Template-Type: ReDIF-Paper 1.0
Author-Name: Franses, Ph.H.B.F.
Author-Name-Last: Franses
Author-Name-First: Philip Hans
Author-Person: pfr226
Author-Name: van Dijk, D.J.C.
Author-Name-Last: van Dijk
Author-Name-First: Dick
Author-Person: pva27
Title: The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production
Abstract: Seasonality often accounts for the major part of quarterly or monthly movements in detrended macro-economic time series. In addition, business cycle nonlinearity is a prominent feature of many such 
 series too. A forecaster can nowadays consider a wide variety of time series models which describe seasonal variation and regime-switching behaviour. In this paper we examine the forecasting performance of various models for seasonality and nonlinearity using quarterly industrial production series for 17 OECD countries. We find that forecasting performance varies widely across series, across forecast horizons and across seasons. However, in general, 
 linear models with fairly simple descriptions of seasonality outperform at short forecast horizons, whereas nonlinear models with 
 more elaborate seasonal components dominate at longer horizons.
Creation-Date: 2001-04-26
File-URL: https://repub.eur.nl/pub/1678/feweco20010426095757.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2001-14
Keywords: forecasting, industrial production, nonlinearity, seasonality
Handle: RePEc:ems:eureir:1678