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Comparing IV with Structural Models: What Simple IV Can and Cannot Identify

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  • Heckman, James J.

    ()
    (University of Chicago)

  • Urzua, Sergio

    ()
    (University of Maryland)

Abstract

This paper compares the economic questions addressed by instrumental variables estimators with those addressed by structural approaches. We discuss Marschak's Maxim: estimators should be selected on the basis of their ability to answer well-posed economic problems with minimal assumptions. A key identifying assumption that allows structural methods to be more informative than IV can be tested with data and does not have to be imposed.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3980.

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Length: 34 pages
Date of creation: Jan 2009
Date of revision:
Publication status: published in: Journal of Econometrics, 2010, 156 (1), 27-37
Handle: RePEc:iza:izadps:dp3980

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Keywords: Marschak's Maxim; instrumental variables; structural approaches;

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References

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  1. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2009. "Understanding Instrumental Variables in Models with Essential Heterogeneity," Working Papers, Geary Institute, University College Dublin 200941, Geary Institute, University College Dublin.
  2. 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, IFAU - Institute for Evaluation of Labour Market and Education Policy 2003:9, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  3. 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, Elsevier, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 72 Elsevier.
  4. Heckman, James J. & Navarro, Salvador, 2007. "Dynamic discrete choice and dynamic treatment effects," Journal of Econometrics, Elsevier, Elsevier, vol. 136(2), pages 341-396, February.
  5. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4 National Bureau of Economic Research, Inc.
  6. Heckman, James J. & Urzua, Sergio & Vytlacil, Edward, 2008. "Instrumental Variables in Models with Multiple Outcomes: The General Unordered Case," IZA Discussion Papers 3565, Institute for the Study of Labor (IZA).
  7. Cunha, Flavio & Heckman, James J. & Navarro, Salvador, 2004. "Separating Uncertainty from Heterogeneity in Life Cycle Earnings," IZA Discussion Papers 1437, Institute for the Study of Labor (IZA).
  8. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, International Statistical Institute, vol. 76(1), pages 1-27, 04.
  9. James J. Heckman & Paul A. LaFontaine & Pedro L. Rodriguez, 2008. "Taking the Easy Way Out: How the GED Testing Program Induces Students to Drop Out," Working Papers, Geary Institute, University College Dublin 200829, Geary Institute, University College Dublin.
  10. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects and Econometric Policy Evaluation," NBER Technical Working Papers 0306, National Bureau of Economic Research, Inc.
  11. Matzkin, Rosa L., 1993. "Nonparametric identification and estimation of polychotomous choice models," Journal of Econometrics, Elsevier, Elsevier, vol. 58(1-2), pages 137-168, July.
  12. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, Econometric Society, vol. 69(5), pages 1127-60, September.
  13. Keane, Michael P & Wolpin, Kenneth I, 1997. "The Career Decisions of Young Men," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 105(3), pages 473-522, June.
  14. Flavio Cunha & James Heckman, 2007. "The Evolution of Inequality, Heterogeneity and Uncertainty in Labor Earnings in the U.S. Economy," PIER Working Paper Archive 07-032, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  15. James J. Heckman & Jora Stixrud & Sergio Urzua, 2006. "The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior," Journal of Labor Economics, University of Chicago Press, University of Chicago Press, vol. 24(3), pages 411-482, July.
  16. Matzkin, Rosa L., 1986. "Restrictions of economic theory in nonparametric methods," Handbook of Econometrics, Elsevier, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 42, pages 2523-2558 Elsevier.
  17. Sergio Urzúa, 2008. "Racial Labor Market Gaps: The Role of Abilities and Schooling Choices," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
  18. James J. Heckman & Vytlacil, Edward J., 2007. "Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation," Handbook of Econometrics, Elsevier, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 70 Elsevier.
  19. Matzkin, Rosa L, 1992. "Nonparametric and Distribution-Free Estimation of the Binary Threshold Crossing and the Binary Choice Models," Econometrica, Econometric Society, Econometric Society, vol. 60(2), pages 239-70, March.
  20. Heckman, James J. & Schmierer, Daniel & Urzua, Sergio, 2010. "Testing the correlated random coefficient model," Journal of Econometrics, Elsevier, Elsevier, vol. 158(2), pages 177-203, October.
  21. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
  22. James J. Heckman & Vytlacil, Edward J., 2007. "Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econometric Estimators to Evaluate Social Programs, and to Forecast their Effects in New," Handbook of Econometrics, Elsevier, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 71 Elsevier.
  23. Matzkin, Rosa L., 2007. "Nonparametric identification," Handbook of Econometrics, Elsevier, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 73 Elsevier.
  24. Flavio Cunha & James J. Heckman & Salvador Navarro, 2007. "The Identification and Economic Content of Ordered Choice Models with Stochastic Thresholds," NBER Technical Working Papers 0340, National Bureau of Economic Research, Inc.
  25. Stephen V. Cameron & James J. Heckman, 1998. "Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts of American Males," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 106(2), pages 262-333, April.
  26. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, Econometric Society, vol. 65(3), pages 557-586, May.
  27. Heckman, James & Layne-Farrar, Anne & Todd, Petra, 1996. "Human Capital Pricing Equations with an Application to Estimating the Effect of Schooling Quality on Earnings," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 562-610, November.
  28. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1.
  29. John M. Barron & Mark C. Berger & Dan A. Black, 2006. "Selective Counteroffers," Journal of Labor Economics, University of Chicago Press, University of Chicago Press, vol. 24(3), pages 385-410, July.
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  1. Rise and Fall of a Method
    by Agent Continuum in Agent Continuum on 2010-04-21 13:53:35
  2. Causality and Econometrics
    by Liam Delaney in Geary Behaviour Centre on 2009-04-28 19:19:00
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