Hi all,

I have panel data and I would like to calculate the standard deviation of my scaled sale variable (sales_scaled) at firm-level with the rangestat function. I have now the following code:

rangestat (sd) sigma = sales_scaled, interval (fyear low high) by (Firm_id). However, I don't know what values to take for the interval (for low and for high). My dataset looks like this:

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input str6 gvkey double(fyear sale) float(scaling_variable Firm_id sales_scaled)
"001004" 2002   606.337    698.41  1  .8681678
"001004" 2003   651.958  697.9565  1  .9340955
"001004" 2004   747.848   720.761  1 1.0375811
"001004" 2005   897.284  855.5245  1 1.0488116
"001004" 2006  1061.169  1023.226  1 1.0370817
"001004" 2007  1384.919 1214.8215  1 1.1400185
"001004" 2008  1423.976 1369.7605  1 1.0395802
"001004" 2009  1352.151 1439.2765  1  .9394658
"001004" 2010  1775.782 1602.3845  1 1.1082121
"001004" 2011  2074.498   1949.69  1 1.0640142
"001004" 2012    2167.1 2166.2766  1   1.00038
"001004" 2013      2035    2168.2  1  .9385666
"001004" 2014    1594.3   1857.25  1  .8584197
"001004" 2015    1662.6   1478.55  1   1.12448
"001004" 2016    1767.6    1473.1  1 1.1999185
"001004" 2017    1748.3    1514.4  1 1.1544505
"001045" 2003     17440   29798.5  5  .5852644
"001045" 2004     18645   29051.5  5  .6417913
"001045" 2005     20712     29134  5  .7109219
"001045" 2006     22563     29320  5   .769543
"001045" 2007     22896     28858  5  .7934022
"001045" 2008     23766     26873  5  .8843821
"001045" 2009     19917   25306.5  5   .787031
"001045" 2010     22170     25263  5   .877568
"001045" 2011     24022     24468  5  .9817721
"001045" 2012     24855     23679  5 1.0496643
"001045" 2013     26712     32894  5   .812063
"001045" 2014     42650   43024.5  5  .9912956
"001045" 2015     40990     46093  5   .889289
"001045" 2016     40180   49844.5  5   .806107
"001045" 2017     42207     51335  5  .8221876
"001050" 2003    68.159   43.9155  6 1.5520488
"001050" 2004    69.366   42.2975  6  1.639955
"001050" 2005    81.521   43.1705  6 1.8883497
"001050" 2006   135.359    53.044  6  2.551825
"001050" 2007   235.953   79.8615  6 2.9545274
"001050" 2008    217.89   108.276  6 2.0123572
"001050" 2009   138.985    98.766  6  1.407215
"001050" 2010   140.602    76.153  6 1.8463094
"001050" 2011   139.192    77.068  6 1.8060933
"001050" 2012   135.052   86.7245  6  1.557253
"001050" 2013   197.317    221.32  6  .8915462
"001050" 2014   263.217  381.4505  6  .6900424
"001050" 2015   367.422   506.592  6  .7252819
"001050" 2016   417.011  548.7265  6  .7599615
"001050" 2017   345.051  468.5915  6  .7363578
"001072" 2002  1134.111  1696.056  8  .6686754
"001072" 2003  1136.577  1684.195  8  .6748489
"001072" 2004  1283.202  1678.813  8  .7643508
"001072" 2005  1333.208 1682.4785  8  .7924072
"001072" 2006  1498.495  1787.372  8   .838379
"001072" 2007  1619.275  2004.307  8  .8078977
"001072" 2008  1389.613 1990.8035  8  .6980162
"001072" 2009  1304.966 1962.0105  8  .6651167
"001072" 2010  1653.176  2185.487  8  .7564337
"001072" 2011  1545.254  2393.747  8  .6455377
"001072" 2012    1414.4 2535.0034  8   .557948
"001072" 2013  1442.604 2493.4915  8  .5785478
"001072" 2014  1353.228 2422.0015  8 .55872303
"001072" 2015  1195.529  2434.417  8  .4910946
"001072" 2016  1312.661  2443.616  8 .53717977
"001072" 2017  1562.474 2575.0896  8  .6067649
"001075" 2005  2987.955 10609.696  9 .28162494
"001075" 2006  3401.748 11389.294  9  .2986794
"001075" 2007   3523.62 11349.828  9  .3104558
"001075" 2008  3367.076 11431.902  9  .2945333
"001075" 2009  3297.101 11714.124  9  .2814637
"001075" 2010  3263.645  12085.43  9 .27004793
"001075" 2011  3241.379  12736.86  9 .25448808
"001075" 2012  3301.804 13245.316  9 .24928087
"001075" 2013  3454.628  13444.15  9 .25696144
"001075" 2014  3491.632 13911.108  9 .25099596
"001075" 2015  3495.443 14670.896  9 .23825696
"001075" 2016  3498.682 15516.256  9 .22548494
"001075" 2017  3565.296 16511.668  9 .21592586
"001078" 2003 19680.561  25487.22 11  .7721736
"001078" 2004 19680.016  27741.42 11  .7094092
"001078" 2005 22287.808  28954.35 11  .7697569
"001078" 2006 22476.322  32659.69 11  .6881977
"001078" 2007 25914.238 37946.047 11  .6829233
"001078" 2008 29527.552  41066.57 11  .7190168
"001078" 2009 30764.707  47417.91 11  .6487992
"001078" 2010 35166.721  55939.45 11  .6286569
"001078" 2011 38851.259  59869.58 11  .6489316
"001078" 2012  39873.91  63755.92 11   .625415
"001078" 2013     21848  55093.97 11  .3965588
"001078" 2014     20247     42114 11  .4807665
"001078" 2015     20405     41261 11  .4945348
"001078" 2016     20853   46956.5 11  .4440919
"001078" 2017     27390     64458 11  .4249279
"001104" 2003    34.975   18.8185 14 1.8585434
"001104" 2004    43.381    21.516 14 2.0162203
"001104" 2005    49.946   25.6015 14 1.9509014
"001104" 2006    56.863   31.6075 14  1.799035
"001104" 2007    63.173   38.6215 14 1.6356952
"001104" 2008    68.719    43.823 14 1.5681034
"001104" 2009    59.149   43.8665 14 1.3483865
"001104" 2010    63.149    45.945 14 1.3744477
"001104" 2011    73.302   52.4015 14  1.398853
"001104" 2012     84.37    61.525 14 1.3713125
end
So, what is the interval I should take when I want to know the standard deviation at firm-level (per firm ID)?
Thanks in advance.