Econometric analysis of count data

The book provides graduate students and researchers 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

The book 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

This book presents econometric methods for the analysis of event counts. It reviews the recent literature and introduces several new results. While the emphasis is on methods for cross-section data, the modelling of time series and panel count data is discussed as well. Topics include: dependent processes, unobserved heterogeneity, selectivity and endogeneity, underreporting, Bayesian inference. Methodological and practical aspects are combined in an application dealing with the determinants of individual labor mobility

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