NIGHTLIGHT DATA AS AN INDICATOR OF REGIONAL POPULATION DISTRIBUTION IN LAOS

Christian Rogalski
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Christian Rogalski: Alexandru Ioan Cuza University of IaÅŸi, Faculty of Economics and Business Administration, IaÅŸi, Romania

Review of Economic and Business Studies, 2023, issue 32, 115-128

Abstract: The collection of census data can be costly and often yields inaccurate results in developing countries. This paper explores the potential of using nightlight data as an indicator of both population distribution and regional population density in Laos. Satellite images from the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) are used, as well as population data from the 2015 census of Laos. The study conducts a correlation and regression analysis between the nightlight index, the population distribution and population density across 148 districts in Laos. The findings indicate a positive correlation between nightlight data and population metrics. However, the correlation is more robust for population density than for sheer population numbers. The regression models reveal that nightlight data can explain a significant variation in population and population density, with a greater explanatory power for the latter. This paper concludes by discussing the implications of these results for population distribution estimations using nightlight data and proposes some possible improvements for future research.

Keywords: nightlight satellite imagery; regional population distribution; population density; Laos; census data (search for similar items in EconPapers)
JEL-codes: Q56 R23 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:aic:revebs:y:2023:j:32:rogalskic

DOI: 10.47743/rebs-2023-2-0006

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