Chapter 5
MODEL CHOICE AND SPECIFICATION ANALYSIS
EDWARD E. LEAMER*
University of California, Los Angeles
Contents
1. Introduction 286
2. Model selection with prior distributions 288
2. I. Hypothesis testing searches 289
2.2. Interpretive searches 296
3. Model selection with loss functions 304
3.1. Model selection with quadratic loss 306
3.2. Simplification searches: Model selection with fixed costs 311
3.3. Ridge regression 313
3.4. Inadmissibility 313
4. Proxy searches: Model selection with measurement errors 314
5. Model selection without a true model 315
6. Data-instigated models 317
7. Miscellaneous topics 320
7. I. Stepwise regression 320
7.2. Cross-validation 320
7.3. Goodness-of-fit tests 324
8. Conclusion 325
References 325

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