to a question about whether the worker thought the government should do more on pollution (using a 1-5 scale). We again see positive and significant coefficients on managerial quality. Finally, workers were asked to indicate the characteristics of their ideal job, selecting from a list which included also low exposure to pollution as an option. We create a dummy equal to one if workers selected exposure to pollution among the characteristics of their ideal job, and use this as dependent variables in columns 7 and 8. We find that workers employed by higher quality managers are substantially more likely to indicate exposure to pollution among the characteristics of their ideal job. Interestingly again, the inclusion of employee controls in columns 2, 4, 6 and 8 barely alters the coefficients on our index of manager quality. This once again suggests that the effects are driven by higher quality managers being more aware of pollution as a problem and thus affecting the perceptions of their employees, rather than by differential sorting of workers to managers of varying quality.

In columns 1 and 2 of Appendix Table A3 we construct a standardized index of all the outcome variables in Table 7 and use this as dependent variable. We again find a precisely estimated positive correlation between managerial quality and this index of employee awareness of pollution. Notably, we fail to find a significant correlation between median road size and this index of employee awareness, although again the coefficients are positive. This suggests again that spatial variation in awareness within the city is limited, while the effect of managerial quality is significant.

**Limited role of worker sorting in explaining the results.** As discussed above, the inclusion of worker-level controls in the regressions in Tables 6 and 7 barely affects the coefficient on the managerial quality dummy. This is consistent with the sorting of workers to managers not being a driver of the results in these two tables.

We conduct further checks to shed more light on the role of sorting. First, we look for direct evidence of sorting. We do so in Appendix Table A3, columns 3-8. In columns 3 and 4, the dependent variable is a measure of employee awareness of pollution that we argue is plausibly pre-determined with respect to their current employer. That is, each worker was asked whether low exposure to pollution was an important consideration in deciding where to live.<sup>44</sup> We construct a dummy equal to one for those who answered positively to this question, and use this as dependent variable. The results in columns 3-4 show no evidence of sorting between higher ability managers and workers based on this (pre-determined) measure of pollution awareness. Columns 5-8 instead show that there is sorting by age and education.<sup>45</sup> The lack of sorting on our pre-determined measure of employee pollution awareness limits concerns that the specifications in Tables 6 and 7 with employee controls might capture sorting. Nevertheless, in

> 4418% of workers report that pollution was an important consideration in their location decision.

> 45Appendix Table A4 shows that employee age and education do predict awareness as pollution as a problem.

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