[Lore Fuma]

This is my standardised data set

* Example generated by -dataex-. To install: ssc install dataex
clear
input double Year str19 firm_uniquecode float(eco_subsidies_ha_std Quantità _distribuita_per_Ha_std quantity_minfert_ha_std share_cereals_std share_legumes_std share_external_input_std variety_per_ha_std)
2010 "2222009010010000001"  -.9941834    -.7329233   -.3690802   2.026897   -.8180163    2.736083  -.6454231
2010 "2222008180614000001"  1.4729136    -.7329233   -.3701734  -.9006715   -.8180163    -.700106   .9720542
2011 "2222008180614000001"  1.4061904    -.5282848   -.3701734  -.7468387   -.8180163    -.552767   .7964199
2012 "2222008180614000001"   1.291704    -.5282848   .50986964  -.7297021   -.7215687   .02923895  .43901625
2013 "2222008180614000001"  1.3034506    -.6381871   .50986964  -.8877792   -.8180163  -.44581965   .5304219
2014 "2222008180614000001"  1.0954006    -.6973972   -.3701734  -.6766999   -.7644557  -.58336496  .18472056
2014 "2222008070396000001"  -.9940289    -.6973972   -.3701734   .4522849     1.78152 -.008226826   -.630657
2012 "2502012035204000001"  -.9941834 -.0007952704   -.3701734 -1.1223273   -.8180163    .1086239  -.4437762
2010 "2302008005368000001"  -.9941834    -.4863183 -.002851125  -.9085893     .220522   1.2299663   .5698241
2008 "2302008000358000001"  .28903812    .05810741  -.15972836  1.8791516   -.6765462   -.2424677  -.5396133
2009 "2302008000358000001"  -.9941834     .1304114   -.3701734  2.0108101   -.8026127   1.7093962   -.603066
2010 "2302008000306000001"  -.9941834     -.730638    .3054372   1.262588   -.1810509    1.743287  -.6083527
2010 "2302008032024000001"  -.9941834    -.7333388   -.3701734  1.7921317   -.5932224   1.8836913  -.7233284
2010 "2302008002190000001"  -.9941834    -.6577161   -.2187623   2.026897   -.8180163    .6486254  -.7686381
2011 "2302008032024000001"  -.5769902    -.5893647    .0490769   1.784415   -.5858337   2.3682027  -.7233284
2012 "2302011093120000001"  .49060115     1.413496    .0490769 -1.1223273    1.294403   -.0883804    .705067
2013 "2302011093120000001" -.26586944    -.1711761    .0490769 -1.1223273   1.2349907   -.1631882   .8323785
2014 "2302011093120000001"  -.9941834   -.11425619   .24913636  -.5197971 -.064150706    -.350399  1.0127928
2010 "2302008000223000001"  -.9941834     .3390917   -.3674404  1.7145015   -.8180163  -.11349534 -.10483959
2010 "2302008002341000001"  -.9941834     .3390917   -.3701734   .3356966    .8013511    1.479452 -.19083942
end

[Nick Cox]

That makes more sense. I'd look to principal component analysis here after transforming closer to symmetry.

Can you post a random sample of say 100 farms as an example dataset?

[Lore Fuma]

