Assessing the role of tax-benefit systems in reducing the gender income gap in Latin America

Deza, María Cecilia; Dondo, Mariana; Jara, H. Xavier; Rodriguez, David; Torres, Javier Working Paper Assessing the role of tax-benefit systems in reducing the gender income gap in Latin America IDB Working Paper Series, No. IDB-WP-1652 Provided in Cooperation with: Inter-American Development Bank (IDB), Washington, DC Suggested Citation: Deza, María Cecilia; Dondo, Mariana; Jara, H. Xavier; Rodriguez, David; Torres, Javier (2025) : Assessing the role of tax-benefit systems in reducing the gender income gap in Latin America, IDB Working Paper Series, No. IDB-WP-1652, Inter-American Development Bank (IDB), Washington, DC, https://doi.org/10.18235/0013356 This Version is available at: https://hdl.handle.net/10419/309190 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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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. https://creativecommons.org/licenses/by/3.0/igo/ A ssessing the Role of Tax-benefit S y stems in Reducing the Gender Income Gap in Latin America María Cecilia Deza Mariana Dondo H. Xavier Jara David Rodríguez Javier Torres WORKING PAPER No IDB-WP-1652 InterA merican Development Bank Gender and Diversity Division January 2025 * InterA merican Development Bank ** Universidad Nacional de Río Negro *** London School of Economics § Universidad Externado de Colombia §§ Universidad del Pacífico A ssessing the Role of Tax-benefit S y stems in Reducing the Gender Income Gap in Latin America María Cecilia Deza* Mariana Dondo** H. Xavier Jara*** David Rodríguez§ J avier Torres§§ Inter-American Development Bank Gender and Diversity Division January 2025 Cataloging-in-Publication data provided by the Inter-American Development Bank Felipe Herrera Library Assessing the role of tax-benefit systems in reducing the gender income gap in Latin America / María Cecilia Deza, Mariana Dondo, H. Xavier Jara, David Rodríguez, Javier Torres. p. cm. — (IDB Working Paper Series ; 1652) Includes bibliographic references. 1. Cash transactions-Latin America. 2. Income distribution-Latin America. 3. Taxation-Latin America. 4. Gender mainstreaming-Mexico. I. Deza, María Cecilia. II. Dondo, Mariana. III. Jara H., Xavier. IV. Rodríguez Guerrero, David. V. Torres, Javier. VI. Inter-American Development Bank. Gender and Diversity Division. VII. Series. IDB-WP-1652 http://www.iadb.org Copyright © 2025 Inter-American Development Bank ("IDB"). 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The opinions expressed in this work 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. 1 Abstract1 This paper aims to assess the extent to which cash transfers, direct taxes, and social contributions help to reduce gender income inequalities in seven Latin American countries: Argentina, Bolivia, Colombia, Ecuador, Mexico, Peru, and Uruguay. We apply microsimulation techniques to household survey data and allocate incomes within the household, assuming that each person retains the income they receive (e.g., earnings, benefits targeting mothers) and pays taxes and social insurance contributions on an individual basis according to each country’s rules. Then, we compare gender income ratios based on market (before taxes and benefits) and disposable (after taxes and benefits) income. Our results show that, at the bottom of the distribution, tax-benefit systems significantly reduce gender income disparities in most countries due to the effect of social assistance benefits received by mothers in poor households. Additionally, we find that women have substantially higher poverty rates than men based on individual disposable income. Gender differences in poverty fade away when income is pooled at the couple level and, even more so, at the household level. JEL classifications: D31, J16, J7, H24, I32, I38 Keywords: Taxes, Benefits, Microsimulation, Gender gap, Latin America 1 We are grateful to participants at the Inter-American Development Bank’s Gender and Diversity Knowledge Initiative Workshop “Post-COVID-19 Employment Recovery for Women and Diverse Populations in Latin America and the Caribbean,” in particular to Karen Martínez, Claudia Martínez, Raquel Fernández, and Jeanne Lafortune, for their helpful comments. Daniel Chávez provided excellent research assistance. The usual disclaimer applies. Authors’ contact information: Deza: Inter-American Development Bank, [email protected]. Dondo: Universidad Nacional de Río Negro, Argentina, [email protected] Jara: London School of Economics: h.x.jara-t[email protected]. Rodríguez: Universidad Externado de Colombia: [email protected]. Torres (corresponding author), Universidad del Pacifico: [email protected]. 2 1. Introduction Despite improvements in terms of female labor force participation and the reduction in the gender wage gap over the last decades, gender disparities persist in Latin American labor markets. In 2019, the gap in labor force participation amounted to 21.6 percentage points (Güezmes, 2021), informal employment remained more prevalent among female workers (ILO, 2022b) and market pay remained lower for women, with a gap that represents, on average, 13.5 percent of the salary of men (Vaca, 2019). The literature assessing the evolution and factors influencing the gender gap in work and wages in the region is vast (Blau and Kahn, 2017; Christofides et al., 2013; Olivetti and Petrongolo, 2008; Redmond and McGuinness, 2019, among others). However, less is known about the role played by the tax-benefit system in closing gender disparities; that is, when the analysis shifts from market income (pre-tax and benefits) to disposable income (post-tax and benefits). Tax-benefit systems could reduce gender disparities through two channels. On the one hand, some cash transfers are directly targeted to women or benefit them disproportionately. On the other hand, on average, women earn less than men and due to the progressivity of personal income tax, men might be liable to pay more taxes than women. Given the persistent gender disparities in earnings, closing the gender income gap through the tax-benefit system could provide women with economic freedom and decision-making power over household expenses. Evidence of the gendered effects of the tax-benefit system has so far focused on European countries and suggests that although taxes and transfers significantly reduce gender income inequality, they do not fully compensate for the initial gender earnings gap (Avram