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Differencing Multiple Time Series: Another Look At Canadian Money And Income Data

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  • Helmut Lütkepohl

Abstract

. In multiple time series analysis it is sometimes suggested to remove non‐stationarities of the univariate subseries by differencing prior to the multivariate analysis. It is pointed out that, in general, this is not adequate if AR models are built even if stationarity of the univariate subseries can be induced by differencing. Canadian money and income data that were previously analysed by Hsiao are used to illustrate the resulting problems.

Suggested Citation

  • Helmut Lütkepohl, 1982. "Differencing Multiple Time Series: Another Look At Canadian Money And Income Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(4), pages 235-243, July.
    • Handle: RePEc:bla:jtsera:v:3:y:1982:i:4:p:235-243
    DOI: 10.1111/j.1467-9892.1982.tb00346.x
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    Cited by:

    1. Pierre Duchesne, 2005. "Testing for serial correlation of unknown form in cointegrated time series models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(3), pages 575-595, September.
    2. Gordon Anderson & Jasmin Thomas, 2019. "Measuring Multi-group Polarization, Segmentation and Ambiguity: Increasingly Unequal Yet Similar Constituent Canadian Income Distributions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(3), pages 1001-1032, October.
    3. Erenburg, S. J. & Wohar, Mark E., 1995. "Public and private investment: Are there causal linkages?," Journal of Macroeconomics, Elsevier, vol. 17(1), pages 1-30.
    4. Jeff B. Cromwell & Michael J. Hannan, 1993. "The Utility of Impulse Response Functions in Regional Analysis: Some Critical Issues," International Regional Science Review, , vol. 15(2), pages 199-222, August.

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