Exponential smoothing with regressors: Estimation and initialization

Issue title: Estimation, Testing and Forecasting in Econometrics

Subtitle:

Guest editors: Jiti Gao and Maxwell L. King

Article type: Research Article

Authors: Osman, Ahmad Farid^{a; *} | King, Maxwell L.^b

Affiliations: [a] Department of Applied Statistics, University of Malaya, Kuala Lumpur, Malaysia | [b] Department of Econometrics and Business Statistics, Monash University, Clayton, Victoria, Australia

Correspondence: [*] Corresponding author: Ahmad Farid Osman, Department of Applied Statistics, University of Malaya, 50603 Kuala Lumpur, Malaysia. Tel.: +603 7967 3665; E-mail:[email protected]

Abstract: The main objective of this paper is to outline the estimation and initialization procedures for the exponential smoothing with regressors forecasting approach which was recently introduced. The paper also discusses what restrictions need to be imposed during the estimation process so that the algorithm satisfies the forecastability conditions. An empirical study using real non-seasonal data shows that the new approach sometimes has the ability to produce better forecasts than the existing exponential smoothing methods without regressors.

Keywords: Time-varying parameter, state space representation, time series

DOI: 10.3233/MAS-150329

Journal: Model Assisted Statistics and Applications, vol. 10, no. 3, pp. 253-263, 2015