Bootstrap Tests for Regression Models (Palgrave Texts in Econometrics)

✍ Scribed by Leslie Godfrey

• Publisher: Palgrave Macmillan
• Year: 2009
• Tongue: English
• Leaves: 344
• Series: Palgrave Texts in Econometrics
• Category: Library

✦ Synopsis

This volume contains an accessible discussion examining computationally-intensive techniques and bootstrap methods, providing ways to improve the finite-sample performance of well-known asymptotic tests for regression models. The book uses the linear regression model as a framework for introducing simulation-based tests to help perform econometric analyses.

✦ Table of Contents

Cover......Page 1
Contents......Page 8
Preface......Page 12
1.1. Introduction......Page 16
1.2. Tests for the classical linear regression model......Page 18
1.3. Tests for linear regression models under weaker assumptions: random regressors and non-Normal IID errors......Page 25
1.4. Tests for generalized linear regression models......Page 29
1.4.1. HCCME-based tests......Page 33
1.4.2. HAC-based tests......Page 36
1.5. Finite-sample properties of asymptotic tests......Page 40
1.5.1. Testing the significance of a subset of regressors......Page 42
1.5.2. Testing for non-Normality of the errors......Page 46
1.5.3. Using heteroskedasticity-robust tests of significance......Page 48
1.6. Non-standard tests for linear regression models......Page 50
1.7. Summary and concluding remarks......Page 57
2.1. Introduction......Page 59
2.2. Some key concepts and simple examples of tests for IID variables......Page 61
2.2.1. Monte Carlo tests......Page 62
2.2.2. Bootstrap tests......Page 65
2.3.1. The classical Normal model......Page 70
2.3.2. Models with IID errors from an unspecified distribution......Page 74
2.3.3. Dynamic regression models and bootstrap schemes......Page 79
2.3.4. The choice of the number of artificial samples......Page 82
2.4. Asymptotic properties of bootstrap tests......Page 84
2.5. The double bootstrap......Page 87
2.6. Summary and concluding remarks......Page 92
3.1. Introduction......Page 96
3.2. A Monte Carlo test of the assumption of Normality......Page 98
3.3. Simulation-based tests for heteroskedasticity......Page 103
3.3.1. Monte Carlo tests for heteroskedasticity......Page 106
3.3.2. Bootstrap tests for heteroskedasticity......Page 109
3.3.3. Simulation experiments and tests for heteroskedasticity......Page 110
3.4.1. Regression models with strictly exogenous regressors......Page 116
3.4.2. Stable dynamic regression models......Page 124
3.4.3. Some simulation evidence concerning asymptotic and bootstrap F tests......Page 125
3.5. Bootstrapping LM tests for serial correlation in dynamic regression models......Page 133
3.5.1. Restricted or unrestricted estimates as parameters of bootstrap worlds......Page 134
3.5.2. Some simulation evidence on the choice between restricted and unrestricted estimates......Page 138
3.6. Summary and concluding remarks......Page 147
4.1. Introduction......Page 149
4.2.1. Asymptotic analysis for predictive test statistics......Page 151
4.2.2. Single and double bootstraps for predictive tests......Page 154
4.2.3. Simulation experiments and results......Page 159
4.2.4. Dynamic regression models......Page 163
4.3. Using bootstrap methods with a battery of OLS diagnostic tests......Page 164
4.3.1. Regression models and diagnostic tests......Page 166
4.3.2. Bootstrapping the minimum p-value of several diagnostic test statistics......Page 167
4.3.3. Simulation experiments and results......Page 170
4.4. Bootstrapping tests for structural breaks......Page 175
4.4.1. Testing constant coefficients against an alternative with an unknown breakpoint......Page 177
4.4.2. Simulation evidence for asymptotic and bootstrap tests......Page 181
4.5. Summary and conclusions......Page 188
5.1. Introduction......Page 192
5.2. Bootstrap methods for independent heteroskedastic errors......Page 193
5.2.1. Model-based bootstraps......Page 196
5.2.2. Pairs bootstraps......Page 198
5.2.3. Wild bootstraps......Page 200
5.2.4. Estimating function bootstraps......Page 203
5.2.5. Bootstrapping dynamic regression models......Page 205
5.3. Bootstrap methods for homoskedastic autocorrelated errors......Page 208
5.3.1. Model-based bootstraps......Page 209
5.3.2. Block bootstraps......Page 213
5.3.3. Sieve bootstraps......Page 216
5.3.4. Other methods......Page 220
5.4.1. Asymptotic theory tests......Page 222
5.4.2. Block bootstraps......Page 225
5.4.3. Other methods......Page 228
5.5. Summary and concluding remarks......Page 229
6.1. Introduction......Page 233
6.2.1. The forms of test statistics......Page 236
6.2.2. Simulation experiments......Page 241
6.3. Bootstrapping heteroskedasticity-robust autocorrelation tests for dynamic models......Page 246
6.3.1. The forms of test statistics......Page 247
6.3.2. Simulation experiments......Page 250
6.4. Bootstrapping heteroskedasticity-robust structural break tests with an unknown breakpoint......Page 256
6.5.1. The forms of test statistics......Page 262
6.5.2. Simulation experiments......Page 269
6.6. Summary and conclusions......Page 277
7.1. Introduction......Page 281
7.2. Asymptotic tests for models with non-nested regressors......Page 283
7.2.1. Cox-type LLR tests......Page 284
7.2.2. Artificial regression tests......Page 288
7.2.4. Regularity conditions and orthogonal regressors......Page 289
7.2.5. Testing with multiple alternatives......Page 290
7.2.6. Tests for model selection......Page 292
7.2.7. Evidence from simulation experiments......Page 294
7.3.1. One non-nested alternative regression model: significance levels......Page 296
7.3.2. One non-nested alternative regression model: power......Page 304
7.3.3. One non-nested alternative regression model: extreme cases......Page 305
7.3.4. Two non-nested alternative regression models: significance levels......Page 308
7.3.5. Two non-nested alternative regression models: power......Page 310
7.4. Bootstrapping the LLR statistic with non-nested models......Page 312
7.5. Summary and concluding remarks......Page 315
8 Epilogue......Page 318
Bibliography......Page 320
E......Page 334
L......Page 335
U......Page 336
Z......Page 337
B......Page 338
D......Page 339
I......Page 340
O......Page 341
S......Page 342
W......Page 343
Y......Page 344