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The Data Measurement Process for UK GNP: Stochastic Trends, Long Memory, and Unit Roots

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  • Patterson, Kerry

Abstract

Much published data is subject to a process of revision due, for example, to additional source data, which generates multiple vintages of data on the same generic variable, a process termed the data measurement process or DMP. This article is concerned with several interrelated aspects of the DMP for UK Gross National Product. Relevant questions include the following. Is the DMP well behaved in the sense of providing a single stochastic trend in the vector time series of vintages? Is one of the vintages of data, for example the "final", the sole vintage generating the long-memory component? Does the multivariate framework proposed here add to the debate on the existence of a unit root in GNP? The likely implicit assumptions of users (that the DMP is well behaved and the final vintage is "best") can be cast in terms of testable hypotheses; and we show that these "standard" assumptions have not always been empirically founded. Copyright © 2002 by John Wiley & Sons, Ltd.

Suggested Citation

  • Patterson, Kerry, 2002. "The Data Measurement Process for UK GNP: Stochastic Trends, Long Memory, and Unit Roots," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(4), pages 245-264, July.
    • Handle: RePEc:jof:jforec:v:21:y:2002:i:4:p:245-64
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    Cited by:

    1. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
    2. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
    3. Thomas A. Knetsch & Hans‐Eggert Reimers, 2009. "Dealing with Benchmark Revisions in Real‐Time Data: The Case of German Production and Orders Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 209-235, April.
    4. Hecq, A.W. & Urbain, J.R.Y.J. & Gengenbach, C., 2011. "Are panel unit root tests useful for real-time data?," Research Memorandum 012, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    5. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
    6. Steve Cook, 2008. "Cross‐data‐vintage Encompassing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 849-865, December.
    7. Garratt, Anthony & Lee, Kevin & Mise, Emi & Shields, Kalvinder, 2009. "Real time representation of the UK output gap in the presence of model uncertainty," International Journal of Forecasting, Elsevier, vol. 25(1), pages 81-102.

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