## backgroundpaper1

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---

### Introduction: role of labor force growth and demographics
- More than 40 percent of GDP growth over the last two decades can be attributed to the expanding labor input.
- Drivers of labor growth:
  - Population growth has been the largest contributor.
  - A demographic shift that increased the share of the working-age population (the “demographic dividend”) was the next largest contributor.
  - Labor market outcomes (participation and employment rates) played a more limited role:
    - Modest increases in the overall participation rate during 2000–10 followed by minor decreases thereafter resulted in a negligible contribution of participation rates over the past two decades.
    - Increases in employment rates can explain roughly 0.3 percentage points of the labor force growth on average.
- Demographic outlook and growth implications:
  - The region is aging and the “demographic dividend” is coming to an end due to falling fertility rates and an aging population.
  - A growth accounting exercise estimates that demographic changes could reduce annual GDP growth rates by 0.3 percentage points on average over the next decade.
- Potential mitigation:
  - Increasing labor force participation is highlighted as a potential way to mitigate the negative impact of demographic changes on labor supply and to help sustain economic growth.
  - The paper uses detailed microdata from several Latin American household surveys to document patterns, assess changes (including pandemic effects), analyze determinants, identify critical demographic groups, and explore interactions with informality.
- Historical participation trends:
  - More than 10 percentage points increase in labor force participation for the overall population between the 1950s and 2010.
  - Nearly 25 percentage points increase among the prime working-age population (25–54 years old) over the same period, driven by women entering the labor force.
  - Since 2010, participation rates have plateaued and show uneven levels across gender and age groups.

### Obstacles to women’s labor force participation
- Overview and magnitude:
  - Women in Latin America continue to face numerous obstacles to labor force participation, with unpaid work, including household work, explaining most of the remaining participation gap.
  - Participation gaps widen after parenthood, as women often permanently exit the labor force while men’s participation remains largely unaffected.
  - Substantial heterogeneity across and within countries, particularly by education.
- Unpaid work and household responsibilities:
  - Observable characteristics (age, education, household composition, location) explain, at best, a minimal share of participation gaps:
    - In Mexico and Peru, these factors help explain about 3 and 2 percentage points of the gap, leaving 29 and 10 percentage points unexplained, respectively.
    - In Argentina, Brazil, and Uruguay, observable characteristics suggest the actual effective gap is even larger than the observed gap because women are generally more educated.
  - Women are systematically more likely to report household responsibilities as the main reason for inactivity:
    - In Mexico and Paraguay, household work is the reported reason for inactivity for about two thirds of women who are out of the labor force as opposed to only about a tenth of men.
    - In every country in the sample, women are at least five times more likely than men to report household work as the main reason for inactivity.
  - Attitudes toward gender roles:
    - In Paraguay and Mexico, about 50 percent and 40 percent of respondents, respectively, agree or strongly agree with “It is better that women concentrate on the home and men on work,” compared with 22 percent on average in the six other sample countries (Latinobarómetro 2023).
  - Unpaid care and domestic work valued at market prices are estimated between 15 percent (Ecuador) and 24 percent of GDP (Mexico).
  - The 2025 System of National Accounts update will include "unpaid household service work" in macroeconomic statistics as an extended account (not in GDP).
  - Labor supply elasticity: women’s labor supply is particularly responsive to changes in income (higher elasticity), which can hinder participation and create policy opportunities (e.g., remittances tend to dampen female participation).
- Parenthood and the “motherhood effect”:
  - Female labor force participation drops sharply around motherhood; male participation is largely unaffected or slightly increases.
  - Cross-country heterogeneity:
    - The drop in participation rates in the year after childbirth is smaller and less pronounced in higher-income countries (Uruguay, Chile).
    - In middle-income countries, especially in Brazil and Colombia, the drop is sharper and plateaus around 20 percent.
  - Motherhood effects are estimated to account for about a third of the overall gender participation gap.
  - In Mexico, grandmothers’ deaths can reduce mothers’ employment rate by 13 percentage points.
  - Informality and parental leave:
    - In many countries (for instance, Peru), informality among women drops around motherhood because mothers in formal jobs can use maternal leave, while women in informal jobs typically must exit the labor force; when re-entering, mothers are more likely to take informal jobs that allow flexible hours.
    - Higher informality rates for women after childbirth are also observed in countries with lower overall formality rates such as Chile.
- Childcare and complementary policies:
  - Childcare policies can substantially raise women’s labor force participation:
    - Some studies indicate successful policies can raise participation of the eligible women population by 5 to 15 percentage points (examples include expanding preschool care in Argentina, Chile, and Uruguay, and extending school day programs in Mexico).
  - Childcare policies also deliver benefits for early childhood development and nutrition with positive long-term productivity effects.
  - Other policies: improving safety, transportation, targeted skill training, and measures to encourage cultural change in gender norms.
  - Fiscal note: some policies may be fiscally costly; a full cost-benefit analysis is necessary.
- Interplay between participation and informality:
  - Informality prevalence:
    - In Argentina, Colombia, Mexico, Paraguay, and Peru, the majority of jobs are informal; Chile and Uruguay have informality below one third of the workforce; Brazil is intermediate.
    - Formal jobs are concentrated among prime-age workers; young and older workers face elevated informality, with many older workers working informally into their late 70s (especially in Mexico).
    - A large fraction of women are informally employed as domestic workers where informality incidence is typically above 80 percent; transportation, security, and construction informal jobs are overwhelmingly held by men.
  - Past reform evidence:
    - Uruguay reduced informality by 17 percentage points between 2004 and 2014 while increasing labor force participation by more than 5 percentage points, aided by coordinated policies including measures for domestic workers and maternity leaves.
  - Aggregate and subnational relationships:
    - At the aggregate level, informality and labor force participation appear positively correlated across countries; in Peru and Mexico, higher informality is associated with larger participation.
    - Subnational evidence indicates heterogeneity:
      - For countries with relatively lower informality rates (Chile, Brazil), decreases in informality are associated with lower participation rates for both men and women, especially in urban areas.
      - For countries with higher informality levels (Peru, Mexico), the opposite holds.
    - An increase of one percentage point of informality in Mexico is associated with a decline of 0.38 percentage points in total LFP.
  - Labor market dynamics and productivity:
    - Informal workers experience more frequent job-to-job transitions and higher separation rates.
    - Job separation rates in the region are about twice higher than in advanced economies, contributing to higher frictional unemployment.
    - Excess job turnover and frequent switches across sectors and occupations hinder on-the-job human capital accumulation and reduce returns to education, dampening incentives to join the labor force.

