Nonlinear Forecasting Using Large Datasets: Evidences on US and Euro Area Economies

Alessandro Giovannelli

No 255, CEIS Research Paper from Tor Vergata University, CEIS

Abstract: The primary objective of this paper is to propose two nonlinear extensions for macroeconomic forecasting using large datasets. First, we propose an alternative technique for factor estimation, i.e., kernel principal component analysis, which allows the factors to have a nonlinear relationship to the input variables. Second, we propose artificial neural networks as an alternative to the factor augmented linear forecasting equation. These two extensions allow us to determine whether, in general, there is empirical evidence in favor of nonlinear methods and, in particular, to verify whether the nonlinearity occurs in the estimation of the factors or in the functional form that links the target variable to the factors. In an effort to verify the empirical performances of the methods proposed, we conducted several pseudo forecasting exercises on the industrial production index and consumer price index for the Euro area and US economies. These methods were employed to construct the forecasts at 1-, 3-, 6-, and 12-month horizons using a large dataset containing 259 predictors for the Euro area and 131 predictors for the US economy. The results obtained from the empirical study suggest that the estimation of nonlinear factors, using kernel principal components, significantly improves the quality of forecasts compared to the linear method, while the results for artificial neural networks have the same forecasting ability as the factor augmented linear forecasting equation.

Keywords: Kernel Principal Component Analysis; Large Dataset; Artificial Neural Networks; QuickNet; Forecasting (search for similar items in EconPapers)
JEL-codes: C13 C33 C45 C53 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2012-11-08, Revised 2012-11-08
New Economics Papers: this item is included in nep-eec, nep-ets, nep-for and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://ceistorvergata.it/RePEc/rpaper/RP255.pdf Main text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rtv:ceisrp:255

Ordering information: This working paper can be ordered from
CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma
https://ceistorvergata.it

Access Statistics for this paper

More papers in CEIS Research Paper from Tor Vergata University, CEIS CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma. Contact information at EDIRC.
Bibliographic data for series maintained by Barbara Piazzi ().