Actual StataMP numerical output; machine-specific log header omitted.

. * BEGIN first
. regress logp salestax logincome, vce(robust)

Linear regression                               Number of obs     =         48
                                                F(2, 45)          =      48.98
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6389
                                                Root MSE          =     .07848

------------------------------------------------------------------------------
             |               Robust
        logp | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    salestax |   .0273948   .0040961     6.69   0.000     .0191449    .0356447
   logincome |   .3892825   .0653914     5.95   0.000     .2575776    .5209875
       _cons |   3.590811   .1727273    20.79   0.000      3.24292    3.938701
------------------------------------------------------------------------------

. * END first
. scalar first_b=_b[salestax]

. * BEGIN reduced
. regress logq salestax logincome, vce(robust)

Linear regression                               Number of obs     =         48
                                                F(2, 45)          =       6.37
                                                Prob > F          =     0.0037
                                                R-squared         =     0.1687
                                                Root MSE          =     .22675

------------------------------------------------------------------------------
             |               Robust
        logq | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    salestax |  -.0313226   .0112334    -2.79   0.008    -.0539479   -.0086973
   logincome |  -.2305807   .2521733    -0.91   0.365    -.7384838    .2773224
       _cons |   5.325015   .6694834     7.95   0.000     3.976606    6.673424
------------------------------------------------------------------------------

. * END reduced
. scalar reduced_b=_b[salestax]

. * BEGIN controlled
. ivregress 2sls logq logincome (logp=salestax), vce(robust)

Instrumental-variables 2SLS regression            Number of obs   =         48
                                                  Wald chi2(2)    =      17.47
                                                  Prob > chi2     =     0.0002
                                                  R-squared       =     0.4189
                                                  Root MSE        =     .18355

------------------------------------------------------------------------------
             |               Robust
        logq | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
        logp |  -1.143375   .3604805    -3.17   0.002    -1.849904   -.4368463
   logincome |   .2145153   .3018477     0.71   0.477    -.3770953    .8061258
       _cons |   9.430658   1.219402     7.73   0.000     7.040675    11.82064
------------------------------------------------------------------------------
Endogenous: logp
Exogenous:  logincome salestax

. * END controlled
. scalar iv_b=_b[logp]

. scalar iv_se=_se[logp]

. assert abs(iv_b-reduced_b/first_b)<1e-8

. * BEGIN strength
. estat firststage

  First-stage regression summary statistics
  --------------------------------------------------------------------------
               |            Adjusted      Partial       Robust
      Variable |   R-sq.       R-sq.        R-sq.       F(1,45)   Prob > F
  -------------+------------------------------------------------------------
          logp |  0.6389      0.6228       0.5009       44.7305    0.0000
  --------------------------------------------------------------------------


. * END strength
. * BEGIN weak_test
. estat weakrobust, betanull(-1)

Test robust to weak instruments
Model VCE: Robust

 ( 1)  logp = -1

Anderson–Rubin chi2(1) =   0.16
           Prob > chi2 = 0.6914

Note: Anderson–Rubin test reported by
      default because model is just
      identified.

. * END weak_test
. * No overidentification test can be computed with one excluded instrument for
. * one endogenous regressor. A weak-robust test does not establish exclusion.
. clear

. set obs 1
Number of observations (_N) was 0, now 1.

. generate double first=first_b

. generate double reduced=reduced_b

. generate double iv=iv_b

. generate double iv_robust_se=iv_se

. export delimited using "output/iv_extension_results.csv", replace
(file output/iv_extension_results.csv not found)
file output/iv_extension_results.csv saved

. display "ECO603_IV_EXTENSION_COMPLETE"
ECO603_IV_EXTENSION_COMPLETE

