Forecasting Inflation Using Constant Gain Least Squares

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

No 126, Working Papers from National Institute of Economic Research

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.

Keywords: Out-of-sample forecasts; Inflation (search for similar items in EconPapers)
JEL-codes: E31 E37 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2012-02-01
New Economics Papers: this item is included in nep-ets, nep-for, nep-mac and nep-mon
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Related works:
Journal Article: Forecasting Inflation Using Constant Gain Least Squares (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:nierwp:0126

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