R: R: R: Spatial Durbin Model with regimes in a cross section framework

Here the traceback()
4: stop("0 (non-NA) cases")
3: lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...)
2: lm(y ~ x - 1)
1: lagsarlm(GR5101m ~ 0 + (ONE + LVAPC51):(C_Nord + NOC_Nord), data = 
highwaysreg,
      listw, type = "mixed")

No, problem. Data are not private. I tried to use the lmSLX and I got 
the same error

This is the link to the file with errors 
https://onedrive.live.com/redir?resid=4484D82DD190F118!2202&authkey=!A
EXvKmB
o2FVgrQI&ithint=file%2cRData

Thank you

Loredana



-----Messaggio originale-----
Da: Roger Bivand [mailto:Roger.Bivand at nhh.no]
Inviato: mercoled? 21 ottobre 2015 13:26
A: Loredana Mirra
Cc: r-sig-geo at r-project.org
Oggetto: Re: R: [R-sig-Geo] Spatial Durbin Model with regimes in a 
cross section framework

On Wed, 21 Oct 2015, Loredana Mirra wrote:

Hi, and thank you again for your help. Following Anselin (2007) 
Spatial regression analysis in R  I managed to test for the presence 
of spatial regimes (also performing a Chow test) in R.

Since, I need to apply a Spatial Durbin model, I tried fitting it 
using the following (just adding the option "mixed") to the sar 
command in the cases of regimes (Centre_North and South in my case):

durb<-lagsarlm(GR5101m~ 0+ (ONE+
LVAPC51):(C_Nord+NOC_Nord),data=highways,listw, type="mixed")
summary(durb)

I always get this error
error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
 0 (non-NA) cases

Please provide the output of traceback() after the error has occurred. 
I think that if the same model can be fitted with type="lag", but not 
with "mixed", then the lagged X variables are possibly to blame.

Maybe also try to use lmSLX() on the same formula, data and listw 
objects, to see whether you also see failures in the lagged X 
variables. The underlying create_WX() function does check for NAs, but 
may not do it correctly - possibly for this formula.

If this sounds hard, do:

save(highways, listw, file="chow_error.RData")

and make the "chow_error.RData" file available on a link (possibly 
off-list if the data are private).

Hope this helps,

Roger

I checked if there were NA cases and tried with other variables or 
weight matrices. I wonder if this is a good approach or what is wrong.

Thank you for your attention
Loredana Mirra




-----Messaggio originale-----
Da: Roger Bivand [mailto:Roger.Bivand at nhh.no]
Inviato: venerd? 2 ottobre 2015 10:59
A: Loredana Mirra
Cc: r-sig-geo at r-project.org
Oggetto: Re:[R-sig-Geo] Spatial Durbin Model with regimes in a cross 
section framework

On Fri, 2 Oct 2015, Loredana Mirra wrote:

Thank you very much for your kind help. Yes, I should check also if, 
after having estimated separated coefficients,  the difference, if 
any, is statistically significant (using a chow test). Implementing 
such test is the major issue to me. Can you give me an hint about this?

Please see ch. 4 in Kleiber and Zeilis (2008) Applied Econometrics with

You may use anova() on the no-regime model and the regime model, 
which is equivalent to a Chow test (personal communication, Achim 
Zeileis,

2005).

It will however suffer from misspecification such as outliers, 
discussed in section 4.3 and the use of a Wald test with an HC 
covariance

matrix.

Thanks also for the suggestion about the interpretation of output in

A "Chow" test might go through a Likelihood Ratio test, but should 
arguably be presented using the empirical distributions of the 
impacts for each X variable for the no-regime model and for each regime.

Hope this helps,

Roger

Best Regards
Loredana
-----Messaggio originale-----
Da: Roger Bivand [mailto:Roger.Bivand at nhh.no]
Inviato: gioved? 1 ottobre 2015 20:45
A: Loredana Mirra
Cc: r-sig-geo at r-project.org
Oggetto: Re: [R-sig-Geo] Spatial Durbin Model with regimes in a 
cross section framework

On Thu, 1 Oct 2015, Loredana Mirra wrote:

I am writing to ask you a suggestion about the availability of a R 
routine or piece of program for the purposes of my empirical analysis.
I should revise my paper using a Spatial Durbin model. This was 
recommended in order to mitigate a problem due to the possible 
presence of

unobserved factors.

Unfortunately data do not permit to perform a panel but a cross 
section analysis. I do not have troubles to perform a Spatial 
Durbin Model on the entire sample, but I need to study the presence 
of Spatial Regimes. The problem is that I cannot find a program, in 
a cross sections framework. Do you know if there is a program 
available in R

to perform this analysis?

How do you want to handle the "regimes"? Estimate separate 
coefficients for each regime (regime defined as a factor)? If so, 
this is a standard formula construction, and can be used with 
formula objects in model fitting
functions:

lm(mpg ~ 0 + I(factor(am))/(disp + wt), data=mtcars)

or similar - check in detailed discussions of formula objects.

You need to be careful to report impacts, not coefficient values, 
from the Spatial Durbin model.

Hope this helps,

Roger

Thank you very much in advance for your help.

Best regards

Loredana Mirra





-------------------------



Dott.ssa  Loredana Mirra

Universit??? di Roma ???Tor Vergata???

Dipartimento di Economia Diritto e Istituzioni

Via Columbia, 2

00133 Roma

Italia

tel. +390672595725

<mailto:pozzolo at unimol.it> loredana.mirra at uniroma2.it





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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


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voice: +47 55 95 93 55; fax +47 55 95 91 00
e-mail: Roger.Bivand at nhh.no


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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


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