Gender and ethnic inequalities in LAC countries

Canelas, Carla; Salazar, Silvia Article Gender and ethnic inequalities in LAC countries IZA Journal of Labor & Development Provided in Cooperation with: IZA – Institute of Labor Economics Suggested Citation: Canelas, Carla; Salazar, Silvia (2014) : Gender and ethnic inequalities in LAC countries, IZA Journal of Labor & Development, ISSN 2193-9020, Springer, Heidelberg, Vol. 3, pp. 1-25, https://doi.org/10.1186/2193-9020-3-18 This Version is available at: https://hdl.handle.net/10419/152393 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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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Canelas and Salazar IZA Journal of Labor & Development ORIGINAL ARTICLE Open Access Gender and ethnic inequalities in LAC countries Carla Canelas*and Silvia Salazar *Correspondence: [email protected] Paris School of Economics, Université Paris 1, Centre d’Economie de la Sorbonne, 106-112 Bd de l’Hôpital, 75013 Paris, France Abstract This article examines the structure of gender and ethnic wage gaps and the distribution of both paid and unpaid work in LAC countries. Its main contribution is to expose the double discrimination endured by women in the region. Indeed, the results indicate that women are highly discriminated in the job market and undertake most of the domestic activities in the household, allocating in average 40 hours per week to paid market activities and another 40 hours to in-home unpaid activities. The indigenous population also suffers from discrimination, but the wage gap is mainly explained by the difference in endowments, highlighting their limited access to education and their concentration in rural areas. The wage quantile decomposition results suggest the presence of sticky floor effects for both women and indigenous workers. JEL codes: J22; J31; J71 Keywords: Inequality; Ethnicity; Gender; Time-use 1 Introduction Two important factors are generally associated with gender and ethnic discrimination in Latin America: the low level of human capital and the strength of social norms. The first one is usually captured by educational attainment and years of work experience. In Latin America, the average years of schooling is 8 which is relatively low compared to Europe and more advanced countries. Needless to say that ethnic minorities are the most disadvantaged in this respect. Concentrated mainly in rural areas their access to education and health services is precarious and limited. Moreover, occupational segregation is particularly high. Indigenous workers are mostly found in low-productivity activities either in the agricultural, manufacturing, and construction sectors or in domestic service. The strength of social norms is particularly evident in the strict gender division of labor in the region. In line with traditional gender roles, women are mainly responsible for domestic activities and for looking after children, even though their participation in the labor market has increased over time, and men are perceived as breadwinners working primarily in outside-home activities. These gender stereotypes are culturally acceptable in most Latin American countries and little has been done to change them. Women in the region face premarket discrimination and exclusion in the labor market and they are double burned taking most of the housework in the household. Ethnic and gender disparities have two main consequences in the job market. The first one is the existence of significant entry barriers to the formal job market and the second © Canelas and Salazar; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 2014, 3:18 http://www.izajold.com/content/3/1/18 2014 Canelas and Salazar IZA Journal of Labor & Development Page 2 of 15 one, is that even when these barriers are crossed, there is still a wage gap between the discriminated group and the non discriminated one. A priori, this wage differential could lead to a smaller labor force participation from the discriminated group, increasing the demand for domestic production on in-home activities. In this context, women may have a bigger incentive to stay at home and accomplish domestic tasks rather than participating in the labor market, especially when the wage differential is significant. But to what extend does the level of wages really influence the distribution of domestic activities within a couple? The literature on gender and ethnic inequality is enormous, but much of the research focuses on wage differences neglecting the importance of domestic labor and time use. In this article, we examine the gender and ethnic gaps in wages and in the allocation of time to paid and unpaid work in Bolivia, Ecuador, and Guatemala. We pay particular attention to the role of education in explaining and reducing the gap along the wage and time distributions. The low level of human capital in the region is an important factor that determines women’s expected social role in domestic activities and it certainly plays a significant part in the inequality of opportunities endured by ethnic minorities and women in these countries. Needless to say that human capital and social norms are highly correlated. Education, for instance, helps individuals changing existing norms by influencing their perceptions and behavior. In order to assess the importance and determinants of the wage gap between the discriminated group and those who are not, we use the standard Blinder-Oaxaca decomposition (BO decomposition, hereafter) and complete the analysis with a quantile decomposition method proposed by Firpo et al. (2009). In order to explain the determinants of weekly allocation of time between domestic and paid market activities, while taking into account the inter-dependance of decision-making process inside the household, we use seemingly unrelated regressions. The structure of the paper is as follows: Section 2 reviews the theoretical framework. Section 3 provides a literature review. Section 4 introduces the econometric methodology. Section 5 describes the data, and Section 6 presents the results and concludes. 