Advances in spatial econometrics: methodology, tools and applications ; with ... 83 tables
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| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2004
|
| Schriftenreihe: | Advances in spatial science
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXII, 513 S. graph. Darst., Kt. |
| ISBN: | 3540437290 |
Internformat
MARC
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| 245 | 1 | 0 | |a Advances in spatial econometrics |b methodology, tools and applications ; with ... 83 tables |c Luc Anselin ... (ed.) |
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 2004 | |
| 300 | |a XXII, 513 S. |b graph. Darst., Kt. | ||
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Datensatz im Suchindex
| _version_ | 1804130059054743552 |
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| adam_text | Contents
Preface vii
Foreword ix
1 Econometrics for Spatial Models: Recent Advances 1
Luc Anselin, Raymond J.G.M. Florax, Sergio J. Rey
1.1 Introduction 1
1.2 Recent Advances 2
1.3 Specification, Testing and Estimation 11
1.4 Discrete Choice, Nonparametric and Bayesian Approaches 14
1.5 Spatial Externalities 18
1.6 Urban Growth and Agglomeration Economies 20
1.7 Trade and Economic Growth 22
1.8 Future Directions 24
Part I. Specification, Testing and Estimation
2 The Performance of Diagnostic Tests for Spatial Dependence in
Linear Regression Models: A Meta Analysis of Simulation Studies 29
Raymond J.G.M. Florax, Thomas de Graaff
2.1 Introduction 29
2.2 Meta Analysis and Response Surfaces 32
2.3 Spatial Dependence Tests and Data Generating Processes 34
2.4 A Taxonomy of Spatial Dependence Tests 40
2.5 Review of the Simulation Literature on Spatial Dependence Tests 41
2.6 Experimental Design and Meta Regression Results 43
2.7 Conclusions 63
3 Moran Flavored Tests with Nuisance Parameters: Examples 67
Joris Pinkse
3.1 Introduction 67
3.2 Test Statistics 68
3.3 Weights Matrix 69
3.4 Nuisance Parameters 70
3.5 Conditions 74
3.6 Conclusions 76
Appendix: Synopsis of Conditions 77
xii
4 The Influence of Spatially Correlated Heteroskedasticity on Tests for
Spatial Correlation 79
Harry H. Kelejian, Dennis P. Robinson
4.1 Introduction 79
4.2 The Model 81
4.3 Basic Results 87
4.4 Conclusions 90
Appendix: Preliminaries and Proofs 91
5 A Taxonomy of Spatial Econometric Models for Simultaneous Equa¬
tions Systems 99
Sergio J. Rey, Marlon G. Boarnet
5.1 Introduction 99
5.2 Recent Applications of Spatial Econometrics in a Multi Equation Frame¬
work 99
5.3 Taxonomy 102
5.4 Estimation Issues 105
5.5 Monte Carlo Experiments 109
5.6 Results Ill
5.7 Conclusions 114
6 Exploring Spatial Data Analysis Techniques Using R: The Case of
Observations with No Neighbors 121
Roger S. Bivand, Boris A. Portnov
6.1 Introduction 121
6.2 Implementing spatial weights objects in R 122
6.3 Spatial Lags: Consequences of Observations with No Neighbors 125
6.4 Case Study: Clusters of Towns in an Urban System with Sparsely Pop¬
ulated Regions 129
6.5 Conclusions 140
Part II. Discrete Choice and Bayesian Approaches
7 Techniques for Estimating Spatially Dependent Discrete Choice Models 145
Mark M. Fleming
7.1 Introduction 145
7.2 Heteroskedastic Estimators 149
7.3 Full Spatial Information Estimators 151
7.4 Weighted Non Linear Least Squares Estimators 160
7.5 Conclusions 166
8 Probit in a Spatial Context: A Monte Carlo Analysis 169
Kurt J. Beron, Wim P.M. Vijverberg
8.1 Introduction 169
8.2 Probit Models 170
xiii
8.3 The RIS Simulator 176
8.4 Monte Carlo Data 178
8.5 Monte Carlo Results 181
8.6 Spatial Linear Probability Model 187
8.7 Conclusions 192
9 Simultaneous Spatial and Functional Form Transformations 197
R. Kelley Pace, Ronald Barry, V. Carlos Slawson Jr., C.F. Sirmans
9.1 Introduction 197
9.2 Simultaneous Spatial and Variable Transformations 200
9.3 Baton Rouge Housing 206
9.4 Conclusions 213
10 Locally Weighted Maximum Likelihood Estimation: Monte Carlo
