Econometrics II (in English)

Indicative content

1. General linear model with more than one explanatory variables.
2. Structural changes of variables and their consequences on the estimation of models.
Problem of under-parameterization and over-parameterization.
3. Violations of the assumptions of the classical model. Heteroskedasticity – detecting andimplications, solving, weighted least squares method.
4. Heteroskedasticity in time series models. Violations of the assumptions of the classical model. Multicollinearity – detecting andimplications, solution options.
5. Basic stochastic processes, white noise, random walk and their properties.
6. Autoregressive processes and moving average processes. Box-Jenkins and ARIMA models.
7. Seasonal time series, Box-Jenkins methodology of SARIMA models.
8. Stationarity of processes and its testing using unit root tests.
9. Non-stationarity of processes with respect to mean and variance, transformation of time seriesgenerated by non-stationary processes, differentiation and logarithmization.
10. Co-integration of non-stationary time series, Engle and Granger procedure, error correctionmodels and their estimation.
11. Estimation using instrumental variables, testing of instruments and endogeneity.
12. Introduction to multi-equation models. Two-stage least squares method.
13. Multi-equation models, recursive models, and models with seemingly unrelated regressions. Introduction to panel data analysis.