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Educación superior e ingresos laborales: estimaciones paramétricas y no paramétricas de la rentabilidad por niveles y carreras en el Perú

Author

Listed:
  • Gustavo Yamada

    (Universidad del Pacífico)

  • Juan F. Castro

    (Universidad del Pacífico)

Abstract

Si relacionamos el logaritmo del ingreso laboral con los años de educación a través de una especificación “minceriana” tradicional obtenemos que, en el Perú, el rendimiento de un año adicional de educación sería del orden del 10%. En la primera parte de este estudio, sin embargo, encontramos que los principales supuestos que permiten relacionar este porcentaje con el concepto de retorno no se verifican para el caso peruano. Proponemos hasta cinco estrategias más flexibles para modelar los salarios en función de la educación. Encontramos que cada año adicional de educación puede provocar un incremento en salarios que fluctúa entre 3.5% y casi 30%, dependiendo de si se trata de la instrucción básica o superior, o si estamos hablando de cursar el nivel o completar el nivel. Se confirman dos elementos característicos del mercado laboral peruano: (i) los rendimientos crecientes de la educación (o “convexificación” de los retornos); y (ii) la prima salarial asociada a completar cada nivel de instrucción (o “efecto diploma”). En la segunda parte del estudio, empleamos la metodología de cuantiles para estimar rendimientos diferenciados para la educación superior, distinguiendo entre distintos tipos de instrucción y familias de carreras universitarias. Asimismo, utilizamos los costos directos de la educación y proyectamos los ingresos laborales utilizando un método no paramétrico flexible para hallar indicadores de rentabilidad más precisos, tanto para el promedio del mercado laboral como para diversos puntos de la distribución. Encontramos: (i) que el nivel universitario y, al interior de éste, las carreras de Medicina e Ingeniería prometen el retorno más alto para aquellos con la habilidad necesaria para ubicarse en el 10% superior de ingresos; también dominan si tomamos en cuenta las pérdidas y ganancias potenciales bajo escenarios más extremos que el promedio; y (ii) que las carreras de Pedagogía y Otras Ciencias de la Salud no han permitido utilizar la habilidad para capitalizar los años de educación y, en términos monetarios, no deberían haber sido atractivas incluso después de incorporar consideraciones de riesgo. Por tanto, otras consideraciones, tales como restricciones financieras, de habilidades, de información y preferencias vocacionales, parecieran ser las razones que explican su alta participación en la fuerza laboral profesional.

Suggested Citation

  • Gustavo Yamada & Juan F. Castro, 2010. "Educación superior e ingresos laborales: estimaciones paramétricas y no paramétricas de la rentabilidad por niveles y carreras en el Perú," Working Papers 10-06, Centro de Investigación, Universidad del Pacífico.
  • Handle: RePEc:pai:wpaper:10-06
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    References listed on IDEAS

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    4. Gustavo Yamada, 2004. "Avances recientes," Chapters of Books, in: Gustavo Yamada (ed.), Economía laboral en el Perú: avances recientes y agenda pendiente, edition 1, volume 1, chapter 1, pages 11-42, Fondo Editorial, Universidad del Pacífico.
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    Cited by:

    1. World Bank, 2011. "Strengthening Skills and Employability in Peru : Final Report," World Bank Publications - Reports 12533, The World Bank Group.
    2. Juan F. Castro & Gustavo Yamada & Omar Arias, 2011. "Higher education decisions in Peru : on the role of financial constraints, skills, and family background," Working Papers 11-14, Centro de Investigación, Universidad del Pacífico.
    3. Ana Luna & Miguel Nuñez-del-Prado & Jose Luján & Luis Mantilla García & Daniel Malca, 2017. "Alternative setup for estimating reliable frequency values in a ripple tank," Working Papers 17-01, Centro de Investigación, Universidad del Pacífico.
    4. Pablo Lavado & Jamele Rigolini & Gustavo Yamada, 2015. "Giving Peru a productivity boost : towards a system of continuous education and training," Working Papers 15-16, Centro de Investigación, Universidad del Pacífico.
    5. Robles, Adrian & Robles, Marcos, 2016. "Changes in Welfare with a Heterogeneous Workforce: The Case of Peru," IDB Publications (Working Papers) 7507, Inter-American Development Bank.
    6. Juan F. Castro & Gustavo Yamada, 2012. "“Convexification” and “deconvexification” of the peruvian wage profile: a tale of declining education quality," Working Papers 12-02, Centro de Investigación, Universidad del Pacífico.
    7. Luis García & Sara Sánchez, 2020. "Acerca de la relación entre el gasto por alumno y los retornos a la educación en el Perú: un análisis por cohortes," Documentos de Trabajo / Working Papers 2020-482, Departamento de Economía - Pontificia Universidad Católica del Perú.

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