Dear STATA Community,
i am estimating following model using panel data with dummy control variables like religion colonial legacy and country fixed effects. i have one endogenous regressor and instrument variable. Although the results include weak instrument test but it does not contain the endogeniety test and i am also confused by warning message "Warning: estimated covariance matrix......" therefore as mentioned in the ivre2 manual i reestimated the model with partial (varlist) option..now i have all the post-estimation results but the coefficients for dummy variables which are important control variables are not given in the coefficient table ...i dont understand what happens with these control variables and how can i interpret results for dropped control variables in the partial out model.....
Code:
ivreg2 lninval (bm=msphund) lnpn polity2 popd religion i.colonyg i.ccode, cluster(ccode) endog(bm)
Code:
Warning - collinearities detected
Vars dropped:       14.ccode 16.ccode 33.ccode 36.ccode 40.ccode 43.ccode

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ccode

Number of clusters (ccode) =        42                Number of obs =     1176
                                                      F( 45,    41) =     4.02
                                                      Prob > F      =   0.0000
Total (centered) SS     =  8782.392021                Centered R2   =   0.9527
Total (uncentered) SS   =  102392.8999                Uncentered R2 =   0.9959
Residual SS             =  415.5114745                Root MSE      =    .5944

------------------------------------------------------------------------------
             |               Robust
     lninval |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
          bm |  -.0550026   .0148295    -3.71   0.000    -.0840679   -.0259372
        lnpn |   .6344185   .1019784     6.22   0.000     .4345445    .8342925
     polity2 |  -.0221709   .0163135    -1.36   0.174    -.0541447    .0098029
        popd |   -.000797   .0045606    -0.17   0.861    -.0097356    .0081416
    religion |  -1.545679    .655505    -2.36   0.018    -2.830446   -.2609131
             |
     colonyg |
     France  |   .6188915   1.295867     0.48   0.633     -1.92096    3.158743
         GB  |   1.185666   1.627479     0.73   0.466    -2.004134    4.375467
      Italy  |   .8160768    1.44639     0.56   0.573    -2.018796     3.65095
   Portugal  |   .8450834    1.63738     0.52   0.606    -2.364123    4.054289
      Spain  |  -1.075271   1.421021    -0.76   0.449    -3.860421     1.70988
             |
       ccode |
          2  |  -.1374123   .2565583    -0.54   0.592    -.6402574    .3654327
          3  |  -.1817275   .3549695    -0.51   0.609     -.877455    .5139999
          4  |   .4715192   .7613694     0.62   0.536    -1.020737    1.963776
          5  |   -.344699   .3413542    -1.01   0.313    -1.013741     .324343
          6  |   .9443374   .6825825     1.38   0.167    -.3934998    2.282175
          7  |  -.3731629   .2848706    -1.31   0.190     -.931499    .1851732
          8  |  -.9599937   .3675614    -2.61   0.009    -1.680401   -.2395866
          9  |   .4102447   .7871616     0.52   0.602    -1.132564    1.953053
         10  |  -2.560205   .9727601    -2.63   0.008     -4.46678   -.6536305
         11  |  -.4878504   1.429966    -0.34   0.733    -3.290532    2.314831
         12  |  -1.076217   .3745986    -2.87   0.004    -1.810417   -.3420175
         13  |     .09228   .2410625     0.38   0.702    -.3801938    .5647538
         14  |          0  (omitted)
         15  |  -.9769211   .3463366    -2.82   0.005    -1.655728   -.2981138
         16  |          0  (omitted)
         17  |  -1.456316   .3746422    -3.89   0.000    -2.190601   -.7220305
         18  |   .0666229   .3060478     0.22   0.828    -.5332199    .6664656
         19  |  -.5456202   .4413525    -1.24   0.216    -1.410655    .3194149
         20  |   .6744012   .6622356     1.02   0.309    -.6235566    1.972359
         21  |  -.7752258   .2783507    -2.79   0.005    -1.320783   -.2296683
         22  |   .6843882   .1415277     4.84   0.000     .4069989    .9617774
         23  |  -.0550631   .3391241    -0.16   0.871     -.719734    .6096079
         24  |   -.588617   .4212288    -1.40   0.162     -1.41421    .2369764
         25  |  -.5324383   .6261119    -0.85   0.395    -1.759595    .6947185
         26  |    1.18508   .8053307     1.47   0.141     -.393339    2.763499
         27  |  -2.671196   .5901045    -4.53   0.000     -3.82778   -1.514612
         28  |   1.662388   2.332419     0.71   0.476     -2.90907    6.233846
         29  |   .7522117   .2014798     3.73   0.000     .3573185    1.147105
         30  |   .2789614   .4216059     0.66   0.508    -.5473709    1.105294
         31  |    .291211   .7230231     0.40   0.687    -1.125888     1.70831
         32  |   1.595191   .6150546     2.59   0.009     .3897066    2.800676
         33  |          0  (omitted)
         34  |  -4.751193   1.205532    -3.94   0.000    -7.113993   -2.388393
         35  |   .9146707   .5859546     1.56   0.119    -.2337793    2.063121
         36  |          0  (omitted)
         37  |   2.840891   .4285955     6.63   0.000     2.000859    3.680922
         39  |  -.6249982   .2278374    -2.74   0.006    -1.071551   -.1784452
         40  |          0  (omitted)
         41  |  -.7446223   .6522119    -1.14   0.254    -2.022934    .5336895
         42  |  -.6195256   .2473664    -2.50   0.012    -1.104355   -.1346965
         43  |          0  (omitted)
             |
       _cons |   3.131583   1.924318     1.63   0.104     -.640011    6.903177
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             18.031
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              228.980
                         (Kleibergen-Paap rk Wald F statistic):         36.294
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Warning: estimated covariance matrix of moment conditions not of full rank.
         overidentification statistic not reported, and standard errors and
         model tests should be interpreted with caution.
Possible causes:
         number of clusters insufficient to calculate robust covariance matrix
         singleton dummy variable (dummy with one 1 and N-1 0s or vice versa)
partial option may address problem.
------------------------------------------------------------------------------
Instrumented:         bm
Included instruments: lnpn polity2 popd religion 2.colonyg 3.colonyg 4.colonyg
                      5.colonyg 6.colonyg 2.ccode 3.ccode 4.ccode 5.ccode
                      6.ccode 7.ccode 8.ccode 9.ccode 10.ccode 11.ccode 12.ccode
                      13.ccode 15.ccode 17.ccode 18.ccode 19.ccode 20.ccode
                      21.ccode 22.ccode 23.ccode 24.ccode 25.ccode 26.ccode
                      27.ccode 28.ccode 29.ccode 30.ccode 31.ccode 32.ccode
                      34.ccode 35.ccode 37.ccode 39.ccode 41.ccode 42.ccode
Excluded instruments: msphund
Dropped collinear:    14.ccode 16.ccode 33.ccode 36.ccode 40.ccode 43.ccode
------------------------------------------------------------------------------

