The Effects of Real Exchange Rate Fluctuations on the Gender Wage Gap and Domestic Violence in Uruguay

Munyo, Ignacio; Rossi, Martín Antonio Working Paper The Effects of Real Exchange Rate Fluctuations on the Gender Wage Gap and Domestic Violence in Uruguay IDB Working Paper Series, No. IDB-WP-618 Provided in Cooperation with: Inter-American Development Bank (IDB), Washington, DC Suggested Citation: Munyo, Ignacio; Rossi, Martín Antonio (2015) : The Effects of Real Exchange Rate Fluctuations on the Gender Wage Gap and Domestic Violence in Uruguay, IDB Working Paper Series, No. IDB-WP-618, Inter-American Development Bank (IDB), Washington, DC, https://doi.org/10.18235/0000143 This Version is available at: https://hdl.handle.net/10419/146431 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Rossi IDB WORKING PAPER SERIES Nº IDB-WP-618 August 2015 Institutions for Development Sector Inter-American Development Bank August 2015 The Effects of Real Exchange Rate Fluctuations on the Gender Wage Gap and Domestic Violence in Uruguay Ignacio Munyo* Martín A. Rossi** *Universidad de Montevideo **Universidad de San Andrés Cataloging-in-Publication data provided by the Inter-American Development Bank Felipe Herrera Library Munyo, Ignacio. The effects of real exchange rate fluctuations on the gender wage gap and domestic violence in Uruguay / Ignacio Munyo, Martín A. Rossi. p. cm. — (IDB Working Paper Series ; 618) Includes bibliographic references. 1. Foreign exchange rates—Uruguay. 2. Pay equity—Uruguay. 3. Family violence—Uruguay. 4. Sex discrimination—Uruguay. I. Rossi, Martín A. II. Inter-American Development Bank. Institutional Capacity of State Division. III. Title. IV. Series. 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The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the Inter-American Development Bank, its Board of Directors, or the countries they represent. http://www.iadb.org 2015 Abstract* In this paper, we bring to light the experiences resulting from the significant depreciation of the Uruguayan real exchange rate between 2002 and 2003, followed by an equally considerable appreciation between 2004 and 2010. We explore the link between these fluctuations and the incidence of domestic violence taking place in Uruguay. The real exchange rate is a measure of the relative price between tradable and nontradable goods. While men are traditionally employed in tradable industries, such as manufacturing, women are more likely to work in nontradable industries, such as the service sector. A change in the real exchange rate, therefore, can affect the potential wages of men differently from those of women. In line with the models that represent household bargaining, an increase in the real exchange rate can generate an increase in the bargaining power of men relative to that of women within the household. We present evidence that it raises the frequency of domestic violence. This holds true in rich and poor areas of the city. JEL Code: K42 Keywords: Real exchange rate, gender wage gap, domestic violence, assault !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! *!Ignacio Munyo, [email protected]; Martín Rossi, [email protected]. Appreciation goes to Gerardo Licandro, Rodrigo Lluberas, Carlos Scartascini, and the participants at various seminars and conferences for their useful comments and suggestions. Acknowledgement is given to Mauricio Echeverría for the excellent research assistance he has provided towards this paper.! 2! ! 