Evidence and an Application 225
Daniel P. McMillen, John F. McDonald
10.1 Introduction 225
10.2 The Locally Weighted Log Likelihood Function 226
10.3 Monte Carlo Experiments 229
10.4 Density Zoning in 1920s Chicago 232
10.5 Conclusions 236
Appendix: Computational Steps for an LWML Model 237
11 A Family of Geographically Weighted Regression Models 241
James P. LeSage
11.1 Introduction 241
11.2 The GWR and Bayesian GWR models 243
11.3 Estimation of the BGWR model 246
11.4 Examples 253
11.5 Conclusions 263
Part III. Spatial Externalities
12 Hedonic Price Functions and Spatial Dependence: Implications for
the Demand for Urban Air Quality 267
Kurt J, Beron, Yaw Hanson, James C. Murdoch, Mark A. Thayer
12.1 Introduction 267
12.2 Hedonic Functions and Benefit Estimation 268
12.3 Econometric Issues 270
12.4 Estimates 271
12.5 Conclusions 278
Appendix: Data Sources 279
xiv
13 Prediction in the Panel Data Model with Spatial Correlation 283
Badi H. Baltagi, Dong Li
13.1 Introduction 283
13.2 Estimation 284
13.3 Prediction 291
13.4 Conclusions 295
14 External Effects and Cost of Production 297
Rosina Moreno, Enrique Lopez Bazo, Esther Vayd, Manuel Artis
14.1 Introduction 297
14.2 Sources of Regional and Industrial Externalities 299
14.3 Theoretical Framework: Duality Theory and External Effects 302
14.4 Spatial and Sectoral Externalities 304
14.5 Data 309
14.6 Empirical Results 310
14.7 Conclusions 316
Part IV. Urban Growth and Agglomeration Economies
15 Identifying Urban Rural Linkages:
Tests for Spatial Effects in the Carlino Mills Model 321
Shunting Bao, Mark Henry, David Barkley
15.1 Introduction 321
15.2 Spatial Context of the Analysis 322
15.3 Econometric Model 325
15.4 Empirical Results 329
15.5 Conclusions 333
16 Economic Geography and the Spatial Evolution of Wages in the
United States 335
Yannis M. loannides
16.1 Introduction 335
16.2 Theoretical Strands 335
16.3 The Model 336
16.4 Data 343
16.5 Econometric Analysis 350
16.6 Conclusions 357
17 Endogenous Spatial Externalities: Empirical Evidence and
Implications for the Evolution of Exurban Residential Land Use Patterns 359
Elena Irwin, Nancy Bockstael
17.1 Introduction 359
17.2 Spatial Externalities and Residential Location 360
17.3 A Model of Land Use Conversion with Interaction Effects 362
17.4 Estimation of the Empirical Model 366
XV
17.5 Predicted Patterns of Development 375
17.6 Conclusions 378
Part V. Trade and Economic Growth
18 Does Trade Liberalization Cause a Race to the Bottom in
Environmental Policies? A Spatial Econometric Analysis 383
Paavo Eliste, Per G. Fredriksson
18.1 Introduction 383
18.2 Model Specification 385
18.3 Data Description and Hypothesis Specification 388
18.4 Empirical Results 388
18.5 Conclusions 395
19 Regional Economic Growth and Convergence: Insights from a
Spatial Econometric Perspective 397
Bernard Fingleton
19.1 Introduction 397
19.2 Growth Theory: Overview 397
19.3 The Single Equation Approach to the Verdoorn Law 401
19.4 A Simultaneous Equation Approach: Problems and Issues 405
19.5 Convergence Theory and Methodology 409
19.6 Empirical Convergence Analysis 416
19.7 Conclusions 425
Appendix: Description of Data 427
20 Growth and Externalities Across Economies: An Empirical Analysis
Using Spatial Econometrics 433
Esther Vayd, Enrique Ldpez Bazo, Rosina Moreno, Jordi Surinach
20.1 Introduction 433
20.2 Do Spatial Externalities Matter? 434
20.3 A Simple Growth Model With Spillovers Across Regions 436
20.4 Empirical Specifications 439
20.5 The Spatial Econometrics of Considering Externalities Across Economies441
20.6 Empirical Evidence 448
20.7 Conclusions 453
References 457
Author Index 489
Index 499
List of Contributors 507
xvii
List of Tables
1.1 Spatial Econometrics in Econometric Methods Journals 3
1.2 Spatial Econometric Applications in Economic Field Journals 4
2.1 A taxonomy of spatial dependence tests 41
2.2 Overview of the simulation literature 44
