Econometric Analysis of Count Data

Rainer Winkelmann

304 pages, parution le 10/09/2003 (4^eme édition)

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Résumé

Graduate students and researchers are provided with an up-to-date survey of statistical and econometric techniques for the analysis of count data, with a focus on conditional distribution models. Proper count data probability models allow for rich inferences, both with respect to the stochastic count process that generated the data, and with respect to 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 from frequentist and Bayesian perspectives. Finally, applications are reviewed in fields such as economics, marketing, sociology, demography, and health sciences. The fourth edition contains several new sections, for example on nonnested hurdle models, quantile regression and on software. Many other sections have been entirely rewritten and extended.

Introduction
Probability Models for Count Data
Econometric Modeling
Basic Issues
Econometric Modeling
Extensions
Correlated Count Data
Bayesian Analysis of Count Variables
Applications

L'auteur - Rainer Winkelmann

University of Zürich, Switzerland

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Rainer Winkelmann
Parution	10/09/2003
Édition	4^eme édition
Nb. de pages	304
Format	16 x 24
Couverture	Relié
Poids	600g
Intérieur	Noir et Blanc
EAN13	9783540404040