Teaching

By the end of this course, participants will:

1. gain knowledge and understanding of basic concepts of probability theory and probability distributions;

2. learn to select an appropriate method to solve typical problems in probability theory and applying these methods correctly;

3. be able to a verbally described problems in the language of probability theory to solve the problem;

4. gain knowledge of probability distributions which occur most commonly in practice and being able to use the known properties of these distributions to solve problems.

By the end of this course, participants will:

1. have detailed knowledge of analysing multivariate time series with a focus on stationarity and non-stationarity;

2. understand the limit theory of behind stationary VARs;

3. understand the limit theory of behind unit root tests;

4. understand the limit theory behind spurious regression and cointegration;

5. be familiar with advanced unit-root and cointegration tests;

6. understand the concept of cross-sectional dependence in static panel data models;

7. understand the challenges in estimating dynamic panel data models;

8. understand the challenges in designing, estimating and analysing linear econometric models for non-stationary time-series and panel data.