Gary King

The classic work on qualitative methods in political scienceDesigning Social Inquiry presents a unified approach to qualitative and quantitative research in political science, showing how the same logic of inference underlies both. This stimulating book discusses issues related to framing research questions, measuring the accuracy of data and the uncertainty of empirical inferences, discovering causal effects, and getting the most out of qualitative research. It addresses topics such as interpretation and inference, comparative case studies, constructing causal theories, dependent and explanatory variables, the limits of random selection, selection bias, and errors in measurement. The book only uses mathematical notation to clarify concepts, and assumes no prior knowledge of mathematics or statistics.Featuring a new preface by Robert O. Keohane and Gary King, this edition makes an influential work available to new generations of qualitative researchers in the social sciences.

The classic work on qualitative methods in political scienceDesigning Social Inquiry presents a unified approach to qualitative and quantitative research in political science, showing how the same logic of inference underlies both. This stimulating book discusses issues related to framing research questions, measuring the accuracy of data and the uncertainty of empirical inferences, discovering causal effects, and getting the most out of qualitative research. It addresses topics such as interpretation and inference, comparative case studies, constructing causal theories, dependent and explanatory variables, the limits of random selection, selection bias, and errors in measurement. The book only uses mathematical notation to clarify concepts, and assumes no prior knowledge of mathematics or statistics.Featuring a new preface by Robert O. Keohane and Gary King, this edition makes an influential work available to new generations of qualitative researchers in the social sciences.

Before Bob and Barry, even before Bud, there was Bennie, and he might have been the best of them all. He was certainly the most innovative. Best remembered as the mentor of the University of Oklahoma's football team from 1905 through 1926, Bennie Owen also coached baseball and basketball and served as the director of athletics. He retired as intramural director at the age of seventy-five. A visionary and a builder, he exerted the driving force that created the university's Memorial Stadium, one field house, Memorial Union building, men's swimming pool, baseball field and bleachers, concrete tennis courts, nine-hole golf course and intramural playing fields. A true man of all seasons, he laid the foundation for a Sooner tradition of excellence--in football and beyond.

Demographic Forecasting introduces new statistical tools that can greatly improve forecasts of population death rates. Mortality forecasting is used in a wide variety of academic fields, and for policymaking in global health, social security and retirement planning, and other areas. Federico Girosi and Gary King provide an innovative framework for forecasting age-sex-country-cause-specific variables that makes it possible to incorporate more information than standard approaches. These new methods more generally make it possible to include different explanatory variables in a time-series regression for each cross section while still borrowing strength from one regression to improve the estimation of all. The authors show that many existing Bayesian models with explanatory variables use prior densities that incorrectly formalize prior knowledge, and they show how to avoid these problems. They also explain how to incorporate a great deal of demographic knowledge into models with many fewer adjustable parameters than classic Bayesian approaches, and develop models with Bayesian priors in the presence of partial prior ignorance. By showing how to include more information in statistical models, Demographic Forecasting carries broad statistical implications for social scientists, statisticians, demographers, public-health experts, policymakers, and industry analysts. * Introduces methods to improve forecasts of mortality rates and similar variables * Provides innovative tools for more effective statistical modeling * Makes available free open-source software and replication data * Includes full-color graphics, a complete glossary of symbols, a self-contained math refresher, and more

One of the hallmarks of the development of political science as a discipline has been the creation of new methodologies by scholars within the discipline--methodologies that are well-suited to the analysis of political data. Gary King has been a leader in the development of these new approaches to the analysis of political data. In his book, Unifying Political Methodology, King shows how the likelihood theory of inference offers a unified approach to statistical modeling for political research and thus enables us to better analyze the enormous amount of data political scientists have collected over the years. Newly reissued, this book is a landmark in the development of political methodology and continues to challenge scholars and spark controversy."Gary King's Unifying Political Methodology is at once an introduction to the likelihood theory of statistical inference and an evangelist's call for us to change our ways of doing political methodology. One need not accept the altar call to benefit enormously from the book, but the intellectual debate over the call for reformation is likely to be the enduring contribution of the work." --Charles Franklin, American Political Science Review"King's book is one of the only existing books which deal with political methodology in a clear and consistent framework. The material in it is now and will continue to be essential reading for all serious students and researchers in political methodology." --R. Michael Alvarez, California Institute of Tech-nologyGary King is Professor of Government, Harvard University. One of the leading thinkers in political methodology, he is the author of A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data and other books and articles.

This book provides a solution to the ecological inference problem, which has plagued users of statistical methods for over seventy-five years: How can researchers reliably infer individual-level behavior from aggregate (ecological) data? In political science, this question arises when individual-level surveys are unavailable (for instance, local or comparative electoral politics), unreliable (racial politics), insufficient (political geography), or infeasible (political history). This ecological inference problem also confronts researchers in numerous areas of major significance in public policy, and other academic disciplines, ranging from epidemiology and marketing to sociology and quantitative history. Although many have attempted to make such cross-level inferences, scholars agree that all existing methods yield very inaccurate conclusions about the world. In this volume, Gary King lays out a unique--and reliable--solution to this venerable problem. King begins with a qualitative overview, readable even by those without a statistical background. He then unifies the apparently diverse findings in the methodological literature, so that only one aggregation problem remains to be solved. He then presents his solution, as well as empirical evaluations of the solution that include over 16,000 comparisons of his estimates from real aggregate data to the known individual-level answer. The method works in practice. King's solution to the ecological inference problem will enable empirical researchers to investigate substantive questions that have heretofore proved unanswerable, and move forward fields of inquiry in which progress has been stifled by this problem.