(), Farid Jimmy Boumediene
() and Pär Österholm
Jan-Erik Antipin: National Institute of Economic Research, Postal: National Institute of Economic Research, P.O. Box 3116, SE-103 62 Stockholm, Sweden
Farid Jimmy Boumediene: Ministry of Finance, Postal: Ministry of Finance, Drottninggatan 21, 103 33 Stockholm, Sweden
Pär Österholm: Sveriges Riksbank, Postal: Sveriges Riksbank, 103 37 Stockholm, Sweden
Abstract: This paper assesses the usefulness of constant gain least squares when forecasting inflation. An out-of-sample forecast exercise is conducted, in which univariate autoregressive models for inflation in Australia, Swe-den, the United Kingdom and the United States are used. The results suggest that it is possible to improve the forecast accuracy by employing constant gain least squares instead of ordinary least squares. In particular, when using a gain of 0.05, constant gain least squares generally outper-forms the corresponding autoregressive model estimated with ordinary least squares. In fact, at longer forecast horizons, the root mean square forecast error is reliably lowered for all four countries and for all lag lengths considered in the study.
26 pages, February 1, 2012
Full text files
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 ().
This page generated on 2018-01-23 23:36:16.