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Forecasting GDP growth from outer space

Jaqueson Galimberti ()

No 2020-02, Working Papers from Auckland University of Technology, Department of Economics

Abstract: We evaluate the usefulness of satellite-based data on night-time lights for forecasting GDP growth across a global sample of countries, proposing innovative location-based indicators to extract new predictive information from the lights data. Our findings are generally favorable to the use of night lights data to improve the accuracy of model-based forecasts. We also find a substantial degree of heterogeneity across countries in the relationship between lights and economic activity: individually-estimated models tend to outperform panel specifications. Key factors underlying the night lights performance include the country’s size and income level, logistics infrastructure, and the quality of national statistics.

Keywords: night lights; remote sensing; big data; business cycles; leading indicators (search for similar items in EconPapers)
JEL-codes: C55 C82 E01 E37 R12 (search for similar items in EconPapers)
Date: 2020-02
New Economics Papers: this item is included in nep-big, nep-for, nep-geo and nep-mac
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Journal Article: Forecasting GDP Growth from Outer Space (2020) Downloads
Working Paper: Forecasting GDP growth from the outer space (2017) Downloads
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