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Econometric Causality

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Author Info

  • 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. James J. Heckman & Sergio Urzua & Edward J. Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," NBER Working Papers 12574, National Bureau of Economic Research, Inc.
  2. William A. Brock & Steven N. Durlauf, 2000. "Interactions-Based Models," Working Papers 00-05-028, Santa Fe Institute.
  3. Elie Tamer, 2003. "Incomplete Simultaneous Discrete Response Model with Multiple Equilibria," Review of Economic Studies, Wiley Blackwell, vol. 70(1), pages 147-165, January.
  4. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2002. "Removing the Veil of Ignorance in Assessing the Distributional Impacts of Social Policies," IZA Discussion Papers 453, Institute for the Study of Labor (IZA).
  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. Reuben Gronau, 1973. "Wage Comparisons -A Selectivity Bias," NBER Working Papers 0013, National Bureau of Economic Research, Inc.
  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. 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.
  9. 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.
  10. James J. Heckman & Salvador Navarro, 2005. "Dynamic Discrete Choice and Dynamic Treatment Effects," NBER Technical Working Papers 0316, National Bureau of Economic Research, Inc.
  11. Hensher, David & Louviere, Jordan & Swait, Joffre, 1998. "Combining sources of preference data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 197-221, November.
  12. 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.
  13. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January.
  14. 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.
  15. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-59, July.
  16. 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.
  17. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-49, September.
  18. 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..
  19. 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.
  20. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-18, May.
  21. 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.
  22. James J. Heckman & Jeffrey A. Smith, 1998. "Evaluating the Welfare State," NBER Working Papers 6542, National Bureau of Economic Research, Inc.
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Citations

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
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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Cited by:
  1. Heckman, James J. & Urzua, Sergio, 2009. "Comparing IV with Structural Models: What Simple IV Can and Cannot Identify," IZA Discussion Papers 3980, Institute for the Study of Labor (IZA).
  2. M. Hashem Pesaran & Ron P. Smith, 2012. "Counterfactual Analysis in Macroeconometrics: An Empirical Investigation into the Effects of Quantitative Easing," CESifo Working Paper Series 3879, CESifo Group Munich.
  3. Armstrong, Christopher S. & Guay, Wayne R. & Weber, Joseph P., 2010. "The role of information and financial reporting in corporate governance and debt contracting," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 179-234, December.
  4. María Laura Alzúa & Guillermo Cruces & Laura Ripani, 2010. "Welfare Programs and Labor Supply in Developing Countries. Experimental Evidence from Latin America," CEDLAS, Working Papers 0095, CEDLAS, Universidad Nacional de La Plata.
  5. Channing Arndt & Sam Jones & Finn Tarp, 2011. "Aid Effectiveness: Opening the Black Box," Working Papers UNU-WIDER Working Paper W, World Institute for Development Economic Research (UNU-WIDER).
  6. Thomas, Ranjeeta & Jones, Andrew M & Squire, Lyn, 2010. "Methods for Evaluating Innovative Health Programs (EIHP): A Multi-Country Study," MPRA Paper 29402, University Library of Munich, Germany.
  7. Georg Wamser, 2008. "The Impact of Thin-Capitalization Rules on External Debt Usage – A Propensity Score Matching Approach," Ifo Working Paper Series Ifo Working Paper No. 62, Ifo Institute for Economic Research at the University of Munich.
  8. David I. Stern & Kerstin Enflo, 2013. "Causality Between Energy and Output in the Long-Run," CAMA Working Papers 2013-01, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  9. Smith, Ron, 2009. "EMU and the Lucas Critique," Economic Modelling, Elsevier, vol. 26(4), pages 744-750, July.
  10. David I. Stern, 2011. "From Correlation to Granger Causality," Crawford School Research Papers 1113, Crawford School of Public Policy, The Australian National University.

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