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Wildfires reveal the large toll of air pollution on labor market outcomes

Key Takeaways

  • Wildfires cause more than just direct damage to life and property: Smoke exposure can decrease labor income, employment, and labor force participation.
  • Wildfire smoke reduced earnings in the U.S. by an average of $125 billion a year between 2007 and 2019.
  • Earning losses from smoke exposure are about 60 percent larger in counties whose populations have an above-median proportion of Black residents.
  • Policymakers should consider that the positive income effects from cleaner air may be as large as the mortality benefits.


Wildfires in the European Union have burned nearly 2 million acres since the start of 2022 through early December, about 2.5 times the year-to-date average for 2006–2021 (European Forest Fire Information System, 2022). As of mid-November, the United States has suffered more than 60,000 fires that destroyed a total of 7.2 million acres. That’s about 6 percent more than the 10-year average (National Interagency Fire Center, 2022).

Smoke from these wildfires can drift for thousands of miles, bringing air pollution to areas far from the regions where the fires burn. The amount of air pollution from wildfire smoke is substantial, accounting for about 20 percent of the emissions of PM2.5 — particles less than 2.5 microns in diameter that can cause serious health problems when inhaled — in the United States (U.S. Environmental Protection Agency, 2014). Wildfires are likely to become increasingly relevant as a source of air pollution in the years ahead, with forecasts projecting that the wildfire season will expand and fires will become more frequent and severe with climate change (Kurvits et al., 2022).

Accurately measuring the health and economic impacts of air pollution, whether caused by wildfire smoke or other sources, is essential for ensuring that individuals and policymakers can reduce exposure and increase resilience to poor air quality.

While the effects of air pollution on human health are well documented (Chay and Greenstone, 2003; Jayachandran, 2009; Chen et al., 2013; Deryugina et al., 2019; Anderson, 2020), the extent of the impact on the labor market is largely unknown and is often depicted as limited. For example, major assessments of the economic benefits from reducing air pollution have attributed a small fraction of the benefits to labor market effects, partly because they have considered only certain effects such as lost days of work due to specific illnesses or death (e.g., U.S. Environmental Protection Agency, 2011; OECD, 2016).

A challenge for assessing how air pollution impacts the labor market is that correlations between air quality and labor market outcomes could reflect reverse causality: Labor market activity itself can generate air pollution through vehicle traffic, manufacturing, and electricity generation. Wildfires present an opportunity to sidestep this challenge by focusing on variation in air pollution caused by drifting wildfire smoke plumes.

Using this strategy, our recent paper, “Air Pollution and the Labor Market: Evidence from Wildfire Smoke” (Borgschulte, Molitor, and Zou, 2022), examines the toll that air pollution from wildfire smoke took on the U.S. labor market from 2007 to 2019. During this period, regions across the country were covered by wildfire smoke for an average of about 20 days per year, with nearly every state experiencing some exposure (Figure 1).

Figure 1. Days of Smoke per Year, 2007-2019

Figure 1. Days of Smoke per Year, 2007-2019


Our analysis relies on a novel linkage of three data sources: 1) high-resolution, remote-sensing data from satellites that show daily locations of wildfire smoke plumes; 2) air-quality data from pollution monitors on the ground; and 3) labor market data for all counties in the contiguous United States. We use variation in the number of days of smoke a county experiences each quarter to estimate the impacts of air pollution on both ground-level air quality and labor market outcomes nationwide.

We find that air quality deteriorates substantially on days with wildfire smoke (Figure 2, Panel A). An additional day of smoke increases concentrations of ground-level PM2.5 by more than 2 μg/m3 on average, about one-third of the daily standard deviation. At the quarterly level, the time frequency of the labor market analysis, an additional day of smoke raises a county’s average PM2.5 concentration by about 0.06 μg/m3.  

Wildfire smoke exposure also leads to statistically and economically significant losses in earnings (Figure 2, Panel A). A day of smoke reduces quarterly per capita earnings by $5.20, or about 0.10 percent. Multiplying this effect by the average number of smoke days each year, we calculate that wildfire smoke reduced earnings by nearly 2 percent of U.S. annual labor income ($125 billion in 2018 dollars) per year on average in our sample period.

