Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009
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DOI: 10.1016/j.ijforecast.2013.01.003
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- Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009," CREATES Research Papers 2011-28, Department of Economics and Business Economics, Aarhus University.
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- Ferrara, L. & Marcellino, M. & Mogliani, M., 2012. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," Working papers 383, Banque de France.
- Laurent Ferrara & Massimiliano Marcellino & Matteo Mogliani, 2015. "Macroeconomic forecasting during the Great Recession: the return of non-linearity?," Post-Print hal-01635951, HAL.
- Laurent Ferrara & Massimiliano Marcellino & Matteo Mogliani, 2015. "Macroeconomic forecasting during the Great Recession: the return of non-linearity?," Post-Print hal-01385973, HAL.
- Ferrara, Laurent & Marcellino, Massimiliano & Mogliani, Matteo, 2013. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," CEPR Discussion Papers 9313, C.E.P.R. Discussion Papers.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Jan 2021.
- Oscar Claveria & Enric Monte & Salvador Torra, 2015.
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- Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
- Jahn, Malte, 2020. "Artificial neural network regression models in a panel setting: Predicting economic growth," Economic Modelling, Elsevier, vol. 91(C), pages 148-154.
- Oscar Claveria & Enric Monte & Salvador Torra, 2017.
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- Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting”," AQR Working Papers 201701, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2017.
- Jahn, Malte, 2018. "Artificial neural network regression models: Predicting GDP growth," HWWI Research Papers 185, Hamburg Institute of International Economics (HWWI).
- Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.
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More about this item
Keywords
Autometrics; Economic forecasting; Marginal Bridge estimator; Neural network; Nonlinear time series model; QuickNet; RETINA; Root mean squared forecast error;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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