Lost in Translation? A Critical Review of Economics Research Using Nighttime Lights Data - John Gibson; Omoniyi Alimi; Geua Boe-Gibson (Remote Sensing)
In the three decades since a digital archive of satellite-detected night-time lights (NTL) data was created, thousands of scholarly articles have been published using these data. An important change in the last decade saw a significant share of highly cited articles with NTL data now written by economists. The way that economists treat the literature in other disciplines potentially interferes with the diffusion of updated findings on NTL data. Our bibliometric analysis finds that many economics studies using NTL data, especially highly cited ones, ignore studies by the remote sensing scientists who help provide the NTL data. This review considers two implications of the growing distance in the literature between economists using NTL data and remote sensing scientists. First, newer, more accurate and precise NTL data from sources like VIIRS (Visible Infrared Imaging Radiometer Suite) have slower uptake in economics, perhaps due to a lack of awareness. Yet, economists using NTL data increasingly work with spatially disaggregated units, for which the older, coarser, DMSP data are less suited. Second, a misunderstanding of DMSP spatial resolution leads to pixel-level regression studies in economics that are potentially subject to measurement error bias, for which we provide two case studies. Overall, the full value of NTL-based research may not be realized due to these weak connections.