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Spatial and spatiotemporal econometrics / edited by James P. Lesage and R. Kelley Pace.

EBSCOhost Academic eBook Collection (North America) Available online

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Format:
Book
Contributor:
LeSage, James P.
Pace, R. Kelley.
Series:
Advances in econometrics ; v. 18.
Advances in econometrics, 0731-9053 ; v. 18
Language:
English
Subjects (All):
Econometrics.
Physical Description:
1 online resource (341 p.)
Place of Publication:
Amsterdam : Elsevier JAI, 2004.
Language Note:
English
Summary:
This volume focuses on econometric models that confront estimation and inference issues occurring when sample data exhibit spatial or spatiotemporal dependence. This can arise when decisions or transactions of economic agents are related to the behaviour of nearby agents. Dependence of one observation on neighbouring observations violates the typical assumption of independence made in regression analysis. Contributions to this volume by leading experts in the field of spatial econometrics provide details regarding estimation and inference based on a variety of econometric methods including, maximum likelihood, Bayesian and hierarchical Bayes, instrumental variables, generalized method of moments, maximum entropy, non-parametric and spatiotemporal. An overview of spatial econometric models and methods is provided that places contributions to this volume in the context of existing literature. New methods for estimation and inference are introduced in this volume and Monte Carlo comparisons of existing methods are described. In addition to topics involving estimation and inference, approaches to model comparison and selection are set forth along with new tests for spatial dependence and functional form. These methods are applied to a variety of economic problems including: hedonic real estate pricing, agricultural harvests and disaster payments, voting behaviour, identification of edge cities, and regional labour markets. The volume is supported by a web site containing data sets and software to implement many of the methods described by contributors to this volume.
Contents:
Introduction / James P. LeSage, R. Kelley Pace
Bayesian model choice in spatial econometrics / Leslie W. Hepple
A Bayesian probit model with spatial dependencies / Tony E. Smith, James P. LeSage
Instrumental variable estimation of a spatial autoregressive model with autoregressive disturbances : large and small sample results / Harry H. Kelejian, Ingmar R. Prucha, Yevgeny Yuzefovich
Generalized maximum entropy estimation of a first order spatial autoregressive model / Thomas L. Marsh, Ron C. Mittelhammer
Employment subcenters and home price appreciation rates in metropolitan Chicago / Daniel P. McMillen
Searching for housing submarkets using mixtures of linear models / M.D. Ugarte, T. Goicoa, A.F. Militino
Spatio-temporal autoregressive models for U.S. unemployment rate / Xavier de Luna, Marc G. Genton
A learning rule for inferring local distributions over space and time / Stephen M. Stohs, Jeffrey T. LaFrance
Testing for linear and log-linear models against box-cox alternatives with spatial lag dependence / Badi H. Baltagi, Dong Li
Spatial lags and spatial errors revisited : some Monte Carlo evidence / Robin Dubin.
Notes:
Description based upon print version of record.
Includes bibliographical references.
Print version record
ISBN:
1-281-01647-0
9786611016470
0-08-047181-1
OCLC:
437177067

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