Temporal Disaggregation of Gross Domestic Product Data with Night-Time Lights Data for South Africa

Abstract

The absence of high-frequency time series data is a real constraint for many researchers worldwide. Generating high-frequency economic data, especially at the sub-national level, generates significant advantages and opportunities. Research otherwise impossible now becomes possible and indeed desirable. Therefore, this study aims to investigate the usefulness of several temporal disaggregation methods and the reliability of the derived results. Temporal disaggregation is one such method that can be used to generate high-frequency time series data from low-frequency time series data. The methods employed will specifically refer to methods that use related series as the high-frequency time series data related to the South African economy. To this effect, monthly night-time lights sensed by satellite were assessed. The results derived through the study seem to generate robust estimates suggesting that it is indeed possible to use night-time lights as a related indicator and the various temporal disaggregation methods contained within the Ecotrim computer software program and ‘tempdisagg’ R package to disaggregate annual national and provincial gross domestic product (GDP). The derived quarterly and monthly national and provincial GDP time series/data will subsequently assist in addressing the constraints researchers face, especially at a sub-national level. From a policy perspective, policymakers should note that remote sensing technologies offer unique opportunities to conduct sub-national economic policy and research.