On prediction errors in regression models with nonstationary regressors

Details On prediction errors in regression models with nonstationary regressors On prediction errors in regression models with nonstationary regressors

2007-02-26

arxiv.org/abs/math/0702769v1

IMS Lecture Notes Monograph Series 2006, Vol. 52, 60-71

Mathematics

Statistics Theory

Published at http://dx.doi.org/10.1214/074921706000000950 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/p

Scientific paper

10.1214/074921706000000950

In this article asymptotic expressions for the final prediction error (FPE) and the accumulated prediction error (APE) of the least squares predictor are obtained in regression models with nonstationary regressors. It is shown that the term of order $1/n$ in FPE and the term of order $\log n$ in APE share the same constant, where $n$ is the sample size. Since the model includes the random walk model as a special case, these asymptotic expressions extend some of the results in Wei (1987) and Ing (2001). In addition, we also show that while the FPE of the least squares predictor is not affected by the contemporary correlation between the innovations in input and output variables, the mean squared error of the least squares estimate does vary with this correlation.

Affiliated with

Also associated with

No associations

Rating

On prediction errors in regression models with nonstationary regressors does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with On prediction errors in regression models with nonstationary regressors, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On prediction errors in regression models with nonstationary regressors will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-131755