and Popova, 2021; Doorley and Keane, 2023). The aim of this paper is to assess the extent to which tax-benefit systems contribute to closing the gender income gap in seven Latin American countries: Argentina, Bolivia, Colombia, Ecuador, Mexico, Peru, and Uruguay. These countries were selected to cover a wide range of cases in terms of female labor force participation, gender wage gap, and the redistributive role of taxbenefit systems in Latin America. Harmonized tax-benefit models have been recently developed for these countries, which are used in the analysis. In all these countries, personal income tax and social insurance contributions are assessed at the individual level, and in most of them the main social assistance programs are targeted to mothers with children. Our approach consists of using tax-benefit microsimulation applied to household survey data to obtain the distribution of individual disposable income under a “no income sharing” 3 assumption; that is, income sources where entitlement is at the individual level (e.g., earnings or individual-level taxes, individual benefits) are assigned to the person receiving them, household benefits targeted to mothers according to the legislation are allocated to them, and other benefits assessed at the household level are split equally among household members. Using this measure of individual income, we assess the effect of tax-benefit systems by comparing the ratios of women’s average income to men’s average income based on market and disposable income, for individuals between 18 and 60 years of age. Two remarks are worth noting. First, the exercise assumes that legal incidence corresponds to economic incidence in the case of benefits. For social insurance contributions and personal income tax, the assumption is partly relaxed as the presence of informality is taken into account in the simulations, i.e., social insurance contributions and personal income tax are simulated only for individuals in formal employment. Second, in the case of benefits, our allocation rule focuses on the person who receives them according to the legislation, as we are unable to observe how the benefit is split within the household. As such, the total amount of benefits targeted to mothers is allocated to them, although we do not claim that the benefit will be used only for their own expenses. Our results show that tax-benefit systems significantly reduce the gender gap at the bottom of the income distribution in most countries, due to the effect of social assistance benefits received by women with children. At the top of the distribution, we observe no effect of direct taxes in reducing gender disparities. Our analysis further highlights that poverty rates by gender vary widely depending on the unit of assessment used to aggregate income. In line with previous research, we find that female poverty rates are significantly larger than those of men when they are calculated at the individual level (see Amarante et al., 2022). Additionally, we show that gender differences in poverty decrease when income is pooled at the couple level and, even more so, at the household level. Traditional measures of poverty across genders might therefore hide gender disparities. To the best of our knowledge, this is the first paper that assesses the role of taxes and benefits in reducing the gender income gap in Latin America. In particular, recently developed tax-benefit microsimulation models for Latin American countries are exploited to allocate taxes and benefits at the individual level according to the national rules governing these instruments. Our analysis complements existing efforts to measure the equalizing effect of fiscal policy in Latin 4 America (e.g., Lustig et al., 2023; Bargain et al., 2024) but from a gender perspective.2 Our work also and extends recent studies focusing on European countries and shows the more limited role of taxes and benefits in reducing gender disparities in Latin America. The paper is divided into six sections, with this introduction being the first. Section 2 presents a review of the literature on gender gaps and the role of tax-benefit systems. In Section 3, we provide an overview of the characteristics of tax-benefit systems in the countries under study. Section 4 presents the data and methodology used to assess the effect of taxes and benefits on the gender income gap. Section 5 showcases our main results, and Section 6 concludes. 2. Literature Review 2.1. The Gender Work and Wage Gap Significant progress has been made towards convergence in participation and employment rates in Latin America in the last 30 years.3 However, gaps in labor force participation remain. Between 2016 and 2018, women's labor force participation in the region averaged around 50 percent, contrasting with approximately 75 percent for men (Güezmes, 2021), with large differences across countries.4 In 2019, the gender labor force participation gap ranged from 9pp in Jamaica to 48pp in Guatemala.5 Moreover, women find employment in the informal economy more frequently than men (Güezmes et al., 2022).6 Women are also more likely to work in small firms, in domestic work, and in unpaid family work.7 As a result, women tend to perceive less income than men, i.e., women earn around 13.5 percent less than men (Bando, 2019; Vaca, 2019). 2 The Commitment to Equity (CEQ) initiative uses information on taxes and transfers reported directly in survey data to perform incidence analysis (Lustig et al., 2023). If information is not reported, other methods are used to derive taxes and transfers (see Table B3 in Lustig et al., 2023). Contrary to Lustig et al. (2023) and in line with Bargain et al. (2024), we systematically simulate taxes and transfers according to their governing rules based on market income and demographic information from household surveys in each country under study. 3 Women in Latin America increased their employment rates faster than in any other region in the last 30 years. 4 The number comes from a weighted average of 24 Latin American and Caribbean Countries. 5 Information from IDB’s repository of social data: https://sociometro.iadb.org/es/public 6 The informal economy refers to all economic activities by workers who are–in law or practice–not covered or insufficiently covered by formal arrangements. 