Working Paper: NBER ID: w25560
Authors: Meredith Fowlie; Edward A. Rubin; Reed Walker
Abstract: We use state-of-the-art, satellite-based PM2.5 estimates to assess the extent to which the EPA's existing, monitor-based measurements over- or under-estimate true exposure to PM2.5 pollution. Treating satellite-based estimates as truth implies a substantial number of "policy errors"—over-regulating areas that comply with air quality standards and under-regulating other areas that appear to violate standards. We investigate the health implications of these apparent errors and highlight the importance of accounting for prediction error in satellite-based estimates. Uncertainty in "policy errors" increases substantially when we account for these underlying prediction errors.
Keywords: satellite data; PM2.5; air quality; EPA; public health
JEL Codes: H23; H41; Q50; Q52; Q53
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Satellite-based PM2.5 estimates (C80) | EPA monitor readings (Y10) |
| Satellite-based PM2.5 estimates (C80) | type 1 errors (C52) |
| Satellite-based PM2.5 estimates (C80) | type 2 errors (C52) |
| type 1 errors (C52) | reduced mortality benefits (J17) |
| type 2 errors (C52) | increased mortality (I12) |
| EPA monitor readings (Y10) | regulatory errors (L51) |
| Satellite-based PM2.5 estimates (C80) | misclassification in EPA's nonattainment designations (H23) |