Posting again as I did not receive any helpful suggestions from my previous post. I have imputed and registered data for a dataset with a lot of missing data. When I run my mi estimate: regression (or mi estimate: xtreg) commands, the STATA output on provides results for a subset of my data, not the newly imputed data. The commands and results are below. Any assistance is appreciated.

Code:
 mi query
mi set mlong
quietly misstable summarize log_accessions diff_minority deprivationindex pctbachelors pctmasters pctdoctorate pctturnover unemploymentrate15_oecd, generate (miss_)
describe miss_*
mi register imputed log_accessions diff_minority pct_maori deprivationindex pctbachelors pctmasters  pctdoctorate pctturnover unemploymentrate15_oecd
mi register regular employmentrate15_oecd mean_earn_nzstatmi impute mvn log_accessions pct_maori pctbachelors pctmasters pctdoctorate deprivationindex  pctturnover unemploymentrate15_oecd, add(20) rseed (1234)
mi estimate, saving (olsest2): reg $ylist diff_minority deprivationindex pctbachelors pctmasters pctdoctorate pctturnover unemploymentrate15_oecd policyscore##funding##postcanterbury
HTML Code:
 mi estimate, saving (ols): reg $ylist diff_minority deprivationindex pctbachelors pctmasters pctdoctorate pctturnover unemploymentrate15_oecd policyscore#funding#postcanterbury

Multiple-imputation estimates                   Imputations       =         20
Linear regression                               Number of obs     =         26
                                                Average RVI       =     0.1554
                                                Largest FMI       =     0.4478
                                                Complete DF       =         15
DF adjustment:   Small sample                   DF:     min       =       7.57
                                                        avg       =      11.25
                                                        max       =      13.28
Model F test:       Equal FMI                   F(  10,   12.7)   =       4.20
Within VCE type:          OLS                   Prob > F          =     0.0096

----------------------------------------------------------------------------------------------------
                    log_accessions |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                     diff_minority |  -.3833525   .8673539    -0.44   0.666    -2.253172    1.486467
                  deprivationindex |   .0433965   .0156211     2.78   0.015     .0096986    .0770944
                      pctbachelors |  -.0136013   .0548682    -0.25   0.811    -.1413866     .114184
                        pctmasters |   .1554737   .1071908     1.45   0.175    -.0809909    .3919383
                      pctdoctorate |  -.1303299   .1012635    -1.29   0.225    -.3540136    .0933537
                       pctturnover |  -.0194386   .0758147    -0.26   0.802    -.1843108    .1454336
           unemploymentrate15_oecd |  -.0868002   .1196383    -0.73   0.483    -.3495745    .1759741
                                   |
policyscore#funding#postcanterbury |
                            0 0 1  |          0  (omitted)
                            0 1 0  |   .6229431   .4451461     1.40   0.185    -.3374752    1.583361
                            0 1 1  |          0  (omitted)
                            1 0 0  |          0  (empty)
                            1 0 1  |   .0101002   .4038377     0.03   0.980    -.8671615     .887362
                            1 1 0  |          0  (empty)
                            1 1 1  |   .6662499   .5448059     1.22   0.246     -.525413    1.857913
                                   |
                             _cons |   10.27254   2.496735     4.11   0.004     4.482924    16.06216
----------------------------------------------------------------------------------------------------
Code:
. mi describe

  Style:  mlong
          last mi update 15sep2020 10:44:27, approximately 1 minute ago

  Obs.:   complete           24
          incomplete        144  (M = 20 imputations)
          ---------------------
          total             168

  Vars.:  imputed:  9; log_accessions(24) diff_minority(142) deprivationindex(126) pctbachelors(142) pctmasters(142)
                    pctdoctorate(142) pctturnover(24) unemploymentrate15_oecd(14) pct_maori(142)

          passive:  0

          regular:  2; employmentrate15_oecd mean_earn_nzstat

          system:   3; _mi_m _mi_id _mi_miss

         (there are 67 unregistered variables)
HTML Code:
 . sum $xlist $ylist

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
diff_minor~y |      2,906    .6226473    .2442557  -.2052834   1.466744
deprivatio~x |      2,922    6.849442    9.205344  -24.29531   42.14392
pctbachelors |      2,906    45.54763    5.907764   20.81843    69.3688
  pctmasters |      2,906    7.798592    2.991676  -4.717332   19.29404
pctdoctorate |      2,906    2.407225    2.249541  -6.408797   11.34198
-------------+---------------------------------------------------------
 pctturnover |      3,024    16.32659    2.005034    10.6232    22.9954
unemployme~d |      3,034    5.340202     1.58543  -.0036189   10.17787
 policyscore |      3,048    .5964567    .4906884          0          1
     funding |      3,048    .0695538    .2544353          0          1
postcanter~y |      3,048    .6929134    .4613613          0          1
-------------+---------------------------------------------------------
log_access~s |      3,024    9.936792    .6676036   7.808344   13.75531