Dynamic Panel Data Model: Post-Estimation and Sample Bias - Part 11

Explore post-estimation techniques for Dynamic Panel Data (DPD) models, focusing on overidentification estimation and sample bias. Delve into the intricacies of analyzing DPD models after initial estimation, gaining insights into the challenges and solutions for addressing overidentification issues. Learn how to assess and mitigate sample bias in DPD models, enhancing your understanding of these advanced econometric techniques. This 25-minute lecture, part of a series on Dynamic Panel Data Models, provides valuable knowledge for researchers and practitioners working with complex panel data structures.