Students in both social and natural sciences often seek regression methods to explain the frequency of events, such as visits to a doctor, auto accidents, or new patents awarded. This book provides the most comprehensive and up-to-date account of models and methods to interpret such data. The authors have conducted research in the field for more than twenty-five years. In this book, they combine theory and practice to make sophisticated methods of analysis accessible to researchers and practitioners working with widely different types of data and software in areas such as applied statistics, econometrics, marketing, operations research, actuarial studies, demography, biostatistics, and quantitative social sciences. The book may be used as a reference work on count models or by students seeking an authoritative overview. Complementary material in the form of data sets, template programs, and bibliographic resources can be accessed on the Internet through the authors' homepages. This second edition is an expanded and updated version of the first, with new empirical examples and more than one hundred new references added. The new material includes new theoretical topics, an updated and expanded treatment of cross-section models, coverage of bootstrap-based and simulation-based inference, expanded treatment of time series, multivariate and panel data, expanded treatment of endogenous regressors, coverage of quantile count regression, and a new chapter on Bayesian methods.

List of Figures List of Tables Preface Preface to the First Edition 1 Introduction 2 Model Specification and Estimation 3 Basic count Regression 4 Generalized Count Regression 5 Model Evaluation and Testing 6 Empirical Illustrations 7 Time Series Data 8 Multivariate Data 9 Longitudinal Data 10 Endongenous Regressors and Selection 11 Flexible Methods for Counts 12 Bayesian Methods for counts 13 Measurement Errors References Author Index Subject Index