Identifying Dynamic Discrete Decision Processes

In this paper, we analyse the non parametric identification of dynamic discrete choice models using short-panel data. Our identification methodology is based on the ideas explored in the seminal paper of Hotz and Miller (1993) that Bellman equations can be interpreted as moment conditions. We derive the exact degree of underidentification of these models both in the case where random shocks on preferences are independent over time and in a case with correlated fixed effects. We investigate the necessity and power of various identifying restrictions.

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