### Exit to unemployment rates, estimated effects by gender, and policy implications
- Key takeaways on participation and gender gaps:
  - Latin America’s average participation gender gap remains about 20 percentage points, comparable to peer economies but twice as large as the average gap across advanced economies.
  - Female participation rates start declining from a relatively early age; women exit the labor force sooner than men and sooner than women in advanced economies.
  - Around 20 percent of young people are neither employed nor enrolled in education or training; a significant part of youth inactivity is explained by women not entering the labor force upon completion of education.
  - Closing gender participation gaps to levels comparable to advanced economies can increase annual GDP growth rates by around half a percentage point per year over the span of a decade.
  - With growth in most of these economies expected to be around 2 percent per year in the next five years, closing the gender gap would represent a sizable boost.
  - Working women in Latin America and the Caribbean earn, on average, 30 percent less than men.
  - By 2020, around 6.5 percent of the population of Latin American and Caribbean (LAC) region was residing abroad; remittances reduce labor force participation rates for both genders, with a stronger effect for women.
- Growth-accounting and scenarios:
  - Growth accounting framework: ΔY_it = α ΔL_it + (1−α) ΔK_it + Δω.
  - Labor identity: ΔL_it = ΔN_it + ΔWAP_it + ΔLFPR_it + ΔER_it.
  - Counterfactuals use Penn World Table data and UN Population Prospects; baseline comparison is 2010–19 observed growth.
  - Estimated change in average annual GDP growth:
    - Observed 2010–19 average: roughly 2.8 percent.
    - Projected (with demographic changes, holding other factors at 2010–19 levels): decreases to 2.5 percent on average per year.
  - Scenarios for closing gender gaps (female participation increases; male participation constant):
    - “Scenario 1”: increase female participation so gender gap ≈ 15 percent (close to Peru and Uruguay).
    - “Scenario 2”: increase female participation so gender gap ≈ 10 percent (similar to advanced economies).
    - “Scenario 3”: close the gender gap completely (women’s participation same as men’s).
  - Effects of scenarios:
    - Scenario 2 would increase annual GDP growth rates by almost half a percentage point per year.
    - Scenario 3 would more than offset the negative demographic effect for all countries in the sample.
  - Note: same overall participation improvements could be achieved by increasing participation among youth and/or older workers instead of only raising female participation.
- Pandemic-era trends and shift-share decomposition (2013–19 and 2019–23):
  - Regional patterns:
    - Pre-pandemic (2013–19): female participation generally increased (except in Colombia); male participation generally declined (except Paraguay), especially among young men.
    - Post-pandemic (2019–23): no clear uniform pattern for female participation; continued decline in participation among young men; decline in participation rates for both genders among older adults (above 55), with participation of those above 55 not recovered to pre-pandemic levels.
  - Shift-Share Analysis (selected exact figures preserved)
    - 2013–19 — Total population: LFPR Change -0.1; Population Shift -0.4; Participation Shift 0.3
    - 2013–19 — Female Total: LFPR Change 1.1; Population Shift -0.6; Participation Shift 1.6
    - 2013–19 — Male Total: LFPR Change -1.4; Population Shift -0.3; Participation Shift -1.2
    - 2019–23 — Total population: LFPR Change -1; Population Shift -0.2; Participation Shift -0.8
    - 2019–23 — Female Total: LFPR Change -0.6; Population Shift -0.3; Participation Shift -0.2
    - 2019–23 — Male Total: LFPR Change -1.5; Population Shift -0.1; Participation Shift -1.4
- Remittances and migration effects:
  - Macro regressions (1991–2019) show countries with a higher share of remittances in GDP have lower labor force participation rates for both genders, with a stronger negative effect for women.
  - Mexico has the strongest estimated negative effect of remittances on female LFPR among the LA8, followed by Colombia.
  - Microdata from Colombia: outmigration reduces labor force participation, stronger negative effect for women; effect increases with remittance value and declines with educational attainment.
- Regression estimate (exact):
  - For every one percentage point increase in the remittances share of GDP, the female labor force participation rate is expected to decrease by 0.5 percentage points, and the male labor force participation rate is expected to decrease by 0.18 percentage points, holding all other factors constant.
- Policy implications and recommendations (selected):
  - Relax constraints to entering and participating fully in the labor force, with a focus on policies that increase women’s participation.
  - Improve availability and affordability of childcare and parental benefits.
  - Promote more flexible work arrangements; reform tax and benefits systems to reduce fiscal costs for second earners (individualize taxation, increase progressivity, eliminate asymmetries in parental benefits).
  - Encourage women’s involvement in careers with acute skill shortages (such as STEM).
  - Increase statutory retirement ages and/or provide incentives to have longer careers.
  - Improve availability and affordability of care services for grandmothers and women who leave careers to care for aging parents.
  - Address youth inactivity with vocational training or short-cycle programs.