7 For instance, in Peru, more than 20 percent of occupied women work in unpaid housework or as domestic workers, compared to only 7 percent of men. 5 Even after controlling for factors such as economic sector, education and experience, a sizable gender wage gap remains unexplained.8 The unexplained gender wage gap primarily arises from differences in the returns to human capital, not attributable to differences in productivity levels (Gallego-Granados and Geyer, 2015). Such unexplained wage gaps are prominent in high-, middle-, and low-income countries and might differ across the income distribution (ILO, 2018). The causes of the gender wage gap are complex and can be described by a wide range of factors, from pay and job task discrimination in the workplace at the top of the income distribution (“glass ceiling effect”) to reasons related occupational choice, social preferences, and institutions; especially labor regulations (Bando, 2019), long-term penalization of motherhood, and premiums for fatherhood care (ILO, 2018).9 In Latin America, the gender gap not only impedes economic growth but also discourages women from participating in the labor market, thereby causing an inefficient allocation of talent resources (Agénor et al., 2018; Schober and Winter-Ebmer, 2009). Hence, understanding the role of tax-benefit systems in narrowing the gender income gap is critical.10 2.2. Tax-benefit Systems and the Gender Income Gap Taxes and benefits can play an important role in reducing income poverty and inequality. For Latin America, recent studies show that direct taxes and cash transfers reduce income poverty and inequality but to different extents across countries and to a more limited extent than in European countries (Arancibia et al., 2019; Lustig, 2023; Bargain et al., 2017; Bargain et al., 2024).11 Additionally, Rodríguez et al. (2022) show that the emergency tax-benefit policies implemented 8 For instance, Ñopo (2012) studies the gender gap in Peru from 1997 to 2009. He finds that, when controlled by demographic characteristics such as age and education level, a large proportion of the gap remains unexplained. In another study, Urquidi and Chalup (2023) found that the unexplained gap (not explained by the components of the models, including education, experience, personal and family characteristics, occupation, and occupational category, economic activity, among others) accounts for most of the gap. 9 The impact of the motherhood penalty on gender wage gaps varies between developed and developing countries. In developed countries, it generally ranges from 0 percent to close to 20 percent, while in developing countries the range can exceed 40 percent (Grimshaw and Rubery, 2015). In Latin America, motherhood often leads to reduced labor supply and a higher likelihood of mothers adopting flexible job arrangements such as part-time jobs, self-employment, or informal employment, resulting in lower wages compared to non-mothers (Villanueva and Lin, 2020), although there is heterogeneity across countries (Piras and Ripani, 2005). 10 Evidence for Morocco suggests that reducing the gender gap in employment by one quarter is associated with an increase in GDP per capita of about 10 percent (Bargain and Lo Bue, 2021). 11 Our study focuses on the effect of the direct taxes and cash transfers on income earned in the labor market. It does not directly incorporate/monetize governmental services (such as education or health). However, we indirectly capture their (per country) effect, to the extent that these services (such as education) may lead to lower wage gaps. 12 The models are used to simulate the main components of disposable income in 2019 and 2020 in each country. Household disposable income is defined as market income net of social insurance contributions and direct taxes plus cash transfers and public pensions.23 More precisely, the models take the information about market income and sociodemographic characteristics directly from the data and based on this information they apply the policy rules to calculate i) employee social insurance contributions, ii) self-employed social insurance contributions, iii) personal income tax, and iv) the main cash transfer programs in each country before and during the pandemic (see Tables in the Appendix A). Due to data limitations, some tax-benefit instruments cannot be simulated but they are included in disposable income if they are reported in the data. Such is the case of contributory benefits and public pensions which cannot be simulated due to the lack of data on contribution histories. In the case of COVID-related policies, benefit amounts or tax payments are simulated as a monthly average over the year, considering the duration of these instruments according to national legislation.24 Importantly, the microsimulation models are also used to allocate household level benefits to specific individuals within the household to assess their effect on the gender income gap. The details of the specific allocation of different income sources are provided in the next section. Assumptions and limitations. To account for the presence of informal employment in the analysis, we take a common approach to simulate social insurance contributions and personal income tax only for formal workers. Here, we follow the legalistic view of formality and consider that someone is in formal employment if they have labor income and report affiliation with social security in the survey. An important limitation of our study relates to the underestimation of social insurance contributions and personal income tax because of top income under-coverage in household survey data. Our estimates of the number of taxpayers follow the tributary rules of each country applied to the data available in household surveys (see Table A1). Although population totals are consistent in household surveys, this might not be the case for individuals identified as taxpayers in the simulations, and there might be heterogeneity across countries. In general, our 23 Market income is defined as the sum of employment and self-employment income, bonuses, in-kind income, own consumption from self-employment activities, capital and property income, inter-household payments, private transfers, minus alimony payments. Imputed rent is not included as part of market income. Corporate income is not included because it is not available in the surveys. 24 Appendix B provides a list of Covid Policies per country. 