The hidden economic costs of air pollution in China: evidence from remotely sensed nighttime light data

While the negative health consequences of air pollution exposure are well documented, its effects on economic activities remain less understood. Existing empirical studies often focus on the impacts of air pollution on production-related economic indicators, such as labor productivity and innovation, neglecting its effect on consumption-related activities associated with pollution avoidance behaviors. Given the increasing availability of remotely sensed nighttime light data that captures both production and consumption dynamics, in this study, we examine the causal impact of air pollution on nighttime light brightness using a two-stage least squares model on an 18-year panel dataset (2002–2019) of 2098 administrative units in China. Our findings reveal that, on average, a 1% increase in particulate matter concentrations leads to a 0.65% decline in nighttime light brightness. This estimate can be translated into a 0.29% decrease in gross domestic product attributable to a 1% rise in particulate matter levels, given a reference light elasticity of gross domestic product of 0.45. Moreover, heterogeneity tests confirm spatial-temporal variations in the estimates, which may be attributed to differences in awareness of air pollution harms, pollution exposure levels, and recreational facilities or services. The contribution of this study is twofold. First, it uncovers the hidden economic co-benefits of air quality improvement. Second, it underscores the importance of remote sensing techniques in advancing a balanced environment–economy relationship.