Verfügbarkeit: Econometrics :: THWS Bibkatalog

Econometrics:

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Bibliographische Detailangaben
1. Verfasser:	Peracchi, Franco (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Chichester [u.a.] Wiley 2001
Schlagworte:	Econometria Econometrie Econometrics Ökonometrie Lehrbuch
Online-Zugang:	Publisher description Inhaltsverzeichnis
Beschreibung:	Literaturverz. S. [601] - 618
Beschreibung:	XXII, 679 S. graph. Darst.
ISBN:	0471987646

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Datensatz im Suchindex

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adam_text	Contents Preface ........................................ xvii Notation....................................... xix MATHEMATICAL SYMBOLS......................... xix STATISTICAL SYMBOLS........................... xx ABBREVIATIONS ................................ xxi 1 Regression Models.............................. 1 1.1 PARAMETRIC STATISTICAL MODELS................ 2 1.1.1 EXAMPLES OF PARAMETRIC MODELS ........... 3 1.1.2 LOCATION AND SCALE MODELS ............... 7 1.1.3 THE QUANTILE FUNCTION .................. 9 1.1.4 HAZARD RATE MODELS .................... 11 1.1.5 IDENTIFIABILITY ........................ 14 1.1.6 REGULAR PARAMETRIC MODELS .............. 17 1.1.7 EXPONENTIAL FAMILIES ................... 20 1.2 CONDITIONAL PARAMETRIC MODELS ............... 23 1.2.1 CONDITIONING ......................... 23 1.2.2 EXOGENEITY ........................... 24 1.2.3 CONDITIONAL LOCATION AND SCALE MODELS ..... 26 1.2.4 CONDITIONAL PARAMETRIZATIONS ............ 27 1.3 NONPARAMETRIC AND SEMIPARAMETRIC PROBLEMS .... 27 1.3.1 UNCONDITIONAL PREDICTION PROBLEMS ........ 28 1.3.2 CONDITIONAL PREDICTION PROBLEMS ......... 30 1.3.3 MODELS OF THE CONDITIONAL MEAN .......... 32 1.3.4 MODELS OF THE CONDITIONAL VARIANCE ....... 37 1.3.5 MODELS OF CONDITIONAL QUANTILES .......... 39 1.4 STATISTICAL MODELS AS APPROXIMATIONS .......... 40 1.4.1 PARAMETRIC MODELS AS APPROXIMATIONS ...... 40 1.4.2 LINEAR PREDICTION ...................... 42 1.4.3 RELATION BETWEEN THE BLP AND THE CMF ..... 45 BIBLIOGRAPHIC NOTES ........................... 47 PROBLEMS ................................... 47 2 Sampling .................................... 51 2.1 SAMPLING FROM A FINITE POPULATION ............. 51 2.1.1 SRS WITH REPLACEMENT .................. 52 2.1.2 SRS WITHOUT REPLACEMENT ................ 53 2.1.3 UNEQUAL PROBABILITY SAMPLING ............ 54 2.1.4 STRATIFIED SAMPLING .................... 55 2.1.5 OPTIMAL SAMPLE ALLOCATION .............. 57 2.2 SAMPLING FROM AN INFINITE POPULATION .......... 58 2.2.1 PROPERTIES OF THE SAMPLE MEAN AND VARIANCE . 59 2.2.2 THE EMPIRICAL DISTRIBUTION FUNCTION ....... 60 2.3 SELECTIVE SAMPLING ......................... 63 2.3.1 CENSORED AND TRUNCATED SAMPLING ......... 64 2.3.2 THE KAPLAN-MEIER ESTIMATOR ............. 67 2.3.3 BOUNDS ON THE REGRESSION FUNCTION UNDER CENSORING ............................ 69 2.3.4 RESPONSE-BASED SAMPLING ................ 71 2.3.5 FLOW AND STOCK SAMPLING ................ 72 2.4 UNOBSERVED HETEROGENEITY AND MIXTURE MODELS . . 73 2.5 MEASUREMENT ERRORS ....................... 75 2.5.1 THE CLASSICAL MEASUREMENT ERROR MODEL .... 76 2.5.2 OTHER MEASUREMENT ERROR MODELS ......... 77 2.5.3 CONTAMINATED SAMPLING ................. 78 BIBLIOGRAPHIC NOTES ........................... 