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Microdata, Heterogeneity and the Evaluation of Public Policy

Author

Listed:
  • Heckman, James J.

    (University of Chicago)

Abstract

This paper summarizes the contributions of microeconometrics to economic knowledge. Four main themes are developed. (1) Microeconometricians developed new tools to respond to econometric problems raised by the analysis of the new source of microdata produced after the Second World War. (2) Microeconometrics improved on aggregate time series methods by building models that linked economic models for individuals to data on individual behaviour. (3) An important empirical regularity detected by the field is the diversity and heterogeneity of behaviour. This heterogeneity has profound consequences for economic theory and for econometric practice. (4) Microeconometrics has contributed substantially to the scientific evaluation of public policy.

Suggested Citation

  • Heckman, James J., 2000. "Microdata, Heterogeneity and the Evaluation of Public Policy," Nobel Prize in Economics documents 2000-4, Nobel Prize Committee.
    • Handle: RePEc:ris:nobelp:2000_004
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    File URL: http://nobelprize.org/nobel_prizes/economics/laureates/2000/heckman-lecture.pdf
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    Citations

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    Cited by:

    1. Rokhaya Dieye & Habiba Djebbari & Felipe Barrera-Osorio, 2014. "Accounting for Peer Effects in Treatment Response," AMSE Working Papers 1435, Aix-Marseille School of Economics, France, revised Jul 2014.
    2. Bessho, Shun-ichiro & Hayashi, Masayoshi, 2011. "Labor supply response and preferences specification: Estimates for prime-age males in Japan," Journal of Asian Economics, Elsevier, vol. 22(5), pages 398-411, October.
    3. Machado, Cecilia, 2012. "Selection, Heterogeneity and the Gender Wage Gap," IZA Discussion Papers 7005, Institute of Labor Economics (IZA).
    4. Christopher L. Gilbert & Duo Qin, 2005. "The First Fifty Years of Modern Econometrics," Working Papers 544, Queen Mary University of London, School of Economics and Finance.
    5. Doucouliagos, Hristos & Paldam, Martin & Stanley, T.D., 2018. "Skating on thin evidence: Implications for public policy," European Journal of Political Economy, Elsevier, vol. 54(C), pages 16-25.
    6. Odd O. Aalen & Johan Fosen & Harald Weedon-Fekjær & Ørnulf Borgan & Einar Husebye, 2004. "Dynamic Analysis of Multivariate Failure Time Data," Biometrics, The International Biometric Society, vol. 60(3), pages 764-773, September.
    7. Shun-ichiro Bessho & Masayoshi Hayashi, 2005. "The CES utility function, non-linear budget constraints and labor supply : results on prime-age males in Japan," Labor Economics Working Papers 21911, East Asian Bureau of Economic Research.
    8. Jan-Jan Soon, 2008. "The determinants of international students' return intention," Working Papers 0806, University of Otago, Department of Economics, revised Jul 2008.
    9. Martin P. Shanahan & John K. Wilson & William E. Becker, 2012. "Following Zahka: Using Nobel Prize Winners’ Speeches and Ideas to Teach Economics," The Journal of Economic Education, Taylor & Francis Journals, vol. 43(2), pages 190-199, April.
    10. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5, July-Dece.
    11. Sudhir Alladi Venkatesh & Steven D. Levitt, 2001. "Growing Up in the Projects: The Economic Lives of a Cohort of Men Who Came of Age in Chicago Public Housing," American Economic Review, American Economic Association, vol. 91(2), pages 79-84, May.
    12. Shun-ichiro Bessho & Masayoshi Hayashi, 2013. "Estimating the Social Marginal Cost of Public Funds," Public Finance Review, , vol. 41(3), pages 360-385, May.

    More about this item

    Keywords

    Microeconometrics;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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