The econometrics of panel data: fundamentals and recent developments in theory and practice ; with ... 43 tables
Saved in:
| Format: | Book |
|---|---|
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
2008
|
| Edition: | 3. ed. |
| Series: | Advanced studies in theoretical and applied econometrics
46 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis Inhaltstext Inhaltsverzeichnis |
| Physical Description: | XXVI, 950 S. graph. Darst. |
| ISBN: | 9783540758891 |
Staff View
MARC
| LEADER | 00000nam a2200000 cb4500 | ||
|---|---|---|---|
| 001 | BV022395790 | ||
| 003 | DE-604 | ||
| 005 | 20100218 | ||
| 007 | t | ||
| 008 | 070420s2008 gw d||| |||| 00||| eng d | ||
| 015 | |a 06,N02,0877 |2 dnb | ||
| 016 | 7 | |a 97755435X |2 DE-101 | |
| 020 | |a 9783540758891 |9 978-3-540-75889-1 | ||
| 020 | |z 0387257543 |c Gb. : ca. EUR 319.93, sfr 505.50 |9 0-387-25754-3 | ||
| 024 | 3 | |a 9780387257549 | |
| 035 | |a (OCoLC)315725871 | ||
| 035 | |a (DE-599)BVBBV022395790 | ||
| 040 | |a DE-604 |b ger |e rakddb | ||
| 041 | 0 | |a eng | |
| 044 | |a gw |c XA-DE-BE | ||
| 049 | |a DE-355 |a DE-N2 |a DE-703 |a DE-19 |a DE-521 |a DE-20 | ||
| 082 | 0 | |a 330.15195 |2 22//ger | |
| 082 | 0 | |a 330.15195 |2 22/ger | |
| 084 | |a QH 244 |0 (DE-625)141558: |2 rvk | ||
| 084 | |a QH 300 |0 (DE-625)141566: |2 rvk | ||
| 084 | |a 510 |2 sdnb | ||
| 084 | |a 330 |2 sdnb | ||
| 245 | 1 | 0 | |a The econometrics of panel data |b fundamentals and recent developments in theory and practice ; with ... 43 tables |c Lászlo Mátyás ... (ed.) |
| 250 | |a 3. ed. | ||
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 2008 | |
| 300 | |a XXVI, 950 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Advanced studies in theoretical and applied econometrics |v 46 | |
| 650 | 0 | 7 | |a Panelanalyse |0 (DE-588)4173172-4 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Ökonometrie |0 (DE-588)4132280-0 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)4151278-9 |a Einführung |2 gnd-content | |
| 689 | 0 | 0 | |a Panelanalyse |0 (DE-588)4173172-4 |D s |
| 689 | 0 | |5 DE-604 | |
| 689 | 1 | 0 | |a Ökonometrie |0 (DE-588)4132280-0 |D s |
| 689 | 1 | 1 | |a Panelanalyse |0 (DE-588)4173172-4 |D s |
| 689 | 1 | |5 DE-604 | |
| 700 | 1 | |a Mátyás, László |d 1957- |e Sonstige |0 (DE-588)131764632 |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-3-540-75892-1 |
| 830 | 0 | |a Advanced studies in theoretical and applied econometrics |v 46 |w (DE-604)BV000002376 |9 46 | |
| 856 | 4 | 2 | |u http://d-nb.info/985757493/04 |3 Inhaltsverzeichnis |
| 856 | 4 | 2 | |q text/html |u http://deposit.dnb.de/cgi-bin/dokserv?id=2738760&prov=M&dok_var=1&dok_ext=htm |3 Inhaltstext |
| 856 | 4 | 2 | |m OEBV Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015604536&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-015604536 | ||
Record in the Search Index
| _version_ | 1804136455659847680 |
|---|---|
| adam_text | CONTENTS PART I FUNDAMENTALS 1 INTRODUCTION * 3 MARC NERLOVE, PATRICK
SEVESTRE AND PIETRO BALES TR A 1.1* INTRODUCTION* 3 1.2 DATA,
DATA-GENERATING PROCESSES (DGP), AND INFERENCE * 4 1.3 HISTORY AND
DYNAMICS * 8 1.4 * BRIEF REVIEW OF OTHER METHODOLOGICAL DEVELOPMENTS* 13
1.5* CONCLUSION* 21 REFERENCES * 21 FIXED EFFECTS MODELS AND FIXED
COEFFICIENTS MODELS * 23 PIETRO BALES TR A AND JAYALAKSHMI KRISHNAKUMAR
2.1* THE COVARIANCE MODEL: INDIVIDUAL EFFECTS ONLY* 24 2.1.1*
SPECIFICATION * 24 2.1.2* ESTIMATION * 25 2.1.3* INFERENCE* 28 2.2 THE
COVARIANCE MODEL: INDIVIDUAL AND TIME EFFECTS * 29 2.2.1* TIME EFFECTS
ONLY* 29 2.2.2* TIME AND INDIVIDUAL EFFECTS * 30 2.2.3* INFERENCE* 32
2.3 NON-SPHERICAL DISTURBANCES* 33 2.3.1* WHAT VARIANCE*COVARIANCE
STUCTURE?* 33 2.3.2* TWO GENERAL PROPOSITIONS FOR FIXED EFFECTS MODELS*
34 2.3.3* INDIVIDUAL FIXED EFFECTS AND SERIAL CORRELATION* 36 2.3.4*
HETEROSCEDASTICITY IN FIXED EFFECTS MODELS* 38 2.4 EXTENSIONS * 40
2.4.1* CONSTANT VARIABLES IN ONE DIMENSION* 40 2.4.2* VARIABLE SLOPE
COEFFICIENTS * 41 2.4.3* UNBALANCED PANELS * 44 REFERENCES * 48 VII
VIII* CONTENTS 3 ERROR COMPONENTS MODELS * 49 BADI H. BALTAGI, LASZLO
MATYAS AND PATRICK SEVESTRE 3.1* INTRODUCTION* 49 3.2 THE ONE-WAY ERROR
COMPONENTS MODEL* 50 3.2.1* DEFINITION/ASSUMPTIONS OF THE MODEL* 50
3.2.2 THE GLS ESTIMATOR* 52 3.2.3* THE FEASIBLE GLS ESTIMATOR * 55
3.2.4* SOME OTHER ESTIMATORS* 58 3.2.5* PREDICTION* 63 3.3* MORE GENERAL
STRUCTURES OF THE DISTURBANCES * 64 3.3.1 THE TWO-WAY ERROR COMPONENTS
MODEL * 64 3.3.2* SERIAL CORRELATION IN THE DISTURBANCES* 70 3.3.3
TWO-WAY ERROR COMPONENTS VS KMENTA S APPROACH* 73 3.3.4*
HETEROSKEDASTICITY IN THE DISTURBANCES* 74 3.4* TESTING * 78 3.4.1*
TESTING FOR THE ABSENCE OF INDIVIDUAL EFFECTS * 79 3.4.2* TESTING FOR
UNCORRELATED EFFECTS: HAUSMAN S TEST* 80 3.4.3* TESTING FOR SERIAL
CORRELATION* 81 3.4.4* TESTING FOR HETEROSKEDASTICITY * 82 3.5
ESTIMATION USING UNBALANCED PANELS* 84 REFERENCES* 85 4 ENDOGENOUS
REGRESSORS AND CORRELATED EFFECTS * 89 RACHID BOUMAHDI AND ALBAN THOMAS
4.1* INTRODUCTION* 89 4.2 ESTIMATION OF TRANSFORMED LINEAR PANEL DATA
MODELS* 90 4.2.1* ERROR STRUCTURES AND FILTERING PROCEDURES* 91 4.2.2 AN
IV REPRESENTATION OF THE TRANSFORMED LINEAR MODEL * 93 4.3 ESTIMATION
WITH TIME-INVARIANT REGRESSORS* 95 4.3.1* INTRODUCTION * 95 4.3.2*
INSTRUMENTAL VARIABLE ESTIMATION* 96 4.3.3* MORE EFFICIENT IV PROCEDURES
* 98 4.4 A MEASURE OF INSTRUMENT RELEVANCE* 99 4.5* INCORPORATING
TIME-VARYING REGRESSORS* 101 4.5.1* INSTRUMENTAL VARIABLES ESTIMATION*
102 4.6 GMM ESTIMATION OF STATIC PANEL DATA MODELS* 104 4.6.1* STATIC
MODEL ESTIMATION* 105 4.6.2 GMM ESTIMATION WITH HT, AM AND BMS
INSTRUMENTS * 107 4.7 UNBALANCED PANELS * 108 REFERENCES * 110 5 THE
CHAMBERLAIN APPROACH TO PANEL DATA: AN OVERVIEW AND SOME SIMULATIONS *
113 BRUNO CREPON AND JACQUES MAIRESSE 5.1* INTRODUCTION* 113 5.2 THE
CHAMBERLAIN H MATRIX FRAMEWORK* 115 CONTENTS* IX 5.2.1* THE * MATRIX*
115 5.2.2* REIATIONS BETWEEN * AND THE PARAMETERS OF INTEREST* 118
5.2.3* FOUR IMPORTANT CASES * 120 5.2.4* RESTRICTIONS ON THE COVARIANCE
MATRIX OF THE DISTURBANCES 124 5.2.5* A GENERAIIZATION OF THE
CHAMBERIAIN METHOD* 125 5.2.6* THE VECTOR REPRESENTATION OF THE
CHAMBERIAIN ESTIMATING EQUATIONS * 126 5.2.7 THE ESTIMATION OF MATRIX *
* 127 5.3* ASYMPTOTIC LEAST SQUARES * 130 5.3.1* ALS ESTIMATION* 130
5.3.2* THE OPTIMAL ALS ESTIMATOR * 132 5.3.3* SPECIFICATION TESTING IN
THE ALS FRAMEWORK* 135 5.4 THE EQUIVALENCE OF THE GMM AND THE
CHAMBERIAIN METHODS* 137 5.4.1 A REMINDER ON THE GMM* 137 5.4.2
EQUIVALENCE OF THE GMM AND THE CHAMBERIAIN METHODS * 139 5.4.3*
EQUIVALENCE IN SPECIFIC CASES * 140 5.5* MONTE CARIO SIMUIATIONS* 144
5.5.1* DESIGN OF THE SIMUIATION EXPERIMENTS * 144 5.5.2* CONSISTENCY AND
BIAS * 147 5.5.3* EFFICIENCY AND ROBUSTNESS * 152 5.5.4* STANDARD ERRORS
* 155 5.5.5* SPECIFICATION TESTS* 158 5.6 APPENDIX A: AN EXTENDED VIEW
OF THE CHAMBERIAIN METHOD* 160 5.6.1* SIMUITANEOUS EQUATIONS MODEIS *
160 5.6.2 VAR MODEIS * 160 5.6.3* ENDOGENOUS ATTRITION * 162 5.7
APPENDIX B: VECTOR REPRESENTATION OF THE CHAMBERIAIN ESTIMATING
EQUATIONS * 163 5.7.1* THE VEC OPERATOR * 163 5.7.2* CORREIATED EFFECTS
