The Impact of Pollution on Worker Productivity

As one of the primary factors of production, labor is an essential element in every nation's economy. Investing in human capital is widely viewed as a key to sustaining increases in labor productivity and economic growth. While health is increasingly seen as an important part of human capital, environmental protection, which typically promotes health, has not been viewed through this lens. Indeed, such interventions are typically cast as a tax on producers and consumers, and thus a drag on the labor market and the economy in general. Given the large body of evidence that causally links pollution with poor health outcomes (e.g., Bell et al. 2004; Chay and Greenstone 2003; Currie and Neidell 2005; Dockery et al. 1993; Pope et al. 2002), it seems plausible that efforts to reduce pollution could in fact also be viewed as an investment in human capital, and thus a tool for promoting, rather than retarding, economic growth. The key to this assertion lies in the impacts of pollution on labor market outcomes. While a handful of studies have documented impacts of pollution on labor supply (Carson, Koundouri, and Nauges 2011; Graff Zivin and Neidell forthcoming; Hanna and Oliva 2011; Hausman, Ostro, and Wise 1984; Ostro 1983),1 their focus on the extensive margin, where behavioral responses are nonmarginal, only captures high-visibility labor market impacts. Pollution is also likely to have productivity impacts on the intensive margin, even in cases where labor supply remains unaffected. Since worker productivity is more difficult to monitor than labor supply, these more subtle impacts may be pervasive throughout the workplace, so that even small individual effects may translate into large welfare losses when aggregated across the economy. There is, however, no systematic evidence to date on the direct impact of pollution on worker productivity.2 This paper is the first to rigorously assess this environmental productivity effect. Estimation of this relationship is complicated for two reasons. One, although datasets frequently measure output per worker, these measures do not isolate worker productivity from other inputs (i.e., capital and technology), so that obtaining clean measures of worker productivity is a perennial challenge. Two, exposure to pollution levels is typically endogenous. Since pollution is capitalized into housing prices (Chay and Greenstone 2005), individuals may sort into areas with better air quality depending, in part, on their income, which is a function of their productivity (Banzhaf and Walsh 2008). Furthermore, even if ambient pollution is exogenous, individuals may respond to ambient levels by reducing time spent outside, so that their exposure to pollution is endogenous (Neidell 2009). In this paper, we use a unique panel dataset on the productivity of agricultural workers to overcome these challenges in analyzing the impact of ozone pollution on productivity. Our data on daily worker productivity is derived from an electronic payroll system used by a large farm in the Central Valley of California that pays its employees through piece rate contracts. A growing body of evidence suggests that piece rates reduce shirking and increase productivity over hourly wages and relative incentive schemes, particularly in agricultural settings (Bandiera, Barankay, and Rasul 2005, 2010; Lazear 2000; Paarsch and Shearar 1999, 2000; Shi 2010). Given the incentives under these contracts, our measures of productivity can be viewed as a reasonable proxy for productive capacity under typical work conditions. We conduct our analysis at a daily level to exploit the plausibly exogenous daily fluctuations in ambient ozone concentrations. Although aggregate variation in environmental conditions is largely driven by economic activity, daily variation in ozone is likely to be exogenous. Ozone is not directly emitted but forms from complex interactions between nitrogen oxides (NOx) and volatile organic chemicals (VOCs), both of which are directly emitted, in the presence of heat and sunlight. Thus, ozone levels vary in part because of variations in temperature, but also because of the highly nonlinear relationship with NOx and VOCs. For example, the ratio of NOx to VOCs is almost as important as the level of each in affecting ozone levels (Auffhammer and Kellogg 2011), so that small decreases in NOx can even lead to increases in ozone concentrations, which has become the leading explanation behind the “ozone weekend effect” (Blanchard and Tanenbaum 2003). Moreover, regional transport of NOx from distant urban locations, such as Los Angeles and San Francisco, has a tremendous impact on ozone levels in the Central Valley (Sillman 1999). Given the limited local sources of ozone precursors, this suggests that the ozone formation process coupled with emissions from distant urban activities are the driving forces behind the daily variation in environmental conditions observed near this farm. Furthermore, the labor supply of agricultural workers is highly inelastic in the short run. Workers arrive at the field in crews and return as crews, thus spending the majority of their day outside regardless of environmental conditions. Moreover, since we have measures of both the decision to work and the number of hours worked, we can test whether workers respond to ozone, and in fact we are able to rule out even small changes in avoidance behavior. Thus, focusing on agricultural workers greatly limits the scope for avoidance behavior, further ensuring that exposure to pollution is exogenous in this setting, and that we are detecting productivity impacts on the intensive margin. Although these workers are paid through piece-rate contracts, worker compensation is subject to minimum wage rules, which can alter the incentive for workers to supply costly effort. Since the minimum wage decouples daily job performance from compensation, workers may have an incentive to shirk. If pollution leads to more workers earning the minimum wage, and this in turn induces shirking, linear regression estimates will be upward biased. On the other hand, the threat of termination may provide a sufficient incentive to provide effort, particularly in our setting where output is easily verified and labor contracts are extremely short-lived, in which case linear regression models should be unbiased. After merging this worker data with environmental conditions based on readings from air quality and meteorology stations in the California air monitoring network, we first estimate linear models that relate mean ozone concentrations during the typical workday to productivity. We find that ozone levels well below federal air quality standards have a significant impact on productivity: a 10 parts per billion (ppb) decrease in ozone concentrations increases worker productivity by 5.5 percent. To account for potential concerns about shirking, we artificially induce “bottom- coding” on productivity measures for observations where the minimum wage binds, and estimate censored regression models. Under this specification, the actual measures of productivity when the minimum wage binds no longer influence estimates of the impact of ozone on productivity. Thus, if the marginal effects of productivity on this latent variable differ from the marginal effects from our baseline linear model, this would indicate shirking is occurring. Our results, however, remain unchanged, suggesting that the threat of termination provides sufficient incentives for workers to supply effort even when compensation is not directly tied to output. These impacts are particularly noteworthy as the US Environmental Protection Agency is currently contemplating a reduction in the federal ground-level ozone standard of approximately 10 ppb (Environmental Protection Agency 2010). The environmental productivity effect estimated in this paper offers a novel measure of morbidity impacts that are both more subtle and more pervasive than the standard health impact measures based on hospitalizations and physician visits. Moreover, they have the advantage of already being monetized for use in the regulatory cost-benefit calculations required by Executive Order 12866 (The White House, 1994). In developing countries, where environmental regulations are typically less stringent and agriculture plays a more prominent role in the economy, this environmental productivity effect may have particularly detrimental impacts on national prosperity. The paper is organized as follows. Section I briefly summarizes the relationship between ozone and health, and highlights potentially important confounders. Section II describes the piece-rate and environmental data. Section III provides a conceptual framework that largely serves to guide our econometric model, which is described in Section IV. Section V describes the results, with a conclusion provided in Section VI.