79 PROBLEMS ................................... 80 Time Series ................................... 83 3.1 UNIVARIATE TIME SERIES ...................... 83 3.1.1 STOCHASTIC PROCESSES ................... 83 3.1.2 STATIONARITY ......................... 86 3.1.3 AUTOCOVARIANCES AND AUTOCORRELATIONS .... 88 3.1.4 STABILITY AND INVERTIBILITY ............... 96 3.1.5 PREDICTION ........................... 98 3.1.6 THE LAG OPERATOR ...................... 100 3.1.7 GENERATING FUNCTIONS .................. 101 3.1.8 LINEAR PROCESSES ...................... 102 3.1.9 THE SPECTRAL DENSITY ................... 104 3.2 ARMA PROCESSES ............................ 107 3.2.1 STATIONARITY, STABILITY AND INVERTIBILITY .... 109 3.2.2 PREDICTION ........................... 112 3.2.3 ARMA- ARCH PROCESSES ................... 114 3.3 MULTIVARIATE TIME SERIES ..................... 117 3.3.1 STATIONARITY AND AUTOCOVARIANCES ........ 117 3.3.2 MULTIVARIATE ARMA PROCESSES ............. 120 3.3.3 IMPULSE RESPONSE ANALYSIS ............... 122 3.3.4 GRANGER NONCAUSALITY .................. 123 3.3.5 EXOGENEITY ........................... 125 3.4 MODELS FOR NONSTATIONARY TIME SERIES .......... 126 3.4.1 DETERMINISTIC COMPONENT MODELS .......... 126 3.4.2 INTEGRATED PROCESSES ................... 128 3.4.3 COINTEGRATION ........................ 132 BIBLIOGRAPHIC NOTES ........................... 134 PROBLEMS ................................... 135 Point Estimation ............................... 139 4.1 THE ANALOGY PRINCIPLE ...................... 139 4.2 ESTIMATING MOMENTS AND QUANTILES ............. 140 4.2.1 SAMPLE MOMENTS ....................... 140 4.2.2 ESTIMATING THE MOMENTS OF A STATIONARY TIME SERIES ............................... 141 4.2.3 THE METHOD OF MOMENTS ................. 145 4.2.4 SAMPLE QUANTILES ...................... 147 4.3 ESTIMATING CONDITIONAL MOMENTS AND QUANTILES ... 151 4.3.1 NONPARAMETRIC METHODS ................. 151 4.3.2 PARAMETRIC METHODS ................... 152 4.3.3 ORDINARY LEAST SQUARES ................. 154 4.4 MAXIMUM LIKELIHOOD ESTIMATION ............... 156 4.4.1 ML ESTIMATES .......................... 156 4.4.2 LIKELIHOOD EQUATIONS AND LOCAL ML ESTIMATES 162 4.5 MINIMUM VARIANCE UNBIASEDNESS ............... 164 4.5.1 SUFFICIENCY . ,......................... 165 4.5.2 THE CRAMÉR-RAO BOUND .................. 167 4.6 ASYMPTOTIC PROPERTIES OF ML ESTIMATORS ........ 169 4.6.1 CONSISTENCY .......................... 169 4.6.2 ASYMPTOTIC NORMALITY .................. 170 4.7 BAYES METHODS ............................ 172 4.7.1 BAYES THEOREM ........................ 172 4.7.2 CONJUGATE PRIORS ...................... 174 4.7.3 DIFFUSE PRIORS ........................ 175 4.7.4 THE BINOMIAL MODEL .................... 176 4.7.5 BAYES POINT ESTIMATES ................... 178 4.7.6 THE GAUSSIAN LOCATION MODEL ............. 179 4.8 STATISTICAL DECISION PROBLEMS ................. 181 4.8.1 STATISTICAL GAMES ...................... 181 4.8.2 THE MINIMAX AND BAYES PRINCIPLES .......... 182 4.8.3 THE COMPLETE CLASS THEOREM ............. 185 BIBLIOGRAPHIC NOTES ........................... 186 PROBLEMS ................................... 187 Statistical Accuracy and Hypothesis Testing ............. 191 5.1 ASSESSING VARIABILITY AND BIAS ................. 191 5.1.1 ASSESSING VARIABILITY ................... 191 5.1.2 THE NONPARAMETRIC BOOTSTRAP ............ 