✦ LIBER ✦

The impact of measurement errors on ARMA prediction

✍ Scribed by Sergio G. Koreisha; Yue Fang

Publisher: John Wiley and Sons
Year: 1999
Tongue: English
Weight: 174 KB
Volume: 18
Category: Article
ISSN: 0277-6693
DOI: 10.1002/(sici)1099-131x(199903)18:2<95::aid-for717>3.0.co;2-e

No coin nor oath required. For personal study only.

✦ Synopsis

Measurement errors can have dramatic impact on the outcome of empirical analysis. In this article we quantify the eects that they can have on predictions generated from ARMA processes. Lower and upper bounds are derived for dierences in minimum mean squared prediction errors (MMSE) for forecasts generated from data with and without errors. The impact that measurement errors have on MMSE and other relative measures of forecast accuracy are presented for a variety of model structures and parameterizations. Based on these results the need to set up the models in state space form to extract the signal component appears to depend upon whether processes are nearly non-invertible or non-stationary or whether the noise-to-signal ratio is very high.

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