Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Comparing Implementations of Estimation Methods for Spatial Econometrics | Bivand | Journal of Statistical Software
Authors: Roger Bivand, Gianfranco Piras
Title: Comparing Implementations of Estimation Methods for Spatial Econometrics
Abstract: Recent advances in the implementation of spatial econometrics model estimation techniques have made it desirable to compare results, which should correspond between implementations 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 using the MATLAB Spatial Econometrics toolbox, Stata's user-written sppack commands, Python with PySAL and R packages including spdep, sphet and McSpatial.

Page views:: 4755. Submitted: 2013-05-23. Published: 2015-02-16.
Paper: Comparing Implementations of Estimation Methods for Spatial Econometrics     Download PDF (Downloads: 5257)
Supplements:
v63i18-replication.zip: Replication materials Download (Downloads: 404; 713KB)
spdep_0.5-83.tar.gz: R source package Download (Downloads: 294; 3MB)
sphet_1.6.tar.gz: R source package Download (Downloads: 271; 450KB)
SEtoolbox_local.tar.gz: Modified MATLAB Spatial Econometrics Toolbox Download (Downloads: 376; 5MB)
DOI: 10.18637/jss.v063.i18

by
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.