. 
end of do-file
Code:
ivreg2 lninval (bm=msphund) lnpn polity2 popd religion i.colonyg i.ccode, cluster(ccode) endog(bm) partial(religion i.colonyg i.ccode)
Code:
Warning - collinearities detected
Vars dropped:       14.ccode 16.ccode 33.ccode 36.ccode 40.ccode 43.ccode

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ccode

Number of clusters (ccode) =        42                Number of obs =     1176
                                                      F(  4,    41) =    15.74
                                                      Prob > F      =   0.0000
Total (centered) SS     =  427.3671414                Centered R2   =   0.0277
Total (uncentered) SS   =  427.3671414                Uncentered R2 =   0.0277
Residual SS             =  415.5114745                Root MSE      =    .5944

------------------------------------------------------------------------------
             |               Robust
     lninval |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
          bm |  -.0550026   .0148295    -3.71   0.000    -.0840679   -.0259372
        lnpn |   .6344185   .1019784     6.22   0.000     .4345445    .8342925
     polity2 |  -.0221709   .0163135    -1.36   0.174    -.0541447    .0098029
        popd |   -.000797   .0045606    -0.17   0.861    -.0097356    .0081416
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             18.031
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              228.980
                         (Kleibergen-Paap rk Wald F statistic):         36.294
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
-endog- option:
Endogeneity test of endogenous regressors:                              10.926
                                                   Chi-sq(1) P-val =    0.0009
Regressors tested:    bm
------------------------------------------------------------------------------
Instrumented:         bm
Included instruments: lnpn polity2 popd
Excluded instruments: msphund
Partialled-out:       religion 2.colonyg 3.colonyg 4.colonyg 5.colonyg
                      6.colonyg 2.ccode 3.ccode 4.ccode 5.ccode 6.ccode 7.ccode
                      8.ccode 9.ccode 10.ccode 11.ccode 12.ccode 13.ccode
                      15.ccode 17.ccode 18.ccode 19.ccode 20.ccode 21.ccode
                      22.ccode 23.ccode 24.ccode 25.ccode 26.ccode 27.ccode
                      28.ccode 29.ccode 30.ccode 31.ccode 32.ccode 34.ccode
                      35.ccode 37.ccode 39.ccode 41.ccode 42.ccode _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
Dropped collinear:    14.ccode 16.ccode 33.ccode 36.ccode 40.ccode 43.ccode
------------------------------------------------------------------------------

. 
end of do-file

.
as mentioned in the ivreg2 help manual for the partial out option it says " By the Frisch-Waugh-Lovell (FWL) theorem, in IV, two-step GMM and LIML estimation the coefficients for the remaining regressors are the same as those that would be obtained if the variables were not partialled out."

does it mean that the coefficient will not be changed for those that are dropped in the partial out model... can i merge the results for instance the coefficients table from the first model and postestimation results from the partial out model and then provide a note "post-estimation statistics are obtained using Frisch-Waugh-Lovell Theorem to partial out the exogenous regressors"