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Sesgo de selección y estimación de la brecha por género para Mar del Plata

Author

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  • Di Paola, Rosángela
  • Berges, Miriam

Abstract

El objetivo del trabajo, es estimar la brecha por género existente en el nivel de ingreso de quienes trabajan en la ciudad de Mar del Plata. Nuestras investigaciones anteriores para la ciudad, demostraron que los ingresos de las mujeres, con idéntica ocupación y características de capital humano que los hombres, sistemáticamente se ubicaban un 30% por debajo al de aquellos. La estimación consiste en medir la discriminación teniendo en cuenta la técnica de Blinder-Oaxaca que la descompone en dos partes o fuentes de explicación, una en función de las diferentes dotaciones de capital humano y características de las actividades realizadas por el grupo desfavorecido respecto al otro, y otra segunda, que surge como residual o diferencia entre la total, calculada para los valores medios de las variables y la parte ya explicada. Considerándose como "discriminación" a esta última. Los resultados indican la existencia de sesgo de selección negativo en la muestra y la discriminación corregida queda explicada finalmente un 78% por diferencias en las dotaciones de capital humano y ocupación de las mujeres y un 22% de discriminación residual o factores atribuibles a la estructura de los mercados

Suggested Citation

  • Di Paola, Rosángela & Berges, Miriam, 2000. "Sesgo de selección y estimación de la brecha por género para Mar del Plata," Nülan. Deposited Documents 891, Universidad Nacional de Mar del Plata, Facultad de Ciencias Económicas y Sociales, Centro de Documentación.
    • Handle: RePEc:nmp:nuland:891
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    References listed on IDEAS

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    1. Michael Sattinger (ed.), 2001. "Income Distribution," Books, Edward Elgar Publishing, volume 0, number 2018.
    2. Rodríguez, Elsa Mirta M. & Berges, Miriam & Casellas, Karina, 2000. "Food consumption and income distribution in Argentina," Nülan. Deposited Documents 882, Universidad Nacional de Mar del Plata, Facultad de Ciencias Económicas y Sociales, Centro de Documentación.
    3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    4. Goldin, Claudia & Polachek, Solomon, 1987. "Residual Differences by Sex: Perspectives on the Gender Gap in Earnings," American Economic Review, American Economic Association, vol. 77(2), pages 143-151, May.
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    Cited by:

    1. Mora, Jhon James & Arcila, Andrés Mauricio, 2014. "Brechas salariales por etnia y ubicación geográfica en Santiago de Cali || Wage Gap by Geographic Location and Ethnicity in Cali (Colombia)," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 18(1), pages 34-53, December.
    2. Actis Di Pasquale, Eugenio, 2001. "Desigualdad de remuneraciones entre hombres y mujeres. Un estudio de las estructuras distributivas y de las funciones de ingresos de los asalariados en el aglomerado Mar del Plata-Batán (1996-2000)," Nülan. Deposited Documents 561, Universidad Nacional de Mar del Plata, Facultad de Ciencias Económicas y Sociales, Centro de Documentación.

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