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Sensitivity of univariate AR(1) time-series forecasts near the unit root

Banerjee, A.N.

Authors



Abstract

We consider the linear time-series model yt=dt+ut(t=1,...,n), where dt is the deterministic trend and ut the stochastic term which follows an AR(1) process; ut=ut-1+t, with normal innovations t. Various assumptions about the start-up will be made. Our main interest lies in the behaviour of the l-period-ahead forecast yn+1 near =1. Unlike in other studies of the AR(1) unit root process, we do not wish to ask the question whether =1 but are concerned with the behaviour of the forecast estimate near and at =1. For this purpose we define the sth (s=1,2) order sensitivity measure l(s) of the forecast yn+1 near =1. This measures the sensitivity of the forecast at the unit root. In this study we consider two deterministic trends: dt=t and dt=t+tt. The forecast will be the Best Linear Unbiased forecast. We show that, when dt=t, the number of observations has no effect on forecast sensitivity. When the deterministic trend is linear, the sensitivity is zero. We also develop a large-sample procedure to measure the forecast sensitivity when we are uncertain whether to include the linear trend. Our analysis suggests that, depending on the initial conditions, it is better to include a linear trend for reduced sensitivity of the medium-term forecast.

Citation

Banerjee, A. (2001). Sensitivity of univariate AR(1) time-series forecasts near the unit root. Journal of Forecasting, 20(3), 203-229. https://doi.org/10.1002/1099-131x%28200104%2920%3A3%3C203%3A%3Aaid-for766%3E3.0.co%3B2-d

Journal Article Type Article
Publication Date 2001-04
Deposit Date Aug 27, 2008
Journal Journal of Forecasting
Print ISSN 0277-6693
Electronic ISSN 1099-131X
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 20
Issue 3
Pages 203-229
DOI https://doi.org/10.1002/1099-131x%28200104%2920%3A3%3C203%3A%3Aaid-for766%3E3.0.co%3B2-d
Keywords Unit root, Forecasting, Univariate time series, Sensitivity.
Public URL https://durham-repository.worktribe.com/output/1604426