Original Research
Remote night-time lights sensing: Investigation and econometric application
Submitted: 21 August 2020 | Published: 17 March 2021
About the author(s)
Clive E. Coetzee, TRADE Research Entity, Faculty of Economic and Management Sciences, North-West University, Potchefstroom, South AfricaEwert P.J. Kleynhans, School of Economics, Faculty of Economic and Management Sciences, North-West University, Potchefstroom, South Africa
Abstract
Orientation: Some recent studies have been published that demonstrated the value of remote sensing night-time lights as descriptors and/or proxies for human activity.
Research purpose: This article investigated the association between night-time light emissions and gross domestic product (GDP) estimates for South Africa.
Motivation for the study: Satellite night-lights data seemed to be a useful proxy for economic activity at temporal and geographic scales for which traditional data are of poor quality, are unavailable or only available with a large time lag.
Research approach/design and method: The article primarily used the remote sensing of night-time light emissions using satellite technologies. The methodology employed in this study involved estimating both a vector error correction modelling (VECM) and autoregressive distributed lag (ARDL) models that map light growth into a proxy for GDP growth.
Main findings: Both the VECM and ARDL models confirmed a long-term co-integrating relationship between GDP (per capita) and night-time lights (total light intensity), a statistically significant short-term error correction term could, however, not be established through the VECM, but indeed through the ARDL model.
Practical/managerial implications: The results of the study suggested that satellite remote sensing technologies held much promise and opportunities in terms of the field of Economics and Development.
Contribution/value-add: This study contributes to our understanding of the spatial and temporal behaviour and trends in economic activity. It also suggested the use of satellite remote sensing technologies as part of official statistical frameworks and methodologies.
Keywords
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Crossref Citations
1. Nighttime lights-innovative approach for identification of temporal and spatial changes in population distribution
Milena Panic, Marija Drobnjakovic, Gorica Stanojevic, Vlasta Kokotovic-Kanazir, Dejan Doljak
Journal of the Geographical Institute Jovan Cvijic, SASA vol: 72 issue: 1 first page: 51 year: 2022
doi: 10.2298/IJGI2201051P