
Spatial Econometrics and Spatial Statistics
Palgrave Macmillan (Publisher)
Published on 24. February 2004
Book
Hardback
XVII, 297 pages
978-1-4039-0797-4 (ISBN)
Description
The field of spatial econometrics has come to include the methods and models that deal with estimation and testing problems encountered when attempting to implement regional economic models. Those problems are often characterized by the difficulties associated with assessing the importance of spatial dependence and spatial heterogeneity. This book includes contributions on spatial proximity, spatial patterning and in particular the spatial association (dependence) contained in local map patterns.
More details
Series
Edition
2004 ed.
Language
English
Place of publication
London
United Kingdom
Publishing group
Palgrave USA
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
With dust jacket
Illustrations
XVII, 297 p.
Dimensions
Height: 235 mm
Width: 160 mm
Thickness: 28 mm
Weight
585 gr
ISBN-13
978-1-4039-0797-4 (9781403907974)
Schweitzer Classification
Other editions
Additional editions

A. Getis | J. Lacambra | H. Zoller
Spatial Econometrics and Spatial Statistics
Book
02/2004
Palgrave Macmillan
€106.99
Shipment within 15-20 days
Persons
SHUMING BAO Senior Researcher, China Data Centre, University of Michigan, USA
KIERAN P. DONAGHY Department of Urban and Regional Planning, University of Illinois at Urbana-Champaign, USA
J. PAUL ELHORST Associate Professor of Regional and Labour Economics, University of Groningen, The Netherlands
BERNARD FINGLETON Department of Land Economy, University of Cambridge, UK
JOHAN F. KAASHOEK Associate professor, Econometric Institute, Erasmus University, The Netherlands
HARRY H. KELEJIAN Professor of Economics, University of Maryland, USA
JAMES P. LESAGE Department of Economics, University of Toledo, USA
DANIEL P. MCMILLEN Professor of economics and Director, Centre for Urban Real Estate, University of Illinois at Chicago, USA
R. KELLEY PACE Louisiana Real Estate Chair of Real Estate, Louisiana State University, USA
JEAN H. P. PAELINCK Emeritus Professor, Erasmus University, The Netherlands
MARIA PLOTNIKOVA Department of Urban and Regional Planning, University of Illinois at Urbana-Champaign, USA
SERGIO J. REY Department of Geography, San Diego State University, USA
PETER A. ROGERSON Professor of Geography, University of Buffalo, USA
TONY SMITH Professor of Regional Science and Systems Engineering, University of Pennsylvania, USA
F. JAVIER TRIVEZ Associate Professor, Department of Economic Analysis, University of Zaragoza, Spain
LI-AN XU Pharmaceutical Research Institute, Bristol-Myers Squibb Company, Princeton, USA
YEVGENY YUZEFOVICH Department of Economics, University of Maryland, USA
Content
Preface Notes on the Contributors PART I: INTRODUCTION Contributions to Spatial Econometrics and Spatial Statistics; A.Getis & J.Mur Theoretical Economic Geography and Spatial Econometrics: Bridging the Gap Between Theory and Evidence; B.Fingleton PART II: SPATIAL ECONOMETRICS ESTIMATION Spatial Autoregressive Local Estimation; R.K.Pace & J.P.LeSage Aggregation Bias in Maximum Likelihood estimation of spatial Autoregressive Processes; T.Smith Econometric Estimation of a Spatial Dynamic Model in Continuous Space and Continuous Time: an Empirical Demonstration; K.P.Donaghy & M.Plotnikova Using Matrix Exponentials to Estimate Spatial Probit/Tobit Models; J.P.LeSage & R.K.Pace PART III: SPATIAL DEPENDENCE AND SPATIAL ERRORS Properties of Tests for Spatial Error Components: A Further Analysis; H.H.Kelejian & Y.Yuzefovich Some Proposals for Discriminating Between Spatial Processes; F.J.Trivez & J.Mur Serial and Spatial Error Dependence in Space-Time Models; J.P.Elhorst Spatial Dependence in the Evolution of Regional Income Distributions; S.J.Rey PART IV: SPATIAL PATTERNS AND LOCAL SPATIAL ANALYSIS On Connectropy; J.F.Kaashoek, J.H.P.Paelinck & H.G.Zoller Locally Weighted Regression and Time-Varying Distance Gradients; D.P.McMillen The Statistical Significance of the Maximum Local Statistic; P.A.Rogerson Detecting Spatial Clusters: A Bayesian Approach with Application to Identifying Disability Patterns in Mississippi and Alabama; X-A .Xu & S.Bao Bibliography Author Index Subject Index