This book is a full-scale exposition of Charles Manski's new methodology for analyzing empirical questions in the social sciences. He recommends that researchers first ask what can be learned from data alone, and then ask what can be learned when data are combined with credible weak assumptions. Inferences predicated on weak assumptions, he argues, can achieve wide consensus, while ones that require strong assumptions almost inevitably are subject to sharp disagreements.
Building on the foundation laid in the author's Identification Problems in the Social Sciences (Harvard, 1995), the book's fifteen chapters are organized in three parts. Part I studies prediction with missing or otherwise incomplete data. Part II concerns the analysis of treatment response, which aims to predict outcomes when alternative treatment rules are applied to a population. Part III studies prediction of choice behavior. Each chapter juxtaposes developments of methodology with empirical or numerical illustrations. The book employs a simple notation and mathematical apparatus, using only basic elements of probability theory.Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Charles F. Manski is Board of Trustees Professor of Economics at Northwestern University.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardback. Etat : Good. 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. N° de réf. du vendeur 00109653667
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