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Identification of Counterfactuals and Payoffs in Dynamic Discrete Choice with an Application to Land Use

Listed author(s):
  • Myrto Kalouptsidi
  • Paul T. Scott
  • Eduardo Souza-Rodrigues

Dynamic discrete choice models are non-parametrically not identified without restrictions on payoff functions, yet counterfactuals may be identified even when payoffs are not. We provide necessary and sufficient conditions for the identification of a wide range of counterfactuals for models with nonparametric payoffs, as well as for commonly used parametric functions, and we obtain both positive and negative results. We show that access to extra data of asset resale prices (when applicable) can solve non-identifiability of both payoffs and counterfactuals. The theoretical findings are illustrated empirically in the context of agricultural land use. First, we provide identification results for models with unobserved market-level state variables. Then, using a unique spatial dataset of land use choices and land resale prices, we estimate the model and investigate two policy counterfactuals: long run land use elasticity (identified) and a fertilizer tax (not identified, affected dramatically by restrictions).

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File URL: https://www.economics.utoronto.ca/public/workingPapers/tecipa-546.pdf
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Paper provided by University of Toronto, Department of Economics in its series Working Papers with number tecipa-546.

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Length: Unknown pages
Date of creation: 31 Aug 2015
Handle: RePEc:tor:tecipa:tecipa-546
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  16. Andriy Norets, 2009. "Inference in Dynamic Discrete Choice Models With Serially orrelated Unobserved State Variables," Econometrica, Econometric Society, vol. 77(5), pages 1665-1682, 09.
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