### Measurement methods, evidence on parental policies, informality metrics, and labor-market dynamics
- Fiscal policy, taxation, and parental benefits:
  - Individualize tax systems and increase progressivity of PIT and SSC to strengthen incentives for women to work.
  - Country tax design notes:
    - As of 2022, some Latin American countries (e.g., Brazil, Peru) allowed for optional joint taxation.
    - Argentina, Brazil, and Colombia contain family-based provisions that impose additional tax burdens for married women.
    - Argentina: allowance for a dependent spouse if their spouse earns below a certain (low) threshold.
    - Brazil: formal workers entitled to a tax-free allowance for each dependent regardless of earnings.
    - Colombia: allowance for a single dependent up to a maximum of 10 percent of gross income; recent reforms added fixed deductions for up to four additional dependents.
  - Maternity leave and coverage:
    - Paid maternity leave ranges from 12 weeks in Mexico to 18 weeks in Chile in the Latin American countries included in the TaxFit simulation model.
    - Formal employees are granted maternity leave in all countries in the region.
    - Self-employed are covered only in Brazil, Chile, Colombia, Peru, and El Salvador if they have a minimum number of months of contributions to social security before taking leave.
    - Eligible self-employed mothers receive a replacement wage based on prior taxable income; example: 40 percent in Colombia.
    - In Colombia, although maternity leave is 18 weeks, the last 6 can be transferred to the father as parental leave.
    - Fathers: paternity leave entitlements vary — 2 days in Argentina, up to 2-weeks of paid leave in Colombia.
  - Childcare financing and coverage:
    - Over the last decade, the average Latin American country has allocated less than 0.5 percent of GDP to early childhood care and education, compared to over 0.7 percent of GDP on average in the OECD.
    - Policy options: subsidized childcare or tax credits (including refundable credits), implementing quality standards, providing home-care training services, guaranteeing access and affordability in remote regions.
    - Examples: Brazil state guarantees for vulnerable families; Chile’s “Chile Crece Contigo” childcare subsidies; Colombia childcare tax deductions (benefit only tax-paying parents).
- Informality measurement alternatives (Brazil example):
  - Three definitions for informality:
    - Definition 1: no social security contribution (standard criterion).
    - Definition 2: for self-employed, whether business is formally registered in CNPJ; expressed as "No CTPS and no CNPJ".
    - Definition 3: for employees, whether they have a formal contract (CTPS); expressed as "No CTPS".
  - Empirical patterns:
    - Around 41 percent of workers are equally classified as informal under Definitions 1 and 2.
    - Among those, almost half are employees without a CTPS (Definition 3) and half are self-employed without CNPJ.
    - The share of informal self-employed workers increases steadily from the age of 40.
    - Behavioral responses to pension system age thresholds are significant and can affect observed informality at older ages.
- Econometric and decomposition methods:
  - Oaxaca-Blinder decomposition: Δ ȳ = β̂_1 (X̄_1 − X̄_2) [Endowment effect] + (α̂_1 − α̂_2) + (β̂_1 − β̂_2) X̄_2 [Coefficient effect].
  - Event-study method for motherhood penalties uses panel data around birth of first child, includes dummies for event time (excluding reference year −1), age, and year. Percentage effects defined as P_t^g ≡ α̂_t^g / E[Ŷ_it^g | t].
  - Excess job turnover approach builds on Donovan and others (2023) linking Log GDP per capita to job-to-job transitions.

### Annex evidence: job-to-job transitions and occupation switching (exact regression results and interpretations)
- Annex Table 2.1 — Job-to-Job Transition Rates by Formality Status (selected exact coefficients and statistics)
  - Dependent variables: (1) Informal to Formal; (2) Formal to Informal; (3) Formal to Formal; (4) Informal to Formal; (5) Formal to Informal; (6) Formal to Formal.
  - Coefficients for Log GDP per capita:
    - Column (1): -0.034*** (0.009)
    - Column (2): -0.028*** (0.004)
    - Column (3): -0.015 (0.012)
    - Column (4): -0.011 (0.009)
    - Column (5): -0.019*** (0.003)
    - Column (6): 0.001 (0.006)
  - Coefficients for LAC dummy:
    - Column (2): 0.085*** (0.014)
    - Column (5): 0.034*** (0.006)
    - Column (6): 0.049*** (0.015)
  - Observations: 598, 598, 476, 598, 598, 476 (columns (1)–(6))
  - R-squared: 0.176, 0.531, 0.097, 0.533, 0.779, 0.406 (columns (1)–(6))
  - Mean of dependent variable: 0.071, 0.023, 0.037, 0.071, 0.023, 0.037 (columns (1)–(6))
  - Notes: Standard errors clustered by country. *p<.05, **p<.01, ***p<.001.
  - Interpretation: LAC countries have higher job-to-job transitions and higher occupation switching rates, hampering accumulation of sector-specific human capital.
- Annex Table 2.2 — Labor Market Flows by Formality Status (selected exact coefficients and statistics)
  - Dependent variables: (1) Job-to-Job; (2) Switch of Occupations; (3) Job-to-Job; (4) Switch of Occupations.
  - Coefficients for Log GDP per capita:
    - Column (1): -0.031*** (0.011)
    - Column (2): -0.073*** (0.013)
    - Column (3): -0.01 (0.007)
    - Column (4): -0.037*** (0.01)
  - Coefficients for LAC dummy:
    - Column (2): 0.073*** (0.012)
    - Column (4): 0.149*** (0.021)
  - Observations: 494, 553, 494, 553 (columns (1)–(4))
  - R-squared: 0.258, 0.316, 0.68, 0.691 (columns (1)–(4))
  - Mean of dependent variable: 0.050, 0.105, 0.050, 0.105 (columns (1)–(4))
  - Interpretation: LAC countries show higher occupation switching in addition to higher job-to-job transition rates, reducing opportunities to accumulate sector-specific human capital and reinforcing lower labor productivity and lower returns on education.

