Econometric Analysis of Count Data
Editorial Reviews
Book Description
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.
Book Info
A graduate-level textbook providing students and researchers with an up-to-date survey of statistical and econometric techniques for the analysis of count data, focusing on regression models. Reviews applications in a variety of fields, from marketing to health sciences. Previous edition not cited.
--This text refers to the
Hardcover
edition.
Econometric Analysis of Count Data,Rainer Winkelmann,Springer,354040404X,Business & Economics,Business / Economics / Finance,Business/Economics,Econometric models,Econometrics,Economics - General,Labor mobility,Statistics,Time-series analysis,Business & Economics / Econometrics
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