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.
Highlights
This article focuses on examining the economics and economic application of the remote sensing of night-time light (NTL) emissions using satellite technologies within the South African context
This study investigates the economics application of the remote sensing of NTL emissions using satellite technologies within a South African context
The literature on the use of remote sensing NTLs seems to support its use in many different fields of study, including economics
Summary
This article focuses on examining the economics and economic application of the remote sensing of night-time light (NTL) emissions using satellite technologies within the South African context. Levin et al (2020) argue that the use of NTL emissions in the visible band offers a unique opportunity to directly observe human activity from space. It shows some significant differences within the lower frequencies (1–3) and higher frequencies above 60. ∑ ∑ ∆lnYt = β0 + βi∆lnYt − i + δi∆lnXt − i + φzt − i + μt , i=1 i=0 where ln Yt is the real GDP per capita at period t, lnX is the total light intensity at period t (lnLt) and the number of pixels that are dim with DN 0–5 at period t (lnCt); μt is the stationary error term; z is the error correction term and is the ordinary least square residuals from the long-term cointegration regression: lnYt = β 0 + β1lnXt + εt and is defined as: zt − 1 = ECTt − 1 = lnYt − 1 − β0 − β1lnXt − 1.
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