# **1 Introduction and literature review**

Air pollution has a significant and well-documented negative impact on human health. This results in income loss as well as in various adverse socioeconomic consequences and these effects are present in both developed and developing countries. For a proper accounting of the effects associated with fossil fuel use, such costs need to be incorporated into the analysis. Put differently, economic policy modeling designed to internalize costs associated with fossil fuel use will be -at best- incomplete without taking these additional effects into account. A proper inclusion of air pollution in macro models poses several challenges. As a result, different approaches in the existing literature often lead to inconclusive, or even inconsistent findings. We propose a theoretical model to analyze the impact of air pollution on both the intensive and extensive margins of labor supply. We then employ a novel identification approach to quantify these effects on labor productivity. Our framework allows us to estimate the impact of pollution on labor productivity at the city level.Our purpose is two-fold: (1) to find a generic causal identification scheme that can be applied across countries and (2) to use these estimates to analyze the effects of pollution in a macroeconomic model.

The two-way relationship between macroeconomic performance and environmental effects has been the focus of several studies. Initially, the emphasis was mainly on documenting the effect of economic growth on pollution levels. In an influential paper, Grossman and Krueger (1995) investigated the relationship between per capita income and various environmental indicators, including urban air pollution. They found a nonmonotonic relationship, where initially economic growth is associated with a deterioration in environmental quality, followed by a subsequent phase of improvement. More recently, several studies investigate how pollution might have a feedback on economic growth, mainly through premature deaths and adverse effects on human health. Bakhsh et al. (2017) performed an empirical study of the relationship between economic growth and pollution in Pakistan. They concentrated on the role of foreign direct investment. They found that, once a particular threshold level of pollution is reached, further increases in overall pollution cause a significant reduction in economic growth in the country.

The narrower question of the impact of air pollution on labor productivity has also been the subject of several studies in recent years. Findings reported in the literature draw a complicated picture, depending on the identification strategy employed and the study’s spatial and temporal focus. The channels through which local pollution can affect labor productivity can be far-reaching. As an example of the wide-ranging related effects, Victor et al. (2014) studied the relationship between cognitive performance and ambient PM2.5 pollution exposure in Israel. They used a sample of high-school examinations during 2000-2002 and found evidence of a strong negative relationship between performance outcomes and pollution concentrations. Their results suggest that reduced cognitive performance due to pollution could provide a channel to reduced labor productivity. Chang et al. (2016) studied the relationship between PM2.5 and worker productivity using daily panel data from an indoor pear-packing factory in Northern California. They found that a 10 _μg/m_ 3 increase in PM2.5 reduces productivity by $0.41/hour (approximately 6 percent of average hourly earnings), with PM2.5 adversely affecting productivity even at levels lower than current US air quality standards. They did not find evidence of a labor supply response to PM2.5 flows. Likewise, they found that outdoor pollutants such as ozone have negligible effects on labor productivity.

Hanna and Oliva (2015) and Hansen-Lewis (2018) argue that pollution-related effects on productivity might be economically significant even if the pollution effects are small in absolute terms. Chen and Zhang (2021) argue that the causal effect strengthens at higher pollution levels, and the effect might be different for different age groups. Chang et al. (2019) point out that the effects can be significant even for desk jobs that require minimal physical effort. He et al. (2019) point to significant adverse output effects from prolonged pollution exposure, with more productive workers having a greater response to pollution. More recently, Adhvaryu et al. (2022a) document the adverse effects of PM pollution on worker productivity in a 1