2 Theoretical framework In a broader sense, discrimination is defined as the unjustified difference in treatment between two distinct groups of the population based on cultural or physical characteristics such as gender, age, race, religion, or political views. In the labor market it is usually measured in terms of wage differentials between workers, the degree of segregation in different types of employment or sectors, and labor force participation, see Cain (1987) and Altonji and Blank (1999). Neoclassical theory of discrimination is divided in two classes of models: competitive and collective models. In collective models, as its name indicates, groups act collectively against each other, while competitive models focus on individual behavior. Competitive models are further divided in taste-based models with complete information and statistical models of discrimination with imperfect information. The former one is the primary interest of this article since it is the model introduced by Becker (1957), which gives the theoretical framework for the well known and widely used BO decomposition. The main drawback of these models is that pre-market discrimination is not taken into account. Differences in endowments are certainly explained by the environment in which 2014, 3:18 http://www.izajold.com/content/3/1/18 Canelas and Salazar IZA Journal of Labor & Development Page 3 of 15 each individual evolves. For instance, immigrants families usually live in sectors where criminality rates are high, integration with country natives is limited, and education is of low quality. In this context, the probability that children from immigrated families attend to college may be significantly reduced. Therefore, in average, these children have a clear disadvantage compare to those who have had access to a good education and have grown up far from violence and criminality. Discrimination in the labor market is an open, pervasive, and persistent phenomenon as many of the empirical works have shown. But discrimination or disparities also exist inside the households. The gender differences in the allocation of time to housework and labor market activities is a recognized fact. Indeed, it is known that women spend more time in housework activities compared to men. It is more questionable why this is the case. In order to explain the differences in time allocation three main theories have been proposed: The time availability hypothesis, the relative resource hypothesis, and the gender hypothesis. The time availability hypothesis argues that time spend on domestic chores is related to the amount of time available for each family member, thus there is an inverse correlation between the hours spend in market labor activities and the hours spend in domestic task, see Hiller (1984) and Coverman (1985). The relative resources perspective suggests that the amount of hours spend on household chores depends on the bargaining power of each partner, so that the member of the couple with the bigger bargaining power imposes his own housework preference on the other one, see Brines (1994). The gender hypothesis explains that the amount of housework done by women is bigger than those of men simply because the society automatically links housework and gender. This perspective highlights that there is no a real trade off between labor market activities and housework, since all the housework is dictated to women by the social norm, see Bianchi et al. (2000). 2.1 A model of allocation of time Following Kooreman and Kapteyn (1987), the husband mand the wife fof a household h maximize the utility urepresented by the function: u=U(xm,xf,cm,cf,lm,lf),(1) subject to time and monetary constraints: lm+cm+hm=Tm,(2) lf+cf+hf=Tf,(3) p(xm+xf)=wmhm+wfhf+vh,(4) where xiis the consumption of market goods, cithe housework time, lithe leisure time, hithe labor market hours, withe net wage rates, pthe market price of goods xi,vhother non-labor income of the household, and Tifixed time endowments, with i∈{m,f}. Combining the two constrains, under the assumption of perfect substitutability of time between activities, yields the full income constraint: p(xm+xf)+wm(lm+cm)+wf(lf+cf)=wmTm+wfTf+vh≡Y,(5) 2014, 3:18 http://www.izajold.com/content/3/1/18 Canelas and Salazar IZA Journal of Labor & Development Page 4 of 15 Solving this maximization problem yields solutions for xi,ci,li,hi(endogenous variables of the model) as function of the exogenous variables wi,Ti,vh,andZh. qk=fk(wm,wf,Tm,Tf,vh,Zh),(6) with qk⊆(xm,xf,cm,cf,lm,lf,hm,hf),(7) where Zhis the other exogenous variables affecting the utility, such as household’s demographic characteristics. 