Specification of spatial models: A simulation study on weights matrices

The correct specification of spatial models, and especially the choice of the spatial weights matrix, represents a crucial decision for researchers using georeferenced data. However, few guidelines exist on which weights matrix is most appropriate in certain cases. This paper therefore (1) studies the sensitivity of testing and estimating spatial models with different weights matrix specifications and (2) formulates recommendations for researchers applying spatial models regarding model selection and weights matrix specification. The research is based on Monte Carlo simulations with synthetic data. Copyright (c) 2008 the author(s). Journal compilation (c) 2008 RSAI.

[1]  A. Getis,et al.  Using AMOEBA to Create a Spatial Weights Matrix and Identify Spatial Clusters , 2006 .

[2]  Daniel A. Griffith,et al.  On the quality of likelihood-based estimators in spatial autoregressive models when the data dependence structure is misspecified , 1998 .

[3]  Harvey S. Rosen,et al.  Budget spillovers and fiscal policy interdependence: Evidence from the states , 1993 .

[4]  Sergio J. Rey,et al.  Specification Searches in Spatial Econometrics: The Relevance of Hendry's Methodology , 2003 .

[5]  Timothy G. Conley,et al.  Economic Distance and Cross-Country Spillovers , 2001 .

[6]  A. Getis,et al.  Constructing the Spatial Weights Matrix Using a Local Statistic , 2004 .

[7]  François Bavaud,et al.  MODELS FOR SPATIAL WEIGHTS: A SYSTEMATIC LOOK , 2010 .

[8]  H. Akaike.  A new look at the statistical model identification , 1974 .

[9]  Luc Anselin,et al.  Under the hood , 2002 .

[10]  Steven Farber,et al.  Topology and Dependency Tests in Spatial and Network Autoregressive Models , 2009 .

[11]  Luc Anselin,et al.  Properties of Tests for Spatial Dependence in Linear Regression Models , 2010 .

[12]  Roger Th. A. J. Leenders,et al.  Modeling social influence through network autocorrelation: constructing the weight matrix , 2002, Soc. Networks.

[13]  L. Anselin.  Spatial Econometrics: Methods and Models , 1988 .

[14]  H. Bozdogan.  Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions , 1987 .

[15]  Anil K. Bera,et al.  Simple diagnostic tests for spatial dependence , 1996 .

[16]  J. Keith Ord,et al.  Spatial Processes Models and Applications , 1981 .

[17]  Bart J. Bronnenberg.  Spatial Models in Marketing Research and Practice , 2004 .

[18]  Tony E. Smith,et al.  Estimation Bias in Spatial Models with Strongly Connected Weight Matrices , 2009 .

[19]  Johan H. L. Oud,et al.  How to Get Rid of W: A Latent Variables Approach to Modelling Spatially Lagged Variables , 2008 .

[20]  M. Goodchild,et al.  GIS and spatial data analysis: Converging perspectives , 2003 .

[21]  Darren M. Scott,et al.  Weight matrices for social influence analysis: An investigation of measurement errors and their effect on model identification and estimation quality , 2008, Soc. Networks.

[22]  Harry H. Kelejian,et al.  A suggested test for spatial autocorrelation and/or heteroskedasticity and corresponding Monte Carlo results , 1998 .

[23]  F. Stetzer,et al.  Specifying Weights in Spatial Forecasting Models: The Results of Some Experiments , 1982 .

[24]  P. Burridge,et al.  On the Cliff‐Ord Test for Spatial Correlation , 1980 .