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A New Framework for the Analysis of Inequality

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  • Flavio Cunha
  • James J. Heckman

Abstract

This paper presents a new framework for analyzing inequality that moves beyond the anonymity postulate. We estimate the determinants of sectoral choice and the joint distributions of outcomes across sectors. We determine which components of realized earnings variability are due to uncertainty and which components are due to components of human diversity that are forcastable by agents. Using our tools, we can determine how policies shift persons across sectors and outcome distributions across sectors.

Suggested Citation

  • Flavio Cunha & James J. Heckman, 2006. "A New Framework for the Analysis of Inequality," NBER Working Papers 12505, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:12505
    Note: DAE IFM LS CH
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    References listed on IDEAS

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    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    2. Heckman, James J & Lochner, Lance & Taber, Christopher, 1998. "General-Equilibrium Treatment Effects: A Study of Tuition Policy," American Economic Review, American Economic Association, vol. 88(2), pages 381-386, May.
    3. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
    4. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    5. Heckman, James J. & Navarro, Salvador, 2007. "Dynamic discrete choice and dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 136(2), pages 341-396, February.
    6. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 487-535.
    7. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute of Labor Economics (IZA).
    8. Pedro Carneiro & James J. Heckman, 2002. "The Evidence on Credit Constraints in Post--secondary Schooling," Economic Journal, Royal Economic Society, vol. 112(482), pages 705-734, October.
    9. Aakvik, A. & Heckman, J.J. & Vytlacil, E.J., 1999. "Training Effects on Employment when the Training Effects are Heterogenous : an Application to Norwegian Vocational Rehabilitation Programs," Norway; Department of Economics, University of Bergen 0599, Department of Economics, University of Bergen.
    10. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-1149, September.
    11. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "2001 Lawrence R. Klein Lecture Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 361-422, May.
    12. Browning, Martin & Hansen, Lars Peter & Heckman, James J., 1999. "Micro data and general equilibrium models," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 8, pages 543-633, Elsevier.
    13. James J. Heckman, 1991. "Randomization and Social Policy Evaluation Revisited," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc.
    14. Card, David, 1999. "The causal effect of education on earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 30, pages 1801-1863, Elsevier.
    15. James Heckman & Lance Lochner & Christopher Taber, 1998. "Explaining Rising Wage Inequality: Explanations With A Dynamic General Equilibrium Model of Labor Earnings With Heterogeneous Agents," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(1), pages 1-58, January.
    16. Heckman, James J & Lochner, Lance & Taber, Christopher, 1998. "Tax Policy and Human-Capital Formation," American Economic Review, American Economic Association, vol. 88(2), pages 293-297, May.
    17. Flavio Cunha & James Heckman, 2006. "The Evolution of Labor Earnings Risk in the US Economy," 2006 Meeting Papers 665, Society for Economic Dynamics.
    18. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
    19. Aakvik, Arild & Heckman, James J. & Vytlacil, Edward J., 2005. "Estimating treatment effects for discrete outcomes when responses to treatment vary: an application to Norwegian vocational rehabilitation programs," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 15-51.
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    More about this item

    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General

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