Selected Issues

Abstract

Selected Issues

Addressing Gender Issues in Argentina’s Labor Market1

A. Background

1. Argentina’s female labor force participation rate is lower than that of Brazil, Chile, Peru, and Uruguay, and is below the OECD average. Furthermore, the ratio of the female to male labor force participation rate is lower than all other Latin American countries except for Mexico. Among countries in the region, Chile, Colombia, and Ecuador had a ratio below that of Argentina in 1990 (and in 2000 for Chile), but by 2014, these countries had all closed the gap between males and females in labor force participation. For Argentina, the gap has remained constant since early 2000s.

uA04fig01

Female labor force participation

Citation: IMF Staff Country Reports 2017, 410; 10.5089/9781484335833.002.A004

Source: World Bank, Gender Statistics

2. More than 90 percent of women in the labor force in Argentina are employed in the service sector, a rate that is approximately 12 percentage points above that in Brazil or Mexico and more than 5 percentage points above the OECD average. The service sector is composed by both a modern service sector, but also by a traditional and large share of the informal sector.

uA04fig02

Employment by Sector and Gender

Citation: IMF Staff Country Reports 2017, 410; 10.5089/9781484335833.002.A004

Source: World Bank, Gender Statistics

3. Argentina lags at least one of its major peers in each of the four components of the Gender Inequality Index (Gindex).2 The Gindex (developed by Jain-Chandra and others, 2017) incorporates not only indicators of education and health, but also equality of legal rights and financial access. It therefore measures important differences of opportunity across genders, which could have implications for female labor force participation rates in Argentina. Though Argentina performs better than Brazil and Mexico in terms of the index’s educational empowerment score, it lags Brazil and Mexico when looking at legal empowerment. For financial access, Argentina is behind Brazil and Chile.

uA04fig03

Gender Inequality Index (2015)

Citation: IMF Staff Country Reports 2017, 410; 10.5089/9781484335833.002.A004

Source: United Nations Development Programme, Human Development Reports.

4. Increasing gender equality and closing the gender gap can generate growth. Gender gaps in education can harm growth (Klasen and Lamanna (2009), Knowles et al. (2002) and Seguino (2010)); improvements in female health outcomes can raise growth (Bloom, Kuhn, and Prettner (2015)); and legal barriers reduce female labor force participation (IMF, 2015). Aguirre et al. (2012) estimate that increasing female employment to male employment levels, would raise GDP per capita in Argentina by approximately 12 percent.

B. Labor Market Conditions for Women in Argentina

5. In Argentina women work more in the informal sector than men. According to the Household Survey (Encuesta Permanente de Hogares de Argentina, March 2017), 39 percent of the women in the labor force work in the informal sector (versus 34 percent for men). Men also hold most of the formal sector jobs (56 percent) and most of the fulltime formal jobs (65 percent).

uA04fig04

Labor Force Participation: Household Survey Data

Citation: IMF Staff Country Reports 2017, 410; 10.5089/9781484335833.002.A004

Source: Argentina Household survey, March 2017

6. Informality and inequality (particularly gender) are tightly linked. Informal jobs are characterized by lower earnings, poor employment conditions, lack of protection, compulsory overtime or extra shifts, layoffs without notice or compensation, unsafe working conditions and the absence of social benefits such as health insurance, sick pay and maternity leave. The household survey shows that hourly wages are on average 50 percent lower in the informal sector than in the formal sector. Argentina is among the emerging economies with the largest wage gap between formal and informal workers (OECD, 2015c). These jobs are concentrated in the service sector, and workers are on average less educated than formal workers (see companion SIP).

7. The wage gender gap in Argentina is rather high. The overall gender wage gap is the difference between females and males’ total earnings from labor, and it is 24 percent in Argentina, based on household survey data. This gap can reflect different working conditions and job characteristics between genders, related for example to the number of hours worked or the skills required for the job. However, they can also reflect pure gender discrimination—a wage premium for male workers that cannot be explained by controlling for observable individual and job characteristics.

