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The distinction between dictatorial and incentive policy interventions and its implication for IV estimation

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  • Christian Belzil

    (Department of Economics, Ecole Polytechnique - CNRS : UMR7176 - Polytechnique - X, ENSAE - École Nationale de la Statistique et de l'Administration Économique - ENSAE ParisTech, IZA - Institute for the Study of Labor)

  • J. Hansen

    (IZA - Institute for the Study of Labor, CIREQ - Centre Interuniversitaire de Recherche en Economie Quantitative, CIRANO - Montréal, Department of Economics, Concordia University - Concordia University)

Abstract

We investigate if, and under which conditions, the distinction between dictatorial and incentive-based policy interventions, affects the capacity of Instrument Variable (IV) methods to estimate the relevant treatment effect parameter of an outcome equation. The analysis is set in a non-trivial framework, in which the right-hand side variable of interest is affected by selectivity, and the error term is driven by a sequence of unobserved life-cycle endogenous choices. We show that, for a wide class of outcome equations, incentive-based policies may be designed so to generate a sufficient degree of post-intervention randomization (a lesser degree of selection on individual endowments among the sub-population affected). This helps the instrument to fulfill the orthogonality condition. However, for a same class of outcome equation, dictatorial policies that enforce minimum consumption cannot meet this condition. We illustrate these concepts within a calibrated dynamic life cycle model of human capital accumulation, and focus on the estimation of the returns to schooling using instruments generated from mandatory schooling reforms and education subsidies. We show how the nature of the skill accumulation process (substitutability vs complementarity) may play a fundamental role in interpreting IV estimates of the returns to schooling.

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Bibliographic Info

Paper provided by HAL in its series Working Papers with number hal-00463877.

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Date of creation: 15 Mar 2010
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Handle: RePEc:hal:wpaper:hal-00463877

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Keywords: Returns to schooling; Instrumental Variable methods; Dynamic Discrete Choice; Dynamic Programming; Local Average Treatment Effects .;

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References

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  1. Heckman, James J. & Urzua, Sergio & Vytlacil, Edward, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," IZA Discussion Papers 2320, Institute for the Study of Labor (IZA).
  2. Paul J Devereux & Robert A Hart, 2009. "Forced to be Rich? Returns to Compulsory Schooling in Britain," Working Papers 200924, School Of Economics, University College Dublin.
  3. 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.
  4. Michael P. Keane & Kenneth I. Wolpin, 1995. "The career decisions of young men," Working Papers 559, Federal Reserve Bank of Minneapolis.
  5. Christian Belzil, 2007. "The Return to Schooling in Structural Dynamic Models: A Survey," Post-Print halshs-00201230, HAL.
  6. Belzil, Christian & Hansen, Jorgen, 2007. "A structural analysis of the correlated random coefficient wage regression model," Journal of Econometrics, Elsevier, vol. 140(2), pages 827-848, October.
  7. 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.
  8. Keane, Michael P., 2010. "Structural vs. atheoretic approaches to econometrics," Journal of Econometrics, Elsevier, vol. 156(1), pages 3-20, May.
  9. Flavio Cunha & James Heckman & Susanne Schennach, 2010. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," NBER Working Papers 15664, National Bureau of Economic Research, Inc.
  10. Cunha, Flavio & Heckman, James & Navarro, Salvador, 2004. "Separating uncertainty from heterogeneity in life cycle earnings," Working Paper Series 2005:6, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  11. Belzil, Christian, 2007. "Testing the Specification of the Mincer Wage Equation," IZA Discussion Papers 2650, Institute for the Study of Labor (IZA).
  12. Yoram Ben-Porath, 1967. "The Production of Human Capital and the Life Cycle of Earnings," Journal of Political Economy, University of Chicago Press, vol. 75, pages 352.
  13. Thierry Magnac & David Thesmar, 2002. "Identifying Dynamic Discrete Decision Processes," Econometrica, Econometric Society, vol. 70(2), pages 801-816, March.
  14. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March.
  15. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
  16. Stephen V. Cameron & Christopher Taber, 2004. "Estimation of Educational Borrowing Constraints Using Returns to Schooling," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 132-182, February.
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Cited by:
  1. Christian Belzil & Jörgen Hansen, 2012. "Characterizing the Instrumental Variable Identifying Assumption as Sample Selection Conditions," Working Papers hal-00753539, HAL.
  2. Belzil, Christian & Hansen, Jörgen & Liu, Xingfei, 2011. "Dynamic Skill Accumulation, Comparative Advantages, Compulsory Schooling, and Earnings," IZA Discussion Papers 6167, Institute for the Study of Labor (IZA).

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