Resumo

CEPEDA-CUERVO, Edilberto  e  SICACHA, Jorge Armando. Spatial Econometric Models: A Bayesian Approach. Rev.Colomb.Estad. [online]. 2022, vol.45, n.2, pp.341-361.  Epub 01-Fev-2023. ISSN 0120-1751.  https://doi.org/10.15446/rce.v45n2.92390.

In this paper we propose Bayesian methods to fit econometric regression models, including those where the variability is assumed to follow a regression structure. We formulate the main functions of the statistical R-package BSPADATA, developed according to the proposed methods to obtain posteriori parameter inferences. After that, we include results of simulated studies to illustrate the use of this package and the performance of the proposed methods. Finally, we provide studies to illustrate the applications of the models and compare our results with that obtained by maximum likelihood.

Palavras-chave : Bayesian methods; CAR models; Spatial econometric models; SAR models.

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