Econometrics:
Saved in:
| Format: | Electronic eBook |
|---|---|
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
2008
|
| Edition: | 4. ed. |
| Subjects: | |
| Online Access: | BTU01 FAN01 FHI01 FHM01 FHR01 FKE01 FNU01 HWR01 UBG01 UBR01 UBT01 UBY01 Inhaltsverzeichnis Volltext Inhaltsverzeichnis |
| Physical Description: | 1 Online-Ressource (XV, 392 S.) graph. Darst. |
| ISBN: | 9783540765165 |
| DOI: | 10.1007/978-3-540-76516-5 |
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Record in the Search Index
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| adam_text | Table of Contents
Preface VII
Table of Contents XI
Part I 1
1 What Is Econometrics? 3
1.1 Introduction 3
1.2 A Brief History 5
1.3 Critiques of Econometrics 7
1.4 Looking Ahead 8
Notes 9
References 10
2 Basic Statistical Concepts 13
2.1 Introduction 13
2.2 Methods of Estimation 13
2.3 Properties of Estimators 16
2.4 Hypothesis Testing 21
2.5 Confidence Intervals 30
2.6 Descriptive Statistics 31
Notes 36
Problems 36
References 42
Appendix 42
3 Simple Linear Regression 49
3.1 Introduction 49
3.2 Least Squares Estimation and the Classical Assumptions 50
3.3 Statistical Properties of Least Squares 55
3.4 Estimation of a2 56
3.5 Maximum Likelihood Estimation 57
3.6 A Measure of Fit 58
3.7 Prediction 60
3.8 Residual Analysis 60
3.9 Numerical Example 63
3.10 Empirical Example 64
Problems 67
References 71
Appendix 72
4 Multiple Regression Analysis 73
4.1 Introduction 73
XII Table of Contents
4.2 Least Squares Estimation 73
4.3 Residual Interpretation of Multiple Regression Estimates 75
4.4 Overspecification and Underspecification of the Regression Equation 76
4.5 R Squared versus R Bar Squared 78
4.6 Testing Linear Restrictions 78
4.7 Dummy Variables 81
Note 85
Problems 85
References 91
Appendix 92
5 Violations of the Classical Assumptions 95
5.1 Introduction 95
5.2 The Zero Mean Assumption 95
5.3 Stochastic Explanatory Variables 96
5.4 Normality of the Disturbances 98
5.5 Heteroskedasticity 98
5.6 Autocorrelation 109
Notes 119
Problems 120
References 126
6 Distributed Lags and Dynamic Models 129
6.1 Introduction 129
6.2 Infinite Distributed Lag 135
6.2.1 Adaptive Expectations Model (AEM) 136
6.2.2 Partial Adjustment Model (PAM) 137
6.3 Estimation and Testing of Dynamic Models with Serial Correlation 137
6.3.1 A Lagged Dependent Variable Model with AR(1) Disturbances 138
6.3.2 A Lagged Dependent Variable Model with MA(1) Disturbances 140
6.4 Autoregressive Distributed Lag 141
Note 142
Problems 142
References .... 144
Part II 147
7 The General Linear Model: The Basics 149
7.1 Introduction 149
7.2 Least Squares Estimation 149
7.3 Partitioned Regression and the Frisch Waugh Lovell Theorem 152
7.4 Maximum Likelihood Estimation 154
7.5 Prediction 157
7.6 Confidence Intervals and Test of Hypotheses 158
7 7 Joint Confidence Intervals and Test of Hypotheses 158
Table of Contents XIII
7.8 Restricted MLE and Restricted Least Squares 159
7.9 Likelihood Ratio, Wald and Lagrange Multiplier Tests 160
Notes 165
Problems 165
References 170
Appendix 171
8 Regression Diagnostics and Specification Tests 177
8.1 Influential Observations 177
8.2 Recursive Residuais 185
8.3 Specification Tests 194
8.4 Nonlinear Least Squares and the Gauss Newton Regression 204
8.5 Testing Linear versus Log Linear Functional Form 212
Notes 214
Problems 214
References 218
9 Generalized Least Squares 221
9.1 Introduction 221
9.2 Generalized Least Squares 221
