Econometrics I

Indicative content

Course contents - schedule for 13 weeks of the semester
1. Characteristics of econometric approach to the analysis of economic phenomena. Econometric model. Phases of econometric modeling
2. Two-variable regression model. Deterministic and stochastic part of the model, nature of stochastic term. Standard assumptions of a linear model.
3. Estimation of linear model parameters. Statistical properties of estimators. Least squares method. Properties of the least squares method.
4. General linear model. Model in matrix form. Least squares method for k-variable model.
5. Model verification. Coefficient of determination. Testing the statistical significance of individual parameters of the model. Interval estimation and hypothesis testing.
6. Functional forms of regression models – log-log model, semi-log models, reciprocal models.
7. Qualitative variables and their modeling.
8. Regression on dummy variables. Seasonality, fluctuations, structural breaks, and their testing.
9. Violations of the assumptions of the classical model. Autocorrelation – detecting and implications.
10. Violations of the assumptions of the classical model. Autocorrelation – solving, model dynamization and generalized least squares method.
11. Violations of the assumptions of the classical model. Heteroskedasticity – detecting and implications, solving, weighted least squares method.
12. Violations of the assumptions of the classical model. Multicollinearity – detecting and implications, solution options.
13. Forecasting with single-equation model. Forecasting error. Confidence interval for the forecasts.