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008			101115s2004 enk o 000 0 eng d
020			_a9781849503013 (electronic bk.) : _c£70.95 ; €99.95 ; $126.95
040			_aUtOrBLW _cUtOrBLW
050		4	_aHB139 _b.S63 2004
072		7	_aKCH _2bicssc
072		7	_aECO _2bicssc
072		7	_aBUS021000 _2bisacsh
072		7	_aBUS039000 _2bisacsh
080			_a330.43
082	0	4	_a330.015195 _222
245	0	0	_aSpatial and spatiotemporal econometrics _h[electronic resource] / _cedited by James P. Lesage and R. Kelley Pace.
260			_aBingley, U.K. : _bEmerald, _c2004.
300			_a1 online resource (vi, 331 p.).
490	1		_aAdvances in econometrics, _x0731-9053 ; _vv. 18
505	0		_aIntroduction / 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.
520			_aThis 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.
588	0		_aPrint version record
650		7	_aBusiness & Economics _xEconometrics. _2bisacsh
650		7	_aBusiness & Economics _xEconomics _xMacroeconomics. _2bisacsh
650		7	_aEconometrics. _2bicssc
650		0	_aEconometrics.
700	1		_aLeSage, James P.
700	1		_aPace, R. Kelley.
776	1		_z9780762311484
830		0	_aAdvances in econometrics ; _vv. 18.
856	4	0	_uhttps://www.emerald.com/insight/publication/doi/10.1016/S0731-9053(2004)18
913			_1BMEbacklist
999			_c31861 _d31861