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Economic Forecasting Techniques

Code 12431
Year 1
Semester S2
ECTS Credits 6
Workload OT(15H)/TP(30H)
Scientific area Economics
Entry requirements The basics of statistics.
Mode of delivery Face-to-face
Work placements Not applicable
Learning outcomes -Learn the importance of forecasting economic quantities
-Learn some of the most important forecasting techniques in economics, whether short, medium, long or very long term
-Learn how to deal with seasonality in economic forecasting using several methodologies
-Learn to perform economic forecasts in the short, medium and long term and even very long term.
Learn how to make simultaneous forecasts of several variables using VAR and VAR/ECM (VECM) models.
Syllabus - Introduction to Forecasting and Model Selection in Economics
- Time Series Decomposition and Classic Forecasting: Trend, Seasonal, Cyclical and Irregular Effects
- Forecasting with Single and Double Moving Averages and Single and Double Exponential Smoothing
- Forecasting with Single and Multiple Regression Models
- Forecasting with Advanced Models: Box-Jenkins Methodology and ARIMA models
- Forecasting Series with Additive and Multiplicative Seasonality
- Forecasting Multiple Variables with VAR and VAR/ECM Models
Main Bibliography Elliott, G., & Timmermann, A. (2016). Economic Forecasting. Princeton University Press.
Fuleky, P. (2020). Macroeconomic Forecasting in the Era of Big Data. Springer
Ghysels, E., & Marcelino, M. (2018). Applied Economic Forecasting using Time Series Methods. Oxford University Press
Mills, T. C. (2019). Applied Time Series Analysis: A Practical Guide to Modeling and Forecasting. Academic Press.
Powers, D. (2019). On Trend: The Business of Forecasting the Future. University of Illinois Press.
Agung, I. G. N. (2019). Advanced Time Series Data Analysis: Forecasting Using Eviews. Wiley
Teaching Methodologies and Assessment Criteria The subject is always taught in a practical perspective, always in the computer lab with continuous use of software. In the presentation of the subjects, the projection of slides and the creation of scripts in real time are frequently used. In economic and econometric applications, data collected from national and international databases is used. These are then introduced into the software in order to estimate the models, carry out statistical tests, interpret the economic results and forecast economic quantities in the short, medium, long or very long term.
The teaching-learning classification is made up of 2 moments of assessment: attendance (50%) and individual work (50%).
Language Portuguese. Tutorial support is available in English.
Last updated on: 2022-06-15

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