193 5.1.3 THE PARAMETRIC BOOTSTRAP ............... 195 5.1.4 JACKKNIFE ESTIMATES OF VARIANCE .......... 195 5.1.5 ASSESSING BIAS ......................... 196 5.2 CONFIDENCE SETS ........................... 197 5.2.1 CLASSICAL CONFIDENCE SETS ............... 198 5.2.2 BOOTSTRAP CONFIDENCE INTERVALS .......... 200 5.2.3 BAYESIAN CONFIDENCE SETS ................ 201 5.3 HYPOTHESIS TESTING ......................... 202 5.3.1 STATISTICAL TESTS ...................... 203 5.3.2 DUALITY BETWEEN CONFIDENCE SETS AND CRITI¬ CAL REGIONS .......................... 206 5.3.3 OPTIMALITY IN TESTING ................... 207 5.3.4 THE NEYMAN-PEARSON THEOREM ............ 209 5.3.5 COMPOSITE ALTERNATIVES ................. 210 5.4 LIKELIHOOD-BASED TESTS ...................... 211 5.4.1 THE LIKELIHOOD RATIO PRINCIPLE ............ 212 5.4.2 THE WALD PRINCIPLE ..................... 214 5.4.3 THE SCORE PRINCIPLE .................... 214 5.4.4 PARTITIONED PARAMETERS ................. 215 5.4.5 SAMPLING DISTRIBUTION .................. 216 5.4.6 BOOTSTRAP HYPOTHESIS TESTING ............ 218 5.5 BAYESIAN HYPOTHESIS TESTING .................. 219 5.5.1 SIMPLE HYPOTHESES ..................... 220 5.5.2 COMPOSITE HYPOTHESES .................. 221 5.5.3 MULTIPLE HYPOTHESES ................... 222 BIBLIOGRAPHIC NOTES ........................... 222 PROBLEMS ................................... 223 6 The Classical Linear Model: Estimation ................ 225 6.1 ELEMENTS OF A LINEAR REGRESSION MODEL ......... 225 6.1.1 TYPES OF COVARIATE ..................... 226 6.1.2 EQLTVARIANCE PROPERTIES ................ 228 6.2 ORDINARY LEAST SQUARES ..................... 229 6.2.1 THE OLS ESTIMATE ....................... 229 6.2.2 GEOMETRIC INTERPRETATION ............... 230 6.2.3 FITTED VALUES AND RESIDUALS .............. 232 6.2.4 GOODNESS-OF-FIT AND EQUIVARIANCE PROPERTIES . 232 { 6.2.5 MULTIVARIATE OLS ...................... 234 6.2.6 PARTITIONED REGRESSION ................. 235 6.2.7 ADDING AND EXCLUDING OBSERVATIONS ........ 237 6.3 SAMPLING PROPERTIES OF THE OLS ESTIMATOR ....... 239 6.3.1 THE CLASSICAL LINEAR MODEL .............. 239 6.3.2 STOCHASTIC REGRESSORS .................. 241 6.3.3 ESTIMATES OF PRECISION .................. 242 6.4 THE GAUSSIAN LINEAR MODEL ................... 243 6.4.1 SAMPLING DISTRIBUTION^ OF THE OLS ESTIMATOR . . 243 6.4.2 THE GAUSSIAN ML ESTIMATOR ............... 244 6.4.3 MINIMUM VARIANCE UNBIASED ESTIMATION ...... 245 6.4.4 CONFIDENCE SETS ....................... 246 6.5 CONSTRAINED OLS ........................... 247 6.6 BAYESIAN ESTIMATORS ........................ 251 6.6.1 UNINFORMATIVE PRIORS................... 251 6.6.2 CONJUGATE PRIORS...................... 252 6.7 SHRINKAGE ESTIMATORS ....................... 254 6.7.1 STEIN ESTIMATORS ....................... 254 6.7.2 JAMES-STEIN ESTIMATORS ................. 255 BIBLIOGRAPHIC NOTES ........................... 258 PROBLEMS ................................... 258 7 Violations of the Ideal Conditions for OLS ............... 263 7.1 COLLINEARITY .............................. 263 7.1.1 QUASI-COLLINEARITY ..................... 264 7.1.2 RIDGE-REGRESSION ESTIMATORS ............. 266 7.2 MISSPECIFICATION OF THE REGRESSION FUNCTION ..... 267 7.3 MISSPECIFICATION OF THE VARIANCE FUNCTION ....... 270 7.3.1 PURE HETEROSKEDASTICITY ................ 