Spatial econometrics:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
London
Academic Press
[2017]
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xxi, 435 Seiten Diagramme |
| ISBN: | 9780128133873 |
Internformat
MARC
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| 100 | 1 | |a Kelejian, Harry H. |d 1937- |e Verfasser |0 (DE-588)135963028 |4 aut | |
| 245 | 1 | 0 | |a Spatial econometrics |c Harry Kelejian (Emeritus Professor at the University of Maryland, College Park, USA), Gianfranco Piras (Associate Professor, The Busch School of Business and Economics, The Catholic University of America, Washington, D.C., USA) |
| 264 | 1 | |a London |b Academic Press |c [2017] | |
| 300 | |a xxi, 435 Seiten |b Diagramme | ||
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| 650 | 0 | 7 | |a Ökonometrie |0 (DE-588)4132280-0 |2 gnd |9 rswk-swf |
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Datensatz im Suchindex
| _version_ | 1804177867010998272 |
|---|---|
| adam_text | Contents
Preface xvii
Acknowledgements xxi
1. Spatial Models: Basic Issues
1.1 Illustrations Involving Spatial Interactions 1
1.2 Concept of a Neighbor and the Weighting Matrix 3
1.3 Some Different Ways to Specify Spatial Weighting Matrices 4
1.4 Typical Weighting Matrices in Computer Studies 8
Suggested Problems 10
2. Specification and Estimation
2.1 The General Model 12
2.1.1 Triangular Arrays 14
2.1.2 Gersgorin s Theorem and Weighting Matrices 15
2.1.3 Normalization to Ensure a Continuous Parameter Space 18
2.1.4 An Important Condition in Large Sample Analysis 20
2.2 Estimation: Various Special Cases 22
2.2.1 Estimation When pi = p2 = 0 22
2.2.2 Estimation When Pi = 0 and P2 0 27
2.2.2.1 Maximum Likelihood Estimation: pi =0, P2 ^ 0 28
2.2.3 Assumptions of the General Model 33
2.2.4 A Generalized Moments Estimator of P2 37
2.3 IV Estimation of the General Model 43
2.4 Maximum Likelihood Estimation of the General Model 46
2.5 An Identification Fallacy 49
2.6 Time Series Procedures Do Not Always Carry Over 50
Appendix A2 Proofs for Chapter 2 52
Suggested Problems 58
3. Spillover Effects in Spatial Models
3.1 Effects Emanating From a Given Unit 61
3.2 Emanating Effects of a Uniform Worsening of Fundamentals 64
v
vi Contents
3.3 Vulnerability of a Given Unit to Spillovers 66
Suggested Problems 69
4. Predictors in Spatial Models
4.1 Preliminaries on Expectations 71
4.2 Information Sets and Predictors of the Dependent Variable 75
4.3 Mean Squared Errors of the Predictors 80
Suggested Problems 86
5. Problems in Estimating Weighting Matrices
5.1 The Spatial Model 87
5.2 Shortcomings of Selection Based on R2 88
5.3 An Extension to Nonlinear Spatial Models 90
5.4 R2 Selection in the Multiple Panel Case 91
Suggested Problems 95
6. Additional Endogenous Variables: Possible
Nonlinearities
6.1 Introductory Comments 97
6.2 Identification and Estimation: A Linear System 98
6.3 A Corresponding Nonlinear Model 100
6.4 Estimation in the Nonlinear Model 102
6.5 Large Sample and Related Issues 106
6.6 Generalizations and Special Points to Note 108
6.7 Applications to Spatial Models 113
6.8 Problems With MLE 120
Suggested Problems 121
7. Bayesian Analysis
7.1 Introductory Comments 123
7.2 Fundamentals of the Bayesian Approach 124
7.3 Learning and Prejudgment Issues 125
7.4 Comments on Uninformed Priors 127
7.5 Applications and Limiting Cases 129
7.6 Properties of the Multivariate t 138
7.7 Useful Sampling Procedures in Bayesian Analysis 140
7.8 The Spatial Lag Model and Gibbs Sampling 154
7.9 Bayesian Posterior Odds and Model Selection 158
7.10 Problems With the Bayesian Approach 160
Suggested Problems 161
8. Pretest and Sample Selection Issues in Spatial Analysis
8.1 Introductory Comments 163
Contents VII
8.2 A Preliminary Result 163
8.3 Illustrations 164
8.4 Mean Squared Errors 168
8.5 Pretesting in Spatial Models: Large Sample Issues 169
8.6 Final Comments on Pretesting 175
8.7 A Related Issue: Data Selection 177
8.8 Endogenous Data Selection Issues 178
8.9 Exogenous Data Selection Issues 180
Suggested Problems 1 82
9. HAC Estimation of VC Matrices
9.1 Introductory Comments on Heteroskedasticity 185
9.2 Spatially Correlated Errors: Illustrations 189
9.3 Assumptions and HAC Estimation 193
9.4 Kernel Functions That Satisfy Assumption 9.8 200
9.5 HAC Estimation With Multiple Distances 205
9.6 Nonparametric Error Terms and Maximum Likelihood: Serious
Problems 206
Suggested Problems 208
10. Missing Data and Edge Issues
10.1 Introductory Comments 209
10.2 A Simple Model and Limits of Information 210
10.3 Incomplete Samples and External Data 218
10.4 The Spatial Error Model: IV and ML With Missing Data 219
10.5 A More General Spatial Model 221
10.6 Spatial Error Models: Be Careful What You Do 230
Appendix A10 Proofs for Chapter 10 232
Suggested Problems 235
11. Tests for Spatial Correlation
11.1 Introductory Comments: Occam s Razor 237
11.2 Some Preliminary Issues on a Quadratic Form 238
11.3 The Moran I Test: A Basic Model 240
11.4 An Important Independence Result 245
11.5 Application: The Moments of the Moran I 246
11.6 Generalized Moran / Tests: Qualitative Models and Spatially
Lagged Dependent Variable Models 247
