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Spatial and spatiotemporal econometrics

LeSage, James P.

Spatial and spatiotemporal econometrics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Spatial and spatiotemporal econometricsedited by James P. Lesage and R. Kelley Pace.
其他作者:	LeSage, James P.
出版者:	Bingley, U.K. :Emerald,2004.
面頁冊數:	1 online resource (vi, 331 p.).
標題:	Business & EconomicsEconometrics.
電子資源:	http://www.emeraldinsight.com/0731-9053/18
ISBN:	9781849503013 (electronic bk.)

Spatial and spatiotemporal econometrics
Spatial and spatiotemporal econometrics[electronic resource] /edited by James P. Lesage and R. Kelley Pace. - Bingley, U.K. :Emerald,2004. - 1 online resource (vi, 331 p.). - Advances in econometrics,v. 180731-9053 ;. - Advances in econometrics ;17.

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 forU.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 modelsagainst box-cox alternatives with spatial lag dependence / Badi H. Baltagi, Dong Li -- Spatial lags and spatial errors revisited : some MonteCarlo evidence / Robin Dubin.

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 ortransactions of economic agents are related to the behaviour of nearby agents. Dependence of one observation on neighbouring observations violates the typicalassumption 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 contributionsto 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, andregional labour markets. The volume is supported by a web site containing datasets and software to implement many of the methods described by contributors to this volume.

ISBN: 9781849503013 (electronic bk.)Subjects--Topical Terms:

532721
Business & Economics
--Econometrics.

LC Class. No.: HB139 / .S63 2004

Dewey Class. No.: 330.015195

Universal Decimal Class. No.: 330.43

Spatial and spatiotemporal econometrics
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520 $a 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 ortransactions of economic agents are related to the behaviour of nearby agents. Dependence of one observation on neighbouring observations violates the typicalassumption 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 contributionsto 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, andregional labour markets. The volume is supported by a web site containing datasets and software to implement many of the methods described by contributors to this volume.
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