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Research article

Modelling US light pollution

, &
Pages 883-903
Received 24 Jan 2012
Accepted 05 Feb 2013
Published online: 14 May 2013
 

This paper uses a unique US dataset to study the economic causes of light pollution at the local (county) level. Light pollution has been shown to have negative consequences for both wildlife and humans. Light pollution is a form of pollution commonly ignored by environmental professionals. Traditionally, light-pollution models focus on population-based explanations. This paper confirms the importance of population in understanding light pollution. However, the results highlight the importance of economic variables, especially local economic development, in explaining the existence and extent of light pollution. Estimated models show, for example, that local employment patterns, personal income, roads and energy use are all important explanatory variables. By highlighting the connections between light pollution and specific types of local economic activity, this paper provides policy makers with additional information that they can use to improve public policies intended to safeguard the environment and local wildlife.

Notes

1. Although, as will be seen, one of the local factors is proximity to large population centres.

2. Naturally, the discrete nature of the buffers, like the Cinzano's original eight light pollution tiers themselves, are an imperfect way of modelling the continuous decline in artificial sky brightness when moving away from the source. Nevertheless, the resulting models seem to be very useful and robust.

3. Papke and Woolridge (1996) suggested using STATA's GLM procedure with family (binomial), link(logit) and robust.

4. Testing the relevancy of the environmental Kuznets curve for light pollution is not the main point of the current paper. However, GDP is one of the most important economic variables and its proxy, personal income, is included as a result. For more information regarding testing for the environmental Kuznets curve see Merlevede, Verbeke, and De Clercq (2006).

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