Variable not found using user-written XTMORAN command

[Maxence Morlet]

Dear all (data extract at the end),

I am trying to test for spatial autocorrelation in panel data using the xtmoran command (from ssc install).

I am facing the following problem, with the following code:

spset canton, coord(lat lng) coordsys(latlong, kilometers)
spmatrix create idistance W if Datum_n==tm(2022m4) , normalize(row) replace
spmatrix summarize W
spmatrix export W using myfile.csv, replace
import delimited "Downloads\myfile.csv", clear delimiter(space)
drop if v2==.
drop v1
save W, replace 

use "$data/SPATIAL_CT", clear

xtset canton Datum_n, monthly
xtmoran cant_month_sum_newpositions, wname(W.dta) 

ERROR: variable cant_month_sum_newpositions728 not found

I do not understand what caused this error, please could someone let me know where I've gone wrong?

I suspect it might because of the weighting matrix, which is not associated to a shape file in this case. Is this a problem? I manually inputted latitude and longitude and used Robert Picard's

geo2xy

command.

The inverse distance weighting matrix then looks like this (the first row is removed in the above code, but I wonder why it appears):

clear
input byte v1 float(v2 v3 v4 v5 v6 v7 v8 v9 v10 v11 v12 v13 v14 v15 v16 v17 v18 v19 v20 v21)
20          .          .          .          .          .          .          .          .          .          .          .          .          .          .          .          .          .          .          .          .
 1          0 .033741657  .03030484  .12817147  .08562172  .05523836  .03843883 .018478306  .03841457   .0262484  .05917112  .09705798 .034991365 .031389296  .02688484  .04822607  .05271863  .03087607  .07970407   .0843224
 2  .02411275          0   .2011876  .01914739 .017467113 .015746543 .013430405 .008860125  .07270077  .05050749 .015362188  .02866992  .01246935  .29798737 .024665046  .07084346 .035942703  .01330989  .03742783  .04016205
 3 .022734886  .21120374          0  .01842274 .016914003 .015509573  .01336643 .008999494  .06785418  .06338729 .015050041  .02702102 .012417258  .30877945 .026185364  .05501815 .034226473 .013403355 .034017157 .035489395
 4  .11857197 .024786765 .022717685          0   .2293703  .06522042  .04351062  .01895996  .02738773 .020184765  .09689056  .05472162  .04150366 .023418346 .021237774  .03290169  .03557517  .03005152  .04580312  .04718633
 5  .08392707 .023958456 .022099564  .24303265          0  .06575013  .04679817 .020611595 .025993675  .01969346  .13354287  .04683619  .04741533 .022771975   .0206344 .031139906  .03263503 .030579703  .04055284    .042027
 6  .06158894  .02456783 .023050535  .07860585  .07478947          0  .13934332  .03088488  .02851434 .022141643  .10842347  .05385603  .08946498 .023348544 .026437223 .029477676  .03889909  .06480422  .04236245  .03943949
 7  .04633558  .02265443 .021477267  .05669555   .0575513   .1506498          0  .04287126 .025891064  .02096824  .08377001  .04249001  .17009193 .021684255 .025338067  .02631301  .03366471   .0829645 .035332017 .033256985
 8  .04925651 .033049196 .031977072  .05463213   .0560525 .073838934  .09480326          0 .036432654  .03206876 .066223174  .04781438  .09896535 .032095328  .03834209 .036130037  .04296947  .09058557   .0432367  .04152688
 9  .03882307  .10281408  .09140917 .029919846  .02680054  .02584612 .021706983  .01381285          0  .08374035 .023972394  .05464591  .01964082  .08530086  .05059366  .07704156  .09039225 .022346275 .074078284 .067114964
10  .03603124  .09701788   .1159839 .029950865 .027579116   .0272599  .02387778 .016514182  .11374102          0  .02538452  .04557164  .02185678  .09659707 .069489054  .06026143  .06323402 .025288576  .05350425  .05085678
11   .0660215 .023985475 .022383735  .11686014   .1520121   .1085018  .07753894 .027719423  .02646629  .02063328          0  .04624471  .08363428 .022886014  .02266927 .029711787 .033635903  .04115531  .03909741   .0388426
12  .08968846  .03707246 .033283293   .0546605  .04415387  .04463522 .032572247  .01657534  .04996536  .03067776  .03829938          0  .02801797  .03382407 .034324046  .04924373  .10098927  .03102193  .15553167  .09546342
13  .04729979  .02358641  .02237398  .06064487  .06538815  .10846496   .1907382  .05018571  .02627024 .021523267  .10132277  .04098545          0 .022661775 .024992887 .027498275 .032872498  .06402014 .035200875  .03396977
14 .021432357  .28471205  .28103212 .017284384 .015862474 .014298358 .012282548 .008221077  .05762989  .04804807  .01400499 .024992455 .011446795          0  .02246958  .05748762 .030761763 .012178725 .031790815 .034063958
15  .04563466  .05858533  .05924683  .03896778 .035732307  .04024771  .03567931 .024415277  .08497467  .08592656  .03448651  .06304933  .03138379   .0558591          0  .05210727  .09108242  .04231307   .0646004   .0557077
16   .0511027  .10504644  .07771183  .03768682  .03366365  .02801517 .023130666 .014362464    .080778  .04651843  .02821728  .05646868 .021556044  .08921707 .032529164          0  .06017355  .02182539  .08149308  .11050357
17   .0530232  .05058621  .04588632  .03867748 .033486348 .035089675 .028088745 .016212888  .08995786  .04633149  .03032001  .10991875  .02445886   .0453132  .05396958  .05711438          0 .029507225   .1303475  .08171028
18   .0517574  .03122084  .02994906  .05445355  .05229566   .0974298  .11537146  .05696499 .037064794  .03088151  .06183021  .05627479  .07939053   .0298995  .04178665 .034526333  .04917869          0  .04707629  .04264795
19  .06562516  .04312252  .03733423  .04076564   .0340638 .031283047  .02413315 .013354911  .06035133 .032092378 .028851096  .13858093    .021441  .03833568 .031335585 .063321136  .10670649  .02312287          0  .16617905
20  .07512265  .05006837  .04214497  .04544158  .03819779 .031513546 .024579126 .013878925  .05916343  .03300658  .03101421   .0920364  .02238836  .04444621  .02923855  .09290569 .072377376  .02266604   .1798102          0
end

