Microeconometrics: methods and applications
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge [u.a.]
Cambridge Univ. Press
2008
|
| Edition: | 7. print. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXII, 1034 S. graph. Darst. |
| ISBN: | 0521848059 9780521848053 |
Staff View
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| 100 | 1 | |a Cameron, Adrian Colin |d 1956- |e Verfasser |0 (DE-588)12870022X |4 aut | |
| 245 | 1 | 0 | |a Microeconometrics |b methods and applications |c A. Colin Cameron ; Pravin K. Trivedi |
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| 264 | 1 | |a Cambridge [u.a.] |b Cambridge Univ. Press |c 2008 | |
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| adam_text | Contents
List of Figures page
xv
List of Tables
xvii
Preface
xxi
I Preliminaries
1
Overview
3
1.1
Introduction
3
1.2
Distinctive Aspects of Microeconometrics
5
10
14
15
16
18
18
20
22
23
29
31
31
35
38
Microeconomic Data Structures
39
3.1
Introduction
39
3.2
Observational Data
40
3.3
Data from Social Experiments
48
3.4
Data from Natural Experiments
54
VII
1.3
Book Outline
1.4
How to Use This Book
1.5
Software
1.6
Notation and Conventions
Causal and Noncausal Models
2.1
Introduction
2.2
Structural Models
2.3
Exogeneity
2.4
Linear Simultaneous Equations Model
2.5
Identification Concepts
2.6
Single-Equation Models
2.7
Potential Outcome Model
2.8
Causal Modeling and Estimation Strategies
2.9
Bibliographic Notes
CONTENTS
3.5
Practical
Considerations
58
3.6
Bibliographic Notes
61
II Core Methods
4
Linear Models
65
4.1
Introduction
65
4.2
Regressions and Loss Functions
66
4.3
Example: Returns to Schooling
69
4.4
Ordinary Least Squares
70
4.5
Weighted Least Squares
81
4.6
Median and Quantile Regression
85
4.7
Model Misspecification
90
4.8
Instrumental Variables
95
4.9
Instrumental Variables in Practice
103
4.10
Practical Considerations
112
4.11
Bibliographic Notes
112
5
Maximum Likelihood and Nonlinear Least-Squares Estimation
116
5.1
Introduction
116
5.2
Overview of Nonlinear Estimators
117
5.3
Extrémům
Estimators
124
5.4
Estimating Equations
133
5.5
Statistical Inference
135
5.6
Maximum Likelihood
139
5.7
Quasi-Maximum Likelihood
146
5.8
Nonlinear Least Squares
150
5.9
Example: ML and NLS Estimation
159
5.10
Practical Considerations
163
5.11
Bibliographic Notes
163
6
Generalized Method of Moments and Systems Estimation
166
6.1
Introduction
166
6.2
Examples
167
6.3
Generalized Method of Moments
172
6.4
Linear Instrumental Variables
183
6.5
Nonlinear Instrumental Variables
192
6.6
Sequential Two-Step m-Estimation
200
6.7
Minimum Distance Estimation
202
6.8
Empirical Likelihood
203
6.9
Linear Systems of Equations
206
6.10
Nonlinear Sets of Equations
214
6.11
Practical Considerations
219
6.12
Bibliographic Notes
220
viii
CONTENTS
7
Hypothesis
Tests 223
7.1
Introduction
223
224
233
241
243
246
250
254
256
257
259
259
260
271
274
278
285
287
291
292
9 Semiparametric
Methods
294
9.1
Introduction
294
9.2
Nonparametric Example: Hourly Wage
295
9.3
Kernel Density Estimation
298
9.4
Nonparametric Local Regression
307
9.5
Kernel Regression
311
9.6
Alternative Nonparametric Regression
319
Estimators
9.7
Semiparametric Regression
322
9.8
Derivations of Mean and Variance
330
of Kernel Estimators
9.9
Practical Considerations
333
9.10
Bibliographic Notes
333
10
Numerical Optimization
336
10.1
Introduction
336
10.2
General Considerations
336
10.3
Specific Methods
341
10.4
Practical Considerations
348
10.5
Bibliographic Notes
352
ix
7.2
Wald Test
7.3
Likelihood-Based Tests
7.4
Example: Likelihood-Based Hypothesis
