Trade-offs associated with computational simplifications for estimating spatial statistical/econometric models

Etapes nécessaires afin de rendre l'informatique plus facile pour l'estimation de modèles spatiaux statistiques et économétriques

Daniel A. Griffith and Akio Sone
Additional contact information
Daniel A. Griffith: Syracuse University
Akio Sone: Syracuse University

Working Papers from HAL

Abstract: Spatial statistics and spatial econometrics seek to account for, or exploit, redundant information that is latent in virtually all geo-referenced data. When ignored, such redundancies compromise traditional parameter estimators, causing certain ones to be biased, most to be insufficient and inefficient, and selected ones to be inconsistent. The cost of retaining these desirable statistical properties, though, is a sizeable increase in computational requirements, or considerable numerical intensity, in some instances to an extent that precludes the proper data analysis altogether. Over the years various attempts have been made to reduce this computational burden. The primary objective of this paper is to initiate an evaluation of benefits and costs associated with implementing computational simplifications when estimating spatial statistical and spatial econometric models.

Keywords: Mathematics; Statistics; Operation research; Mathématiques (search for similar items in EconPapers)
Date: 1992
Note: View the original document on HAL open archive server: https://hal.science/hal-01534400
References: View complete reference list from CitEc
Citations:

Published in [Research Report] Institut de mathématiques économiques ( IME). 1992, 22 p., ref. bib. : 15 ref

Downloads: (external link)
https://hal.science/hal-01534400/document (application/pdf)

Related works:
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:hal:wpaper:hal-01534400

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().