Econometrics II (in English)

Indicative content

General linear model with more than one explanatory variables. Standard assumptions of the linear model and their violations.
2. Model verification, hypothesis testing, application of one-equation models.
3. Structural changes of variables and their consequences on the estimation of models.
4. Simultaneous system of equations and the problem of identification of a multi-equation model.
5. Estimation of parameters of a multi-equation model, two-stage least squares method and its
properties. System methods of parameter estimation.
6. Estimation using instrumental variables, testing of instruments and endogeneity.
7. Prognostic application of a multi-equation model. The core model of the economy.
8. Simulations and scenarios in a multi-equation model. 9. Other types of multi-equation models and their estimation, recursive models, and models with seemingly unrelated regressions. 10. Basic stochastic processes, white noise process, random walk process and their properties. Autoregressive processes and moving average processes. 11. Stationarity of processes and its testing using unit root tests. 12. Non-stationarity of processes with respect to mean and variance, transformation of time series generated by non-stationary processes, differentiation and logarithmization. 13. Co-integration of non-stationary time series, Engle and Granger procedure, error correction models and their estimation.