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Estimation of the Autoregressive Order in the Presence of Measurement Errors

Author

Listed:
  • Terence Tai-Leung Chong

    (The Chinese University of Hong Kong)

  • Chi-Leung Wong

    (University of British Columbia)

  • Venus Liew

    (Universiti Putra Malaysi)

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.

Suggested Citation

  • Terence Tai-Leung Chong & Chi-Leung Wong & Venus Liew, 2006. "Estimation of the Autoregressive Order in the Presence of Measurement Errors," Economics Bulletin, AccessEcon, vol. 3(12), pages 1-10.
  • Handle: RePEc:ebl:ecbull:eb-06c20003
    as

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    References listed on IDEAS

    as
    1. Chong, Terence Tai-Leung, 2001. "Structural Change In Ar(1) Models," Econometric Theory, Cambridge University Press, vol. 17(1), pages 87-155, February.
    2. Jushan Bai & Haiqiang Chen & Terence Tai-Leung Chong & Seraph Xin Wang, 2008. "Generic consistency of the break-point estimators under specification errors in a multiple-break model," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 287-307, July.
    3. Chong, Terence Tai-Leung, 2000. "Estimating the differencing parameter via the partial autocorrelation function," Journal of Econometrics, Elsevier, vol. 97(2), pages 365-381, August.
    4. 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.
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    More about this item

    Keywords

    Autoregressive Process Measurement Error Akaike Information Criterion Bayesian Information Criterion;

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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