*International Monetary Fund | backgroundpaper1 (backgroundpaper1.pdf), Regional Economic Outlook — Western Hemisphere, October 2024.*

### 1. Introduction

### 1. Introduction

### Role of labor force growth in Latin America
- More than 40 percent of GDP growth over the last two decades can be attributed to the expanding labor input.
- A large portion of labor growth has come from demographic factors:
  - Population growth has been the largest contributor.
  - A demographic shift that increased the share of the working-age population (the “demographic dividend”) was the next largest contributor.
- Labor market outcomes (participation and employment rates) have played a more limited role:
  - Modest increases in the overall participation rate during 2000–10 followed by minor decreases thereafter resulted in a negligible contribution of participation rates over the past two decades.
  - Increases in employment rates can explain roughly 0.3 percentage points of the labor force growth on average.

### Demographic trends and projected impact on growth
- The region is aging and the “demographic dividend” is coming to an end due to falling fertility rates and an aging population.
- All else equal, lower future contributions from the working-age population imply lower economic growth going forward.
- A growth accounting exercise estimates that demographic changes could reduce annual GDP growth rates by 0.3 percentage points on average over the next decade.

### Potential role of raising labor force participation
- Increasing labor force participation is highlighted as a potential way to mitigate the negative impact of demographic changes on labor supply and to help sustain economic growth.
- The paper uses detailed microdata from several Latin American household surveys to:
  - Document key patterns in labor market participation.
  - Assess changes in participation (including pandemic effects).
  - Analyze potential determinants of participation patterns.
  - Identify demographic groups that can critically shape the labor force going forward.
  - Explore interactions between these factors and pervasive labor market informality.

### Transition to trends (preview of Section 2)
- Latin America experienced a significant historical rise in participation:
  - More than 10 percentage points increase in labor force participation for the overall population between the 1950s and 2010.
  - Nearly 25 percentage points increase among the prime working-age population (25–54 years old) over the same period, driven by women entering the labor force.
- Since 2010, participation rates have plateaued and show uneven levels across gender and age groups.

*International Monetary Fund | backgroundpaper1 - 1. Introduction*

### 3. Obstacles to Women’s Labor Force Participation

### 3. Obstacles to Women’s Labor Force Participation

### Overview
- Women in Latin America continue to face numerous obstacles to labor force participation, with unpaid work, including household work, explaining most of the remaining participation gap.
- Participation gaps widen after parenthood, as women often permanently exit the labor force while men’s participation remains largely unaffected.
- There is substantial heterogeneity both across and within countries, particularly along education levels.

### Unpaid work and household responsibilities
- A standard decomposition accounting for age, education, household composition, and location shows observable characteristics play, at best, a minimal role in participation gaps:
  - In Mexico and Peru, these factors help explain about 3 and 2 percentage points of the gap, leaving 29 and 10 percentage points unexplained, respectively.
  - In Argentina, Brazil, and Uruguay, observable characteristics suggest the actual effective gap is even larger than the observed gap because women are generally more educated.
- Women are systematically more likely to report household responsibilities (childcare, elderly care, chores) as the main reason for inactivity:
  - In Mexico and Paraguay, household work is the reported reason for inactivity for about two thirds of women who are out of the labor force as opposed to only about a tenth of men.
  - In every country in the sample, women are at least five times more likely than men to report household work as the main reason for inactivity.
- Variation in attitudes toward gender roles:
  - In Paraguay and Mexico, about 50 percent and 40 percent of respondents, respectively, agree or strongly agree with “It is better that women concentrate on the home and men on work,” compared with 22 percent on average in the six other sample countries (Latinobarómetro 2023).
- Unmeasured household output and national accounts:
  - Unpaid care and domestic work are estimated to range between 15 percent (Ecuador) and 24 percent of GDP (Mexico), when hours of domestic work are valued at their corresponding market price.
  - The 2025 System of National Accounts update will include "unpaid household service work" in macroeconomic statistics as an extended account (not in GDP).
- Labor supply elasticity:
  - Women’s labor supply is particularly responsive to changes in income (higher elasticity), which can both hinder participation and create policy opportunities (e.g., remittances tend to dampen female participation).

### Parenthood and the “motherhood effect”
- Female labor force participation drops sharply around motherhood; male participation is largely unaffected or slightly increases.
- Cross-country and income-level heterogeneity:
  - The drop in participation rates in the year after childbirth is smaller and less pronounced in higher-income countries (Uruguay, Chile).
  - In middle-income countries, especially in Brazil and Colombia, the drop is sharper and plateaus around 20 percent.
- Quantification and comparisons:
  - Motherhood effects are estimated to account for about a third of the overall gender participation gap.
  - Grandmothers are a major source of childcare; in Mexico, grandmothers’ deaths can reduce mothers’ employment rate by 13 percentage points.
- Informality and parental leave:
  - In many countries (for instance, Peru), informality among women drops around motherhood because mothers in formal jobs can use maternal leave, while women in informal jobs typically must exit the labor force; when re-entering, mothers are more likely to take informal jobs that allow flexible hours.
  - Higher informality rates for women after childbirth are also observed in countries with lower overall formality rates such as Chile.