271 7.3.2 AUTOCORRELATION ...................... 272 7.3.3 SEEMINGLY UNRELATED REGRESSION EQUATIONS . . 275 7.4 GENERALIZED LEAST SQUARES ................... 276 7.4.1 AITKEN THEOREM ....................... 276 7.4.2 FEASIBLE GLS ESTIMATORS ................. 280 7.5 ESTIMATING THE PRECISION OF OLS ............... 281 7.5.1 HETEROSKEDASTICITY .................... 281 7.5.2 AUTOCORRELATION ...................... 283 7.6 NON-NORMALITY ............................ 284 7.6.1 EFFICIENCY OF OLS ...................... 284 7.6.2 TRANSFORMATIONS OF THE RESPONSE rARIABLE . . 285 BIBLIOGRAPHIC NOTES ........................... 288 PROBLEMS ................................... 289 8 Diagnostics Based on the OLS Estimates ................ 291 8.1 OLS RESIDUALS ............................. 292 8.2 TRANSFORMATIONS OF THE OLS RESIDUALS .......... 297 8.2.1 PREDICTED RESIDUALS .................... 299 8.2.2 STUDENTIZED RESIDUALS .................. 299 8.2.3 LUS AND BLUS RESIDUALS .................. 300 8.2.4 RECURSIVE RESIDUALS .................... 301 8.3 INFLUENCE AND LEVERAGE ..................... 303 BIBLIOGRAPHIC NOTES ........................... 305 PROBLEMS ................................... 305 9 The Classical Linear Model: Hypothesis Testing ........... 307 9.1 THE CLASSICAL t- AND F-TESTS .................. 307 9.1.1 THEi-TEST ............................ 307 9.1.2 THE F-TEST ........................... 309 9.1.3 RELATIONS WITH LIKELIHOOD-BASED TESTS ...... 314 9.1.4 CLASSICAL PRE-TEST ESTIMATION ............ 316 9.2 SPECIFICATION TESTS ......................... 319 9.2.1 RESET............................... 319 9.2.2 THE DIFFERENCE TEST .................... 320 9.2.3 RELATIONS WITH THE CLASSICAL TESTS ........ 323 9.2.4 THE DURBIN-WATSON TEST ................. 324 9.3 CLASSICAL MODEL SELECTION CRITERIA ............ 326 9.3.1 R2 AND ADJUSTED R2 ..................... 326 9.3.2 THE Cp PROCEDURE ...................... 328 9.3.3 CROSS-VALIDATION ....................... 330 9.3.4 INFORMATION CRITERIA ................... 331 9.4 BAYESIAN HYPOTHESIS TESTING .................. 334 BIBLIOGRAPHIC NOTES ........................... 336 PROBLEMS ................................... 336 10 Asymptotic Properties of Least Squares Methods .......... 339 10.1 CONSISTENCY OF THE OLS ESTIMATOR ............. 339 10.1.1 THE MAIN RESULT ....................... 340 10.1.2 SOME PRIMITIVE ASSUMPTIONS .............. 340 10.1.3 VIOLATIONS OF THE FUNDAMENTAL ASSUMPTION . . 342 10.1.4 TRENDS IN THE COVARIATES ................ 344 10.2 ASYMPTOTIC NORMALITY OF THE OLS ESTIMATOR ..... 346 10.2.1 THE MAIN RESULT ....................... 346 10.2.2 SOME PRIMITIVE ASSUMPTIONS .............. 347 10.2.3 ESTIMATES OF STATISTICAL PRECISION ......... 351 10.3 ASYMPTOTIC PROPERTIES OF THE GLS ESTIMATOR ...... 353 10.4 ASYMPTOTIC PROPERTIES OF t- AND F-TESTS ......... 355 10.4.1 CONSISTENCY .......................... 356 10.4.2 LOCAL ALTERNATIVES .................... 356 10.4.3 NONSCALAR VARIANCE .................... 358 10.4.4 TESTS BASED ON THE OLS CRITERION .......... 359 10.4.5 NONLINEAR CONSTRAINTS .................. 361 10.5 LIKELIHOOD-BASED TESTS ...................... 362 10.5.1 LIKELIHOOD RATIO TESTS .................. 362 10.5.2 WALD TESTS ........................... 362 10.5.3 SCORE TESTS .......................... 363 10.6 TESTING NON-NESTED HYPOTHESES ............... 