Panel Data Econometrics with R

Table of contents

1. Cover
2. Dedication
3. Preface
4. Acknowledgments
5. About the Companion Website
6. Chapter 1: Introduction
   1. 1.1 Panel Data Econometrics: A Gentle Introduction
   2. 1.2 R for Econometric Computing
   3. 1.3 plm for the Casual R User
   4. 1.4 plm for the Proficient R User
   5. 1.5 plm for the R Developer
   6. 1.6 Notations
7. Chapter 2: The Error Component Model
   1. 2.1 Notations and Hypotheses
   2. 2.2 Ordinary Least Squares Estimators
   3. 2.3 The Generalized Least Squares Estimator
   4. 2.4 Comparison of the Estimators
   5. 2.5 The Two‐ways Error Components Model
   6. 2.6 Estimation of a Wage Equation
8. Chapter 3: Advanced Error Components Models
   1. 3.1 Unbalanced Panels
   2. 3.2 Seemingly Unrelated Regression
   3. 3.3 The Maximum Likelihood Estimator
   4. 3.4 The Nested Error Components Model
9. Chapter 4: Tests on Error Component Models
   1. 4.1 Tests on Individual and/or Time Effects
   2. 4.2 Tests for Correlated Effects
   3. 4.3 Tests for Serial Correlation
   4. 4.4 Tests for Cross‐sectional Dependence
10. Chapter 5: Robust Inference and Estimation for Non‐spherical Errors
    1. 5.1 Robust Inference
    2. 5.2 Unrestricted Generalized Least Squares
11. Chapter 6: Endogeneity
    1. 6.1 Introduction
    2. 6.2 The Instrumental Variables Estimator
    3. 6.3 Error Components Instrumental Variables Estimator
    4. 6.4 Estimation of a System of Equations
    5. 6.5 More Empirical Examples
12. Chapter 7: Estimation of a Dynamic Model
    1. 7.1 Dynamic Model and Endogeneity
    2. 7.2 GMM Estimation of the Differenced Model
    3. 7.3 Generalized Method of Moments Estimator in Differences and Levels
    4. 7.4 Inference
    5. 7.5 More Empirical Examples
13. Chapter 8: Panel Time Series
    1. 8.1 Introduction
    2. 8.2 Heterogeneous Coefficients
    3. 8.3 Cross‐sectional Dependence and Common Factors
    4. 8.4 Nonstationarity and Cointegration
14. Chapter 9: Count Data and Limited Dependent Variables
    1. 9.1 Binomial and Ordinal Models
    2. 9.2 Censored or Truncated Dependent Variable
    3. 9.3 Count Data
    4. 9.4 More Empirical Examples
15. Chapter 10: Spatial Panels
    1. 10.1 Spatial Correlation
    2. 10.2 Spatial Lags
    3. 10.3 Individual Heterogeneity in Spatial Panels
    4. 10.4 Serial and Spatial Correlation
16. Bibliography
17. Index
18. End User License Agreement