1. Introduction Domestic violence is a common and widespread issue. Out of every three women in the world, one has suffered violence from a partner at some time in her life (WHO, 2013). The incidence is more frequent in developing countries. A report, based on data from the Demographic and Health Surveys in nine developing countries (Cambodia, Colombia, Dominican Republic, Egypt, Haiti, India, Nicaragua, Peru, and Zambia), indicates that the percentage of women who have experienced violence from an intimate partner ranged between 18 percent in Cambodia and 48 percent in Zambia (Kishor and Johnson, 2004). In this paper, we explore the causes of domestic violence, using data from Uruguay. A recent survey from Uruguay’s Ministry of Public Health reveals that one out of four women falls victim to domestic violence. The survey also indicates that the incidence of domestic violence is higher for those women with low educational attainment. In this study, we identify the effects of Uruguay’s major depreciation of the real exchange rate between 2002 and 2003.1 We include an examination of the consequences of an equally significant appreciation of the real exchange rate between 2004 and 2010. As this is a measure of the relative price between tradable and nontradable goods, the fact that men are traditionally employed in tradable industries (e.g., manufacturing) and women in nontradable industries (e.g., services) will be taken into account. We examine the exogenous variations in the gender wage gap due to these fluctuations to estimate the impact that better alternative options may have on women with regard to domestic violence. By using the variables in the proportion of women visá-vis men in the tradable and nontradable sectors across the jurisdictions of Montevideo, Uruguay’s capital (with a population of 1.5 million), we find that reduction in potential wages for women relative to men leads to increased incidences of domestic violence. This result holds true in not only the poor jurisdictions of Montevideo, but also in the rich areas. There are two alternative theories on which the debate continues and to which this study contributes. On the one hand, socio-cultural models predict that violence against !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 1 Due to the lack of international reserves to sustain the value of the currency in July 2002, the Central Bank of Uruguay was forced to suddenly interrupt the fixed exchange rate regime (crawling peg). 3! ! women increases as their wages increase, mainly because men perceive that their traditional gender role is threatened: “when she brings home the bacon” (Macmillan and Gartner, 1999). On the other hand, models of household bargaining estimate that an increase in a woman’s relative potential wage will raise her bargaining power by providing her with better options (Farmer and Tiefenthaler, 1997; Aizer, 2010). Given that it is not the actual wage but rather the potential wage that determines another alternative, improving the relative labor market conditions for women will help to decrease such violence, especially in those households where the woman does not work outside the home (Pollak, 2005). The opposite holds true; that is, the deterioration in women’s potential wages relative to men’s will increase domestic violence. Most empirical studies (Gelles, 1976; Tauchen, Witte, and Long, 1991; Farmer and Tiefenthaler, 1997; Bowlus and Seitz, 2006;) have methodological shortcomings. They either have problems with omitted variables associated with women’s wages (e.g., education), explaining the negative relationship with violence, or have problems with the reverse causality given by the fact that domestic violence may reduce woman’s productivity and earnings. A notable exception is Aizer (2010) who presents a household bargaining model that incorporates violence and analyzes the impact of the gender wage gap as a function of local demand for female and male labor. She provides empirical support, in the case of the United States, for a causal relationship between relative labor market conditions for women and female hospitalization as a result of assault. Her main finding has been that a decrease in the wage gap between men and women can reduce violence against women. This study expands upon these results by considering not only the serious physical but also the nonphysical abuse against women. In fact, according to a recent survey by the National Bureau of Statistics (INE, 2013), a third of the females who were victims of domestic violence also had suffered from physical force and two thirds had experienced psychological aggression.2 The findings presented in this paper, within the wider definition of domestic violence, are consistent with the household bargaining model. !