Hey everyone!

I have panel data between 2014 and 2018 on multiple socioeconomic and demography factors for 108 local authorities in England. I am performing an IV regression where the dependent variable is rent. The control variables are unemployment (unemp), crime rate per 1000 inhabitants (crime), and the number of dwellings per 1000 inhabitants (dwelling). The endogenous variable is refugees (ref) and the instrument I'm using is the foreign-born non-EU population, denoted as "iv". I am investigating the effect that refugees have on rental prices in England. Below is an example of the data:

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input int(id year) str28 city double(ref rent unemp iv dwelling crime house) long citydummy float(unemp_L1 dwelling_L1 crime_L1 v2hat)
 1 2014 "Birmingham"                                        .                     . 5.2151714077315825                      .  .3900346462436178  272.1134208606856                     .   7         .         .         .              .
 1 2015 "Birmingham"                    8.205689277899343e-06   .020425134615904117   3.99517686340653  -.0013776440554339898  .3883094978550781 274.25081394949444    .06570433033843326   7  5.215171 .39003465 272.11343  -.00005961159
 1 2016 "Birmingham"                    .00004067487756861852    .01887119338140497  3.971597709354186    .028752619010172335  .3868193048272802 296.34022638106944  -.010791363051775527   7  3.995177  .3883095 274.25082 -.000034011697
 1 2017 "Birmingham"                    .00016101071794679132   .015020326395324801 3.7171110718700335    .006443112229837433 .38335687797986934  336.0215433515804 -.0062825779391504355   7  3.971598  .3868193 296.34024   .00008426196
 1 2018 "Birmingham"                    .00010330213667667315   .002453647667271852  3.572528920367716    .006161045382306198   .383893248973666  366.4554456488441    .02468309788167211   7  3.717111  .3833569  336.0215  .000021826463
 2 2014 "Leeds"                                             .                     .  4.333027883230789                      . .44186411834009687 306.98651655975914                     .  54         .         .         .              .
 2 2015 "Leeds"                         .00006545359340227778    -.1030368951604701 3.0899861080456486    -.01785574028014138 .44080339638809185   341.878399958454     .0664721755373554  54  4.333028  .4418641  306.9865   -4.05524e-06
 2 2016 "Leeds"                          .0001051633927528141   -.04562566646438215  2.146799982517078    .005637277176947146  .4396312131862368 411.67653509053844   -.01794009425056764  54  3.089986  .4408034  341.8784   .00002501094
 2 2017 "Leeds"                         .00010412622669693612    .05559640310545699 2.3117193955811675    -.01352998192574386  .4403889308233936 469.63281977401346  -.013819021423820743  54    2.1468  .4396312  411.6765  .000011424105
 2 2018 "Leeds"                         .00009962105682614976  .0074731536401340115  1.702625092119641    .008780702124099739 .44103072348860256  513.3236766537063   .021721356337354614  54 2.3117194  .4403889  469.6328  1.5545903e-06
 3 2014 "Bradford"                                          .                     .  3.868765408685758                      .  .3974966812061445  299.2983121562678                     .  11         .         .         .              .
 3 2015 "Bradford"                      .00019154181680257917   .016756586393507078  4.493397726114193    .023258107339275556  .3978544969848924 330.17599770421356    .05891719769275028  11  3.868765  .3974967  299.2983    .0001127746
 3 2016 "Bradford"                      .00009817507636888152  -.002603171521629477 3.0034088690663907   -.023159878111866723  .3972759081557568  404.0241924584403  -.023879145249947165  11 4.4933977  .3978545   330.176     .000019693
 3 2017 "Bradford"                       .0002759381898454746   .020401143243884423  2.698296700207994    .016822843927858117  .3993666498023123 480.16939307062415  -.016562414005032444  11  3.003409  .3972759  404.0242    .0001811274
 3 2018 "Bradford"                      .00018550789813929957   .009039568161282041 1.7724310477679497   -.011471508610189817 .40066270264017595  542.0933716675964  .0046664641861768885  11  2.698297 .39936665  480.1694   .00008030644
 4 2014 "Liverpool"                                         .                     . 2.5557011795543905                      . .20313611683205393 160.74237034263248                     .  57         .         .         .              .
 4 2015 "Liverpool"                                         0    .05901022289999158 1.1759880450776294 -.00011795543905635649  .1566788950301598 124.12051869677579    .06559698632374555  57  2.555701  .2031361 160.74237   2.210697e-06
 4 2016 "Liverpool"                    .000014341317622897922   .012283895142308765 1.1552952100176932  -.0005557260578872944 .15726277760068005 132.59365914084546    -.0359936897632549  57 1.1759881  .1566789 124.12052   .00002507625
 4 2017 "Liverpool"                     .00004278871148213678  .0008642679109081008  .9759616404642183   -.004519914222896382 .15841696193042384 149.25565244450104  -.015389959245511342  57 1.1552953 .15726277 132.59366    .0000523487
 4 2018 "Liverpool"                    .000023338213141535653  -.003467439432537578  .6972101032082229    .008919440731546898 .15968928373986316  161.7295036075341    .02784955510112308  57  .9759616 .15841696 149.25565  .000029777464
As the title of this question says, I aim to perform a first-stage regression in order to check the strength of the instrument used, and an overidentification test to check if the instrument set is valid and if the model is correctly specified. I tried to use the command "estat firststage" to do the first one and "estat overid" for the second one. However, for both commands, STATA replied that they are not valid. Furthermore, when I use the command "estat summarize", no values appear in the table (as can be seen in the attachment to this post).
I would be extremely grateful if someone could help me with this!