IDEAS home Printed from https://ideas.repec.org/a/kap/jecinq/v15y2017i3d10.1007_s10888-017-9355-9.html
   My bibliography  Save this article

Mean and quantile regression Oaxaca-Blinder decompositions with an application to caste discrimination

Author

Listed:
  • Gabriel Montes-Rojas

    () (Universitat Autònoma de Barcelona
    City University London)

  • Lucas Siga

    () (New York University-Abu Dhabi)

  • Ram Mainali

    (Ministry of Finance)

Abstract

Abstract This paper extends the Oaxaca-Blinder decomposition method to the quantile regression random-coefficients framework. Mean-based decompositions are obtained as the integration of the quantile regression decomposition process. This method allows identifying if the observed differences between two groups differ across quantiles, and if so, what is the contribution to the mean-based Oaxaca-Blinder decomposition. The proposed methodology is applied to the analysis of caste discrimination in Nepal. The results indicate that much of the discrimination occurs at the lowest quantiles, which implies that disadvantaged groups are the ones who suffer the most caste discrimination.

Suggested Citation

  • Gabriel Montes-Rojas & Lucas Siga & Ram Mainali, 2017. "Mean and quantile regression Oaxaca-Blinder decompositions with an application to caste discrimination," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(3), pages 245-255, September.
  • Handle: RePEc:kap:jecinq:v:15:y:2017:i:3:d:10.1007_s10888-017-9355-9
    DOI: 10.1007/s10888-017-9355-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10888-017-9355-9
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    2. V. Chernozhukov & I. Fernández-Val & A. Galichon, 2009. "Improving point and interval estimators of monotone functions by rearrangement," Biometrika, Biometrika Trust, vol. 96(3), pages 559-575.
    3. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    4. Victor Chernozhukov & Iv·n Fern·ndez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves Without Crossing," Econometrica, Econometric Society, vol. 78(3), pages 1093-1125, May.
    5. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    6. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    7. George J. Borjas, 1994. "Long-Run Convergence of Ethnic Skill Differentials: The Children and Grandchildren of the Great Migration," ILR Review, Cornell University, ILR School, vol. 47(4), pages 553-573, July.
    8. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    9. Banerjee, Biswajit & Knight, J. B., 1985. "Caste discrimination in the Indian urban labour market," Journal of Development Economics, Elsevier, vol. 17(3), pages 277-307, April.
    10. repec:spo:wpecon:info:hdl:2441/5rkqqmvrn4tl22s9mc4b6ga2g is not listed on IDEAS
    11. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    12. Oaxaca, Ronald L. & Ransom, Michael R., 1994. "On discrimination and the decomposition of wage differentials," Journal of Econometrics, Elsevier, vol. 61(1), pages 5-21, March.
    Full references (including those not matched with items on IDEAS)

    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:kap:jecinq:v:15:y:2017:i:3:d:10.1007_s10888-017-9355-9. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.