Investigating the Predictive Ability of ONS Big Data-Based Indicators

21 Pages Posted: 22 Apr 2021 Last revised: 28 Apr 2021

See all articles by George Kapetanios

George Kapetanios

King's College, London

Fotis Papailias

Quantf Research; University of London, King's College London, Department of Management

Date Written: March 20, 2020

Abstract

This paper investigates the predictive ability of brand new dataset which is based on big unstructured data published by the UK Office for National Statistics as “Faster Indicators of UK Economic Activity”. We consider some indicative ways to be used in macroeconomic nowcasting. Even though ONS confirm that the newly introduced big data-based indicators are not constructed with forecasting purposes in mind, and the applied researcher should be cautious when using them in this way, a simple out-of-sample nowcasting exercise reveals partial evidence that this dataset has some predictive power over GDP growth. Our results, which show a positive and encouraging first step towards the utilisation of this type of data, suggest that national statistics agencies should allocate more resources in constructing big data-based databases.

Keywords: Big Data, Nowcasting, Sparse Regressions, Factor Models

JEL Classification: C00

Suggested Citation

Kapetanios, George and Papailias, Fotis, Investigating the Predictive Ability of ONS Big Data-Based Indicators (March 20, 2020). Available at SSRN: https://ssrn.com/abstract=3831765 or http://dx.doi.org/10.2139/ssrn.3831765

George Kapetanios

King's College, London ( email )

30 Aldwych
London, WC2B 4BG
United Kingdom
+44 20 78484951 (Phone)

Fotis Papailias (Contact Author)

Quantf Research ( email )

London
United Kingdom

HOME PAGE: http://www.quantf.com

University of London, King's College London, Department of Management ( email )

150 Stamford Street
London, SE1 9NN
United Kingdom

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