This lamentable empirical situation is not surprising given the inherent difficulties in collecting socio-economic and demographic data at the sub-national level, the typically low frequency of detailed national data collection, and the scaling back of national household data collection in places like the U.S. Studying urban dynamics at a truly global scale is therefore an urgent research task, but also one which is hampered by the absence of comprehensive, consistently-defined, and reliably collected data on urban economic output, population size and physical presence. (Throughout the text we use the terms “cities”, “urban areas”, and “metropolitan areas” interchangeably, avoiding the unnecessary controversy of defining them and relying on the readers’ sense of what differentiates urban from non-urban population agglomerations.) The pressing challenges of sustainability, adaptation to climate change, economic recovery and poverty reduction are in effect, all urban challenges. Our planet has indeed become a “planet of cities”. Urbanization is a hallmark of the 21 st century, characterized by massive demographic shifts and an unprecedented rapid expansion of urban areas and the built environment. Homo sapiens is now an urban species with over half the world’s population living in urban areas, including many millions in informal settlements. Further, we find the link between light and economic activity, especially estimated by wages, to be slightly overestimated in large urban areas and underestimated in rural areas. We also find a closer connection between radiance light and economic activity, than with saturated light. In general, we find a stronger relation between light and density values, than with light and total values. We find that the correlation between NTL and economic activity is strong enough to make it a relatively good proxy for population and establishment density, but the correlation is weaker in relation to wages. We use a fine-grained geo-coded residential and industrial full sample micro-data set for Sweden, and match it with both radiance and saturated light emissions. But, just how close is the statistical relationship between NTL and economic activity at a fine-grained geographical level? This paper uses a combination of correlation analysis and geographically weighted regressions in order to examine if light can function as a proxy for economic activities at a finer level. As governments around the world either collect census data infrequently or are scaling back the amount of detail collected, alternate sources of population and economic information like NTL are being considered. Much research has suggested that night-time light (NTL) can be used as a proxy for a number of variables, including urbanization, density, and economic growth.
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