Figure 2. Effect of Wildfire Smoke on Air Quality and Earnings

Figure 2. Effect of Wildfire Smoke on Air Quality and Earnings

We find that smoke reduces earnings across a wide variety of sectors, including manufacturing, crop production (though not agriculture overall), utilities, health care, real estate, administration, and transportation. It hurts people of all ages, but the impact is worse among older workers. This suggests that age and related poor health may amplify the effects of wildfire smoke. Smoke-induced earnings declines are also about 60 percent larger in counties whose populations have above-median proportion of residents who are Black.

Our estimated effect of air pollution on earnings is similar in magnitude to estimates from previous studies that focused on specific industries or regions (e.g., Graff Zivin and Neidell, 2012; Hanna and Oliva, 2015). Our study builds on these prior studies by studying nationally representative data on labor market outcomes. We also examine outcomes like employment and labor force participation that are not easily captured in studies of specific industries. We find that exposure to wildfire smoke reduces employment and labor force participation, illuminating the diverse channels through which air pollution can affect the labor market.

Comparing the labor market and mortality costs of air pollution

To understand how the labor market costs of air pollution compare to conventional mortality-based costs of air pollution, we benchmark the welfare costs of lost earnings to the costs of premature mortality due to smoke exposure. We estimate that for each 1 μg/m3 annual increase in PM2.5 due to smoke, annual labor market earnings decrease by $123 billion (2018 dollars), with a welfare cost of $92 billion. Using previously established estimates of the causal effect of PM2.5 on elderly mortality (Deryugina et al., 2019), and a range of commonly used values of a statistical life, we calculate the premature mortality cost of PM2.5 from wildfire smoke to be about $8 billion to $31 billion annually. Our analysis therefore suggests that the social welfare costs of lost earnings exceed the costs of increased mortality due to wildfire smoke.

Our findings contrast sharply with previous air pollution assessments that put labor market costs of air pollution at less than 5 percent of the premature mortality costs in the United States (U.S. Environmental Protection Agency, 2011; OECD, 2016; World Bank, 2016). These prior assessments generally focused on lost work due to illness or premature mortality, and they relied on modeling assumptions in lieu of direct estimation. By contrast, our results are based on administrative measures of income, allowing for a more direct comparison of the mortality and labor market effects of air pollution exposure.

Policy implications

Many agencies that engage in environmental policymaking, including the World Bank, the Organisation for Economic Co-operation and Development, and the U.S. Environmental Protection Agency, have traditionally treated pollution damages arising from lost labor market hours and earnings as considerably smaller than the mortality costs of air pollution. Indeed, the pollution variation we study and the harmful ramifications we document primarily occur from exposure to levels of pollution that are below regulatory standards set by the U.S. Environmental Protection Agency.

Our findings suggest that the positive income effects of cleaner air are likely greater than previously recognized and environmental policymaking should take them into account. Indeed, our findings also suggest that policies to improve air quality can generate a fiscal “double dividend” as reductions in air pollution increase both labor income and associated tax revenue, which in turn allows for lower tax rates and reduces the distortions they impose (Goulder, 1995).

Our findings have implications for wildfire policy and management. Wildfire smoke creates large externalities, as decisions about land use and fire management in one location can affect those living in distant regions, underscoring the importance of cross-regional coordination. Policies should consider factors that go beyond narrower goals of defending land and property exposed to fires in a given region, such as the amount of smoke produced by the fire and whether the smoke plumes may reach urban centers. For example, greater use of prescribed fires could help to limit uncontrolled burns and ultimately reduce smoke pollution.

Wildfire smoke cannot be completely eliminated. Yet even in the face of poor air quality, there are actions that individuals and organizations can take to mitigate its harms (Burke et al., 2022). Employing high-quality air filters in indoor spaces like homes, schools, and workplaces can protect individuals and may be more cost-effective than trying to reduce ambient air pollution levels. Improved air-quality monitoring and forecasting can further help individuals to plan and adapt. Advancing our understanding of the costs of air pollution helps individuals and policymakers to make informed choices that ultimately reduce the damages from poor air quality.

David Molitor is a Visiting Associate Professor at SIEPR and an Associate Professor of Finance and Economics at Gies College of Business, University of Illinois at Urbana-Champaign. His research explores how location and the environment shape health and health care delivery in the United States.

Mark Borgschulte is an assistant professor of economics at the University of Illinois, Urbana-Champaign

Eric Zou is an Assistant Professor of Economics at the University of Oregon.


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Mark Borgschulte
David Molitor
Eric Yongchen Zou
Publication Date
December, 2022