The book provides graduate students and researchers with an up-to-date surveyof 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. Up-to-date survey of econometric and statistical techniques Presentation of theory as well as applications in economics, marketing, sociology INDICE: Introduction.- Probability Models for Count Data.- Econometric Modeling - Basic Issues.- Econometric Modeling - Extensions.- Correlated Count Data.- Bayesian Analysis of Count Variables.- Applications. The complete table of contents can be found on the Internet: www.springer.de
- ISBN: 978-3-540-77648-2
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 320
- Fecha Publicación: 01/04/2008
- Nº Volúmenes: 1
- Idioma: Inglés