This is an introduction to econometrics, which provides a reasonably rigorous treatment in econometric techniques that are useful in obtaining information about the relationship between variables from empirical data. We can then use the information to test hypothesis derived from theory or to make forecast about future events. We start with the basic linear regression model, and discuss in details about its estimation, statistical properties and method of inference. Then, we discuss more complicated models when certain basic assumptions are not satisfied. We will also discuss specific models that are used for panel data and time series data. The techniques introduced in this class are particularly helpful for your thesis research.
The language for this class is English, including lectures, class materials, homework and exams.
You will need to use statistical software to perform data analysis. I will demonstrate the use of Stata in this class, which is commonly used in research. Other software such as EViews, R, SAS, etc., can also be used.
Probability and Mathematical Statistics, Calculus, Linear Algebra, Basic Microeconomics and Macroeconomics.