GENERALIZED BAYES ESTIMATION OF SPATIAL AUTOREGRESSIVE MODELS

Anoop Chaturvedi () and Mishra Sandeep ()
Additional contact information
Mishra Sandeep: Department of Statistics, University of Allahabad, Allahabad, 211002, India .

Statistics in Transition New Series, 2019, vol. 20, issue 2, 15-32

Abstract: The spatial autoregressive (SAR) models are widely used in spatial econometrics for analyzing spatial data involving spatial autocorrelation structure. The present paper derives a Generalized Bayes estimator for estimating the parameters of a SAR model. The admissibility and minimaxity properties of the estimator have been discussed. For investigating the finite sample behaviour of the estimator, the results of a simulation study have been presented. The results of the paper are applied to demographic data on total fertility rate for selected Indian states.

Keywords: spatial autoregressive model; prior and posterior distributions; generalized Bayes estimator; admissibility and minimaxity; total fertility rate (TFR). (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.21307/stattrans-2019-012 (text/html)

Related works:
Journal Article: GENERALIZED BAYES ESTIMATION OF SPATIAL AUTOREGRESSIVE MODELS (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:20:y:2019:i:2:p:15-32:n:8

DOI: 10.21307/stattrans-2019-012

Access Statistics for this article

Statistics in Transition New Series is currently edited by Włodzimierz Okrasa

More articles in Statistics in Transition New Series from Statistics Poland
Bibliographic data for series maintained by Peter Golla ().