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Workers in climate exposed industries such as agriculture, construction, and manufacturing face increased health risks of working on high temperature days and may make decisions to reduce work on high-heat days to mitigate this risk. Utilizing the American Time Use Survey (ATUS) for the period 2003 through 2018 and historical weather data, we model the relationship between daily temperature and time allocation, focusing on hours worked by high-risk laborers. The results indicate that labor allocation decisions are context specific and likely driven by supply-side factors. We do not find a significant relationship between temperature and hours worked during the Great Recession (2008–2014), perhaps due to high competition for employment, however during periods of economic growth (2003–2007, 2015–2018) we find a significant reduction in hours worked on high-heat days. During periods of economic growth, for every degree above 90 on a particular day, the average high-risk worker reduces their time devoted to work by about 2.6 minutes relative to a 90-degree day. This effect is expected to intensify in the future as temperatures rise. Applying the modeled relationships to climate projections through the end of century, we find that annual lost wages resulting from decreased time spent working on days over 90 degrees across the United States range from $36.7 to $80.0 billion in 2090 under intermediate and high emission futures, respectively. [ABSTRACT FROM AUTHOR]

The extreme temperatures expected under climate change may be especially harmful to children. Children are more vulnerable to heat partly because of their physiological features, but, perhaps more important, because they behave and respond differently than adults do. Children are less likely to manage their own heat risk and may have fewer ways to avoid heat; for example, because they don't plan their own schedules, they typically can't avoid activity during hot portions of the day. And very young children may not be able to tell adults that they're feeling heat's effects. Joshua Graff Zivin and Jeffrey Shrader zero in on how rising temperatures from global warming can be expected to affect children. They review evidence that high temperatures would mean more deaths, especially among fetuses and young children (as well as the elderly). When combined with other conditions--such as high humidity, diseases, or pollution--heat can be even deadlier. Even when it doesn't kill, high heat directly causes heat-related illnesses such as heat exhaustion; worsens other conditions, such as asthma, by increasing smog and ozone pollution; and harms fetuses in the womb, often with long-term consequences. High temperatures can also make learning more difficult, affecting children's adult job prospects. What can we do to protect children from a hotter climate? Graff Zivin and Shrader discuss a range of policies that could help. Such policies include requiring air conditioning in schools; heat wave warning systems coupled with public infrastructure that helps people stay indoors and stay cool; and readjusting schedules so that, for example, children are mostly indoors during the hottest time of day or the hottest season of the year. Joshua Graff Zivin is a professor of economics at the University of California, San Diego. Jeffrey Shrader is a PhD candidate in economics at the University of California, San Diego. [ABSTRACT FROM AUTHOR]

In this paper, we develop a methodology for estimating marginal emissions of electricity demand that vary by location and time of day across the United States. The approach takes account of the generation mix within interconnected electricity markets and shifting load profiles throughout the day. Using data available for 2007 through 2009, with a focus on carbon dioxide (CO 2 ), we find substantial variation among locations and times of day. Marginal emission rates are more than three times as large in the upper Midwest compared to the western United States, and within regions, rates for some hours of the day are more than twice those for others. We apply our results to an evaluation of plug-in electric vehicles (PEVs). The CO 2 emissions per mile from driving PEVs are less than those from driving a hybrid car in the western United States and Texas. In the upper Midwest, however, charging during the recommended hours at night implies that PEVs generate more emissions per mile than the average car currently on the road. Underlying many of our results is a fundamental tension between electricity load management and environmental goals: the hours when electricity is the least expensive to produce tend to be the hours with the greatest emissions. In addition to PEVs, we show how our estimates are useful for evaluating the heterogeneous effects of other policies and initiatives, such as distributed solar and real-time pricing. [ABSTRACT FROM AUTHOR]

