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Valuing the Benefits of Reducing Childhood Lead Exposure—Human Capital, Parental Preferences, Or Both?

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Valuing the Benefits of Reducing Childhood Lead Exposure—Human Capital, Parental Preferences, Or Both? Valuing the Benefits of Reducing Childhood Lead Exposure—Human Capital, Parental Preferences, or Both? Ying Zhou1, Scott D Grosse2 1 Environmental Health Tracking Section, Division of Environmental Health Practice and Science, National Center for Environmental Health, Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA 2 National Center on Birth Defects and Developmental Disabilities, CDC, Atlanta, GA, USA * Corresponding Author: Ying Zhou Environmental Health Tracking Section Division of Environmental Health Practice and Science National Center for Environmental Health (NCEH) Centers for Disease Control and Prevention (CDC) Atlanta, GA, USA Email: [email protected] Disclaimer: The findings and conclusions in this paper are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. The authors declare they have no actual or potential competing financial interests. This paper has been prepared for the Harvard Center for Risk Analysis “Risk Assessment, Economic Evaluation, and Decisions” workshop, September 26‐27, 2019. 1 Abstract Early childhood lead exposure can impair neurobehavioral development. There is a well‐documented relationship between increases in blood lead levels (BLL) and reduced IQ. Public health actions have been taken to reduce lead in drinking water including lead service line (LSL) replacement. This narrative review summarized two methods used in the literature to assign economic value to IQ—human capital approach and willingness to pay (WTP) approach. We used estimates from the literature in a case study that estimated the economic benefits of prevention of cognitive impairment caused by lead exposure in young children. In the case study, we made assumptions in the reduction in lead levels in drinking water after LSL replacement, corresponding reduction in blood lead levels, and IQ increases. We assigned monetary values to the increase in IQ using human capital and WTP approaches. Our review of literature in human capital approach shows that the proportional increase in earnings with increased cognitive ability may be in the range of 1.3% to 2.2% per IQ point. The present value of real earnings in early childhood likely increased by 1.5‐1.8% per IQ point, which implies a range of $12,000 to $17,500 per IQ point in 2018 dollars, assuming a linear relationship. Those estimates place no economic value on cognitive ability applied to childrearing or other unpaid household services. For WTP estimates, we found one stated preference study in the peer reviewed literature that estimated WTP per IQ point to be $466 (2005 dollar). A working paper estimated parents’ WTP to be $1,100 and $1,900 per IQ point gained. Based on human capital approach estimates, if more than one child benefits from LSL replacement in a house, the benefit will outweigh the cost. Based on the WTP estimates, there would need to be 4 to 21 children per house to break‐even. When estimating the health benefits of reducing childhood lead exposure, the monetary value per IQ has the largest uncertainty comparing with other inputs used in the calculation. The large discrepancy from these two approaches is mainly due to the target for measurement and different perspectives. Estimates using these two approaches can complement each other. More WTP studies on this topic are needed to help fill in the gap in knowledge. Keywords: economic value, willingness to pay, human capital, IQ, lead exposure 2 Introduction Lead (Pb) exposure can affect nearly every system in the body. Children are especially at risk from lead exposure because of their small size and developing brains. No safe lead level in children has been identified (CDC 2019a). Early childhood lead exposure can impair neurobehavioral development. Even low levels of lead in blood have been shown to affect a child’s intelligence quotient (IQ), ability to pay attention, and academic achievement (Chen et al. 2005; Lanphear et al. 2005). In particular, multiple high‐quality epidemiologic studies summarized in a U.S. Environmental Protection Agency (EPA) report have demonstrated a causal relationship between blood lead level (BLL) and cognitive function decrements in children (EPA 2013). Lead can be found in the air, the soil, the water, and past use of lead‐based paint in homes. The recent crisis in Flint, Michigan shed light on the problem of lead in drinking water (Ruckart et al. 2019). EPA estimates that drinking water contaminated with lead can contribute to 20% or more of a person’s total exposure to lead (EPA 2019a). Infants who consume mostly mixed formula can receive 40% to 60% of their total exposure to lead from drinking water. Lead can enter drinking water when plumbing materials that contain lead corrode, especially where the water has high acidity or low mineral content that corrodes pipes and fixtures (EPA 2019a). The most common sources of lead in drinking water are lead pipes, faucets, and fixtures. In homes with lead