Tests
7.5
Tests in Non-ML Settings
7.6
Power and Size of Tests
7.7
Monte Carlo Studies
7.8
Bootstrap Example
7.9
Practical Considerations
7.10
Bibliographic Notes
8
Specification Tests and Model Selection
8.1
Introduction
8.2
m-Tests
8.3
Hausman Test
8.4
Tests for Some Common Misspecifications
8.5
Discriminating between Nonnested
Models
8.6
Consequences of Testing
8.7
Model Diagnostics
8.8
Practical Considerations
8.9
Bibliographic Notes
CONTENTS
III Simulation-Based Methods
11
Bootstrap Methods
357
11.1
Introduction
357
358
366
368
373
376
382
382
12
Simulation-Based Methods
384
384
385
387
393
398
404
406
410
416
13
Bayesian Methods
419
13.1
Introduction
419
13.2
Bayesian Approach
420
13.3
Bayesian Analysis of Linear Regression
435
13.4
Monte Carlo Integration
443
13.5
Markov Chain Monte Carlo Simulation
445
13.6
MCMC Example: Gibbs Sampler for
SUR
452
13.7
Data Augmentation
454
13.8
Bayesian Model Selection
456
13.9
Practical Considerations
458
13.10
Bibliographic Notes
458
IV Models for Cross-Section Data
14
Binary Outcome Models
463
14.1
Introduction
463
14.2
Binary Outcome Example: Fishing Mode Choice
464
14.3
Logit and
Probit
Models
465
14.4
Latent Variable Models
475
14.5
Choice-Based Samples
478
14.6
Grouped and Aggregate Data
480
14.7
Semiparametric Estimation
482
11.2
Bootstrap Summary
11.3
Bootstrap Example
11.4
Bootstrap Theory
11.5
Bootstrap Extensions
11.6
Bootstrap Applications
11.7
Practical Considerations
11.8
Bibliographic Notes
Simulation-Based Methods
12.1
Introduction
12.2
Examples
12.3
Basics of Computing Integrals
12.4
Maximum Simulated Likelihood Estimation
12.5
Moment-Based Simulation Estimation
12.6
Indirect Inference
12.7
Simulators
12.8
Methods of Drawing Random
Variâtes
12.9
Bibliographic Notes
CONTENTS
14.8
Derivation of Logit from Type I Extreme Value
486
14.9
Practical Considerations
487
14.10
Bibliographic Notes
487
15
Multinomial Models
490
15.1
Introduction
490
15.2
Example: Choice of Fishing Mode
491
15.3
General Results
495
15.4
Multinomial Logit
500
15.5
Additive Random Utility Models
504
15.6
Nested Logit
507
15.7
Random Parameters Logit
512
15.8
Multinomial
Probit
516
15.9
Ordered, Sequential, and Ranked Outcomes
519
15.10
Mul ti variate
Discrete Outcomes
521
15.11
Semiparametric Estimation
523
15.12
Derivations for MNL, CL, and NL Models
524
15.13
Practical Considerations
527
15.14
Bibliographic Notes
528
16
Tobit and Selection Models
529
16.1
Introduction
529
16.2
Censored and Truncated Models
530
16.3
Tobit Model
536
16.4
Two-Part Model
544
16.5
Sample Selection Models
546
16.6
Selection Example: Health Expenditures
553
16.7
Roy Model
555
16.8
Structural Models
558
16.9
Semiparametric Estimation
562
16.10
Derivations for the Tobit Model
566
16.11
Practical Considerations
568
16.12
Bibliographic Notes
569
17
Transition Data: Survival Analysis
573
17.1
Introduction
573
17.2
Example: Duration of Strikes
574
17.3
Basic Concepts
576
17.4
Censoring
579
17.5
Nonparametric Models
580
17.6
Parametric Regression Models
584
17.7
Some Important Duration Models
591
17.8
Cox PH Model
592
17.9
Time-Varying Regressors
597
17.10
Discrete-Time Proportional Hazards
600
17.11
Duration Example: Unemployment Duration
603
xi
CONTENTS
17.12
Practical
Considerations
608
17.13
Bibliographic Notes
608
18
Mixture Models and Unobserved Heterogeneity
611
18.1
Introduction
611
18.2
Unobserved Heterogeneity and Dispersion
612
18.3
Identification in Mixture Models
618
18.4
Specification of the Heterogeneity Distribution
620
18.5
Discrete Heterogeneity and Latent Class Analysis