8. We estimate both explained and unexplained components of the gender wage gap in Argentina. Following Blinder (1973) and Oaxaca (1994), we run linear regression models of men and women’s hourly wages on workers’ age, education, sector of activity, location and occupation, using Argentina’s household survey data. We thus estimate what part of the wage gap can be explained by observable variables, and what part cannot be explained (reflecting gender discrimination). We perform the method for full-time workers first, and then separately for full-time workers in the formal versus informal sectors.

9. We find evidence of significant gender wage discrimination, particularly in the informal sector. The unexplained component of the wage gender gap is equal to 14.9 percent if we consider all full-time workers. However, for jobs in the informal sector the unexplained component is almost three times larger than in the formal sector (27.5 percent vs 9.2 percent). This result suggests that there is more discrimination against women in the informal sector, where institutions and rule of law are weak. Another interesting result is the negative coefficient for the “explained” part of the wage gender gap. This suggests that controlling for age, education, sectors, location, and occupation, women receive salaries that are smaller than what would have been predicted by the regression.

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C. Policies to Address Gender Issues in Argentina

10. To analyze the impact of reforms on economic growth, income inequality, and female labor force participation, we build a dynamic general equilibrium model with heterogeneous agents. The policies considered are (i) a reduction of the tax wedge on labor income (ii) measures that reduce discrimination against women in the formal sector, and (iii) a subsidy to childcare to low- and mid-income formal female workers.

11. The model is calibrated to match Argentina’s macro and micro data and captures important aspects of that economy. Our model replicates important features of the Argentinian economy, such as tax, transfers, and pension systems, as well as the duality of formal and informal labor markets. Agents in this framework differ from each other in terms of generation (children, young adults, adults, old), gender (male and female) and an initial ability received at birth. These differences generate distinct incentives and choices for agents throughout the life cycle. The model also features endogenous human capital formation. Its full description can be found in Annex I of this SIP.

12. The model treats separately men’s and women’s labor supplies, making it an ideal tool to study gender and distributional effects of policies. We built a framework where husbands and wives decide together how much their families should consume, how much labor each of them should supply to the formal and informal sectors, and how much to invest in their kids’ education. Wives and husbands have different decisions towards participating in the labor market: when women supply labor, there is a utility cost incurred by the family. This cost relates to the difficulty of coordinating multiple household activities, such as home production and rearing children. Furthermore, the model features gender discrimination in formal labor markets in the form of unexplained gender wage gaps.

Reducing the Tax Wedge

13. Reducing the tax wedge in Argentina can yield higher economic growth, increase female labor supply, and lower the wage gender gap. We simulate the impact of a reform in labor income tax as described in the companion SIP (Dudine et al, 2017). The reform reduces employer and employees’ social security contributions to a flat 10 percent rate (excluding contributions to health care or obras sociales),3 while cutting by about half the main deductions on personal income tax. The mains results are (see Figure 1):

  • Long-run GDP would be 1.2 percent higher, reflecting a greater formal sector, which becomes more competitive, attracts more skilled workers (particularly females), and increases the return to human capital accumulation, leading to more investment in education.

  • In the new model’s steady state, the average real wage would be 3 percent higher for females and 2.7 percent for males, reducing the wage gender gap as higher skilled (also higher earners) females join the labor force and accumulate more human capital. After the reform, hours worked by females in the formal sector would be higher (by about 12 percent).

  • The reform would reduce poverty, while inequality would not be affected. The increase in overall demand increases the prices of informal goods, which are mostly produced by low-skilled, low wage workers, increasing their income and reducing poverty. The impact on inequality is negligible, because the reform benefits both low income earner that work on the informal sector and high-skilled earner that work on the formal sector.

Figure 1.
Figure 1.

How Do These Policies Change GDP and the Gender Wage Gap?

Citation: IMF Staff Country Reports 2017, 410; 10.5089/9781484335833.002.A004

Reducing Discrimination in the Work Place

14. Reducing discrimination against women in the formal sector increases female labor force participation, reduces poverty, and boosts GDP growth (Figure 1). We simulate a policy that eliminates Argentina’s unexplained wage gender gap in the formal sector.4 This would reduce the overall gender wage gap by 6 percentage points, increasing the returns of working in the formal sector and resulting in a larger share of female employment in this sector. High-skilled females are particularly affected by the measure, as they see the largest absolute increase in the return from working in the formal sector. The result is a formal sector that is more productive as it employs more skilled workers. The greater aggregate demand pushes up the prices of informal goods, which are mostly produced by low-skilled, low wage agents, increasing their income and reducing poverty.