These are the standardised variables

* Example generated by -dataex-. To install: ssc install dataex
clear
input double Year str19 firm_uniquecode float(eco_subsidies_ha_std Quantità _distribuita_per_Ha_std quantity_minfert_ha_std share_cereals_std share_legumes_std share_external_input_std variety_per_ha_std)
2010 "2222009010010000001"  -.9941834    -.7329233   -.3690802     2.026897   -.8180163    2.736083     -.6454231
2010 "2222008180614000001"  1.4729136    -.7329233   -.3701734    -.9006715   -.8180163    -.700106      .9720542
2011 "2222008180614000001"  1.4061904    -.5282848   -.3701734    -.7468387   -.8180163    -.552767      .7964199
2012 "2222008180614000001"   1.291704    -.5282848   .50986964    -.7297021   -.7215687   .02923895     .43901625
2013 "2222008180614000001"  1.3034506    -.6381871   .50986964    -.8877792   -.8180163  -.44581965      .5304219
2014 "2222008180614000001"  1.0954006    -.6973972   -.3701734    -.6766999   -.7644557  -.58336496     .18472056
2014 "2222008070396000001"  -.9940289    -.6973972   -.3701734     .4522849     1.78152 -.008226826      -.630657
2012 "2502012035204000001"  -.9941834 -.0007952704   -.3701734   -1.1223273   -.8180163    .1086239     -.4437762
2010 "2302008005368000001"  -.9941834    -.4863183 -.002851125    -.9085893     .220522   1.2299663      .5698241
2008 "2302008000358000001"  .28903812    .05810741  -.15972836    1.8791516   -.6765462   -.2424677     -.5396133
2009 "2302008000358000001"  -.9941834     .1304114   -.3701734    2.0108101   -.8026127   1.7093962      -.603066
2010 "2302008000306000001"  -.9941834     -.730638    .3054372     1.262588   -.1810509    1.743287     -.6083527
2010 "2302008032024000001"  -.9941834    -.7333388   -.3701734    1.7921317   -.5932224   1.8836913     -.7233284
2010 "2302008002190000001"  -.9941834    -.6577161   -.2187623     2.026897   -.8180163    .6486254     -.7686381
2011 "2302008032024000001"  -.5769902    -.5893647    .0490769     1.784415   -.5858337   2.3682027     -.7233284
2012 "2302011093120000001"  .49060115     1.413496    .0490769   -1.1223273    1.294403   -.0883804       .705067
2013 "2302011093120000001" -.26586944    -.1711761    .0490769   -1.1223273   1.2349907   -.1631882      .8323785
2014 "2302011093120000001"  -.9941834   -.11425619   .24913636    -.5197971 -.064150706    -.350399     1.0127928
2010 "2302008000223000001"  -.9941834     .3390917   -.3674404    1.7145015   -.8180163  -.11349534    -.10483959
2010 "2302008002341000001"  -.9941834     .3390917   -.3701734     .3356966    .8013511    1.479452    -.19083942
2011 "2302008000223000001"  -.9941834     4.391142  -.16136818     .7669621   -.8180163  -.04747067      .1259851
2011 "2302008002341000001"  -.9941834     4.391142   1.1696286     .5192897    .6255561   2.0105743     .01002212
2011 "2302008080514000001"   .4096902     4.391142   -.3652539   -1.1223273   2.1349492    .5342937      .6740102
2012 "2302008080514000001"   .4333592     1.413496   .16222528   -1.1223273   2.1847358   1.8837472     .20135917
2012 "2302010093102000001"  .42129135     1.413496   .16222528    .44390935    .6616454   -.5600518     1.0896531
2012 "2302008002341000001"   .4371141    3.5580454    .5951409    .51660955    .6281226   1.8133703    -.19083942
2012 "2302008000223000001"  -.9941834    -.7310535   -.2706903    1.6478125   -.8180163    .2295612    -.05789678
2013 "2302008080514000001"   .4333592    -.1711761   .16222528   -1.1223273   2.1847358  -.08262672     .20135917
2013 "2302010093102000001"   .4244685    -.1711761   .16222528   -.21761596    .9509225   -.7260545     1.7944305
2014 "2302010093102000001"  -.9941834   -.11425619   -.3701734      .631846    .4880228   -.5958501      .7592887
2014 "2302008080514000001"  -.9941834   -.11425619   .16222528   -1.1223273   2.1847358    3.452861     .20135917
2010 "2422008002752000001"  -.9941834    -.6909568   -.3701734   -1.1223273   -.8180163    -.542407       .697965