2.3 Annotated chronological listing of Monte Carlo simulation studies of
spatial dependence tests in linear regression models 46
2.4 Weighted least squares results for diffuse spatial dependence tests un¬
der all data generating processes 54
2.5 Weighted least squares results for focused unidirectional spatial depen¬
dence tests under known data generating processes 57
2.6 Weighted least squares results for diffuse and focused multidirectional
tests against spatial dependence and heteroskedasticity for correspond¬
ing data generating processes, and a comparison with Moran s / and
the LM test against spatial autoregressive errors 61
3.1 Taylor expansion components for the six models 73
5.1 Model taxonomy 106
5.2 Parameter values for experiments 110
5.3 Bias and RMSE p2,i, OLS=1 112
5.4 Bias and RMSE p4,2, OLS=1 113
5.5 Bias and RMSE ft,i, OLS=1 115
5.6 Bias and RMSE Yi^,OLS=l 116
5.7 Bias and RMSE pM,OLS=l 117
5.8 Bias and RMSE p2,2, OLS=1 118
6.1 Neighborhood sets for lattices shown in Fig. 6.1 A and B 124
6.2 The incremental neighborhood sets of zone 8 (Fig. 6.1 D) 124
6.3 Same color join count statistics for percentage population change classes
by neighborhood criterion and weighting scheme: standard deviates
and probability values under non free sampling 138
6.4 Moran s / statistic for ranks of percentage population change 139
7.1 Summary of Estimator Differences 168
8.1 Characteristics of the weights matrices: number of connections among
observations (in percents) 180
8.2 Likelihood Ratio tests for spatial error autocorrelation and spatial lag,
probit estimators 182
8.3 Estimates for pi, S samples 184
8.4 Estimates for a and p, 5 samples 184
8.5 Estimates for Pi, T samples 188
8.6 Estimates for a and p, T samples 188
8.7 Likelihood Ratio tests for spatial error autocorrelation and spatial lag,
linear model estimators 190
8.8 Comparison of linear and probit estimates for pi 193
8.9 Comparison of linear and probit estimates for a and p 194
9.2 Likelihood Ratio Tests 211
xviii
9.3 Sample Error Statistics Across Models For Prediction of the Untrans
formed Dependent Variable 212
10.1 Standard Probit Monte Carlo Results 231
10.2 Locally Weighted Probit Monte Carlo Results: n 250 232
10.3 Locally Weighted Probit Monte Carlo Results: n 750 233
10.4 Ordered Probit Models for Density Zoning 234
10.5 Predictions: Standard Probit Model 236
10.6 Predictions: Locally Weighted Probit Model 237
12.1 Variable description 272
12.2 Descriptive statistics 273
12.3 OLS estimates of the semilog hedonic price functions (1992) 274
12.4 Maximum Likelihood estimates of the semilog hedonic price functions
(1992) 276
12.5 Estimates of the demand for air quality OLS based 277
12.6 Estimates of the demand for air quality SAR based 277
13.1 Pooled estimates of cigarette demand 285
13.2 Heterogeneous estimates of cigarette demand 286
13.3 Out of sample forecast RMSE performance 294
14.1 Description of the industrial sectors 310
14.2 Spatial dependence tests in the regional case with p values in parentheses311
14.3 Elasticities from the specifications with the external input in the re¬
gional case 312
14.4 Elasticities from the specification with the external input and the across
region externality in the regional case 313
14.5 Spatial dependence tests in the sectoral case with p values in parentheses314
14.6 Elasticities from the specification with the external input in the sectoral
case 315
14.7 Elasticities from the specification with the external input and the across
industry externality in the sectoral case 316
15.1 Selected amenity variables from factor analysis 329
15.2 Parameter estimates for the rural/urban linkage models 331
16.1 Descriptive statistics, decennial data (1900 1990) 345
16.2 Descriptive statistics for all cities, 1900 1990, 1990 observations 346
16.3 Earnings, schooling and size of cities and their neighbors 348
