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Estimation of the Autoregressive Order in the Presence of Measurement Errors

  • Terence Tai-Leung Chong

    ()

    (The Chinese University of Hong Kong)

  • Chi-Leung Wong

    ()

    (University of British Columbia)

  • Venus Liew

    ()

    (Universiti Putra Malaysi)

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.

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Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 3 (2006)
Issue (Month): 12 ()
Pages: 1-10

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Handle: RePEc:ebl:ecbull:eb-06c20003
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  1. Chong, Terence Tai-Leung, 2001. "Structural Change In Ar(1) Models," Econometric Theory, Cambridge University Press, vol. 17(01), pages 87-155, February.
  2. Venus Khim-Sen Liew & Terence Tai-leung Chong, 2005. "Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors," Economics Bulletin, AccessEcon, vol. 3(19), pages 1-5.
  3. Terence Tai-Leung, Chong, 1998. "Estimating the Differencing Parameter Via the Partial Autocorrelation Function," Departmental Working Papers _088, Chinese University of Hong Kong, Department of Economics.
  4. Seraph Xin Wang & Terence Tai-leung Chong & Haiqiang Chen, 2004. "Generic Consistency of the Break-Point Estimators under Specification Errors in a Multiple-Break Model," Departmental Working Papers _160, Chinese University of Hong Kong, Department of Economics.
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