368 10.6.1 THE COMPREHENSIVE APPROACH ............. 368 10.6.2 THE COX TEST .......................... 369 10.6.3 ENCOMPASSING ......................... 370 10.7 THE INFORMATION MATRIX TEST ................. 371 BIBLIOGRAPHIC NOTES ........................... 373 PROBLEMS ................................... 374 11 The Instrumental Variables Method . .................. 377 11.1 INSTRUMENTAL VARIABLES ESTIMATION ............ 377 11.1.1 THE SIMPLE IV ESTIMATOR ................. 378 11.1.2 THE CLASS OF IV ESTIMATORS ............... 379 11.2 ASYMPTOTIC PROPERTIES OF IV ESTIMATORS ......... 380 11.2.1 CONSISTENCY .......................... 381 11.2.2 ASYMPTOTIC NORMALITY .................. 381 11.2.3 ASYMPTOTIC EFFICIENCY .................. 382 11.2.4 ESTIMATES OF PRECISION .................. 385 11.2.5 THE GENERALIZED 2SLS ESTIMATOR ........... 387 11.3 HYPOTHESIS TESTING ......................... 389 11.3.1 WALD TESTS ........................... 389 11.3.2 TESTS OF OVERIDENTIFYING RESTRICTIONS ...... 389 11.3.3 DIFFERENCE TESTS ...................... 391 11.4 THE GENERALIZED METHOD OF MOMENTS ........... 392 BIBLIOGRAPHIC NOTES ........................... 395 PROBLEMS ................................... 395 12 Linear Models for Panel Data ....................... 397 12.1 THE BASIC MODEL ........................... 398 12.2 THE FIXED EFFECTS MODEL AND THE WITHIN GROUP ESTIMATOR ................................ 399 12.3 THE RANDOM EFFECTS MODEL ................... 401 12.3.1 THE GLS AND THE BETWEEN GROUP ESTIMATORS . . 402 12.3.2 TESTING FOR INDIVIDUAL EFFECTS ............ 404 12.3.3 SPECIFICATION TESTS ..................... 406 12.4 UNBALANCED PANELS ......................... 407 12.5 MINIMUM DISTANCE ESTIMATION ................. 409 12.6 IV ESTIMATION ............................. 413 12.6.1 ASYMPTOTICALLY EFFICIENT IV ESTIMATION ..... 414 12.6.2 CHOICE OF INSTRUMENTS .................. 417 12.6.3 AUTOREGRESSIVE MODELS FOR PANEL DATA ..... 419 12.7 TIME SERIES OF REPEATED CROSS-SECTIONS .......... 420 BIBLIOGRAPHIC NOTES ........................... 422 PROBLEMS ................................... 422 13 Linear Simultaneous Equation Models ................. 425 13.1 THE STATISTICAL PROBLEM ..................... 425 13.2 IDENTIFIABILITY ............................ 426 13.2.1 CONDITIONS FOR IDENTIFIABILITY: FIRST METHOD . 427 13.2.2 SEPARABLE CONSTRAINTS .................. 429 13.2.3 NORMALIZATION AND EXCLUSION CONSTRAINTS ... 429 13.2.4 CONDITIONS FOR IDENTIFIABILITY: SECOND METHOD 430 13.3 SINGLE EQUATION ESTIMATION .................. 431 13.3.1 OLS ESTIMATION ........................ 432 13.3.2 IV ESTIMATION ......................... 433 13.4 SYSTEM ESTIMATION ......................... 434 13.4.1 IV ESTIMATION ......................... 435 13.4.2 MINIMUM DISTANCE ESTIMATION ............. 437 BIBLIOGRAPHIC NOTES ........................... 439 PROBLEMS ................................... 439 14 Nonparametric Methods .......................... 443 14.1 DENSITY ESTIMATION ......................... 443 14.1.1 EMPIRICAL DENSITIES ..................... 443 14.1.2 THE KERNEL METHOD .................... 447 14.2 STATISTICAL PROPERTIES OF THE KERNEL METHOD ..... 452 14.2.1 LOCAL PROPERTIES ...................... 452 14.2.2 GLOBAL PROPERTIES ..................... 453 14.2.3 OPTIMAL CHOICE OF BANDWIDTH AND KERNEL FUNCTION ............................ 