Uncertainty measures for economic accounts

Abstract

The problem of adjusting economic or social accounts can be quite complex when large accounting equation systems are considered. This is especially true if they must fulfill predefined, known functional relationships. For such complex systems, evaluating the accuracy of the estimates after the adjustment is difficult since they are defined by unadjusted initial estimates, the accounting equations and the adjustment method. In this paper, we consider such systems as a single entity and develop scalar uncertainty measures that capture the adjustment effect as well as the relative contribution of the various input estimates to the final estimated account. The scalar measures are based on the first two moments of the joint distribution of the underlying true accounting system without requiring specification of the distribution in full. 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 will be illustrated both analytically and by simulation. Applications to supply and use tables and to time series data will be presented.

Estimating Sampling Errors in Consumer Price Indices

“…The processing of the weights through the national accounting framework also presents some challenges for quality estimation, although in general, it is expected to improve the quality of the estimated weights by triangulation from different sources. Estimating the variances of outputs balanced in this way is already a challenging problem (Mushkudiani et al, 2020), before the extra complexity of inclusion in a price index is added, and this is a topic needing further study.…”