The rest of the data (an extract of it):

clear
input float(canton Datum_n cant_month_sum_newpositions) double(lat lng Y X _CX _CY)
1 723  129      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 724  301      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 725   73      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 726  425      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 727  319      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 732  403      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 733  412      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 734  454      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 735  418      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 736  433      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 737  382      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 738  349      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 739  348      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 740  340      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 744  305      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 745  316      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 746  253      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 747  225      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
1 749  268      47.4    8.05 133.72444444444446 -89.62326573311933      47.4    8.05
2 723    8 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 724   10 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 725    0 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 726   30 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 727   30 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 732   42 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 733   33 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 734   20 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 735   27 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 736   28 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 737   19 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 738   21 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 739   18 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 740   10 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 744   22 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 745   22 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 746   28 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 747   15 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884
2 749   27 47.385849 9.27884  134.5982862222222 -89.63813046864622 47.385849 9.27884

[Nick Cox]

You don't have a canton 728 in your example dataset. Perhaps xtmoran expects every integer in a sequence to be represnted in the data. Just guessing.

[Maxence Morlet]

Thank you very much for your prompt response.

There are 20 cantons in the dataset; indeed, there is no canton 728:

tab canton

group(Kanto |
         n) |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |         19        5.00        5.00
          2 |         19        5.00       10.00
          3 |         19        5.00       15.00
          4 |         19        5.00       20.00
          5 |         19        5.00       25.00
          6 |         19        5.00       30.00
          7 |         19        5.00       35.00
          8 |         19        5.00       40.00
          9 |         19        5.00       45.00
         10 |         19        5.00       50.00
         11 |         19        5.00       55.00
         12 |         19        5.00       60.00
         13 |         19        5.00       65.00
         14 |         19        5.00       70.00
         15 |         19        5.00       75.00
         16 |         19        5.00       80.00
         17 |         19        5.00       85.00
         18 |         19        5.00       90.00
         19 |         19        5.00       95.00
         20 |         19        5.00      100.00
------------+-----------------------------------
      Total |        380      100.00

[Maxence Morlet]

For anyone who faced the same problem, Nick Cox was absolutely correct: there were gaps in my time variable, so I used egen group() and created a new time variable without gaps. xtmoran does expect continuity in the time variable.