PROPERTIES OF PREDICTORS IN OVERDIFFERENCED NEARLY NONSTATIONARY AUTOREGRESSION

Daniel Peña and Ismael Sánchez
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Ismael Sánchez: Universidad de Alicante

Working Papers. Serie AD from Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie)

Abstract: This paper analyzes the effect of overdifferencing a stationary AR(p+1) process whoselargest root is near unity. It is found that if the process is nearly nonstationary, the estimators ofthe overdifferenced model ARIMA (p, 1, 0) are root-T consistent. It is also found that thismisspecified ARIMA (p, 1, 0) has lower predictive mean squared error, to terms of small order,that the properly specified AR(p+1) model due to its parsimony. The advantage of theoverdifferenced predictor depends on the remaining roots, the prediction horizon, and the meanof the process.

Keywords: Autoregressive processes; near nonstationarity; overdifferencing (search for similar items in EconPapers)
Pages: 25 pages
Date: 1999-05
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http://www.ivie.es/downloads/docs/wpasad/wpasad-1999-08.pdf Fisrt version / Primera version, 1999 (application/pdf)

Related works:
Journal Article: Properties of Predictors in Overdifferenced Nearly Nonstationary Autoregression (2001)
Working Paper: Properties of predictors in overdifferenced nearly nonstationary autoregression (1995)
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Persistent link: https://EconPapers.repec.org/RePEc:ivi:wpasad:1999-08

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