While lead was outlawed from use in gasoline and paint in the 1970s, many children in this country continue to be exposed to lead in dust, soil, and deteriorated paint in housing units. Efforts to cut the use of this neurotoxin in other products—such as foods, cosmetics, folk remedies, and toys—continue because exposure is known to be harmful, particularly in utero and in early childhood.
In fact, thousands of scientific studies over the last two decades have shown that young children suffer neurological harm at much lower blood lead levels than previously recognized, with potentially serious implications for brain development and cognitive and noncognitive abilities. This was a major motivation behind a recent court challenge that resulted in a dramatic tightening in the National Ambient Air Quality Standard for lead (due to take effect by 2017) to 0.15 micrograms per cubic meter. The previous standard, set in 1978, had been 1.5 micrograms per cubic meter.
So is this change justifiable? Do the social benefits from reducing lead emissions outweigh the costs? Economists address these questions by:
- determining the impact of the control policy on reducing the atmospheric concentration,
- assessing the exposed population that potentially benefits from the reduction in ambient concentrations,
- estimating the reduction in blood-lead levels for the affected population,
- evaluating the resulting health benefits, and
- obtaining a monetary measure of these benefits.
The first four steps can be measured by linking emissions/air quality models to local population data, as well as evidence from the scientific literature. The final one is our focus here, as this is perhaps the most contentious.
The benefits of reducing exposure to lead are based on estimated changes in mental ability—usually measured by changes in IQ—in children aged seven and below, and associated changes in their future earnings potential. EPA’s regulatory impact assessment for the new lead standard assumed that each 1-percent increase in IQ would increase lifetime earnings by around 1.8 to 2.3 percent. But the reliability of these assumptions is open to question. Would alternative assumptions alter economic assessments of the desirability of previous policies to reduce lead emissions?
The EPA assumption was based on two earlier, widely cited studies by Schwartz (1994) and Salkever (1995). The estimates of the IQ premium in those studies were obtained by comparing lifetime earnings of individuals—which depend on their wages and fringe benefits, hours worked, and likelihood of employment—with different IQ levels, holding other factors, like occupation or age, constant.
However, recent analyses appear to cast some doubt on these earlier findings (Grosse 2007, Gayer and Hahn 2006). Heckman et al. (2006) developed better measures to take into account the quality of people’s education, finding that, for 30-year old men, a 1-percent difference in cognitive ability made only a 0.6 percent difference in hourly wages—less than a third of EPA’s assumption. (However, this was exclusively for relatively young men, for whom the estimated association between IQ and earnings is somewhat weaker than for older men, and women.) Another study by Zak and Rees (2002) estimated the wage premium at 0.6 to 1.4 percent for men.
The more recent evidence suggests that the association between cognitive ability and earnings has previously been overstated, and, by implication, the EPA regulatory impact analysis may have overstated the benefits of reducing children’s exposure to environmental lead. For example, Grosse et al. (2002) estimated that reductions in lead exposure from the mid-1970s to the late 1990s increased the total lifetime productivity of each year’s U.S. birth cohort by $110-$320 billion. Based on the newer Zak-Rees figures, the estimates would fall to $70-$150 billion.
Nonetheless, even these lower benefit figures are large relative to estimates of the annualized costs of phasing out leaded gasoline and paint, and other control measures. Moreover, the benefit estimates would be higher if recent findings were taken into account that link adverse health impacts to relatively low blood lead levels. Furthermore, the Grosse et al. estimate did not account for lead’s effects on noncognitive functioning, such as the ability to show up for work and focus on a task. Some studies find that those types of abilities or personality traits may be an even more important determinant of earnings than cognitive ability (Heckman et al., 2006). Nor did the study account for the possible association between lead exposure in childhood and criminal behavior among adults. Interventions in childhood that reduce criminal behavior in adulthood can generate very large economic returns.
As for the recent tightening of the lead standard, cost/benefit analyses are less conclusive, as the results are sensitive to different assumptions, such as the rate at which higher future earnings are discounted. Scaling back the benefits in the EPA regulatory impact assessment (which include some side-benefits from related reductions in particulate emissions) to account for the smaller earnings/IQ association, leaves an overall net benefit under some range of assumptions and a net loss under others as it is difficult to make a definitive case for or against a tighter standard at this time. Perhaps new assessments will be more positive down the road, if firms develop innovative, low-cost ways to reduce lead emissions and some broader benefits of reduced lead poisoning, noted above, are quantified and taken into account.
The author would like to thank Scott Grosse for his thoughtful review of this article.
Views expressed are those of the author. RFF does not take institutional positions on legislative or policy questions.
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