Title

Estimation of the autoregressive order in the presence of measurement errors

Document Type

Journal article

Source Publication

Economics Bulletin

Publication Date

5-1-2006

Volume

3

Issue

12

First Page

1

Last Page

10

Abstract

Most of the existing autoregressive models presume that the observations are perfectly measured. In empirical studies, the variable of interest is unavoidably measured with various kinds of errors. Thus, misleading conclusions may be yielded due to the inconsistency of the parameter estimates caused by the measurement errors. Thus far, no theoretical result on the direction of bias of the lag order estimate is available in the literature. In this note, we will discuss the estimation an AR model in the presence of measurement errors. It is shown that the inclusion of measurement errors will drastically increase the complexity of the problem. We show that the lag lengths selected by the AIC and BIC are increasing with the sample size at a logarithmic rate.

Print ISSN

15452921

Publisher Statement

Copyright © 2006 Economics Bulletin.

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Recommended Citation

Chong, T. T.-L., Liew, V., Zhang, Y., & Wong, C.-L. (2006). Estimation of the autoregressive order in the presence of measurement errors. Economics Bulletin, 3(12), 1-10.