Identification for Prediction and Decision (9780674026537)

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.

Product details

• Format Hardback | 368 pages
• Dimensions 156 x 235 x 27.18mm | 644.1g
• Publication date 01 Mar 2008
• Publisher Harvard University Press
• Publication City/Country Cambridge, Mass, United States
• Language English
• Illustrations note 2 line illustrations, 7 tables
• ISBN10 0674026535
• ISBN13 9780674026537
• Bestsellers rank 855,676

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