About predictions in spatial autoregressive models: Optimal and almost optimal strategies
We address the problem of prediction in the classical spatial autoregressive lag model for areal data. In contrast with the spatial econometrics literature, the geostatistical literature has devoted much attention to prediction using the Best Linear Unbiased Prediction approach. From the methodological point of view, we explore the limits of the extension of BLUP formulas in the context of the spatial autoregressive lag models for in sample prediction as well as out-of-sample prediction simultaneously at several sites. We propose a more tractable “almost best” alternative. From an empirical perspective, we present data-based simulations to compare the efficiency of the classical formulas with the best and almost best predictions.
|Date of creation:||18 Dec 2013|
|Date of revision:||Sep 2014|
|Contact details of provider:|| Phone: (+33) 5 61 12 86 23|
Web page: http://www.tse-fr.eu/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- D A Griffith & R J Bennett & R P Haining, 1989. "Statistical analysis of spatial data in the presence of missing observations: a methodological guide and an application to urban census data," Environment and Planning A, Pion Ltd, London, vol. 21(11), pages 1511-1523, November.
- Kelejian, Harry H. & Prucha, Ingmar R., 2007. "The relative efficiencies of various predictors in spatial econometric models containing spatial lags," Regional Science and Urban Economics, Elsevier, vol. 37(3), pages 363-374, May.
- James P. LeSage & R. Kelley Pace, 2004. "Models for Spatially Dependent Missing Data," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 233-254, 09.
When requesting a correction, please mention this item's handle: RePEc:tse:wpaper:27788. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If references are entirely missing, you can add them using this form.