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Dynamic Discrete Choice and Dynamic Treatment Effects Author info | Abstract | Publisher info | Download info | Related research | Statistics James J. Heckman () (University of Chicago and IZA Bonn)
Salvador Navarro () (University of Wisconsin-Madison)
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This paper considers semiparametric identiÞcation of structural dynamic discrete choice models and models for dynamic treatment effects. Time to treatment and counterfactual outcomes associated with treatment times are jointly analyzed. We examine the implicit assumptions of the dynamic treatment model using the structural model as a benchmark. For the structural model we show the gains from using cross equation restrictions connecting choices to associated measurements and outcomes. In the dynamic discrete choice model, we identify both subjective and objective outcomes, distinguishing ex post and ex ante outcomes. We show how to identify agent information sets.
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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number
1790.
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Length: 96 pages
Date of creation: Oct 2005Date of revision:
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Keywords: dynamic treatment effects ; dynamic discrete choice ; semiparametric identification ; Other versions of this item:
Find related papers by JEL classification: C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
This paper has been announced in the following NEP Reports :
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.: Hansen, Karsten T. & Heckman, James J. & Mullen, Kathleen J., 2003.
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