* 164 5.7.3* ERRORS IN VARIABIES* 164 5.7.4* WEAK SIMUITANEITY * 166
5.7.5* COMBINATION OF THE DIFFERENT CASES * 166 5.7.6* LAGGED DEPENDENT
VARIABIE * 167 5.7.7* RESTRICTIONS ON THE COVARIANCE MATRIX OF THE
DISTURBANCES 167 5.8 APPENDIX C: MANIPUIATION OF EQUATIONS AND
PARAMETERS IN THE ALS FRAMEWORK* 168 5.8.1* TRANSFORMATION OF THE
ESTIMATING EQUATIONS * 168 5.8.2* EIIMINATING PARAMETERS OF SECONDARY
INTEREST * 169 5.8.3* RECOVERING PARAMETERS OF SECONDARY INTEREST ONCE
EIIMINATED * 170 5.8.4* EIIMINATION OF AUXIIIARY PARAMETERS* 173 5.9
APPENDIX D: EQUIVALENCE BETWEEN CHAMBERIAIN S, GMM AND USUAI PANEI DATA
ESTIMATORS * 174 5.10 APPENDIX E: DESIGN OF SIMUIATION EXPERIMENTS* 177
X* CONTENTS 5.10.1 GENERATING PROCESS OF THE VARIABIE X* 177 5.10.2
REGRESSION MODEI * 178 5.10.3 CAIIBRATION OF SIMULATIONS * 179 5.10.4
THREE SCENARIOS* 180 5.10.5 THE CHAMBERIAIN AND GMM ESTIMATORS* 180
5.10.6 STANDARD ERRORS AND SPECIFICATION TESTS * 181 REFERENCES * 181 6
RANDOM COEFFICIENT MODELS * 185 CHENG HSIAO AND M. HASHEM PESARAN 6.1*
INTRODUCTION* 185 6.2 THE MODEIS * 186 6.3 SAMPIING APPROACH * 189 6.4
MEAN GROUP ESTIMATION* 192 6.5 BAYESIAN APPROACH* 193 6.6 DYNAMIC RANDOM
COEFFICIENTS MODEIS * 197 6.7 TESTING FOR HETEROGENEITY UNDER WEAK
EXOGENEITY * 199 6.8 A RANDOM COEFFICIENT SIMUITANEOUS EQUATION SYSTEM *
203 6.9 RANDOM COEFFICIENT MODEIS WITH CROSS-SECTION DEPENDENCE* 206
6.10 CONCIUDING REMARKS * 208 REFERENCES * 211 7 PARAMETRIC BINARY
CHOICE MODELS * 215 MICHAEI LECHNER, STEFAN LOIIIVIER AND THIERRY MAGNAC
7.1* INTRODUCTION* 215 7.2 RANDOM EFFECTS MODEIS UNDER STRICT
EXOGENEITY* 217 7.2.I* ERRORS ARE INDEPENDENT OVER TIME * 218 7.2.2* ONE
FACTOR ERROR TERMS * 219 7.2.3* GENERAI ERROR STRUCTURES* 221 7.2.4*
SIMUIATION METHODS * 223 7.2.5 HOW TO CHOOSE A RANDOM EFFECTS ESTIMATOR
FOR AN APPIICATION * 228 7.2.6* CORREIATED EFFECTS * 229 7.3 FIXED
EFFECTS MODEIS UNDER STRICT EXOGENEITY * 230 7.3.1* THE MODEI * 231
7.3.2* THE METHOD OF CONDITIONAI LIKEIIHOOD * 232 7.3.3 FIXED EFFECTS
MAXIMUM SCORE* 235 7.3.4 GMM ESTIMATION * 236 7.3.5* LARGE-T
APPROXIMATIONS * 237 7.4 DYNAMIC MODEIS* 238 7.4.1 DYNAMIC RANDOM
EFFECTS MODELS* 238 7.4.2 DYNAMIC FIXED EFFECTS MODEIS * 241 REFERENCES*
242 CONTENTS* XI PART II ADVANCED TOPICS 8 DYNAMIC MODELS FOR SHORT
PANELS * 249 MARK *. HARRIS, LASZIO MATYAS AND PATRICK SEVESTRE 8.1*
INTRODUCTION* 249 8.2 THE MODEI* 250 8.3* THE INCONSISTENCY OF
TRADITIONAL ESTIMATORS * 252 8.4 IV AND GMM ESTIMATORS * 255 8.4.1*
UNCORREIATED INDIVIDUAL EFFECTS: THE ORIGINAI BALESTRA*NERIOVE ESTIMATOR
AND ITS EXTENSIONS * 256 8.4.2* CORRELATED INDIVIDUAL EFFECTS * 257
8.4.3* SOME MONTE CARIO EVIDENCE * 269 8.5 THE MAXIMUM LIKEIIHOOD
ESTIMATOR * 270 8.6 TESTING IN DYNAMIC MODEIS* 272 8.6.1* TESTING THE
VAIIDITY OF INSTRUMENTS * 272 8.6.2* TESTING FOR UNOBSERVED EFFECTS *
273 8.6.3* TESTING FOR THE ABSENCE OF SERIAL CORREIATION IN ** 274
8.6.4* SIGNIFICANCE TESTING IN TWO-STEP VARIANTS * 275 REFERENCES* 276 9
UNIT ROOTS AND COINTEGRATION IN PANELS * 279 JOERG BREITUNG AND M. HASHEM
PESARAN 9.1* INTRODUCTION* 279 9.2* FIRST GENERATION PANEI UNIT ROOT
TESTS * 281 9.2.1* THE BASIC MODEI * 281 9.2.2* DERIVATION OF THE TESTS
* 282 9.2.3* NUII DISTRIBUTION OF THE TESTS * 284 9.2.4* ASYMPTOTIC
POWER OF THE TESTS * 287 9.2.5* HETEROGENEOUS TRENDS * 288 9.2.6*
SHORT-RUN DYNAMICS* 291 9.2.7* OTHER APPROACHES TO PANEI UNIT ROOT
TESTING * 293 9.3* SECOND GENERATION PANEL UNIT ROOT TESTS * 295 9.3.1*
CROSS-SECTION DEPENDENCE* 295 9.3.2* TESTS BASED ON GLS REGRESSIONS* 296
9.3.3* TEST STATISTICS BASED ON OLS REGRESSIONS * 297 9.3.4* OTHER
APPROACHES * 298 9.4* CROSS-UNIT COINTEGRATION* 299 9.5* FINITE SAMPIE
PROPERTIES OF PANEI UNIT ROOT TESTS * 301 9.6* PANEI COINTEGRATION:
GENERAI CONSIDERATIONS * 302 9.7 RESIDUAL-BASED APPROACHES TO PANEI
COINTEGRATION * 306 9.7.1* SPURIOUS REGRESSION * 306 9.7.2* TESTS OF
PANEI COINTEGRATION* 307 9.8* TESTS FOR MUITIPIE COINTEGRATION * 308
9.9* ESTIMATION OF COINTEGRATING REIATIONS IN PANEIS * 309 9.9.1* SINGIE
EQUATION ESTIMATORS * 309 9.9.2* SYSTEM ESTIMATORS* 312 XII* CONTENTS
9.10 CROSS-SECTION DEPENDENCE AND THE GLOBAI VAR* 313 9.11 CONCIUDING
REMARKS * 316 REFERENCES * 316 10 MEASUREMENT ERRORS AND SIMULTANEITY *
323 ERIK BIOERN AND JAYAIAKSHMI KRISHNAKUMAR 10.1 INTRODUCTION* 323 10.2
MEASUREMENT ERRORS AND PANEL DATA* 323 10.2.1 MODEI AND ORTHOGONAIITY
CONDITIONS * 325 10.2.2 IDENTIFICATION AND THE STRUCTURE OF THE SECOND
ORDER MOMENTS * 327 10.2.3 MOMENT CONDITIONS * 328 10.2.4 ESTIMATORS
CONSTRUCTED FROM PERIOD MEANS* 331 10.2.5 GMM ESTIMATION AND TESTING IN
THE GENERAI CASE * 332 10.2.6 ESTIMATION BY GMM, COMBINING DIFFERENCES
AND LEVEIS 335 10.2.7 EXTENSIONS: MODIFICATIONS * 343 10.2.8 CONCLUDING
REMARKS* 343 10.3 SIMUITANEITY AND PANEI DATA * 344 10.3.1 SEM WITH EC*
345 10.3.2 EXTENSIONS * 361 10.4 CONCIUSION* 364 REFERENCES* 365 11
PSEUDO - PANELS AND REPEATED CROSS - SECTIONS * 369 MARNO VERBEEK 11.1
INTRODUCTION* 369 11.2 ESTIMATION OF A LINEAR FIXED EFFECTS MODEI * 370
11.3 ESTIMATION OF A LINEAR DYNAMIC MODEL* 376 11.4 ESTIMATION OF A
BINARY CHOICE MODEI * 380 11.5 CONCIUDING REMARKS * 381 REFERENCES* 382
12 ATTRITION, SELECTION BIAS AND CENSORED REGRESSIONS * 385 BO HONORE,
FRANCIS VEIIA AND MARNO VERBEEK 12.1 INTRODUCTION* 385 12.2 CENSORING,
SAMPIE SEIECTION AND ATTRITION * 386 12.3 SAMPIE SELECTION AND ATTRITION
* 389 12.4 SAMPIE SEIECTION BIAS AND ROBUSTNESS OF STANDARD ESTIMATORS *
391 12.5 TOBIT AND CENSORED REGRESSION MODEIS* 393 12.5.1 RANDOM EFFECTS
TOBIT* 394 12.5.2 RANDOM EFFECTS TOBIT WITH ENDOGENOUS EXPIANATORY
VARIABIES* 396 12.5.3 DYNAMIC RANDOM EFFECTS TOBIT* 398 12.5.4 FIXED
EFFECTS TOBIT ESTIMATION* 399 12.5.5 SEMI-PARAMETRIC ESTIMATION* 401
CONTENTS* XIII 12.5.6 SEMI-PARAMETRIC ESTIMATION IN THE PRESENCE OF
LAGGED DEPENDENT VARIABLES* 402 12.6 MODELS OF SAMPLE SELECTION AND
ATTRITION* 402 12.6.1 MAXIMUM LIKELIHOOD ESTIMATORS * 403 12.6.2
TWO-STEP ESTIMATORS* 404 12.6.3 ALTERNATIVE SELECTION RULES * 407 12.6.4
TWO-STEP ESTIMATORS WITH FIXED EFFECTS* 408 12.6.5 SEMI-PARAMETRIC
SAMPLE SELECTION MODELS * 409 12.6.6 SEMI-PARAMETRIC ESTIMATION OF A
TYPE-3 TOBIT MODEL * 410 12.7 SOME EMPIRICAL APPLICATIONS * 412 12.7.1
ATTRITION IN EXPERIMENTAL DATA* 412 12.7.2 REAL WAGES OVER THE BUSINESS
CYCLE * 413 12.7.3 UNIONS AND WAGES* 415 REFERENCES* 416 13 SIMULATION
TECHNIQUES FOR PANELS: EFFICIENT IMPORTANCE SAMPLING .. 419 ROMAN
LIESENFELD AND JEAN-FRANCOIS RICHARD 13.1 INTRODUCTION* 419 13.2
PSEUDORANDOM NUMBER GENERATION * 420 13.2.1 UNIVARIATE DISTRIBUTIONS *
421 13.2.2 MULTIVARIATE DISTRIBUTIONS* 424 13.3 IMPORTANCE SAMPLING* 426
13.3.1 GENERAL PRINCIPLE* 426 13.3.2 EFFICIENT IMPORTANCE SAMPLING * 428
13.3.3 MC SAMPLING VARIANCE OF (*)IS ESTIMATES * 431 13.3.4 GHK
SIMULATOR * 432 13.3.5 COMMON RANDOM NUMBERS* 432 13.4 SIMULATION-BASED
INFERENCE PROCEDURES* 434 13.4.1 INTEGRATION IN PANEL DATA MODELS * 434
13.4.2 SIMULATED LIKELIHOOD * 435 13.4.3 SIMULATED METHOD OF MOMENTS *
435 13.4.4 BAYESIAN POSTERIOR MOMENTS * 437 13.5 NUMERICAL PROPERTIES OF
