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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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  1. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects and Econometric Policy Evaluation," NBER Working Papers 11259, National Bureau of Economic Research, Inc.
  2. Christian Belzil, 2006. "The Return to Schooling in Structural Dynamic Models: A Survey," Post-Print halshs-00142538, HAL.
  3. Magnac & Thesmar, 2002. "Identifying dynamic discrete decision processes," Working Papers 155888, Institut National de la Recherche Agronomique, France.
  4. 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.
  5. 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.
  6. Paul J. Devereux & Robert A. Hart, 2009. "Forced to be Rich? Returns to Compulsory Schooling in Britain," Working Papers 200940, Geary Institute, University College Dublin.
  7. 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.
  8. 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.
  9. Belzil, Christian, 2007. "Testing the Specification of the Mincer Wage Equation," IZA Discussion Papers 2650, Institute for the Study of Labor (IZA).
  10. Flavio Cunha & James Heckman & Salvador Navarro, 2005. "Separating uncertainty from heterogeneity in life cycle earnings," Oxford Economic Papers, Oxford University Press, vol. 57(2), pages 191-261, April.
  11. Flavio Cunha & James Heckman & Susanne Schennach, 2010. "Estimating the technology of cognitive and noncognitive skill formation," CeMMAP working papers CWP09/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  12. 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.
  13. Keane, Michael P., 2010. "Structural vs. atheoretic approaches to econometrics," Journal of Econometrics, Elsevier, vol. 156(1), pages 3-20, May.
  14. Keane, Michael P & Wolpin, Kenneth I, 1997. "The Career Decisions of Young Men," Journal of Political Economy, University of Chicago Press, vol. 105(3), pages 473-522, June.
  15. 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.
  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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