13 simulations show less than 10 percent of the population paying personal income tax.25 Thus, as high earners are not well captured in the data, our simulations of social insurance contributions and personal income tax underestimate the effect of these instruments. As a result, there might be some bias in our analysis of the role of social insurance contributions and personal income tax in reducing gender disparities at the top of the income distribution. Ideally, analysis based on tax records data could complement the analysis presented in this paper. However, this is beyond the scope of our study. 4.3. Measurement of Individual Disposable Income and the Gender Income Gap Our approach consists of comparing differences in market income (i.e., mainly earnings) and disposable income between men and women in each country. For this, we work under the assumption of “no income sharing” and therefore require measuring disposable income at the individual level. In this section, we describe the income splitting rules according to different income sources. As mentioned above, we focus on a sample of individuals between the ages of 18 and 60. To measure individual disposable income, the following allocation rules are taken. First, earnings and other market incomes (e.g., capital and property income) where entitlement is defined at the individual level are assigned to the person receiving them. The same rule is applied to individual-level benefits such as public pensions, unemployment, disability or parental leave benefits. Second, according to the legislation of each country under analysis, personal income tax and social insurance contributions are assessed at the individual level. Therefore, we assign their own taxes and social insurance contributions payments to each individual in the household.26 As previously mentioned, personal income tax and social insurance contributions are calculated only for formal workers. The assignment of cash transfers within the household, however, deserves more attention. Some benefits are defined at an individual level (e.g., some non-contributory pensions), in which case they are assigned to the individual receiving them. However, some cash transfers are assessed 25 The exceptions are Mexico (39 percent) and Uruguay (23 percent). It is important, however, to highlight that the figures estimate the number of people who actually have to pay income tax, and not the number of people who have to declare income taxes. 26 In the simulations, only payments for a person’s own affiliation with social security are calculated. Social security payments made by a person to cover other household members are not considered. 14 at the household or family level, and we must make some assumptions about how they are allocated among household members. Following the discussion in Section 3, for most cash transfers in the region the legislation stipulates that the benefit is preferentially paid to the mother in the family unit. In those cases, we assign the whole benefit amount to the mother. Finally, all other benefits assessed at the household level are assumed to be shared equally.27 Based on our measures of individual income, we are interested in assessing the effect of taxes and benefits on the gender income gap. For this, we will compare market income to disposable income, as the difference between the two reflects the effect of taxes and benefits. More precisely, we measure gender inequalities in income as the ratio of women’s average income to men’s average income, for market and disposable income. The difference between these two ratios reflects the effect of tax-benefit systems on the gender income gap. If the ratio of women to men disposable income is higher than that based on market income, this signals that the tax-benefit system decreases the income gap between women and men. Two important points related to our analysis are worth mentioning. First, our analysis concentrates on the effect of taxes and benefits on the raw gender income gap, as we do not explore gender differences conditioned by any factors. Second, the gender gap in market income and the effect of taxes and benefits might vary across demographic and income groups. Therefore, in addition to providing results for the full sample, we also show income gender gaps across specific subgroups. 5. Empirical Results The empirical results of our analysis are divided into three parts. First, we compare the relative importance of different income sources between men and women. Then, we assess the effect of taxes and benefits on the gender gap in incomes across countries. Finally, we analyze differences in poverty between men and women when income is measured at the level of the individual, the couple, or the household. As mentioned before, our estimations are representative at the national level. 27 That is, we share “all the benefits among all the adults within the household.” If there are more than two, the benefits are divided among the number of adults. Note that this is the case only for a limited number of benefits in the countries under study. 15 5.1. Relative Size of Income Sources by Gender Figure 1 shows the contribution of different income components to individual disposable income, by quintile and gender in 2019 (see also Table C1 in Appendix C). The figure distinguishes among six income sources: i) earnings (dark blue bars), ii) non-labor market income (light gray bars), iii) social insurance contributions, SIC, (white bars), iv) direct taxes (dark gray bars), v) government cash transfers (black bars), and vi) public pensions (light blue bars). The relative size of each component is measured as a percentage of the average individual disposable income (e.g., mean individual earnings divided by mean individual disposable income). Direct taxes and social insurance contributions are shown as negative values, as they are subtracted in the calculation of disposable income. The results are presented for men and women separately and by quintiles of per capita household disposable income. The use of household income quintiles to split individuals is motivated by the fact that tax-benefit policies, cash transfers in particular, are assessed at the household level even if targeted to mothers. Results for 2020 are presented in Figure D1 in the Appendix. In all countries, earnings is the component that weighs the most in individual disposable income for all quintiles, regardless of gender. In all cases, it is higher for men than for women, remains relatively stable between quintiles for men, but increases with household income for women, representing between 42.8 percent (Ecuador) and 74.2 percent (Bolivia) of individual disposable income for women in quintile 1 to reach