Some Remarks on CCP-based Estimators of Dynamic Models

Mogens Fosgerau, Emerson Melo, Matthew Shum and Jesper R.-V. Sørensen
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Emerson Melo: Indiana University
Matthew Shum: California Institute of Technology
Jesper R.-V. Sørensen: University of Copenhagen

No 21-03, Discussion Papers from University of Copenhagen. Department of Economics

Abstract: This note provides several remarks relating to the conditional-choice probability (CCP) based estimation approaches for dynamic discrete-choice models. Specifically, the Arcidiacono and Miller [2011] estimation procedure relies on the “inverse-CCP” mapping (p) from CCP’s to choice-specific value functions. Exploiting the convex-analytic structure of discrete choice models, we discuss two approaches for computing this, using either linear or convex programming, for models where the utility shocks can follow arbitrary parametric distributions. Furthermore, the function is generally distinct from the “selection adjustment” term (i.e. the expectation of the utility shock for the chosen alternative), so that computational approaches for computing the latter may not be appropriate for computing .

Keywords: dynamic discrete choice; random utility; linear programming; convex analysis; convex optimization (search for similar items in EconPapers)
JEL-codes: C35 C61 D90 (search for similar items in EconPapers)
Date: 2021-02-21
New Economics Papers: this item is included in nep-dcm and nep-upt
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Citations: View citations in EconPapers (3)

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Journal Article: Some remarks on CCP-based estimators of dynamic models (2021)
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