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Gender-Segmented Labor Markets and the Effects of Local Demand Shocks Juan Pablo Chauvin Research Department, Inter-American Development Bank 6th Urbanization and Poverty Reduction Research Conference Washington DC, Sept. 2019 JP Chauvin

  1. Gender-Segmented Labor Markets and the Effects of Local Demand Shocks Juan Pablo Chauvin Research Department, Inter-American Development Bank 6th Urbanization and Poverty Reduction Research Conference Washington DC, Sept. 2019 JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 1 / 17

  2. People, markets, cities... and policies Cities are engines of growth in developing-world countries But the economic opportunities are not equally accessible to everyone Policies can open the access to oportunities for some groups and reduce it for others Distributional effects are not always the intended JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 2 / 17

  3. Place-making policies Large investments in “place-making” policies around the world Literature on who benefits from these policies (Bartik 1991, and many that followed) Existing studies largely assume away gender But gender differences in the labor market are large, likely to matter JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 3 / 17

  4. This paper How do local labor and housing markets react to: Shocks to labor demand that favor male employment, vs. Shocks to labor demand that favor female employment Context: Brazil 1990s y 2000s Unit of observation: “microregions” Primarily decennial census data JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 4 / 17

  5. Intuition of the model JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 5 / 17

  6. Intuition of the model JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 5 / 17

  7. Intuition of the model JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 5 / 17

  8. Intuition of the model JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 5 / 17

  9. Intuition of the model JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 5 / 17

  10. Male-leaning shocks to labor demand JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 6 / 17

  11. Male-leaning shocks to labor demand JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 6 / 17

  12. Male-leaning shocks to labor demand JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 6 / 17

  13. Female-leaning shocks to labor demand JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 7 / 17

  14. Female-leaning shocks to labor demand JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 7 / 17

  15. Female-leaning shocks to labor demand JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 7 / 17

  16. Reduced-form relationship of interest ∆ t − t o Outcome j = α + β ∆ t − t o Labor Demand jG + δ Controls j , t 0 + ∆ t − t o ǫ jt for genders G = {M,W} Outcomes of interest Population (migration) Housing rents Employment and wages by gender Need exogenous variation for changes in labor demand for males and females JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 8 / 17

  17. Gender-specific Bartik shocks B G � g G j , t − t o = s ind , j , t 0 − j , ind , t − t 0 � �� � ind � �� � Local industry National growth in gender G ’s share at t 0 employment in industry for genders G = { M , W } Predicts gender-specific employment growth in region j over a given period, based on: The industries located in the region in the base year, and, How gender G employment grew in the rest of the country in those industries. JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 9 / 17

  18. Identification Recent research on Bartik-style (shift-share) shocks (Goldsmith Pinkham et al. 2019, Adão et al. 2018, Borusyak et al. 2018.) In this light, I assess the validity of identifying assumptions and find similar issues as Goldsmith-Pinkham et al. (2019) do in the U.S. context: The shares are correlated with baseline characteristics potentially endogenous (i.e. initial income and education levels) Pre-trends are present I introduce start-year level controls and lagged-growth controls After controls, shocks are uncorrelated with a large set of observable confounders JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 10 / 17

  19. Addressing identification concerns Figure: Gender-specific Bartik shocks and Female informality rate Simple Residualized Male shocks Female shocks JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 11 / 17

  20. Distributions of residualized shocks 1991-2010 Female Shocks Male Shocks JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 12 / 17

  21. Effects on Population Own-gender shocks Other-gender shocks Hypothesis tests Females Males Females Males (1)-(2) (3)-(4) (1) (2) (3) (4) ( χ 2 and p-val.) Panel A: Effects on aggregate working -age population Two decades (1991 - 2010) 0.15 0.60* 1.75 (0.21) (0.36) 0.19 The nineties (1991 - 2000) 0.23 0.76** 12.00 (0.21) (0.31) 0.00 The two thousands (2000 - 2010) 0.24 0.88*** 2.34 (0.34) (0.23) 0.13 Panel B: Effects on working-age population by gender Two decades (1991 - 2010) 0.10 0.63* 0.54 0.19 2.34 1.12 (0.22) (0.37) (0.36) (0.21) 0.13 0.29 The nineties (1991 - 2000) 0.22 0.78** 0.74** 0.23 8.35 11.60 (0.21) (0.32) (0.31) (0.20) 0.00 0.00 The two thousands (2000 - 2010) 0.21 0.90*** 0.87*** 0.26 2.80 1.90 (0.33) (0.24) (0.23) (0.36) 0.09 0.17 Note: All coefficients are estimated with SUR regression models with a common set of controls. Outcomes are measured restricting the sample to individuals aged 15 through 64, excluding individuals in school, employers, civil servants, and public security. Robust standard errors clustered at the mesoregion level in parentheses, except for the hypothesis tests. The hypothesis tests are Wald chi-square tests of the hypothesis H 0 : β males − β females = 0 on SUR models including the respective female and male regressions. JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 13 / 17

  22. Effects on Population Own-gender shocks Other-gender shocks Hypothesis tests Females Males Females Males (1)-(2) (3)-(4) (1) (2) (3) (4) ( χ 2 and p-val.) Panel A: Effects on aggregate working -age population Two decades (1991 - 2010) 0.15 0.60* 1.75 (0.21) (0.36) 0.19 The nineties (1991 - 2000) 0.23 0.76** 12.00 (0.21) (0.31) 0.00 The two thousands (2000 - 2010) 0.24 0.88*** 2.34 (0.34) (0.23) 0.13 Panel B: Effects on working-age population by gender Two decades (1991 - 2010) 0.10 0.63* 0.54 0.19 2.34 1.12 (0.22) (0.37) (0.36) (0.21) 0.13 0.29 The nineties (1991 - 2000) 0.22 0.78** 0.74** 0.23 8.35 11.60 (0.21) (0.32) (0.31) (0.20) 0.00 0.00 The two thousands (2000 - 2010) 0.21 0.90*** 0.87*** 0.26 2.80 1.90 (0.33) (0.24) (0.23) (0.36) 0.09 0.17 Note: All coefficients are estimated with SUR regression models with a common set of controls. Outcomes are measured restricting the sample to individuals aged 15 through 64, excluding individuals in school, employers, civil servants, and public security. Robust standard errors clustered at the mesoregion level in parentheses, except for the hypothesis tests. The hypothesis tests are Wald chi-square tests of the hypothesis H 0 : β males − β females = 0 on SUR models including the respective female and male regressions. JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 13 / 17

  23. Effects on housing rents 1991-2010 Female Male Hypothesis tests ( χ 2 and p-val.) Shock Shock (1) (2) (3) Effects on nominal housing rents 0.23 1.09*** 6.08 (0.27) (0.32) 0.01 Effects on residualized housing rents 0.15 0.71** 2.82 (0.25) (0.32) 0.09 Note: All coefficients are estimated with SUR regression models with a common set of controls. Outcomes are measured restricting the sample to individuals aged 15 through 64, excluding individuals in school, employers, civil servants, and public security. Robust standard errors clustered at the mesoregion level in parentheses, except for the hypothesis tests. The hypothesis tests are Wald chi-square tests of the hypothesis H 0 : β males − β females = 0 on SUR models including the respective female and male regressions. JP Chauvin (IADB-RES) Gender and Local Demand Shocks Washington DC, Sept. 2019 14 / 17

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