### Childcare and complementary policies
- Childcare policies can substantially raise women’s labor force participation:
  - Some studies indicate successful policies can raise participation of the eligible women population by 5 to 15 percentage points (examples include expanding preschool care in Argentina, Chile, and Uruguay, and extending school day programs in Mexico).
  - Childcare policies also deliver benefits for early childhood development and nutrition with positive long-term productivity effects.
- Other policies that can boost female participation include improving safety, transportation, targeted skill training, and measures to encourage cultural change in gender norms.
- Fiscal considerations:
  - Some policies may be fiscally costly; a full cost-benefit analysis is necessary to assess desirability.

### Interplay between participation and informality
- Pervasive informality:
  - In Argentina, Colombia, Mexico, Paraguay, and Peru, the majority of jobs are informal; Chile and Uruguay have informality below one third of the workforce; Brazil is intermediate.
  - Formal jobs are concentrated among prime-age workers; young and older workers face elevated informality, with many older workers working informally into their late 70s (especially in Mexico).
  - Sectoral distribution: a large fraction of women are informally employed as domestic workers where informality incidence is typically above 80 percent; transportation, security, and construction informal jobs are overwhelmingly held by men.
- Past reform evidence:
  - Uruguay reduced informality by 17 percentage points between 2004 and 2014 while increasing labor force participation by more than 5 percentage points, aided by coordinated policies including measures for domestic workers and maternity leaves.
- Potential tradeoff and nuanced relationship:
  - At the aggregate level, informality and labor force participation appear positively correlated across countries; in Peru and Mexico, higher informality is associated with larger participation.
  - Subnational evidence indicates heterogeneity:
    - For countries with relatively lower informality rates (Chile, Brazil), decreases in informality are associated with lower participation rates for both men and women, especially in urban areas.
    - For countries with higher informality levels (Peru, Mexico), the opposite holds.
  - An increase of one percentage point of informality in Mexico is associated with a decline of 0.38 percentage points in total LFP.
- Labor market dynamics and productivity:
  - Informal workers experience more frequent job-to-job transitions and higher separation rates.
  - Job separation rates in the region are about twice higher than in advanced economies, contributing to higher frictional unemployment.
  - Excess job turnover and frequent switches across sectors and occupations hinder on-the-job human capital accumulation and reduce returns to education, dampening incentives to join the labor force.

*Italic: Source — backgroundpaper1 - 3. Obstacles to Women’s Labor Force Participation (backgroundpaper1.pdf), IMF Regional Economic Outlook — Western Hemisphere, October 2024.*

### 1. Exit to Unemployment Rates

### 1. Exit to Unemployment Rates

### Key takeaways on labor force participation and gender gaps
- Latin America experienced a significant increase in labor force participation in the five decades up to 2010; with male participation already high, deceleration in female participation led aggregate participation to plateau.
- Latin America’s average participation gender gap remains about 20 percentage points, comparable to peer economies but twice as large as the average gap across advanced economies.
- Female participation rates start declining from a relatively early age; women exit the labor force sooner than men and sooner than women in advanced economies.
- Around 20 percent of young people are neither employed nor enrolled in education or training; a significant part of youth inactivity is explained by women not entering the labor force upon completion of education.
- Closing gender participation gaps to levels comparable to advanced economies can increase annual GDP growth rates by around half a percentage point per year over the span of a decade.
- With growth in most of these economies expected to be around 2 percent per year in the next five years, closing the gender gap would represent a sizable boost.
- Working women in Latin America and the Caribbean earn, on average, 30 percent less than men and are often paid less for the same work, particularly among high-income earners.
- By 2020, around 6.5 percent of the population of Latin American and Caribbean (LAC) region was residing abroad; remittances are found to reduce labor force participation rates for both genders, with a stronger effect for women.

### Policy implications and recommendations
- Relax constraints to entering and participating fully in the labor force, with a focus on policies that increase women’s participation.
- Improve availability and affordability of childcare and parental benefits to reduce family-responsibility constraints (household chores and caring for relatives, especially tending to children).
- Promote more flexible work arrangements to adapt work patterns to family needs; such arrangements can also contribute to formalizing work.
- Reform tax and benefits systems to reduce fiscal costs for second earners (often women), including individualizing taxation, increasing progressivity, and eliminating asymmetries in parental benefits between men and women.
- Encourage women’s involvement in careers with acute skill shortages (such as STEM) to increase returns to education for women and improve incentives to work outside the home.
- Increase statutory retirement ages and/or provide incentives to have longer careers (for example, allowing workers to improve their pension by working past a minimum retirement age) to boost participation among older adults.
- Improve availability and affordability of care services to reduce participation constraints for grandmothers and women who leave careers to care for aging parents.
- Address youth inactivity with vocational training or short-cycle programs to equip young inactive and unemployed people with job-ready skills; vocational training can increase formal employment.

### Quantitative evidence and scenarios (growth accounting and participation)
- Growth accounting framework: ΔY_it = α ΔL_it + (1−α) ΔK_it + Δω
- Labor identity used: ΔL_it = ΔN_it + ΔWAP_it + ΔLFPR_it + ΔER_it
- Counterfactuals use Penn World Table data and UN Population Prospects projections; baseline comparison is 2010–19 observed growth.
- Estimated change in average annual GDP growth:
  - Observed 2010–19 average: roughly 2.8 percent.
  - Projected (with demographic changes, holding other factors at 2010–19 levels): decreases to 2.5 percent on average per year.
- Scenarios for closing gender gaps (female participation increases; male participation constant):
  - “Scenario 1”: increase female participation so gender gap ≈ 15 percent (close to Peru and Uruguay).
  - “Scenario 2”: increase female participation so gender gap ≈ 10 percent (similar to advanced economies).
  - “Scenario 3”: close the gender gap completely (women’s participation same as men’s).
- Effects of scenarios:
  - Scenario 2 would increase annual GDP growth rates by almost half a percentage point per year.
  - Scenario 3 would more than offset the negative demographic effect for all countries in the sample.
- Note: same overall participation improvements could be achieved by increasing participation among youth and/or older workers instead of only raising female participation.

