Econometric Analysis of Count DataThe “count data” ?eld has further ?ourished since the previous edition of this book was published in 2003. The development of new methods has not slowed down by any means, and the application of existing ones in applied work has expanded in many areas of social science research. This, in itself, would be reason enough for updating the material in this book, to ensure that it continues to provide a fair representation of the current state of research. In addition, however, I have seized the opportunity to undertake some major changes to the organization of the book itself. The core material on cross-section models for count data is now presented in four chapters, rather than in two as previously. The ?rst of these four chapters introduces the Poissonregressionmodel,anditsestimationbymaximumlikelihoodorpseudo maximum likelihood. The second focuses on unobserved heterogeneity, the third on endogeneity and non-random sample selection. The fourth chapter provides an extended and uni?ed discussion of zeros in count data models. This topic deserves, in my view, special emphasis, as it relates to aspects of modeling and estimation that are speci?c to counts, as opposed to general exponential regression models for non-negative dependent variables. Count distributions put positive probability mass on single o- comes, and thus o?er a richer set of interesting inferences. |
Contents
| 1 | |
Poisson Regression | 63 |
4 | 127 |
Sample Selection and Endogeneity | 143 |
Zeros in Count Data Models | 173 |
Correlated Count Data | 203 |
Bayesian Analysis of Count Data | 241 |
Applications | 251 |
A Probability Generating Functions | 281 |
Software 289 | 288 |
| 299 | |
| 321 | |
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Common terms and phrases
alternative application assumption asymptotic bivariate censoring Chap conditional distribution conditional expectation correlation count data distribution count data models covariance matrix density function dependent variable derive discussed distribution function E(yx Econometrics Economics endogenous example exogeneity exp(x exp(x'ẞ explanatory variables exponential family fixed effects gamma distribution given Gurmu hurdle model hurdle Poisson independent integer job changes joint distribution Journal likelihood function linear model log-likelihood function marginal distribution marginal probability maximum likelihood estimator mean function method mixture models multivariate negative binomial distribution negative binomial model non-negative normal distribution number of events number of job observed obtained outcome overdispersion Poisson distribution Poisson model Poisson process Poisson regression model Poisson-log-normal model probability function probability generating function quantile random variable regressors restrictions sample Santos Silva simulation standard errors Statistics Trivedi truncated underdispersion unobserved heterogeneity variance function vector Winkelmann zero
Popular passages
Page 318 - Winkelmann, R. and KF Zimmermann (1995), Recent Developments in Count Data Modeling: Theory and Applications, Journal of Economic Surveys 9,1- 24.
Page 302 - Medicine 20, 3667-3676. van den Broek, J. (1995). A score test for zero inflation in a Poisson distribution.
References to this book
Univariate Discrete Distributions Norman L. Johnson,Adrienne W. Kemp,Samuel Kotz Limited preview - 2005 |
Multivariate Statistical Modelling Based on Generalized Linear Models Ludwig Fahrmeir,Gerhard Tutz No preview available - 2001 |
