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Few United States government programs are as controversial as those designed to aid the poor. From tax credits to medical assistance, aid to needy families is surrounded by debate—on what benefits should be offered, what forms they should take, and how they should be administered. The past few decades, in fact, have seen this debate lead to broad transformations of aid programs themselves, with Aid to Families with Dependent Children replaced by Temporary Assistance to Needy Families, the Earned Income Tax Credit growing from a minor program to one of the most important for low-income families, and Medicaid greatly expanding its eligibility. This volume provides a remarkable overview of how such programs actually work, offering an impressive wealth of information on the nation's nine largest "means-tested" programs—that is, those in which some test of income forms the basis for participation. For each program, contributors describe origins and goals, summarize policy histories and current rules, and discuss the recipient's characteristics as well as the different types of benefits they receive. Each chapter then provides an overview of scholarly research on each program, bringing together the results of the field's most rigorous statistical examinations. The result is a fascinating portrayal of the evolution and current state of means-tested programs, one that charts a number of shifts in emphasis—the decline of cash assistance, for instance, and the increasing emphasis on work. This exemplary portrait of the nation's safety net will be an invaluable reference for anyone interested in American social policy.
Addressing the challenge of covering heath care expenses—while minimizing economic risks. Moral hazard—the tendency to change behavior when the cost of that behavior will be borne by others—is a particularly tricky question when considering health care. Kenneth J. Arrow’s seminal 1963 paper on this topic (included in this volume) was one of the first to explore the implication of moral hazard for health care, and Amy Finkelstein—recognized as one of the world’s foremost experts on the topic—here examines this issue in the context of contemporary American health care policy. Drawing on research from both the original RAND Health Insurance Experiment and her own research, including a 2008 Health Insurance Experiment in Oregon, Finkelstein presents compelling evidence that health insurance does indeed affect medical spending and encourages policy solutions that acknowledge and account for this. The volume also features commentaries and insights from other renowned economists, including an introduction by Joseph P. Newhouse that provides context for the discussion, a commentary from Jonathan Gruber that considers provider-side moral hazard, and reflections from Joseph E. Stiglitz and Kenneth J. Arrow. “Reads like a fireside chat among a group of distinguished, articulate health economists.” —Choice
Today, more American women than ever before stay in the workforce into their sixties and seventies. This trend emerged in the 1980s, and has persisted during the past three decades, despite substantial changes in macroeconomic conditions. Why is this so? Today’s older American women work full-time jobs at greater rates than women in other developed countries. In Women Working Longer, editors Claudia Goldin and Lawrence F. Katz assemble new research that presents fresh insights on the phenomenon of working longer. Their findings suggest that education and work experience earlier in life are connected to women’s later-in-life work. Other contributors to the volume investigate additional factors that may play a role in late-life labor supply, such as marital disruption, household finances, and access to retirement benefits. A pioneering study of recent trends in older women’s labor force participation, this collection offers insights valuable to a wide array of social scientists, employers, and policy makers.
Personalized and precision medicine (PPM)—the targeting of therapies according to an individual’s genetic, environmental, or lifestyle characteristics—is becoming an increasingly important approach in health care treatment and prevention. The advancement of PPM is a challenge in traditional clinical, reimbursement, and regulatory landscapes because it is costly to develop and introduces a wide range of scientific, clinical, ethical, and socioeconomic issues. PPM raises a multitude of economic issues, including how information on accurate diagnosis and treatment success will be disseminated and who will bear the cost; changes to physician training to incorporate genetics, probability and statistics, and economic considerations; questions about whether the benefits of PPM will be confined to developed countries or will diffuse to emerging economies with less developed health care systems; the effects of patient heterogeneity on cost-effectiveness analysis; and opportunities for PPM’s growth beyond treatment of acute illness, such as prevention and reversal of chronic conditions. This volume explores the intersection of the scientific, clinical, and economic factors affecting the development of PPM, including its effects on the drug pipeline, on reimbursement of PPM diagnostics and treatments, and on funding of the requisite underlying research; and it examines recent empirical applications of PPM.
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.