Analysis of microdata:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2009
|
| Ausgabe: | 2. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturverz. S. [301] - 309 |
| Beschreibung: | XIV, 343 S. graph. Darst. |
| ISBN: | 9783540927471 |
Internformat
MARC
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| 100 | 1 | |a Winkelmann, Rainer |d 1963- |e Verfasser |0 (DE-588)131412434 |4 aut | |
| 245 | 1 | 0 | |a Analysis of microdata |c Rainer Winkelmann ; Stefan Boes |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 2009 | |
| 300 | |a XIV, 343 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Literaturverz. S. [301] - 309 | ||
| 650 | 7 | |a Data-analyse |2 gtt | |
| 650 | 7 | |a Maximum-Likelihood-Methode |2 stw | |
| 650 | 7 | |a Mikrodaten |2 stw | |
| 650 | 7 | |a Mikroökonometrie |2 stw | |
| 650 | 7 | |a Nichtparametrisches Verfahren |2 stw | |
| 650 | 4 | |a Personenbezogene Daten - Qualitative Daten - Lineare Regression - Maximum-Likelihood-Schätzung | |
| 650 | 7 | |a Qualitatives Verfahren |2 stw | |
| 650 | 7 | |a Statistische Bestandsanalyse |2 stw | |
| 650 | 7 | |a Statistische Methodenlehre |2 stw | |
| 650 | 7 | |a Theorie |2 stw | |
| 650 | 0 | 7 | |a Lineare Regression |0 (DE-588)4167709-2 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Maximum-Likelihood-Schätzung |0 (DE-588)4194624-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Qualitative Daten |0 (DE-588)4176592-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Personenbezogene Daten |0 (DE-588)4173908-5 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Personenbezogene Daten |0 (DE-588)4173908-5 |D s |
| 689 | 0 | 1 | |a Qualitative Daten |0 (DE-588)4176592-8 |D s |
| 689 | 0 | 2 | |a Lineare Regression |0 (DE-588)4167709-2 |D s |
| 689 | 0 | 3 | |a Maximum-Likelihood-Schätzung |0 (DE-588)4194624-8 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Boes, Stefan |e Verfasser |4 aut | |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017068346&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-017068346 | ||
Datensatz im Suchindex
| _version_ | 1804138546751078400 |
|---|---|
| adam_text | Contents
1
Introduction
............................................... 1
1.1
What Are
Microdata?.................................... 1
1.2
Types of
Microdata...................................... 4
1.2.1
Qualitative Data
.................................. 4
1.2.2
Quantitative Data
................................. 6
1.3
Why Not Linear Regression?
.............................. 8
1.4
Common Elements of
Microdata
Models
.................... 11
1.5
Examples
............................................... 12
1.5.1
Determinants of Fertility
........................... 12
1.5.2
Secondary School Choice
........................... 16
1.5.3
Female Hours of Work and Wages
................... 18
1.6
Overview of the Book
.................................... 20
2
From Regression to Probability Models
.................... 21
2.1
Introduction
............................................ 21
2.2
Conditional Probability Functions
......................... 23
2.2.1
Definition
........................................ 23
2.2.2
Estimation
....................................... 25
2.2.3
Interpretation
..................................... 26
2.3
Probability and Probability Distributions
................... 30
2.3.1
Axioms of Probability
.............................. 30
2.3.2
Univariate Random Variables
....................... 31
2.3.3
Multivariate Random Variables
..................... 32
2.3.4
Conditional Probability Models
..................... 36
2.4
Further Exercises
........................................ 41
3
Maximum Likelihood Estimation
.......................... 47
3.1
Introduction
............................................ 47
3.2
Likelihood Function
..................................... 48
3.2.1
Score Function and Hessian Matrix
.................. 50
3.2.2
Conditional Models
................................ 52
VIII Contents
3.2.3
Maximization
..................................... 52
3.3
Properties of the Maximum Likelihood Estimator
............ 55
3.3.1
Expected Score
................................... 56
3.3.2
Consistency
...................................... 57
3.3.3
Information Matrix
................................ 59
3.3.4
Asymptotic Distribution
........................... 61
3.3.5
Covariance Matrix
................................. 62
3.4
Normal Linear Model
.................................... 65
3.5
Further Aspects of Maximum Likelihood Estimation
......... 69
3.5.1
Invariance
and Delta Method
....................... 69
3.5.2
Numerical Optimization
............................ 72
3.5.3
Identification
..................................... 77
3.5.4
Quasi Maximum Likelihood
......................... 78
3.6
Testing
................................................. 79
3.6.1
Introduction
...................................... 79
3.6.2
Restricted Maximum Likelihood
..................... 82
3.6.3 Wald Test........................................ 84
3.6.4
Likelihood Ratio Test
.............................. 86
3.6.5
Score Test
........................................ 89
3.6.6
Model Selection
................................... 90
3.6.7
Goodness-of-Fit
................................... 91
3.7
Pros and Cons of Maximum Likelihood
..................... 92
3.8
Further Exercises
........................................ 93
