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This lecture by the instructor covers the concept of heteroskedasticity in econometrics, focusing on the issues related to standard errors when the assumptions of the Gauss-Markov model are violated. The lecture explains the impact of heteroskedasticity on OLS estimators and the need for alternative estimators like Generalized Least Squares (GLS). It discusses the simulation of heteroskedasticity, the problems it causes, and solutions such as Weighted Least Squares. The lecture also delves into testing for heteroskedasticity using Breusch-Pagan and White tests, the consequences of heteroskedasticity on hypothesis testing, and the use of heteroskedasticity-consistent standard errors in statistical analysis.