SIMULATED ESTIMATORS * 437 13.6 EIS APPLICATION: LOGIT PANEL WITH
UNOBSERVED HETEROGENEITY* 439 13.6.1 THE MODEL * 439 13.6.2 EIS
EVALUATION OF THE LIKELIHOOD * 440 13.6.3 EMPIRICAL APPLICATION* 443
13.7 CONCLUSION* 445 13.8 APPENDIX: IMPLEMENTATION OF EIS FOR THE LOGIT
PANEL MODEL* 446 REFERENCES * 448 14 SEMI-PARAMETRIC AND NON-PARAMETRIC
METHODS IN PANEL DATA MODELS * 451 CHUNRONG AI AND QI LI 14.1
INTRODUCTION* 451 14.2 LINEAR PANEL DATA MODEL* 452 XIV* CONTENTS 14.2.1
ADDITIVE EFFECT* 452 14.2.2 MULTIPLICATIVE EFFECT* 460 14.3 NONLINEAR
PANEL DATA MODEL* 462 14.3.1 CENSORED REGRESSION MODEL* 462 14.3.2
DISCRETE CHOICE MODEL* 470 14.3.3 SAMPLE SELECTION MODEL* 474 14.4
CONCLUSION* 475 REFERENCES* 476 15 PANEL DATA MODELING AND INFERENCE: A
BAYESIAN PRIMER * 479 SIDDHARTHA CHIB 15.1 INTRODUCTION* 479 15.1.1
HIERARCHICAL PRIOR MODELING* 480 15.1.2 ELEMENTS OF MARKOV CHAIN MONTE
CARLO * 483 15.1.3 SOME BASIC BAYESIAN UPDATES* 486 15.1.4 BASIC VARIATE
GENERATORS * 488 15.2 CONTINUOUS RESPONSES * 489 15.2.1
GAUSSIAN*GAUSSIAN MODEL* 490 15.2.2 ROBUST MODELING OF BI :
STUDENT*STUDENT AND STUDENT-MIXTURE MODELS * 492 15.2.3
HETEROSKEDASTICITY* 495 15.2.4 SERIAL CORRELATION * 496 15.3 BINARY
RESPONSES * 497 15.4 OTHER OUTCOME TYPES* 501 15.4.1 CENSORED OUTCOMES *
501 15.4.2 COUNT RESPONSES* 502 15.4.3 MULTINOMIAL RESPONSES * 503 15.5
BINARY ENDOGENOUS REGRESSOR * 504 15.6 INFORMATIVE MISSINGNESS * 507
15.7 PREDICTION* 508 15.8 RESIDUAL ANALYSIS * 509 15.9 MODEL COMPARISONS
* 509 15.9.1 GAUSSIAN*GAUSSIAN MODEL* 512 15.9.2 GAUSSIAN*GAUSSIAN TOBIT
MODEL * 512 15.9.3 PANEL POISSON MODEL* 513 15.10 CONCLUSION* 513
REFERENCES * 514 16 TOPOOL OR NOT TO POOL? * 517 BADI H. BALTAGI,
GEORGES BRESSON AND ALAIN PIROTTE 16.1 INTRODUCTION* 517 16.2 TESTS FOR
POOLABILITY, PRETESTING AND STEIN-RULE METHODS* 521 16.2.1 TESTS FOR
POOLABILITY * 521 16.2.2 PRETESTING AND STEIN-RULE METHODS * 525 16.2.3
EXAMPLE* 526 16.3 HETEROGENEOUS ESTIMATORS * 527 CONTENTS* XV 16.3.1
AVERAGING ESTIMATORS * 529 16.3.2 BAYESIAN FRAMEWORK* 530 16.3.3 AN
EXAMPLE* 538 16.4 COMMENTS ON THE PREDICTIVE APPROACH * 541 16.4.1 FROM
THE POST-SAMPLE PREDICTIVE DENSITY* * 541 16.4.2 ... TO THE GOOD
FORECAST PERFORMANCE OF THE HIERARCHICAL BAYES ESTIMATOR: AN EXAMPLE*
542 16.5 CONCLUSION* 544 REFERENCES* 545 17 DURATION MODELS AND POINT
PROCESSES * 547 JEAN-PIERRE FLORENS, DENIS FOUGERE AND MICHEL MOUCHART
17.1 MARGINAL DURATION MODELS* 548 17.1.1 DISTRIBUTION, SURVIVOR AND
DENSITY FUNCTIONS * 548 17.1.2 TRUNCATED DISTRIBUTIONS AND HAZARD
FUNCTIONS * 550 17.2 CONDITIONAL MODELS * 552 17.2.1 GENERAL
CONSIDERATIONS* 552 17.2.2 THE PROPORTIONAL HAZARD OR COX MODEL* 555
17.2.3 THE ACCELERATED TIME MODEL* 557 17.2.4 AGGREGATION AND
HETEROGENEITY* 558 17.2.5 ENDOGENEITY* 560 17.3 COMPETING RISKS AND
MULTIVARIATE DURATION MODELS * 561 17.3.1 MULTIVARIATE DURATIONS * 561
17.3.2 COMPETING RISKS MODELS: DEFINITIONS * 563 17.3.3 IDENTIFIABILITY
OF COMPETING RISKS MODELS* 566 17.3.4 RIGHT-CENSORING * 568 17.4
INFERENCE IN DURATION MODELS * 570 17.4.1 INTRODUCTION * 570 17.4.2
PARAMETRIC MODELS * 570 17.4.3 NON-PARAMETRIC AND SEMI-PARAMETRIC
MODELS* 576 17.5 COUNTING PROCESSES AND POINT PROCESSES * 579 17.5.1
DEFINITIONS * 579 17.5.2 STOCHASTIC INTENSITY, COMPENSATOR AND
LIKELIHOOD OF A COUNTING PROCESS * 581 17.6 POISSON, MARKOV AND
SEMI-MARKOV PROCESSES * 584 17.6.1 POISSON PROCESSES * 584 17.6.2 MARKOV
PROCESSES * 585 17.6.3 SEMI-MARKOV PROCESSES * 592 17.7 STATISTICAL
ANALYSIS OF COUNTING PROCESSES * 594 17.7.1 THE COX LIKELIHOOD * 596
17.7.2 THE MARTINGALE ESTIMATION OF THE INTEGRATED BASELINE INTENSITY *
597 17.8 CONCLUSIONS* 600 REFERENCES* 600 XVI* CONTENTS 18 GMM FOR PANEL
DATA COUNT MODELS * 603 FRANK WINDMEIJER 18.1 INTRODUCTION* 603 18.2 GMM
IN CROSS-SECTIONS* 604 18.3 PANEL DATA MODELS * 606 18.3.1 STRICTLY
EXOGENOUS REGRESSORS* 607 18.3.2 PREDETERMINED REGRESSORS * 608 18.3.3
ENDOGENOUS REGRESSORS * 609 18.3.4 DYNAMIC MODELS* 610 18.4 GMM* 612
18.5 APPLICATIONS AND SOFTWARE* 614 18.6 FINITE SAMPLE INFERENCE* 615
18.6.1 WALD TEST AND FINITE SAMPLE VARIANCE CORRECTION* 615 18.6.2
CRITERION-BASED TESTS * 617 18.6.3 CONTINUOUS UPDATING ESTIMATOR* 618
18.6.4 MONTE CARLO RESULTS * 619 REFERENCES* 623 19 SPATIAL PANEL
ECONOMETRICS * 625 LUC ANSELIN, JULIE LE GALLO AND HUBERT JAYET 19.1
INTRODUCTION* 625 19.2 SPATIAL EFFECTS * 626 19.2.1 SPATIAL WEIGHTS AND
SPATIAL LAG OPERATOR * 628 19.2.2 SPATIAL LAG MODEL* 630 19.2.3 SPATIAL
ERROR MODEL* 632 19.3 A TAXONOMY OF SPATIAL PANEL MODEL SPECIFICATIONS*
636 19.3.1 TEMPORAL HETEROGENEITY* 637 19.3.2 SPATIAL HETEROGENEITY *
639 19.3.3 SPATIO-TEMPORAL MODELS * 644 19.4 ESTIMATION OF SPATIAL PANEL
MODELS * 648 19.4.1 MAXIMUM LIKELIHOOD ESTIMATION * 648 19.4.2
INSTRUMENTAL VARIABLES AND GMM* 652 19.5 TESTING FOR SPATIAL DEPENDENCE*
654 19.5.1 LAGRANGE MULTIPLIER TESTS FOR SPATIAL LAG AND SPATIAL ERROR
DEPENDENCE IN POOLED MODELS* 655 19.5.2 TESTING FOR SPATIAL ERROR
CORRELATION IN PANEL DATA MODELS* 655 19.6 CONCLUSIONS* 656 REFERENCES*
657 PART III APPLICATIONS 20 FOREIGN DIRECT INVESTMENT: LESSONS FROM
PANEL DATA * 663 PIERRE BLANCHARD, CARL GAIGNE AND CLAUDE MATHIEU 20.1
INTRODUCTION* 663 20.2 A SIMPLE MODEL OF FD** 664 20.2.1 ASSUMPTIONS AND
PRELIMINARY RESULTS* 665 CONTENTS* XVII 20.2.2 TECHNOLOGY AND COUNTRY
CHARACTERISTICS AS DETERMINANTS OF FD** 666 20.3 ECONOMETRIC
IMPLEMENTATION AND DATA * 668 20.3.1 A GENERAL ECONOMETRIC MODEL * 669
20.3.2 FDI AND DATA ISSUES * 670 20.4 EMPIRICAL ESTIMATIONS: SELECTED
APPLICATIONS* 672 20.4.1 TESTING THE TRADE-OFF BETWEEN FD* AND EXPORTS*
672 20.4.2 TESTING THE ROLE OF TRADE POLICY IN FD** 677 20.4.3 TESTING
THE RELATIONSHIP BETWEEN FD* AND EXCHANGE RATE * 683 20.5 SOME RECENT
ECONOMETRIC ISSUES * 690 20.5.1 FDI, PANEL DATA AND SPATIAL
ECONOMETRICS* 690 20.5.2 EXCHANGE RATE, UNIT ROOTS AND COINTEGRATION*
691 REFERENCES * 693 21 STOCHASTIC FRONTIER ANALYSIS AND EFFICIENCY
ESTIMATION * 697 CHRISTOPHER CORNWELL AND PETER SCHMIDT 21.1 MEASUREMENT
OF FIRM EFFICIENCY* 698 21.2 INTRODUCTION TO SFA * 700 21.2.1 THE BASIC
SFA EMPIRICAL FRAMEWORK* 700 21.2.2 STOCHASTIC VS DETERMINISTIC
FRONTIERS * 700 21.2.3 OTHER FRONTIER FUNCTIONS * 702 21.2.4 SFA WITH
CROSS-SECTION DATA* 703 21.3 SFA WITH PANEL DATA * 704 21.3.1 MODELS
WITH TIME-INVARIANT INEFFICIENCY * 704 21.3.2 MODELS WITH TIME-VARYING
INEFFICIENCY * 714 21.4 APPLICATIONS * 718 21.4.1 EGYPTIAN TILE
MANUFACTURERS * 718 21.4.2 INDONESIAN RICE FARMERS * 720 21.5 CONCLUDING
REMARKS * 723 REFERENCES* 723 22 ECONOMETRIC ANALYSES OF LINKED
EMPLOYER*EMPLOYEE DATA * 727 JOHN M. ABOWD, FRANCIS KRAMARZ AND SIMON
WOODCOCK 22.1 INTRODUCTION* 727 22.2 A PROTOTYPICAL LONGITUDINAL LINKED
DATA SET * 729 22.2.1 MISSING DATA * 730 22.2.2 SAMPLING FROM LINKED
DATA* 732 22.3 LINEAR STATISTICAL MODELS WITH PERSON AND FIRM EFFECTS*
733 22.3.1 A GENERAL SPECIFICATION * 733 22.3.2 THE PURE PERSON AND FIRM
EFFECTS SPECIFICATION * 734 22.4 DEFINITION OF EFFECTS OF INTEREST* 735
22.4.1 PERSON EFFECTS AND UNOBSERVABLE PERSONAL HETEROGENEITY* 735
22.4.2 FIRM EFFECTS AND UNOBSERVABLE FIRM HETEROGENEITY* 736 22.4.3
