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Uncertainty measures for economic accounts

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  • Nino Mushkudiani
  • Jeroen Pannekoek
  • Li-Chun Zhang

Abstract

The problem of adjusting large systems of estimated economic or social accounts such that they fulfill known functional relationships can be quite complex. For such complex systems, evaluating the accuracy of the estimates after the adjustment is difficult since these estimates are defined by unadjusted initial estimates, the accounting equations and the adjustment method. In this paper, we consider such accounting systems as a single entity and develop scalar uncertainty measures that are based on the first two moments of the joint distribution of final adjusted estimates. Scalar measures can help to effectively communicate to the users the relevant uncertainty of disseminated macro-economic accounts and can assist the producer in choosing and improving adjustment method and input estimators. The proposed approach is illustrated both analytically and by simulation. Applications to supply and use tables and to time series data are presented.

Suggested Citation

  • Nino Mushkudiani & Jeroen Pannekoek & Li-Chun Zhang, 2020. "Uncertainty measures for economic accounts," Economic Systems Research, Taylor & Francis Journals, vol. 32(4), pages 476-501, October.
    • Handle: RePEc:taf:ecsysr:v:32:y:2020:i:4:p:476-501
    DOI: 10.1080/09535314.2020.1792843
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    Cited by:

    1. Paul A. Smith, 2021. "Estimating Sampling Errors in Consumer Price Indices," International Statistical Review, International Statistical Institute, vol. 89(3), pages 481-504, December.

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