Reducing Costs for Working Women

15. Giving childcare subsidies for low and middle income women that work on the formal sector decreases gender inequality and boost long-term growth (Figure 1). Increasing the provision of childcare subsidies for mothers that earn, at most, the average income in Argentina and work on the formal sector, expands the participation of women in the formal sector, increases human capital, reduces the wage gender gap and ultimately generates higher economic growth. The model shows that the measure would be broadly budget neutral, as higher income tax payments from women compensate the childcare subsidy cost.

D. Conclusions

16. Female labor force participation in Argentina is lower than its peers. Working women work more in the informal sector than men. Reducing the size of the informal sector generates higher economic growth and lower gender inequality. Policies that bring workers from the informal sector to the formal sector can produce sustainable and inclusive growth. Female employment in the informal sector is larger than men, and this is worrisome since informal jobs are characterized by larger wage gender gaps, lack of social protection, sometimes unsafe working conditions, and instability. Reducing the informal sector generates higher and inclusive growth. Policies like increasing job flexibility, reducing and simplifying dismissal procedures, and getting the minimal wage right can reduce the size of the informal sector.

17. Policies that reduce discrimination against women can generate higher economic growth, reduce the wage gender gap, and reduce poverty. Reducing discrimination against women increases female labor force participation, their working hours, and their human capital, and these effects are particularly important for high-skilled women that benefits more form the reform. The reform also reduces poverty, mainly due to the increase in the overall demand of the economy that pushes the prices of informal goods up. These goods are mostly produced by low income workers that benefit the mostly from this reform.

18. Providing childcare subsidies for low and middle-income women is a winning policy, since it generates economic growth, boosts government revenues and lowers income inequality. The policy gives more incentives to women in lower deciles of the income distribution to work in the formal sector, accumulating higher levels of human capital, and closing the wage gender gap.

Appendix I. Description of the Model

We construct an overlapping generations (OLG) model with three periods to analyze an economy where agents differ from each other in many aspects: gender, a shock received at birth, accumulation of human capital, income, and (of course) generation. In this economy, a household is a family, comprised of a husband, a wife and two kids, or simply a husband and a wife (after their two kids have married and formed another household/family). Husbands and wives make all the decisions for the household, together. Men and women’s labor supply are chosen endogenously.

In the first period a household is comprised of a husband, a wife, and two kids (a boy and a girl). Husband and wife decide together how much to work in the formal and informal sector, how much to invest in kids’ education, and how much to consume of each of the two types of goods in this economy (formal and informal goods). In the second period, kids have grown and started their own family, so that the initial household has now only the husband and the wife. They now only choose how much labor to supply in the formal and informal sectors, and how much to consume. Whenever women supply labor (in either period 1 or 2), there is a utility cost incurred by the family. This cost relates to the difficulty of coordinating multiple household activities, such as home production and rearing children. When agents are old (period 3), they receive pensions provided by the government.

The government collects income tax, social security contributions, consumption tax and corporate tax. It spends on cash transfers to households, on pensions benefits, and on goods produced in the formal sector. The formal sector in this economy is modeled as a representative firm that hires both male and female effective hours of labor to produce the formal good. The firm practices discrimination of salaries by paying women less than their marginal product of labor. This reflects the gender wage gap after controlling for education, experience, type of jobs, location, that we find in Argentina’s household survey data and also in ILO’s 2014/2015 Global Wage Report.

Endogenous Human Capital Accumulation

Human capital formation starts at birth and evolves according to an innate shock, education, and the amount of labor supply to the formal sector. In period 1 human capital is h1 = εeαe. In periods 2 and 3, human capital is given by

hj=(1δ)hj1+(1+lg,fo)αh,wheregenderg{m,f}andj{2,3}

Recursive Problems of Households

We describe below the recursive problems of households for each of the three periods. We denote by Vtj the value function for each household at date t and period of life j.

We start by posing the first problem of a household, as soon as the household is formed (period 1). At this stage, the household is comprised of a husband, a wife and two kids (one boy and one girl). The marriage market is such that males and females randomly marry other females and males, respectively, with same age and human capital.

