Working Paper: NBER ID: w30061
Authors: Michael Gilraine; Angela Zheng
Abstract: We combine satellite-based pollution data and test scores from over 10,000 U.S. school districts to estimate the relationship between air pollution and test scores. To deal with potential endogeneity we instrument for air quality using (i) year-to-year coal production variation and (ii) a shift-share instrument that interacts fuel shares used for nearby power production with national growth rates. We find that each one-unit increase in particulate pollution reduces test scores by 0.02 standard deviations. Our findings indicate that declines in particulate pollution exposure raised test scores and reduced the black-white test score gap by 0.06 and 0.01 standard deviations, respectively.
Keywords: air pollution; student performance; education; PM2.5; instrumental variables
JEL Codes: I14; I24; Q53
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| PM2.5 concentrations (Y10) | Test Scores (Y10) |
| Coal Production within 60 km of school districts (L94) | PM2.5 concentrations (Y10) |
| Reduction in PM2.5 exposure (I14) | Test Scores (Y10) |
| Improved Air Quality (Q53) | Black-White Test Score Gap (I24) |