Regression Analysis of Count Data.

Cover -- Half-title -- Series-title -- Title -- Copyright -- Dedication -- Contents -- List of Figures -- List of Tables -- Preface -- CHAPTER 1 Introduction -- 1.1 Poisson Distribution -- 1.1.1 Poisson as the "Law of Rare Events" -- 1.1.2 Poisson Process -- 1.1.3 Waiting Time Distributions -- 1.1.4 Binomial Stopped by the Poisson -- 1.2 Poisson Regression -- 1.2.1 Counts Derived from a Point Process -- 1.2.2 Counts Derived from Continuous Data -- 1.2.3 Regression Specification -- 1.3 Examples -- 1.3.1 Health Services -- 1.3.2 Patents -- 1.3.3 Recreational Demand -- 1.3.4 Takeover Bids -- 1.3.5 Bank Failures -- 1.3.6 Accident Insurance -- 1.3.7 Credit Rating -- 1.3.8 Presidential Appointments -- 1.3.9 Criminal Careers -- 1.3.10 Doctoral Publications -- 1.3.11 Manufacturing Defects -- 1.4 Overview of Major Issues -- 1.5 Bibliographic Notes -- CHAPTER 2 Model Specification and Estimation -- 2.1 Introduction -- 2.2 Example and Definitions -- 2.2.1 Example -- 2.2.2 Definitions -- 2.3 Likelihood-Based Models -- 2.3.1 Regularity Conditions -- 2.3.2 Maximum Likelihood -- 2.3.3 Profile Likelihood -- 2.3.4 Misspecified Density -- 2.4 Generalized Linear Models -- 2.4.1 Weighted Linear Least Squares -- 2.4.2 Linear Exponential Family Models -- 2.4.3 LEF with Nuisance Parameter -- 2.4.4 Generalized Linear Models -- 2.4.5 Extensions -- 2.5 Moment-Based Models -- 2.5.1 Estimating Equations -- 2.5.2 Generalized Methods of Moments -- 2.5.3 Optimal GMM -- 2.5.4 Sequential Two-Step Estimators -- 2.6 Testing -- 2.6.1 Likelihood-Based Models -- 2.6.2 General Models -- 2.6.3 Conditional Moment Tests -- 2.7 Derivations -- 2.7.1 General Framework -- 2.7.2 Likelihood-Based Models -- 2.7.3 Generalized Linear Models -- 2.7.4 Moment-Based Models -- 2.7.5 Conditional Moment Tests -- 2.8 Bibliographic Notes -- 2.9 Exercises -- CHAPTER 3 Basic Count Regression.