3 Literature review Empirical evidence on wage disparities is extensive. Results are well established, women and gender minorities are discriminated in the labor market with different degrees across countries. Among the works that use Latin America data we find those by Tenjo et al. (2005), who analyze the evolution of the gender gap in six LAC countries and find evidence of statistical discrimination. Ñopo (2012) finds that gender and ethnic earnings gaps persist in the region, even though the situation of these groups in the labor market and the society in general has improved over time. Finally, Popli (2013) uses a nonparametric-distributional approach to study gender wage differentials and finds evidence of a reduction of labor market discrimination against women due to a diminishing discrimination at the lower tail of the wage distribution. Regarding the differences in the allocation of time to domestic and market activities, it has been shown that there is an important inequality in the time spend in housework activities between men and women, see Wales and Woodland (1977), Sousa-Poza et al. (2001), and Álvarez and Miles (2003). Indeed, women tend to spend more time doing household chores compared to men and men spend more time in paid work activities. Articles studying the determinants of the allocation of time in Latin American countries are limited, probably because of the scarcity of Time Use surveys in the region. Some of the few works found in the literature are those of Newman (2002) who uses survey data from Ecuador to examine the effects of women’s employment on the allocation of paid and unpaid labor within the household. She finds that women’s labor market opportunities have no effect on women’s total time in paid labor but they increase men’s time in unpaid labor, which in turn reflects women’s increased bargaining power at home. Medeiros et al. (2007) analyze paid and unpaid work-time inequalities among Bolivian urban adults. They find that gender is an important variable to explain how much paid and unpaid work is done by individuals, but not so important to explain why some people have a higher total workload than others. 4 Methodology 4.1 The Blinder-Oaxaca decomposition The standard approach for the study of earnings differentials was introduced in the economics literature by Blinder (1973) and Oaxaca (1973). From the estimation of wage equations this method allows us to decompose the mean wage difference between two groups into three effects: the “Endowments effect”, that amounts to the part of the differential due to group differences in the vector of characteristics; the “Coefficient effect”, 2014, 3:18 http://www.izajold.com/content/3/1/18 Canelas and Salazar IZA Journal of Labor & Development Page 5 of 15 that corresponds to the differences in the coefficients; and the “Interaction effect”, that accounts for the simultaneous existence of differences in endowments and coefficients. In the original BO decomposition, one has to choose the reference group for the counterfactual. For instance, in assessing the potential wage of women in absence of discrimination, one usually assumes that the male wage structure provides a good counterfactual, but this is not always the case. Reimers (1983), Neumark (1988) and Oaxaca and Ransom (1994) suggest different alternatives for a new wage structure that can be used instead. One popular application is to calculate β∗(the estimated non-discriminatory earning structure) from a pooled regression over both groups, with the inclusion of a dummy variable as group indicator in order to avoid the transfer of parts of the unexplained component into the explained one, see Jann (2008). This is the procedure used in this article for the Oaxaca decomposition as well as for the Firpo et al. (2009) decomposition. Concerning the wage equation, the usual regression model is based on the “human capital specification”, but recent approaches additionally control for occupation and industry in order to reduce the error term and to take into account occupational segregation. As pointed out by Blau and Kahn (2000) any approach that relies on a statistical residual is open to questions regarding the inclusion of all necessary independent variables in the regression. Unobserved factors such as ability can overstate the size of the unexplained part of the wage gap. On the other hand, the inclusion of economic sectors and worker occupation may understate the part attributed to discrimination if occupational segregation is the result of discriminatory practices in the labor market. 