Identification of Dynamic Discrete Choice Models
综述了动态离散选择模型识别的最新进展，包括无动态选择偏差的条件、离散时间模型中的未观测异质性和状态识别，以及连续时间最优停止模型的识别，对实证研究者有重要参考价值。
Econometric models of dynamic discrete choice processes are applied to a wide variety of economic problems. Recent research on their empirical content has brought important new insights. It has clarified the conditions for their identification from choice and covariate panel data in the absence of dynamic selection on unobservables. It has provided important new identification results for discrete-time models with unobserved heterogeneity and unobserved states. Finally, it has enhanced the attractiveness of continuous-time models, by developing new insights on the identification of continuous-time optimal stopping models. Current developments in the literature promise to shed further light on the specification and identification of models with unobserved state variables, theory-based nonproportional hazard models, continuous-time optimal stopping models with time-varying covariates, and dynamic games in discrete and continuous time.