"Economic gains resulting from the reduction in children's exposure to lead in the United States", Grosse et al 2002 (fulltext)

We assumed the change in cognitive ability resulting from declines in BLLs, on the basis of published meta-analyses, to be between 0.185 and 0.323 IQ points for each 1 g/dL blood lead concentration. These calculations imply that, because of falling BLLs, U.S. preschool-aged children in the late 1990s had IQs that were, on average, 2.2-4.7 points higher than they would have been if they had the blood lead distribution observed among U.S. preschool-aged children in the late 1970s. We estimated that each IQ point raises worker productivity 1.76-2.38%. With discounted lifetime earnings of $723,300 for each 2-year-old in 2000 dollars, the estimated economic benefit for each year's cohort of 3.8 million 2-year-old children ranges from $110 billion to $319 billion.

...We calculated the economic benefit realized by reduced lead exposure in the United States since the late 1970s through a series of steps, each associated with a component of the model in Figure 1. First, we estimated the amount by which BLLs have fallen over time through secondary analysis of data from the National Health and Nutrition Examination Surveys (NHANES). Second, we applied estimates from published studies of the strength, shape, and magnitude of the association between BLLs and cognitive ability test scores. In particular, we examined two published meta-analyses to arrive at estimates of the ratio of change in BLL to change in IQ. Third, on the basis of a brief review of literature on the association between cognitive ability and earning potential, we estimated the percentage change in earnings associated with absolute differences in IQ levels. Fourth, we calculated the present value (2000 dollars) of the percentage change in earnings.

...Schwartz (6) calculated that the total effect of a 1-point difference in cognitive ability is a 1.76% difference in earnings. Of this amount, 0.5% is the direct effect of ability on earnings. Schwartz (6) took this estimate from an econometric study by Griliches (19) that was representative of other econometric studies from the 1970s. Schwartz (6) assumed that a given difference in IQ scores observed in school-aged children can be expected to lead to a comparable difference in achieved cognitive ability in young adults.

The indirect effect of ability on earnings, which accounts for the remaining 1.26% difference, is modeled through two pathways. One is the effect of ability on years of schooling multiplied by the effect of years of schooling on hourly earnings. Needleman et al. (20) reported that a 4.5-point difference in IQ between groups with high tooth lead and with low tooth lead was associated with a 0.59 difference in grade level attained. The ratio of the two numbers implies a difference of 0.131 years of schooling for 1 IQ point. If each additional year of schooling results in a 6% increase in hourly wages, 1 IQ point would lead to a 0.79% increase in expected earnings through years of education. Second, Schwartz (6) modeled ability as influencing employment participation through influence on high school graduation. On the basis of the analysis of Needleman et al. (20) and 1978 survey data reported by Krupnick and Cropper (21), Schwartz (6) calculated that 1 point in IQ is associated with a 4.5% difference in probability of graduating from high school and that high school graduation is associated with a 10.5% difference in labor force participation. On the assumption of an equivalent percentage change in annual earnings, this leads to a 0.47% difference in expected earnings. Salkever (22) published an alternate estimation of the effect of cognitive ability on earnings. Salkever directly estimated the effect of ability on annual earnings, among those with earnings. The estimated association of ability with annual earnings incorporates both the effect of ability on hourly earnings and its effect on annual hours of work. He also added a direct pathway from ability to work participation independent of education.

According to Salkever (22), a 1-point difference in ability is associated with a 1.931% difference in earnings for males and a 3.225% difference for females. The direct effect on earnings is 1.24% for males and 1.40% for females. Salkever (22) analyzed income and educational attainment data from the 1990 wave of the National Longitudinal Study of Youth (NLSY) in combination with AFQT scores collected during 1979–1980, when the respondents were 14–23 years of age.

For the indirect effect of ability on schooling attainment, Salkever (22) reported that a 1-point difference was associated with 0.1007 years of schooling attained for both males and females in the NLSY data. Also, 1 year of schooling attainment raised hourly earnings by 4.88% for males and 10.08% for females in the 1990 NLSY data. According to these results, a 1-point difference in ability is associated, through an indirect effect on schooling, with a 0.49% difference in earnings for males and a 1.10% difference in earnings for females.

Salkever (22) reported that the direct effect of a 1-point difference in ability was a 0.1602 percentage point difference in probability of labor force participation for males and a 0.3679 percentage point difference for females. In addition, he calculated that 1 year of schooling raised labor force participation rates by 0.3536 percentage points for males and 2.8247 percentage points for females. Subtracting the other components from the totals, a 1-point change in cognitive ability is associated with a difference in earnings of 0.20% for males and 0.72% for females through effects on labor force participation. Finally, in an analysis of the 1990 NLSY earnings data, Neal and Johnson (23) reported smaller estimates of the effect of cognitive ability on earnings. They included workers who took the AFQT test when they were 14–18 years of age and excluded those who took the AFQT test at 19–23 years of age to make the test scores more comparable. They also estimated the total effect of ability on hourly earnings by excluding schooling variables. Their estimates indicate that a 1point difference in AFQT scores is associated with a 1.15% difference in earnings for men and a 1.52% difference for women. Their estimate of the direct effect of ability on hourly earnings, controlling for schooling, is 0.83% for men; they reported no estimate for women.

The analysis of Neal and Johnson (23) has no link from ability to labor force participation. According to Salkever (22), a 1-point difference in ability leads to a 0.20% difference for males and 0.72% for females. If we add Salkever’s figures (22) to the estimates from Neal and Johnson (23), the total effect of a 1-point difference in ability on earnings is 1.35% for males and 2.24% for females.

Their summary estimate from pg5/567 is a lower-middle-upperbound of each IQ point is worth, in net present value 2000 dollars: 12,700-14,500-17,200.

(Note that these figures, as usual, are net estimates of the value to an individual: so they are including zero-sum games and positional benefits. They aren't giving estimates of the positive externalities or marginal benefits.)