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Testing time series data compatibility for benchmarking

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  • Quennevillle, Benoît
  • Gagné, Christian

Abstract

Compatibility testing determines whether two series, say a sub-annual and an annual series, both of which are subject to sampling errors, can be considered suitable for benchmarking. We derive statistical tests and discuss the issues with their implementation. The results are illustrated using the artificial series from Denton (1971) and two empirical examples. A practical way of implementing the tests is also presented.

Suggested Citation

  • Quennevillle, Benoît & Gagné, Christian, 2013. "Testing time series data compatibility for benchmarking," International Journal of Forecasting, Elsevier, vol. 29(4), pages 754-766.
    • Handle: RePEc:eee:intfor:v:29:y:2013:i:4:p:754-766
    DOI: 10.1016/j.ijforecast.2011.10.001
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    References listed on IDEAS

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    1. J. Durbin & B. Quenneville, 1997. "Benchmarking by State Space Models," International Statistical Review, International Statistical Institute, vol. 65(1), pages 23-48, April.
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    1. Weigand Roland & Wanger Susanne & Zapf Ines, 2018. "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, vol. 34(1), pages 265-301, March.

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