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Antipin, J., Boumediene, F., Österholm, P. On the Usefulness of Constant Gain Least Squares when Forecasting the Unemployment Rate. Applied Economics Quarterly, 60(4), 315-336. https://doi.org/10.3790/aeq.60.4.315
Antipin, Jan-Erik; Boumediene, Farid Jimmy and Österholm, Pär "On the Usefulness of Constant Gain Least Squares when Forecasting the Unemployment Rate" Applied Economics Quarterly 60.4, , 315-336. https://doi.org/10.3790/aeq.60.4.315
Antipin, Jan-Erik/Boumediene, Farid Jimmy/Österholm, Pär: On the Usefulness of Constant Gain Least Squares when Forecasting the Unemployment Rate, in: Applied Economics Quarterly, vol. 60, iss. 4, 315-336, [online] https://doi.org/10.3790/aeq.60.4.315

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On the Usefulness of Constant Gain Least Squares when Forecasting the Unemployment Rate

Antipin, Jan-Erik | Boumediene, Farid Jimmy | Österholm, Pär

Applied Economics Quarterly, Vol. 60 (2014), Iss. 4 : pp. 315–336

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Finnish Tax Administration, P.O. Box 325, 00052 VERO, Finland. Phone: +358 40 668 4931.

Confederation of Swedish Enterprise, Storgatan 19, 114 82 Stockholm, Sweden. Phone: +46 70 345 6041.

National Institute of Economic Research, Box 3116, 103 62 Stockholm, Sweden. Phone: +46 8 453 5948.

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 employed. 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 macroeconomic 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.

JEL Classification: E24, E27