9.3 Special Forms of fi 223
9.4 Maximum Likelihood Estimation 224
9.5 Test of Hypotheses 224
9.6 Prediction 225
9.7 Unknown ft 225
9.8 The W, LR and LM Statistics Revisited 226
9.9 Spatial Error Correlation 228
Note 229
Problems 230
References 234
10 Seemingly Unrelated Regressions 237
10.1 Introduction 237
10.2 Feasible GLS Estimation 239
10.3 Testing Diagonality of the Variance Covariance Matrix 242
10.4 Seemingly Unrelated Regressions with Unequal Observations 242
10.5 Empirical Example 244
Problems 245
References 249
11 Simultaneous Equations Model 253
11.1 Introduction 253
11.1.1 Simultaneous Bias 253
11.1.2 The Identification Problem 256
11.2 Single Equation Estimation: Two Stage Least Squares 259
11.2.1 Spatial Lag Dependence 266
XIV Table of Contents
11.3 System Estimation: Three Stage Least Squares 267
11.4 Test for Over Identification Restrictions 269
11.5 Hausman s Specification Test 271
11.6 Empirical Example: Crime in North Carolina 273
Notes 277
Problems 277
References 287
Appendix 289
12 Pooling Time Series of Cross Section Data 295
12.1 Introduction 295
12.2 The Error Components Model 295
12.2.1 The Fixed Effects Model 296
12.2.2 The Random Effects Model 298
12.2.3 Maximum Likelihood Estimation 302
12.3 Prediction 303
12.4 Empirical Example 303
12.5 Testing in a Pooled Model 307
12.6 Dynamic Panel Data Models 311
12.6.1 Empirical Illustration 314
12.7 Program Evaluation and Difference in Differences Estimator 316
12.7.1 The Difference in Differences Estimator 317
Problems 317
References 320
13 Limited Dependent Variables 323
13.1 Introduction 323
13.2 The Linear Probability Model 323
13.3 Functional Form: Logit and Probit 324
13.4 Grouped Data 326
13.5 Individual Data: Probit and Logit 331
13.6 The Binary Response Model Regression 332
13.7 Asymptotic Variances for Predictions and Marginal Effects 334
13.8 Goodness of Fit Measures 334
13.9 Empirical Examples 335
13.10 Multinomial Choice Models 339
13.10.1 Ordered Response Models 339
13.10.2 Unordered Response Models 340
13.11 The Censored Regression Model 341
13.12 The Truncated Regression Model 344
13.13 Sample Selectivity 345
Notes 347
Problems .... 347
References .... 351
Appendix .... 353
Tahle of Contents XV
14 Time Series Analysis 355
14.1 Introduction 355
14.2 Stationarity 355
14.3 The Box and Jenkins Method 356
14.4 Vector Autoregression 360
14.5 Unit Roots 361
14.6 Trend Stationary versus Difference Stationary 365
14.7 Cointegration 366
14.8 Autoregressive Conditional Heteroskedasticity 368
Note 371
Problems 371
References 375
Appendix 379
List of Figures 385
List of Tables 387
Index 389
|
| adam_txt |
Table of Contents
Preface VII
Table of Contents XI
Part I 1
1 What Is Econometrics? 3
1.1 Introduction 3
1.2 A Brief History 5
1.3 Critiques of Econometrics 7
1.4 Looking Ahead 8
Notes 9
References 10
2 Basic Statistical Concepts 13
2.1 Introduction 13
2.2 Methods of Estimation 13
2.3 Properties of Estimators 16
2.4 Hypothesis Testing 21
2.5 Confidence Intervals 30
2.6 Descriptive Statistics 31
Notes 36
Problems 36
References 42
Appendix 42
3 Simple Linear Regression 49
3.1 Introduction 49
3.2 Least Squares Estimation and the Classical Assumptions 50
3.3 Statistical Properties of Least Squares 55
3.4 Estimation of a2 56
3.5 Maximum Likelihood Estimation 57
3.6 A Measure of Fit 58
3.7 Prediction 60
3.8 Residual Analysis 60
3.9 Numerical Example 63
3.10 Empirical Example 64
Problems 67
References 71
Appendix 72
