We start with the classical linear regression model and tests for restrictions of the parameter. We cover the geometric interpretation of OLS and elementary optimality theory (Gauss-Markov theorem), as well as GLS estimation and feasible GLS estimators. Then we deal with generalizations necessary for practical applications: Asymptotic theory, heteroscedasticity and consistent estimators for the variance of the estimation errors like Eicker-White. Additionally, we discuss maximum-likelihood estimation, and the Wald-LM-LR tests and their equivalence.
Section 01Quantitative Methods in Economics II
INSTRUCTOR: PlobergerView Course Listing