a problem. As the model makes clear, these results could be driven either by high ability managers facing a lower marginal cost of adaptation, or by higher ability managers employing more highly skilled workers, who demand more protection. Our evidence is consistent with the first mechanism. That is, we show that our results on adaptation are not just driven by the sorting of better workers to better managers: while higher ability managers do employ higher skilled workers, controlling for a rich set of worker characteristics barely affects the role of managerial quality in explaining these results. The fact that mitigation activities include not only the provision of physical equipment but also changes in organizational strategies further suggests that the lower cost of adaptation for higher ability managers is not just driven by easier access to capital and may reflect also a higher awareness of the costs of pollution on worker productivity.<sup>3</sup> Taken together, our results highlight the importance of managerial quality in determining adaptation to environmental conditions and in limiting workers’ exposure to pollution. In doing so, we contribute to a classic literature on the role of managers for firm productivity (Bloom and Van Reenen 2007, 2011; Bloom et al. 2013; McKenzie and Woodruff 2017; Bruhn et al. 2018). This literature has established that good management practices lead to a reduction in pollution emissions by firms: Bloom et al. (2010) document that higher quality managers are more energy efficient, and Gosnell et al. (2019) show the importance of management practices in reducing carbon emissions in the airline industry. In addition, recent evidence shows that higher quality managers are better able to respond to shocks to worker productivity caused by exposure to pollution: Adhvaryu et al. (2019) find that more attentive managers in Indian factories reallocate workers across tasks to mitigate the productivity impacts of exposure to pollution. Our contribution is to study the role of managers in _preventing_ workers’ exposure to pollution, distinguishing between the possible channels of avoidance and adaptation.

We also contribute to a growing literature on access to demand for small firms in developing countries. This literature highlights that information frictions are a critical source of inefficiency for buyers and sellers (Jensen and Miller 2018, Startz 2018) and that lack of managerial or marketing ability creates a sizable barrier to accessing new markets (Anderson et al. 2018, Hjort et al. 2020). As a consequence, small firms tend to sell locally. We contribute by highlighting exposure to traffic pollution as another negative consequence of firms struggling to tap into new markets and having to locate on busy roads to access the local demand. In doing so, we

> 3Our cross-sectional data is appropriate to study avoidance through location choice and adaptation through investment in protective equipment/organizational strategies, as these are likely the result of sustained exposure to pollution. However, our data is not appropriate to study the short-run (nor the long-run, which are inherently harder to pin down) productivity impacts of pollution exposure (or of adopting mitigation strategies), as identification would require high-frequency panel data on both pollution and firm outcomes. Therefore, we do not estimate the productivity impacts of pollution, and instead rely on an extensive literature that is able to do so with appropriate data (see Graff Zivin and Neidell 2012, Chang et al. 2016, Adhvaryu et al. 2019 and Fu et al. 2021).

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