4 Multiple Regression Analysis 73
4.1 Introduction 73
XII Table of Contents
4.2 Least Squares Estimation 73
4.3 Residual Interpretation of Multiple Regression Estimates 75
4.4 Overspecification and Underspecification of the Regression Equation 76
4.5 R Squared versus R Bar Squared 78
4.6 Testing Linear Restrictions 78
4.7 Dummy Variables 81
Note 85
Problems 85
References 91
Appendix 92
5 Violations of the Classical Assumptions 95
5.1 Introduction 95
5.2 The Zero Mean Assumption 95
5.3 Stochastic Explanatory Variables 96
5.4 Normality of the Disturbances 98
5.5 Heteroskedasticity 98
5.6 Autocorrelation 109
Notes 119
Problems 120
References 126
6 Distributed Lags and Dynamic Models 129
6.1 Introduction 129
6.2 Infinite Distributed Lag 135
6.2.1 Adaptive Expectations Model (AEM) 136
6.2.2 Partial Adjustment Model (PAM) 137
6.3 Estimation and Testing of Dynamic Models with Serial Correlation 137
6.3.1 A Lagged Dependent Variable Model with AR(1) Disturbances 138
6.3.2 A Lagged Dependent Variable Model with MA(1) Disturbances 140
6.4 Autoregressive Distributed Lag 141
Note 142
Problems 142
References . 144
Part II 147
7 The General Linear Model: The Basics 149
7.1 Introduction 149
7.2 Least Squares Estimation 149
7.3 Partitioned Regression and the Frisch Waugh Lovell Theorem 152
7.4 Maximum Likelihood Estimation 154
7.5 Prediction 157
7.6 Confidence Intervals and Test of Hypotheses 158
7 7 Joint Confidence Intervals and Test of Hypotheses 158
Table of Contents XIII
7.8 Restricted MLE and Restricted Least Squares 159
7.9 Likelihood Ratio, Wald and Lagrange Multiplier Tests 160
Notes 165
Problems 165
References 170
Appendix 171
8 Regression Diagnostics and Specification Tests 177
8.1 Influential Observations 177
8.2 Recursive Residuais 185
8.3 Specification Tests 194
8.4 Nonlinear Least Squares and the Gauss Newton Regression 204
8.5 Testing Linear versus Log Linear Functional Form 212
Notes 214
Problems 214
References 218
9 Generalized Least Squares 221
9.1 Introduction 221
9.2 Generalized Least Squares 221
9.3 Special Forms of fi 223
9.4 Maximum Likelihood Estimation 224
9.5 Test of Hypotheses 224
9.6 Prediction 225
9.7 Unknown ft 225
9.8 The W, LR and LM Statistics Revisited 226
9.9 Spatial Error Correlation 228
Note 229
Problems 230
References 234
10 Seemingly Unrelated Regressions 237
10.1 Introduction 237
10.2 Feasible GLS Estimation 239
10.3 Testing Diagonality of the Variance Covariance Matrix 242
10.4 Seemingly Unrelated Regressions with Unequal Observations 242
10.5 Empirical Example 244
Problems 245
References 249
11 Simultaneous Equations Model 253
11.1 Introduction 253
11.1.1 Simultaneous Bias 253
11.1.2 The Identification Problem 256
11.2 Single Equation Estimation: Two Stage Least Squares 259
11.2.1 Spatial Lag Dependence 266
XIV Table of Contents
11.3 System Estimation: Three Stage Least Squares 267
11.4 Test for Over Identification Restrictions 269
11.5 Hausman's Specification Test 271
11.6 Empirical Example: Crime in North Carolina 273
Notes 277
Problems 277
References 287
Appendix 289
12 Pooling Time Series of Cross Section Data 295
12.1 Introduction 295
12.2 The Error Components Model 295
12.2.1 The Fixed Effects Model 296
12.2.2 The Random Effects Model 298
12.2.3 Maximum Likelihood Estimation 302
12.3 Prediction 303
12.4 Empirical Example 303
12.5 Testing in a Pooled Model 307
12.6 Dynamic Panel Data Models 311
12.6.1 Empirical Illustration 314
