Econometric Analysis of Count Data

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Springer Science & Business Media, 2003 - Business & Economics - 304 pages
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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.
 

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Contents

Introduction
1
11 Poisson Regression Model
2
12 Some Thoughts on Methodology
3
13 Examples
4
14 Organization of the Book
6
Probability Models for Count Data
7
22 Poisson Distribution
8
222 Genesis of the Poisson Distribution
12
452 Incidental Censoring
136
453 Incidental Truncation
137
46 Hurdle Count Data Models
138
461 Hurdle Poisson Model
141
462 Marginal Effects
142
463 Hurdle Negative Binomial Model
143
464 Nonnested Hurdle Models
144
465 Unobserved Heterogeneity in Hurdle Models
145

224 Generalizations of the Poisson Process
15
225 Poisson Distribution as a Binomial Limit
16
226 Exponential Interarrival Times
18
227 NonPoissonness
19
23 Further Distributions for Count Data
22
232 Binomial Distribution
27
233 Logarithmic Distribution
29
234 Summary
30
24 Modified Count Data Distributions
33
242 Censoring and Grouping
34
25 Generalizations
35
251 Mixture Distributions
36
252 Compound Distributions
39
253 Birth Process Generalizations
41
254 Katz Family of Distributions
42
255 Linear Exponential Families
44
256 Additive LogDifferenced Probability Models
47
257 Summary
48
261 Distributions for Interarrival Times
49
262 Renewal Processes
52
264 Gamma Count Distribution
53
265 Duration Mixture Models
56
Econometric Modeling Basic Issues
61
312 Ordinary Least Squares and Other Alternatives
63
313 Generalized Linear Model
67
314 Interpretation of the Parameters
68
315 Period at Risk
71
32 Estimation
74
322 PseudoMaximum Likelihood
81
323 Generalized Method of Moments
83
324 Bias Reduction Techniques
85
33 Sources of Misspecification
88
331 Mean Function
89
333 Measurement Error
92
334 Dependent Process
94
336 Simultaneity and Endogeneity
95
337 Underreporting
96
339 Variance Function
97
34 Testing for Misspecification
99
341 Classical Speciftcation Tests
100
342 Regression Based Tests
105
343 GoodnessofFit Tests
106
344 Tests for NonNested Models
107
Econometric Modeling Extensions
113
42 Unobserved Heterogeneity
115
421 Parametric Mixture Models
116
422 Negative Binomial Models
119
423 Semiparametric Mixture Models
124
424 Finite Mixture Models
125
43 Dependent Count Process
127
44 Censoring and Truncation
128
441 Truncated Count Data Models
129
443 Censored Count Data Models
131
444 Grouped Poisson Regression Model
132
451 Bivariate Normal Distribution
133
466 Finite Mixture Versus Hurdle Models
146
467 Correlated Hurdle Models
147
47 ZeroInflated Count Data Models
148
48 Underreporting
151
482 Count Amount Model
153
483 Endogenous Underreporting
154
49 Endogenous Regressors
156
491 Instrumental Variable Estimation
157
492 Simultaneous Equations
159
493 Binary Endogenous Variables
161
494 Mixed DiscreteContinuous Models
165
410 Generalized Variance Models
166
4102 Generalized Poisson Regression
168
4103 Robust Poisson Regression
170
4104 NonParametric Variance Estimation
175
411 Quantile Regression for Count Data
177
Correlated Count Data
181
511 Multivariate Poisson Distribution
183
512 Multivariate Negative Binomial Model
188
513 Multivariate PoissonGamma Mixture Model
190
514 Multivariate PoissonLogNormal Model
191
515 Latent PoissonNormal Model
194
516 MomentBased Methods
195
52 Panel Data Models
197
521 Fixed Effects Poisson Model
198
522 Fixed Effects Negative Binomial Model
203
523 Random Effects Count Data Models
204
524 MomentBased Methods
205
53 TimeSeries Count Data Models
208
Bayesian Analysis of Count Variables
217
61 Bayesian Analysis of the Poisson Model
218
62 A Poisson Model with Underreporting
221
63 Estimation of the Multivariate PoissonLogNormal Model by MCMC
223
64 Estimation of a Random Coefficients Model by MCMC
224
Applications
227
72 Crime
228
74 Health Economics
230
75 Demography
233
76 Marketing and Management
236
77 Labor Mobility
237
771 Economics Models of Labor Mobility
238
772 Previous Literature
239
773 Data and Descriptive Statistics
241
774 Regression Results
245
775 Model Performance
248
776 Marginal Probability Effects
250
777 Structural Inferences
254
Probability Generating Functions
257
GaussHermite Quadrature
261
Software
265
Tables
267
References
275
Authors Index
295
Subject Index
299
Copyright

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Popular passages

Page 293 - Zimmermann (1995), Recent Developments in Count Data Modeling: Theory and Applications, Journal of Economic Surveys 9,1- 24.
Page 278 - Markov Chain Monte Carlo Analysis of Correlated Count Data," Journal of Business and Economic Statistics, 19. 428^35. Cincera, M. (1997), "Patents. R&D. and Technological Spillovers at the Firm Level: Some Evidence from Econometric Count Models for Panel Data.
Page 277 - Medicine 20, 3667-3676. van den Broek, J. (1995). A score test for zero inflation in a Poisson distribution.
Page 278 - A Microeconometric Model of the Demand for Health Care and Health Insurance in Australia," Review of Economic Studies LV: 85- II H\.

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