dc.contributor.author | Bivand, Roger S. | |
dc.date.accessioned | 2010-10-19T12:52:39Z | |
dc.date.available | 2010-10-19T12:52:39Z | |
dc.date.issued | 2010-08 | |
dc.identifier.issn | 0804-6824 | |
dc.identifier.uri | http://hdl.handle.net/11250/163240 | |
dc.description.abstract | Despite attempts to get around the Jacobian in fitting spatial econometric
models by using GMM and other approximations, it remains a central problem
for maximum likelihood estimation. In principle, and for smaller data sets,
the use of the eigenvalues of the spatial weights matrix provides a very rapid
and satisfactory resolution. For somewhat larger problems, including those
induced in spatial panel and dyadic (network) problems, solving the eigenproblem
is not as attractive, and a number of alternatives have been proposed.
This paper will survey chosen alternatives, and comment on their relative usefulness. | en |
dc.language.iso | eng | en |
dc.publisher | Norwegian School of Economics and Business Administration. Department of Economics | en |
dc.relation.ispartofseries | Discussion paper | en |
dc.relation.ispartofseries | 2010:20 | en |
dc.title | Computing the Jacobian in spatial models : an applied survey | en |
dc.type | Working paper | en |
dc.subject.nsi | VDP::Samfunnsvitenskap: 200::Økonomi: 210::Økonometri: 214 | en |