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  • Cited by 2
Publisher:
Cambridge University Press
Online publication date:
May 2021
Print publication year:
2021
Online ISBN:
9781139026819

Book description

Tension has long existed in the social sciences between quantitative and qualitative approaches on one hand, and theory-minded and empirical techniques on the other. The latter divide has grown sharper in the wake of new behavioural and experimental perspectives which draw on both sides of these modelling schemes. This book works to address this disconnect by establishing a framework for methodological unification: empirical implications of theoretical models (EITM). This framework connects behavioural and applied statistical concepts, develops analogues of these concepts, and links and evaluates these analogues. The authors offer detailed explanations of how these concepts may be framed, to assist researchers interested in incorporating EITM into their own research. They go on to demonstrate how EITM may be put into practice for a range of disciplines within the social sciences, including voting, party identification, social interaction, learning, conflict and cooperation to macro-policy formulation.

Reviews

'Empirical Implications of Theoretical Models is a major contribution to political science. Granato, Lo, and Wong explain the rationale for establishing a systematic ‘dialogue between theory and test,’ and how this produces important breakthroughs in the study of campaigns and elections, comparative and international political economy and other fields. The book is essential reading for students of political science in particular and of social science in general.'John R. Freeman, University of Minnesota

'A book that systematically expounds the idea and reaps the harvest of EITM is long overdue. The publication of this book is a triumphant celebration of the tremendous achievements a scientifically rigorous framework has brought to political, social, and economic sciences.'Tse-min Lin, University of Texas at Austin

'Success in science is defined by the presence of a powerful exemplar. For the EITM movement, this book is such an exemplar. It is more than an argument for closing the gap between theory and evidence; it lays out the steps that any student of the social sciences might emulate when tackling complex questions of humans and their institutions. This book belongs on the shelf of every serious scholar concerned with the empirical and theoretical study of social behavior.'Rick K. Wilson, Rice University

'Based on extensive experience in teaching the EITM approach, the authors work through many examples that make it an invaluable teaching tool for graduate research courses. A rewarding read for those who want to contribute to the advancement of the social sciences'.Norman Bradburn, University of Chicago

'The goal of social science is to understand more and more by less and less. In this effort the spirit of EITM plays a big part - a unified field for both the theoretical and the empirical components, a unified methodology encompassing mathematical tools for the formal work and statistical tools for the empirical work, someday the surprise of unifying seemingly disparate topical domains. Granato, Lo, and Wong have written a masterly guide to every aspect of EITM, providing a wealth of tools and describing a wide range of applications. This book will be invaluable to all researchers, seasoned and novice alike, dedicated to the growth of knowledge in the social sciences.'Guillermina Jasso, New York University

'Too often in the social sciences, formal theories and empirical studies have occupied separate worlds. This book is a masterful overview of a more modern approach, demonstrating how empirical implications can be rigorously derived from theoretical models. The new framework not only lets researchers test models more reliably, but more importantly, it directs them to previously unsuspected empirical findings that conventional empirical analysis will not uncover. This is a volume that every empirical researcher will want to read.'Christopher H. Achen, Princeton University

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