Re: st: spatgsa and converting coordinates from shp file

[Maurizio Pisati <maurizio.pisati@unimib.it>]

The bandwidth for computing Moran's I should be set to any value that 
makes sense to your research problem. In your case, coordinates appear 
to be expressed in meters, so that option -band(0 10991) means that you 
are defining the neighbors of every municipality j as the set of 
municipalities whose centers are within a radius of 11 kilometers from 
the center of j. If this definition doesn't suit your needs, than you 
can extend the bandwidth the way you deem more appropriate to your 
research problem. Likewise, choosing a binary or a non-binary spatial 
weight matrix -- standardized or not -- depends on the way you want to 
define spatial contiguity between municipalities (see related literature 
for more info on spatial weight matrices).
Best wishes,
Maurizio Pisati






Il 19/06/10 10.06, Joost Bruijsten ha scritto:
> Dear Statalisters,
>
> my problem is about Moran's I (command: spatgsa) en the Weights matrix (spatwmat).
>
> I use Stata/SE 11.0 for Windows (32-bit).
> Born 21 October 2009
>
> First of all, I am analyzing the urban structure of the Veneto region in Italy using commuting flows.
> I want to use Moran's I to see if employment is concentrated. Employment is defined in my study as the total number of working persons that commute into a region or municipality.
>
> Using shp files (from istat.it/ambiente/cartografia) I made the map of Veneto and the provinces and municipalities (using spmap).
>
> Then I took the coordinates that the spmap command uses (using shp2dta) of every municipality and used the mean of the x and y coordinates for every municipality in a new dataset with the total number of ingoing commuters into a municipality. Beneath you see an example I used.
>
>
>
> destinationprovince destinationmunicipality totalpersons x y
>
> 23 3 892 1630494 5007893
>
> 23 8 686 1633549 5013109
>
> 23 9 538 1641141 5030001
>
> 23 10 489 1648422 5032311
>
> 23 19 2463 1649542 5041687
>
> 23 20 1882 1652473 5044176
>
> 23 25 8405 1660123 5045447
>
> 23 29 471 1662310 5047371
>
> 23 44 15613 1667065 5051641
>
> 23 48 1870 1668117 5052971
>
> 23 72 1834 1668861 5053562
>
> 23 85 676 1670068 5056730
>
> 23 95 1607 1681036 5057435
>
> I performed the commands for spatwmat and spatgsa (see beneath), although I changed the band width from a very high number (35000+) to the largest minimum distance the spatwmat command gave:
>
> spatwmat, name(test7) xcoord(x) ycoord(y) band(0 10991)
>
> My first question is: What is the best way with these sort of coordinates to set the band width? Or is there a way to convert these coordinates to real latitude and longitude variables? The last would actually be my preferred solution.
>
> I then used this command to calculate Moran's I:
>
> spatgsa totalpersons, weights(test7) moran
>
> This gave me a result, however I do not know whether these are good given the problems. Below you see the output.
>
> My second question is: should I standardize the spatwmat command, or use binary? I could not find in the help files what these do, in 'real' explanation.
>
> Thanks for your consideration,
>
>
> Joost Bruijsten
>   		 	   		
>
>
> . spatwmat, name(test7) xcoord(x) ycoord(y) band(0 10991)
>
>
> The following matrix has been created:
>
> 1. Inverse distance weights matrix test7
>     Dimension: 13x13
>     Distance band: 0<  d<= 10991
>     Friction parameter: 1
>     Minimum distance: 950.2
>     1st quartile distance: 11229.2
>     Median distance: 21674.2
>     3rd quartile distance: 36380.2
>     Maximum distance: 70773.6
>     Largest minimum distance: 10990.63
>     Smallest maximum distance: 38792.54
>
>
>
> .
> .
> . spatgsa aantalpersonen, weights(test7) moran
>
>
> Measures of global spatial autocorrelation
>
>
> Weights matrix
> --------------------------------------------------------------
> Name: test7
> Type: Distance-based (inverse distance)
> Distance band: 0.0<  d<= 10991.0
> Row-standardized: No
> --------------------------------------------------------------
>
> Moran's I
> --------------------------------------------------------------
>            Variables |    I      E(I)   sd(I)     z    p-value*
> --------------------+-----------------------------------------
>       aantalpersonen | -0.189  -0.083   0.211  -0.499   0.309
> --------------------------------------------------------------
> *1-tail test
>
>   		 	   		
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