454 14.2.4 AUTOMATIC BANDWIDTH SELECTION .......... 455 14.2.5 ASYMPTOTIC PROPERTIES .................. 457 14.3 OTHER METHODS FOR DENSITY ESTIMATION .......... 460 14.3.1 THE NEAREST NEIGHBOR METHOD ............ 460 14.3.2 THE MAXIMUM PENALIZED LIKELIHOOD METHOD . . 461 14.4 REGRESSION SMOOTHERS ...................... 462 14.4.1 REGRESSION SPLINES ..................... 463 14.4.2 THE KERNEL METHOD .................... 467 14.4.3 THE NEAREST NEIGHBOR METHOD ............ 469 14.4.4 SMOOTHING SPLINES AND PENALIZED LS ........ 471 14.5 STATISTICAL PROPERTIES OF LINEAR SMOOTHERS ...... 473 14.5.1 MEASURES OF ACCURACY .................. 473 14.5.2 EQUIVALENT KERNELS AND EQUIVALENT DEGREES OF FREEDOM ........................... 474 14.5.3 ASYMPTOTIC PROPERTIES OF KERNEL REGRESSION ESTIMATORS ........................... 475 14.5.4 TESTS OF PARAMETRIC MODELS .............. 477 14.6 OTHER METHODS FOR HIGH-DIMENSIONAL DATA ....... 478 14.6.1 THE CURSE OF DIMENSIONALITY PROBLEM ...... 478 14.6.2 PROJECTION PURSUIT DENSITY ESTIMATION ..... 479 14.6.3 PROJECTION PURSUIT REGRESSION ESTIMATION ... 480 14.6.4 ADDITIVE REGRESSION .................... 481 BIBLIOGRAPHIC NOTES ........................... 484 PROBLEMS ................................... 485 15 M-Estimators ................................. 489 15.1 THE CLASS OF M-ESTIMATORS ................... 489 15.2 CONSISTENCY .............................. 490 15.2.1 SUFFICIENT CONDITIONS FOR CONSISTENCY ...... 490 15.2.2 CONDITIONS FOR UNIFORM CONVERGENCE IN PROB¬ ABILITY .............................. 493 15.3 ASYMPTOTIC NORMALITY ...................... 495 15.3.1 THE STANDARD CASE ..................... 495 15.3.2 ONE-STEP M-ESTIMATORS .................. 497 15.3.3 ASYMPTOTIC NORMALITY UNDER NONSTANDARD CONDITIONS ........................... 498 15.4 ROBUSTNESS ............................... 503 15.4.1 QUALITATIVE AND QUANTITATIVE ROBUSTNESS ... 504 15.4.2 THE INFLUENCE FUNCTION ................. 504 15.4.3 B-ROBUSTNESS ......................... 507 15.4.4 THE INFLUENCE FUNCTION OF M-ESTIMATORS .... 508 15.4.5 ASYMPTOTIC EFFICIENCY .................. 510 15.4.6 OPTIMAL B-ROBUST ESTIMATORS ............. 511 15.4.7 THE BREAKDOWN POINT ................... 516 BIBLIOGRAPHIC NOTES ........................... 516 PROBLEMS ................................... 517 16 Adaptive and Robust Regression Estimators ............. 519 16.1 ADAPTIVE ESTIMATORS ........................ 519 16.1.1 PARTIALLY ADAPTIVE ESTIMATORS ............ 519 16.1.2 FULLY ADAPTIVE ESTIMATORS ............... 521 16.2 QUANTILE REGRESSION ........................ 521 16.2.1 DEFINITIONS AND ALGEBRAIC PROPERTIES ...... 522 16.2.2 COMPUTATIONAL ASPECTS ................. 523 16.2.3 ROBUSTNESS PROPERTIES .................. 524 16.2.4 ASYMPTOTIC DISTRIBUTION ................ 525 16.2.5 SOME DRAWBACKS OF ALAD ESTIMATORS ....... 526 16.3 ROBUST ESTIMATORS ......................... 527 16.3.1 HUBER ESTIMATOR OF REGRESSION ........... 527 16.3.2 OPTIMAL BOUNDED INFLUENCE ESTIMATORS ..... 529 16.3.3 COMPUTATIONAL ASPECTS ................. 530 16.3.4 HIGH-BREAKDOWN ESTIMATORS .............. 531 BIBLIOGRAPHIC NOTES ........................... 532 PROBLEMS ................................... 533 17 Models for Discrete Responses ...................... 535 17.1 MODELS FOR BINARY RESPONSES ................. 535 17.1.1 BINOMIAL REGRESSION MODELS .............. 