Temporal Disaggregation of Overlapping Noisy Quarterly Data: Estimation of Monthly Output from Uk Value-added Tax Data

Abstract

SummaryThe paper derives monthly estimates of business sector output in the UK from rolling quarterly value-added tax based turnover data. The administrative nature of the value-added tax data implies that their use could ultimately yield a more precise and granular picture of output across the economy. However, they show two particular features which complicate their exploitation: they are overlapping and subject to substantial noise. This motivates our choice of a multivariate unobserved components model for filtering and disaggregating temporally the aggregate figures. After illustrating our method by using one industry as a case-study, we estimate monthly seasonally adjusted gross output figures for the 75 industries for which the data are available. Our results show material differences from the existing output profile.