pipes that connect the home to the water main, also known as lead service lines (LSL), these pipes are typically the most significant source of lead in the water. Lead pipes are more likely to be found in older cities and homes built before 1986 (EPA 2019a). Among homes without lead service lines, the most common problem is with brass or chrome‐plated brass faucets and plumbing with lead solder. Actions have been taken to reduce lead in drinking water. For example, from 2004 through 2016, Lansing, Michigan, replaced 12,150 LSLs with copper lines at a cost of $44.5 million (Health Impact Project 2017). New York’s Clean Water Infrastructure Act of 2017 requires the New York State Department of Health to implement a Lead Service Line Replacement Program (LSLRP) (New York State Department of Health 2018). Milwaukee 3 requires full replacement of LSLs with copper pipes if a leak or failure is discovered or if the utility‐owned portion is replaced (Health Impact Project 2017). To estimate the economic value of efforts to reduce lead in drinking water, it is necessary to assign monetary values to expected improvements in health. In regulatory benefit‐cost analyses (BCA), it is preferred to use preference‐based estimates of societal willingness to pay (WTP) to reduce risks or willingness to accept (WTA) risks with monetary compensation. In particular, it is standard to use a WTP/WTA estimate of roughly $10 million per death averted to value deaths avoided by regulatory actions (Viscusi 2018). Lacking WTP estimates for nonfatal endpoints, it is common to use estimates of direct and indirect (productivity) costs associated with morbidity or disability to inform regulatory BCAs. For economic assessments of childhood lead poisoning prevention, change in IQ scores, a measure of cognitive outcome, is the most commonly used outcome measure. Because of the well documented relationship between increases in BLL and reduced IQ, this study focused on two methods to assign economic value to IQ—avoided costs and welfare gains. Avoided costs included both direct and indirect productivity costs. Of particular relevance to lead is the loss in lifetime economic productivity associated with reductions in cognitive skills, also referred to as the human capital approach. Welfare gains are valued by economists using WTP/WTA estimates. The objective of this study is to first review and summarize the estimates from the literature on assigning monetary values of an IQ point using human capital and WTP approaches. Then, we conducted a case study to estimate the economic benefits of prevention of cognitive impairment caused by lead exposure in young children based on these two approaches. Methods Human capital approach In the human capital approach used in health economics, societal productivity costs associated with premature death or disability are calculated as the present value of lost future economic production, discounted using a 4 social discount rate. Productivity is calculated in the literature as economic production at the national level, including anything that contributes to gross domestic product (GDP) plus the value of non‐market services that are not included in GDP, e.g., child rearing and volunteer services. Similarly, future market production has been projected in published studies based on employment rates, life table survival probabilities, and projected gross (pre‐tax) earnings (Grosse and Krueger 2011; Grosse et al. 2019a; Pike and Grosse 2018). Updated estimates of annual and lifetime productivity for the US population stratified by age and sex were recently published based on 2016 data (Grosse et al. 2019a). The lifetime estimates of gross market earnings, which include payroll taxes and monetary benefits, for an infant in 2016 were estimated as $0.8‐0.9 million assuming a 3% discount rate and future growth in real earnings of 0.5‐1.0% per year (Grosse et al. 2019a). The monetary value of nonmarket production is typically imputed on the basis of time use data with hours conservatively valued using the replacement cost approach (Grosse et al. 2019a; Grosse et al. 2019b). Lifetime total productivity is estimated as $1.2‐1.5 million in 2016 (Grosse et al. 2019a). Anything that reduces individuals’ employment and earning capacity, even if not associated with overt disability, has an adverse economic impact on overall societal productivity. For example, if a 1 IQ point reduction is estimated to be associated with a 1% reduction in future earnings, one can multiply the present value of future earnings, roughly $900,000, by 1% to calculate the expected loss of future market productivity, or $9,000. The sources of published estimates summarized in the Results section are derived from previous reviews of the literature on estimates of the IQ‐earnings association published through 2014 (Grosse 2007; Grosse 2014) supplemented by searches of Google Scholar and PubMed for more recent studies. Willingness to pay approach WTP for a health improvement program or policy is the aggregation of the maximum amounts of money individuals would voluntarily pay to obtain the improvement, given their budget constraints (Robinson and Hammitt 2013).
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