Table of Contents
Preface
1 Introduction
1.1 Panel Data: Some Examples
1.2 Why Should We Use Panel Data? Their Benefits and Limitations
Note
2 The One-way Error Component Regression Model
2.1 Introduction
2.2 The One-way Fixed Effects Model
2.3 The One-way Random Effects Model
2.4 Maximum Likelihood Estimation
2.5 Prediction
2.6 Examples
2.7 Selected Applications
2.8 Computational Note
Notes
Problems
3 The Two-way Error Component Regression Model
3.1 Introduction
3.2 The Two-way Fixed Effects Model
3.3 The Two-way Random Effects Model
3.4 Maximum Likelihood Estimation
3.5 Prediction
3.6 Examples
3.7 Computational Note
Notes
Problems
4 Test of Hypotheses with Panel Data
4.1 Tests for Poolability
4.2 Tests for Individual and Time Effects
4.3 Hausman's Specification Test
4.4 Further Reading
Notes
Problems
5 Heteroskedasticity and Serial Correlation in the Error Component Model
5.1 Heteroskedasticity
5.2 Serial Correlation
5.3 Time-wise Autocorrelated and Cross-sectionally Heteroskedastic Panel Regression
5.4 Further Reading
Notes
Problems
6 Seemingly Unrelated Regressions with Error Components
6.1 The One-way Model
6.2 The Two-way Model
6.3 Applications and Extensions
Problems
7 Simultaneous Equations with Error Components
7.1 Single Equation Estimation
7.2 Empirical Example: Crime in North Carolina
7.3 System Estimation
7.4 The Hausman and Taylor Estimator
7.5 Empirical Example: Earnings Equation Using PSID Data
7.6 Further Reading
Notes
Problems
8 Dynamic Panel Data Models
8.1 Introduction
8.2 The Arellano and Bond Estimator
8.3 The Arellano and Bover Estimator
8.4 The Ahn and Schmidt Moment Conditions
8.5 The Blundell and Bond System GMM Estimator
8.6 The Keane and Runkle Estimator
8.7 Limited Information Maximum Likelihood
8.8 Further Developments
8.9 Empirical Examples
8.10 Selected Applications
8.11 Further Reading
Notes
Problems
9 Unbalanced Panel Data Models
9.1 Introduction
9.2 The Unbalanced One-way Error Component Model
9.3 Empirical Example: Hedonic Housing
9.4 The Unbalanced Two-way Error Component Model
9.5 Testing for Individual and Time Effects Using Unbalanced Panel Data
9.6 The Unbalanced Nested Error Component Model
Notes
Problems
10 Special Topics
10.1 Measurement Error and Panel Data
10.2 Rotating Panels
10.3 Pseudo Panels
10.4 Short-run versus Long-run Estimates in Pooled Models
10.5 Heterogeneous Panels
10.6 Count Panel Data
Notes
Problems
11 Limited Dependent Variables and Panel Data
11.1 Introduction
11.2 Fixed and Random Logit and Probit Models
11.3 Simulation Estimation of Limited Dependent Variable Models with Panel Data
11.4 Dynamic Panel Data Limited Dependent Variable Models
11.5 Selection Bias in Panel Data
11.6 Censored and Truncated Panel Data Models
11.7 Applications
11.8 Empirical Example: Nurses’ Labour Supply
11.9 Further Reading
Notes
Problems
12 Nonstationary Panels
12.1 Introduction
12.2 Panel Unit Roots Tests Assuming Cross-sectional Independence
12.3 Panel Unit Roots Tests Allowing for Cross-sectional Dependence
12.4 Spurious Regression in Panel Data
12.5 Panel Cointegration Tests
12.6 Estimation and Inference in Panel Cointegration Models
12.7 Empirical Examples
12.8 Further Reading
Notes
Problems
13 Spatial Panel Data Models
13.1 Introduction
13.2 Spatial Error Component Regression Model
13.3 Spatial Lag Panel Data Regression Model
13.4 Forecasts using Panel Data with Spatial Error Correlation
13.5 Panel Unit Root Tests and Spatial Dependence
13.6 Panel Data Tests for Cross-sectional Dependence
13.7 Further Reading
Problems
References
Appendix
Index
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