Econometrics II

4.0 credits

Brief description: "This course focuses on the fundamental issue of identification in econometrics and covers modern econometric models and techniques, including asymptotic theory, M-estimation, maximum likelihood methods, Generalized Method of Moments, pseudo-maximum likelihood methods, quantile regression, and empirical likelihood methods. While emphasizing econometric theory and asymptotic properties, students will also apply these techniques to various data sets and conduct Monte Carlo simulations to evaluate the finite sample performances of different estimators and testing procedures." Topics covered: M-Estimation; Maximum Likelihood; Pseudo-Maximum Likelihood; Nonlinear Least Squares; Generalized Method of Moments (GMM); Quantile Regression; Empirical Likelihood Estimation; Monte Carlo; Treatment Effect.