### Pandemic-era trends and decomposition (Box 2)
- Periods analyzed: 2013–19 (pre-pandemic) and 2019–23 (post-pandemic).
- Pre-pandemic (2013–19): female participation generally increased (except in Colombia); male participation generally declined (except Paraguay), especially among young men.
- Post-pandemic (2019–23): no clear uniform pattern for female participation across countries and age groups; two regional patterns stand out:
  - Continued decline in participation among young men.
  - Decline in participation rates for both genders among older adults (above 55), and participation of those above 55 has not recovered to pre-pandemic levels.
- Shift-share decomposition: total change in participation = population share shift + participation rate shift (interaction term negligible for short periods).
- Box Table 2.1 — Shift-Share Analysis of Changes in Labor Force Participation Rates (exact figures preserved)
  - 2013–19
    - Total population: LFPR Change -0.1; Population Shift -0.4; Participation Shift 0.3
    - Female
      - 15-24: LFPR Change (blank); Population Shift -0.9; Participation Shift -0.2
      - 25-54: LFPR Change (blank); Population Shift -0.5; Participation Shift 1.2
      - 55-64: LFPR Change (blank); Population Shift 0.6; Participation Shift 0.4
      - 65+: LFPR Change (blank); Population Shift 0.3; Participation Shift 0.1
      - Total: LFPR Change 1.1; Population Shift -0.6; Participation Shift 1.6
    - Male
      - 15-24: LFPR Change (blank); Population Shift -1.2; Participation Shift -0.9
      - 25-54: LFPR Change (blank); Population Shift -0.5; Participation Shift -0.4
      - 55-64: LFPR Change (blank); Population Shift 0.9; Participation Shift 0.0
      - 65+: LFPR Change (blank); Population Shift 0.5; Participation Shift 0.1
      - Total: LFPR Change -1.4; Population Shift -0.3; Participation Shift -1.2
  - 2019–23
    - Total population: LFPR Change -1; Population Shift -0.2; Participation Shift -0.8
    - Female
      - 15-24: LFPR Change (blank); Population Shift -0.6; Participation Shift -0.2
      - 25-54: LFPR Change (blank); Population Shift -0.3; Participation Shift 0.3
      - 55-64: LFPR Change (blank); Population Shift 0.3; Participation Shift -0.1
      - 65+: LFPR Change (blank); Population Shift 0.2; Participation Shift -0.2
      - Total: LFPR Change -0.6; Population Shift -0.3; Participation Shift -0.2
    - Male
      - 15-24: LFPR Change (blank); Population Shift -0.7; Participation Shift -0.7
      - 25-54: LFPR Change (blank); Population Shift -0.1; Participation Shift -0.3
      - 55-64: LFPR Change (blank); Population Shift 0.4; Participation Shift -0.2
      - 65+: LFPR Change (blank); Population Shift 0.4; Participation Shift -0.3
      - Total: LFPR Change -1.5; Population Shift -0.1; Participation Shift -1.4
- Notes: LFPR = labor force participation rate. Total change equals the sum of the population shift, participation shift, and a second-order interaction term (omitted).

### Cross-border migration, remittances, and gender gaps (Box 3)
- Cross-border emigration reduces overall labor force participation rates across LAC; women are more susceptible due to higher elasticity of labor supply to income.
- Macro regressions (1991–2019) of female and male LFPR on remittances (as a share of GDP) and controls show:
  - Countries with a higher share of remittances in GDP have lower labor force participation rates for both genders.
  - The negative effect of remittances is stronger for women.
- Predicted effects across LA8 (Argentina, Brazil, Chile, Colombia, Mexico, Paraguay, Peru, Uruguay): Mexico has the strongest estimated negative effect of remittances on female LFPR, followed by Colombia.
- Microdata evidence from Colombia confirms outmigration reduces labor force participation, with a stronger negative effect for women; the effect increases with the value of remittances and declines with the level of educational attainment.

*Source: REGIONAL ECONOMIC OUTLOOK—Western Hemisphere, INTERNATIONAL MONETARY FUND | October 2024*

### 1.  Estimated Effects by Gender

### 1.  Estimated Effects by Gender

### Regression evidence on remittances and labor force participation
- For every one percentage point increase in the remittances share of GDP, the female labor force participation rate is expected to decrease by 0.5 percentage points, and the male labor force participation rate is expected to decrease by 0.18 percentage points, holding all other factors constant.
- Sources: World Bank, World Development Indicators; and IMF staff calculations.
- Notes: Additional regression controls include unemployment rate, GDP per capita, and country and year fixed effects.
- LA8 = Latin America 8 (Brazil, Chile, Colombia, Mexico, Paraguay, Peru, Uruguay).
- Participation rates are calculated defining working age as 15–64 (following the OECD).
- Authors of this section: Cassie Chen Xiang and Manuk Ghazanchyan.
- Colombia case: Colombia has about 6 percent of its population as international emigrants; detailed microdata from the household survey (Gran Encuesta Integrada de Hogares) were used with monthly data for the period 2017–19 for analysis.
- Interpretation: Consistent with Amuedo-Dorantes and Pozo (2006) and Hanson (2007), findings suggest remittances lead to an income effect that raises the reservation wage for non-migrating women and, hence, decreases domestic female labor force participation.