proportions between 90.8 percent (Peru) and 120.4 percent (Uruguay) of disposable income for women in quintile 5. In terms of benefits, their relative size is larger for women at the bottom of the distribution. They represent between 14 percent and 43 percent in the first quintile for Argentina, Colombia, Ecuador, Peru, and Mexico, whereas they account for less than 10 percent of women’s income in Bolivia and Uruguay. Regarding pensions, in all countries we find that they weigh less for men than for women. In Bolivia, Colombia, Ecuador, and Peru, they account for less than 4 percent of individual disposable income in all quintiles. In Mexico, pensions increase with income for women, reaching 6 percent in the fifth quintile. In Argentina and Uruguay, the relative size of pension is larger than in other countries and decreases with income for women.28 28 In Argentina, the pension component is not purely made of contributory pensions. The pension system is partially financed from contributions, but access was extended to workers who have not contributed the required years (Moratoria previsional). In addition, non-contributory pensions for older adults (PUAM), mothers of 7 or more 16 Figure 1. Relative Size of Income Sources by Gender and Household Income Quintiles, 2019 Source: Authors’ formulation based on microsimulation models. Note: Income quintiles are calculated based on per capita household disposable income. F stands for female, and M stands for male. children and pensions for disability or invalidity are also part of the pension component in Argentina and cannot be disaggregated in the data. 17 In terms of Social Insurance Contributions (SIC), we observe that their relative size increases with income in all countries. Their incidence is smaller for women at the bottom of the distribution, but the relative size is more similar across genders at the top. These results can be explained by the presence of informal employment, which is more prevalent among women at the bottom of the distribution. In fact, Uruguay and Argentina stand out, where the relative importance of social insurance contributions is larger, which is also explained by the larger share of affiliation to social security (i.e., higher formal employment) in these countries relative to other countries under analysis. In the bottom quintile of Argentina, SIC represents 3 percent of individual disposable income for women and 6.5 percent for men. The relative size of SIC is larger in the bottom quintile of Uruguay, representing 8.6 percent for women and 13 percent for men. At the top, the relative size is similar across genders, reaching between 15 percent and 20 percent in Argentina and Uruguay, respectively. Finally, the relative size of direct taxes is, in general, modest in all countries. Previous research has shown that in LAC, a low share of the population is liable to personal income tax compared to advanced economies (Arancibia et al., 2019; Lustig et al., 2017). The limited size of personal income tax (PIT) in Latin America has been explained by the high levels of informal employment in the region but also by the high exempted thresholds and generous deductions which are part of the design of this policy instrument in the region. As previously mentioned, the limited effect of PIT might also reflect the fact that high-income individuals are not properly covered by household survey data. Figure 1 shows that, in Argentina, Colombia, Ecuador, and Peru, PIT appears to play a role only for individuals in the top income quintile. In Uruguay and Mexico, the contribution of PIT is somewhat more generalized across the income distribution, but the higher quintiles pay more taxes due to the progressivity of this policy.29 5.2. The Gender Income Gap We now turn to the analysis of the effect of taxes and benefits on the gender income gap. Figure 2 compares market income and disposable income gender ratios in all countries for 2019 and 2020. As previously mentioned, the smaller the ratios, the larger the income of men compared to that of 29 It is important to mention the weakness in the collection of income tax and social security contributions in Latin America relative to other regions (OECD, 2020). Personal income tax contributes an average of 8.6 percent of GDP in OECD countries, while it only reaches 2 percent of GDP, on average, in Latin America and the Caribbean. In the case of SIC, the percentages reach 9.2 percent in OECD countries and 3.9 percent in LAC. Thus, we expect them to have a smaller redistributive effect across genders. 18 women. Taxes and benefits reduce the gender income gap if the gender income ratio of disposable income is larger than that of market income. The average incomes for these ratios are only conditional on age (i.e., our sample considers all individuals aged between 18 to 60) and not on labor status. Therefore, the ratios are capturing simultaneously gender differences in earnings and gender gaps in employment; that is, differences in earnings among the working population and differences in earnings between people in work and people out work (i.e., women out of work are part of our sample). We come back to this point later in the next subsections. We find that, for both 2019 and 2020, all countries face a marked gender income gap. Analyzing only market income, we find that the average income of women in 2019 represents between 47 percent (in Mexico) and 69 percent (in Uruguay) of the average income of men in our sample, though the precision of our estimates varies from country to country. In 2020, the gaps in market income in Ecuador and Colombia widen slightly, while those of the other countries close slightly. That year, the smallest gap was found for Uruguay, where the market income of women was equivalent to 70 percent of that of men. Figure 2. Market Income and Disposable Income Gender Ratios (women’s average income relative to men’s average income) Source: Authors’ formulation based on microsimulation models. Note: The sample considers individuals between the ages of 18 and 60 years old. 95% confidence intervals are presented. 