Microeconometrics: Methods and Applications

Microeconometrics: Methods and Applications

A. Colin Cameron Cambridge University Press ISBN: 978-0-521-84805-3
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This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.

Table of Contents

  • Front matter
  • CHAPTER 1 Overview
  • CHAPTER 2 Causaland NoncausalModels
  • CHAPTER 3 Microeconomic Data Structures
  • CHAPTER 4 Linear Models
  • CHAPTER 5 Maximum Likelihood and Nonlinear Least-Squares Estimation
  • CHAPTER 6 Generalized Method of Moments and Systems Estimation
  • CHAPTER 7 Hypothesis Tests
  • CHAPTER 8 Specification Tests and Model Selection
  • CHAPTER 9 Semiparametric Methods
  • CHAPTER 10 Numerical Optimization
  • CHAPTER 11 Bootstrap Methods
  • CHAPTER 12 Simulation-Based Methods
  • CHAPTER 13 Bayesian Methods
  • CHAPTER 14 Binary Outcome Models
  • CHAPTER 15 Multinomial Models
  • CHAPTER 16 Tobit and Selection Models
  • CHAPTER 17 Transition Data: Survival Analysis
  • CHAPTER 18 Mixture Models and Unobserved Heterogeneity
  • CHAPTER 19 Models of Multiple Hazards
  • CHAPTER 20 Models of Count Data
  • CHAPTER 21 Linear Panel Models: Basics
  • CHAPTER 22 Linear Panel Models: Extensions
  • CHAPTER 23 Nonlinear Panel Models
  • CHAPTER 24 Stratified and Clustered Samples
  • CHAPTER 25 Treatment Evaluation
  • CHAPTER 26 Measurement Error Models
  • CHAPTER 27 Missing Data and Imputation
  • Back Matter

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