IDEAS home Printed from https://ideas.repec.org/p/ube/dpvwib/dp1308.html
   My bibliography  Save this paper

Decomposing Differences in Arithmetic Means: A Doubly-Robust Estimation Approach

Author

Listed:
  • Boris Kaiser

Abstract

When decomposing differences in average economic outcome between two groups of individuals, it is common practice to base the analysis on logarithms if the dependent variable is nonnegative. This paper argues that this approach raises a number of undesired statistical and conceptual issues because decomposition terms have the interpretation of approximate percentage differences in geometric means. Instead, we suggest that the analysis should be based on the arithmetic means of the original dependent variable. We present a flexible parametric decomposition framework that can be used for all types of continuous (or count) nonnegative dependent variables. In particular, we derive a propensity-score-weighted estimator for the aggregate decomposition that is "doubly robust", that is, consistent under two separate sets of assumptions. A comparative Monte Carlo study illustrates that the proposed estimator performs well in a many situations. An application to the union wage gap in the United States finds that the importance of the unexplained union wage premium is much smaller than suggested by the standard log-wage decomposition.

Suggested Citation

  • Boris Kaiser, 2013. "Decomposing Differences in Arithmetic Means: A Doubly-Robust Estimation Approach," Diskussionsschriften dp1308, Universitaet Bern, Departement Volkswirtschaft.
    • Handle: RePEc:ube:dpvwib:dp1308
    as

    Download full text from publisher

    File URL: http://www.vwl.unibe.ch/wp-content/uploads/papers/dp/dp1308.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2009. "Dealing with limited overlap in estimation of average treatment effects," Biometrika, Biometrika Trust, vol. 96(1), pages 187-199.
    2. 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.
    3. John M. Krieg & Paul Storer, 2006. "How Much Do Students Matter? Applying The Oaxaca Decomposition To Explain Determinants Of Adequate Yearly Progress," Contemporary Economic Policy, Western Economic Association International, vol. 24(4), pages 563-581, October.
    4. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, September.
    5. Rothe, Christoph, 2012. "Decomposing the Composition Effect," IZA Discussion Papers 6397, Institute of Labor Economics (IZA).
    6. Jacob A. Mincer, 1974. "Age and Experience Profiles of Earnings," NBER Chapters,in: Schooling, Experience, and Earnings, pages 64-82 National Bureau of Economic Research, Inc.
    7. Boris Kaiser, 2013. "Detailed Decompositions in Generalized Linear Models," Diskussionsschriften dp1309, Universitaet Bern, Departement Volkswirtschaft.
    8. repec:ags:stataj:122615 is not listed on IDEAS
    9. David Neumark, 1988. "Employers' Discriminatory Behavior and the Estimation of Wage Discrimination," Journal of Human Resources, University of Wisconsin Press, vol. 23(3), pages 279-295.
    10. Yun, Myeong-Su, 2004. "Decomposing differences in the first moment," Economics Letters, Elsevier, vol. 82(2), pages 275-280, February.
    11. Słoczyński, Tymon, 2012. "New Evidence on Linear Regression and Treatment Effect Heterogeneity," MPRA Paper 39524, University Library of Munich, Germany.
    12. Darity, William Jr & Guilkey, David & Winfrey, William, 1995. "Ethnicity, race, and earnings," Economics Letters, Elsevier, vol. 47(3-4), pages 401-408, March.
    13. Jann, Ben, 2008. "The Blinder–Oaxaca decomposition for linear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 1-27.
    14. Terza, Joseph V., 1998. "Estimating count data models with endogenous switching: Sample selection and endogenous treatment effects," Journal of Econometrics, Elsevier, vol. 84(1), pages 129-154, May.
    15. Ian A. Munn & Anwar Hussain, 2010. "Factors Determining Differences in Local Hunting Lease Rates: Insights from Blinder-Oaxaca Decomposition," Land Economics, University of Wisconsin Press, vol. 86(1), pages 66-78.
    16. 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.
    17. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Słoczyński, Tymon & Wooldridge, Jeffrey M., 2018. "A General Double Robustness Result For Estimating Average Treatment Effects," Econometric Theory, Cambridge University Press, vol. 34(01), pages 112-133, February.
    2. Gail Pacheco & Bill Cochrane, 2015. "Decomposing the temporary-permanent wage gap in New Zealand," Working Papers 2015-07, Auckland University of Technology, Department of Economics.

    More about this item

    Keywords

    Oaxaca-Blinder; Decomposition Methods; Quasi-Maximum-Likelihood; Doubly Robust Estimation; Arithmetic and Geometric Means; Inverse Probability Weighting;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

    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:ube:dpvwib:dp1308. 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: (Franz Koelliker). General contact details of provider: http://edirc.repec.org/data/vwibech.html .

    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.