19 Figure 2 further shows that the gender gap in disposable income is smaller than that of market income in all countries. The gender income ratio for disposable income in 2019 ranges between 0.49 in Mexico and 0.70 in Uruguay. This points to a positive effect of tax-benefit policies in closing the gender gap in income. However, with the exception of Argentina in 2019, the changes in the gender gap are not statistically significant; that is, we cannot assert whether the taxbenefit system reduces the gender income gap or not. The effect of the policy in Argentina can probably be explained by the broader coverage of the AUH (Asignación Universal por Hijo) program, which prioritizes mothers as beneficiaries. As previously mentioned, our analysis relies on allocating income sources to individuals according to the legislation on tax-benefit instruments. In particular, benefits targeted to mothers are allocated to them in our simulations. However, it is possible that reported information of benefit receipt in the survey might differ from the simulations. To test this, Figure A3 in the Appendix compared disposable income gender ratios obtained with simulated and reported benefits. The results show that simulated and reported benefits provide similar information. 5.3. The Gender Income Gap by Household Income Deciles The results presented in the previous section for the whole sample in each country might mask differences across population subgroups. In particular, the effect of cash transfers is expected to be more prevalent at the bottom of the income distribution, whereas social insurance contributions and personal income tax might have a higher incidence at the top. For this reason, Figure 3 presents gender income ratios by income decile groups for 2019, where deciles are based on per capita household disposable income. The analysis therefore aims to compare gender gaps between men and women living in households located in different parts of the income distribution. The gender composition across deciles is not entirely balanced. In the bottom decile, the share of women is between 53 percent and 57 percent in all countries. In the top decile the share of women is slightly lower, between 45 percent and 49 percent. Table C2 in the Appendix provides information about the gender composition deciles in each country. Figure D2 in the Appendix replicates the analysis for 2020, and the patterns of the effects are very similar. Figure 3 shows that the “market income gap” displays, in general, similar behavior across deciles in all countries. The gender income ratio from market income remains roughly stable up to the fourth decile and increases afterward; although it always remains below 0.85 for the upper part 20 of the household income distribution (that is, on average, as even in the upper deciles women’s income is never higher than 85 percent of men’s income). This finding can be potentially explained by the changes in occupation profiles across the income distribution. For instance, women (and men) in the poorest deciles are employed in lower-skilled occupations; within them, women are more likely to work informally and have fewer hours than men to allow for non-paid home care work, or simply be paid less for the same job because of non-observable factors, such as biases and cultural patterns. As income grows, however, women might tend to work full-time in formal employment and professional occupations, as the household has the economic buffers to finance the necessary support for home duties. As such, the gender income gap decreases. Figure 3 also shows that, in almost all countries, taxes and benefits reduce the gender gap in the lower income deciles; in particular in the first one, while the effect fades away progressively to become negligible in the highest deciles. To be specific, for the bottom decile of the income distribution we find that in Argentina, Colombia, Ecuador, Mexico, and Peru, the market income ratio and the disposable income ratios are statistically different. This reflects the role of social assistance targeted to low-income mothers with children. As discussed in Section 3, in most countries under analysis, cash transfer programs have a component destined for women with children and by default, the benefit is paid to the mother. As previously mentioned, we have not restricted our samples to individuals in work. Therefore, our results are capturing simultaneously gender differences in earnings and gender gaps in employment. To disentangle between the two, Figure 4 replicates the analysis provided in Figure 3 but for a sample of individuals in work (those with positive labor income regardless of the number of hours of work), aged between 18 and 60. Although the patterns are similar to those based on the unrestricted sample (Figure 3), there is a visible increase in women’s income relative to men’s, particularly for Bolivia, Colombia, Ecuador, and Peru, and for the first deciles. That is, a proportion of the gender income differences observed in Figure 3 for the poorest population is due to differences in the share of men and women who are out of work. Interestingly, the reduction in the gender income gap (from Figure 3 to Figure 4) is not marked for people in the middle of the distribution (deciles 5 and 6). Additionally, the role of tax-benefit systems in reducing the gender income gap is smaller in Figure 4 and only significant, at the bottom of the distribution, in Argentina, Colombia, and 21 Mexico.30 This means that the effect observed in Figure 3 is mainly driven by the role of cash transfers in reducing the income gender gap for women out of work (rather than reducing the gender gap in earnings for women in work. Figure 3. Market Income and Disposable Income Gender Ratios, (women’s average income / men’s average income) by Household Disposable Income Deciles, 2019 Source: Authors’ formulation based on microsimulation models. Note: The sample considers individuals between the ages of 18 and 60 years old. 95% confidence intervals presented. 30 To be specific, the difference between Figures 3 and 4 is that Figure 3 includes people who are out of work (either unemployed or not looking for a job). 