Trương Thanh Vũ

Applied Econometrics Professor William Greene

1. The Paradigm of Econometrics
2. Conditional Means and the Linear Regression Model
3. Linear Least Squares
4. Least Squares Algebra – Partial Regression and Partial Correlation
5. Regression Algebra and a Fit Measure; Restricted Least Squares
6. Finite Sample Properties of the Least Squares Estimator
7. Estimating the Variance of the Least Squares Estimator
8. Hypothesis Testing in the Linear Regression Model
9. Hypothesis Tests: Analytics and an Application
10. Prediction in the Classical Regression Model
11. Asymptotic Distribution Theory
12. Asymptotic Results for the Classical Regression Model
13. Instrumental Variables Estimation
14. Nonlinear Regression and Nonlinear Least Squares Estimation
15. The Generalized Regression Model
16. Applications of Feasible GLS (Two Step) Estimation
17. Some Linear Models for Panel Data
18. Maximum Likelihood Estimation
19. Applications of Maximum Likelihood Estimation and a Two Step Estimator
20. Generalized Method of Moments – GMM Estimation
21. Models for Discrete Choice
22. Simulation Based Estimation – Classical and Bayesian
23. Sample Selection
24. Time Series Data
25. Non and Semiparametric Approaches – Quantile Regression

Filed under: Econometric, Stata

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