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

  • Boris Kaiser

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.

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Paper provided by Universitaet Bern, Departement Volkswirtschaft in its series Diskussionsschriften with number dp1308.

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Date of creation: Oct 2013
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Handle: RePEc:ube:dpvwib:dp1308
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  1. 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.
  2. Steffen Mueller, 2012. "Works Councils and Establishment Productivity," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 65(4), pages 880-898, October.
  3. 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.
  4. 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.
  5. 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.
  6. Darity, William Jr & Guilkey, David & Winfrey, William, 1995. "Ethnicity, race, and earnings," Economics Letters, Elsevier, vol. 47(3-4), pages 401-408, March.
  7. Ben Jann, 2008. "The Blinder–Oaxaca decomposition for linear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 453-479, December.
  8. Słoczyński, Tymon, 2012. "New Evidence on Linear Regression and Treatment Effect Heterogeneity," MPRA Paper 39524, University Library of Munich, Germany.
  9. 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.
  10. David Neumark, 1987. "Employers' discriminatory behavior and the estimation of wage discrimination," Special Studies Papers 227, Board of Governors of the Federal Reserve System (U.S.).
  11. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, 07.
  12. 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.
  13. Rothe, Christoph, 2012. "Decomposing the Composition Effect," IZA Discussion Papers 6397, Institute for the Study of Labor (IZA).
  14. Yun, Myeong-Su, 2004. "Decomposing differences in the first moment," Economics Letters, Elsevier, vol. 82(2), pages 275-280, February.
  15. Boris Kaiser, 2013. "Detailed Decompositions in Generalized Linear Models," Diskussionsschriften dp1309, Universitaet Bern, Departement Volkswirtschaft.
  16. Willard G. Manning & John Mullahy, 1999. "Estimating Log Models: To Transform or Not to Transform?," NBER Technical Working Papers 0246, National Bureau of Economic Research, Inc.
  17. 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.
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