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Estimating autocorrelations in the presence of deterministic trends

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  • Wang, Shin-Huei

    (Université catholique de Louvain (UCL). Center for Operations Research and Econometrics (CORE))

  • Hafner, Christian

    (Université catholique de Louvain (UCL). Center for Operations Research and Econometrics (CORE)
    ---)

Abstract

This paper considers the impact of ordinary least squares (OLS) detrending and the first difference (FD) detrending on autocorrelation estimation in the presence of long memory and deterministic trends. We show that the FD detrending results in inconsistent autocorrelation estimates when the error term is stationary. Thus, the FD detrending should not be employed for autocorrelation estimation of the detrended series when constructing e.g. portmanteau-type tests. In an empirical application of volume in Dow Jones stocks, we show that for some stocks, OLS and FD detrending result in substantial differences in ACF estimates.

Suggested Citation

  • Wang, Shin-Huei & Hafner, Christian, 2008. "Estimating autocorrelations in the presence of deterministic trends," LIDAM Discussion Papers CORE 2008073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:2008073
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    References listed on IDEAS

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    1. Eugene Canjels & Mark W. Watson, 1997. "Estimating Deterministic Trends In The Presence Of Serially Correlated Errors," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 184-200, May.
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    More about this item

    Keywords

    autocorrelations; OLS; first difference detrending; long memory.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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