Household problem in period 1

The household decision at this stage will depend on their children’s future utility. Therefore, parents’ decisions on how much to spend on children’s education will also take into account the expected earnings of their children. The state of a household in the beginning of this period is given by husband and the wife’s age and human capital (assumed to be equal – given the matching process), and the idiosyncratic initial shock received by their children (ε). We assume that there is only one shock for both children and that parents invest the same amount on the boy and the girl. Thus, both children have the same human capital at this stage. Given wages wf and wm (measured in units of efficient labor), the problem of the household in period 1 is to maximize utility choosing consumption, amount spent on kids’ education, and labor force supply to the formal and informal sectors:

Vtj=1(h,ϵ)=max{c,e,lm,fo,lm,inf,lf,fo,lf,inf}u()+βVt+1j=2(hf,hm)+ηkβ{Vt+1j=1(hk,ϵ)+Vt+1j=1(hk,ϵ)}

subjected to

θ[cfo(1+τc)pfo+cinfpinf]+2pfoe(1τf())(1τss,f())wflf,fohf+(1τm())(1τss,m())wmlm,fohm+pinf(ym,inf+yf,inf)+T1()yg,inf=zinf[lg,inf]αinf,wheregenderg{m,f}hg=(1δ)hg+(1+lg,fo)αh,g{m,f}hk=ϵeαelg,fo+lg,inf1,g{m,f}lm,fo,lm,inf,lf,fo,lf,inf(0,1)

In the above problem, h = hf = hm are wife’s and husband’s human capital (assumed to be equal due to the matching process); hk is their kids’ ability in the next period (which will be the same for the boy and the girl, since they both got the same human capital). e is the birh shock that children receive at birth. lm,fo and lf,fo are male and female’s time devoted to working in the formal sector; lm,inf and lf,inf are male and female times devoted to working in the informal sector. ηk is the parameter indicating preference for each child’s utility. θ is a parameter denoting higher consumption given the presence of kids in the household in period 1. τm (·) and τf (·) are tax rate functions for males and females, and depend on husband and wife’s formal income. τc is the tax rate on consumption. τss,f and τss,m, are the social security contributions that are different for male and females, and are functions of husband and wife’s formal earnings. e is the amount of education invested in each of the 2 children. T1(·) and T1(·) are transfers functions, reflecting government cash transfers programs, that depend on husband and wife’s earnings in the formal sector. ym,inf and yf,inf are the production functions in the informal sector. hg’ is the human capital of husband or wife in the following period. Note that children’s education is expressed in terms of formal goods prices.

Household problem in period 2

After children get married, parents live as a two-member household and choose consumption and labor supply in the formal and informal sectors. The state of a household at the beginning of this stage is given by their human capital (hf and hm). Their value functions are described below:

Vtj=2(hf,hm)=max{c,lm,fo,lm,inf,lf,fo,lf,inf}u()+βVt+1j=3(hf,hm)

subjected to

cfo(1+τc)pfo+cinfpinf(1τf())(1τss,f())wflf,fohf+(1τm())(1τss,m())wmlm,fohm+pinf(ym,inf+yf,inf)+T2()yg,inf=zinf[lg,inf]αinf,wheregenderg{m,f}hg=(1δ)hg+(1+lg,fo)αh,g{m,f}lg,fo+lg,inf1,g{m,f}lm,fo,lm,inf,lf,fo,lf,inf(0,1)

Household problem in period 3

In period 3 both husband and wife retire, receiving pensions from the government Tp(hm) and Tp(hf), respectively. The household in chooses consumption so as to maximize:

Vtj=3(hf,hm)=max{c}.u()

subjected to

Tp(hm)+Tp(hf)cfo(1+τc)pfo+cinfpinfTPg=TP¯+ρhg,wheregenderg{m,f}

A retiree receives a pension benefit composed of a constant flat amount (TP¯) and an amount dependent on how much he or she worked in the formal sector, which we approximate by using the human capital variable.