4.2 The RIF regression Decomposition methods for parameters other than the mean face econometric complications since the law of iterated expectations does not hold for them. Various methods to overcome this problem have been proposed. Among them, the most popular are the residual imputation method by Juhn et al. (1993), the conditional quantile regression method by Mata and Machado (2005) and Melly (2005), and the RIF regression method by Firpo et al. (2009). In this article we use the latter one since it allows us to compute the effect of each covariate on the unconditional wage distribution, and it is also less computational demanding than those proposed by Mata and Machado (2005) and Melly (2005). A detailed explanation for the method used here and for all the other decomposition methods cited above, can be found in Firpo et al. (2010). In the following we give a short overview of the RIF-regression method. Let Ybe the output variable, in our case wages, and υ(FY)the distributional statistic of interest, in our case quintiles. The influence function IF(y;υ) of υat the observed wage y is given by: IF(Y,Qτ)=τ−1{Y≤Qτ} fY(Qτ),(8) where τrepresents the quantile of interest, 1{·} is an indicator function expressing whether the outcome variable is smaller or equal to the quantile, and fY(·)is the density of the marginal distribution on Yevaluated at the population τ-quantile of the unconditional distribution of Y. 2014, 3:18 http://www.izajold.com/content/3/1/18 Canelas and Salazar IZA Journal of Labor & Development Page 6 of 15 Since the recentered influence function is defined as RIF(y;υ) =υ(FY)+IF(y;υ),for thequantilecaseitiswrittenas: RIF(Y,Qτ)=Qτ+τ−1{Y≤Qτ} fY(Qτ).(9) After computing the RIF, usually by kernel methods, it replaces the outcome variable in the regression over the covariates. The RIF regression is carried out in a standard OLS framework. Once this has been done, the estimated coefficients are used to perform a detailed decomposition in the same spirit of the classical Blinder-Oaxaca methodology. 4.3 Seemingly unrelated regressions Theoretical models suggest that both spouses’ decision of time allocation between housework hours and labor market activities are determined simultaneously. In order to take into account the inter-dependance of the decision-making process, we use seemingly unrelated regressions. The reduced equations based on the (Kooreman and Kapteyn 1987) model explained above, leads to the following estimation specification: hm=αwm+βwf+γjZmj +θkZhk +m, (10) cm=αwm+βwf+γjZmj +θkZhk +m, (11) hf=αwm+βwf+γjZfj +θkZhk +f, (12) cf=αwm+βwf+γjZfj +θkZhk +f, (13) where Zmand Zfincludes all the individual characteristics j∈{1, ...,n}that affect labor and domestic activities, Zhall the other household demographic characteristics k∈{1, ...,m},andiis the regression residual, with i∈{m,f}. A usual problem that we face with the above estimation, is the presence of zero observations. This is a common characteristic of time use data and there are two possible explanations: either the individual in question does not participate in domestic activities at all, or the individual usually participates but for some reason he/she did not do it during the recording period. Since one cannot differentiate one from the other, this fact needs to be taken into account during the estimation. Common procedures include the Tobit and the Heckman selection model. The choice of the model depends on the results of the normality and homoskedasticity tests, hypothesis that our results reject1. In this article we use the Heckman two stages procedure for men’s time allocation in domestic activities. Since the proportion of women that shows zero observations for housework activities correspond, in average, to 1% of each country sample, there is no need to perform this procedure for them. 4.4 Selectivity issues This article does not address selection into the job market when estimating wage differentials at quantile levels. The reasons are as follows: First, we are interested in studying wage disparities conditional on being employed. Second, selection bias correction in a quantile framework requires techniques that are less developed, with just few studies addressing 2014, 3:18 http://www.izajold.com/content/3/1/18 Canelas and Salazar IZA Journal of Labor & Development Page 7 of 15 the problem. These studies, in turn, rely on the validity of instruments and the correct identification of the intercept of the wage equation2. The second problem concerns the time equations. Since for the second part of the study, we use a sample of couples where both individuals work, it is easy to imagine that women who are working in the labor market, especially when their husbands are also working, are very positively selected. We correct this problem using the Heckman selection model for the equation corresponding to the hours allocated to paid market activities by women. The other two equations are performed by OLS, and the whole system is estimated as seemingly unrelated regressions. The errors are corrected using a standard bootstrap procedure with 1200 replications. 5Data The vast majority of indigenous people in Latin America lives in Bolivia, Ecuador, Guatemala, Mexico, and Peru. Altogether, the five countries, account for almost 90 per cent of the indigenous population in the region. Due to data limitations, we carry out the analysis using data from Bolivia, Ecuador, and Guatemala, but it would be ideal to do it for all of them. The analysis in this paper draws on individual level data from the Bolivian National Living Standards Survey (MECOVI ) 2001 conducted by the Bolivian National Institute of Statistics (INE), the Ecuadorian Survey of Employment and Unemployment (ENEMDU) 2007 conducted by the Ecuadorian National Institute of Statistics and Census (INEC), and the Guatemalan National Living Standards Survey (ENCOVI) 2000 conducted by the Guatemalan National Institute of Statistics (INE). For the three countries, individuals answered questions regarding ethnic background, income, and time use on domestic