Temporal Disaggregation of Time Series with Regularization Term

Sebastian Wójcik

doi:10.56583/br.505

Published : 2016-11-22

Vol. 14 No. 3 (2016)

Temporal Disaggregation of Time Series with Regularization Term

Sebastian Wójcik

DOI: https://doi.org/10.56583/br.505

Abstract

Methods of temporal disaggregation are used to obtain high frequency time series from the same low frequency time series — so-called disaggregation—with respect to some additional consistency conditions between low and high frequency series. Conditions depend on the nature of the data — e.g., stack, flow, average and may pertain to the sum, the last value and the average of the obtained high frequency series, respectively. Temporal disaggregation methods are widely used all-over the world to disaggregate for example quarterly GDP. These methods are usually two-stage methods which consist of regression and benchmarking. In this article we propose a method which performs regression and benchmarking at the same time and allows to set a trade-off between them.

Keywords:

temporal disaggregation, benchmarking, time series analysis, regularization term

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Wójcik, S. (2016). Temporal Disaggregation of Time Series with Regularization Term. Regional Barometer. Analyses & Prognoses, 14(3), 183–188. https://doi.org/10.56583/br.505

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