Advances in Spatial Econometrics: Methodology, Tools and Applications

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Luc Anselin, Raymond Florax, Sergio J. Rey
Springer Science & Business Media, Aug 12, 2004 - Business & Economics - 514 pages
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The volume on New Directions in Spatial Econometrics appeared in 1995 as one of the first in the then new Springer series on Advances in Spatial Sciences. It very quickly became evident that the book satisfied a pent up demand for a collection of advanced papers dealing with the methodology and application of spatial economet rics. This emerging subfield of applied econometrics focuses on the incorporation of location and spatial interaction in the specification, estimation and diagnostic testing of regression models. The current effort is a follow up to the New Directions volume. Even though the number of empirical and theoretical journal articles dealing with various as pects of spatial econometrics has grown tremendously in the recent past, the need remained to bring together an advanced collection on methodology, tools and appli cations. This volume contains several papers that were presented at special sessions on spatial econometrics organized as part of a number of conferences of the Re gional Science Association International. In addition, a few papers were invited for submission. All papers were refereed. The focus in the volume reflects the advances made in the field in recent years.
 

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Contents

Econometrics for Spatial Models Recent Advances
1
12 Recent Advances
2
13 Specification Testing and Estimation
11
14 Discrete Choice Nonparametric and Bayesian Approaches
14
15 Spatial Externalities
18
16 Urban Growth and Agglomeration Economies
20
17 Trade and Economic Growth
22
18 Future Directions
24
112 The GWR and Bayesian GWR Models
243
113 Estimation of the BGWR Model
246
114 Examples
253
115 Conclusions
263
Spatial Externalities
265
Hedonic Price Functions and Spatial Dependence Implications for the Demand for Urban Air Quality
267
122 Hedonic Functions and Benefit Estimation
268
123 Econometric Issues
270

Specification Testing and Estimation
27
The Performance of Diagnostic Tests for Spatial Dependence in Linear Regression Models A MetaAnalysis of Simulation Studies
29
22 MelaAnalysis and Response Surfaces
32
23 Spatial Dependence Tests and Data Generating Processes
34
24 A Taxonomy of Spatial Dependence Tests
40
25 Review of the Simulation Literature on Spatial Dependence Tests
41
26 Experimental Design and MetaRegression Results
43
27 Conclusions
63
MoranFlavored Tests with Nuisance Parameters Examples
67
32 Test Statistics
68
33 Weights Matrix
69
34 Nuisance Parameters
70
35 Conditions
74
36 Conclusions
76
Synopsis of Conditions
77
The Influence of Spatially Correlated Heteroskedasticity on Tests for Spatial Correlation
79
42 The Model
81
43 Basic Results
87
44 Conclusions
90
Appendix
91
A Taxonomy of Spatial Econometric Models for Simultaneous Equations Systems
99
53 Taxonomy
102
54 Estimation Issues
105
55 Monte Carlo Experiments
109
56 Results
111
57 Conclusions
114
Exploring Spatial Data Analysis Techniques Using R The Case of Observations with No Neighbors
121
62 Implementing Spatial Weights Objects in R
122
Consequences of Observations with No Neighbors
125
Clusters of Towns in an Urban System with Sparsely Populated Regions
129
65 Conclusions
140
Discrete Choice and Bayesian Approaches
143
Techniques for Estimating Spatially Dependent Discrete Choice Models
145
72 Heteroskedastic Estimators
149
73 Full Spatial Information Estimators
151
74 Weighted NonLinear Least Squares Estimators
160
75 Conclusions
166
Probit in a Spatial Context A Monte Carlo Analysis
169
82 Probit Models
170
83 The RIS Simulator
176
84 Monte Carlo Data
178
85 Monte Carlo Results
181
86 Spatial Linear Probability Model
187
87 Conclusions
192
Simultaneous Spatial and Functional Form Transformations
197
92 Simultaneous Spatial and Variable Transformations
200
93 Baton Rouge Housing
206
94 Conclusions
213
Locally Weighted Maximum Likelihood Estimation Monte Carlo Evidence and an Application
225
102 The Locally Weighted LogLikelihood Function
226
103 Monte Carlo Experiments
229
104 Density Zoning in 1920s Chicago
232
105 Conclusions
236
Computational Steps for an LWML Model
237
A Family of Geographically Weighted Regression Models
241
124 Estimates
271
125 Conclusions
278
Data Sources
279
Prediction in the Panel Data Model with Spatial Correlation
283
132 Estimation
284
133 Prediction
291
134 Conclusions
295
External Effects and Cost of Production
297
142 Sources of Regional and Industrial Externalities
299
Duality Theory and External Effects
302
144 Spatial and Sectoral Externalities
304
145 Data
309
146 Empirical Results
310
147 Conclusions
316
Urban Growth and Agglomeration Economies
319
Identifying UrbanRural Linkages Tests for Spatial Effects in the CarlinoMills Model
321
152 Spatial Context of the Analysis
322
153 Econometric Model
325
154 Empirical Results
329
155 Conclusions
333
Economic Geography and the Spatial Evolution of Wages in the United States
335
163 The Model
336
164 Data
343
165 Econometric Analysis
350
166 Conclusions
357
Endogenous Spatial Externalities Empirical Evidence and Implications for the Evolution of Exurban Residential Land Use Patterns
359
172 Spatial Externalities and Residential Location
360
173 A Model of Land Use Conversion with Interaction Effects
362
174 Estimation of the Empirical Model
366
175 Predicted Patterns of Development
375
176 Conclusions
379
Trade and Economic Growth
381
Does Trade Liberalization Cause a RacetotheBottom in Environmental Policies? A Spatial Econometric Analysis
383
182 Model Specification
385
183 Data Description and Hypothesis Specification
388
185 Conclusions
395
Regional Economic Growth and Convergence Insights from a Spatial Econometric Perspective
397
193 The Single Equation Approach to the Verdoorn Law
401
Problems and Issues
405
195 Convergence Theory and Methodology
409
196 Empirical Convergence Analysis
416
197 Conclusions
425
Description of Data
427
Growth and Externalities Across Economies An Empirical Analysis Using Spatial Econometrics
433
202 Do Spatial Externalities Matter?
434
203 A Simple Growth Model With Spillovers Across Regions
436
204 Empirical Specifications
439
205 The Spatial Econometrics of Considering Externalities Across Economies
441
206 Empirical Evidence
448
207 Conclusions
453
References
457
Author Index
489
Index
499
List of Contributors
507
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