Econometric Analysis of Count Data - Rilegato

Winkelmann, Rainer

 
9783540673408: Econometric Analysis of Count Data

Sinossi

This text provides graduate students and researchers with an up-to-date survey of econometric and statistical techniques for the analysis of count data, with a focus on regression models. Specialised discrete data probability models are required in order to interpret results in terms of an underlying structural process, and to use the model for predicting the distribution of outcomes. The book starts with a presentation of the benchmark Poisson regression model. Alternative models address unobserved heterogeneity, state dependence, selectivity, endogeneity, underreporting, and clustered sampling. Testing and estimation is discussed, including Bayesian inference. Finally, applications are reviewed in fields such as economics, marketing, sociology, demography, and health sciences.

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Recensione

From the reviews:

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

"Winkleman has published numerous articles on using content models in economics and other social science journals. Because these are both applied and theoretical, he is well suited to write a monograph in this area. This book provides a very useful survey for anyone doing serious research using count data...for those who are doing substantive research using count data, [this book] will prove quite useful."

From the reviews of the fourth edition:

"The main objective of the book is to introduce count models at a graduate level so that these models can be used by students, researchers or interested practitioners. ... For all researchers who are concerned with count data the book offers a very good introduction into this field of research and many examples and interpretations of the results. Therefore, the book provides an excellent starting point for working in this area of applied research." (Herbert S. Buscher, Zentralblatt MATH, Vol. 1032 (7), 2004)

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Altre edizioni note dello stesso titolo

9783540776482: Econometric Analysis of Count Data

Edizione in evidenza

ISBN 10:  3540776486 ISBN 13:  9783540776482
Casa editrice: Springer Nature, 2008
Rilegato