Course overview
The objective of this course is to study more advanced topics in econometrics. Students are expected to have knowledge in statistics and multiple regression models at the level of Econometrics III/PG or equivalent. Topics typically include linear regression models, instrument variables (IV) estimation, generalized method of moment (GMM), maximum likelihood estimation (MLE), limited dependent variable (LDV) models, treatment effect and sample selection corrections, panel data methods, Monte Carlo simulations and bootstrap methods. The emphasis is on understanding the models and the related theories. Through the course, we will apply the theories developed to real-world data and interpret the estimation results in many different respects.
Course learning outcomes
- Acquire knowledge of various advanced econometric models, estimation methods and related econometric theories
- Apply the above theories to empirical data or be able to develop new econometric theory
- Write Matlab code and how to use statistical packages like STATA to estimate econometric models using real world data
- Work in groups when doing problem solving and computer exercises, and present relevant research papers in the field of applied or theoretical econometrics
- Conduct econometric analysis of data properly and understand the results