IDEAS home Printed from https://ideas.repec.org/a/ecm/emetrp/v77y2009i3p953-973.html
   My bibliography  Save this article

Unconditional Quantile Regressions

Author

Listed:
  • Sergio Firpo
  • Nicole M. Fortin
  • Thomas Lemieux

Abstract

We propose a new regression method to evaluate the impact of changes in the distribution of the explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered) influence function (RIF) of the unconditional quantile on the explanatory variables. The influence function, a widely used tool in robust estimation, is easily computed for quantiles, as well as for other distributional statistics. Our approach, thus, can be readily generalized to other distributional statistics. Copyright 2009 The Econometric Society.

Suggested Citation

  • Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
  • Handle: RePEc:ecm:emetrp:v:77:y:2009:i:3:p:953-973
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.3982/ECTA6822
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. J. P. Florens & J. J. Heckman & C. Meghir & E. Vytlacil, 2008. "Identification of Treatment Effects Using Control Functions in Models With Continuous, Endogenous Treatment and Heterogeneous Effects," Econometrica, Econometric Society, vol. 76(5), pages 1191-1206, September.
    2. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-1044, September.
    3. Guido W. Imbens & Whitney K. Newey, 2009. "Identification and Estimation of Triangular Simultaneous Equations Models Without Additivity," Econometrica, Econometric Society, vol. 77(5), pages 1481-1512, September.
    4. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444606, September.
    5. David Card & Thomas Lemieux & W. Craig Riddell, 2004. "Unions and Wage Inequality," Journal of Labor Research, Transaction Publishers, vol. 25(4), pages 519-562, October.
    6. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    7. John Dinardo & Thomas Lemieux, 1997. "Diverging Male Wage Inequality in the United States and Ganada, 1981–1988: Do Institutions Explain the Difference?," ILR Review, Cornell University, ILR School, vol. 50(4), pages 629-651, July.
    8. Javier Gardeazabal & Arantza Ugidos, 2005. "Gender wage discrimination at quantiles," Journal of Population Economics, Springer;European Society for Population Economics, vol. 18(1), pages 165-179, July.
    9. Rosa L. Matzkin, 2003. "Nonparametric Estimation of Nonadditive Random Functions," Econometrica, Econometric Society, vol. 71(5), pages 1339-1375, September.
    10. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    11. Thomas Lemieux, 2006. "Increasing Residual Wage Inequality: Composition Effects, Noisy Data, or Rising Demand for Skill?," American Economic Review, American Economic Association, vol. 96(3), pages 461-498, June.
    12. Nicole M. Fortin & Thomas Lemieux, 1998. "Rank Regressions, Wage Distributions, and the Gender Gap," Journal of Human Resources, University of Wisconsin Press, vol. 33(3), pages 610-643.
    13. James J. Heckman & Edward J. Vytlacil, 2000. "Local Instrumental Variables," NBER Technical Working Papers 0252, National Bureau of Economic Research, Inc.
    14. Jeffrey M. Wooldridge, 2004. "Estimating average partial effects under conditional moment independence assumptions," CeMMAP working papers CWP03/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. 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.
    16. Newey, Whitney K, 1994. "The Asymptotic Variance of Semiparametric Estimators," Econometrica, Econometric Society, vol. 62(6), pages 1349-1382, November.
    17. Jean-Pierre Florens & James Heckman & Costas Meghir & Edward Vytlacil, 2002. "Instrumental variables, local instrumental variables and control functions," CeMMAP working papers CWP15/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590, September.
    19. Lemieux, Thomas, 1998. "Estimating the Effects of Unions on Wage Inequality in a Panel Data Model with Comparative Advantage and Nonrandom Selection," Journal of Labor Economics, University of Chicago Press, vol. 16(2), pages 261-291, April.
    20. Thomas Lemieux, 2008. "The changing nature of wage inequality," Journal of Population Economics, Springer;European Society for Population Economics, vol. 21(1), pages 21-48, January.
    21. Andrew Chesher, 2003. "Identification in Nonseparable Models," Econometrica, Econometric Society, vol. 71(5), pages 1405-1441, September.
    22. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    23. David H. Autor & Lawrence F. Katz & Melissa S. Kearney, 2008. "Trends in U.S. Wage Inequality: Revising the Revisionists," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 300-323, May.