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 2 Among those victims of physical domestic violence, nearly half experience sexual aggression. 4! ! 2. Empirical Strategy Our estimates of domestic violence in Uruguay represent a period when the potential gender wage gap suffered as a result of significant exchange rate variations. Specifically, these variations⎯as a measure of the relative price between tradable goods (male-work intensive) and nontradable goods (female-work intensive)⎯will be examined. This approach accounts for the theory that potential wages⎯not actual⎯contribute to domestic violence. Uruguayan Law defines domestic violence in a similar way to that of the U.S. Department of Justice. This paper, therefore, will consider domestic violence as a pattern of abusive behavior in a relationship, used by one partner to gain or maintain power and control over another. Domestic violence can be physical, sexual, emotional, economic, or psychological, in action and in threat, borne by a partner in the home. There are various definitions of real exchange rate in the literature (Hinkle and Montiel, 1999). First, real exchange rate can be defined as the relationship between domestic and external prices (trade-weighted multilateral), expressed in the same currency (RXR1 = (E.P*)/P, where E is the nominal exchange rate measured in domestic currency per foreign currency; P* is the level of external prices; and P is the level of domestic prices). More importantly⎯for the purpose of this paper⎯real exchange rate can also be equivalent to a price ratio of different categories of goods within the domestic economy: tradable goods and services and nontradable goods and services. Tradable goods and services are subject to international trade, in which case arbitrage can determine whether or not the domestic price is equal to the international price. This does not hold true for nontradable goods and services, however, where the price must be adjusted to close the excess of demand or supply in the domestic market. The real exchange rate, therefore, is alternatively defined as follows: RXR2 = PT/PN, where PT refers to the tradable price and PN for the nontradable price. It is straightforward to show that both definitions, RXR1 and RXR2, are closely related.3 Therefore, changes in the multilateral trade-weighted real exchange rate come hand in hand with changes in the relative prices of tradable and nontradable goods. Data from Uruguay’s National Household Survey confirms that men’s wages, relative to women’s, move with the real exchange rate. In fact, between 2002 and 2004, !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 3 RXR1 = (E.P*)/P = (E.P*)/ (PT! .PN(1-!)) = E.P*/( PT) [PT / PN] (1-!) = D.RER2(1-!) where P is a geometric price average, D is the tradable goods price deviation with respect to the external prices expressed in the same currency, and ! is the share of the tradable goods in the domestic prices basket. 5! ! after a significant real exchange rate depreciation, the ratio of men’s wages to women’s in Montevideo increased from 1.52 to 1.58; and between 2004 and 2010, following a real exchange rate appreciation (similar in absolute values to the previous depreciation), the wage ratio dropped back to 1.52. Figure 1, in which data derives from the Ministry of the Interior and the Central Bank of Uruguay, presents a striking pattern of the time series of domestic violence and the trade-weighted multilateral real exchange rate in the period January 2002 to December 2010. Between May 2002 and January 2004, the