### Fiscal policy, taxation design, and gender gaps in labor supply (Box 4)
- Key policy levers to boost female labor force participation:
  - Individualize the tax system to treat each partner’s income separately rather than household-level taxation, thereby maximizing work incentives of secondary earners (often women).
  - Increase progressivity of personal income tax (PIT) and social security contribution systems to strengthen incentives for women to take up work, work more hours, and potentially shift toward formal employment.
  - Strengthen the social safety net by expanding parental benefits and childcare support.
- Country-specific tax design notes:
  - As of 2022, some Latin American countries (e.g., Brazil, Peru) allowed for optional joint taxation.
  - Argentina, Brazil, and Colombia contain family-based provisions that impose additional tax burdens for married women.
  - Argentina: allowance for a dependent spouse if their spouse earns below a certain (low) threshold.
  - Brazil: formal workers are entitled to a tax-free allowance for each dependent regardless of earnings.
  - Colombia: provided an allowance for a single dependent of up to a maximum of 10 percent of gross income; recent reforms added fixed deductions for up to four additional dependents.
- Evidence on progressivity:
  - In EMDEs with more progressive PIT and SSC systems, women tend to work longer hours (Box Figure 4.1).
- Parental leave and gendered labor supply:
  - Female labor force participation drops sharply around motherhood; male labor force participation is largely unaffected.
  - Female labor force participation rates are higher where the duration of paid maternity leave is longer, but only up to a certain point, after which excessively long maternity leave can lead to a decline in female labor force participation.
  - Male labor force participation is unrelated to paternal leave durations.
  - Incentives from parental policies depend on duration, eligibility requirements, and the wage replacement rate.
- Maternity leave and coverage in selected countries:
  - Paid maternity leave ranges from 12 weeks in Mexico to 18 weeks in Chile in the Latin American countries included in the TaxFit simulation model.
  - Formal employees are granted maternity leave in all countries in the region.
  - Self-employed are covered only in Brazil, Chile, Colombia, Peru, and El Salvador if they have a minimum number of months of contributions to social security before taking leave.
  - Eligible self-employed mothers receive a replacement wage based on prior taxable income; example: 40 percent in Colombia.
  - In Colombia, although maternity leave is 18 weeks, the last 6 can be transferred to the father as parental leave.
  - Fathers: paternity leave entitlements vary — 2 days in Argentina, up to 2-weeks of paid leave in Colombia.
- Childcare: availability, affordability, and quality
  - Over the last decade, the average Latin American country has allocated less than 0.5 percent of GDP to early childhood care and education, compared to over 0.7 percent of GDP on average in the OECD.
  - Policy options: subsidized childcare or tax credits (including refundable credits), implementing quality standards for childcare providers, providing home-care training services, guaranteeing access and affordability in remote regions.
  - Examples in the region:
    - Brazil: state guarantees of access and priority enrolment to socioeconomically vulnerable families.
    - Chile: “Chile Crece Contigo” program provides childcare subsidies for young children of low-income families.
    - Colombia: childcare tax deductions (benefit only tax-paying parents).
  - Caveats: Vulnerable groups face barriers to childcare services because informal workers often cannot access employer-supported services, or face logistical difficulties accessing childcare centers.

### Informality measurement for self-employed and older workers (Box 5)
- Problem: ILO definition of informality can interact with statutory pension age thresholds and reclassification behavior around retirement ages, potentially overstating informality for older workers.
- Three alternative measures constructed for Brazil (using PNAD Contínua):
  - Definition 1: no social security contribution (standard criterion).
  - Definition 2: for self-employed, whether their business is formally registered in the Cadastro Nacional de Pessoa Jurídica (CNPJ); also expressed as "No CTPS and no CNPJ" in Box Figure 5.1.
  - Definition 3: for employees, whether they have a formal contract guaranteed the legal benefits, known as the Carteira de Trabalho e Previdência Social (CTPS); also expressed as "No CTPS" in Box Figure 5.1.
- Rationale: Absence of CTPS (for employees) or CNPJ (for self-employed) is a more direct indicator of lack of compliance with labor, fiscal, and overall legislation, limited access to credit, and ineligibility to benefits and safety nets.
- Empirical patterns:
  - Around 41 percent of workers are equally classified as informal under Definitions 1 and 2.
  - Among those, almost half are employees without a CTPS (Definition 3) and half are self-employed without CNPJ.
  - The gap in informality between Definitions 1 and 2 is mostly due to an understatement of informality among prime-age workers because some voluntarily contribute to social security despite holding an informal job.
  - The share of informal self-employed workers increases steadily from the age of 40.
  - Behavioral responses to pension system age thresholds are significant and can affect observed informality at older ages.
- Author: Ana Paula Nothen Ruhe.

### Oaxaca-Blinder Decomposition (Annex 1)
- Purpose: Decompose the mean difference in an outcome between two groups into the portion attributable to observable features (endowment effect) and the portion unexplained (coefficient effect).
- Model setup:
  - Data generating process: y_i = α + β X_i + ε_i.
  - Predicted mean outcome for group g: ȳ_g = α̂_g + β̂_g X̄_g.
  - Outcome gap: Δ ȳ = (ȳ_1 − ȳ_2) = (α̂_1 + β̂_1 X̄_1) − (α̂_2 + β̂_2 X̄_2).
  - Decomposition: Δ ȳ = β̂_1 (X̄_1 − X̄_2) [Endowment effect] + (α̂_1 − α̂_2) + (β̂_1 − β̂_2) X̄_2 [Coefficient effect].
- Interpretation:
  - Endowment effect quantifies explained differences due to differences in observable characteristics X across groups (evaluated using group 1’s coefficients).
  - Coefficient effect represents the fraction of the gap not explained by observable features but by differences in the treatment of the same characteristics.
- Note: The error term is omitted because the average residual in OLS is zero by definition.

