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Lead exposure and academic achievement: evidence from childhood lead poisoning prevention efforts


Though the adverse consequences of lead exposure in children have been well known for over a century, the recent Flint water crisis has drawn renewed attention to the impacts of lead exposure on human health and development. This study considers connections to educational outcomes, asking whether population-level lead exposure in early childhood influences later academic achievement and racial achievement gaps. It assesses the effectiveness of recent local- and state-level lead hazard control programs in mitigating exposure and uses this source of exogenous variation in early childhood exposure across birth cohorts to draw inferences about the long-term effects of lead on mean student test scores. Our findings indicate that lead hazard control grants reduced lead poisoning incidents by over 70% of the baseline prevalence. And each one percentage point reduction in lead poisoning in early childhood translated to a growth of 0.04 standard deviations in student math test scores and 0.08 standard deviations in student reading scores. This same reduction in lead poisoning narrowed both the white-Hispanic math achievement gap and white-Hispanic reading achievement gap by 0.06 standard deviations, implying important downstream consequences for economic inequality.

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  1. 1.

    For more information, see Fig. 6, which plots the total amount of HUD spending on lead hazard control and lead hazard reduction demonstration grants by fiscal year, and Table 7 in the Appendix, which lists aggregate HUD lead hazard control funding received by each state (and counties within the state) over the analytical time period.

  2. 2.

    For more information on lead screening and reporting requirements across states, see Dickman (2017).

  3. 3.

    A one standard deviation improvement in our analysis represents one standard deviation in the distribution of student scores rather than one standard deviation in the distribution of county scores, which would be an average effect of smaller magnitude.

  4. 4.

    For the education data, we assign every grade-by-year cohort of students to a birth year based on the median age of that grade level.

  5. 5.

    We also estimate effects of treatment by “age-at-grant-receipt” of the cohort to see if our findings are sensitive to the cutoff point between pre- and postprogram. See Section 4.

  6. 6.

    Because this equation also serves as a first-stage equation for lead exposure effects on academic achievement, we additionally include year and grade fixed effects in the model with pooled grade levels.

  7. 7.

    Some of these variables reflect relevant population or demographic shifts; the educational control variables are included because we need consistent covariates between the first-stage equation and second-stage equation, which predicts test score outcomes.

  8. 8.

    This precision-weighting process is motivated by the fact that county achievement mean statistics have large variation in their margins of error, and is a standard procedure in other research using this data (Shores and Steinberg 2017; Reardon et al. 2017).

  9. 9.

    To examine this question, we used county-level data on geographic mobility from the 2006 to 2010 5-year American Community Survey. Using the 5-year data allows us to examine mobility by subgroup for even less populous counties, but limits our ability to examine residential sorting through panel data methods as used in the rest of the study. Instead, we compared inflow and outflow migration cross-sectionally for counties that had received lead hazard control grants between the years 2004 to 2006 to those that had not. We find no significant differential net changes in population composition (inflow-outflow) by percent black, percent Hispanic, and percent with children from 1 to 4 years of age in treatment counties as compared to control counties in the years following lead poisoning prevention activities.

  10. 10.

    We chose 2003 for our main event study analysis because it is the year with the largest number of grant recipients and because it is right in the center of our birth year cohort coverage span. Approximately a third of all lead hazard control grants were received in 2003. Similar pretreatment trends graphs for recipients in a later year are provided in Fig. 8.

  11. 11.

    In fact, positive tests for 2 to 10 lead in children’s blood are over 100 times more common than positive tests for greater than 10 (Gould 2009).

  12. 12.

    According to Bloom et al. (2008), the average gain in nationally referenced test scores between sixth and seventh grades is 0.30 standard deviations in math and 0.28 standard deviations in reading.

  13. 13.

    Figure 8 presents the same information for counties receiving grants in 2008 and counties never receiving grants to allow for more years of pretreatment binned averages.


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The authors are grateful for the support from the Russell Sage Foundation, William T. Grant Foundation, and the Nelson A. Rockefeller Institute of Government. They would like to thank the anonymous reviewers for valuable comments and recommendations, as well as Sean Reardon, Steven Alvarado, participants at the RSF Workshop on Monitoring Educational Opportunity, and participants at the 2017 AEFP session on Special Education, Special Needs, and Health.


This study was funded by the Russell Sage Foundation and William T. Grant Foundation (Award #83-17-05). It was also supported by the Nelson A. Rockefeller Institute of Government.

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Correspondence to Lucy C. Sorensen.

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Responsible editor: Erdal Tekin



Table 7 Aggregate HUD lead hazard control grants by state
Table 8 Sensitivity of results to alternative coding of suppressed elevated blood lead level counts
Table 9 Full regression results: effect of county-level lead hazard control grants on childhood elevated blood lead level prevalence (first stage)
Table 10 Full regression results: effect of state-level lead hazard control grants on childhood elevated blood lead level prevalence (first stage)
Table 11 Placebo test for lead hazard control grant effects on childhood lead poisoning incidence
Table 12 Full regression results: IV estimates of effect of lead poisoning incidence on mean student test scores (pooled across grade levels)
Table 13 Full regression results: IV estimates of effect of lead poisoning incidence on racial achievement gaps (pooled across grade levels)
Fig. 6

Total HUD lead hazard control spending by year (2000–2016)

Fig. 7

Demographic trends for counties receiving LHC grants in 2003 compared to counties never receiving grants

Fig. 8

a Elevated blood lead level trends for counties receiving LHC grants in 2008 compared to counties never receiving grants. b Math score trends for counties receiving LHC grants in 2008 compared to counties never receiving grants

Fig. 9

Number of children tested trends for counties receiving LHC grants in 2008 compared to counties never receiving grants

Fig. 10

Per-pupil education expenditure trends for counties receiving LHC grants in 2008 compared to counties never receiving grants

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Sorensen, L.C., Fox, A.M., Jung, H. et al. Lead exposure and academic achievement: evidence from childhood lead poisoning prevention efforts. J Popul Econ 32, 179–218 (2019).

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  • Lead exposure
  • Population intervention
  • Early childhood health
  • Economics of education
  • Achievement gap

JEL Classification

  • I18
  • I24
  • J1