TY  - RPRT
CY  - Toulouse
ID  - publications15788
UR  - http://tse-fr.eu/pub/27788
A1  - Thomas-Agnan, Christine
A1  - Laurent, Thibault
A1  - Goulard, Michel
Y1  - 2014/09/25/
N2  - We address the problem of prediction in the spatial autoregressive SAR model for areal data which is classically used in spatial econometrics. With the Kriging theory, prediction using Best Linear Unbiased Predictors is at the heart of the geostatistical literature. From the methodological point of view, we explore the limits of the extension of BLUP formulas in the context of the spatial autoregressive SAR models for out-of-sample prediction simultaneously at several sites. We propose a more tractable \almost best" alternative and clarify the relationship between the BLUP and a proper EM-algorithm predictor. From an empirical perspective, we present data-based simulations to compare the efficiency of the classical formulas with the best and almost best predictions.
PB  - TSE Working Paper
T3  - TSE Working Paper
KW  - Spatial simultaneous autoregressive models
KW  - out of sample prediction
KW  - best linear unbiased prediction
M1  - working_paper
TI  - About predictions in spatial autoregressive models
AV  - public
EP  - 19
ER  -