Econometric Analysis Of Sequential Discrete Choice Models

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Abstract
This paper specifies an estimable dynamic model of sequential discrete choices in a controlled jump-process framework. We study sufficient conditions under which the agent's optimal policy is stationary. We show that the observable event histories at the micro-level are sample paths of a semi-Markovian process. We provide, for the first time, sufficient and necessary conditions under which the destination specific hazard functions belong to the proportional hazard family. Finally, we propose a computing algorithm for statistical inference of the structural parameters from longitudinal survey data.