Author: University of Wisconsin--Madison. Institute for Research on Poverty
Publisher:
ISBN:
Category : Agricultural laborers
Languages : en
Pages : 590

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Author: Alicia Haydock Munnell
Publisher:
ISBN:
Category : Basic income
Languages : en
Pages : 276

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Author: United States. General Accounting Office
Publisher:
ISBN:
Category : Evaluation research (Social action programs)
Languages : en
Pages : 96

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Author: Charles Murray
Publisher: Rowman & Littlefield
ISBN: 1442260726
Category : Political Science
Languages : en
Pages : 152

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Imagine that the United States were to scrap all its income transfer programs—including Social Security, Medicare, and all forms of welfare—and give every American age twenty-one and older $10,000 a year for life.This is the Plan, a radical new approach to social policy that defies any partisan label. First laid out by Charles Murray a decade ago, the updated edition reflects economic developments since that time. Murray, who previous books include Losing Ground and The Bell Curve, demonstrates that the Plan is financially feasible and the uses detailed analysis to argue that many goals of the welfare state—elimination of poverty, comfortable retirement for everyone, universal access to healthcare—would be better served under the Plan than under the current system. Murray’s goal, shared by Left and Right, is a society in which everyone, including the unluckiest among us, has the opportunity and means to construct a satisfying life. In Our Hands offers a rich and startling new way to think about how that goal might be achieved.

Author: Judith M. Gueron
Publisher: Russell Sage Foundation
ISBN: 1610448138
Category : Political Science
Languages : en
Pages : 594

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Once primarily used in medical clinical trials, random assignment experimentation is now accepted among social scientists across a broad range of disciplines. The technique has been used in social experiments to evaluate a variety of programs, from microfinance and welfare reform to housing vouchers and teaching methods. How did randomized experiments move beyond medicine and into the social sciences, and can they be used effectively to evaluate complex social problems? Fighting for Reliable Evidence provides an absorbing historical account of the characters and controversies that have propelled the wider use of random assignment in social policy research over the past forty years. Drawing from their extensive experience evaluating welfare reform programs, noted scholar practitioners Judith M. Gueron and Howard Rolston portray randomized experiments as a vital research tool to assess the impact of social policy. In a random assignment experiment, participants are sorted into either a treatment group that participates in a particular program, or a control group that does not. Because the groups are randomly selected, they do not differ from one another systematically. Therefore any subsequent differences between the groups can be attributed to the influence of the program or policy. The theory is elegant and persuasive, but many scholars worry that such an experiment is too difficult or expensive to implement in the real world. Can a control group be truly insulated from the treatment policy? Would staffers comply with the random allocation of participants? Would the findings matter? Fighting for Reliable Evidence recounts the experiments that helped answer these questions, starting with the income maintenance experiments and the Supported Work project in the 1960s and 1970s. Gueron and Rolston argue that a crucial turning point came during the 1980s, when Congress allowed states to experiment with welfare programs and foundations, states, and the federal government funded larger randomized trials to assess the impact of these reforms. As they trace these historical shifts, Gueron and Rolston discuss the ways that strategies for resolving theoretical and practical problems were developed, and they highlight the strict conditions required to execute a randomized experiment successfully. What emerges is a nuanced portrait of the potential and limitations of social experiments to advance empirical knowledge. Weaving history, data analysis and personal experience, Fighting for Reliable Evidence offers valuable lessons for researchers, policymakers, funders, and informed citizens interested in isolating the effect of policy initiatives. It is an essential primer on welfare policy, causal inference, and experimental designs.

Author: Michael Luca
Publisher: MIT Press
ISBN: 0262542277
Category : Business & Economics
Languages : en
Pages : 229

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How tech companies like Google, Airbnb, StubHub, and Facebook learn from experiments in our data-driven world—an excellent primer on experimental and behavioral economics Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of different online experiences. Once an esoteric tool for academic research, the randomized controlled trial has gone mainstream. No tech company worth its salt (or its share price) would dare make major changes to its platform without first running experiments to understand how they would influence user behavior. In this book, Michael Luca and Max Bazerman explain the importance of experiments for decision making in a data-driven world. Luca and Bazerman describe the central role experiments play in the tech sector, drawing lessons and best practices from the experiences of such companies as StubHub, Alibaba, and Uber. Successful experiments can save companies money—eBay, for example, discovered how to cut $50 million from its yearly advertising budget—or bring to light something previously ignored, as when Airbnb was forced to confront rampant discrimination by its hosts. Moving beyond tech, Luca and Bazerman consider experimenting for the social good—different ways that governments are using experiments to influence or “nudge” behavior ranging from voter apathy to school absenteeism. Experiments, they argue, are part of any leader's toolkit. With this book, readers can become part of “the experimental revolution.”