FIRM-AVERAGE PERSON EFFECT* 737 CONTENTS* XIX 23.7 CONCLUSION* 790
REFERENCES * 791 24 DYNAMIC POLICY ANALYSIS * 795 JAAP H. ABBRING AND
JAMES J. HECKMAN 24.1 INTRODUCTION* 795 24.2 POLICY EVALUATION AND
TREATMENT EFFECTS * 796 24.2.1 THE EVALUATION PROBLEM* 796 24.2.2 THE
TREATMENT EFFECT APPROACH* 800 24.2.3 DYNAMIC POLICY EVALUATION * 801
24.3 DYNAMIC TREATMENT EFFECTS AND SEQUENTIAL RANDOMIZATION * 803 24.3.1
DYNAMIC TREATMENT EFFECTS * 803 24.3.2 POLICY EVALUATION AND DYNAMIC
DISCRETE-CHOICE ANALYSIS * 810 24.3.3 THE INFORMATION STRUCTURE OF
POLICIES * 813 24.3.4 SELECTION ON UNOBSERVABLES * 815 24.4 THE
EVENT-HISTORY APPROACH TO POLICY ANALYSIS* 816 24.4.1 TREATMENT EFFECTS
IN DURATION MODELS * 817 24.4.2 TREATMENT EFFECTS IN MORE GENERAL
EVENT-HISTORY MODELS * 823 24.4.3 A STRUCTURAL PERSPECTIVE * 828 24.5
DYNAMIC DISCRETE CHOICE AND DYNAMIC TREATMENT EFFECTS* 829 24.5.1
SEMI-PARAMETRIC DURATION MODELS AND COUNTERFACTUALS . * 831 24.5.2 A
SEQUENTIAL STRUCTURAL MODEL WITH OPTION VALUES* 844 24.5.3
IDENTIFICATION AT INFINITY * 850 24.5.4 COMPARING REDUCED-FORM AND
STRUCTURAL MODELS * 851 24.5.5 A SHORT SURVEY OF DYNAMIC DISCRETE-CHOICE
MODELS * 853 24.6 CONCLUSION* 857 REFERENCES* 857 25 ECONOMETRICS OF
INDIVIDUAL LABOR MARKET TRANSITIONS * 865 DENIS FOUGERE AND THIERRY
KAMIONKA 25.1 INTRODUCTION* 865 25.2 MULTI-SPELL MULTI-STATE MODELS *
867 25.2.1 GENERAL FRAMEWORK* 867 25.2.2 NON-PARAMETRIC AND PARAMETRIC
ESTIMATION * 872 25.2.3 UNOBSERVED HETEROGENEITY* 878 25.3 MARKOV
PROCESSES USING DISCRETE-TIME OBSERVATIONS * 882 25.3.1 THE
TIME-HOMOGENEOUS MARKOVIAN MODEL* 883 25.3.2 THE MOVER-STAYER MODEL* 893
25.4 CONCLUDING REMARKS * 901 REFERENCES* 902 XVIII* CONTENTS 22.4.4
PERSON-AVERAGE FIRM EFFECT* 737 22.4.5 INDUSTRY EFFECTS * 738 22.4.6
OTHER FIRM CHARACTERISTIC EFFECTS * 739 22.4.7 OCCUPATION EFFECTS AND
OTHER PERSON X FIRM INTERACTIONS* 739 22.5 ESTIMATION BY FIXED EFFECTS
METHODS* 739 22.5.1 ESTIMATION OF THE FIXED EFFECTS MODEL BY DIRECT
LEAST SQUARES * 739 22.5.2 CONSISTENT METHODS FOR SS AND Y (THE
FIRM-SPECIFIC RETURNS TO SENIORITY)* 743 22.6 THE MIXED MODEL* 744
22.6.1 REML ESTIMATION OF THE MIXED MODEL * 746 22.6.2 ESTIMATING THE
FIXED EFFECTS AND REALIZED RANDOM EFFECTS* 747 22.6.3 MIXED MODELS AND
CORRELATED RANDOM EFFECTS MODELS . * 748 22.7 MODELS OF HETEROGENEITY
BIASES IN INCOMPLETE MODELS * 750 22.7.1 OMISSION OF THE FIRM EFFECTS*
750 22.7.2 OMISSION OF THE PERSON EFFECTS * 751 22.7.3 INTER-INDUSTRY
WAGE DIFFERENTIALS * 752 22.8 ENDOGENOUS MOBILITY * 753 22.8.1 A
GENERALIZED LINEAR MIXED MODEL* 754 22.8.2 A MODEL OF WAGES, ENDOGENOUS
MOBILITY AND PARTICIPATION WITH PERSON AND FIRM EFFECTS * 755 22.8.3
STOCHASTIC ASSUMPTIONS * 756 22.9 CONCLUSION* 758 REFERENCES* 758 23
LIFE CYCLE LABOR SUPPLY AND PANEL DATA: A SURVEY * 761 BERTRAND KOEBEL,
FRANCOIS LAISNEY, WINF RI ED POHLMEIER AND MATTHIAS STAAT 23.1
INTRODUCTION* 761 23.2 THE BASIC MODEL OF LIFE CYCLE LABOR SUPPLY* 762
23.2.1 THE FRAMEWORK* 763 23.2.2 FIRST SPECIFICATIONS OF THE UTILITY
FUNCTION* 765 23.3 TAKING ACCOUNT OF UNCERTAINTY AND RISK* 768 23.3.1
FIRST DEVELOPMENTS* 768 23.3.2 RECENT CONTRIBUTIONS * 770 23.3.3
EMPIRICAL RESULTS * 773 23.4 VOLUNTARY AND INVOLUNTARY NON-PARTICIPATION
* 774 23.4.1 ACCOUNTING FOR THE PARTICIPATION DECISION * 775 23.4.2
UNEMPLOYMENT * 778 23.5 ALTERNATIVE PARAMETERIZATION AND IMPLICATIONS *
779 23.6 RELAXING SEPARABILITY ASSUMPTIONS * 783 23.6.1 RELAXING
WITHIN-PERIOD ADDITIVE SEPARABILITY* 783 23.6.2 RELAXING INTERTEMPORAL
SEPARABILITY IN PREFERENCES * 784 XX* CONTENTS 26 SOFTWARE REVIEW * 907
PIERRE BLANCHARD 26.1 INTRODUCTION* 907 26.2 GENERAL-PURPOSE ECONOMETRIC
PACKAGES * 908 26.2.1 EVIEWS (V. 5.1) * 908 26.2.2 LIMDEP (V. 8) WITH
NLOGIT (V. 3) * 912 26.2.3 RATS (V. 6) * 916 26.2.4 SAS (V. 9.1) * 920
26.2.5 STATA (V. 9) * 923 26.2.6 TSP (V. 5) * 927 26.3 HIGH-LEVEL MATRIX
PROGRAMMING LANGUAGES * 930 26.3.1 GAUSS (V. 5)* 930 26.3.2 OX (V. 3.4)
* 936 26.4 PERFORMANCE HINTS AND NUMERICAL ACCURACY EVALUATION * 941
26.4.1 SPEED COMPARISON * 941 26.4.2 NUMERICAL ACCURACY EVALUATIONS *
944 REFERENCES* 949
|
| adam_txt |
CONTENTS PART I FUNDAMENTALS 1 INTRODUCTION * 3 MARC NERLOVE, PATRICK
SEVESTRE AND PIETRO BALES TR A 1.1* INTRODUCTION* 3 1.2 DATA,
DATA-GENERATING PROCESSES (DGP), AND INFERENCE * 4 1.3 HISTORY AND
DYNAMICS * 8 1.4 * BRIEF REVIEW OF OTHER METHODOLOGICAL DEVELOPMENTS* 13
1.5* CONCLUSION* 21 REFERENCES * 21 FIXED EFFECTS MODELS AND FIXED
COEFFICIENTS MODELS * 23 PIETRO BALES TR A AND JAYALAKSHMI KRISHNAKUMAR
2.1* THE COVARIANCE MODEL: INDIVIDUAL EFFECTS ONLY* 24 2.1.1*
SPECIFICATION * 24 2.1.2* ESTIMATION * 25 2.1.3* INFERENCE* 28 2.2 THE
COVARIANCE MODEL: INDIVIDUAL AND TIME EFFECTS * 29 2.2.1* TIME EFFECTS
ONLY* 29 2.2.2* TIME AND INDIVIDUAL EFFECTS * 30 2.2.3* INFERENCE* 32
2.3 NON-SPHERICAL DISTURBANCES* 33 2.3.1* WHAT VARIANCE*COVARIANCE
STUCTURE?* 33 2.3.2* TWO GENERAL PROPOSITIONS FOR FIXED EFFECTS MODELS*
34 2.3.3* INDIVIDUAL FIXED EFFECTS AND SERIAL CORRELATION* 36 2.3.4*
HETEROSCEDASTICITY IN FIXED EFFECTS MODELS* 38 2.4 EXTENSIONS * 40
2.4.1* CONSTANT VARIABLES IN ONE DIMENSION* 40 2.4.2* VARIABLE SLOPE
COEFFICIENTS * 41 2.4.3* UNBALANCED PANELS * 44 REFERENCES * 48 VII
VIII* CONTENTS 3 ERROR COMPONENTS MODELS * 49 BADI H. BALTAGI, LASZLO
MATYAS AND PATRICK SEVESTRE 3.1* INTRODUCTION* 49 3.2 THE ONE-WAY ERROR
COMPONENTS MODEL* 50 3.2.1* DEFINITION/ASSUMPTIONS OF THE MODEL* 50
3.2.2 THE GLS ESTIMATOR* 52 3.2.3* THE FEASIBLE GLS ESTIMATOR * 55
3.2.4* SOME OTHER ESTIMATORS* 58 3.2.5* PREDICTION* 63 3.3* MORE GENERAL
STRUCTURES OF THE DISTURBANCES * 64 3.3.1 THE TWO-WAY ERROR COMPONENTS
MODEL * 64 3.3.2* SERIAL CORRELATION IN THE DISTURBANCES* 70 3.3.3
TWO-WAY ERROR COMPONENTS VS KMENTA'S APPROACH* 73 3.3.4*
HETEROSKEDASTICITY IN THE DISTURBANCES* 74 3.4* TESTING * 78 3.4.1*
TESTING FOR THE ABSENCE OF INDIVIDUAL EFFECTS * 79 3.4.2* TESTING FOR
UNCORRELATED EFFECTS: HAUSMAN'S TEST* 80 3.4.3* TESTING FOR SERIAL
CORRELATION* 81 3.4.4* TESTING FOR HETEROSKEDASTICITY * 82 3.5
ESTIMATION USING UNBALANCED PANELS* 84 REFERENCES* 85 4 ENDOGENOUS
REGRESSORS AND CORRELATED EFFECTS * 89 RACHID BOUMAHDI AND ALBAN THOMAS
4.1* INTRODUCTION* 89 4.2 ESTIMATION OF TRANSFORMED LINEAR PANEL DATA
MODELS* 90 4.2.1* ERROR STRUCTURES AND FILTERING PROCEDURES* 91 4.2.2 AN
IV REPRESENTATION OF THE TRANSFORMED LINEAR MODEL * 93 4.3 ESTIMATION
WITH TIME-INVARIANT REGRESSORS* 95 4.3.1* INTRODUCTION * 95 4.3.2*
INSTRUMENTAL VARIABLE ESTIMATION* 96 4.3.3* MORE EFFICIENT IV PROCEDURES
* 98 4.4 A MEASURE OF INSTRUMENT RELEVANCE* 99 4.5* INCORPORATING
TIME-VARYING REGRESSORS* 101 4.5.1* INSTRUMENTAL VARIABLES ESTIMATION*
102 4.6 GMM ESTIMATION OF STATIC PANEL DATA MODELS* 104 4.6.1* STATIC
MODEL ESTIMATION* 105 4.6.2 GMM ESTIMATION WITH HT, AM AND BMS
INSTRUMENTS * 107 4.7 UNBALANCED PANELS * 108 REFERENCES * 110 5 THE
CHAMBERLAIN APPROACH TO PANEL DATA: AN OVERVIEW AND SOME SIMULATIONS *
113 BRUNO CREPON AND JACQUES MAIRESSE 5.1* INTRODUCTION* 113 5.2 THE
CHAMBERLAIN H MATRIX FRAMEWORK* 115 CONTENTS* IX 5.2.1* THE * MATRIX*
115 5.2.2* REIATIONS BETWEEN * AND THE PARAMETERS OF INTEREST* 118