621
18.6
Stock and Flow Sampling
625
18.7
Specification Testing
628
18.8
Unobserved Heterogeneity Example: Unemployment Duration
632
18.9
Practical Considerations
637
18.10
Bibliographic Notes
637
19
Models of Multiple Hazards
640
19.1
Introduction
640
19.2
Competing Risks
642
19.3
Joint Duration Distributions
648
19.4
Multiple Spells
655
19.5
Competing Risks Example: Unemployment Duration
658
19.6
Practical Considerations
662
19.7
Bibliographic Notes
663
20
Models of Count Data
665
20.1
Introduction
665
20.2
Basic Count Data Regression
666
20.3
Count Example: Contacts with Medical Doctor
671
20.4
Parametric Count Regression Models
674
20.5
Partially Parametric Models
682
20.6
Multivariate Counts and Endogenous Regressors
685
20.7
Count Example: Further Analysis
690
20.8
Practical Considerations
690
20.9
Bibliographic Notes
691
V Models for Panel Data
21
Linear Panel Models: Basics
697
21.1
Introduction
697
21.2
Overview of Models and Estimators
698
21.3
Linear Panel Example: Hours and Wages
708
21.4
Fixed Effects versus Random Effects Models
715
21.5
Pooled Models
720
21.6
Fixed Effects Model
726
21.7
Random Effects Model
734
Xli
CONTENTS
21.8
Modeling Issues
737
21.9
Practical Considerations
740
21.10
Bibliographic Notes
740
22
Linear Panel Models: Extensions
743
22.1
Introduction
743
22.2
GMM Estimation of Linear Panel Models
744
22.3
Panel GMM Example: Hours and Wages
754
22.4
Random and Fixed Effects Panel GMM
756
22.5
Dynamic Models
763
22.6
Difference-in-Differences Estimator
768
22.7
Repeated Cross Sections and
Pseudo
Panels
770
22.8
Mixed Linear Models
774
22.9
Practical Considerations
776
22.10
Bibliographic Notes
777
23
Nonlinear Panel Models
779
23.1
Introduction
779
23.2
General Results
779
23.3
Nonlinear Panel Example: Patents and R&D
792
23.4
Binary Outcome Data
795
23.5
Tobit and Selection Models
800
23.6
Transition Data
801
23.7
Count Data
802
23.8
Semiparametric Estimation
808
23.9
Practical Considerations
808
23.10
Bibliographic Notes
809
VI Further Topics
24
Stratified and Clustered Samples
813
24.1
Introduction
813
24.2
Survey Sampling
814
24.3
Weighting
817
24.4
Endogenous Stratification
822
24.5
Clustering
829
24.6
Hierarchical Linear Models
845
24.7
Clustering Example: Vietnam Health Care Use
848
24.8
Complex Surveys
853
24.9
Practical Considerations
857
24.10
Bibliographic Notes
857
25
Treatment Evaluation
860
25.1
Introduction
860
25.2
Setup and Assumptions
862
xiii
CONTENTS
25.3
Treatment
Effects and Selection Bias
865
25.4
Matching and Propensity Score Estimators
871
25.5
Differences-in-Differences Estimators
878
25.6
Regression Discontinuity Design
879
25.7
Instrumental Variable Methods
883
25.8
Example: The Effect of Training on Earnings
889
25.9
Bibliographic Notes
896
26
Measurement Error Models
899
26.1
Introduction
899
26.2
Measurement Error in Linear Regression
900
26.3
Identification Strategies
905
26.4
Measurement Errors in Nonlinear Models
911
26.5
Attenuation Bias Simulation Examples
919
26.6
Bibliographic Notes
920
27
Missing Data and Imputation
923
27.1
Introduction
923
27.2
Missing Data Assumptions
925
27.3
Handling Missing Data without Models
928
27.4
Observed-Data Likelihood
929
27.5
Regression-Based Imputation
930
27.6
Data Augmentation and MCMC
932
27.7
Multiple Imputation
934
27.8
Missing Data MCMC Imputation Example
935
27.9
Practical Considerations
939
27.10
Bibliographic Notes
940
A Asymptotic Theory
943
A.I Introduction
943
A.2 Convergence in Probability
944
A.3 Laws of Large Numbers
947
A.4 Convergence in Distribution
948
