TY - JOUR
T1 - testing isotropy in spatial econometric models
AU - Arbia, Giuseppe
AU - Bee, Marco
AU - Espa, Giuseppe
PY - 2013
Y1 - 2013
N2 - Stationarity in space presents two aspects: homogeneity and isotropy. They correspond
respectively to stationarity under translations and stationarity under rotations. Testing the hypothesis of
isotropy is a common practice in many fields of application of spatial statistics where directional biases
are of paramount importance like, for instance, in meteorology, geology or medicine to name only a few.
10 In spatial econometrics, however, isotropy has been systematically neglected and just assumed away
with no formal testing. This lack is somehow surprising, because anisotropies are more the rule rather
than the exception when observing most economic phenomena. In this paper we introduce a testing
procedure for spatial econometric models based on regional data that derives from Besag’s idea of the
unilateral approximations (Besag, 1974). The power of the test is assessed by means of a Monte Carlo
15 experiment. Finally, we perform an empirical data analysis to test isotropy when analysing the regional
convergence in Italy in the years 2000–2008
AB - Stationarity in space presents two aspects: homogeneity and isotropy. They correspond
respectively to stationarity under translations and stationarity under rotations. Testing the hypothesis of
isotropy is a common practice in many fields of application of spatial statistics where directional biases
are of paramount importance like, for instance, in meteorology, geology or medicine to name only a few.
10 In spatial econometrics, however, isotropy has been systematically neglected and just assumed away
with no formal testing. This lack is somehow surprising, because anisotropies are more the rule rather
than the exception when observing most economic phenomena. In this paper we introduce a testing
procedure for spatial econometric models based on regional data that derives from Besag’s idea of the
unilateral approximations (Besag, 1974). The power of the test is assessed by means of a Monte Carlo
15 experiment. Finally, we perform an empirical data analysis to test isotropy when analysing the regional
convergence in Italy in the years 2000–2008
KW - anisotropy
KW - asymmetry
KW - likelihood ratio test
KW - spatial econometrics
KW - spatial lag models
KW - anisotropy
KW - asymmetry
KW - likelihood ratio test
KW - spatial econometrics
KW - spatial lag models
UR - http://hdl.handle.net/10807/56646
UR - http://www.tandfonline.com/doi/full/10.1080/17421772.2013.804629#.u14lldph4uu
U2 - 10.1080/17421772.2013.804629
DO - 10.1080/17421772.2013.804629
M3 - Article
SN - 1742-1772
VL - 2013
SP - 228
EP - 240
JO - Spatial Economic Analysis
JF - Spatial Economic Analysis
ER -