Arbeitspapier
Forecasting GDP growth from outer space
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Economics Working Paper Series ; No. 2020/02
- Klassifikation
-
Wirtschaft
Large Data Sets: Modeling and Analysis
Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
Size and Spatial Distributions of Regional Economic Activity
- Thema
-
night lights
remote sensing
big data
business cycles
leading indicators
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Galimberti, Jaqueson K.
- Ereignis
-
Veröffentlichung
- (wer)
-
Auckland University of Technology (AUT), Faculty of Business, Economics and Law
- (wo)
-
Auckland
- (wann)
-
2020
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Galimberti, Jaqueson K.
- Auckland University of Technology (AUT), Faculty of Business, Economics and Law
Entstanden
- 2020
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