Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/springer_journal/alternative-models-for-describing-spatial-dependence-among-dwelling-JCO1B2KC0b
References (30)
-
K. Mardia (1985)
Minimum norm quadratic estimation of components of spatial covarianceMathematical Geology, 18
-
Mike Rees, N. Cressie (1993)
5. Statistics for Spatial DataJournal of The Royal Statistical Society Series A-statistics in Society, 156
-
M. Tiefelsdorf (2000)
Modelling Spatial Processes -
Steven Bourassa, Eva Cantoni, Martin Hoesli (2005)
Spatial Dependence, Housing Submarkets, and House PricesUrban Research eJournal
-
K. Ord (1975)
Estimation Methods for Models of Spatial InteractionJournal of the American Statistical Association, 70
-
N. A. Cressie (1985)
Fitting Variogram Models by Weighted Least SquaresMathematical Geology, 17
-
J. Besag (1974)
Spatial Interaction and the Statistical Analysis of Lattice SystemsJournal of the royal statistical society series b-methodological, 36
-
B. D. Ripley (1981)
Spatial Statistics -
L. Anselin (1988)
Spatial Econometrics: Methods and Models -
R. rshall, K. rdia (1985)
Minimum norm quadratic estimation of components of spatial covarianceMathematical Geosciences, 17
-
N. Cressie (1994)
Statistics for Spatial Data, Revised Edition.Biometrics, 50
-
A. Militino, M. Ugarte (2001)
Assessing the covariance function in geostatisticsStatistics & Probability Letters, 52
-
K. Mardia, R. Marshall (1984)
Maximum likelihood estimation of models for residual covariance in spatial regressionBiometrika, 71
-
K. Lancaster (1966)
A New Approach to Consumer TheoryJournal of Political Economy, 74
-
P. K. Kitanidis (1985)
Minimum Variance Unbiased Quadratic Estimation of Covariance of Regionalized VariablesMathematical Geology, 17
-
Josae Pinheiro, D. Bates (2001)
Mixed-Effects Models in S and S-PLUSTechnometrics, 43
-
G. Matheron (1963)
Principles of geostatisticsEconomic Geology, 58
-
N. Cressie (1985)
Fitting variogram models by weighted least squaresJournal of the International Association for Mathematical Geology, 17
-
A. Gelfand, S. Ghosh, J. Knight, C. Sirmans (1998)
Spatio-Temporal Modeling of Residential Sales DataJournal of Business & Economic Statistics, 16
-
N. Wrigley, A. Cliff, J. Ord (1981)
Spatial Processes: Models and Applications, 147
-
M. Verbeek (2000)
Modern Econometrics -
S. Basu, T. Thibodeau (1998)
Analysis of Spatial Autocorrelation in House PricesThe Journal of Real Estate Finance and Economics, 17
-
P. Kitanidis (1985)
Minimum-variance unbiased quadratic estimation of covariances of regionalized variablesJournal of the International Association for Mathematical Geology, 17
-
R. Dubin (1998)
Spatial Autocorrelation: A PrimerJournal of Housing Economics, 7
-
R. Nicholson, Z. Griliches (1973)
Price Indexes And Quality Change -
Oleg Smirnov, L. Anselin (2001)
Fast maximum likelihood estimation of very large spatial autoregression models: a characteristic polynomial approachComputational Statistics & Data Analysis, 35
-
J. Warnes, B. Ripley (1987)
Problems with likelihood estimation of covariance functions of spatial Gaussian processesBiometrika, 74
-
S. Rosen (1974)
Hedonic Prices and Implicit Markets: Product Differentiation in Pure CompetitionJournal of Political Economy, 82
-
R. Pace, Ronald Barry, Otis Gilley, C. Sirmans (2000)
A method for spatial–temporal forecasting with an application to real estate pricesInternational Journal of Forecasting, 16
-
P. Kitanidis (1983)
Statistical estimation of polynomial generalized covariance functions and hydrologic applicationsWater Resources Research, 19
- Publisher
- Springer Journals
- Copyright
- Copyright © 2004 by Kluwer Academic Publishers
- Subject
- Economics; Regional/Spatial Science; Financial Services
- ISSN
- 0895-5638
- eISSN
- 1573-045X
- DOI
- 10.1023/B:REAL.0000035310.20223.e9
- Publisher site
- See Article on Publisher Site
Abstract
In this article different spatial statistics techniques to analyze the behavior of used dwelling market prices are compared. We fit two lattice models: simultaneous and conditional autoregressive, a geostatistical model, the so-called universal kriging and finally, a linear mixed-effect model. Different spatial neighborhood structures are considered, as well as different spatial weight matrices and covariance models. The results are illustrated through a real data set of 293 properties from Pamplona, Spain.
Journal
The Journal of Real Estate Finance and Economics – Springer Journals
Published: Oct 13, 2004