5.2.3* FOUR IMPORTANT CASES * 120 5.2.4* RESTRICTIONS ON THE COVARIANCE
MATRIX OF THE DISTURBANCES 124 5.2.5* A GENERAIIZATION OF THE
CHAMBERIAIN METHOD* 125 5.2.6* THE VECTOR REPRESENTATION OF THE
CHAMBERIAIN ESTIMATING EQUATIONS * 126 5.2.7 THE ESTIMATION OF MATRIX *
* 127 5.3* ASYMPTOTIC LEAST SQUARES * 130 5.3.1* ALS ESTIMATION* 130
5.3.2* THE OPTIMAL ALS ESTIMATOR * 132 5.3.3* SPECIFICATION TESTING IN
THE ALS FRAMEWORK* 135 5.4 THE EQUIVALENCE OF THE GMM AND THE
CHAMBERIAIN METHODS* 137 5.4.1 A REMINDER ON THE GMM* 137 5.4.2
EQUIVALENCE OF THE GMM AND THE CHAMBERIAIN METHODS * 139 5.4.3*
EQUIVALENCE IN SPECIFIC CASES * 140 5.5* MONTE CARIO SIMUIATIONS* 144
5.5.1* DESIGN OF THE SIMUIATION EXPERIMENTS * 144 5.5.2* CONSISTENCY AND
BIAS * 147 5.5.3* EFFICIENCY AND ROBUSTNESS * 152 5.5.4* STANDARD ERRORS
* 155 5.5.5* SPECIFICATION TESTS* 158 5.6 APPENDIX A: AN EXTENDED VIEW
OF THE CHAMBERIAIN METHOD* 160 5.6.1* SIMUITANEOUS EQUATIONS MODEIS *
160 5.6.2 VAR MODEIS * 160 5.6.3* ENDOGENOUS ATTRITION * 162 5.7
APPENDIX B: VECTOR REPRESENTATION OF THE CHAMBERIAIN ESTIMATING
EQUATIONS * 163 5.7.1* THE VEC OPERATOR * 163 5.7.2* CORREIATED EFFECTS
* 164 5.7.3* ERRORS IN VARIABIES* 164 5.7.4* WEAK SIMUITANEITY * 166
5.7.5* COMBINATION OF THE DIFFERENT CASES * 166 5.7.6* LAGGED DEPENDENT
VARIABIE * 167 5.7.7* RESTRICTIONS ON THE COVARIANCE MATRIX OF THE
DISTURBANCES 167 5.8 APPENDIX C: MANIPUIATION OF EQUATIONS AND
PARAMETERS IN THE ALS FRAMEWORK* 168 5.8.1* TRANSFORMATION OF THE
ESTIMATING EQUATIONS * 168 5.8.2* EIIMINATING PARAMETERS OF SECONDARY
INTEREST * 169 5.8.3* RECOVERING PARAMETERS OF SECONDARY INTEREST ONCE
EIIMINATED * 170 5.8.4* EIIMINATION OF AUXIIIARY PARAMETERS* 173 5.9
APPENDIX D: EQUIVALENCE BETWEEN CHAMBERIAIN'S, GMM AND USUAI PANEI DATA
ESTIMATORS * 174 5.10 APPENDIX E: DESIGN OF SIMUIATION EXPERIMENTS* 177
X* CONTENTS 5.10.1 GENERATING PROCESS OF THE VARIABIE X* 177 5.10.2
REGRESSION MODEI * 178 5.10.3 CAIIBRATION OF SIMULATIONS * 179 5.10.4
THREE SCENARIOS* 180 5.10.5 THE CHAMBERIAIN AND GMM ESTIMATORS* 180
5.10.6 STANDARD ERRORS AND SPECIFICATION TESTS * 181 REFERENCES * 181 6
RANDOM COEFFICIENT MODELS * 185 CHENG HSIAO AND M. HASHEM PESARAN 6.1*
INTRODUCTION* 185 6.2 THE MODEIS * 186 6.3 SAMPIING APPROACH * 189 6.4
MEAN GROUP ESTIMATION* 192 6.5 BAYESIAN APPROACH* 193 6.6 DYNAMIC RANDOM
COEFFICIENTS MODEIS * 197 6.7 TESTING FOR HETEROGENEITY UNDER WEAK
EXOGENEITY * 199 6.8 A RANDOM COEFFICIENT SIMUITANEOUS EQUATION SYSTEM *
203 6.9 RANDOM COEFFICIENT MODEIS WITH CROSS-SECTION DEPENDENCE* 206
6.10 CONCIUDING REMARKS * 208 REFERENCES * 211 7 PARAMETRIC BINARY
CHOICE MODELS * 215 MICHAEI LECHNER, STEFAN LOIIIVIER AND THIERRY MAGNAC
7.1* INTRODUCTION* 215 7.2 RANDOM EFFECTS MODEIS UNDER STRICT
EXOGENEITY* 217 7.2.I* ERRORS ARE INDEPENDENT OVER TIME * 218 7.2.2* ONE
FACTOR ERROR TERMS * 219 7.2.3* GENERAI ERROR STRUCTURES* 221 7.2.4*
SIMUIATION METHODS * 223 7.2.5 HOW TO CHOOSE A RANDOM EFFECTS ESTIMATOR
FOR AN APPIICATION * 228 7.2.6* CORREIATED EFFECTS * 229 7.3 FIXED
EFFECTS MODEIS UNDER STRICT EXOGENEITY * 230 7.3.1* THE MODEI * 231
7.3.2* THE METHOD OF CONDITIONAI LIKEIIHOOD * 232 7.3.3 FIXED EFFECTS
MAXIMUM SCORE* 235 7.3.4 GMM ESTIMATION * 236 7.3.5* LARGE-T
APPROXIMATIONS * 237 7.4 DYNAMIC MODEIS* 238 7.4.1 DYNAMIC RANDOM
EFFECTS MODELS* 238 7.4.2 DYNAMIC FIXED EFFECTS MODEIS * 241 REFERENCES*
242 CONTENTS* XI PART II ADVANCED TOPICS 8 DYNAMIC MODELS FOR SHORT
PANELS * 249 MARK *. HARRIS, LASZIO MATYAS AND PATRICK SEVESTRE 8.1*
INTRODUCTION* 249 8.2 THE MODEI* 250 8.3* THE INCONSISTENCY OF
TRADITIONAL ESTIMATORS * 252 8.4 IV AND GMM ESTIMATORS * 255 8.4.1*
UNCORREIATED INDIVIDUAL EFFECTS: THE ORIGINAI BALESTRA*NERIOVE ESTIMATOR
AND ITS EXTENSIONS * 256 8.4.2* CORRELATED INDIVIDUAL EFFECTS * 257
8.4.3* SOME MONTE CARIO EVIDENCE * 269 8.5 THE MAXIMUM LIKEIIHOOD
ESTIMATOR * 270 8.6 TESTING IN DYNAMIC MODEIS* 272 8.6.1* TESTING THE
VAIIDITY OF INSTRUMENTS * 272 8.6.2* TESTING FOR UNOBSERVED EFFECTS *
273 8.6.3* TESTING FOR THE ABSENCE OF SERIAL CORREIATION IN ** 274
8.6.4* SIGNIFICANCE TESTING IN TWO-STEP VARIANTS * 275 REFERENCES* 276 9
UNIT ROOTS AND COINTEGRATION IN PANELS * 279 JOERG BREITUNG AND M. HASHEM
PESARAN 9.1* INTRODUCTION* 279 9.2* FIRST GENERATION PANEI UNIT ROOT
TESTS * 281 9.2.1* THE BASIC MODEI * 281 9.2.2* DERIVATION OF THE TESTS
* 282 9.2.3* NUII DISTRIBUTION OF THE TESTS * 284 9.2.4* ASYMPTOTIC
POWER OF THE TESTS * 287 9.2.5* HETEROGENEOUS TRENDS * 288 9.2.6*
SHORT-RUN DYNAMICS* 291 9.2.7* OTHER APPROACHES TO PANEI UNIT ROOT
TESTING * 293 9.3* SECOND GENERATION PANEL UNIT ROOT TESTS * 295 9.3.1*
CROSS-SECTION DEPENDENCE* 295 9.3.2* TESTS BASED ON GLS REGRESSIONS* 296
9.3.3* TEST STATISTICS BASED ON OLS REGRESSIONS * 297 9.3.4* OTHER
APPROACHES * 298 9.4* CROSS-UNIT COINTEGRATION* 299 9.5* FINITE SAMPIE
PROPERTIES OF PANEI UNIT ROOT TESTS * 301 9.6* PANEI COINTEGRATION:
GENERAI CONSIDERATIONS * 302 9.7 RESIDUAL-BASED APPROACHES TO PANEI
COINTEGRATION * 306 9.7.1* SPURIOUS REGRESSION * 306 9.7.2* TESTS OF
PANEI COINTEGRATION* 307 9.8* TESTS FOR MUITIPIE COINTEGRATION * 308
9.9* ESTIMATION OF COINTEGRATING REIATIONS IN PANEIS * 309 9.9.1* SINGIE
EQUATION ESTIMATORS * 309 9.9.2* SYSTEM ESTIMATORS* 312 XII* CONTENTS
9.10 CROSS-SECTION DEPENDENCE AND THE GLOBAI VAR* 313 9.11 CONCIUDING
REMARKS * 316 REFERENCES * 316 10 MEASUREMENT ERRORS AND SIMULTANEITY *
323 ERIK BIOERN AND JAYAIAKSHMI KRISHNAKUMAR 10.1 INTRODUCTION* 323 10.2
MEASUREMENT ERRORS AND PANEL DATA* 323 10.2.1 MODEI AND ORTHOGONAIITY
CONDITIONS * 325 10.2.2 IDENTIFICATION AND THE STRUCTURE OF THE SECOND
ORDER MOMENTS * 327 10.2.3 MOMENT CONDITIONS * 328 10.2.4 ESTIMATORS
CONSTRUCTED FROM PERIOD MEANS* 331 10.2.5 GMM ESTIMATION AND TESTING IN
THE GENERAI CASE * 332 10.2.6 ESTIMATION BY GMM, COMBINING DIFFERENCES
AND LEVEIS 335 10.2.7 EXTENSIONS: MODIFICATIONS * 343 10.2.8 CONCLUDING
REMARKS* 343 10.3 SIMUITANEITY AND PANEI DATA * 344 10.3.1 SEM WITH EC*
345 10.3.2 EXTENSIONS * 361 10.4 CONCIUSION* 364 REFERENCES* 365 11
PSEUDO - PANELS AND REPEATED CROSS - SECTIONS * 369 MARNO VERBEEK 11.1
INTRODUCTION* 369 11.2 ESTIMATION OF A LINEAR FIXED EFFECTS MODEI * 370
11.3 ESTIMATION OF A LINEAR DYNAMIC MODEL* 376 11.4 ESTIMATION OF A
BINARY CHOICE MODEI * 380 11.5 CONCIUDING REMARKS * 381 REFERENCES* 382
12 ATTRITION, SELECTION BIAS AND CENSORED REGRESSIONS * 385 BO HONORE,
FRANCIS VEIIA AND MARNO VERBEEK 12.1 INTRODUCTION* 385 12.2 CENSORING,
SAMPIE SEIECTION AND ATTRITION * 386 12.3 SAMPIE SELECTION AND ATTRITION
* 389 12.4 SAMPIE SEIECTION BIAS AND ROBUSTNESS OF STANDARD ESTIMATORS *
391 12.5 TOBIT AND CENSORED REGRESSION MODEIS* 393 12.5.1 RANDOM EFFECTS
TOBIT* 394 12.5.2 RANDOM EFFECTS TOBIT WITH ENDOGENOUS EXPIANATORY
VARIABIES* 396 12.5.3 DYNAMIC RANDOM EFFECTS TOBIT* 398 12.5.4 FIXED
EFFECTS TOBIT ESTIMATION* 399 12.5.5 SEMI-PARAMETRIC ESTIMATION* 401
CONTENTS* XIII 12.5.6 SEMI-PARAMETRIC ESTIMATION IN THE PRESENCE OF
LAGGED DEPENDENT VARIABLES* 402 12.6 MODELS OF SAMPLE SELECTION AND
ATTRITION* 402 12.6.1 MAXIMUM LIKELIHOOD ESTIMATORS * 403 12.6.2
