Panel data: serial correlation

This lecture covers the panel effect model, which relaxes the assumption of independence across time periods by considering unobserved factors that persist over time. It explains the static model with fixed and random effects, discussing the estimation process and the challenges of consistent estimation. The lecture also delves into the mixture model for random effects estimation, emphasizing the need for simulation and the impact of serial correlation on parameter estimation.