Some remarks on CCP-based estimators of dynamic models

Mogens Fosgerau, Emerson Melo, Matthew Shum and Jesper R.-V. Sørensen

Economics Letters, 2021, vol. 204, issue C

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 ψp from CCPs to choice-specific value functions. Exploiting the convex-analytic structure of discrete choice models, we discuss two approaches for computing this mapping, using either linear or convex programming, for models where the utility shocks can follow arbitrary parametric distributions. Furthermore, the ψ 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 ψ.

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
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Working Paper: Some Remarks on CCP-based Estimators of Dynamic Models (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:204:y:2021:i:c:s0165176521001889

DOI: 10.1016/j.econlet.2021.109911

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