Testing time series data compatibility for benchmarking

Benoît Quennevillle and Christian Gagné

International Journal of Forecasting, 2013, vol. 29, issue 4, 754-766

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.

Keywords: Autoregressive process; Chi-square distribution; Likelihood ratio test; Score test; Wald test (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:29:y:2013:i:4:p:754-766

DOI: 10.1016/j.ijforecast.2011.10.001

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