Goulard, Michel, Laurent, Thibault and Thomas-Agnan, Christine (2017) About predictions in spatial autoregressive models : Optimal and almost optimal strategies. Spatial Economic Analysis, 12 (2-3). pp. 304-325.

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Identification Number : 10.1080/17421772.2017.1300679


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.

Item Type: Article
Sub-title: Optimal and almost optimal strategies
Language: French
Date: April 2017
Refereed: Yes
Uncontrolled Keywords: Spatial simultaneous autoregressive models, out of sample prediction, best linear unbiased prediction
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 28 Apr 2017 07:28
Last Modified: 31 Aug 2023 07:46
OAI Identifier: oai:tse-fr.eu:31635
URI: https://publications.ut-capitole.fr/id/eprint/23765

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