### Event-study method for estimating motherhood penalties (Annex 2)
- Method: Event study leveraging panel data on individuals who enter parenthood; compares changes in outcomes around the birth of first child (event time t = 0) for women versus men.
- Model (for each gender separately):
  - Y_ist_g = Σ_{j ≠ −1} α_{j}^g 1[j = t] + Σ_{k} β_{k}^g 1[k = age_is] + Σ_{y} γ_{y}^g 1[y = s] + ν_ist_g,
    - where Y_ist_g denotes the labor outcome for individual i of gender g ∈ {w, m} at event time t.
    - The first term includes dummies for each event time (excluding a reference year prior to childbirth); α̂_t^g captures the influence of childbirth on gender g in event year t relative to the reference year.
    - The subsequent terms include dummies for age and year to control non-parametrically for life cycle and time trends.
- Metrics:
  - Absolute outcomes are used (not logs) to include zero earnings or employment observations and to capture intensive and extensive margin responses.
  - Percentage effects: P_t^g ≡ α̂_t^g / E[Ŷ_it^g | t], where Ŷ_it^g is the predicted outcome omitting the event time coefficient’s influence (hypothetical outcome in absence of children).
  - Child penalty: mean impact of childbearing on women relative to men across a designated event time span.
- References: Kleven, Landais, and Søgaard (2019); Berniell and others (2023); Casas and others (forthcoming).

### Excess job turnover in LAC labor markets (Annex 3)
- Approach: Builds on Donovan and others (2023) linking countries’ level of development (Log GDP per capita) to measures of Job-to-Job transitions (transitions from informal to formal, formal to informal, and formal to formal).
- Findings summary:
  - Strong link between countries’ income levels and frequency of transitions between informal and formal jobs; workers in lower-income countries are more likely to switch between formal and informal jobs.
  - LAC countries drive a significant share of this relationship and stand apart from peers with much higher transition rates.
  - Transitions between formal jobs are also more frequent in LAC.
- Annex Table 2.1 documents these patterns for a large set of developing and developed countries with panel data tracking worker statuses over time.

*Source: backgroundpaper1 - 1.  Estimated Effects by Gender (PDF chapter/section).*

### Annex Table 2.1. Job-to-Job Transition Rates by Formality Status

### Annex Table 2.1. Job-to-Job Transition Rates by Formality Status

### Regression results: job-to-job transitions by formality (coefficients and standard errors)
- Dependent variables by column (as labeled in source):
  - (1) Informal to Formal
  - (2) Formal to Informal
  - (3) Formal to Formal
  - (4) Informal to Formal
  - (5) Formal to Informal
  - (6) Formal to Formal

- Coefficients for Log GDP per capita:
  - Column (1): -0.034*** (0.009)
  - Column (2): -0.028*** (0.004)
  - Column (3): -0.015 (0.012)
  - Column (4): -0.011 (0.009)
  - Column (5): -0.019*** (0.003)
  - Column (6): 0.001 (0.006)

- Coefficients for LAC (Latin American countries dummy), where reported:
  - Column (2): 0.085*** (0.014)
  - Column (5): 0.034*** (0.006)
  - Column (6): 0.049*** (0.015)

- Sample and fit statistics:
  - Observations: 598, 598, 476, 598, 598, 476 (corresponding to columns (1)–(6))
  - R-squared: 0.176, 0.531, 0.097, 0.533, 0.779, 0.406 (corresponding to columns (1)–(6))
  - Mean of dependent variable: 0.071, 0.023, 0.037, 0.071, 0.023, 0.037 (corresponding to columns (1)–(6))

- Notes on estimation:
  - Panel regressions of labor flows measures on log GDP per capita, with and without a dummy variable for LAC.
  - Standard errors clustered by country.
  - *p<.05, **p<.01, ***p<.001.

### Interpretation and substantive findings (text from source)
- LAC countries have higher job-to-job transitions and are characterized by higher occupation switching rates (harmonized at the one-digit International Standard Classification of Occupations 2008), which makes it more difficult for LAC workers to accumulate human capital and build sector-specific skills.
- These patterns highlight dysfunctions in LAC labor markets that can contribute to lower labor productivity and lower returns on education.

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### Annex Table 2.2. Labor Market Flows by Formality Status

### Regression results: job-to-job transitions and switches of occupations
- Dependent variables by column (as labeled in source):
  - (1) Job-to-Job
  - (2) Switch of Occupations
  - (3) Job-to-Job
  - (4) Switch of Occupations

- Coefficients for Log GDP per capita:
  - Column (1): -0.031*** (0.011)
  - Column (2): -0.073*** (0.013)
  - Column (3): -0.01 (0.007)
  - Column (4): -0.037*** (0.01)

- Coefficients for LAC (Latin American countries dummy), where reported:
  - Column (2): 0.073*** (0.012)
  - Column (4): 0.149*** (0.021)

- Sample and fit statistics:
  - Observations: 494, 553, 494, 553 (corresponding to columns (1)–(4))
  - R-squared: 0.258, 0.316, 0.68, 0.691 (corresponding to columns (1)–(4))
  - Mean of dependent variable: 0.050, 0.105, 0.050, 0.105 (corresponding to columns (1)–(4))

- Notes on estimation:
  - Panel regressions of job-to-job transitions on log GDP per capita, with and without a dummy variable for LAC.
  - Standard errors clustered by country.
  - *p<.05, **p<.01, ***p<.001.

### Interpretation and substantive findings (text from source)
- LAC countries show higher occupation switching in addition to higher job-to-job transition rates.
- Higher occupation switching reduces opportunities for accumulating sector-specific human capital, reinforcing lower labor productivity and lower returns on education in LAC.

*Sources: Donovan and others (2023); and IMF staff calculations.*

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_Source: https://www.imf.org/-/media/files/publications/reo/whd/2024/october/english/backgroundpaper1.pdf_