Hi all,

I try it again
I have a dataset having as inputs: the id of products, quarters, Year corresponding to quarter, sales, standard units (quantity of units sold) and price. All data are quarterly and in quarterly format:

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float(idproduct quarter) double(salesmnf stdunits) float(price Year trimestre log_sales)
 309 1  549428.8959562927   208530 2.6778486 2015 220 13.216635
 309 2 1657635.6735686143   621990   2.62871 2015 221 14.320903
 309 3 2361742.0307672094   879120  2.787183 2015 222  14.67491
 309 4  2708969.867707035   982620  2.783677 2015 223  14.81208
 967 1 184693056.44742548  2123448  69.92604 2006 184 19.034206
 967 2  186583645.8088604  2131386   72.9989 2006 185  19.04439
 967 3 195114029.24053717  2126052  76.26028 2006 186 19.089094
 967 4 211430381.58983797  2244936  78.51543 2006 187 19.169407
 968 1  94245656.30939752  1951221  43.02343 2010 200 18.361416
 968 2 106193726.41838197  2246121  40.94118 2009 197 18.480776
 968 3 126991064.20802969  2581852  43.04422 2009 198 18.659628
 968 4 131882758.77489536  2516289  43.29467 2009 199 18.697424
4834 1  2386084.582423094  2936683  38.43847 2008 192 14.685164
4834 2  2988950.166766347  3438293  31.67041 2007 189 14.910433
4834 3  21072007.09334628 21285772  41.51537 2007 190 16.863457
4834 4  4232758.643618916  4991422  47.45229 2007 191 15.258365
6068 1 2856639582.4348493 31039572  54.41778 2004 176  21.77291
6068 2  2868131337.495672 30779047  56.97757 2004 177 21.776926
6068 3 2964321233.5777473 30719826  57.55517 2004 178 21.809914
6068 4 3102891325.7371497 31502475  60.23185 2004 179   21.8556
6069 1 1274750484.2723105 24761448  44.77084 2008 192 20.966017
6069 2 1321443568.6101897 25389605  45.13775 2008 193  21.00199
6069 3  1450067330.289578 26692361  59.08562 2008 194 21.094875
6069 4  1622238762.625174 29031081  60.22854 2008 195 21.207073
6070 1  126134306.5626635  2524050  44.07946 2008 192 18.652859
6070 2 126160278.29548052  2526460  44.34878 2008 193 18.653063
6070 3 133952400.29167828  2600550  45.94165 2008 194 18.712996
6070 4 145466515.49067545  2759600  47.45404 2008 195 18.795456
6071 1  715550633.3935665 13916068  43.81797 2008 192 20.388563
6071 2  735844351.1348764 14172592  44.28768 2008 193  20.41653
6071 3  787807606.7341623 14610150  46.09623 2008 194 20.484764
6071 4  841888838.8800159 15310000  46.74739 2008 195  20.55116
6072 1  75009962.13975018   647480  111.3589 2007 188 18.133131
6072 2  74588181.81412561   646650  113.1978 2007 189 18.127493
6072 3   77185508.6298286   655104 116.64356 2007 190 18.161722
6072 4  80405694.76067226   669178 116.24467 2006 187 18.202595
6073 1  967880303.1021518 10379874  98.05796 2004 176  20.69062
6073 2  940204820.2090411  9971840  99.46415 2004 177  20.66161
6073 3  943518026.6403258  9721450 102.63863 2004 178 20.665127
6073 4  937029685.4230168  9462950 104.92355 2004 179 20.658226
6074 1  325298810.4768621 10541274  29.95105 2009 196 19.600254
6074 2 318927130.92226684 10325853 29.956696 2006 185 19.580473
6074 3 318537182.08938503 10198362 30.118374 2004 178  19.57925
6074 4 314911730.62714845  9984549 30.122837 2004 179   19.5678
6075 1 23100089.994157523   680650 33.122414 2006 184 16.955347
6075 2 23657358.264116693   704568  32.76325 2006 185 16.979185
6075 3 24755341.757148325   736362 32.484085 2006 186 17.024551
6075 4 24159466.021932237   714762 33.550167 2006 187 17.000187