535 17.1.2 ML ESTIMATION ......................... 537 17.1.3 ASYMPTOTIC PROPERTIES OF ML ESTIMATORS .... 539 17.1.4 THE LOGIT LINK ........................ 540 17.1.5 DISCRIMINANT ANALYSIS AND LOGIT ........... 541 17.1.6 OTHER LINKS .......................... 543 17.1.7 GROUPED DATA ......................... 543 17.1.8 UNOBSERVED HETEROGENEITY .............. 544 17.1.9 SEMIPARAMETRIC ESTIMATION .............. 546 17.2 MODELS FOR MULTINOMIAL RESPONSES ............. 549 17.2.1 THE MULTINOMIAL LOG-LIKELIHOOD ........... 550 17.2.2 ORDERED CATEGORICAL RESPONSES ........... 552 17.2.3 MULTINOMIAL LOGIT ..................... 553 17.2.4 NESTED LOGIT .......................... 554 17.2.5 MULTINOMIAL CHOICE MODELS .............. 555 17.2.6 THE METHOD OF SIMULATED MOMENTS ......... 556 17.3 PANEL DATA MODELS ......................... 559 17.3.1 THE FIXED EFFECTS APPROACH .............. 559 17.3.2 THE RANDOM EFFECTS APPROACH ............ 561 17.4 GENERALIZED LINEAR MODELS ................... 562 17.4.1 ONE-PARAMETER EXPONENTIAL FAMILIES ....... 562 17.4.2 ELEMENTS OF A GLM ..................... 565 17.5 ESTIMATION OF A GLM ........................ 566 17.5.1 ML ESTIMATION ......................... 566 17.5.2 RESIDUALS AND DIAGNOSTICS ............... 568 17.5.3 LEAST SQUARES ESTIMATION ................ 570 17.5.4 PSEUDO ML METHODS ..................... 571 17.6 POISSON REGRESSION ......................... 572 BIBLIOGRAPHIC NOTES ........................... 575 PROBLEMS ................................... 576 18 Models for Truncated and Censored Data ............... 577 18.1 DISTRIBUTION AND MOMENTS OF TRUNCATED AND CEN¬ SORED DATA ............................... 577 18.1.1 TRUNCATED DATA ....................... 578 18.1.2 CENSORED DATA ........................ 579 18.2 THE ROY MODEL ............................ 581 18.3 LEAST SQUARES ESTIMATION .................... 584 18.3.1 OLS ESTIMATION ........................ 584 18.3.2 NONLINEAR LEAST SQUARES ................ 586 18.3.3 TWO-STEP ESTIMATION .................... 586 18.4 ML ESTIMATION ............................. 587 18.4.1 GAUSSIAN ML ESTIMATORS ................. 588 18.4.2 AN ALTERNATIVE PARAMETRIZATION .......... 589 18.4.3 NONGAUSSIAN ML ESTIMATORS .............. 591 18.5 SEMIPARAMETRIC ESTIMATION ................... 591 18.5.1 SEMIPARAMETRIC LEAST SQUARES ............ 592 18.5.2 QUANTILE RESTRICTIONS .................. 593 18.5.3 SYMMETRY RESTRICTIONS .................. 594 18.6 DIVARIATE MODELS .......................... 595 18.6.1 TYPE-2 TOBIT MODELS .................... 596 18.6.2 TYPE-3 TOBIT MODELS .................... 598 ¿ BIBLIOGRAPHIC NOTES ........................... 599 PROBLEMS ................................... 599 References ...................................... 601 Appendix A Review of Linear Algebra .................. . 619 A.I VECTOR SPACES AND LINEAR TRANSFORMATIONS ...... 619 A. 2 MATRICES AND MATRIX OPERATIONS ............... 620 A.3 DETERMINANT AND INVERSE OF A MATRIX ........... 621 A.4 RANK AND TRACE OF A MATRIX .................. 622 A.5 EIGENVALUES AND EIGENVECTORS ................ 622 A.6 QUADRATIC FORMS AND DEFINITE MATRICES ......... 623 A.7 PARTITIONED MATRICES ....................... 624 A.8 KRONECKER PRODUCT AND VEC OPERATOR .......... 624 A.9 DIFFERENTIATION OF MATRICES AND VECTORS ........ 625 A. 10 GENERALIZED INVERSES ....................... 