A test to select between spatial weighting matrices

Stephen Hall, George Tavlas and Deborah Gefang

Journal of Spatial Econometrics, 2023, vol. 4, issue 1, 1-10

Abstract: Abstract There exist a number of ways of selecting the best spatial weighting matrix in a spatial regression framework. But these methods all work under the assumption that there is only one matrix in the final model and they simply aim to pick the best one. We propose an encompassing tests which allows for the possibility that the final preferred model may have two or more spatial weighting matrices. We validate the proposed test through a Monte Carlo study. We then illustrate the test by applying it to a two-equation simultaneous system determining sovereign bond ratings and spreads for two groups comprising northern and Southern Euro-area countries.

Keywords: Spatial weighting matrix; Cross-country spillovers; Spatial estimation (search for similar items in EconPapers)
JEL-codes: E3 G01 G21 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s43071-022-00032-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:jospat:v:4:y:2023:i:1:d:10.1007_s43071-022-00032-9

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/43071

DOI: 10.1007/s43071-022-00032-9

Access Statistics for this article

Journal of Spatial Econometrics is currently edited by Giuseppe Arbia, Lung Fei Lee and James LeSage

More articles in Journal of Spatial Econometrics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().