28 5.5. Policy Implications Based on the analysis presented in this paper, we draw some policy implications related to gender disparities and the role of taxes and benefits in reducing the gender income gap in Latin America. A first clear result is the marked gap in market income between men and women when considering all those aged 18 to 60 years, regardless of labor status. Therefore, although our analysis focuses on the role of tax-benefit policies in reducing gender disparities, it is important to highlight the need to consider policies to reduce gender disparities in the labor market. A second important result is that tax-benefit policies reduce gender income disparities. Their effect is larger and significant at the bottom of the household income distribution. Yet, the different socio-fiscal instruments show widely varying effects. For instance, cash transfers have a larger impact on the lowest income deciles and, if allocated to mothers, they have the effect of closing the gender gap. From a policy perspective, the results highlight the importance of expanding cash transfers with a gender perspective. On the contrary, we find that SIC and income taxes have a limited contribution to reducing the gender gap in LAC countries, as a result of low levels of coverage (i.e., informality and high exempted thresholds (see Jara et al., 2023). It also seems advisable to consider different ways of measuring poverty according to gender. In particular, our results show that large gender differences in poverty are observed when different income pooling assumptions are used. The assumption of full income sharing does not allow for a precise measurement of the phenomenon. For example, in cases where there is no equitable distribution within the household, if the woman has no income, she would be poor but would not be detected under the assumption of full income pooling. While mitigating the gender income gap is a desirable policy objective, a significant gap is expected to remain even if the tax-benefit system is strengthened to reduce both the wage and the employment gap. In the case of the latter, the problem of low female labor force participation relative to men, is multifaceted in nature and goes beyond the scope of fiscal policies. As mentioned in Section 2, socioeconomic, cultural and structural factors are important contributors to the decision taken by women to participate in the labor force. Women’s decision to participate in the labor market is influenced by observable personal and family decisions (such as investing in education or having children), household characteristics and composition (how many children, elderly, or members with a disability live in the household), the economic environment that influence employment opportunities and returns, access to care services, financial inclusion, access 29 to social protection and affordable childcare (Gontero and Vezza, 2023). Additionally, unobservable factors play a role, such as social and cultural norms that influence preferences, values, customs, perceptions of opportunities and gender roles. While the abovementioned considerations are important, we argue that fiscal policies can have a direct influence on the economic environment through the tax and benefit system, as is the case in advanced economies. An effective tax system could create incentives that encourage women’s participation in the workforce, and a well-targeted benefit system can complement women’s income and reduce the gender income gap without disincentivizing, and sometimes while encouraging, participation in the labor force. For instance, the provision of inclusive government services, such as quality education, training and employability services focused on women, and affordable childcare can be considered, as well as in-kind transfers that can be incorporated in further analysis of the impact of a broad range of fiscal policies on the gender income gap. Therefore, fiscal policies can constitute potential levers for change that could complement broader societal efforts. 6. Conclusions This paper assesses the extent to which tax-benefit systems contribute to reducing the gender income gap in Latin America. Closing it, could provide women with economic freedom, and more agency over household expenses. Using a novel set of microsimulation models for Latin America and nationally representative household surveys, we calculate distributions of individual disposable income assuming “no income sharing” within the household. The role of taxes and benefits is assessed by comparing gender income ratios (female over male) from market to disposable income for individuals between the ages of 18 and 60, and by income subgroups. We find that women’s market incomes represent on average between 47 percent (Mexico) and 69 percent (Uruguay) of men’s market incomes. Interestingly, the analysis by income deciles shows that gender market income ratios tend to decrease between the first and second (sometimes third) decile. Gender disparities start to visibly reduce after the fourth decile, reaching a minimum for the top deciles (ninth or tenth). The gender market income ratio is around 0.85 for the top deciles. Furthermore, we find that the tax-benefit policies significantly reduce gender income disparities in the lower income deciles in Argentina, Colombia, Ecuador, Mexico and Peru. The reduction in the gender income gap at the bottom of the distribution is due to the role of social 30 assistance benefits received by mothers in poor households. Moreover, our results show that this reduction in the gender income gap is explained by the effect of cash transfers in reducing income differences due to the gender gap in employment, rather than by the income gender gap among the employed population. At the top of the distribution, we observe no effect of direct taxes in reducing the gender income gap. The latter might be due to the fact that household survey data suffer from under-coverage of high incomes and, therefore, the role of personal income tax might be underestimated in case the simulations of the number of taxpayers may not match administrative information. Still, our findings offer valuable insights, and the under-coverage of high incomes most likely does not affect our results regarding the effects of tax-benefit policies in the lower income deciles. Lastly, we find large differences in poverty rates by gender calculated using individual disposable income, with women always having higher poverty rates than men. The poverty rate of men is relatively similar across countries (between 21 percent and 26 percent); whereas women’s poverty rate varies widely (from around 39 percent to close to 60 percent). Assuming income pooling at the couple or household level, instead, reduces gender differences in poverty. As such, we argue that using total household income to determine members’ economic well-being may hide economic gender disparities. 31 References Agénor, P., Ozdemir, K. K., Moreira, E. P. (2021). Gender Gaps in the Labor Market and Economic Growth. 