626 A. 11 PROJECTION THEOREMS ....................... 627 BIBLIOGRAPHIC NOTES ........................... 629 Appendix В Methods of Numerical Maximization ............ 631 B.I ALGORITHMS ............................... 631 B.2 DIRECT SEARCH METHODS ...................... 632 B.3 NEWTON-TYPE METHODS ...................... 633 B.3.1 NEWTON-RAPHSON ...................... 633 B.3.2 AIETHOD OF SCORING ..................... 634 B.3.3 BHHH ................................ 634 B.3.4 GAUSS-NEWTON ........................ 634 B.4 THE Ελί ALGORITHM .......................... 635 B.5 NUMERICAL DERIVATIVES ...................... 638 BIBLIOGRAPHIC NOTES ........................... 638 Appendix С Review of Probability ...................... 639 C.I CONDITIONAL DISTRIBUTIONS ................... 639 C.2 CONDITIONAL EXPECTATIONS ................... 640 C.3 STOCHASTIC INEQUALITIES ..................... 642 C.4 MOMENT GENERATING AND CHARACTERISTIC FUNCTIONS 642 C.5 THE GAMMA AND BETA DISTRIBUTIONS ............. 645 C.6 DISTRIBUTIONS RELATED TO THE EXPONENTIAL ....... 647 C.7 DISTRIBUTIONS RELATED TO THE GAUSSIAN .......... 651 C.8 QUADRATIC FORMS IN GAUSSIAN RANDOM VARIABLES ... 655 C.9 MOMENTS OF THE TRUNCATED GAUSSIAN DISTRIBUTION . 655 BIBLIOGRAPHIC NOTES ........................... 656 Appendix D Elements of Asymptotic Theory ............... 657 D.I CONVERGENCE OF SEQUENCES OF RANDOM VARIABLES . . 657 D.2 WEAK CONVERGENCE ......................... 658 D.3 ORDERS IN PROBABILITY ....................... 660 D.4 LAWS OF LARGE NUMBERS ...................... 662 D.5 CENTRAL LIMIT THEOREMS ..................... 663 D.6 CONVERGENCE OF SEQUENCES OF TRANSFORMED RANDOM VARIABLES ................................ 665 D.7 THE ASYMPTOTIC DELTA METHOD ................ 667 D.8 THE FUNCTIONAL CENTRAL LIMIT THEOREM ......... 668 BIBLIOGRAPHIC NOTES ........................... 670 Index ......................................... 671
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spelling	Peracchi, Franco Verfasser aut Econometrics Franco Peracchi Chichester [u.a.] Wiley 2001 XXII, 679 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. [601] - 618 Econometria larpcal Econometrie gtt Econometrics Ökonometrie (DE-588)4132280-0 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Ökonometrie (DE-588)4132280-0 s DE-604 http://www.loc.gov/catdir/description/wiley031/00043915.html Publisher description Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008846361&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Peracchi, Franco Econometrics Econometria larpcal Econometrie gtt Econometrics Ökonometrie (DE-588)4132280-0 gnd
subject_GND	(DE-588)4132280-0 (DE-588)4123623-3
title	Econometrics
title_auth	Econometrics
title_exact_search	Econometrics
title_full	Econometrics Franco Peracchi
title_fullStr	Econometrics Franco Peracchi
title_full_unstemmed	Econometrics Franco Peracchi
title_short	Econometrics
title_sort	econometrics
topic	Econometria larpcal Econometrie gtt Econometrics Ökonometrie (DE-588)4132280-0 gnd
topic_facet	Econometria Econometrie Econometrics Ökonometrie Lehrbuch
url	http://www.loc.gov/catdir/description/wiley031/00043915.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008846361&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT peracchifranco econometrics

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