Econometrics and Forecasting 2400-ZEWW1048

The Econometrics and Forecasting is a course focused on the theory and practical application of econometric methods used to analyse economic data and build forecasts.
The course begins with the Ordinary Least Squares method. Students derive the OLS estimator and examine the properties of the regression hyperplane. The course covers the assumptions of the classical linear regression model, the interpretation of regression coefficients, and the conditions required for reliable estimation and inference. Particular attention is given to the interpretation of econometric results and to the diagnosis of problems that may arise in empirical data.
The course also introduces panel data methods. Students test for individual effects and learn how to estimate fixed effects models and random effects models. The Hausman test is discussed as a tool for choosing between alternative approaches to modelling individual effects.
The time series part of the course covers the main concepts and methods used in time series analysis and forecasting. Students learn about time series decomposition and the concept of stationarity. The Dickey-Fuller test is introduced as a method for testing for unit roots and assessing stationarity. The course also covers autoregressive models, moving average models, and autoregressive moving average models.
Throughout the course, emphasis is placed on understanding the assumptions behind econometric models, interpreting empirical results, diagnosing potential problems with data, and applying appropriate econometric techniques to economic and financial time series.
The classes will be conducted in a computer laboratory in the form of seminars. For each topic, a theoretical introduction will be provided, followed by examples of how to conduct the relevant analysis using statistical software. In addition, exercises will be completed during the classes to practice the interpretation of the results obtained.