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Which Night Lights Data Should we Use in Economics, and Where?

Gibson, John and Olivia, Susan and Boe-Gibson, Geua (2019): Which Night Lights Data Should we Use in Economics, and Where?

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Abstract

Popular DMSP night lights data are flawed by blurring, top-coding, and lack of calibration. Yet newer and better VIIRS data are rarely used in economics. We compare these two data sources for predicting Indonesian GDP at the second sub-national level. DMSP data are a bad proxy for GDP outside of cities. The city lights-GDP relationship is twice as noisy using DMSP as using VIIRS. Spatial inequality is considerably understated with DMSP data. A Pareto adjustment to correct for top-coding in DMSP data has a modest effect but still understates spatial inequality and misses key features of economic activity in Jakarta.

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