Function stslshac {sphet}: heteroskedasticity and autocorrelation consistent (HAC) estimator
On Sat, 19 Sep 2015, monika nov wrote:
Dear R-users, I have quite basic question for econometricians, however I would like to be sure in this. If I use a HAC estimator of the variance-covariance (VC) matrix for a spatial econometric model, do I still need to test the residuals for spatial autocorrelation and heteroscedasticity? (in particular I am using function stslshac available in package sphet. The estimator is based on Kelejian, H.H. and Prucha, I.R. (2007) HAC estimation in a spatial framework, Journal of Econometrics, 140, pages 131?154). What if the residuals from model estimated by stslshac are spatially autocorrelated and (or) heteroscedastic? Can I still use this estimator with HAC estimate of VC matrix or shall I go for different estimator or specification? Do the estimates have required properties (are they unbiased, consistent, efficient)? I would be grateful for any reaction.
Does this reference throw any light on the question? I'm not aware of
implementations:
@article{
year={2015},
issn={1864-4031},
journal={Letters in Spatial and Resource Sciences},
doi={10.1007/s12076-015-0146-2},
title={Critical issues in spatial models: error term specifications,
additional endogenous variables, pre-testing, and Bayesian analysis},
url={http://dx.doi.org/10.1007/s12076-015-0146-2},
publisher={Springer Berlin Heidelberg},
keywords={Specifications of spatial models; Additional endogenous
variables; Pre-testing; Bayesian analysis; C01; C12; C13},
author={Kelejian, HarryH.},
pages={1-24},
language={English}
}
Roger
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Roger Bivand Department of Economics, Norwegian School of Economics, Helleveien 30, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 91 00 e-mail: Roger.Bivand at nhh.no