Edward Conard

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Upside of Inequality Oxford Unintended Consequences

AI Summary. Across more than 10,000 U.S. school districts, the authors estimate that each one-unit increase in fine particulate pollution lowers test scores by 0.02 standard deviations, and that a 3µg/m3 decline in these particulates raised scores nationwide by 0.06 standard deviations.

Michael Gilraine National Bureau of Economic Research
Date Posted:
Is Database:
Database

Air pollution has a significant impact on student performance in the US. Each one-unit increase in particulate pollution reduces test scores by 0.02 standard deviations.

Does air pollution lower student test scores?

Core argument: Across more than 10,000 U.S. school districts, each one-unit increase in particulate pollution is associated with test scores 0.02 standard deviations lower.

Analysis of over 10,000 U.S. school districts reveals that each one-unit increase in particulate pollution reduces test scores by 0.02 standard deviations. Instrumental variable estimates show that a 3µg/m3 reduction in PM2.5 concentrations from 2002-03 to 2018-19 raised test scores by 0.06 standard deviations nationwide. This improvement is significant compared to a policy releasing the bottom 5% of teachers, which would only increase scores by 0.02-0.025 standard deviations. The black-white PM2.5 exposure gap decreased by 0.50µg/m3, reducing the test score gap by 0.01 standard deviations, or 6% of the total decline over this period. Further reductions in PM2.5 could raise scores by 0.036 and eliminate racial disparities in exposure, decreasing the black-white test score gap by an additional 0.024 standard deviations.

Takeaways by Macro Roundup® AI

  1. Across more than 10,000 U.S. school districts, each one-unit increase in particulate pollution is associated with test scores 0.02 standard deviations lower.
  2. Instrumental variable estimates indicate that a 3µg/m3 decline in PM2.5 from 2002–03 to 2018–19 raised U.S. test scores by 0.06 standard deviations, compared with 0.02–0.025 standard deviations from releasing the bottom 5% of teachers.
  3. The black-white PM2.5 exposure gap narrowed by 0.50µg/m3, reducing the test score gap by 0.01 standard deviations, or 6% of its total decline, and eliminating the remaining exposure disparity is estimated to close an additional 0.024 standard deviations.

Core Findings

First, “…we develop an instrument that exploits variation in the proximity of districts to coal power plants and year-to-year fluctuations in power production at these plants, as in Duque and Gilraine (2020). Specifically, we instrument for air quality using the yearly coalbased energy production occurring within 60km of a school district. The choice of 60km is informed by prior research which finds a strong relationship between coal power production and PM2.5 concentrations only for locations within roughly 40-60km of the plant (Levy et al., 2002; Clay et al., 2016). We confirm this relationship, showing that increased power production within 60km of a school district significantly raises PM2.5 concentrations and correspondingly lowers student test scores; increased power production located further than 60km away has limited impacts on air quality and no effect on test scores. Our IV estimates indicate that each microgram per cubic meter (μg/m3) increase in PM2.5 concentrations causes a 0.02 standard deviation decline in test scores. These estimates are larger in magnitude compared to our OLS estimates, as expected given we suspect OLS regressions will feature severe attenuation bias in this context….”

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….Figure 2(a) displays the PM2.5 concentrations among low- (dashed line) and high-coal (solid line) districts over time. As expected, there is a large drop in PM2.5 concentration in 2011-12 for high- relative to low-coal districts, which coincides with the significant decrease in U.S. coal production that year….Our two empirical strategies indicate that each µg/m3 reduction in PM2.5 increases test scores by 0.02 standard deviations. Panel A of Table 2 places these estimates into perspective by reporting the PM2.5 exposure an average student in the United States faced in 2002-03, 2010-11, and 2018-19. We see a large decline in pollution exposure over the last two decades: the average student saw their PM2.5 exposure drop a full 3µg/m3 from 2002-03 to 2018-19. Our estimates therefore indicate that air quality improvements raised test scores nationwide by a full 0.06 standard deviations. This nationwide test score impact is large; in comparison a nationwide policy that releases the bottom 5% of teachers according to value-added would only raise test scores by 0.02-0.025 standard deviations. Given that the decline in pollution exposure over the past two decades has disproportionately benefited areas where African Americans reside...it is also natural to wonder whether test score equity has also been impacted. Panel B reports PM2.5 exposure for the average white and black student in the United States. From 2002-03 to 2018-19 the black-white PM2.5 exposure gap declined by 0.50µg/m3. This suggests that changes in pollution exposure decreased the black-white test score gap by 0.01 standard deviations, or 6 percent of the 0.18 standard deviations decline in the black-white test score gap over this period. Using instrumental variables that leverage exposure to nearby power production, we find that air pollution significantly lowers student test scores. Given that, the large 3µg/m3 drop in PM2.5 concentrations experienced by the average student materially raised test scores nationwide. Substantial improvements to student performance and equity through cleaner air are still possible, however. For example, decreasing average PM2.5 to that of the first quartile district would raise nationwide test scores by 0.036 and completely eliminating black-white differences in particulate exposure would further decrease the black-white test score gap by 0.024 standard deviations.

Ed Comment:I think it’s overstated because of the correlation between poor and pollution

Second, “…we implement a shift-share design that uses national changes in fuels used for power production by interacting pre-existing shares for four fuel sources (coal, oil, gas, and renewables) nearby a district with annual aggregate growth in each source to instrument for the pollution faced by a school district. We motivate our shift-share instrument by highlighting the dramatic shift from coal to natural gas as the primary fuel used for power production during our time period; a motivation supported by the Rotemberg weights in our shift-share design (Goldsmith- Pinkham et al., 2020). Estimates from our shift-share instrument are near-identical to those from the first instrumental variable strategy and indicate that each microgram per cubic meter (μg/m3) increase in PM2.5 concentrations causes a 0.02 standard deviation decline in test scores…”
Michael Gilraine and Angela Zheng, "Air Pollution and Student Performance in the U.S.,"National Bureau Of Economic Research, May 2022, https://www.nber.org/papers/w30061

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