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Evaluating Theories of Income Dynamics: A Probabilistic Approach

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  • Robert Aebi
  • Klaus Neusser
  • Peter Steiner

Abstract

The paper proposes an approach to evaluate hypotheses about transition dynamics when only the distributions at two points in time are observed. Using principles of statistical mechanics, we show how to adjust in the "most probable" way a hypothesis such that it becomes compatible with the observed distributions. This adjustment procedure also allows to test hypotheses in a statistical sense. The test is based on the relative entropy and is equivalent to a likelihood ratio test. We apply our approach to compare the dynamics of the income distribution between men and women in the U.S. using PSID data.

Suggested Citation

  • Robert Aebi & Klaus Neusser & Peter Steiner, 1999. "Evaluating Theories of Income Dynamics: A Probabilistic Approach," Diskussionsschriften dp9905, Universitaet Bern, Departement Volkswirtschaft.
    • Handle: RePEc:ube:dpvwib:dp9905
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    References listed on IDEAS

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    1. Atkinson, A B, 1997. "Bringing Income Distribution in from the Cold," Economic Journal, Royal Economic Society, vol. 107(441), pages 297-321, March.
    2. Yuichi Kitamura & Michael Stutzer, 1997. "An Information-Theoretic Alternative to Generalized Method of Moments Estimation," Econometrica, Econometric Society, vol. 65(4), pages 861-874, July.
    3. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    4. Durlauf, Steven N. & Quah, Danny T., 1999. "The new empirics of economic growth," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 4, pages 235-308, Elsevier.
    5. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    6. Schluter, Christian, 1998. "Statistical inference with mobility indices," Economics Letters, Elsevier, vol. 59(2), pages 157-162, May.
    7. Trede, Mark M., 1994. "Statistical inference in mobility measurement: Sex differences in earnings mobility," Discussion Papers in Econometrics and Statistics 4/94, University of Cologne, Institute of Econometrics and Statistics.
    8. Quah, Danny T., 1996. "Empirics for economic growth and convergence," European Economic Review, Elsevier, vol. 40(6), pages 1353-1375, June.
    9. Quah, Danny T, 1996. "Convergence Empirics across Economies with (Some) Capital Mobility," Journal of Economic Growth, Springer, vol. 1(1), pages 95-124, March.
    10. Shorrocks, A F, 1978. "The Measurement of Mobility," Econometrica, Econometric Society, vol. 46(5), pages 1013-1024, September.
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    Cited by:

    1. Erik Figueiredo & Flávio Ziegelmann, 2010. "The dynamics of the Brazilian income," Economics Bulletin, AccessEcon, vol. 30(2), pages 1249-1260.
    2. Robert Aebi & Klaus Neusser & Peter Steiner, 2008. "Improving Models of Income Dynamics using Cross-Section-Information," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(II), pages 117-151, June.

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    More about this item

    Keywords

    income dynamics; large deviation; relative entropy; misspecification;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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