4
Binary Response Models
.................................. 97
4.1
Introduction
............................................ 97
4.2
Models for Binary Response Variables
...................... 99
4.2.1
General Framework
................................ 99
4.2.2
Linear Probability Model
...........................100
4.2.3
Probit
Model
.....................................102
4.2.4
Logit Model
......................................104
4.2.5
Interpretation of Parameters
........................106
4.3
Discrete Choice Models
..................................109
4.4
Estimation
.............................................113
4.4.1
Maximum Likelihood
..............................113
4.4.2
Perfect Prediction
.................................116
4.4.3
Properties of the Estimator
.........................117
4.4.4
Endogenous Regressors in Binary Response Models
.... 119
4.4.5
Estimation of Marginal Effects
......................122
4.5
Goodness-of-Fit
.........................................125
4.6
Non-Standard Sampling Schemes
..........................130
4.6.1
Stratified Sampling
................................130
4.6.2
Exogenous Stratification
...........................130
4.6.3
Endogenous Stratification
..........................131
4.7
Flexible Specification of Binary Response Models
............132
Contents
IX
4.8
Further Exercises
........................................135
Multinomial Response Models
.............................141
5.1
Introduction
............................................141
5.2
Multinomial Logit Model
.................................143
5.2.1
Basic Model
......................................143
5.2.2
Estimation
.......................................144
5.2.3
Interpretation of Parameters
........................148
5.3
Conditional Logit Model
.................................154
5.3.1
Introduction
......................................154
5.3.2
General Model of Choice
...........................155
5.3.3
Modeling Conditional Logits
........................156
5.3.4
Interpretation of Parameters
........................159
5.3.5
Independence of Irrelevant Alternatives
..............163
5.4
Generalized Multinomial Response Models
..................164
5.4.1
Multinomial
Probit
Model
..........................165
5.4.2
Mixed Logit Models
...............................168
5.4.3
Nested Logit Models
...............................169
5.5
Further Exercises
........................................170
Ordered Response Models
.................................175
6.1
Introduction
............................................175
6.2
Standard Ordered Response Models
........................178
6.2.1
General Framework
................................178
6.2.2
Ordered
Probit
Model
.............................180
6.2.3
Ordered Logit Model
..............................181
6.2.4
Estimation
.......................................183
6.2.5
Interpretation of Parameters
........................183
6.2.6
Single Indices and Parallel Regression
................190
6.3
Generalized Threshold Models
............................192
6.3.1
Generalized Ordered Logit and
Probit
Models
.........192
6.3.2
Interpretation of Parameters
........................193
6.4
Sequential Models
.......................................198
6.4.1
Modeling Conditional Transitions
...................198
6.4.2
Generalized Conditional Transition Probabilities
......200
6.4.3
Marginal Effects
...................................201
6.4.4
Estimation
.......................................202
6.5
Interval Data
...........................................204
6.6
Further Exercises
........................................206
Limited Dependent Variables
..............................211
7.1
Introduction
............................................211
7.1.1
Corner Solution Outcomes
..........................212
7.1.2
Sample Selection Models
...........................213
7.1.3
Treatment Effect Models
...........................214
X
Contents
7.2 Tobin s Corner
Solution
Model
............................215
7.2.1
Introduction
......................................215
7.2.2
Tobit
Model......................................
216
7.2.3
Truncated
Normal Distribution
.....................218
7.2.4
Inverse Mills Ratio
and its Properties................
219
7.2.5
Interpretation of the Tobit Model
...................222
7.2.6
Comparing Tobit and OLS
.........................225
7.2.7
Further Specification Issues
.........................227
7.3
Sample Selection Models
.................................228
7.3.1
Introduction
......................................228
7.3.2
Censored Regression Model
.........................230
7.3.3
Estimation of the Censored Regression Model
.........232
7.3.4
Truncated Regression Model
........................234
7.3.5
Incidental Censoring
...............................235
7.3.6
Example: Estimating a Labor Supply Model
..........242
7.4
Treatment Effect Models
.................................244
7.4.1
Introduction
......................................244
7.4.2
Endogenous Binary Variable
........................247
7.4.3
Switching Regression Model
........................249
7.5
Further Exercises
........................................251
8
Event History Models
.....................................255
8.1
Introduction
............................................255
8.2
Duration Models
........................................258