Formal Sector

A representative firm hires both male and female effective hours of labor to produce the formal good. Its maximization problem is given by:

max{Lf,fo,Lm,fo}Σt=0βt(1τυ)[pfozfo(Lm,fo+φLf,fo)αfo(1+τssf)(wmLm,fo+wfLf,fo)],

where ϕ is a parameter reflecting direct discrimination in the workplace, τυ is the tax on firms’ profits and τssf is the social security contribution rate paid by firms (employers). The firm’s profits (after taxes) are redistributed to the richest households (last decile of the income distribution).

Government Budget Constraint

The government taxes consumption, (formal) labor income and firms profits, and collects social security contributions. It spends on transfers to households, pension benefits, and formal goods (total expenditure on formal good equals to G). Its budget constraint must hold every period, and it states that the revenues from collections must be equal to the expenditures. Let C¯ be total expenditure in consumption goods (net of VAT) in this economy at time t Abstracting from the time subscript, the government budget constraint for each time t is the following:

τcC¯+[τf()+τss,f()τf().τss,f()+τssf]wfLf,fo+[τm()+τss,m()τm().τss,m()+τssf]wmLm,fo+τυ[pfozfo(Lm,fo+φLf,fo)αfo(1+τssf)(wmLm,fo+wfLf,fo)]=μ1T1()+μ2T2()+μ3[2TP¯+ρ(h3m+h3f)]+G

Description of the Steady State Equilibrium

We will consider a stationary equilibrium in which wages and prices are constant, and the distribution of human capital for both males and females at each period j are stationary. Let:

  • Γ1(h, ε) be the stationary distribution function of parents’ human capital and birth shock in period 1;

  • Γ2(hf,hm) and Γ3(hf,hm) be, respectively, periods 2 and 3 stationary distribution functions of husbands and wives’ human capital.

Letting μ12 and μ3 be the measure of households at each period in time, define the following aggregates:

  • Cfo (aggregate consumption of formal goods and kids’ education):
    Cfo=μ1θhϵcfo1(h,ϵ)dΓ1(h,ϵ)+μ2hfhmcfo2(hf,hm)dΓ2(hf,hm)+μ3hfhmcfo3(hf,hm)dΓ3(hf,hm)+μ1hfϵe(h,ϵ)dΓ1((h,ϵ)
  • Cfo (aggregate consumption of informal goods):
    Cinf=μ1θhϵcinf1(h,ϵ)dΓ1(h,ϵ)+μ2hfhmcinf2(hf,hm)dΓ2(hf,hm)+μ3hfhmcinf3(hf,hm)dΓ3(hf,hm)
  • Yfo = zfo(Lm,fo + (ϕLf,f0)αfo is the total production of formal goods

  • Yinf (production of informal goods):

Yinf=μ1zinfhϵ[(l1f,inf(h,ϵ))αinf+(l1m,inf(h,ϵ))αinf]dΓ1(h,ϵ)+μ2zinfhfhm[(l2m,inf(hf,hm))αinf+(l2f,inf(hf,hm))αinf]dΓ2(hf,hm)

A competitive equilibrium in this economy is comprised of: stationary distributions of human capital and birth shocks Γ1(h,ε), Γ2(hf,hm),Γ3(hf,hm), constant prices and wages pfo,pinf,wm,wf, together with households’ allocations of consumption, labor choices and investment in kids’ education, such that:

  • wm and wf solve the firm’s optimization problem

  • given prices pfo,pinf, wages wm,wf, transfers T1(·),T2(·) and pensions Tp(·), households choose consumption, labor supply, and investment in their children education that maximize their utilities, as described in their maximization problems

  • the government budget is balanced

  • the aggregates of this economy are constants and are given by Cfo, Cinf, Yfo, Yinf described above

  • all markets clear:

    • (i) female formal labor market clears:
      Lf,fo=μ1ϵhh1fh1f,fo(h,ϵ)dΓ1(h,ϵ)dhdϵ+μ2hfh2fl2f,fo(hf,hm)Γ2(hf,hm)dhf
    • (ii) male formal labor market clears:
      Lm,fo=μ1ϵhh1mh1m,fo(h,ϵ)dΓ1(h,ϵ)dhdϵ+μ2hmh2ml2m,fo(hf,hm)Γ2(hf,hm)dhm
    • (iii) formal goods market clears: Yfo = Cfo

    • (iv) informal goods market clears: Yinf = Cinf

Calibration Methodology

The model period is 20 years, so that agents work from 20 to 60 years of age, are retired from 60 to 80, and die at 80. Since all agents live and die at 80 years of age, the measure of households at each period must be equal to 1/3 (i.e., μ1 = μ2 = μ3 = 1/3).