trade-weighted multilateral real exchange rate depreciated by 58 percent while, at the same time, domestic violence increased by 154 percent. That is, in this period violence against women in Uruguay increased as their potential relative earnings decreased. Interestingly, the reverse is also true: between January 2004 and February 2009, the trade-weighted multilateral real exchange rate appreciated by 29 percent while, at the same time, domestic violence decreased by 61 percent. In this same time frame, the behavior of a similar type of crime, assault (abusive behavior against another person that excludes domestic violence), differed to that observed in domestic violence.4 Assaults increased by 40 percent between May 2002 and January 2004 and by 6 percent between January 2004 and February 2009. A basic regression analysis on monthly data (not reported) from January 2002 to December 2010 confirms these results.5 The coefficient of regressing domestic violence on the real exchange rate is positive and statistically significant at the 10-percent level. The coefficient is not statistically significant when assaults are considered in place of domestic violence. An analysis of this observed pattern was made by accessing the database of the Police Department of Montevideo (responsible for 24 police jurisdictions), which includes offenses that have been reported between 2002 and 2010.6 The data include the date of incidence and the jurisdiction where it occurred. Additionally, we gathered data from the National Household Survey, managed by the National Bureau of Statistics on an annual basis, in order to compute the labor participation of men and women in tradable and nontradable industries. Initially, we !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 4 Data include 19,276 cases in Montevideo of domestic violence (2 percent of total crime between 2002 and 2010) and 38,657 cases of assault (5 percent of total crime between 2020 and 2010). 5 The Augmented Dickey-Fuller Test (MacKinnon, 1996) rejects the null hypothesis that the time series on domestic violence and assault have a unit root. To deal with potential heteroskedasticity and serial correlation, Newey-West robust standard errors are computed with a lag truncation of four months. All results mentioned, but not shown, are available from the authors upon request. 6 There is no regular survey available on domestic violence victimization. 12! ! Table 1. Summary of Statistics Mean St. dev. Min. Max. Obs. Domestic violence 7.394 6.514 0 44 2,592 Assaults 14.879 9.683 0 56 2,592 Per capita income 7,706 4,133 2,298 22,527 216 Ratio of men to female Participation in tradable sectors 2.081 0.564 1 2.4 24 Multilateral exchange rate 121.593 15.079 91 150 108 13# # Table 2. Employment Rates in the Tradable Sectors Jurisdiction 2002 2003 2004 2005 2006 2007 2008 2009 2010 Men Women Men Women Men Women Men Women Men Women Men Women Men Women Men Women Men Women 1 13% 15% 7% 9% 10% 13% 12% 11% 11% 10% 15% 7% 18% 12% 9% 8% 11% 9% 2 16% 7% 9% 7% 13% 7% 12% 10% 12% 7% 17% 10% 13% 7% 11% 12% 12% 8% 3 12% 7% 14% 9% 15% 7% 14% 11% 14% 10% 14% 9% 13% 7% 13% 10% 12% 9% 4 14% 9% 12% 9% 15% 12% 17% 13% 15% 13% 18% 13% 15% 11% 12% 10% 14% 10% 5 14% 8% 12% 7% 13% 9% 15% 9% 13% 9% 15% 10% 12% 7% 14% 10% 12% 8% 6 19% 12% 16% 15% 18% 12% 16% 14% 19% 12% 18% 12% 19% 12% 17% 11% 18% 11% 7 17% 12% 21% 14% 18% 11% 17% 12% 20% 12% 18% 11% 21% 13% 17% 12% 21% 12% 8 20% 15% 19% 16% 21% 16% 21% 12% 21% 17% 21% 15% 25% 17% 22% 14% 22% 14% 9 14% 10% 14% 10% 12% 10% 15% 10% 14% 10% 15% 10% 14% 9% 12% 8% 12% 9% 10 18% 10% 12% 11% 15% 9% 14% 10% 13% 8% 16% 11% 13% 7% 12% 9% 13% 9% 11 15% 13% 15% 12% 15% 7% 16% 9% 15% 8% 14% 9% 16% 9% 16% 8% 14% 11% 12 16% 12% 17% 15% 21% 16% 14% 14% 17% 14% 16% 15% 15% 16% 19% 12% 18% 15% 13 15% 11% 15% 13% 19% 17% 15% 12% 17% 10% 19% 13% 18% 11% 18% 11% 16% 12% 14 15% 12% 17% 9% 20% 11% 18% 10% 18% 11% 17% 10% 17% 11% 17% 10% 18% 10% 15 18% 12% 16% 11% 