8.2.1
Introduction
......................................258
8.2.2
Basic Concepts
....................................258
8.2.3
Discrete Time Duration Models
.....................263
8.2.4
Continuous Time Duration Models
..................266
8.2.5
Key Element: Hazard Function
......................269
8.2.6
Duration Dependence
..............................271
8.2.7
Unobserved Heterogeneity
..........................275
8.3
Count Data Models
......................................283
8.3.1
Poisson
Regression Model
..........................283
8.3.2
Unobserved Heterogeneity
..........................288
8.3.3
Efficient versus Robust Estimation
..................293
8.3.4
Censoring and Truncation
..........................293
8.3.5
Hurdle and Zero-Inflated Count Data Models
.........295
8.4
Further Exercises
........................................298
References
.....................................................301
Solutions to Selected Exercises
................................311
Index
..........................................................339
|
| any_adam_object | 1 |
| author | Winkelmann, Rainer 1963- Boes, Stefan |
| author_GND | (DE-588)131412434 |
| author_facet | Winkelmann, Rainer 1963- Boes, Stefan |
| author_role | aut aut |
| author_sort | Winkelmann, Rainer 1963- |
| author_variant | r w rw s b sb |
| building | Verbundindex |
| bvnumber | BV035262849 |
| classification_rvk | QH 320 |
| ctrlnum | (OCoLC)312701652 (DE-599)DNB991447646 |
| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | 2. ed. |
| format | Book |
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| id | DE-604.BV035262849 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T21:29:55Z |
| institution | BVB |
| isbn | 9783540927471 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017068346 |
| oclc_num | 312701652 |
| open_access_boolean | |
| owner | DE-N2 DE-355 DE-BY-UBR DE-703 DE-M382 DE-83 DE-19 DE-BY-UBM DE-11 DE-2070s |
| owner_facet | DE-N2 DE-355 DE-BY-UBR DE-703 DE-M382 DE-83 DE-19 DE-BY-UBM DE-11 DE-2070s |
| physical | XIV, 343 S. graph. Darst. |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Springer |
| record_format | marc |
| spelling | Winkelmann, Rainer 1963- Verfasser (DE-588)131412434 aut Analysis of microdata Rainer Winkelmann ; Stefan Boes 2. ed. Berlin [u.a.] Springer 2009 XIV, 343 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. [301] - 309 Data-analyse gtt Maximum-Likelihood-Methode stw Mikrodaten stw Mikroökonometrie stw Nichtparametrisches Verfahren stw Personenbezogene Daten - Qualitative Daten - Lineare Regression - Maximum-Likelihood-Schätzung Qualitatives Verfahren stw Statistische Bestandsanalyse stw Statistische Methodenlehre stw Theorie stw Lineare Regression (DE-588)4167709-2 gnd rswk-swf Maximum-Likelihood-Schätzung (DE-588)4194624-8 gnd rswk-swf Qualitative Daten (DE-588)4176592-8 gnd rswk-swf Personenbezogene Daten (DE-588)4173908-5 gnd rswk-swf Personenbezogene Daten (DE-588)4173908-5 s Qualitative Daten (DE-588)4176592-8 s Lineare Regression (DE-588)4167709-2 s Maximum-Likelihood-Schätzung (DE-588)4194624-8 s DE-604 Boes, Stefan Verfasser aut Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017068346&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Winkelmann, Rainer 1963- Boes, Stefan Analysis of microdata Data-analyse gtt Maximum-Likelihood-Methode stw Mikrodaten stw Mikroökonometrie stw Nichtparametrisches Verfahren stw Personenbezogene Daten - Qualitative Daten - Lineare Regression - Maximum-Likelihood-Schätzung Qualitatives Verfahren stw Statistische Bestandsanalyse stw Statistische Methodenlehre stw Theorie stw Lineare Regression (DE-588)4167709-2 gnd Maximum-Likelihood-Schätzung (DE-588)4194624-8 gnd Qualitative Daten (DE-588)4176592-8 gnd Personenbezogene Daten (DE-588)4173908-5 gnd |
| subject_GND | (DE-588)4167709-2 (DE-588)4194624-8 (DE-588)4176592-8 (DE-588)4173908-5 |
| title | Analysis of microdata |
| title_auth | Analysis of microdata |
| title_exact_search | Analysis of microdata |
| title_full | Analysis of microdata Rainer Winkelmann ; Stefan Boes |
| title_fullStr | Analysis of microdata Rainer Winkelmann ; Stefan Boes |
| title_full_unstemmed | Analysis of microdata Rainer Winkelmann ; Stefan Boes |
| title_short | Analysis of microdata |
| title_sort | analysis of microdata |
| topic | Data-analyse gtt Maximum-Likelihood-Methode stw Mikrodaten stw Mikroökonometrie stw Nichtparametrisches Verfahren stw Personenbezogene Daten - Qualitative Daten - Lineare Regression - Maximum-Likelihood-Schätzung Qualitatives Verfahren stw Statistische Bestandsanalyse stw Statistische Methodenlehre stw Theorie stw Lineare Regression (DE-588)4167709-2 gnd Maximum-Likelihood-Schätzung (DE-588)4194624-8 gnd Qualitative Daten (DE-588)4176592-8 gnd Personenbezogene Daten (DE-588)4173908-5 gnd |
| topic_facet | Data-analyse Maximum-Likelihood-Methode Mikrodaten Mikroökonometrie Nichtparametrisches Verfahren Personenbezogene Daten - Qualitative Daten - Lineare Regression - Maximum-Likelihood-Schätzung Qualitatives Verfahren Statistische Bestandsanalyse Statistische Methodenlehre Theorie Lineare Regression Maximum-Likelihood-Schätzung Qualitative Daten Personenbezogene Daten |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017068346&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT winkelmannrainer analysisofmicrodata AT boesstefan analysisofmicrodata |