2012 "2422012001031000001"  -.9941834    -.7331311    .3333144   -1.1223273   -.8180163    -.737295     2.3534071
2010 "2432008030202000001"  -.9941834    -.6899181  -.09686814     .7240645   .42947915    .2231105     -.6333615
2010 "2432008033240000001"  -.9941834    -.6899181   1.2313956     .3970597   -.8180163    .5366404     -.3760725
2011 "2432010080837000001"   .9858877    -.6024533    .4814459   -1.1223273    .9083934     .602519      2.809818
2011 "2432008033240000001"  -.9941834    -.7219123    .4218653   -.13662449   -.8180163   .06933835    -.27658182
2011 "2432011080972000001"  -.3341597     3.503198   -.3701734   -1.1223273   -.8180163   -.3428284      2.769026
2011 "2432008033252000001"  -.9941834     .7262774    .4000008   .069524765   1.0562174   -.3244986       -.39153
2012 "2432008033252000001"  1.0316176     2.041435    .3890686    .17409673    .8739289     -.77016    -.29105645
2012 "2432008033240000001"   .8095668     2.041435   1.0455481     .9464539   -.8180163   .23182838     -.4627588
2013 "2432008033252000001"  -.8204398    -.1711761   .17479734   -.14364111    1.150571   -.7481658    -.29105645
2014 "2432008033252000001"  .29125237    -.6504446    .2245389    -.2736857   1.2750918   -.3188566    -.29105645
2011 "2432010080746000001"  -.3341597   -.08728865   .23328465   -1.1223273   -.8180163   1.8486305      -.588196
2008 "2432008031044000001"  -.9941834    .05810741   -.0487664    1.2243208   -.5255831    .4071968     .05822164
2008 "2442008005034000001"  -.9941834    -.4778004   1.0056454     .7142378    .3557413   -.7401891      .5081145
2008 "2442008011435000001"  -.9941834    2.2452424   .42295855    1.2104315   -.8180163    1.769031      .9548154
2010 "2442010011826000001"  -.9941834    -.7281449   2.7318416     .3856247  -.15736966   -.2335222     .56134653
2010 "2442010011936000001"   2.735191     6.906015     2.87888    .17419106    .2471113   1.6495068     2.5862274
2011 "2442010011936000001"   2.801481    1.9595795     .752018   -1.1223273   2.0607066   1.1063702      .8964016
2012 "2442010011826000001"  -.9941834    -.4896424   1.0127513      .728341   -.4574013    .3669722  -.0031411985
2012 "2442012012174000001"  -.9941834    1.2764816   -.3701734   -1.1223273    1.232498  -.13526401     2.3534071
2013 "2442013012247000001"   .8018522     .9352649    5.622318    1.7205245  -.52465683  -.29659617      2.054387
2013 "2442013012248000001"   .5061842    -.6045308   -.0996012   -1.1223273   1.5308414    .2024856     -.3648951
2013 "2442012012174000001"   2.716711    -.7285604   -.3701734   -1.1223273    1.232498   .18147212     2.3534071
2013 "2442010011826000001"  -.3512817    -.5791847   13.825304     .8707001    -.271324   -.4462886     .44844905
2013 "2442013012246000001"  -.9941834   -.28458834  -.15590207   -1.1223273   -.8180163   .03508439      5.762474
2013 "2442013012252000001"  1.4825993     6.873189   4.7564874     .5436963    .5284778   -.3800411      .6488162
2014 "2442014012271000001"  -.9941834    .21049145    .7875478    .05772692    .3327119  -.26781264       7.88749
2014 "2442013012252000001"  1.4786884    1.3061905  -.30949965     .4584706    .6100835    .1010967      .6488162
2014 "2442013012247000001"   .8018522    -.2183146    -.355415     .9771557   .18713784     .519199      1.342434
2014 "2442012012174000001"  2.3657818    -.4104878   -.3701734   -1.1223273   -.8180163    .3976625     2.3534071
2008 "2602008012678000001"  -.2640042    .05810741   -.3701734    -.8549907   1.9261055    .3170463    .007976011
2009 "2602008012678000001"  -.9941834     .1304114   -.3701734    -.5382957   1.5662248 -.015303715     .25493717
2010 "2602008012678000001"  .04375875   -.17798702   -.3701734    -.6743083    1.755921   -.3785893    -.13934833
2011 "2602008012678000001"  -.0136183   -.08728865   -.3701734     -.723647   1.8006307  -.57244134    -.00715316
2012 "2602012014300000001"    .622189    .06453096   -.3701734   -1.1223273   -.8180163   -.7033543    -.28695986