13% 10% 12% 10% 15% 12% 16% 11% 14% 11% 13% 9% 15% 9% 16 19% 14% 19% 16% 19% 13% 22% 16% 21% 16% 21% 14% 20% 15% 21% 15% 20% 15% 17 19% 13% 25% 16% 20% 17% 25% 19% 20% 16% 23% 15% 25% 18% 25% 15% 22% 15% 18 18% 14% 23% 17% 22% 14% 23% 16% 23% 17% 21% 16% 24% 16% 23% 17% 22% 13% 19 24% 13% 23% 16% 27% 18% 20% 17% 24% 17% 24% 16% 24% 15% 26% 14% 23% 16% 20 25% 26% 32% 34% 39% 21% 33% 31% 32% 26% 34% 25% 36% 24% 39% 24% 37% 25% 21 24% 18% 29% 18% 26% 18% 27% 18% 25% 19% 27% 17% 28% 16% 26% 17% 23% 16% 22 35% 19% 31% 28% 48% 27% 38% 26% 33% 21% 41% 22% 40% 21% 35% 17% 33% 17% 23 22% 19% 33% 30% 32% 23% 26% 26% 27% 21% 27% 21% 30% 21% 31% 22% 29% 21% 14# # 24 19% 19% 26% 16% 21% 20% 20% 17% 25% 16% 23% 16% 24% 16% 24% 16% 23% 15% Max. 35% 26% 33% 34% 48% 27% 38% 31% 33% 26% 41% 25% 40% 24% 39% 24% 37% 25% Min. 12% 7% 7% 7% 10% 7% 12% 9% 11% 7% 14% 7% 12% 7% 9% 8% 11% 8% Mean 18% 13% 19% 15% 20% 14% 19% 15% 19% 14% 20% 14% 21% 13% 20% 13% 19% 13% St. Dev. 5% 4% 7% 7% 9% 5% 7% 6% 6% 5% 7% 4% 7% 5% 8% 4% 7% 4% T-test p=0,000 p=0,025 p=0,002 p=0,009 p=0,000 p=0,000 p=0,000 p=0,000 p=0,000 Notes: t-test refers to the usual difference of a means test. In the total sample period (2002-2010), 20 percent of men and 14 percent of women were employed in the tradable sector. The differences in the employment rate in the tradable sectors between men and women are statistically significant, according to the variances of the means t-test. 15# # Table 3. Main Results Domestic violence Domestic violence Domestic violence/population Domestic violence Domestic violence All jurisdictions Rich jurisdictions Poor jurisdictions All jurisdictions All jurisdictions All jurisdictions All jurisdictions (1) (2) (3) (4) (5) (6) (7) Ratio * RXR 0.0873 0.05000 0.1616 0.0813 0.0010 0.0982 0.0916 (0.0168) (0.0361) (0.0305) (0.0173) (0.0005) (0.0417) (0.0440) p=0.000 p=0.166 p=0.000 p=0.000 p=0.036 p=0.020 p=0.039 [0.0439] [0.0167] [0.0467] [0.0439] [0.0006] [0.0539] [0.0574] p=0.059 p=0.020 p=0.011 p=0.092 p=0.111 p=0.082 p=0.124 Per capita income 0.0002 0.0002 (0.0001) (0.0002) p=0.039 p=0.382 [0.0002] [0.0002] p=0.430 p=0.505 Observations 2592 864 864 2592 2592 216 216 Notes: RXR refers to real exchange rate. Ratio refers to the ratio of men to female participation in tradable sectors. A rich jurisdiction is one where the average per capita income is above the 66th percentile of the per capita income of the city in the first year of the sample. A poor jurisdiction is one where the average per capita income is below the 33rd percentile of the per capita income of the city in the first year of the sample. All models are estimated by OLS. Models (1) to (5) use monthly data and include month fixed effects and jurisdiction fixed effects. Model (6) and (7) use yearly data and include year fixed effects and jurisdiction fixed effects. Robust standard errors are in parentheses. Standard errors clustered at the jurisdiction level are in brackets; p refers to the p-value of each test. 16# # Table 4. False Experiments Assaults Assaults Assaults (1) (2) (3) Ratio * RXR 0.0218 0.0076 0.0545 (0.0219) (0.0502) (0.0521) p=0.320 p=0.880 p=0.296 [0.0409] [0.0406] [0.0504] p=0.599 p=0.854 p=0.290 Per capita income -0.0011 (0.0003) p=0.001 [0.0005] p=0.034 Observations 2592 216 216 Notes: RXR refers to real exchange rate. Ratio refers to the ratio of men to female participation in tradable sectors. All models are estimated by OLS. Models (1) and (2) use monthly data and include month fixed effects and jurisdiction fixed effects. Model (3) uses yearly data and includes year fixed effects and jurisdiction fixed effects. Robust standard errors are in parentheses. Standard errors clustered at the jurisdiction level are in brackets; p refers to the p-value of each test. 17# # Figure 1. Domestic Violence and the Real Exchange Rate 18# # Figure 2. Real Exchange Rate Fluctuations, Relative Participation in Tradable Sectors, and Variation in Domestic Violence