IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp5210.html
   My bibliography  Save this paper

Returns to Education in Four Transition Countries: Quantile Regression Approach

Author

Listed:
  • Staneva, Anita

    (Griffith University)

  • Arabsheibani, Reza

    (London School of Economics)

  • Murphy, Philip D.

    (Swansea University)

Abstract

This paper uses quantile regression techniques to analyze heterogeneous patterns of return to education across the conditional wage distribution in four transition countries. We correct for sample selection bias using a procedure suggested by Buchinsky (2001), which is based on a Newey (1991, 2009) power series expansion. We also examine the empirical implications of allowing for the endogeneity of schooling, using the control function approach proposed by Lee (2007). Using household data from Bulgaria, Russia, Kazakhstan and Serbia in 2003, we show that the return to education is heterogeneous across the earnings distribution. It is also found that accounting for the endogeneity of schooling leads to a higher rate of return to education.

Suggested Citation

  • Staneva, Anita & Arabsheibani, Reza & Murphy, Philip D., 2010. "Returns to Education in Four Transition Countries: Quantile Regression Approach," IZA Discussion Papers 5210, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp5210
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp5210.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Federico Favata & Sofia Zamparo, 2021. "Estimación del efecto de la segregación ocupacional por sexo en el ingreso laboral para Argentina (2016-2020)," Asociación Argentina de Economía Política: Working Papers 4467, Asociación Argentina de Economía Política.
    2. Javier Alejo & Leonardo Gasparini & Gabriel Montes-Rojas & Walter Sosa-Escudero, 2024. "A decomposition method to evaluate the ‘paradox of progress’, with evidence for Argentina," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 22(2), pages 453-472, June.
    3. Stoilova, Rumiana & Simeonova-Ganeva, Ralitsa & Kotzeva, Tatyana, 2011. "The Impact of Gender on Mid-Career Labour Income: The Case of Bulgaria," MPRA Paper 53353, University Library of Munich, Germany, revised 2011.
    4. Tindara Addabbo & Donata Favaro & Stefano Magrini, 2012. "Gender differences in productivity rewards: the role of human capital," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 59(1), pages 81-110, March.
    5. Niels-Hugo Blunch, 2018. "Just like a woman? New comparative evidence on the gender income gap across Eastern Europe and Central Asia," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 8(1), pages 1-41, December.
    6. Tamar Khitarishvili, 2018. "Gender Pay Gaps in the Former Soviet Union: A Review of the Evidence," Economics Working Paper Archive wp_899, Levy Economics Institute.
    7. Rosalia Castellano & Gennaro Punzo, 2016. "Patterns of earnings differentials across three conservative European welfare regimes with alternative education systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(1), pages 140-168, January.

    More about this item

    Keywords

    rate of return to education; endogeneity; quantile regression; sample selection;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • I2 - Health, Education, and Welfare - - Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp5210. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.