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- W2807544194 abstract "Using results from convex analysis, we characterize the identification and estimation of dynamic discrete-choice models based on the random utility framework. Based on these insights, we propose a new two-step estimator for these models, which is easily applicable to models in which the utility shocks may not derive from an extreme- value distribution, and may be mutually correlated with each other and with the state variables. Monte Carlo results demonstrate the good performance of this estimator, and we provide a short application using the dynamic bus engine replacement model in Rust (1987)." @default.
- W2807544194 created "2018-06-13" @default.
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- W2807544194 date "2013-05-01" @default.
- W2807544194 modified "2023-09-26" @default.
- W2807544194 title "Estimating Dynamic Discrete Choice Models Via Convex Analysis" @default.
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