Dear Roger,

Thank you for your email.

I am sorry for HTML containing email. I am not very good in IT so I

didn't know that my email client is using HTML by default. Now I have

tried to turn it off and I would be very grateful if you could let me

know if it is all right now.

Regarding my question. 'if you use a model with semiparametric fitting

of HAC, how might you check that it actually worked'

is not exactly what I wanted to ask. Although answer to this question

would be also helpful.

What I wanted to ask is a bit more specific. I wanted to know, whether

it is a good practice to apply tests for spatial autocorrelation (for

example one of them can be run in R by function moran.test, package

sphet) to residuals from a model obtained by function stslshac

(package spdep). Further I would like to know whether significance of

this test (rejecting the null hypothesis) means, that I should not use

the estimate produced by stslshac function because model is

missspecified. This is maybe more an econometric theory question

rather than R programming question and I am very sorry if I am not

supposed to ask these questions in this forum.

This is quite specific and technical question so I think that the

question may not be understandable for people without econometric

background, even if asked clearly.

I do not think that including an example of code would help to

understand my question, however I am including one bellow.

Thank you for your suggestion about r-sig-geo mailing list, I have

already posted it there.

Best wishes

Monika

####################################################################################################################################

library(sphet)

library(spdep)

data(auckland)

# In the following part objects needed as arguments for stslshac

function are created:

auckland.listw<-nb2listw(auckland.nb, style="W")

coord1 <- cbind(seq(1, nrow(auckland)), auckland$Easting, auckland$Norting)

id1 <- seq(1, nrow(auckland))

tmp <- distance(auckland, region.id = id1, output = TRUE,

type = "NN", nn = 10, shape.name = "shapefile",

region.id.name = "id1",

firstline = TRUE, file.name = "auckland_nn_10.GWT")

coldist <- read.gwt2dist(file = "auckland_nn_10.GWT", region.id = id1,skip = 1)

# Now follows the estimation and printing of summary of results:

AucklandHAC<-(stslshac(Deaths.1977.85~Deaths.1977.85+Easting+Northing,

listw=auckland.listw, type=c("Triangular"),

distance=coldist,data=auckland))

summary(AucklandHAC)

# Now follows an example of the tests I am asking about. I am not sure

whether it is econometrically correct to apply this test for residuals

estiated by stslshac function

moran.test(AucklandHAC$residuals,listw=auckland.listw, alternative="two.sided")

######################################################################################################################

Here are the results I get after running the Moran.test. The test is

significant and the null hypothesis is rejected. I am wondering, can I

still use the stslshac function and its estimate?

Moran's I test under randomisation

data: AucklandHAC$residuals

weights: auckland.listw

Moran I statistic standard deviate = -4.302, p-value = 1.693e-05

alternative hypothesis: two.sided

sample estimates:

Moran I statistic Expectation Variance

-0.230081673 -0.006024096 0.002712539

On 19 September 2015 at 18:48, Roger Bivand <

[hidden email]> wrote:

> monika nov <monika.novac <at> gmail.com> writes:

>

>>

>> 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).

>>

>

> Please consider posting on R-sig-geo, since your question concerns spatial

> regression. Roughly, you might mean that if you use a model with

> semiparametric fitting of HAC, how might you check that it actually worked,

> but your meaning isn't obvious. If you include an example using a built-in

> data set, then your intentions would be clearer.

>

> ...

>> I would be grateful for any reaction.

>>

>> Monika

>>

> PS. Please post plain text, not HTML

>

> Roger Bivand

> ______________________________________________

>

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>

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______________________________________________

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https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide

http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.