Course overview
This course deepens critical thinking, reasoning, and mathematical problem-solving in time series methods in econometrics (e.g., stationarity; unit roots; autoregressive moving average; forecasting; maximum likelihood estimation; (structural) vector autoregression; co-integration) with an emphasis on understanding the methods and applying them to real-world data.
Course learning outcomes
- Demonstrate knowledge in various advanced time series econometric methods, estimation methods and related econometric theories
- Apply these methods to empirical data or develop new time series econometric theories
- Write code using specialised software
- Use specialised software to estimate time series econometric models using real world data
- Interpret time series models' estimates