Author: United States. Department of Health, Education, and Welfare
Publisher:
ISBN:
Category : Income maintenance programs
Languages : en
Pages : 166

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Author: Ugo Gentilini
Publisher: World Bank Publications
ISBN: 1464815119
Category : Political Science
Languages : en
Pages : 325

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Universal basic income (UBI) is emerging as one of the most hotly debatedissues in development and social protection policy. But what are thefeatures of UBI? What is it meant to achieve? How do we know, andwhat don’t we know, about its performance? What does it take to implementit in practice? Drawing from global evidence, literature, and survey data, thisvolume provides a framework to elucidate issues and trade-offs in UBI with a viewto help inform choices around its appropriateness and feasibility in different contexts.Specifically, the book examines how UBI differs from or complements othersocial assistance programs in terms of objectives, coverage, incidence, adequacy,incentives, effects on poverty and inequality, financing, political economy, andimplementation. It also reviews past and current country experiences, surveys thefull range of existing policy proposals, provides original results from micro–tax benefitsimulations, and sets out a range of considerations around the analytics andpractice of UBI.

Author: Maximilian Sommer
Publisher: Springer
ISBN: 3319240641
Category : Political Science
Languages : en
Pages : 214

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This book analyzes the consequences that would arise if Germany’s means-tested unemployment benefits were replaced with an unconditional basic income. The basic income scheme introduced is based on a negative income tax and calibrated to be both financially feasible and compatible with current constitutional legislation. Using data from the German Socio-Economic Panel (GSOEP) the author examines the impact of the reform on the household labor supply as well as on both poverty and inequality measures. It is shown that by applying reasonable values for both the basic income and the implied marginal tax rate imposed on earned incomes, efficiency gains can be reconciled with generally accepted value statements. Furthermore, as the proposal includes a universal basic income for families, child poverty could be reduced considerably. The estimates are based on the discrete choice approach to labor supply.

Author: Howard S. Bloom
Publisher: Russell Sage Foundation
ISBN: 1610440692
Category : Social Science
Languages : en
Pages : 259

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Book Description
Policy analysis has grown increasingly reliant on the random assignment experiment—a research method whereby participants are sorted by chance into either a program group that is subject to a government policy or program, or a control group that is not. Because the groups are randomly selected, they do not differ from one another systematically. Therefore any differences between the groups at the end of the study can be attributed solely to the influence of the program or policy. But there are many questions that randomized experiments have not been able to address. What component of a social policy made it successful? Did a given program fail because it was designed poorly or because it suffered from low participation rates? In Learning More from Social Experiments, editor Howard Bloom and a team of innovative social researchers profile advancements in the scientific underpinnings of social policy research that can improve randomized experimental studies. Using evaluations of actual social programs as examples, Learning More from Social Experiments makes the case that many of the limitations of random assignment studies can be overcome by combining data from these studies with statistical methods from other research designs. Carolyn Hill, James Riccio, and Bloom profile a new statistical model that allows researchers to pool data from multiple randomized-experiments in order to determine what characteristics of a program made it successful. Lisa Gennetian, Pamela Morris, Johannes Bos, and Bloom discuss how a statistical estimation procedure can be used with experimental data to single out the effects of a program's intermediate outcomes (e.g., how closely patients in a drug study adhere to the prescribed dosage) on its ultimate outcomes (the health effects of the drug). Sometimes, a social policy has its true effect on communities and not individuals, such as in neighborhood watch programs or public health initiatives. In these cases, researchers must randomly assign treatment to groups or clusters of individuals, but this technique raises different issues than do experiments that randomly assign individuals. Bloom evaluates the properties of cluster randomization, its relevance to different kinds of social programs, and the complications that arise from its use. He pays particular attention to the way in which the movement of individuals into and out of clusters over time complicates the design, execution, and interpretation of a study. Learning More from Social Experiments represents a substantial leap forward in the analysis of social policies. By supplementing theory with applied research examples, this important new book makes the case for enhancing the scope and relevance of social research by combining randomized experiments with non-experimental statistical methods, and it serves as a useful guide for researchers who wish to do so.