16.4 Wages and Spatial Evolution 352
17.1 Extent and Area of Neighborhood Indices 371
17.2 Model Specifications 372
17.3 Results from the Proportional Hazards Duration Models of Land Use
Conversion, Models A and B 373
17.4 Results from the Proportional Hazards Duration Models of Land Use
Conversion, Models C 374
18.1 The Impact of Spatially Weighted Stringency of Environmental Regu¬
lations on Domestic Environmental Regulations {STRING) 393
19.1 OLS Estimates of the augmented non spatial effects Verdoom Law 418
xix
19.2 Diagnostics for the augmented non spatial effects Verdoorn Law 419
19.3 OLS Estimates of the augmented non spatial effects Verdoorn Law .... 420
19.4 Diagnostics for the augmented spatial lag Verdoorn Law 421
19.5 Augmented spatial lag Verdoorn Law: groupwise heteroscedasticity 422
Al IV(2SLS) estimates of the augmented non spatial effects Verdoorn Law 427
A2 The augmented non spatial effects Verdoorn Law with manufacturing
employment growth as the dependent variable 428
A3 Maximum likelihood estimates of the augmented spatial error Verdoorn
Law 429
A4 Augmented spatial error Verdoorn Law : diagnostics 429
A5 The full unrestricted spatial effects Verdoorn Law 430
A6 Diagnostics: the full unrestricted spatial effects Verdoorn Law 430
A7 The reduced unrestricted spatial effects Verdoorn Law 431
A8 Diagnostics: the reduced unrestricted spatial effects Verdoorn Law 432
20.1 Results for the production function without externalities across economies
for the Spanish regions (OLS) 449
20.2 Results for the production function with externalities across economies
for the Spanish regions (ML) 450
20.3 Results for the growth equation without externalities across economies
for the European regions (OLS) 452
20.4 Results for the growth equation without externalities across economies
for the European regions (ML) 453
xxi
List of Figures
6.1 Selected neighborhood schemes for polygon and point spatial objects
A: contiguous neighbors, B: distance neighbors, C: nearest neighbors,
D: distance band neighbors 123
6.2 North Carolina: neighbors links between county seats, maximum dis¬
tance 30 miles 127
6.3 Moran scatterplots for the Freeman Tukey square root transformed SIDS
by county in North Carolina, 1974 78, non centered variable (left),
centered variable (right); no neighbor objects marked by grey disks 128
6.4 Urban locations in Israel, UTM zone 36 (background regions represent
varying natural conditions); left map: positions and axes rug plots; right
map: locations marked by circles proportional to their population size
in 1998 2000 and shaded by percentage population change 1994 96 to
1998 2000 133
6.5 Graph based neighborhood criteria: Gabriel graph (left), sphere of in¬
fluence graph (right) 135
8.1 Marginal effect of X on the probability thaty = 1 175
8.2 Measuring accuracy in the simulation of np 178
8.3 Test results for spatial lag and spatial error autocorrelation, So,o.5o 183
8.4 Test results for spatial lag and spatial error autocorrelation, So.so.o !85
8.5 Test results for spatial lag and spatial error autocorrelation, roo.5o(2OO). 186
8.6 Test results for spatial lag and spatial error autocorrelation, 7b.5o,o(200) . 187
9.1a Linear piecewise linear transformation 216
9.1b Slightly concave piecewise linear transformation 216
9.1c Severely concave piecewise linear transformation 217
9.1d Convex piecewise linear transformation 217
9.2 Y, ln(F), S(Y) 218
9.3a Predictions v S(Y) 218
9.3b Predictions v5(y /4) 219
9.3c Predictions v S(Y) 219
9.3d Predictions v In (Y) 220
9.4a Histogram of spatial regression errors on transformed Y 220
9.4b Histogram of spatial regression errors on untransformed Y 221
9.5a Living area transformation 221
9.5b Age transformation 222
9.5c Other area transformation 222
9.5d Baths transformation 223
9.5e Beds transformation 223
9.5f Time index 224
11.1 Distance based weights adjusted by V; 251
11.2 P, estimates for GWR and BGWRV with an outlier 254
