Cover......Page 1
Title Page......Page 4
Copyright Page......Page 5
Contents......Page 8
Preface......Page 12
1.1 Panel Data: Some Examples......Page 14
1.2 Why Should We Use Panel Data? Their Benefits and Limitations......Page 17
Note......Page 22
2.1 Introduction......Page 24
2.2 The Fixed Effects Model......Page 25
2.3 The Random Effects Model......Page 27
2.3.1 Fixed vs Random......Page 31
2.4 Maximum Likelihood Estimation......Page 32
2.5 Prediction......Page 33
2.6.1 Example 1: Grunfeld Investment Equation......Page 34
2.6.2 Example 2: Gasoline Demand......Page 36
2.6.3 Example 3: Public Capital Productivity......Page 38
Notes......Page 41
Problems......Page 42
3.2 The Fixed Effects Model......Page 46
3.2.1 Testing for Fixed Effects......Page 47
3.3 The Random Effects Model......Page 48
3.3.1 Monte Carlo Experiment......Page 52
3.4 Maximum Likelihood Estimation......Page 53
3.5 Prediction......Page 55
3.6.1 Example 1: Grunfeld Investment Equation......Page 56
3.6.3 Example 3: Public Capital Productivity......Page 58
Notes......Page 60
Problems......Page 61
4.1 Tests for Poolability of the Data......Page 66
4.1.1 Test for Poolability under u~N(0, igma^2 I_{NT})......Page 67
4.1.2 Test for Poolability under the General Assumption u~N(0,\Omega)......Page 68
4.1.3 Examples......Page 70
4.1.4 Other Tests for Poolability......Page 71
4.2.1 The Breusch-Pagan Test......Page 72
4.2.2 King and Wu, Honda and the Standardized Lagrange Multiplier Tests......Page 74
4.2.4 Conditional LM Tests......Page 75
4.2.5 ANOVA F and the Likelihood Ratio Tests......Page 76
4.2.6 Monte Carlo Results......Page 77
4.2.7 An Illustrative Example......Page 78
4.3 Hausman's Specification Test......Page 79
4.3.1 Example 1: Grunfeld Investment Equation......Page 83
4.3.2 Example 2: Gasoline Demand......Page 84
4.3.4 Example 4: Production Behavior of Sawmills......Page 85
4.3.7 Hausman's Test for the Two-way Model......Page 86
Notes......Page 87
Problems......Page 88
5.1 Heteroskedasticity......Page 92
5.1.1 Testing for Homoskedasticity in an Error Component Model......Page 95
5.2.1 The AR(1) Process......Page 97
5.2.2 The AR(2) Process......Page 99
5.2.3 The AR(4) Process for Quarterly Data......Page 100
5.2.4 The MA(1) Process......Page 101
5.2.5 Unequally Spaced Panels with AR(1) Disturbances......Page 102
5.2.6 Prediction......Page 104
5.2.7 Testing for Serial Correlation and Individual Effects......Page 106
5.2.8 Extensions......Page 116
Problems......Page 117
6.1 The One-way Model......Page 120
6.2 The Two-way Model......Page 121
6.3 Applications and Extensions......Page 122
Problems......Page 124
7.1 Single Equation Estimation......Page 126
7.2 Empirical Example: Crime in North Carolina......Page 129
7.3 System Estimation......Page 134
7.4 The Hausman and Taylor Estimator......Page 137
7.5 Empirical Example: Earnings Equation Using PSID Data......Page 141
7.6 Extensions......Page 143
Problems......Page 146
8.1 Introduction......Page 148
8.2 The Arellano and Bond Estimator......Page 149
8.2.1 Testing for Individual Effects in Autoregressive Models......Page 151
8.2.2 Models with Exogenous Variables......Page 152
8.3 The Arellano and Bover Estimator......Page 155
8.4 The Ahn and Schmidt Moment Conditions......Page 158
8.5 The Blundell and Bond System GMM Estimator......Page 160
8.6 The Keane and Runkle Estimator......Page 161
8.7 Further Developments......Page 163
8.8 Empirical Example: Dynamic Demand for Cigarettes......Page 169
8.9 Further Reading......Page 171
Notes......Page 174
Problems......Page 175
9.2 The Unbalanced One-way Error Component Model......Page 178
9.2.1 ANOVA Methods......Page 180
9.2.2 Maximum Likelihood Estimators......Page 182
9.2.3 Minimum Norm and Minimum Variance Quadratic Unbiased Estimators (MINQUE and MIVQUE)......Page 183
9.3 Empirical Example: Hedonic Housing......Page 184
9.4.1 The Fixed Effects Model......Page 188
9.4.2 The Random Effects Model......Page 189
9.5 Testing for Individual and Time Effects Using Unbalanced Panel Data......Page 190
9.6 The Unbalanced Nested Error Component Model......Page 193
9.6.1 Empirical Example......Page 194
Notes......Page 196
Problems......Page 197
10.1 Measurement Error and Panel Data......Page 200
10.2 Rotating Panels......Page 204
10.3 Pseudo-panels......Page 205
10.4 Alternative Methods of Pooling Time Series of Cross-section Data......Page 208
10.5 Spatial Panels......Page 210
10.6 Short-run vs Long-run Estimates in Pooled Models......Page 213
10.7 Heterogeneous Panels......Page 214
Problems......Page 219
11.1 Fixed and Random Logit and Probit Models......Page 222
11.2 Simulation Estimation of Limited Dependent Variable Models with Panel Data......Page 228
11.3 Dynamic Panel Data Limited Dependent Variable Models......Page 229
11.4 Selection Bias in Panel Data......Page 232
11.5 Censored and Truncated Panel Data Models......Page 237
11.6 Empirical Applications......Page 241
11.7 Empirical Example: Nurses' Labor Supply......Page 242
11.8 Further Reading......Page 244
Notes......Page 247
Problems......Page 248
12.1 Introduction......Page 250
12.2 Panel Unit Roots Tests Assuming Cross-sectional Independence......Page 252
12.2.1 Levin, Lin and Chu Test......Page 253
12.2.2 Im, Pesaran and Shin Test......Page 255
12.2.3 Breitung's Test......Page 256
12.2.4 Combining p-Value Tests......Page 257
12.2.5 Residual-Based LM Test......Page 259
12.3 Panel Unit Roots Tests Allowing for Cross-sectional Dependence......Page 260
12.4 Spurious Regression in Panel Data......Page 263
12.5.1 Residual-Based DF and ADF Tests (Kao Tests)......Page 265
12.5.2 Residual-Based LM Test......Page 266
12.5.3 Pedroni Tests......Page 267
12.5.4 Likelihood-Based Cointegration Test......Page 268
12.5.5 Finite Sample Properties......Page 269
12.6 Estimation and Inference in Panel Cointegration Models......Page 270
12.7 Empirical Example: Purchasing Power Parity......Page 272
12.8 Further Reading......Page 274
Problems......Page 276
References......Page 280
Index......Page 304