Management Science II

Indicative content

1. Characteristics of econometric approach to the data analysis and 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. Least squares method. General linear model.
4. Model verification. Coefficient of determination. Testing the statistical significance of individual parameters of the model. Interval estimation and hypothesis testing.
5. Qualitative variables and their modeling.
6. Regression on dummy variables. Seasonality, fluctuations, structural breaks, and their testing
7. Functional forms of regression models – log-log model, semi-log models, reciprocal models.
8. Violations of the assumptions of the classical model. Autocorrelation – detecting and implications, solving, generalized least squares method.
9. Introduction to time series analysis. Stationarity of processes and its testing using unit root tests.
10. Co-integration of non-stationary time series, Engle and Granger procedure, error correction models and their estimation.
11. Applications of single equation econometric models.
12. Forecasting. Forecasting error. Confidence interval for the forecasts. Naive forecasts.
13. Forecasting application of econometric model.