dc.contributor.author | Bivand, Roger | |
dc.contributor.author | Piras, Gianfranco | |
dc.date.accessioned | 2015-02-19T13:17:29Z | |
dc.date.accessioned | 2015-02-20T11:08:23Z | |
dc.date.available | 2015-02-19T13:17:29Z | |
dc.date.available | 2015-02-20T11:08:23Z | |
dc.date.issued | 2015-01 | |
dc.identifier.citation | Journal of Statistical Software 2015, 63(18) | nb_NO |
dc.identifier.issn | 1548-7660 | |
dc.identifier.uri | http://hdl.handle.net/11250/276920 | |
dc.description | http://www.jstatsoft.org/v63/i18 | nb_NO |
dc.description.abstract | Recent advances in the implementation of spatial econometrics model estimation tech-
niques have made it desirable to compare results, which should correspond between im-
plementations across software applications for the same data. These model estimation
techniques are associated with methods for estimating impacts (emanating effects), which
are also presented and compared. This review constitutes an up-to-date comparison of
generalized method of moments and maximum likelihood implementations now available.
The comparison uses the cross-sectional US county data set provided by
Drukker, Prucha,
and Raciborski
(
2013d
). The comparisons will be cast in the context of alternatives us-
ing the
MATLAB
Spatial Econometrics toolbox,
Stata
's user-written
sppack
commands,
Python
with
PySAL
and
R
packages including
spdep
,
sphet
and
McSpatial
. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | American Statistical Association | nb_NO |
dc.relation.uri | http://www.jstatsoft.org/v63/i18 | |
dc.rights | Navngivelse 3.0 Norge | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/no/ | * |
dc.subject | spatial econometrics | nb_NO |
dc.subject | maximum likelihood | nb_NO |
dc.subject | generalized method of moments | nb_NO |
dc.subject | estimation | nb_NO |
dc.subject | R | nb_NO |
dc.subject | stata | nb_NO |
dc.subject | python | nb_NO |
dc.subject | MATLAB | nb_NO |
dc.title | Comparing Implementations of Estimation Methods for Spatial Econometrics | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.date.updated | 2015-02-19T13:17:29Z | |
dc.source.volume | 63 | nb_NO |
dc.source.journal | Journal of Statistical Software | nb_NO |
dc.source.issue | 18 | nb_NO |
dc.identifier.cristin | 1224401 | |