TY - JOUR
T1 - Properties of tests for spatial error components
AU - Anselin, Luc
AU - Moreno, Rosina
N1 - Funding Information:
Anselin’s research was supported in part by NSF Grant BCS-9978058 to the Center for Spatially Integrated Social Science (CSISS). Rosina Moreno is grateful to the Regional Research Institute at West Virginia University for its hospitality when carrying out part of this work. Also, she gratefully acknowledges financial support from the DGICYT SEC99-0700. Anil Bera made several useful suggestions, which are greatly appreciated. Other comments were provided by the anonymous referee and by participants in the spatial econometrics sessions at the 40th Western Regional Science Association/Applied Econometrics Association Meetings in Palm Springs, CA, Feb. 2001, and in seminar presentations at the University of Barcelona and Texas A&M University.
PY - 2003/9
Y1 - 2003/9
N2 - In spatial econometrics, the typical alternative of spatial autocorrelation is expressed in the form of a spatial autorregressive process. While the bulk of the literature is devoted to specification tests and estimation methods for this model, alternatives have been suggested as well. In this paper, we consider an alternative that takes the form of the spatial error components formulation proposed by [Kelejian and Robinson (1995)]. We consider a number of specification tests against this alternative, based on both a maximum likelihood framework as well as on a general method of moments estimation approach. We compare the performance of these tests in a series of Monte Carlo simulation experiments for a range of different spatial layouts and under a number of different error distributions.
AB - In spatial econometrics, the typical alternative of spatial autocorrelation is expressed in the form of a spatial autorregressive process. While the bulk of the literature is devoted to specification tests and estimation methods for this model, alternatives have been suggested as well. In this paper, we consider an alternative that takes the form of the spatial error components formulation proposed by [Kelejian and Robinson (1995)]. We consider a number of specification tests against this alternative, based on both a maximum likelihood framework as well as on a general method of moments estimation approach. We compare the performance of these tests in a series of Monte Carlo simulation experiments for a range of different spatial layouts and under a number of different error distributions.
KW - Spatial econometrics
KW - Spatial error components
KW - Specification tests
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U2 - 10.1016/S0166-0462(03)00008-5
DO - 10.1016/S0166-0462(03)00008-5
M3 - Article
AN - SCOPUS:0043032897
SN - 0166-0462
VL - 33
SP - 595
EP - 618
JO - Regional Science and Urban Economics
JF - Regional Science and Urban Economics
IS - 5
ER -