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GDP Forecasting using Payments Transaction Data

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  • Arunav Das

Abstract

UK GDP data is published with a lag time of more than a month and it is often adjusted for prior periods. This paper contemplates breaking away from the historic GDP measure to a more dynamic method using Bank Account, Cheque and Credit Card payment transactions as possible predictors for faster and real time measure of GDP value. Historic timeseries data available from various public domain for various payment types, values, volume and nominal UK GDP was used for this analysis. Low Value Payments was selected for simple Ordinary Least Square Simple Linear Regression with mixed results around explanatory power of the model and reliability measured through residuals distribution and variance. Future research could potentially expand this work using datasets split by period of economic shocks to further test the OLS method or explore one of General Least Square method or an autoregression on GDP timeseries itself.

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  • Arunav Das, 2021. "GDP Forecasting using Payments Transaction Data," Papers 2101.06478, arXiv.org.
    • Handle: RePEc:arx:papers:2101.06478
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    1. Jennifer Thomas & Joanne Evans, 2010. "There's more to life than GDP but how can we measure it?," Economic & Labour Market Review, Palgrave Macmillan;Office for National Statistics, vol. 4(9), pages 29-36, August.
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