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Manski argues that public policy is based on untrustworthy analysis. Failing to account for uncertainty in an uncertain world, policy analysis routinely misleads policy makers with expressions of certitude. Manski critiques the status quo and offers an innovation to improve both how policy research is conducted and how it is used by policy makers.
Juxtaposing methodology with empirical and numerical illustrations, this book is a full-scale exposition of a new approach for analyzing empirical questions in the social sciences. Manski recommends that researchers first ask what can be learned from data alone, and then what can be learned when data are combined with credible weak assumptions.
The original research papers collected in this volume continue the development of discrete choice analysis, of related structural models for analysis of choice behavior, and of the statistical theory used in inference on these models. Most papers in the volume are revised versions of ones presented at a 2005 conference in honor of Daniel L.
This book provides a language and tools for finding bounds on predictions social and behavioral scientists can logically make from nonexperimental and experimental data. Manski draws on criminology, demography, epidemiology, social psychology, sociology, and economics to illustrate this language and to demonstrate the usefulness of the tools.
How should planners use the available evidence to choose treatments? This book addresses key aspects of this question, exploring and partially resolving pervasive problems of identification and statistical inference that arise when studying treatment response and making treatment choices.
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