11.3 / statistics for the GWR and BGWRV with an outlier 255
11.4 GWR versus BGWR estimates for Columbus data set 256
11.5 Average V; estimates over all draws and observations 257
xxii
11.6 GWR versus BGWR confidence intervals 258
11.7 Absolute differences between GWR and BGWR household income es¬
timates 259
11.8 Absolute differences between GWR and BGWR house value estimates . 260
11.9 Ohio GWR versus BGWR estimates 261
11.10 Posterior probabilities and v, estimates 262
11.11 Estimates based on a tight imposition of the prior 263
13.1 Log likelihood for the FE spatial model 288
13.2 Log likelihood for the RE spatial model 291
15.1 Functional economic areas with classification of urban core, fringe and
hinterland 324
16.1 U.S. States and Census Regions 344
17.1 Changes in land use pattern in Calvert County, MD 361
17.2a Observed pattern of residential development between 1991 93 377
17.2b Simulated pattern of residential development with endogenous and ex¬
ogenous effects 378
17.2c Simulated pattern of residential development with exogenous effects only 379
17.3 Comparison of Nearest Neighbor Statistics 380
18.1a Stringency of environmental regulations (WEXP) 389
18.1b Stringency of environmental regulations (WCONT) 390
18.1c Stringency of environmental regulations (WDIST) 391
18.2 Stringency of environmental regulations (WEXP) 392
19.1 Dynamics for 3 regions 411
19.2 Iterative solution for 3 regions 412
19.3 Deterministic solution (178 EU regions) 423
19.4 Stochastic solution (178 EU regions) 424
19.5 Empirical and simulated G distributions 426
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| series2 | Advances in spatial science |
| spelling | Advances in spatial econometrics methodology, tools and applications ; with ... 83 tables Luc Anselin ... (ed.) Berlin [u.a.] Springer 2004 XXII, 513 S. graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Advances in spatial science Ökonometrisches Modell (DE-588)4043212-9 gnd rswk-swf Raumwirtschaftstheorie (DE-588)4121557-6 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Raumwirtschaftstheorie (DE-588)4121557-6 s Ökonometrisches Modell (DE-588)4043212-9 s DE-604 Anselin, Luc 1953- Sonstige (DE-588)170116972 oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010369912&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Advances in spatial econometrics methodology, tools and applications ; with ... 83 tables Ökonometrisches Modell (DE-588)4043212-9 gnd Raumwirtschaftstheorie (DE-588)4121557-6 gnd |
| subject_GND | (DE-588)4043212-9 (DE-588)4121557-6 (DE-588)4143413-4 |
| title | Advances in spatial econometrics methodology, tools and applications ; with ... 83 tables |
| title_auth | Advances in spatial econometrics methodology, tools and applications ; with ... 83 tables |
| title_exact_search | Advances in spatial econometrics methodology, tools and applications ; with ... 83 tables |
| title_full | Advances in spatial econometrics methodology, tools and applications ; with ... 83 tables Luc Anselin ... (ed.) |
| title_fullStr | Advances in spatial econometrics methodology, tools and applications ; with ... 83 tables Luc Anselin ... (ed.) |
| title_full_unstemmed | Advances in spatial econometrics methodology, tools and applications ; with ... 83 tables Luc Anselin ... (ed.) |
| title_short | Advances in spatial econometrics |
| title_sort | advances in spatial econometrics methodology tools and applications with 83 tables |
| title_sub | methodology, tools and applications ; with ... 83 tables |
| topic | Ökonometrisches Modell (DE-588)4043212-9 gnd Raumwirtschaftstheorie (DE-588)4121557-6 gnd |
| topic_facet | Ökonometrisches Modell Raumwirtschaftstheorie Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010369912&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT anselinluc advancesinspatialeconometricsmethodologytoolsandapplicationswith83tables |