I work on a PVAR model covering 8 countries with 88 observations. I using stata 15. I'm trying to determine the optimal lag number for my estimates using the commands proposed by Abrigo and Love (2016) dans l'article "Estimation of autoregression of the panel vector in Stata. stata Journal 16(3), 778-804. I use 5 variables. However, by executing the command:

pvarsoc TID IIF INF lCE PIBT, maxlag(4)pvaropts(instl(1/4))

stata tells me that i can not have fewer observation than parameters r(2001).
please, i need help to continue my estimates. Thank you.

. dataex TID INF IIF lCE PIBT

----------------------- copy starting from the next line -----------------------
Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input double(TID INF IIF) float lCE double PIBT
3.25  1.298068133 .172   26.2415  3.0043410234972754
3.75  7.947298761 .161 26.780577  1.9697293828834717
3.25  2.156829962 .167  27.18014  -.5054680434536039
3.25  2.307356822  .17 27.189594  -.7152954048259943
3.25   2.71280052 .226 27.411076  .11635459968853468
   3  6.753123517 .231 27.448055   1.925340622651703
 2.5   .971851852 .245  27.57817    4.24019272567881
 2.5 -1.085744469 .276 27.719215   3.433603605807349
 2.5   .320398718 .329  27.74791  -.6963933605685071
 2.5   -.93003312 .404 27.925755  1.1310918904936784
 2.5          1.8 .556 28.054203   2.717830180990987
3.25  -.230627306 .184 26.675043  2.5364312680318193
3.75   10.6597979 .198 27.154016   4.097478797038207
3.25  2.608176664 .188   27.2072 -.10739778375899789
3.25  -.764230735 .195  27.42901  2.2394417498435786
3.25  2.759767249 .198  27.57116  3.4663165105120584
   3  3.818152403 .198  27.78441   3.309381877492612
 2.5   .533738507  .22 28.059116   2.684958267592407
 2.5  -.258089518 .261 28.261906  1.2820155320731885
 2.5   .954993317 .283   28.3451   .8848249819982215
 2.5  -.247073221  .29  28.35558  2.8808135353740596
 2.5          2.9 .351  28.52463   3.700834877338096
3.25  1.892006293 .233  28.38761  -.2957888945893927
3.75  6.308527692 .233 28.497147    .375834836885943
3.25  1.019504577 .219  28.68437   .9810613973676396
3.25  1.226456121 .225  28.82813   -.307436734059479
3.25  4.912433951 .235  28.81772  -6.647608026372126
   3  1.304511199 .248 28.971617   8.001760570318183
 2.5  2.581170373 .276  29.14162   6.174367629918123
 2.5    .45303046 .325  29.30347   6.065754946260455
 2.5  1.237443262 .346  29.47474   6.124571813724856
 2.5   .726187589 .363  29.60829  5.6561970400983625
 2.5   .685881065  .41 29.746426   5.139962905216564
3.25  4.617437722  .12 23.757235   .8856246385468722
3.75  10.46007314 .131  24.12591   .7724825087317697
3.25 -1.651397336 .133  23.93331   .8752960437782491
3.25  2.517851402 .137  24.47951   2.026961324163821
3.25  5.046102263 .137 24.857584   5.357595256149537
   3  2.130545803 .164  25.39637  -4.231756793969382
 2.5  1.207125557 .176     25.27   .5935335710165219
 2.5 -1.509244606  .18 25.496014 -1.6242246346427294
 2.5  1.404608873 .183  25.74019   3.449628433579676
 2.5  1.694338806 .185 25.844654  3.6191372284397687
 2.5  1.362148999 .179 25.823084  3.3248959384309984
3.25  1.412002017 .172 27.174303  .09916146646860113
3.75  9.170988137 .181 26.920456   1.345141526937212
3.25  2.463751886  .18 27.144575   1.322384778534186
3.25  1.108926907 .188  27.43111   2.137521280253196
3.25  2.855534106 .194 27.730555   .1452087822712258
   3   5.42738719 .197  27.92461 -3.7211454070707077
 2.5  -.606221674  .21  27.98072  -.6215676214297474
 2.5   .895009182 .254 28.162376  3.9826065527608137
 2.5  1.435735842 .303  28.37012  2.8988280668084627
 2.5 -1.800441907  .33  28.58792  2.7019221632055235
 2.5  1.759857429  .35 28.684946   2.192772082281948
3.25   .053959261 .122 25.872576  -.6244651431480008
3.75  11.30510988 .132  25.91308  5.5564495754048835
3.25   .582906591 .129  26.58792  -4.388017740236094
3.25   .804073081 .139 26.716887    4.33372451486764
3.25   2.94238514 .141   26.8944 -1.5519613964515742
   3    .45508982  .16  26.96871   7.642445755477013
 2.5  2.298521698 .214  26.96773  1.2994313106838007
 2.5   -.92454472 .226 27.115623   3.475427578096827
 2.5  1.006885086 .254  27.40302   .4112458668356709
 2.5   .170799497 .232  27.53618   .9870159902866078
 2.5  2.796373189 .229  27.64371    .966049339964556
3.25  5.853304285  .24  27.86109    2.13866002285728
3.75  5.769758507 .233  28.07456   .8755081160098541
3.25 -2.248021479 .233  28.18864 -.40823035513149364
3.25  1.228681197 .253  28.38527  1.2328396245480917
3.25  3.403228298 .264 28.495195 -1.1819564221844416
   3  1.421378457 .281  28.55834  1.3436271383783236
 2.5   .698626837 .334 28.707724  .40164817022443344
 2.5 -1.079744817 .388 28.770233   1.028617242331407
 2.5    .14510746  .43   28.8946  3.3941789390719066
 2.5   .834768889 .375  29.04203  3.7316124544245923
 2.5  1.318153148 .459   29.1595  3.8298039487113726
3.25   .959947037 .175  26.34823 -.43153918077068454
3.75  8.681967213 .192  26.57864  -.5021325334463995
3.25  3.313390805 .189  26.81086   .7522554419667955
3.25  1.834169331 .196  26.99928  1.2373661341470665
3.25  3.572277228 .204  27.16434  2.1148803898668973
   3  2.630773937 .211 27.350504  2.0666915784323976
 2.5  1.766766021 .233  27.55123  1.2594729003092766
 2.5   .186716067 .248  27.57407  3.1481298557867348
 2.5  1.789864499 .282 27.743824  2.7151684075465994
 2.5   .854424699 .302   27.8005  2.7713311819768762
 2.5   -.98188987 .433 27.926167  2.9756859234017554
end
------------------ copy up to and including the previous line ------------------