TWO-STEP ESTIMATORS* 404 12.6.3 ALTERNATIVE SELECTION RULES * 407 12.6.4
TWO-STEP ESTIMATORS WITH FIXED EFFECTS* 408 12.6.5 SEMI-PARAMETRIC
SAMPLE SELECTION MODELS * 409 12.6.6 SEMI-PARAMETRIC ESTIMATION OF A
TYPE-3 TOBIT MODEL * 410 12.7 SOME EMPIRICAL APPLICATIONS * 412 12.7.1
ATTRITION IN EXPERIMENTAL DATA* 412 12.7.2 REAL WAGES OVER THE BUSINESS
CYCLE * 413 12.7.3 UNIONS AND WAGES* 415 REFERENCES* 416 13 SIMULATION
TECHNIQUES FOR PANELS: EFFICIENT IMPORTANCE SAMPLING . 419 ROMAN
LIESENFELD AND JEAN-FRANCOIS RICHARD 13.1 INTRODUCTION* 419 13.2
PSEUDORANDOM NUMBER GENERATION * 420 13.2.1 UNIVARIATE DISTRIBUTIONS *
421 13.2.2 MULTIVARIATE DISTRIBUTIONS* 424 13.3 IMPORTANCE SAMPLING* 426
13.3.1 GENERAL PRINCIPLE* 426 13.3.2 EFFICIENT IMPORTANCE SAMPLING * 428
13.3.3 MC SAMPLING VARIANCE OF (*)IS ESTIMATES * 431 13.3.4 GHK
SIMULATOR * 432 13.3.5 COMMON RANDOM NUMBERS* 432 13.4 SIMULATION-BASED
INFERENCE PROCEDURES* 434 13.4.1 INTEGRATION IN PANEL DATA MODELS * 434
13.4.2 SIMULATED LIKELIHOOD * 435 13.4.3 SIMULATED METHOD OF MOMENTS *
435 13.4.4 BAYESIAN POSTERIOR MOMENTS * 437 13.5 NUMERICAL PROPERTIES OF
SIMULATED ESTIMATORS * 437 13.6 EIS APPLICATION: LOGIT PANEL WITH
UNOBSERVED HETEROGENEITY* 439 13.6.1 THE MODEL * 439 13.6.2 EIS
EVALUATION OF THE LIKELIHOOD * 440 13.6.3 EMPIRICAL APPLICATION* 443
13.7 CONCLUSION* 445 13.8 APPENDIX: IMPLEMENTATION OF EIS FOR THE LOGIT
PANEL MODEL* 446 REFERENCES * 448 14 SEMI-PARAMETRIC AND NON-PARAMETRIC
METHODS IN PANEL DATA MODELS * 451 CHUNRONG AI AND QI LI 14.1
INTRODUCTION* 451 14.2 LINEAR PANEL DATA MODEL* 452 XIV* CONTENTS 14.2.1
ADDITIVE EFFECT* 452 14.2.2 MULTIPLICATIVE EFFECT* 460 14.3 NONLINEAR
PANEL DATA MODEL* 462 14.3.1 CENSORED REGRESSION MODEL* 462 14.3.2
DISCRETE CHOICE MODEL* 470 14.3.3 SAMPLE SELECTION MODEL* 474 14.4
CONCLUSION* 475 REFERENCES* 476 15 PANEL DATA MODELING AND INFERENCE: A
BAYESIAN PRIMER * 479 SIDDHARTHA CHIB 15.1 INTRODUCTION* 479 15.1.1
HIERARCHICAL PRIOR MODELING* 480 15.1.2 ELEMENTS OF MARKOV CHAIN MONTE
CARLO * 483 15.1.3 SOME BASIC BAYESIAN UPDATES* 486 15.1.4 BASIC VARIATE
GENERATORS * 488 15.2 CONTINUOUS RESPONSES * 489 15.2.1
GAUSSIAN*GAUSSIAN MODEL* 490 15.2.2 ROBUST MODELING OF BI :
STUDENT*STUDENT AND STUDENT-MIXTURE MODELS * 492 15.2.3
HETEROSKEDASTICITY* 495 15.2.4 SERIAL CORRELATION * 496 15.3 BINARY
RESPONSES * 497 15.4 OTHER OUTCOME TYPES* 501 15.4.1 CENSORED OUTCOMES *
501 15.4.2 COUNT RESPONSES* 502 15.4.3 MULTINOMIAL RESPONSES * 503 15.5
BINARY ENDOGENOUS REGRESSOR * 504 15.6 INFORMATIVE MISSINGNESS * 507
15.7 PREDICTION* 508 15.8 RESIDUAL ANALYSIS * 509 15.9 MODEL COMPARISONS
* 509 15.9.1 GAUSSIAN*GAUSSIAN MODEL* 512 15.9.2 GAUSSIAN*GAUSSIAN TOBIT
MODEL * 512 15.9.3 PANEL POISSON MODEL* 513 15.10 CONCLUSION* 513
REFERENCES * 514 16 TOPOOL OR NOT TO POOL? * 517 BADI H. BALTAGI,
GEORGES BRESSON AND ALAIN PIROTTE 16.1 INTRODUCTION* 517 16.2 TESTS FOR
POOLABILITY, PRETESTING AND STEIN-RULE METHODS* 521 16.2.1 TESTS FOR
POOLABILITY * 521 16.2.2 PRETESTING AND STEIN-RULE METHODS * 525 16.2.3
EXAMPLE* 526 16.3 HETEROGENEOUS ESTIMATORS * 527 CONTENTS* XV 16.3.1
AVERAGING ESTIMATORS * 529 16.3.2 BAYESIAN FRAMEWORK* 530 16.3.3 AN
EXAMPLE* 538 16.4 COMMENTS ON THE PREDICTIVE APPROACH * 541 16.4.1 FROM
THE POST-SAMPLE PREDICTIVE DENSITY* * 541 16.4.2 . TO THE GOOD
FORECAST PERFORMANCE OF THE HIERARCHICAL BAYES ESTIMATOR: AN EXAMPLE*
542 16.5 CONCLUSION* 544 REFERENCES* 545 17 DURATION MODELS AND POINT
PROCESSES * 547 JEAN-PIERRE FLORENS, DENIS FOUGERE AND MICHEL MOUCHART
17.1 MARGINAL DURATION MODELS* 548 17.1.1 DISTRIBUTION, SURVIVOR AND
DENSITY FUNCTIONS * 548 17.1.2 TRUNCATED DISTRIBUTIONS AND HAZARD
FUNCTIONS * 550 17.2 CONDITIONAL MODELS * 552 17.2.1 GENERAL
CONSIDERATIONS* 552 17.2.2 THE PROPORTIONAL HAZARD OR COX MODEL* 555
17.2.3 THE ACCELERATED TIME MODEL* 557 17.2.4 AGGREGATION AND
HETEROGENEITY* 558 17.2.5 ENDOGENEITY* 560 17.3 COMPETING RISKS AND
MULTIVARIATE DURATION MODELS * 561 17.3.1 MULTIVARIATE DURATIONS * 561
17.3.2 COMPETING RISKS MODELS: DEFINITIONS * 563 17.3.3 IDENTIFIABILITY
OF COMPETING RISKS MODELS* 566 17.3.4 RIGHT-CENSORING * 568 17.4
INFERENCE IN DURATION MODELS * 570 17.4.1 INTRODUCTION * 570 17.4.2
PARAMETRIC MODELS * 570 17.4.3 NON-PARAMETRIC AND SEMI-PARAMETRIC
MODELS* 576 17.5 COUNTING PROCESSES AND POINT PROCESSES * 579 17.5.1
DEFINITIONS * 579 17.5.2 STOCHASTIC INTENSITY, COMPENSATOR AND
LIKELIHOOD OF A COUNTING PROCESS * 581 17.6 POISSON, MARKOV AND
SEMI-MARKOV PROCESSES * 584 17.6.1 POISSON PROCESSES * 584 17.6.2 MARKOV
PROCESSES * 585 17.6.3 SEMI-MARKOV PROCESSES * 592 17.7 STATISTICAL
ANALYSIS OF COUNTING PROCESSES * 594 17.7.1 THE COX LIKELIHOOD * 596
17.7.2 THE MARTINGALE ESTIMATION OF THE INTEGRATED BASELINE INTENSITY *
597 17.8 CONCLUSIONS* 600 REFERENCES* 600 XVI* CONTENTS 18 GMM FOR PANEL
DATA COUNT MODELS * 603 FRANK WINDMEIJER 18.1 INTRODUCTION* 603 18.2 GMM
IN CROSS-SECTIONS* 604 18.3 PANEL DATA MODELS * 606 18.3.1 STRICTLY
EXOGENOUS REGRESSORS* 607 18.3.2 PREDETERMINED REGRESSORS * 608 18.3.3
ENDOGENOUS REGRESSORS * 609 18.3.4 DYNAMIC MODELS* 610 18.4 GMM* 612
18.5 APPLICATIONS AND SOFTWARE* 614 18.6 FINITE SAMPLE INFERENCE* 615
18.6.1 WALD TEST AND FINITE SAMPLE VARIANCE CORRECTION* 615 18.6.2
CRITERION-BASED TESTS * 617 18.6.3 CONTINUOUS UPDATING ESTIMATOR* 618
18.6.4 MONTE CARLO RESULTS * 619 REFERENCES* 623 19 SPATIAL PANEL
ECONOMETRICS * 625 LUC ANSELIN, JULIE LE GALLO AND HUBERT JAYET 19.1
INTRODUCTION* 625 19.2 SPATIAL EFFECTS * 626 19.2.1 SPATIAL WEIGHTS AND
SPATIAL LAG OPERATOR * 628 19.2.2 SPATIAL LAG MODEL* 630 19.2.3 SPATIAL
ERROR MODEL* 632 19.3 A TAXONOMY OF SPATIAL PANEL MODEL SPECIFICATIONS*
636 19.3.1 TEMPORAL HETEROGENEITY* 637 19.3.2 SPATIAL HETEROGENEITY *
639 19.3.3 SPATIO-TEMPORAL MODELS * 644 19.4 ESTIMATION OF SPATIAL PANEL
MODELS * 648 19.4.1 MAXIMUM LIKELIHOOD ESTIMATION * 648 19.4.2
INSTRUMENTAL VARIABLES AND GMM* 652 19.5 TESTING FOR SPATIAL DEPENDENCE*
654 19.5.1 LAGRANGE MULTIPLIER TESTS FOR SPATIAL LAG AND SPATIAL ERROR
DEPENDENCE IN POOLED MODELS* 655 19.5.2 TESTING FOR SPATIAL ERROR
CORRELATION IN PANEL DATA MODELS* 655 19.6 CONCLUSIONS* 656 REFERENCES*
657 PART III APPLICATIONS 20 FOREIGN DIRECT INVESTMENT: LESSONS FROM
PANEL DATA * 663 PIERRE BLANCHARD, CARL GAIGNE AND CLAUDE MATHIEU 20.1
INTRODUCTION* 663 20.2 A SIMPLE MODEL OF FD** 664 20.2.1 ASSUMPTIONS AND
PRELIMINARY RESULTS* 665 CONTENTS* XVII 20.2.2 TECHNOLOGY AND COUNTRY
CHARACTERISTICS AS DETERMINANTS OF FD** 666 20.3 ECONOMETRIC
IMPLEMENTATION AND DATA * 668 20.3.1 A GENERAL ECONOMETRIC MODEL * 669
20.3.2 FDI AND DATA ISSUES * 670 20.4 EMPIRICAL ESTIMATIONS: SELECTED
APPLICATIONS* 672 20.4.1 TESTING THE TRADE-OFF BETWEEN FD* AND EXPORTS*
672 20.4.2 TESTING THE ROLE OF TRADE POLICY IN FD** 677 20.4.3 TESTING
THE RELATIONSHIP BETWEEN FD* AND EXCHANGE RATE * 683 20.5 SOME RECENT
ECONOMETRIC ISSUES * 690 20.5.1 FDI, PANEL DATA AND SPATIAL
ECONOMETRICS* 690 20.5.2 EXCHANGE RATE, UNIT ROOTS AND COINTEGRATION*
691 REFERENCES * 693 21 STOCHASTIC FRONTIER ANALYSIS AND EFFICIENCY
ESTIMATION * 697 CHRISTOPHER CORNWELL AND PETER SCHMIDT 21.1 MEASUREMENT
