Scandinavian Working Papers in Economics
HomeAboutSeriesSubject/JEL codesAdvanced Search
Konjunkturinstitutet - National Institute of Economic Research Working Papers, Konjunkturinstitutet - National Institute of Economic Research

No 129:
On the Usefulness of Constant Gain Least Squares when Forecasting the Unemployment Rate

Jan-Erik Antipin (), Farid Jimmy Boumediene () and Pär Österholm ()

Abstract: In this paper, we assess the usefulness of constant gain least squares (CGLS) when forecasting the unemployment rate. Using quarterly data from 1970 to 2009, we conduct an out-of-sample forecast exercise in which univariate autoregressive models for the unemployment rate in Australia, Sweden, the United Kingdom and the United States are em-ployed. Results show that CGLS very rarely outperforms OLS. At horizons of six to eight quarters, OLS is always associated with higher forecast precision, regardless of model size or gain employed for Australia, Sweden and the United States. Our findings suggest that while CGLS has been shown valuable when forecasting certain mac-roeconomic time series, it has shortcomings when forecasting the unemployment rate. One problematic feature is found to be an increased tendency for the autoregressive model to have explosive dynamics when estimated with CGLS.

Keywords: Out-of-sample; forecasts; (follow links to similar papers)

JEL-Codes: E24; E27; (follow links to similar papers)

28 pages, September 10, 2013

Before downloading any of the electronic versions below you should read our statement on copyright.
Download GhostScript for viewing Postscript files and the Acrobat Reader for viewing and printing pdf files.

Full text versions of the paper:

Working-Paper-129-On-the- ... the-Unemployment-Rate.pdf    PDF-file
Download Statistics

Questions (including download problems) about the papers in this series should be directed to Sarah Hegardt Grant ()
Report other problems with accessing this service to Sune Karlsson () or Helena Lundin ().

Programing by
Design by Joachim Ekebom

Handle: RePEc:hhs:nierwp:0129 This page was generated on 2016-12-07 23:04:11