6076 1  402642339.2982397 13442632  29.97017 2008 192  19.81356
6076 2 393652682.40141517 13099424 30.053415 2004 177  19.79098
6076 3 384781974.31103617 12630738   30.3134 2007 190 19.768187
6076 4  364490710.2282536 11896252 30.266676 2007 191  19.71401
6077 1  154219.5423851413     2308  67.64907 2014 216 11.946133
6077 2 166348.28589167312     2362  70.35483 2014 217  12.02184
6077 3 275477.74374367687     4124  67.60611 2013 214 12.526262
6077 4 241831.51024506125     3428  70.83441 2013 215 12.395996
6078 1   95367.0953683665     1412  51.04691 2013 212 11.465488
6078 2 101803.97800399363     1437  70.28399 2014 217 11.530805
6078 3 129823.20117755304     2415  53.81084 2013 214  11.77393
6078 4 146620.37886745489     2009  70.72038 2013 215 11.895602
6079 1 31157.172649819393      462   50.8711 2013 212   10.3468
6079 2 27570.082972937766      382  70.42646 2014 217 10.224486
6079 3  32411.17721101825      690   52.5656 2013 214  10.38626
6079 4  34842.60850121315      485  57.08928 2013 215 10.458596
6096 1 15157838.529621929   498530 30.144026 2004 176 16.534029
6096 2 13333880.397857638   447838 30.777826 2004 177 16.405819
6096 3 13627377.140391372   438890  29.87494 2004 178 16.427591
6096 4 13228555.729047967   424874  29.82808 2004 179 16.397888
6097 1  1221010440.549058 29355894  37.75741 2004 176 20.922945
6097 2 1188729687.6971447 28398778  37.74227 2004 177  20.89615
6097 3 1200959683.2091687 27367918  38.23028 2004 178  20.90639
6097 4 1169804504.5442507 26495182  40.07455 2004 179   20.8801
6098 1  60036517.42085347   956812  54.05536 2014 216 17.910463
6098 2 102515708.66158077  1718060  55.79046 2014 217 18.445526
6098 3 109560137.83771564  1730052  58.85126 2014 218 18.511984
6098 4 117026418.36660808  1800952  60.40058 2014 219  18.57791
6099 1  248686246.0095292  8543084 26.423185 2004 176 19.331703
6099 2 206204004.55350846  7612860  28.05136 2004 177 19.144377
6099 3 215206932.38692236  7519608  25.85606 2004 178  19.18711
6099 4 218863168.20073053  7538558 26.363764 2004 179 19.203957
6100 1 15249277.111530745   533173 26.307264 2004 176 16.540043
6100 2  13884645.76745506   492447   26.1729 2004 177 16.446295
6100 3 13234970.984895848   452862  26.57682 2004 178 16.398373
6100 4 10654929.521898188   367615 27.746534 2004 179 16.181534
6101 1  680775094.3047991 17396700 36.580826 2004 176 20.338743
6101 2  666172707.5121135 17052418 35.934723 2004 177  20.31706
6101 3  657835756.2495023 16098298  38.31532 2004 178 20.304466
6101 4  660488478.0382179 16378155 37.930885 2004 179  20.30849
6102 1 23410712.260877848   384104  52.38548 2014 216 16.968704
6102 2 37716567.630523756   647481  53.78031 2014 217  17.44561
6102 3  45046688.97587415   721982  58.26444 2014 218  17.62321
6102 4  50876506.96934605   801653  59.75441 2014 219 17.744911
6103 1 107599801.57738319  3732895  26.34071 2004 176 18.493929
6103 2  91907197.12198395  3392682  26.02587 2004 177  18.33629
6103 3   95196010.3114374  3341626   25.7236 2004 178 18.371449
6103 4   96756092.4612426  3345447  25.89199 2004 179 18.387703
6104 1  619851443.7146848 10731429 162.90004 2004 176  20.24499
6104 2   630954605.489009 10601957 170.46887 2004 177 20.262745
6104 3  673440665.8650074 10430433   178.424 2004 178  20.32791
6104 4  712145296.8299035 10708652 187.66664 2004 179 20.383793
end
format %tq trimestre
Is there a way to deseasonalize such data (so unbalanced panel structure data)?

Thanks,


Federico