Preferences. Households have log-linear preferences over formal and informal goods and disutility over total female labor supply (lf):

u(cfo,cinf,lf)=ξfolog(cfo)+ξinflog(cinf)ξllf,

We calibrate the shares of formal consumption ξfo and informal consumption ξinf to match household expenditure on formal and informal goods, respectively, using Argentina’s consumer price index weights (Índice de Precios al Consumidor, calculated by INDEC), and we estimate these shares to be 70 percent and 30 percent, respectively. Using the same source, parameter ηk (indicating preference over kids’ future utilities) is calibrated to match the share of private education in family expenditure in Argentina (2.9 percent). We calibrate ξl, the parameter that describes the utility cost from female labor supply, to match the female labor force participation in Argentina, which is 60 percent for females between 21 and 60 years old (according to the March 2017 household survey). The discount factor β is set to 0.96 annually (or 0.44 for every period of 20 years), which is a value commonly used in the economic literature. The parameter θ is set to 1.4, using OECD’s modified scale calculations for increase in household consumption when two kids are added in the household1.

Production. We normalize the price of formal sector to 1. The productivity zfo is calibrated to match the share of formal production on GDP (74 percent, estimated using 2014–2016 national accounts results published by INDEC), while the productivity of the informal sector zinf is normalized. We calibrate firm’s discrimination parameter ϕ to match ILO’s 2015 Global Wage Report unexplained wage gap in Argentina, which is 14.6 percent.

Initial Shocks. We set 10 initial shocks, that are calibrated so that the model matches each decile of Argentina’s income distribution, using the March 2017 household survey.

Human Capital Formation Function. We calibrate parameter αe to match Argentina’s share of private education over GDP (1.1 percent, as per 2014–2016 national accounts results published by INDEC).

Fiscal Policy. We set income tax functions τf(·) and τm(·) according to Argentina’s 2017 income tax brackets, including marginal rates and deductions. Similarly, we use employees’ social security contribution functions τss,f(·) and τss,m(·) according to Argentina’s 2017 tax code. In addition, employer’s social security rate is set to 22 percent, calculated through the household survey data using the current rules. Tax on consumption τc is set to Argentina’s average tax rate on consumption (20 percent). Corporate income tax rate is set to 35 percent. In terms of pensions, TP¯ is set to match Argentina’s minimal pension benefit (6,377 Argentinian pesos in 2017), and the parameter ρ is calibrated to match Argentina’s replacement rate of 88 percent (OECD, 2017). Finally, transfer functions T1(·) and T2(·) are calibrated to match Argentinians’ average cash transfers benefits recipients per income and per age group, using the 2017 household survey.

References

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  • World Bank’s 2016 “Women, Business and the Law

1

Prepared by Lisa Kolovich, Vivian Malta, Marina Mendes Tavares (all from SPR).

2

The index is constructed using indicators of empowerment, health, legal rights and financial access. The first two dimensions are captured by the United Nations’ Gender Inequality Index, but the index has drawn criticism for not capturing legal empowerment. To this end, the index is augment the index with information from the Women, Business and the Law database by using indicators from two dimensions that are also available back to 1960 in the World Bank’s 50 Years of Women’s Legal Rights database, accessing institutions, and using property.

3

Including health care, the reform implies a reduction in employees’ social security contribution rate of 3.4 percentage points and a decrease in the employer’s social security contribution rate of 5.2 percentage points.

4

This could require reducing legal barriers to female employment (for instance, based on the 2016 World Bank Women, Business and the Law, there are still tasks and occupations prohibited to women in Argentina) or through launching awareness campaigns on gender inequalities. Mechanically in the model we do this by altering the “discrimination parameter” (denoted with φ) from 0.85 to 1 (Annex).

Argentina: Selected Issues
Author: International Monetary Fund. Western Hemisphere Dept.