Identification and Estimation of Dynamic Structural Models with Unobserved Choices
Explore a comprehensive lecture on the identification and estimation of dynamic structural models with unobserved choices. Delve into Yi Xin's research from Caltech, presented at the Simons Institute as part of the Information Design and Data Science series. Gain insights into the motivation, research questions, and existing literature on DDCA. Examine a basic model and its dynamic process, understanding the intuition and assumptions on state transition processes. Learn about identification methods, closed-form solutions, and ordering assumptions. Discover various extensions, including dynamic discrete games, and discuss key assumptions. Analyze summary statistics, probabilities of shirking, and review the main findings of this complex econometric topic.