    24. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, vol. 12(4), pages 577-590, August.
    25. James Albrecht & Anders Bjorklund & Susan Vroman, 2003. "Is There a Glass Ceiling in Sweden?," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 145-177, January.
    26. Newey, Whitney K & Stoker, Thomas M, 1993. "Efficiency of Weighted Average Derivative Estimators and Index Models," Econometrica, Econometric Society, vol. 61(5), pages 1199-1223, September.
    27. Card, David, 1996. "The Effect of Unions on the Structure of Wages: A Longitudinal Analysis," Econometrica, Econometric Society, vol. 64(4), pages 957-979, July.
    28. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    29. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    2. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    3. Sarah Voitchovsky & Bertrand Maitre & Brian Nolan, 2012. "Wage Inequality in Ireland’s “Celtic Tiger” Boom," The Economic and Social Review, Economic and Social Studies, vol. 43(1), pages 99-133.
    4. Christoph Rothe, 2012. "Partial Distributional Policy Effects," Econometrica, Econometric Society, vol. 80(5), pages 2269-2301, September.
    5. Rothe, Christoph, 2010. "Nonparametric estimation of distributional policy effects," Journal of Econometrics, Elsevier, vol. 155(1), pages 56-70, March.
    6. Sergio P. Firpo & Nicole M. Fortin & Thomas Lemieux, 2018. "Decomposing Wage Distributions Using Recentered Influence Function Regressions," Econometrics, MDPI, vol. 6(2), pages 1-40, May.
    7. Pallab Kumar Ghosh & Jae Yoon Lee, 2016. "Decomposition of Changes in Korean Wage Inequality, 1998–2007," Journal of Labor Research, Springer, vol. 37(1), pages 1-28, March.
    8. Michel Lubrano & Abdoul Aziz Junior Ndoye, 2014. "Bayesian Unconditional Quantile Regression: An Analysis of Recent Expansions in Wage Structure and Earnings Inequality in the US 1992–2009," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(2), pages 129-153, May.
    9. Wang, Wen & Lien, Donald, 2018. "Union membership, union coverage and wage dispersion of rural migrants: Evidence from Suzhou industrial sector," China Economic Review, Elsevier, vol. 49(C), pages 96-113.
    10. Sonja C. Kassenboehmer & Mathias G. Sinning, 2014. "Distributional Changes in the Gender Wage Gap," ILR Review, Cornell University, ILR School, vol. 67(2), pages 335-361, April.
    11. Juan D. Barón & Deborah A. Cobb‐Clark, 2010. "Occupational Segregation and the Gender Wage Gap in Private‐ and Public‐Sector Employment: A Distributional Analysis," The Economic Record, The Economic Society of Australia, vol. 86(273), pages 227-246, June.
    12. Torgovitsky, Alexander, 2017. "Minimum distance from independence estimation of nonseparable instrumental variables models," Journal of Econometrics, Elsevier, vol. 199(1), pages 35-48.
    13. Pallab Ghosh & Jae Lee, 2016. "Decomposition of Changes in Korean Wage Inequality, 1998–2007," Journal of Labor Research, Springer, vol. 37(1), pages 1-28, March.
    14. Philippe Van Kerm, 2013. "Generalized measures of wage differentials," Empirical Economics, Springer, vol. 45(1), pages 465-482, August.
    15. Santiago Pereda Fernández, 2016. "Estimation of counterfactual distributions with a continuous endogenous treatment," Temi di discussione (Economic working papers) 1053, Bank of Italy, Economic Research and International Relations Area.
    16. Zhu, Rong, 2016. "Wage differentials between urban residents and rural migrants in urban China during 2002–2007: A distributional analysis," China Economic Review, Elsevier, vol. 37(C), pages 2-14.
    17. Deshpande, Ashwini & Goel, Deepti & Khanna, Shantanu, 2018. "Bad Karma or Discrimination? Male–Female Wage Gaps Among Salaried Workers in India," World Development, Elsevier, vol. 102(C), pages 331-344.
    18. de la Rica, Sara & Dolado, Juan J. & Llorens, Vanesa, 2005. "Ceiling and Floors: Gender Wage Gaps by Education in Spain," IZA Discussion Papers 1483, Institute of Labor Economics (IZA).
    19. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    20. Joseph G. Altonji & Prashant Bharadwaj & Fabian Lange, 2012. "Changes in the Characteristics of American Youth: Implications for Adult Outcomes," Journal of Labor Economics, University of Chicago Press, vol. 30(4), pages 783-828.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Unconditional Quantile Regressions (ECTA 2009) in ReplicationWiki

    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:ecm:emetrp:v:77:y:2009:i:3:p:953-973. 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.

    If CitEc recognized a bibliographic 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.

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