Hello Statalist users,

I need help with exporting multiple xtbond2 estimations along with their post estimations results (AR1, AR2, Sargan, Hansen) into Word. publication quality level.
example of my multiple commands
xtabond2 L(0/1).ZS3 c.OBSR##c.EA_w Size AssetG ROA LoanAsset LiqR DepFL l.GDPG l.T10Y3M y*,gmm(L.ZS3 OBSR LiqR,laglimits(1 1)) iv(l.GDPG l.T10Y3M y*,eq(level)) iv(l.GDPG l.T10Y3M,eq(diff)) twostep robust small

xtabond2 L(0/1).ZS3 c.OBSR##c.EA_w Size AssetG ROA LoanAsset LiqR LLPLR DepFL l.GDPG l.T10Y3M y*,gmm(L.ZS3 OBSR LiqR,laglimits(1 1)) iv(l.GDPG l.T10Y3M y*,eq(level)) iv(l.GDPG l.T10Y3M,eq(diff)) twostep robust small

xtabond2 L(0/1).ZS3 c.OBSR##c.EA_w Size AssetG ROA LoanAsset LiqR LLPAR DepFL l.GDPG l.T10Y3M y*,gmm(L.ZS3 OBSR LiqR,laglimits(1 1)) iv(l.GDPG l.T10Y3M y*,eq(level)) iv(l.GDPG l.T10Y3M,eq(diff)) twostep robust small
and here is sample of the results i get with each regression
Code:
xtabond2 L(0/1).ZS3 c.OBSR##c.EA_w Size AssetG  ROA LoanAsset LiqR DepFL  l.GDPG l.T10Y3M y*,gmm(L.ZS3 OBSR LiqR,laglimits(1 1)) iv(l.GDPG  l.T10Y3M y*,eq(level)) iv(l.GDPG l.T10Y3M,eq(diff)) twostep robust small
Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm.
Warning: Two-step estimated covariance matrix of moments is singular.
  Using a generalized inverse to calculate optimal weighting matrix for two-step estimation.
  Difference-in-Sargan/Hansen statistics may be negative.

Dynamic panel-data estimation, two-step system GMM
------------------------------------------------------------------------------
Group variable: id                              Number of obs      =      2766
Time variable : Year                            Number of groups   =       336
Number of instruments = 61                      Obs per group: min =         1
F(22, 335)    =  11490.11                                      avg =      8.23
Prob > F      =     0.000                                      max =         9
-------------------------------------------------------------------------------
              |              Corrected
          ZS3 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
          ZS3 |
          L1. |   .9606215   .0519257    18.50   0.000     .8584799    1.062763
              |
         OBSR |   .0166858   .0074719     2.23   0.026     .0019881    .0313835
         EA_w |   .0234135   .0110084     2.13   0.034     .0017592    .0450677
              |
c.OBSR#c.EA_w |  -.0015945   .0006956    -2.29   0.023    -.0029629   -.0002261
              |
         Size |   .0499903   .0244027     2.05   0.041     .0019885    .0979921
       AssetG |  -.0023591   .0018319    -1.29   0.199    -.0059625    .0012443
          ROA |   .0040595   .0352507     0.12   0.908     -.065281    .0734001
    LoanAsset |   .0031209   .0038364     0.81   0.417    -.0044255    .0106672
         LiqR |  -.0025142   .0032188    -0.78   0.435    -.0088458    .0038174
        DepFL |   .0066999   .0037298     1.80   0.073    -.0006368    .0140366
              |
         GDPG |
          L1. |  -.4352625   .2448995    -1.78   0.076     -.916997    .0464721
              |
       T10Y3M |
          L1. |   -.019525   .0240011    -0.81   0.417    -.0667369     .027687
              |
       yearD1 |          0  (omitted)
       yearD2 |          0  (omitted)
       yearD3 |  -.4798001   .2566407    -1.87   0.062    -.9846305    .0250302
       yearD4 |  -.2549777   .1369852    -1.86   0.064    -.5244372    .0144819
       yearD5 |  -.4169946   .2253129    -1.85   0.065     -.860201    .0262117
       yearD6 |  -.1418621    .053773    -2.64   0.009    -.2476374   -.0360869
       yearD7 |   .0177436   .0359721     0.49   0.622     -.053016    .0885032
       yearD8 |  -.5419371   .3025044    -1.79   0.074    -1.136985    .0531103
       yearD9 |  -.1840684   .1093741    -1.68   0.093    -.3992151    .0310783
      yearD10 |          0  (omitted)
        _cons |          0  (omitted)
-------------------------------------------------------------------------------
Instruments for first differences equation
  Standard
    D.(L.GDPG L.T10Y3M)
  GMM-type (missing=0, separate instruments for each period unless collapsed)
    L.(L.ZS3 OBSR LiqR)
Instruments for levels equation
  Standard
    L.GDPG L.T10Y3M yearD1 yearD2 yearD3 yearD4 yearD5 yearD6 yearD7 yearD8
    yearD9 yearD10
    _cons
  GMM-type (missing=0, separate instruments for each period unless collapsed)
    D.(L.ZS3 OBSR LiqR)
------------------------------------------------------------------------------
Arellano-Bond test for AR(1) in first differences: z =  -5.60  Pr > z =  0.000
Arellano-Bond test for AR(2) in first differences: z =   0.19  Pr > z =  0.848
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(38)   = 210.17  Prob > chi2 =  0.000
  (Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(38)   =  44.19  Prob > chi2 =  0.227
  (Robust, but weakened by many instruments.)

Difference-in-Hansen tests of exogeneity of instrument subsets:
  GMM instruments for levels
    Hansen test excluding group:     chi2(12)   =  16.51  Prob > chi2 =  0.169
    Difference (null H = exogenous): chi2(26)   =  27.68  Prob > chi2 =  0.374
  iv(L.GDPG L.T10Y3M yearD1 yearD2 yearD3 yearD4 yearD5 yearD6 yearD7 yearD8 yearD9 yearD10, eq(level))
    Hansen test excluding group:     chi2(29)   =  38.98  Prob > chi2 =  0.102
    Difference (null H = exogenous): chi2(9)    =   5.20  Prob > chi2 =  0.816
  iv(L.GDPG L.T10Y3M, eq(diff))
    Hansen test excluding group:     chi2(36)   =  42.25  Prob > chi2 =  0.219
    Difference (null H = exogenous): chi2(2)    =   1.94  Prob > chi2 =  0.380
what is the best command to do so?

Thank you,
Sad