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New Directions in Spatial Econometrics: Advances in Spatial Science

Editat de Luc Anselin, Raymond Florax
en Limba Engleză Paperback – 24 noi 2011
The field of spatial econometrics, which is concerned with statistical and econo­ metric techniques to be used to handle spatial effects in multiregional models, was first touched upon in the 1950s. It was given its name in the early 70s by Jean Paelinck and has expanded since. Its development can be monitored in various monographs that have been published since, starting with the seminal work by Andrew Cliff and Keith Ord. Also, the wide array of journals in which contributions to spatial econometrics have been published, shows that the relevance of the field is not restricted to regional science, but extends to geography, spatial statistics, biology, psychology, political science and other social sciences. This volume contains a collection of papers that were presented at special sessions on spatial econometrics organized in the context of the European and North American conferences of the Regional Science Association International, that took place in Louvain la Neuve (August 25-28,1992) and in Houston (November 11-14, 1993), respectively. Apart from these conference papers some contributions were written especially for this volume. The central idea of this book is to communicate the state of the art of spatial econometrics and to offer a number of new directions for future research. In order to do so, the editors sought contributions of leading scholars currently active in this field.
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Specificații

ISBN-13: 9783642798795
ISBN-10: 3642798799
Pagini: 444
Ilustrații: XX, 420 p.
Dimensiuni: 155 x 235 x 23 mm
Greutate: 0.62 kg
Ediția:Softcover reprint of the original 1st ed. 1995
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Advances in Spatial Science

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

1 New Directions in Spatial Econometrics: Introduction.- I-A: Spatial Effects in Linear Regression Models Specification of Spatial Dependence.- 2 Small Sample Properties of Tests for Spatial Dependence in Regression Models: Some Further Results.- 3 Spatial Correlation: A Suggested Alternative to the Autoregressive Model.- 4 Spatial Autoregressive Error Components in Travel Flow Models: An Application to Aggregate Mode Choice.- I-B: Spatial Effects in Linear Regression Models Spatial Data and Model Transformations.- 5 The Impacts of Misspecified Spatial Interaction in Linear Regression Models.- 6 Computation of Box-Cox Transform Parameters: A New Method and its Application to Spatial Econometrics.- 7 Data Problems in Spatial Econometric Modeling.- 8 Spatial Filtering in a Regression Framework: Examples Using Data on Urban Crime, Regional Inequality, and Government Expenditures.- II: Spatial Effects in Limited Dependent Variable Models.- 9 Spatial Effects in Probit Models: A Monte Carlo Investigation.- 10 Estimating Logit Models with Spatial Dependence.- 11 Utility Variability within Aggregate Spatial Units and its Relevance to Discrete Models of Destination Choice.- III: Heterogeneity and Dependence in Space-Time Models.- 12 The General Linear Model and Spatial Autoregressive Models.- 13 Econometric Models and Spatial Parametric Instability: Relevant Concepts and an Instability Index.- 14 Bayesian Hierarchical Forecasts for Dynamic Systems: Case Study on Backcasting School District Income Tax Revenues.- 15 A Multiprocess Mixture Model to Estimate Space-Time Dimensions of Weekly Pricing of Certificates of Deposit.- Author Index.- Contributors.