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Estimating Autocorrelations in the Presence of Deterministic Trends

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  • Wang Shin-Huei

    (Université catholique de Louvain and Beijing Normal University)

  • Hafner Christian

    (Université catholique de Louvain)

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, 2011. "Estimating Autocorrelations in the Presence of Deterministic Trends," Journal of Time Series Econometrics, De Gruyter, vol. 3(2), pages 1-25, April.
  • Handle: RePEc:bpj:jtsmet:v:3:y:2011:i:2:n:4
    DOI: 10.2202/1941-1928.1022
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    More about this item

    Keywords

    autocorrelations; OLS; first difference; 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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