that, facing this trade-off, firms choose not to avoid pollution, but rather to cluster in the most polluted and high-traffic areas of the city. They do so primarily in order to access customers. Third, we find an important role of managerial skills: high ability managers do not avoid polluted areas, but better protect their workers from pollution exposure. Overall, our results bring new evidence on how pollution affects firms and workers and uncover better adaptation to pollution as a novel channel through which good management raises worker well-being and firm productivity.

We begin by developing a simple model of a manager that maximizes profits in a polluted city to clarify how taking into account pollution exposure affects production choices, and how this relationship may be mediated by managerial ability. We consider three interrelated choices: (i) where to locate the firm; (ii) which type of workers to hire; and (iii) whether to mitigate the effects of pollution by investing in protective equipment or other organizational strategies to limit exposure. Managers wish to reduce pollution exposure to avoid a productivity cost, and to be able to hire high-skilled workers, who may demand more protection, for instance due to higher awareness of pollution and its effects on health. Managers have two means to reduce exposure: (i) by choosing a less polluted location (avoidance), or (ii) through investment in protective equipment or organizational strategies (adaptation). Both avoidance and adaptation are costly: less polluted areas may be less profitable, and protective investments come at a cost. This creates the key trade-offs in the model. Managerial skill is allowed to affect all these choices both through possible complementarities with location-specific profitability and workers’ type, as well as through a potentially lower cost of protective investments. The framework offers a series of testable predictions that motivate our data collection and empirical strategy.

To test the model’s predictions and offer a descriptive picture of how pollution exposure affects firm production, we collected pollution measurements at high spatial resolution and matched these to a novel firm survey with detailed information on firm location, managerial skills, and managers’ investments to protect their workers from pollution exposure.

We gathered detailed geo-coded pollution measurements in a representative sample of urban areas throughout Uganda, using both mobile and stationary monitors. The resulting high frequency data allows us to document spatial variation in pollution within the city, and to precisely estimate temporal fluctuations in pollution within the day. We combine the pollution data with a novel representative geo-coded survey of 1,000 firms in small-scale manufacturing and their employees that we conducted in the same areas and at the same time as our pollution measurements (Bassi et al. 2021). For each firm, we have available detailed measures of productivity, such as profits per worker, as well as a range of questions about location choice, pollution avoidance behaviors and investments, and awareness of pollution as a problem among employees. Building on the seminal work of Bloom and Van Reenen (2007, 2011) and McKenzie and Woodruff (2017), our survey of small firms also includes a module on eliciting the man2