Econometrics
I took the Ph.D.-level econometrics theory course at NTU. The econometrics theory includes four parts, and the attachments below are my course notes for words on blackboard in one parts of courses. This part goes through topics in the classic Hansen and Hayashi textbooks, including Asymptotic Theory, Prediction Errors, Model Selections, Non-linear LS, GMM, Constrained LS, Hypothesis Testing, Minimum Distance Estimators, James-Stein Estimator, Bayesian, with a theoretical perspective. Other parts of this course include OLS, GLS, 2SLS, SEM, MLE, M-Estimation, and Casual Inference.
In addition, I also took the computational econometrics to learn about the computational methods for economic research. I’ve learned about Numerical Optimization, Bootstrapping, Simulation-Based Estimation, Bayesian Estimation and MCMC, and Dynamic Programming.