OF FIRM EFFICIENCY* 698 21.2 INTRODUCTION TO SFA * 700 21.2.1 THE BASIC
SFA EMPIRICAL FRAMEWORK* 700 21.2.2 STOCHASTIC VS DETERMINISTIC
FRONTIERS * 700 21.2.3 OTHER FRONTIER FUNCTIONS * 702 21.2.4 SFA WITH
CROSS-SECTION DATA* 703 21.3 SFA WITH PANEL DATA * 704 21.3.1 MODELS
WITH TIME-INVARIANT INEFFICIENCY * 704 21.3.2 MODELS WITH TIME-VARYING
INEFFICIENCY * 714 21.4 APPLICATIONS * 718 21.4.1 EGYPTIAN TILE
MANUFACTURERS * 718 21.4.2 INDONESIAN RICE FARMERS * 720 21.5 CONCLUDING
REMARKS * 723 REFERENCES* 723 22 ECONOMETRIC ANALYSES OF LINKED
EMPLOYER*EMPLOYEE DATA * 727 JOHN M. ABOWD, FRANCIS KRAMARZ AND SIMON
WOODCOCK 22.1 INTRODUCTION* 727 22.2 A PROTOTYPICAL LONGITUDINAL LINKED
DATA SET * 729 22.2.1 MISSING DATA * 730 22.2.2 SAMPLING FROM LINKED
DATA* 732 22.3 LINEAR STATISTICAL MODELS WITH PERSON AND FIRM EFFECTS*
733 22.3.1 A GENERAL SPECIFICATION * 733 22.3.2 THE PURE PERSON AND FIRM
EFFECTS SPECIFICATION * 734 22.4 DEFINITION OF EFFECTS OF INTEREST* 735
22.4.1 PERSON EFFECTS AND UNOBSERVABLE PERSONAL HETEROGENEITY* 735
22.4.2 FIRM EFFECTS AND UNOBSERVABLE FIRM HETEROGENEITY* 736 22.4.3
FIRM-AVERAGE PERSON EFFECT* 737 CONTENTS* XIX 23.7 CONCLUSION* 790
REFERENCES * 791 24 DYNAMIC POLICY ANALYSIS * 795 JAAP H. ABBRING AND
JAMES J. HECKMAN 24.1 INTRODUCTION* 795 24.2 POLICY EVALUATION AND
TREATMENT EFFECTS * 796 24.2.1 THE EVALUATION PROBLEM* 796 24.2.2 THE
TREATMENT EFFECT APPROACH* 800 24.2.3 DYNAMIC POLICY EVALUATION * 801
24.3 DYNAMIC TREATMENT EFFECTS AND SEQUENTIAL RANDOMIZATION * 803 24.3.1
DYNAMIC TREATMENT EFFECTS * 803 24.3.2 POLICY EVALUATION AND DYNAMIC
DISCRETE-CHOICE ANALYSIS * 810 24.3.3 THE INFORMATION STRUCTURE OF
POLICIES * 813 24.3.4 SELECTION ON UNOBSERVABLES * 815 24.4 THE
EVENT-HISTORY APPROACH TO POLICY ANALYSIS* 816 24.4.1 TREATMENT EFFECTS
IN DURATION MODELS * 817 24.4.2 TREATMENT EFFECTS IN MORE GENERAL
EVENT-HISTORY MODELS * 823 24.4.3 A STRUCTURAL PERSPECTIVE * 828 24.5
DYNAMIC DISCRETE CHOICE AND DYNAMIC TREATMENT EFFECTS* 829 24.5.1
SEMI-PARAMETRIC DURATION MODELS AND COUNTERFACTUALS . * 831 24.5.2 A
SEQUENTIAL STRUCTURAL MODEL WITH OPTION VALUES* 844 24.5.3
IDENTIFICATION AT INFINITY * 850 24.5.4 COMPARING REDUCED-FORM AND
STRUCTURAL MODELS * 851 24.5.5 A SHORT SURVEY OF DYNAMIC DISCRETE-CHOICE
MODELS * 853 24.6 CONCLUSION* 857 REFERENCES* 857 25 ECONOMETRICS OF
INDIVIDUAL LABOR MARKET TRANSITIONS * 865 DENIS FOUGERE AND THIERRY
KAMIONKA 25.1 INTRODUCTION* 865 25.2 MULTI-SPELL MULTI-STATE MODELS *
867 25.2.1 GENERAL FRAMEWORK* 867 25.2.2 NON-PARAMETRIC AND PARAMETRIC
ESTIMATION * 872 25.2.3 UNOBSERVED HETEROGENEITY* 878 25.3 MARKOV
PROCESSES USING DISCRETE-TIME OBSERVATIONS * 882 25.3.1 THE
TIME-HOMOGENEOUS MARKOVIAN MODEL* 883 25.3.2 THE MOVER-STAYER MODEL* 893
25.4 CONCLUDING REMARKS * 901 REFERENCES* 902 XVIII* CONTENTS 22.4.4
PERSON-AVERAGE FIRM EFFECT* 737 22.4.5 INDUSTRY EFFECTS * 738 22.4.6
OTHER FIRM CHARACTERISTIC EFFECTS * 739 22.4.7 OCCUPATION EFFECTS AND
OTHER PERSON X FIRM INTERACTIONS* 739 22.5 ESTIMATION BY FIXED EFFECTS
METHODS* 739 22.5.1 ESTIMATION OF THE FIXED EFFECTS MODEL BY DIRECT
LEAST SQUARES * 739 22.5.2 CONSISTENT METHODS FOR SS AND Y (THE
FIRM-SPECIFIC RETURNS TO SENIORITY)* 743 22.6 THE MIXED MODEL* 744
22.6.1 REML ESTIMATION OF THE MIXED MODEL * 746 22.6.2 ESTIMATING THE
FIXED EFFECTS AND REALIZED RANDOM EFFECTS* 747 22.6.3 MIXED MODELS AND
CORRELATED RANDOM EFFECTS MODELS . * 748 22.7 MODELS OF HETEROGENEITY
BIASES IN INCOMPLETE MODELS * 750 22.7.1 OMISSION OF THE FIRM EFFECTS*
750 22.7.2 OMISSION OF THE PERSON EFFECTS * 751 22.7.3 INTER-INDUSTRY
WAGE DIFFERENTIALS * 752 22.8 ENDOGENOUS MOBILITY * 753 22.8.1 A
GENERALIZED LINEAR MIXED MODEL* 754 22.8.2 A MODEL OF WAGES, ENDOGENOUS
MOBILITY AND PARTICIPATION WITH PERSON AND FIRM EFFECTS * 755 22.8.3
STOCHASTIC ASSUMPTIONS * 756 22.9 CONCLUSION* 758 REFERENCES* 758 23
LIFE CYCLE LABOR SUPPLY AND PANEL DATA: A SURVEY * 761 BERTRAND KOEBEL,
FRANCOIS LAISNEY, WINF RI ED POHLMEIER AND MATTHIAS STAAT 23.1
INTRODUCTION* 761 23.2 THE BASIC MODEL OF LIFE CYCLE LABOR SUPPLY* 762
23.2.1 THE FRAMEWORK* 763 23.2.2 FIRST SPECIFICATIONS OF THE UTILITY
FUNCTION* 765 23.3 TAKING ACCOUNT OF UNCERTAINTY AND RISK* 768 23.3.1
FIRST DEVELOPMENTS* 768 23.3.2 RECENT CONTRIBUTIONS * 770 23.3.3
EMPIRICAL RESULTS * 773 23.4 VOLUNTARY AND INVOLUNTARY NON-PARTICIPATION
* 774 23.4.1 ACCOUNTING FOR THE PARTICIPATION DECISION * 775 23.4.2
UNEMPLOYMENT * 778 23.5 ALTERNATIVE PARAMETERIZATION AND IMPLICATIONS *
779 23.6 RELAXING SEPARABILITY ASSUMPTIONS * 783 23.6.1 RELAXING
WITHIN-PERIOD ADDITIVE SEPARABILITY* 783 23.6.2 RELAXING INTERTEMPORAL
SEPARABILITY IN PREFERENCES * 784 XX* CONTENTS 26 SOFTWARE REVIEW * 907
PIERRE BLANCHARD 26.1 INTRODUCTION* 907 26.2 GENERAL-PURPOSE ECONOMETRIC
PACKAGES * 908 26.2.1 EVIEWS (V. 5.1) * 908 26.2.2 LIMDEP (V. 8) WITH
NLOGIT (V. 3) * 912 26.2.3 RATS (V. 6) * 916 26.2.4 SAS (V. 9.1) * 920
26.2.5 STATA (V. 9) * 923 26.2.6 TSP (V. 5) * 927 26.3 HIGH-LEVEL MATRIX
PROGRAMMING LANGUAGES * 930 26.3.1 GAUSS (V. 5)* 930 26.3.2 OX (V. 3.4)
* 936 26.4 PERFORMANCE HINTS AND NUMERICAL ACCURACY EVALUATION * 941
26.4.1 SPEED COMPARISON * 941 26.4.2 NUMERICAL ACCURACY EVALUATIONS *
944 REFERENCES* 949 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author_GND | (DE-588)131764632 |
| building | Verbundindex |
| bvnumber | BV022395790 |
| classification_rvk | QH 244 QH 300 |
| ctrlnum | (OCoLC)315725871 (DE-599)BVBBV022395790 |
| dewey-full | 330.15195 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 330 - Economics |
| dewey-raw | 330.15195 |
| dewey-search | 330.15195 |
| dewey-sort | 3330.15195 |
| dewey-tens | 330 - Economics |
| discipline | Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Mathematik Wirtschaftswissenschaften |
| edition | 3. ed. |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02373nam a2200565 cb4500</leader><controlfield tag="001">BV022395790</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20100218 </controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">070420s2008 gw d||| |||| 00||| eng d</controlfield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">06,N02,0877</subfield><subfield code="2">dnb</subfield></datafield><datafield tag="016" ind1="7" ind2=" "><subfield code="a">97755435X</subfield><subfield code="2">DE-101</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783540758891</subfield><subfield code="9">978-3-540-75889-1</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">0387257543</subfield><subfield code="c">Gb. : ca. EUR 319.93, sfr 505.50</subfield><subfield code="9">0-387-25754-3</subfield></datafield><datafield tag="024" ind1="3" ind2=" "><subfield code="a">9780387257549</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)315725871</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV022395790</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rakddb</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="a">gw</subfield><subfield code="c">XA-DE-BE</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-355</subfield><subfield code="a">DE-N2</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-19</subfield><subfield code="a">DE-521</subfield><subfield code="a">DE-20</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">330.15195</subfield><subfield code="2">22//ger</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">330.15195</subfield><subfield code="2">22/ger</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">QH 244</subfield><subfield code="0">(DE-625)141558:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">QH 300</subfield><subfield code="0">(DE-625)141566:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">510</subfield><subfield code="2">sdnb</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">330</subfield><subfield code="2">sdnb</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The econometrics of panel data</subfield><subfield code="b">fundamentals and recent developments in theory and practice ; with ... 