2013 "2602012014338000001"  2.0979877   -.09366167   -.3701734      .274187   -.8180163   -.8233867      .4777376
2013 "2602012014300000001"  2.0979877   -.09366167   -.3701734   -1.1223273   -.8180163  -.28995162     -.4578218
2010 "2602008013170000001"   .5546992   -.17798702   -.3701734   -1.1223273    .2957426   -.7165861     -.6721849
2012 "2602012014598000001"     .96907    -.5931043   -.3701734    -.5562743    .7196613    .3771329    -.39447385
2010 "2602008012388000001"  -.9941834   -.26381287   -.3701734  -.024714895   -.8180163    1.789055     -.4090392
2012 "2602012014515000001"  -.9941834     3.092674   1.1062218    -.6130188   -.8180163   -.4850125     4.2957907
2013 "2602012014629000001"  3.3221545    -.6126333   -.3701734   -1.1223273   -.8180163   -.4357639      3.311138
2010 "2602008012586000001"   2.423587    -.5442819   -.3701734   -1.1223273   -.8180163   1.9956588      .7292361
2012 "2602012012565000001"   .8297402    -.3105577    -.325898     -.220396   1.2483276   -.4041391     -.3416718
2012 "2602012013976000001"  -.9941834    -.3105577    -.325898     2.026897   -.8180163   -.8233867     -.4902612
2013 "2602012014627000001" -.21760875    -.7256519    -.325898    -.5942046    .5545734   -.6576289     -.5334629
2014 "2602008012586000001"  1.6832476    -.5941431   -.3701734   -1.1223273   -.8180163  -.02409021 -.00010530597
2008 "2812008030201000001" -.04368374    .05810741   -.3701734   -1.1223273    1.761752     .980044     1.0013465
2011 "2812009007709000001"  -.9941834    -.7142254   -.3701734     .5528228  .071247324    .3622039    -.14295375
2011 "2812011092436000001"   1.670369    -.7142254   -.3701734    .24693923    .8736259   -.7284169    -.26276118
2012 "2812012096103000001"  -.9941834    -.6398491   -.3701734     .4400153   -.6735091   .20852025     -.5482165
2013 "2812009060404000001" -.03771712    -.5874949  -.02635537   -.43506294    .5961149   1.6715024     -.4147061
2014 "2812008030201000001"  .51249754    1.1069536    .4333441   -.13599303   1.2237732   1.9190177      .9665486
2014 "2812014096305000001"   .7507201    1.1069536  -.27834284     .7837543   -.0867489   -.7082942    .001497889
2014 "2812013096196000001"   .9533804    1.1069536   -.3701734   -.09230597    .8766735   -.6121177     -.6248439
2014 "2812009060404000001"  -.5982617    1.1069536   -.1463364    -.5825595    .4421814    1.160805     -.3200266
2014 "2812012096103000001"  .22983295    1.1069536   -.3701734     .7181284   -.6735091    -.727878     -.4869146
2008 "2812008030163000001" -.15486534    -.6911646   -.3701734   -1.1223273 -.035645906    3.197391     -.6289269
2008 "2812008020301000001"  -.9941834    -.6816079     2.81274     .7064006   -.6673579    .4194535     -.7136161
2008 "2812008009812000001"  -.9941834    -.6816079    .4352573   -1.1223273   1.9654566   -.8233867     -.6052665
2008 "2812008030173000001"   1.947688    -.6816079    .4352573   -1.1223273    1.786086    7.110682     .03565903
2008 "2812008061117000001"  .09448963    -.6816079    .4352573 -.0010077935   1.1237541  -.14509922    -.50775254
2008 "2812008030175000001" -.10774627    -.6720511   -.3701734    -.7961319   -.8180163   3.1508524      .6445794
2008 "2812008030176000001"  -.9941834    -.6816079   -.3313641    .02104691   1.1026362   -.8233867    -.20042828
2009 "2812008090851000001"  .55768466     -.129811   -.3701734    -.8857792    1.255967   -.8233867     -.5798383
2009 "2812008030175000001"   .2382304     -.129811   -.3701734     .3383564    .7988043    1.884757      .6445794
2009 "2812008030173000001"  -.9941834     -.129811   -.3701734   -1.1223273    2.183322     5.32487     .03565903
2009 "2812008009812000001"  -.9941834     -.129811   -.3701734     1.659083   -.8180163   -.8233867     -.6052665
end

[Nick Cox]

That helps give the flavour, but these variables are already standardized. That puts them on comparable scales. You could try PCA, which in effect standardizes for you, unless you choose the covariance option, which you should not in this case.