activities. Information on wages, transfers, and other non labor income was collected, as well as common socio-demographic characteristics such as level of education, age, gender, marital status, area of residence, etc. From the initial sample we selected working individuals aged between 20 and 70 years, living in nuclear families, either in couple or alone. Descriptive statistics of the final sample are shown in Table 1. Table 1 Descriptive statistics (whole sample) Bolivia Ecuador Guatemala Variables Mean Std. Dev Mean Std. Dev Mean Std. Dev Income per capita 889.29 (897.40) 240.23 (234.30) 7153.08 (7976) Household size 4.34 (2.06) 3.89 (1.70) 4.97 (2.13) Age 39.86 (11.77) 42.59 (11.77) 39.34 (11.65) Male 0.63 (0.48) 0.65 (0.47) 0.70 (0.46) Indigenous 0.63 (0.48) 0.07 (0.26) 0.35 (0.47) Urban households 0.53 (0.50) 0.60 (0.49) 0.54 (0.50) Primary education 0.55 (0.50) 0.52 (0.50) 0.75 (0.43) Secondary education 0.31 (0.46) 0.29 (0.45) 0.19 (0.39) Tertiary education 0.14 (0.34) 0.19 (0.39) 0.06 (0.23) Observations 5617 - 12046 - 4492 - Note.- Income data is shown in local currency, Peso Boliviano, American Dollar, Quetzales. Income: sum of wages/salaries, net income from self-employment, and other non labor income. 2014, 3:18 http://www.izajold.com/content/3/1/18 Canelas and Salazar IZA Journal of Labor & Development Page 8 of 15 The set of explanatory variables in the wage equations includes a constant, age, education (primary, secondary, and higher), occupational tenure, area of residence, region, social security, industry of employment constructed using the International Standard Industrial Classification of All Economic Activities (ISIC) published by UN, and occupation using the International Standard Classification of Occupations (ISCO) published by the ILO. Working individuals are defined as those reporting positive hours and earnings. Wages are computed using the labor income from the primary occupation. Earnings are reported in several frequencies (daily, weekly, biweekly, monthly, quarterly, semester, and annual). We standardize the data to a weekly frequency. Hourly wages are obtained by dividing wages by the number of hours worked. Indigenous people are identified using the “self-identification” variable available in the three surveys. Note however, that using the variable “spoken language at home” yields similar results. Table 2 shows labor market indicators for the whole sample and by subpopulations. For the second part of the study, following the theoretical model, the paper considers a restricted dataset consisting on couples where both individuals work. This allows us to specifically address the unequal distribution of domestic activities within Latin American two-earner couples, that is, to compare spouses in similar conditions. Moreover, one of the main objectives of the paper is to test whether or not the wage received by women acts as a bargaining tool for the decision process inside the household. From a policy perspective, if this is the case, improving women’s conditions on the labor market by reducing the wage gap can also have a positive equalizing effect, through the level of wages, in housework shares. So, in line with the first part of the study, we focus on labor and domestic inequalities conditional on being employed. Hence, our restricted sample consists of 651 working couples for Bolivia, 2,097 couples for Ecuador, and 363 couples for Guatemala. Table 2 Labor market indicators Total Ethnic origin Gender Indigenous Non-Indigenous Variables All Indigenous Non-Indig Male Female Male Female Male Female Bolivia Working hours 43.93 43.82 44.12 47.06 37.40 46.38 38.09 48.11 36.33 Hourly wage 5.94 5.12 7.33 5.80 6.23 5.01 5.37 7.21 7.56 Labor force 78.83 80.26 76.50 96.02 57.07 96.02 58.68 96.02 54.73 participation rate Ecuador Working hours 42.20 39.92 42.38 45.30 36.48 42.05 35.79 45.56 36.53 Hourly wage 1.38 0.93 1.42 1.43 1.30 0.97 0.84 1.47 1.34 Labor force 86.92 74.44 88.09 96.24 73.73 95.29 52.32 96.32 76.11 participation rate Guatemala Working hours 43.67 41.25 44.98 47.83 33.83 45.38 29.70 49.26 35.70 Hourly wage 7.24 5.48 8.198 7.29 7.11 5.65 5.01 8.25 8.07 Labor force 50.89 46.66 53.52 73.38 29.52 68.39 24.73 76.64 32.36 participation rate Notes.- Sample: individuals aged between 20 and 70 years living in nuclear families. Wages are shown in local currency, Peso Boliviano, American Dollar, Quetzales. Labor force participation rate: number of working individuals divided by the number of people in the sample. 2014, 3:18 http://www.izajold.com/content/3/1/18 Canelas and Salazar IZA Journal of Labor & Development Page 15 of 15 Competing interests IZA Journal of Labor & Development is committed to the IZA Guiding Principles of Research Integrity. The authors declare that they have observed these principles. Acknowledgments We are grateful to François Gardes, Philip Merrigan, and Christophe Starzec for their helpful comments on this paper. We also thank the participants at the Public Economic Theory Conference, Portugal, July 5-7, 2013, the IARIW-IBGE Conference on Income, Wealth, and Well-Being in Latin America, Brazil, September 11-14, 2013, and the seminar participants at the Paris School of Economics, at the University of Paris 1, and at the University Shiv Nadar, for valuable comments and suggestions. 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