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Econometric Analysis of Count Data

By: Winkelmann, Rainer [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.Edition: Fifth edition.Description: XVI, 320 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540783893.Subject(s): Statistics | Econometrics | Economics | Econometrics | Statistics for Business/Economics/Mathematical Finance/InsuranceDDC classification: 330.015195 Online resources: Click here to access online
Contents:
Probability Models for Count Data -- Poisson Regression -- Unobserved Heterogeneity -- Sample Selection and Endogeneity -- Zeros in Count Data Models -- Correlated Count Data -- Bayesian Analysis of Count Data -- Applications.
In: Springer eBooksSummary: 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 fifth edition contains several new topics, including copula functions, Poisson regression for non-counts, additional semi-parametric methods, and discrete factor models. Other sections have been reorganized, rewritten, and extended. .
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Item type Current location Call number Status Date due Barcode Item holds
E books E books PK Kelkar Library, IIT Kanpur
Available EBK7185
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Probability Models for Count Data -- Poisson Regression -- Unobserved Heterogeneity -- Sample Selection and Endogeneity -- Zeros in Count Data Models -- Correlated Count Data -- Bayesian Analysis of Count Data -- Applications.

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 fifth edition contains several new topics, including copula functions, Poisson regression for non-counts, additional semi-parametric methods, and discrete factor models. Other sections have been reorganized, rewritten, and extended. .

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