Seemingly unrelated regression equations models: estimation and inference
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York [u.a.]
Dekker
1987
|
| Edition: | 1. print. |
| Series: | Statistics
80 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XII, 374 S. |
| ISBN: | 0824776100 |
Staff View
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Record in the Search Index
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| adam_text | Contents
Preface v
1 The Seemingly Unrelated Regression Equations Model 1
1.1 Introduction 1
1.2 The Model 3
1.3 Outline 7
Exercises 8
References 9
2 The Least Squares Estimator and Its Variants 11
2.1 Introduction 11
2. 2 The Ordinary Least Squares and Generalized
Least Squares Estimators 12
2.3 The Feasible Generalized Least Squares Estimator 13
2.4 Optimality of Ordinary Least Squares 17
2.5 Simplifications of Feasible Generalized Least Squares 22
2.6 Some Asymptotic Properties 27
Exercises 35
References 37
ix
x Contents
3 Approximate Distribution Theory for Feasible
Generalized Least Squares Estimators 41
3.1 Introduction 41
3. 2 Asymptotic Approximations for Bias Vectors 42
3. 3 Asymptotic Approximations for Variance
Covariance Matrices 45
3 4 Asymptotic Approximations for Density
and Distribution Functions 62
3. 5 Monte Carlo Evidence 72
3. 6 Some Remarks on Large Sample Approximation
Methodology and the Monte Carlo Technique 74
Exercises 77
References 79
4 Exact Finite Sample Properties of Feasible
Generalized Least Squares Estimators 81
4 1 Introduction 81
4.2 Unbiasedness 82
4.3 The Two Equation Model 85
4.4 Efficiency Properties Under Orthogonal Regressors 87
4.5 Efficiency Properties Under Subset Regressors 104
4.6 Efficiency Properties Under Unconstrained Regressors 116
4.7 Some Further Results 127
4.8 The Multi Equation Model 136
Exercises 143
References 146
5 Iterative Estimators 149
5.1 Introduction 149
5. 2 The Iterative Feasible Generalized
Least Squares Estimator 150
5.3 The Iterative Ordinary Least Squares Estimator 151
5.4 The Maximum Likelihood Estimator 155
5 5 Computational Issues 159
5.6 Unbiasedness 160
5.7 Efficiency Properties 161
Exercises 171
References 172
6 Shrinkage Estimators 175
6.1 Introduction 175
6.2 Stein Rule Estimators 176
Contents xi
6.3 Ridge Type Estimators 186
6.4 Weighted Combination Estimators 190
6.5 LIndley Like Mean Corrections 197
Exercises 199
References 201
7 Autoregressive Disturbances 205
7.1 Introduction 205
7.2 First Order Scalar Autoregressive Disturbances 206
7.3 First Order Vector Autoregressive Disturbances 214
7.4 Efficiency Comparisons 220
7.5 Testing the Autoregressive Structure 225
7.6 Research Suggestions 228
Exercises 229
References 231
8 Heteroscedastic Disturbances 235
8.1 Introduction 235
8.2 Model Specification and Estimation 236
8.3 Estimator Properties 239
8.4 Efficiency Comparisons 251
8.5 Research Suggestions 254
Exercises 254
References 255
9 Constrained Error Covariance Structures 257
9.1 Introduction 257
9. 2 Variance Inequalities and Positivity of Correlations 258
9.3 Error Components Structure 266
9.4 Research Suggestions 274
Exercises 275
References 276
10 Prior Information 279
10.1 Introduction 279
10. 2 Restrictions on the Parameters 280
10.3 Specification Analysis 292
10.4 Bayesian Analysis 316
10.5 Research Suggestions 323
Exercises 324
References 327
xii Contents
11 Some Miscellaneous Topics 331
11.1 Introduction 331
11.2 The Varying Coefficients Model 331
11.3 Missing Observations 339
11.4 Goodness of Fit Measures 346
11.5 Dynamic Models 351
11.6 Non Linear Models 353
11.7 Further Research 357
Exercises 358
References 360
Appendix 363
Index 371
|
| adam_txt |
Contents
Preface v
1 The Seemingly Unrelated Regression Equations Model 1
1.1 Introduction 1
1.2 The Model 3
1.3 Outline 7
Exercises 8
References 9
2 The Least Squares Estimator and Its Variants 11
2.1 Introduction 11
2. 2 The Ordinary Least Squares and Generalized
Least Squares Estimators 12
2.3 The Feasible Generalized Least Squares Estimator 13
2.4 Optimality of Ordinary Least Squares 17
2.5 Simplifications of Feasible Generalized Least Squares 22
2.6 Some Asymptotic Properties 27
Exercises 35
References 37
ix
x Contents
3 Approximate Distribution Theory for Feasible
Generalized Least Squares Estimators 41
3.1 Introduction 41
3. 2 Asymptotic Approximations for Bias Vectors 42
3. 3 Asymptotic Approximations for Variance
Covariance Matrices 45
3 4 Asymptotic Approximations for Density
and Distribution Functions 62
3. 5 Monte Carlo Evidence 72
3. 6 Some Remarks on Large Sample Approximation
Methodology and the Monte Carlo Technique 74
Exercises 77
References 79
4 Exact Finite Sample Properties of Feasible
Generalized Least Squares Estimators 81
4 1 Introduction 81
4.2 Unbiasedness 82
4.3 The Two Equation Model 85
4.4 Efficiency Properties Under Orthogonal Regressors 87
4.5 Efficiency Properties Under Subset Regressors 104
4.6 Efficiency Properties Under Unconstrained Regressors 116
4.7 Some Further Results 127
4.8 The Multi Equation Model 136
Exercises 143
References 146