11.7 Lagrangian Multiplier Tests 258
11.8 The Wald Test 266
11.9 Spatial Correlation Tests: Comments and Caveats 267
Suggested Problems 270
ѵиі Contents
12. Nonnested Models and the J-Test
12.1 Introductory Comments 271
12.2 The Null Model: Nonparametric Error Terms 272
12.3 The Alternative Models 272
12.4 Two Predictors 273
12.5 The Augmented Equation and the /-Test 275
12.6 The J-Test: SAR Error Terms 277
12.7 /-Test and Nonlinear Alternatives 278
Suggested Problems 281
13. Endogenous Weighting Matrices: Specifications and
Estimation
13.1 Introductory Comments 283
13.2 The Model 284
13.3 Issues Concerning Error Term Specification 284
13.4 Further Specifications 285
13.5 The Instrument Matrix 287
13.6 Estimation and Inference 289
Suggested Problems 292
14. Systems of Spatial Equations
14.1 Introductory Comments 293
14.2 An Illustrative Two-Equations Model 294
14.3 The Model With Nonparametric Error Terms 294
14.4 Assumptions of the Model 296
14.5 Interpretation of the Assumptions 297
14.6 Estimation and Inference 298
14.7 The Model With SAR Error Terms 300
14.8 Estimation and Inference: GS3SLS 302
Suggested Problems 306
15. Panel Data Models
15.1 Introductory Comments 307
15.2 Some Important Preliminaries 307
15.3 The Random Effects Model 308
15.4 A Generalization of the Random Effects Model 316
15.5 The Fixed Effects Model 321
15.6 A Generalization of the Fixed Effects Model 329
15.7 Tests of Panel Models: The /-Test 336
Suggested Problems 341
A. Introduction to Large Sample Theory
A.1 An Intuitive Introduction 343
Contents IX
A.2 Application of the Large Sample Result in (A.1.6) 345
A.3 More Formalism: Convergence in Probability 345
A.4 Khinchine s Theorem 348
A.5 An Important Property of Convergence in Probability 349
A.6 A Matrix Illustration of Consistency 349
A.7 Generalizations of Slutsky-Type Results 350
A.8 A Note on the Least Squares Model 352
A. 9 Convergence in Distribution 352
A.10 Results on Convergence in Distribution 353
A.11 Convergence in Distribution: Slutsky-Type Results 354
A.12 Constructing Finite Sample Approximations 355
A.13 A Result Relating to Nonlinear Functions of Estimators 357
A.14 Orders in Probability 359
A.15 Triangular Arrays: A Central Limit Theorem 362
B. Spatial Models in R
B. 1 Introduction 363
B.2 Introductory Tools 364
B.3 Reading Data and Creating Weights 372
B.4 Estimating Spatial Models 376
Answer Manual 389
References 417
Index 429
|
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| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:54:53Z |
| institution | BVB |
| isbn | 9780128133873 |
| language | English |
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| physical | xxi, 435 Seiten Diagramme |
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| publisher | Academic Press |
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| spelling | Kelejian, Harry H. 1937- Verfasser (DE-588)135963028 aut Spatial econometrics Harry Kelejian (Emeritus Professor at the University of Maryland, College Park, USA), Gianfranco Piras (Associate Professor, The Busch School of Business and Economics, The Catholic University of America, Washington, D.C., USA) London Academic Press [2017] xxi, 435 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Ökonometrie (DE-588)4132280-0 gnd rswk-swf Raumwirtschaftstheorie (DE-588)4121557-6 gnd rswk-swf Ökonometrie (DE-588)4132280-0 s Raumwirtschaftstheorie (DE-588)4121557-6 s b DE-604 Piras, Gianfranco Sonstige oth Erscheint auch als Online-Ausgabe 978-0-12-813392-7 (DE-604)BV045459076 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029922078&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Kelejian, Harry H. 1937- Spatial econometrics Ökonometrie (DE-588)4132280-0 gnd Raumwirtschaftstheorie (DE-588)4121557-6 gnd |
| subject_GND | (DE-588)4132280-0 (DE-588)4121557-6 |
| title | Spatial econometrics |
| title_auth | Spatial econometrics |
| title_exact_search | Spatial econometrics |
| title_full | Spatial econometrics Harry Kelejian (Emeritus Professor at the University of Maryland, College Park, USA), Gianfranco Piras (Associate Professor, The Busch School of Business and Economics, The Catholic University of America, Washington, D.C., USA) |
| title_fullStr | Spatial econometrics Harry Kelejian (Emeritus Professor at the University of Maryland, College Park, USA), Gianfranco Piras (Associate Professor, The Busch School of Business and Economics, The Catholic University of America, Washington, D.C., USA) |
| title_full_unstemmed | Spatial econometrics Harry Kelejian (Emeritus Professor at the University of Maryland, College Park, USA), Gianfranco Piras (Associate Professor, The Busch School of Business and Economics, The Catholic University of America, Washington, D.C., USA) |
| title_short | Spatial econometrics |
| title_sort | spatial econometrics |
| topic | Ökonometrie (DE-588)4132280-0 gnd Raumwirtschaftstheorie (DE-588)4121557-6 gnd |
| topic_facet | Ökonometrie Raumwirtschaftstheorie |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029922078&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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