Which Nighttime Lights Data Better Represent India’s Economic Activities and Regional Inequality?
Christopher Kuruvilla Mathen,
Siddhartha Chattopadhyay,
Sohini Sahu and
Abhijit Mukherjee
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Christopher Kuruvilla Mathen: Indian Institute of Technology Kharagpur, Department of Humanities and Social Sciences, West Bengal, India
Sohini Sahu: Indian Institute of Technology Kanpur, Department of Economic Sciences, Uttar Pradesh, India
Abhijit Mukherjee: Indian Institute of Technology Kharagpur, Department of Geology and Geophysics, West Bengal, India
Asian Development Review (ADR), 2024, vol. 41, issue 02, 193-217
Abstract:
This paper demonstrates how the estimation of economic activities and inequality for the Indian economy based on nighttime lights data from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite outperforms those obtained using traditional Defense Meteorological Satellite Program Operational Line-Scan System (DMSP-OLS) sources. In the extant literature, nighttime lights data have been frequently used as a proxy for economic activities, especially at granular geographical levels where gross domestic product data are otherwise unavailable. Since the traditional DMSP-OLS-based nighttime lights data suffer from measurement errors due to blurring and top coding, VIIRS-based nighttime lights data, which are devoid of such limitations, are gaining popularity. We show that at the subnational or district level in India, VIIRS satellite-based nighttime lights data are indeed a better proxy for economic activities and inequality. Our robust findings imply that all future scholarly works that employ nighttime lights data for the Indian economy should use VIIRS-based data for greater accuracy compared to other similar data sources.
Keywords: economic activities; measurement errors; nighttime lights; quantile regression; spatial inequality (search for similar items in EconPapers)
JEL-codes: C21 E01 R11 R12 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:adrxxx:v:41:y:2024:i:02:n:s0116110524500094
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DOI: 10.1142/S0116110524500094
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