This course requires having an intermediate knowledge of Statistics and of the regression model, but does not require previous knowledge on Time Series. The course is centered on forecasting time series economic variables, referred to firms, economic sectors or at macroeconomic level. The course has been designed with the aim that the students obtain a satisfactory initial knowledge of Time Series Econometrics for economic forecasting including the following aspects.
1.The use of forecasts in decision-taking processes within the firm.
2.The main stylized facts of time series economic variables: trends, seasonality, serial correlation, conditional volatility, innovations.
3.Differences between firm variables according with the above stylized facts and with the different aims of the firm in forecasts at short, medium and long-term level.
4.Forecasting with univariate models for: A) variables with deterministic trend and seasonality; B) variables with stochastic trends and seasonalities; C) forecasting with dynamic regression models.
5.The application of the above models in forecasting real data.
BYPRODUCTS. Learning to face the solution of problems using real data. Knowledge of software for forecasting. Use of forecasting in firms.