✦ LIBER ✦

Forecasting with balanced state space representations of multivariate distributed lag models

✍ Scribed by Stefan Mittnik

Publisher: John Wiley and Sons
Year: 1990
Tongue: English
Weight: 681 KB
Volume: 9
Category: Article
ISSN: 0277-6693
DOI: 10.1002/for.3980090302

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✦ Synopsis

A procedure for estimating state space models for multivariate distributed lag processes is described. It involves singular value decomposition techniques and yields an internally balanced state space representation which has attractive properties. Following the specifications of a forecasting competition, the approach is applied to generate ex-post forecasts for US real GNP growth rates. The forecasts of the estimated state space model are compared to those of twelve econometric models and an ARIMA model.

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## Abstract This paper presents a methodology for modelling and forecasting multivariate time series with linear restrictions using the constrained structural state‐space framework. The model has natural applications to forecasting time series of macroeconomic/financial identities and accounts. The