[R-sig-Geo] Function stslshac {sphet}: heteroskedasticity and autocorrelation consistent (HAC) estimator

[Roger Bivand]

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