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Implications of temporal aggregation on the relation between two time series

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Abstract

Using a simple theoretical model and giving an empirical example it is investigated if it matters whether we use (monthly) averages or end-of-period (month) data in performing Granger-causality tests. It is shown that no major problems are to be expected if the two series are temporally aggregated in the same way, but non-trivial problems can occur if the two series have different kinds of temporal aggregation.

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Authors and Affiliations

  1. Fachbereich Wirtschaftswissenschaften, Universität Osnabrück, Postfach 4469, D-4500, Osnabrück

    G. Kirchgässner

  2. Fachbereich Wirtschaftswissenschaften, Freie Universität Berlin, Boltzmannstraße 20, D-1000, Berlin 33

    J. Wolters

Authors
  1. G. Kirchgässner
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  2. J. Wolters
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Additional information

We gratefully acknowledge financial support from the Deutsche Forschungsgemeinschaft by Grant No. 322 147. We thank Gerd Ronnig and a referee for helpful comments and suggestions, Bärbel Finkenstädt for performing the computations and Anna Rushing-Jungeilges for editing the paper in English.

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Kirchgässner, G., Wolters, J. Implications of temporal aggregation on the relation between two time series. Statistical Papers 33, 1–19 (1992). https://doi.org/10.1007/BF02925307

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  • DOI: https://doi.org/10.1007/BF02925307

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