Hello everyone,

I have panel data with six variables concerning governance quality for 59 countries and years from 2005 to 2015. All these six variables have the same scale of measurement (from -2.5 to +2.5) and I would like to aggregate them, building a unique index. Given the nature of these variables, I chose a factor analysis over a pca. My question is if it is correct to perform a factor analysis in panel data. This topic has been already discussed in several posts (here and here). Although other methods were suggested (ex: sem and gsem), nothing was said about the legitimacy to perform, or nor, factor analysis with panel data.
I also attach a small sample of data

Code:
* Example generated by -dataex-. For more info, type help dataex
clear
input str18 cou int year double(indg_accountability indg_control_corruption indg_govt_effect indg_political_stability indg_regulatory_quality indg_rule_law)
"ARG" 2005 .2692317 -.3881924 -.1242145 -.0417681 -.5483672 -.5546548
"ARG" 2006 .4034365 -.3412537 -.0455042  .0030557 -.6406317  -.568944
"ARG" 2007 .4486213 -.3402916 -.0159589  .0988585 -.6682156 -.5916041
"ARG" 2008 .3588959 -.4355765 -.1468119 -.0852222 -.7375205 -.6766081
"ARG" 2009 .2800475 -.4449961 -.3182648 -.2324056 -.8450356 -.6754778
"ARG" 2010 .3616894 -.3614692   -.16279 -.0847979 -.7623686  -.590509
"ARG" 2011 .3449418 -.3661579 -.1200561  .1589937 -.7222099 -.5608934
"ARG" 2012 .2952099 -.4431399 -.2385752  .1030405 -.9292172 -.6796814
"ARG" 2013 .2769879  -.432282 -.2775489  .0653143  -.957261 -.7076761
"ARG" 2014 .3453205 -.5416201 -.1591353 -.0051219 -1.074257 -.8860345
"ARG" 2015 .4117875 -.5470577 -.0750081  .0147854 -.9114419  -.770812
"AUS" 2005 1.507056  1.952358  1.751213  .8935112  1.600643  1.724451
"AUS" 2006 1.382795  1.960568  1.711956  .9351878  1.623903   1.77004
"AUS" 2007   1.3692  2.010918  1.825559  .9287898  1.683095  1.761237
"AUS" 2008 1.368076  2.042482   1.79397  .9556448  1.765919  1.770851
"AUS" 2009 1.383792  2.051661  1.705787   .855689  1.819984  1.740398
"AUS" 2010 1.419766  2.031455  1.768756  .8888599  1.698415  1.764966
"AUS" 2011 1.453721  2.044637   1.69595  .9357101  1.858609   1.74258
"AUS" 2012  1.49919  1.985774   1.62144  .9979972  1.786468  1.766946
"AUS" 2013 1.436414  1.785322  1.639869  1.031073  1.800868  1.778639
"AUS" 2014 1.361716  1.853449  1.607115  1.032192  1.863708  1.923105
"AUS" 2015 1.355591  1.882113  1.564534  .8849798  1.788684  1.825212
"AUT" 2005 1.378657   1.92206  1.684595  1.105386  1.606079  1.859191
"AUT" 2006 1.372685  1.914531  1.831036  1.075933  1.644535  1.913557
"AUT" 2007 1.369262  2.013397  1.870187  1.283752  1.690031  1.960128
"AUT" 2008 1.358464  1.843035   1.78084  1.339206  1.606344  1.922995
"AUT" 2009 1.392846  1.703025   1.66658  1.190602  1.452587   1.78489
"AUT" 2010 1.430291  1.585462  1.841763  1.152648  1.452815    1.8003
"AUT" 2011 1.402444  1.431896  1.617761  1.193522  1.382634  1.801555
"AUT" 2012 1.448773  1.389731  1.575873  1.340567  1.524189  1.858179
end

Thank you to anyone who is willing to shed light on this topic.
Best