House Price Regressions: Exploring OLS Assumptions

This lecture delves into the practical aspects of using Ordinary Least Squares (OLS) regressions for house price analysis. Topics covered include interpreting linear models, handling outliers, assessing influential observations, model specification, and model selection strategies. The instructor demonstrates these concepts through a case study on house price regressions using Stata commands. Diagnostic tests such as RESET, VIF, DFBETA, and avplots are applied to evaluate model assumptions and performance. Additionally, the lecture discusses the importance of presenting regression results effectively, including regression tables and diagnostic plots.