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Main Characteristics of Personal Income Tax in the Countries under Analysis (2019) Country Tax Unit Lowest tax band limit Highest tax band limit Lowest tax rate (%) Highest tax rate (%) Taxpayers (% of Population) Tax deductions Argentina individual 5 31 5 35 6.67 Family charges (children and partner not earning incomes); general deductions (expenditures in health, housing rental, among others); special deductions for labor income Bolivia individual - - 13 (flat) - 1.13 All billed expenditures Colombia individual 3.75 107 0 39 1.95 Expenditures in education, health, mortgage payments, expenditures on dependent relatives Ecuador individual 2.4 24.4 0 35 2.95 Expenditures in food, clothing, education, health, and housing Mexico individual 0.18 93.1 1.92 35 38.97 Expenditures in education, health, funeral, expenditures on dependent relatives Peru individual 2.6 19.6 8 30 6.27 Billed expenditures in rent, and specific services (up to a limit) Uruguay individual 1.9 382 0 36 22.84 Children charges Source: Authors’ formulation based on the 2019 legislation of personal income tax, the legal minimum wages in each country, each country dataset, and the SOUTHMOD country report for Bolivia (see Arancibia, C., and Macas, D. (2023) ) Note: Tax bands are expressed in terms of annualized minimum wages in each country. The tax rates refer to marginal tax rates.The “Taxpayers ( % of Population)” column refers to estimates of the proportion of people over 18 years of age who pay income based on “household survey” data considering the minimum income required to pay income taxes. 44 percent reduction in working time and the consequent reduction in labor income, with the benefit amount defined as 25 percent of gross income before reduction; and v) a temporary tax for public workers with monthly incomes higher than $120,000 (US$2,857April and May 2020). Mexico No Covid-specific policies were introduced by the Mexican government. In 2020, the only policy introduced was Crédito a la palabra consisting of a single loan payment for business, to be repaid in three years with an annual interest rate of 6.5 percent. 45 Appendix C Table C.1. Contribution of Different Income Components to Individual Disposable Income, by Quintile and Gender in 2019 Female Male Quintile Labor Income NonLabor income Social Insurance Cont. Benefits Pensions Income Tax Labor Income Non-Labor income Social Insuran ce Cont. Benefits Pensions Income Tax Argentina 1 45.9% 5.9% -3.2% 43.3% 8.2% 0.0% 100.2% 1.0% -6.5% 2.3% 3.1% -0.1% 2 71.5% 7.3% -6.4% 18.5% 9.1% 0.0% 105.2% 0.6% -9.4% 1.2% 2.6% -0.1% 3 92.3% 6.7% -11.1% 5.4% 6.9% -0.1% 107.4% 1.2% -12.0% 0.4% 3.4% -0.2% 4 101.9% 6.6% -13.7% 1.6% 4.0% -0.4% 109.4% 2.4% -13.9% 0.3% 2.5% -0.8% 5 105.7% 7.8% -14.7% 0.5% 5.1% -4.3% 110.0% 7.3% -14.0% 0.1% 3.0% -6.4% Bolivia 1 74.2% 23.1% -1.0% 3.1% 0.7% 0.0% 102.2% -1.8% -1.3% 0.8% 0.2% 0.0% 2 77.4% 21.3% -1.6% 2.0% 1.0% 0.0% 99.5% 1.5% -2.0% 0.8% 0.3% 0.0% 3 85.6% 15.1% -2.7% 0.9% 1.2% 0.0% 100.3% 1.4% -3.2% 0.6% 1.0% 0.0% 4 91.9% 9.7% -3.7% 1.0% 1.2% 0.0% 100.8% 2.0% -4.1% 0.7% 0.7% 0.0% 5 92.9% 10.8% -6.2% 0.7% 1.9% -0.2% 101.6% 3.4% -6.3% 0.4% 1.4% -0.5% Colombia 1 48.9% 25.6% -1.9% 26.6% 0.8% 0.0% 94.4% 5.0% -2.0% 2.3% 0.3% 0.0% 2 67.5% 19.2% -2.8% 14.8% 1.3% 0.0% 98.0% 3.3% -3.4% 1.4% 0.8% 0.0% 3 82.8% 14.1% -4.4% 5.6% 1.8% 0.0% 98.7% 3.7% -4.7% 0.8% 1.5% 0.0% 4 92.0% 11.4% -5.9% 0.2% 2.4% 0.0% 98.7% 4.6% -5.7% 0.1% 2.3% 0.0% 5 96.0% 10.2% -7.5% 0.0% 3.3% -2.0% 101.7% 6.3% -7.5% 0.0% 2.4% -3.0% 46 Female Male Quintile Labor Income Non-Labor income Social Insuran ce Cont. Benefits Pensions Income Tax Labor Income Non-Labor income Social Insuranc e Cont. Benefits Pensions Income Tax Ecuador 1 42.8% 17.8% -1.0% 38.1% 2.2% 0.0% 93.3% 7.3% -1.6% 0.7% 0.2% 0.0% 2 65.1% 20.3% -1.9% 14.8% 1.7% 0.0% 95.1% 6.8% -2.7% 0.3% 0.5% 0.0% 3 79.6% 15.4% -3.4% 5.5% 2.9% 0.0% 98.3% 4.9% -4.0% 0.2% 0.5% 0.0% 4 89.9% 12.5% -5.4% 1.1% 1.9% 0.0% 99.5% 5.2% -5.6% 0.0% 0.8% 0.0% 5 98.1% 10.0% -8.3% 0.1% 1.8% -1.6% 100.0% 7.1% -8.2% 0.0% 3.2% -2.0% Mexico 1 64.6% 20.4% 0.4% 16.1% 1.2% 1.9% 92.7% 8.5% -0.8% 2.1% 0.4% -3.0% 2 79.0% 14.8% 0.8% 8.4% 1.3% 2.8% 96.5% 7.1% -1.2% 1.7% 0.6% -4.7% 3 85.8% 12.8% 1.2% 4.7% 2.0% 4.1% 98.8% 6.4% -1.5% 1.4% 0.9% -6.1% 4 92.6% 10.5% 1.8% 1.2% 3.0% 5.6% 100.2% 7.0% -1.7% 1.0% 1.5% -8.0% 5 94.9% 13.2% 2.2% 0.2% 5.7% 11.8% 102.2% 11.6% -1.9% 0.2% 2.2% -14.4% Peru 1 68.1% 18.6% -1.2% 14.5% 0.0% 0.0% 96.7% 3.8% -0.6% 0.0% 0.1% 0.0% 2 80.9% 17.5% -1.7% 3.3% 0.1% 0.0% 96.7% 4.1% -1.0% 0.0% 0.2% 0.0% 3 85.3% 15.6% -2.0% 0.9% 0.2% 0.0% 96.3% 5.1% -1.5% 0.0% 0.2% 0.0% 4 89.4% 13.1% -2.8% 0.2% 0.1% -0.1% 94.4% 7.0% -1.6% 0.0% 0.5% -0.3% 5 90.8% 13.4% -2.2% 0.0% 0.2% -2.3% 91.8% 11.2% -1.4% 0.0% 0.9% -2.5% Uruguay 1 70.9% 21.0% -8.6% 9.4% 7.2% -0.1% 100.4% 1.9% -13.1% 6.8% 4.0% -0.1% 2 93.2% 9.6% -15.0% 5.8% 6.7% -0.2% 108.9% 0.8% -17.6% 4.1% 4.9% -1.2% 3 105.1% 5.5% -18.9% 4.6% 4.9% -1.2% 112.1% 0.9% -19.0% 3.8% 4.8% -2.6% 4 112.4% 5.2% -20.7% 3.0% 3.6% -3.6% 116.3% 1.2% -19.8% 3.7% 3.6% -5.0% 5 120.4% 6.5% -21.4% 2.8% 3.4% -11.8% 126.4% 2.4% -19.6% 2.3% 2.9% -14.2% 47 Table C.2. Gender Composition for Each Decile Group (percentage of women by per capita household disposable income decile) 1 2 3 4 5 6 7 8 9 10 Total Argentina 56.9% 54.8% 53.1% 52.3% 50.4% 52.0% 51.1% 47.9% 49.4% 47.9% 51.4% Bolivia 53.8% 55.3% 54.1% 53.2% 53.3% 53.7% 51.7% 49.4% 50.1% 45.1% 51.6% Colombia 56.3% 54.2% 53.5% 52.3% 52.7% 51.8% 50.8% 49.4% 46.8% 48.2% 51.2% Ecuador 53.0% 55.4% 54.2% 52.6% 51.8% 52.1% 50.9% 50.5% 48.0% 48.3% 51.4% Mexico 56.4% 55.7% 54.7% 53.9% 53.8% 52.0% 50.9% 50.5% 50.6% 49.4% 52.5% Peru 53.5% 56.0% 54.9% 53.6% 53.7% 52.3% 51.5% 50.6% 50.3% 48.2% 52.2% Uruguay 55.8% 53.9% 52.6% 51.2% 50.6% 50.6% 49.4% 49.1% 48.2% 48.5% 50.8% 48 Appendix D. Figure D.1. Disposable Income Components, by Gender and Income Quintiles, 2020 Source: Authors’ formulation based on microsimulation models. Note: Income quintiles are calculated based on per capita household disposable income. F stands for female; M stands for male. 49 Figure D.2. Market Income and Disposable Income Gender Ratios (women’s average income / men’s average income) by Household Disposable Income Deciles, 2020 Source: Authors’ formulation based on microsimulation models. Note: The sample considers individuals between the ages of 18 and 60 years old. 95% confidence intervals presented. 50 Figure D.3. Disposable Income Gender Ratios with Observed and Simulated Benefits, 2019 Source: Authors’ formulation based on microsimulation models. Note: The sample considers individuals between the ages of 18 and 60 years old. 95% confidence intervals presented.