Better Night Lights Data, For Longer*
研究发现，较新的VIIRS夜间灯光数据比旧的DMSP数据对欧洲269个NUTS2区域的实际GDP预测能力高出80%，且DMSP数据严重低估了空间不平等，尤其是人口密集区域。
Abstract Night lights data are increasingly used in applied economics, almost always from the Defense Meteorological Satellite Program (DMSP). These data are old, with production ending in 2013, and are flawed by blurring, lack of calibration and top‐coding. These inaccuracies in DMSP data cause mean‐reverting errors. This paper shows newer and better VIIRS night lights data have 80% higher predictive power for real GDP in a cross‐section of 269 European NUTS2 regions. Spatial inequality is greatly understated with DMSP data, especially for the most densely populated regions. A Pareto correction for top‐coding of DMSP data has a modest effect.