized fact concerning IPV on a global scale is that it tends to repeat within a couple, suggesting that across the world, women do not readily leave a relationship once subject to violence (Davis and Taylor 1997; Woodhouse and Dempsey 2016). However the perception (on the part of both men and women) that they can may still be effective.

The results of this study are topical given strong global trends in married women's labor force participation in many parts of the world. In Latin America, many countries, including Mexico and Brazil, have witnessed large increases (ILO 2016). Although the large increases in married women's work participation in richer countries occurred earlier, there is contemporary business cycle variation in the relative participation rates of men and women. In particular, the recent recession has hit men harder than women, narrowing the gender gap. There is a similar tendency in poorer countries, driven by subsistence targets strengthening the added worker effect. In other words, women who may otherwise not work tend to take work in recessions in order to make up for the decline in male income (Bhalotra and Umaña-Aponte 2015).

A recent UN publication outlining a framework to reduce violence against women suggests a range of potential approaches, including the empowerment of women and the changing of social norms to foster mutual respect between men and women (UN Women 2015b). These results show that simply increasing employment opportunities for women, as done by several microcredit programs in developing countries, may backfire. Indeed, the literature shows that women often draw smaller profits from microenterprise than men, and one explanation for this has been the existence of inefficient (noncooperative) models of the household (e.g., De Mel, McKenzie, and Woodruff 2009). This has not been previously considered but the results of this study suggest that adverse male reactions to loans targeting women may play a role.³⁵ Future work should look more carefully at whether implementing women's rights across multiple domains including property rights, custodial rights, and divorce may better protect against IPV. Community empowerment approaches that attempt to change social norms may generate sustained reductions in IPV (More et al. 2017).

Footnotes

Notes

Samantha Rawlings (corresponding author) is a lecturer at the University of Reading, Reading, United Kingdom; her email address is [email protected]. Sonia Bhalotra is a professor at the University of Essex, Colchester, United Kingdom; her email address is [email protected]. Uma Kambhampati is a professor at the University of Reading, Reading, United Kingdom; her email address is [email protected]. Zahra Siddique is a Senior Lecturer at the University of Bristol, Bristol, United Kingdom; her email address is [email protected]. The authors thank the editor, Eric Edmonds, for his helpful comments on the paper. A supplementary online appendix is available with this article at The World Bank Economic Review website.

References