[R-sig-Geo] Spatial Autocorrelation Estimation Method

[Roger Bivand]

On Tue, 5 Nov 2019, Robert R wrote:

> I have a large pooled cross-section data set. ​I would like to 
> estimate/regress using spatial autocorrelation methods. I am assuming 
> for now that spatial dependence is present in both the dependent 
> variable and the error term.​ ​My data set is over a period of 4 years, 
> monthly data (54 periods). For this means, I've created a time dummy 
> variable for each time period.​ ​I also created a weight matrix using the 
> functions "poly2nb" and "nb2listw".​ ​Now I am trying to figure out a way 
> to estimate my model which contains a really big data set.​ ​Basically, my 
> model is as follows: y = γD + ρW1y + Xβ + λW2u + ε​ ​My questions are:​ ​1) 
> My spatial weight matrix for the whole data set will be probably a 
> enormous matrix with submatrices for each time period itself. I don't 
> think it would be possible to calculate this.​ What I would like to know 
> is a way to estimate each time dummy/period separately (to compare 
> different periods alone). How to do it?​ ​2) Which package to use: spdep 
> or splm?​ ​Thank you and best regards,​ Robert​

Please do not post HTML, only plain text. Almost certainly your model 
specification is wrong (SARAR/SAC is always a bad idea if alternatives are 
untried). What is your cross-sectional size? Using sparse kronecker 
products, the "enormous" matrix may not be very big. Does it make any 
sense using time dummies (54 x N x T will be mostly zero anyway)? Are most 
of the covariates time-varying? Please provide motivation and use area 
(preferably with affiliation (your email and user name are not 
informative) - this feels like a real estate problem, probably wrongly 
specified. You should use splm if time make sense in your case, but if it 
really doesn't, simplify your approach, as much of the data will be 
subject to very large temporal autocorrelation.

If this is a continuation of your previous question about using 
self-neighbours, be aware that you should not use self-neighbours in 
modelling, they are only useful for the Getis-Ord local G_i^* measure.

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; e-mail: Roger.Bivand using nhh.no
https://orcid.org/0000-0003-2392-6140
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