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Econometric Causality

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  • Heckman, James J.

    ()
    (University of Chicago)

Abstract

This paper presents the econometric approach to causal modeling. It is motivated by policy problems. New causal parameters are defined and identified to address specific policy problems. Economists embrace a scientific approach to causality and model the preferences and choices of agents to infer subjective (agent) evaluations as well as objective outcomes. Anticipated and realized subjective and objective outcomes are distinguished. Models for simultaneous causality are developed. The paper contrasts the Neyman-Rubin model of causality with the econometric approach.

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File URL: http://ftp.iza.org/dp3425.pdf
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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3425.

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Length: 55 pages
Date of creation: Mar 2008
Date of revision:
Publication status: published in: International Statistical Review, 2008, (76) 1, 1-27
Handle: RePEc:iza:izadps:dp3425

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Related research

Keywords: subjective and objective evaluations; Neyman-Rubin model; Roy model; causality; econometrics; treatment effects; counterfactuals; anticipated vs. realized outcomes;

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References

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  1. Gronau, Reuben, 1974. "Wage Comparisons-A Selectivity Bias," Journal of Political Economy, University of Chicago Press, vol. 82(6), pages 1119-43, Nov.-Dec..
  2. Matzkin, Rosa L., 2007. "Nonparametric identification," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 73 Elsevier.
  3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  4. Carneiro, Pedro & Hansen, Karsten & Heckman, James, 2003. "Estimating distributions of treatment effects with an application to the returns to schooling and measurement of the effects of uncertainty on college choice," Working Paper Series 2003:9, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  5. Jaap Abbring & James Heckman, 2008. "Dynamic policy analysis," CeMMAP working papers CWP05/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  6. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-18, May.
  7. Alberto Abadie & Joshua Angrist & Guido Imbens, 2002. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Econometrica, Econometric Society, vol. 70(1), pages 91-117, January.
  8. James Heckman & Neil Hohmann & Jeffrey Smith & Michael Khoo, 2000. "Substitution And Dropout Bias In Social Experiments: A Study Of An Influential Social Experiment," The Quarterly Journal of Economics, MIT Press, vol. 115(2), pages 651-694, May.
  9. Carneiro, Pedro & Hansen, Karsten T & Heckman, James J, 2002. "Removing the veil of ignorance in assessing the distributional impacts of social policies," Working Paper Series 2002:2, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  10. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-49, September.
  11. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
  12. James J. Heckman & Salvador Navarro, 2005. "Dynamic Discrete Choice and Dynamic Treatment Effects," NBER Technical Working Papers 0316, National Bureau of Economic Research, Inc.
  13. James J. Heckman, 1977. "Dummy Endogenous Variables in a Simultaneous Equation System," NBER Working Papers 0177, National Bureau of Economic Research, Inc.
  14. Jaap H. Abbring & Gerard J. van den Berg, 2003. "The Nonparametric Identification of Treatment Effects in Duration Models," Econometrica, Econometric Society, vol. 71(5), pages 1491-1517, 09.
  15. William A. Brock & Steven N. Durlauf, 2000. "Interactions-Based Models," Working Papers 00-05-028, Santa Fe Institute.
  16. Hensher, David & Louviere, Jordan & Swait, Joffre, 1998. "Combining sources of preference data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 197-221, November.
  17. Bjorklund, Anders & Moffitt, Robert, 1987. "The Estimation of Wage Gains and Welfare Gains in Self-selection," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 42-49, February.
  18. Abbring, Jaap H. & Heckman, James J., 2007. "Econometric Evaluation of Social Programs, Part III: Distributional Treatment Effects, Dynamic Treatment Effects, Dynamic Discrete Choice, and General Equilibrium Policy Evaluation," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 72 Elsevier.
  19. James J. Heckman & Jeffrey A. Smith, 1998. "Evaluating the Welfare State," NBER Working Papers 6542, National Bureau of Economic Research, Inc.
  20. Lewis, H Gregg, 1974. "Comments on Selectivity Biases in Wage Comparisons," Journal of Political Economy, University of Chicago Press, vol. 82(6), pages 1145-55, Nov.-Dec..
  21. Heckman, James J & Smith, Jeffrey, 1997. "Making the Most Out of Programme Evaluations and Social Experiments: Accounting for Heterogeneity in Programme Impacts," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 487-535, October.
  22. Elie Tamer, 2003. "Incomplete Simultaneous Discrete Response Model with Multiple Equilibria," Review of Economic Studies, Wiley Blackwell, vol. 70(1), pages 147-165, January.
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Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Causality and Econometrics
    by Liam Delaney in Geary Behaviour Centre on 2009-04-28 19:19:00
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