A.5 Central Limit Theorems
949
A.6 Multivariate Normal Limit Distributions
951
A.7 Stochastic Order of Magnitude
954
A.8 Other Results
955
A.9 Bibliographic Notes
956
В
Making Pseudo-Random Draws
957
References
961
Index
999
XIV
|
| any_adam_object | 1 |
| author | Cameron, Adrian Colin 1956- Trivedi, Pravin K. 1943- |
| author_GND | (DE-588)12870022X (DE-588)118054791 |
| author_facet | Cameron, Adrian Colin 1956- Trivedi, Pravin K. 1943- |
| author_role | aut aut |
| author_sort | Cameron, Adrian Colin 1956- |
| author_variant | a c c ac acc p k t pk pkt |
| building | Verbundindex |
| bvnumber | BV035602084 |
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| callnumber-subject | HB - Economic Theory and Demography |
| classification_rvk | QC 100 QH 310 QH 320 |
| ctrlnum | (OCoLC)552537115 (DE-599)BVBBV035602084 |
| discipline | Wirtschaftswissenschaften |
| edition | 7. print. |
| format | Book |
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| genre | 1\p (DE-588)4123623-3 Lehrbuch gnd-content |
| genre_facet | Lehrbuch |
| id | DE-604.BV035602084 |
| illustrated | Illustrated |
| indexdate | 2025-02-20T06:36:45Z |
| institution | BVB |
| isbn | 0521848059 9780521848053 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017657111 |
| oclc_num | 552537115 |
| open_access_boolean | |
| owner | DE-M382 DE-634 DE-863 DE-BY-FWS DE-19 DE-BY-UBM |
| owner_facet | DE-M382 DE-634 DE-863 DE-BY-FWS DE-19 DE-BY-UBM |
| physical | XXII, 1034 S. graph. Darst. |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Cambridge Univ. Press |
| record_format | marc |
| spellingShingle | Cameron, Adrian Colin 1956- Trivedi, Pravin K. 1943- Microeconometrics methods and applications Mikroökonometrie stw Mikroökonomie - Ökonometrisches Modell Theorie stw aMicroeconomics xEconometric models Ökonometrie (DE-588)4132280-0 gnd Ökonometrisches Modell (DE-588)4043212-9 gnd Mikroökonomisches Modell (DE-588)4125908-7 gnd Mikroökonomie (DE-588)4039225-9 gnd |
| subject_GND | (DE-588)4132280-0 (DE-588)4043212-9 (DE-588)4125908-7 (DE-588)4039225-9 (DE-588)4123623-3 |
| title | Microeconometrics methods and applications |
| title_auth | Microeconometrics methods and applications |
| title_exact_search | Microeconometrics methods and applications |
| title_full | Microeconometrics methods and applications A. Colin Cameron ; Pravin K. Trivedi |
| title_fullStr | Microeconometrics methods and applications A. Colin Cameron ; Pravin K. Trivedi |
| title_full_unstemmed | Microeconometrics methods and applications A. Colin Cameron ; Pravin K. Trivedi |
| title_short | Microeconometrics |
| title_sort | microeconometrics methods and applications |
| title_sub | methods and applications |
| topic | Mikroökonometrie stw Mikroökonomie - Ökonometrisches Modell Theorie stw aMicroeconomics xEconometric models Ökonometrie (DE-588)4132280-0 gnd Ökonometrisches Modell (DE-588)4043212-9 gnd Mikroökonomisches Modell (DE-588)4125908-7 gnd Mikroökonomie (DE-588)4039225-9 gnd |
| topic_facet | Mikroökonometrie Mikroökonomie - Ökonometrisches Modell Theorie aMicroeconomics xEconometric models Ökonometrie Ökonometrisches Modell Mikroökonomisches Modell Mikroökonomie Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017657111&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT cameronadriancolin microeconometricsmethodsandapplications AT trivedipravink microeconometricsmethodsandapplications |
Indexes
THWS Würzburg Zentralbibliothek Lesesaal
| Call Number: |
1000 QH 320 C182(.008)st |
|---|---|
| Copy 1 | ausleihbar Available Place a Hold |