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Partial Identification and Inference for Dynamic Models and Counterfactuals

Author

Listed:
  • Myrto Kalouptsidi
  • Yuichi Kitamura
  • Lucas Lima
  • Eduardo Souza-Rodrigues

Abstract

We provide a general framework for investigating partial identification of structural dynamic discrete choice models and their counterfactuals, along with uniformly valid inference procedures. In doing so, we derive sharp bounds for the model parameters, counterfactual behavior, and low-dimensional outcomes of interest, such as the average welfare effects of hypothetical policy interventions. We characterize the properties of the sets analytically and show that when the target outcome of interest is a scalar, its identified set is an interval whose endpoints can be calculated by solving well-behaved constrained optimization problems via standard algorithms. We obtain a uniformly valid inference procedure by an appropriate application of subsampling. To illustrate the performance and computational feasibility of the method, we consider both a Monte Carlo study of firm entry/exit, and an empirical model of export decisions applied to plant-level data from Colombian manufacturing industries. In these applications, we demonstrate how the identified sets shrink as we incorporate alternative model restrictions, providing intuition regarding the source and strength of identification.

Suggested Citation

  • Myrto Kalouptsidi & Yuichi Kitamura & Lucas Lima & Eduardo Souza-Rodrigues, 2020. "Partial Identification and Inference for Dynamic Models and Counterfactuals," Working Papers tecipa-655, University of Toronto, Department of Economics.
  • Handle: RePEc:tor:tecipa:tecipa-655
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    More about this item

    Keywords

    Dynamic Discrete Choice; Counterfactual; Partial Identification; Subsampling; Uniform Inference; Structural Model;

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L0 - Industrial Organization - - General

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