5 Iterative Estimators 149
5.1 Introduction 149
5. 2 The Iterative Feasible Generalized
Least Squares Estimator 150
5.3 The Iterative Ordinary Least Squares Estimator 151
5.4 The Maximum Likelihood Estimator 155
5 5 Computational Issues 159
5.6 Unbiasedness 160
5.7 Efficiency Properties 161
Exercises 171
References 172
6 Shrinkage Estimators 175
6.1 Introduction 175
6.2 Stein Rule Estimators 176
Contents xi
6.3 Ridge Type Estimators 186
6.4 Weighted Combination Estimators 190
6.5 LIndley Like Mean Corrections 197
Exercises 199
References 201
7 Autoregressive Disturbances 205
7.1 Introduction 205
7.2 First Order Scalar Autoregressive Disturbances 206
7.3 First Order Vector Autoregressive Disturbances 214
7.4 Efficiency Comparisons 220
7.5 Testing the Autoregressive Structure 225
7.6 Research Suggestions 228
Exercises 229
References 231
8 Heteroscedastic Disturbances 235
8.1 Introduction 235
8.2 Model Specification and Estimation 236
8.3 Estimator Properties 239
8.4 Efficiency Comparisons 251
8.5 Research Suggestions 254
Exercises 254
References 255
9 Constrained Error Covariance Structures 257
9.1 Introduction 257
9. 2 Variance Inequalities and Positivity of Correlations 258
9.3 Error Components Structure 266
9.4 Research Suggestions 274
Exercises 275
References 276
10 Prior Information 279
10.1 Introduction 279
10. 2 Restrictions on the Parameters 280
10.3 Specification Analysis 292
10.4 Bayesian Analysis 316
10.5 Research Suggestions 323
Exercises 324
References 327
xii Contents
11 Some Miscellaneous Topics 331
11.1 Introduction 331
11.2 The Varying Coefficients Model 331
11.3 Missing Observations 339
11.4 Goodness of Fit Measures 346
11.5 Dynamic Models 351
11.6 Non Linear Models 353
11.7 Further Research 357
Exercises 358
References 360
Appendix 363
Index 371 |
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| series2 | Statistics |
| spelling | Srivastava, Virendra K. Verfasser aut Seemingly unrelated regression equations models estimation and inference 1. print. New York [u.a.] Dekker 1987 XII, 374 S. txt rdacontent n rdamedia nc rdacarrier Statistics 80 Analyse de régression Estimation, Théorie de l' Kleinste-kwadratenmethode gtt Moindres carrés Regressieanalyse gtt Schattingstheorie gtt Estimation theory Least squares Regression analysis Methode der kleinsten Quadrate (DE-588)4038974-1 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf Schätztheorie (DE-588)4121608-8 gnd rswk-swf Regressionsmodell (DE-588)4127980-3 gnd rswk-swf Methode der kleinsten Quadrate (DE-588)4038974-1 s DE-604 Schätztheorie (DE-588)4121608-8 s Regressionsanalyse (DE-588)4129903-6 s Regressionsmodell (DE-588)4127980-3 s 1\p DE-604 Giles, David E. Verfasser aut Statistics 80 (DE-604)BV000003265 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015371574&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Srivastava, Virendra K. Giles, David E. Seemingly unrelated regression equations models estimation and inference Statistics Analyse de régression Estimation, Théorie de l' Kleinste-kwadratenmethode gtt Moindres carrés Regressieanalyse gtt Schattingstheorie gtt Estimation theory Least squares Regression analysis Methode der kleinsten Quadrate (DE-588)4038974-1 gnd Regressionsanalyse (DE-588)4129903-6 gnd Schätztheorie (DE-588)4121608-8 gnd Regressionsmodell (DE-588)4127980-3 gnd |
| subject_GND | (DE-588)4038974-1 (DE-588)4129903-6 (DE-588)4121608-8 (DE-588)4127980-3 |
| title | Seemingly unrelated regression equations models estimation and inference |
| title_auth | Seemingly unrelated regression equations models estimation and inference |
| title_exact_search | Seemingly unrelated regression equations models estimation and inference |
| title_exact_search_txtP | Seemingly unrelated regression equations models estimation and inference |
| title_full | Seemingly unrelated regression equations models estimation and inference |
| title_fullStr | Seemingly unrelated regression equations models estimation and inference |
| title_full_unstemmed | Seemingly unrelated regression equations models estimation and inference |
| title_short | Seemingly unrelated regression equations models |
| title_sort | seemingly unrelated regression equations models estimation and inference |
| title_sub | estimation and inference |
| topic | Analyse de régression Estimation, Théorie de l' Kleinste-kwadratenmethode gtt Moindres carrés Regressieanalyse gtt Schattingstheorie gtt Estimation theory Least squares Regression analysis Methode der kleinsten Quadrate (DE-588)4038974-1 gnd Regressionsanalyse (DE-588)4129903-6 gnd Schätztheorie (DE-588)4121608-8 gnd Regressionsmodell (DE-588)4127980-3 gnd |
| topic_facet | Analyse de régression Estimation, Théorie de l' Kleinste-kwadratenmethode Moindres carrés Regressieanalyse Schattingstheorie Estimation theory Least squares Regression analysis Methode der kleinsten Quadrate Regressionsanalyse Schätztheorie Regressionsmodell |
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| volume_link | (DE-604)BV000003265 |
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