Despite its presumed role as an engine of economic growth, we know surprisingly little about the drivers of scientific creativity. We exploit key differences across funding streams within the academic life sciences to estimate the impact of incentives on the rate and direction of scientific exploration. Specifically, we study the careers of investigators of the Howard Hughes Medical Institute (HHMI), which tolerates early failure, rewards long-term success, and gives its appointees great freedom to experiment, and grantees from the National Institutes of Health (NIH), who are subject to short review cycles, predefined deliverables, and renewal policies unforgiving of failure. Using a combination of propensity-score weighting and difference-in-differences estimation strategies, we find that HHMI investigators produce high-impact articles at a much higher rate than a control group of similarly accomplished NIH-funded scientists. Moreover, the direction of their research changes in ways that suggest the program induces them to explore novel lines of inquiry. [ABSTRACT FROM AUTHOR]

Objective. To assess the effectiveness and cost–effectiveness of four treatment modalities for substance abuse. Data Sources. The study used data from the Services Research Outcomes Study (SROS), a survey of 3,047 clients in a random sample of 99 drug treatment facilities across the United States. Detailed sociodemographic, substance use, and clinical data were abstracted from treatment records. Substance abuse outcome and treatment history following discharge from index facilities were assessed using a comprehensive interview with 1,799 of these individuals five years after discharge. Treatment success was defined in two ways: as abstinence and as any reduction in substance use. Study Design. Effectiveness and cost–effectiveness of four modalities were compared: inpatient, residential, outpatient detox/methadone, and outpatient drug–free. Clients were stratified based on propensity scores and analyses were conducted within these strata. Sensitivity analyses examined the impact of future substance abuse treatment on effectiveness and cost–effectiveness estimates. Principal Findings. Treatment of substance disorders appears to be cost–effective compared to other health interventions. The cost per successfully treated abstinent case in the least costly modality, the outpatient drug–free programs, was $6,300 (95 percent confidence intervals: $5,200–$7,900) in 1990 dollars. There were only minor differences between various modalities of treatment with regard to effectiveness. However, modalities varied considerably with regard to cost–effectiveness. Outpatient drug–free programs were the most cost–effective. There was little evidence that relative effectiveness or cost–effectiveness of programs varied according to factors that were associated with selection into different programs. Conclusions. Substance disorders can be treated most cost–effectively in outpatient drug–free settings. Savings from transitioning to the most cost–effective treatment modality may free resources that could be reinvested to improve access to substance abuse treatment for a larger number of individuals in need of such treatment. [ABSTRACT FROM AUTHOR]

Purpose: A systematic review examining the economic effects of pharmacist-provided direct patient care on health outcomes in the United States was conducted., Methods: A comprehensive literature search was conducted using 13 academic and medical databases. Studies were included in the analysis if they described pharmacist-provided direct patient care, used comparison groups, evaluated economic outcomes, and were conducted in the United States. Outcome results were categorized as (1) favorable, indicating significant improvement as a result of pharmacists' interventions or services, (2) not favorable, indicating significant improvement as a result of nonpharmacist care, (3) mixed, having favorable results on one measure of a study variable but not favorable results or no effect on another, (4) having no effect, indicating no significant difference between pharmacists' interventions or services and the comparison, or (5) unclear, indicating the outcome could not be determined based on presented data., Results: Of the 56,573 citations considered, a total of 126 studies met the criteria for inclusion in this systematic review. Results favoring pharmacist-provided care were found in 20 studies (15.9%), mixed results were seen in 53 studies (42.1%), no effect was found in 6 studies (4.8%), and unclear results were found in 47 studies (37.3%)., Conclusion: A majority of studies examining the economic effects of pharmacist-provided direct patient care in the United States were limited by their partial cost analyses, study design, and other analysis considerations. A majority of the 20 studies that found positive economic benefits examined pharmacists' interventions involving technical methods or multimodal approaches.

The influence of current medical technology adoption decisions on the use of future potential interventions is often overlooked. Some health interventions, once exercised, restrict future potential interventions for both related and unrelated medical conditions. For example, treatment of a patient with an antibiotic may lead to resistance in that patient that precludes future treatment with the same or related compounds. This irreversibility raises the value of treatment modalities that preserve future treatment options. Surprisingly, partial reversibility with or without learning can either increase or decrease this value, depending on the distribution of patient types within the treated population. Evaluations that ignore these option values miss an important part of the welfare equation that is becoming increasingly important as individuals live longer and the stock of medical treatments increases., (Copyright (c) 2009 John Wiley & Sons, Ltd.)