Decomposing the Gender Wage Gap with Sample Selection Adjustment: Evidence from Colombia

Alejandro Badel; Ximena Peña

doi:10.4067/S0718-88702010000200007

Authors

Alejandro Badel Federal Reserve Bank of St. Louis
Ximena Peña Universidad de los Andes

DOI:

https://doi.org/10.4067/S0718-88702010000200007

Keywords:

Gender gap, Mincer, wage, semiparametric, quantile regression, selection

Abstract

Despite the remarkable improvement of female labor market characteristics, a sizeable gender wage gap exists in Colombia. We employ quantile regression techniques to examine the degree to which current small differences in the distribution of observable characteristics can explain the gender gap. We find that the gap is largely explained by gender differences in the rewards to labor market characteristics and not by differences in the distribution of characteristics. We claim that Colombian women experience both a “glass ceiling effect’’ and also (what we call) a “quicksand floor effect” because gender differences in returns to characteristics primarily affect women at the top and the bottom of the distribution. Also, self selection into the labor force is crucial for gender gaps: if all women participated in the labor force, the observed gap would be roughly 50% larger at all quantiles

Downloads

Download data is not yet available.

Author Biography

Alejandro Badel, Federal Reserve Bank of St. Louis

Federal Reserve Bank of St. Louis

References

Albrecht, J., Björklund, A., & Vroman, S. (2003). Is there a glass ceiling in Sweden? Journal of Labor Economics, 21, 145–177.

Albrecht, J., Van Vuuren, A., & Vroman, S. (2009). Counterfactual distributions with sample selection adjustments: Econometric theory and an application to the Netherlands. Labour Economics, 16(4), 383–396. https://doi.org/10.1016/j.labeco.2009.01.002

Altonji, J. G., & Blank, R. (1999). Race and gender in the labor market. In O. Ashenfelter & D. Card (Eds.), Handbook of labor economics (Vol. 3, pp. 3143–3259). Elsevier. https://doi.org/10.1016/s1573-4463(99)30039-0

Andrews, D., & Schafgans, M. (1998). Semiparametric estimation of the intercept of a sample selection model. The Review of Economic Studies, 65(3), 497–517. https://doi.org/10.1111/1467-937x.00055

Blau, M., & Kahn, M. (1992). Race and gender pay differentials (NBER Working Paper No. 4120). National Bureau of Economic Research.

Buchinsky, M. (1998). The dynamics of changes in the female wage distribution in the USA: A quantile regression approach. Journal of Applied Econometrics, 13(1), 1–30. https://doi.org/10.1002/(sici)1099-1255(199801/02)13:1<1::aid-jae474>3.0.co;2-a

Butler, R., & Heckman, J. J. (1977). The government's impact on the labor market status of Black Americans: A critical review (NBER Working Paper 0183). National Bureau of Economic Research.

Carneiro, P., Loken, K., & Salvanes, K. (1998). A flying start? Maternity leave and long-term outcomes for mother and child [Unpublished manuscript]. University College London.

Cunningham, W. (2007). Minimum wages and social policy: Lessons from developing countries. World Bank Publications. https://doi.org/10.1596/978-0-8213-7011-7

De la Rica, S., Dolado, J., & Llorens, V. (2008). Ceilings or floors? Gender wage gaps by education in Spain. Journal of Population Economics, 21(3), 751–776. https://doi.org/10.1007/s00148-006-0128-1

Ganguli, I., & Terrell, K. (2005). Wage ceilings and floors: The gender gap in Ukraine's transition (IZA Discussion Paper 1776). Institute for the Study of Labor (IZA).

Greene, W. (2002). Econometric analysis (5th ed.). Prentice Hall.

Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica, 47(1), 153–161. https://doi.org/10.2307/1912352

Hoyos, A., Ñopo, H., & Peña, X. (2010). The persistent gender earnings gap in Colombia, 1994–2010 (RES Working Paper 4673). Inter-American Development Bank, Research Department.

Klein, R., & Spady, R. (1993). An efficient semiparametric estimator for binary response models. Econometrica, 61(2), 387–421. https://doi.org/10.2307/2951556

Machado, J., & Mata, J. (2005). Counterfactual decomposition of changes in wage distribution using quantile regression. Journal of Applied Econometrics, 20(4), 445–465. https://doi.org/10.1002/jae.788

Ñopo, H. (2006). The gender wage gap in Chile 1992–2003 from a matching comparisons perspective (Research Department Working Paper 562). Inter-American Development Bank.

Peña, X. (2006). Assortative matching and the education gap (Working Paper). Georgetown University.

Perticara, M. (2007). Brechas salariales por género en Chile: Un análisis de sensibilidad [Gender wage gaps in Chile: A sensitivity analysis] (ILADES-Georgetown University Working Paper 195). ILADES-Georgetown University, School of Economics and Business.

Perticara, M., & Bueno, I. (2009). Entendiendo las brechas salariales por género en Chile [Understanding gender wage gaps in Chile] (ILADES-Georgetown University Working Paper 212). ILADES-Georgetown University, School of Economics and Business.