12.7 Program Evaluation and Difference in Differences Estimator 316
12.7.1 The Difference in Differences Estimator 317
Problems 317
References 320
13 Limited Dependent Variables 323
13.1 Introduction 323
13.2 The Linear Probability Model 323
13.3 Functional Form: Logit and Probit 324
13.4 Grouped Data 326
13.5 Individual Data: Probit and Logit 331
13.6 The Binary Response Model Regression 332
13.7 Asymptotic Variances for Predictions and Marginal Effects 334
13.8 Goodness of Fit Measures 334
13.9 Empirical Examples 335
13.10 Multinomial Choice Models 339
13.10.1 Ordered Response Models 339
13.10.2 Unordered Response Models 340
13.11 The Censored Regression Model 341
13.12 The Truncated Regression Model 344
13.13 Sample Selectivity 345
Notes 347
Problems . 347
References . 351
Appendix . 353
Tahle of Contents XV
14 Time Series Analysis 355
14.1 Introduction 355
14.2 Stationarity 355
14.3 The Box and Jenkins Method 356
14.4 Vector Autoregression 360
14.5 Unit Roots 361
14.6 Trend Stationary versus Difference Stationary 365
14.7 Cointegration 366
14.8 Autoregressive Conditional Heteroskedasticity 368
Note 371
Problems 371
References 375
Appendix 379
List of Figures 385
List of Tables 387
Index 389 |
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| genre | (DE-588)4123623-3 Lehrbuch gnd-content |
| genre_facet | Lehrbuch |
| id | DE-604.BV023037761 |
| illustrated | Not Illustrated |
| index_date | 2024-07-02T19:19:38Z |
| indexdate | 2024-07-09T21:09:33Z |
| institution | BVB |
| isbn | 9783540765165 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016241502 |
| oclc_num | 740937961 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-706 DE-898 DE-BY-UBR DE-M347 DE-355 DE-BY-UBR DE-703 DE-1102 DE-1049 DE-634 DE-2070s DE-859 DE-573 DE-188 |
| owner_facet | DE-473 DE-BY-UBG DE-706 DE-898 DE-BY-UBR DE-M347 DE-355 DE-BY-UBR DE-703 DE-1102 DE-1049 DE-634 DE-2070s DE-859 DE-573 DE-188 |
| physical | 1 Online-Ressource (XV, 392 S.) graph. Darst. |
| psigel | ZDB-2-SBE |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Springer |
| record_format | marc |
| spelling | Econometrics Badi H. Baltagi 4. ed. Berlin [u.a.] Springer 2008 1 Online-Ressource (XV, 392 S.) graph. Darst. txt rdacontent c rdamedia cr rdacarrier Ökonometrie (DE-588)4132280-0 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Ökonometrie (DE-588)4132280-0 s DE-604 Baltagi, Badi H. 1954- Sonstige (DE-588)128356812 oth Erscheint auch als Druck-Ausgabe, Paperback 3-540-76515-8 Erscheint auch als Druck-Ausgabe, Paperback 978-3-540-76515-8 http://d-nb.info/985929715/04 Inhaltsverzeichnis https://doi.org/10.1007/978-3-540-76516-5 Verlag URL des Erstveröffentlichers Volltext HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016241502&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | 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_exact_search_txtP | Econometrics |
| title_full | Econometrics Badi H. Baltagi |
| title_fullStr | Econometrics Badi H. Baltagi |
| title_full_unstemmed | Econometrics Badi H. Baltagi |
| title_short | Econometrics |
| title_sort | econometrics |
| topic | Ökonometrie (DE-588)4132280-0 gnd |
| topic_facet | Ökonometrie Lehrbuch |
| url | http://d-nb.info/985929715/04 https://doi.org/10.1007/978-3-540-76516-5 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016241502&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT baltagibadih econometrics |
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