Handbook of Econometrics, Volume 5 (Handbook of Econometrics)

The Handbook is a definitive reference source and teaching aid for econometricians. It examines models, estimation theory, data analysis and field applications in econometrics. Comprehensive surveys, written by experts, discuss recent developments at a level suitable for professional use by economists, econometricians, statisticians, and in advanced graduate econometrics courses. For more information on the Handbooks in Economics series, please see our home page on http://www.elsevier.nl/locate/hes Front Cover 1 HANDBOOK IN ECONOMETRICS 4 Copyright Page 5 CONTENTS 16 Introduction to the Series 6 Contents of the Handbook 8 Preface to the Handbook 14 References 15 Part 11: NEW DEVELOPMENTS IN THEORETICAL ECONOMETRICS 24 Chapter 52. The Bootstrap 26 Abstract 27 Keywords 27 1. Introduction 28 2. The bootstrap sampling procedure and its consistency 30 3. Asymptotic refinements 39 4. Extensions 55 5. Monte Carlo experiments 80 6. Conclusions 87 Acknowledgements 88 Appendix A. Informal derivation of Equation (3.27) 88 References 90 Chapter 53. Panel Data Models: Some Recent Developments 96 Abstract 98 Keywords 98 1. Introduction 99 2. Linear models with predetermined variables: identification 100 3. Linear models with predetermined variables: estimation 122 4. Nonlinear panel data models 132 5. Conditional maximum likelihood estimation 134 6. Discrete choice models with “fixed” effects 137 7. Tobit-type models with “fixed” effects 139 8. Models with lagged dependent variables 149 9. “Random” effects models 154 10. Concluding remarks 157 References 157 Chapter 54. Interactions-Based Models 164 Abstract 166 Keywords 166 1. Introduction 167 2. Binary choice with social interactions 172 3. Identification: basic issues 185 4. Further topics in identification 202 5. Sampling properties 215 6. Statistical analysis with grouped data 219 7. Evidence 222 8. Summary and conclusions 229 Appendix A 230 References 238 Chapter 55. Duration Models: Specification, Identification and Multiple Durations 248 Abstract 250 Keywords 250 1. Introduction 251 2. Basic concepts and notation 254 3. Some structural models of durations 256 4. The Mixed Proportional Hazard model 261 5. Identification of the MPH model with single-spell data 272 6. The MPH model with multi-spell data 293 7. An informal classification of reduced-form multiple-duration models 298 8. The Multivariate Mixed Proportional Hazard model 304 9. Causal duration effects and selectivity 314 10. Conclusions and recommendations 316 References 320 Part 12: COMPUTATIONAL METHODS IN ECONOMETRICS 328 Chapter 56. Computationally Intensive Methods for Integration in Econometrics 330 Abstract 332 Keywords 332 1. Introduction 333 2. Monte Carlo methods of integral approximation 335 3. Approximate solution of discrete dynamic optimization problems 348 4. Classical simulation estimation of the multinomial probit model 361 5. Univariate latent linear models 373 6. Multivariate latent linear models 385 7. Bayesian inference for a dynamic discrete choice model 405 Appendix A. The full univariate latent linear model 415 Appendix B. The full multivariate latent linear model 422 References 431 Chapter 57. Markov Chain Monte Carlo Methods: Computation and Inference 436 Abstract 437 Keywords 437 1. Introduction 438 2. Classical sampling methods 440 3. Markov chains 443 4. Metropolis–Hastings algorithm 447 5. The Gibbs sampling algorithm 456 6. Sampler performance and diagnostics 462 7. Strategies for improving mixing 463 8. MCMC algorithms in Bayesian estimation 466 9. Sampling the predictive density 490 10. MCMC methods in model choice problems 493 11. MCMC methods in optimization problems 506 12. Concluding remarks 508 References 509 Part 13: APPLIED ECONOMETRICS 518 Chapter 58. Calibration 520 Abstract 521 Keywords 521 1. Introduction 522 2. Calibration: its meaning and some early examples 523 3. The debate about calibration 528 4. Making calibration more concrete 534 5. Best practice in calibration 551 6. New directions in calibration 561 7. Conclusion 565 References 566 Chapter 59. Measurement Error in Survey Data 572 Abstract 574 Keywords 574 1. Introduction 575 2. The impact of measurement error on parameter estimates 577 3. Correcting for measurement error 595 4. Approaches to the assessment of measurement error 607 5. Measurement error and memory: findings from household-based surveys 610 6. Evidence on measurement error in survey reports of labor-related phenomena 615 7. Conclusions 697 References 700 Author Index 712 Subject Index 730