[R-sig-Geo] Question impacts lagged independent variables lagsarlm

Jorge Cárcamo jcarcamo03 at gmail.com
Sun Jun 5 17:33:13 CEST 2016 

Dear Prof. Bivand,

Many thanks for your time and attention. I will do as you suggest.

Best regards,

Jorge
On Jun 5, 2016 17:22, "Roger Bivand" <Roger.Bivand at nhh.no> wrote:

> On Sun, 5 Jun 2016, Jorge Cárcamo wrote:
>
> Prof. Bivand,
>>
>> Many thanks for your clarification. I think that I should read Läpple &
>> Kelley again.
>>
>> One more question, I assume that if I create independent lag variables
>> with: data$w_xxx <- lag.listw(sy15,data$xxx) and add them into the model I
>> can get the impacts of these lag variables; however, if I add them into
>> the
>> model, do I need to change the type="lag" instead of "mixed" when running
>> lagsarlm command?
>>
>
> Don't even think about this, it is senseless. The impact of x_r is as
> given in the formula, the only contrast is between the impacts in the
> model="lag" case and the model="mixed" case. Because of the interaction
> between \rho and the \betas (and \gammas) in the y = \rho W y + ... models,
> you only get one set of impacts per x_r per model. You can interprete the
> differences between the three impact components between models, but avoid
> playing with stuff without doing all of the maths first.
>
> Roger
>
>
>> Many thanks for your attention.
>>
>> Jorge
>>
>> *Ing. Jorge Alfredo Cárcamo, M. Sc., Ph. D. (c)*
>> Agriculture economics
>> Georg-August-Universität Göttingen
>>
>> On Sun, Jun 5, 2016 at 2:17 PM, Roger Bivand <Roger.Bivand at nhh.no> wrote:
>>
>> On Sat, 4 Jun 2016, Jorge Cárcamo wrote:
>>>
>>> Dear all,
>>>
>>>>
>>>> I am working with a lagsarlm "mixed" model I executed:
>>>> library(spdep)
>>>> library(coda)
>>>> dsts15 <- nbdists(nbs15, data.xy)
>>>> idw15 <- lapply(dsts15, function(x) 1/(x))
>>>> sy15 <- nb2listw(nbs15, glist=idw15, style="W")
>>>> mod.sdm.15<-lagsarlm(AR32 ~ SD46 + Totaland + PC18 + PC22 + sra + sla +
>>>> saa
>>>> + owue + yearrain + yearfdi, data=data, listw=sy15, type="mixed",
>>>> tol.solve=1.0e-12)
>>>> summary(mod.sdm.15)
>>>>
>>>> And got following results (abridged table):
>>>>
>>>>               Estimate Std. Error z value Pr(>|z|)
>>>> (Intercept)   1.4255019  0.4824828  2.9545 0.003132
>>>> SD46          0.0149057  0.0116146  1.2834 0.199365
>>>> Totaland     -0.0217556  0.0072475 -3.0018 0.002684
>>>> ...
>>>> yearrain      0.0557373  0.0485612  1.1478 0.251062
>>>> yearfdi      -0.0109979  0.0069536 -1.5816 0.113741
>>>> lag.SD46      0.0262273  0.0278045  0.9433 0.345539
>>>> lag.Totaland  0.0060992  0.0141515  0.4310 0.666474
>>>> ...
>>>> lag.yearrain -0.2083118  0.0772751 -2.6957 0.007024
>>>> lag.yearfdi   0.0111460  0.0081562  1.3666 0.171761
>>>> Rho: -0.54702, LR test value: 10.052, p-value: 0.0015215
>>>>
>>>> Immediatly, I exectued impacts(mod.sdm.15, R=1000), to get the impacts:
>>>>
>>>>               Direct     Indirect         Total
>>>> SD46      0.013136761  0.013451739  0.0265884995
>>>> Totaland -0.023517332  0.013397014 -0.0101203177
>>>> ...
>>>> yearrain  0.079110119 -0.177734631 -0.0986245121
>>>> yearfdi  -0.012677636  0.012773412  0.0000957761
>>>>
>>>> Through simulation I manage to get credible intervals for direct,
>>>> indirect
>>>> and total impacts (HPDinterval(impacts, choice="XXX")).
>>>>
>>>>
>>> As you must know from the references on the help page for impacts
>>> methods,
>>> these are the combined impacts of the variables:
>>>
>>> S_r(W) = (I - \rho W)^{-1} (\beta_r I - \gamma_r W)
>>>
>>> where the direct impacts are sum(S_r(W))/n, etc. The \gamma_r are the
>>> coefficients on W x_r.
>>>
>>>
>>> However, how can I get the impacts of the lagged variables? I have seen
>>>> some publications such as: Läpple, D., & Kelley, H. (2014). Spatial
>>>> dependence in the adoption of organic drystock farming in Ireland. That
>>>> report a posterior mean and credible intervals for the lagged variables.
>>>>
>>>>
>>> Given the above, either you are misreading Läpple & Kelley (I do not have
>>> access), or both you and they are wrong. There are by definition on
>>> separable impacts for the lagged X variables.
>>>
>>> Hope this clarifies,
>>>
>>> Roger
>>>
>>>
>>> All suggestions are welcome.
>>>>
>>>> Best regards,
>>>>
>>>> *Ing. Jorge Alfredo Cárcamo, M. Sc., Ph. D. (c)*
>>>> Agriculture economics
>>>> Georg-August-Universität Göttingen
>>>>
>>>>         [[alternative HTML version deleted]]
>>>>
>>>> _______________________________________________
>>>> R-sig-Geo mailing list
>>>> R-sig-Geo at r-project.org
>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>>>
>>>>
>>> --
>>> 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
>>> http://orcid.org/0000-0003-2392-6140
>>> https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
>>> http://depsy.org/person/434412
>>>
>>
>>
> --
> 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
> http://orcid.org/0000-0003-2392-6140
> https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
> http://depsy.org/person/434412

	[[alternative HTML version deleted]]

More information about the R-sig-Geo mailing list