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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 economic forecasting
-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 to perform simultaneous forecasts of several variables using VAR and VAR/ECM (VECM) models and neural networks.
Syllabus - Introduction to Forecasting and Model Selection in Economics
- Time Series Decomposition and Forecasting by the Classical Method: Trend, Seasonal, Cyclical and Irregular Effects
- Forecasting with Simple and Double Moving Averages and Simple and Double Exponential Smoothing
- Forecasting with Simple and Multiple Regression Models
- Forecasting with Advanced Models: Box-Jenkins Methodology and ARIMA models
- Prediction of Series with Additive and Multiplicative Seasonality
- Multiple Variables Forecasting with VAR and VAR/ECM Models
- Series forecasting with neural networks.
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
Language Portuguese. Tutorial support is available in English.
Last updated on: 2023-03-08

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