EconPapers    
Economics at your fingertips  
 

Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009

Anders Kock and Timo Teräsvirta ()

International Journal of Forecasting, 2014, vol. 30, issue 3, 616-631

Abstract: In this work we consider the forecasting of macroeconomic variables during an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feed-forward autoregressive neural network models. What makes these models interesting in the present context is the fact that they form a class of universal approximators and may be expected to work well during exceptional periods such as major economic crises. Neural network models are often difficult to estimate, and we follow the idea of White (2006) of transforming the specification and nonlinear estimation problem into a linear model selection and estimation problem. To this end, we employ three automatic modelling devices. One of them is White’s QuickNet, but we also consider Autometrics, which is well known to time series econometricians, and the Marginal Bridge Estimator, which is better known to statisticians. The performances of these three model selectors are compared by looking at the accuracy of the forecasts of the estimated neural network models. We apply the neural network model and the three modelling techniques to monthly industrial production and unemployment series from the G7 countries and the four Scandinavian ones, and focus on forecasting during the economic crisis 2007–2009. The forecast accuracy is measured using the root mean square forecast error. Hypothesis testing is also used to compare the performances of the different techniques.

Keywords: Autometrics; Economic forecasting; Marginal Bridge estimator; Neural network; Nonlinear time series model; QuickNet; RETINA; Root mean squared forecast error (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207013000265
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009 (2011) Downloads
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:eee:intfor:v:30:y:2014:i:3:p:616-631

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

 
Page updated 2019-08-23
Handle: RePEc:eee:intfor:v:30:y:2014:i:3:p:616-631