43 tables</subfield><subfield code="c">Lászlo Mátyás ... (ed.)</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">3. ed.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Berlin [u.a.]</subfield><subfield code="b">Springer</subfield><subfield code="c">2008</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XXVI, 950 S.</subfield><subfield code="b">graph. Darst.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Advanced studies in theoretical and applied econometrics</subfield><subfield code="v">46</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Panelanalyse</subfield><subfield code="0">(DE-588)4173172-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Ökonometrie</subfield><subfield code="0">(DE-588)4132280-0</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4151278-9</subfield><subfield code="a">Einführung</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Panelanalyse</subfield><subfield code="0">(DE-588)4173172-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="1" ind2="0"><subfield code="a">Ökonometrie</subfield><subfield code="0">(DE-588)4132280-0</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2="1"><subfield code="a">Panelanalyse</subfield><subfield code="0">(DE-588)4173172-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mátyás, László</subfield><subfield code="d">1957-</subfield><subfield code="e">Sonstige</subfield><subfield code="0">(DE-588)131764632</subfield><subfield code="4">oth</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe</subfield><subfield code="z">978-3-540-75892-1</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Advanced studies in theoretical and applied econometrics</subfield><subfield code="v">46</subfield><subfield code="w">(DE-604)BV000002376</subfield><subfield code="9">46</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://d-nb.info/985757493/04</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="q">text/html</subfield><subfield code="u">http://deposit.dnb.de/cgi-bin/dokserv?id=2738760&prov=M&dok_var=1&dok_ext=htm</subfield><subfield code="3">Inhaltstext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">OEBV Datenaustausch</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015604536&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-015604536</subfield></datafield></record></collection> |
| genre | (DE-588)4151278-9 Einführung gnd-content |
| genre_facet | Einführung |
| id | DE-604.BV022395790 |
| illustrated | Illustrated |
| index_date | 2024-07-02T17:16:28Z |
| indexdate | 2024-07-09T20:56:41Z |
| institution | BVB |
| isbn | 9783540758891 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015604536 |
| oclc_num | 315725871 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR DE-N2 DE-703 DE-19 DE-BY-UBM DE-521 DE-20 |
| owner_facet | DE-355 DE-BY-UBR DE-N2 DE-703 DE-19 DE-BY-UBM DE-521 DE-20 |
| physical | XXVI, 950 S. graph. Darst. |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Springer |
| record_format | marc |
| series | Advanced studies in theoretical and applied econometrics |
| series2 | Advanced studies in theoretical and applied econometrics |
| spelling | The econometrics of panel data fundamentals and recent developments in theory and practice ; with ... 43 tables Lászlo Mátyás ... (ed.) 3. ed. Berlin [u.a.] Springer 2008 XXVI, 950 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Advanced studies in theoretical and applied econometrics 46 Panelanalyse (DE-588)4173172-4 gnd rswk-swf Ökonometrie (DE-588)4132280-0 gnd rswk-swf (DE-588)4151278-9 Einführung gnd-content Panelanalyse (DE-588)4173172-4 s DE-604 Ökonometrie (DE-588)4132280-0 s Mátyás, László 1957- Sonstige (DE-588)131764632 oth Erscheint auch als Online-Ausgabe 978-3-540-75892-1 Advanced studies in theoretical and applied econometrics 46 (DE-604)BV000002376 46 http://d-nb.info/985757493/04 Inhaltsverzeichnis text/html http://deposit.dnb.de/cgi-bin/dokserv?id=2738760&prov=M&dok_var=1&dok_ext=htm Inhaltstext OEBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015604536&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | The econometrics of panel data fundamentals and recent developments in theory and practice ; with ... 43 tables Advanced studies in theoretical and applied econometrics Panelanalyse (DE-588)4173172-4 gnd Ökonometrie (DE-588)4132280-0 gnd |
| subject_GND | (DE-588)4173172-4 (DE-588)4132280-0 (DE-588)4151278-9 |
| title | The econometrics of panel data fundamentals and recent developments in theory and practice ; with ... 43 tables |
| title_auth | The econometrics of panel data fundamentals and recent developments in theory and practice ; with ... 43 tables |
| title_exact_search | The econometrics of panel data fundamentals and recent developments in theory and practice ; with ... 43 tables |
| title_exact_search_txtP | The econometrics of panel data fundamentals and recent developments in theory and practice ; with ... 43 tables |
| title_full | The econometrics of panel data fundamentals and recent developments in theory and practice ; with ... 43 tables Lászlo Mátyás ... (ed.) |
| title_fullStr | The econometrics of panel data fundamentals and recent developments in theory and practice ; with ... 43 tables Lászlo Mátyás ... (ed.) |
| title_full_unstemmed | The econometrics of panel data fundamentals and recent developments in theory and practice ; with ... 43 tables Lászlo Mátyás ... (ed.) |
| title_short | The econometrics of panel data |
| title_sort | the econometrics of panel data fundamentals and recent developments in theory and practice with 43 tables |
| title_sub | fundamentals and recent developments in theory and practice ; with ... 43 tables |
| topic | Panelanalyse (DE-588)4173172-4 gnd Ökonometrie (DE-588)4132280-0 gnd |
| topic_facet | Panelanalyse Ökonometrie Einführung |
| url | http://d-nb.info/985757493/04 http://deposit.dnb.de/cgi-bin/dokserv?id=2738760&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015604536&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000002376 |
| work_keys_str_mv | AT matyaslaszlo theeconometricsofpaneldatafundamentalsandrecentdevelopmentsintheoryandpracticewith43tables |
There is no print copy available.
Description