. cate aipw (assets \$catecovars) (e401k), rseed(12345671) ///
>         controls(\$controls) group(4) nolog
{\smallskip}
Conditional average treatment effects     Number of observations       = 9,913
Estimator:       Augmented IPW            Number of folds in cross-fit =    10
Outcome model:   Linear lasso             Number of outcome controls   =    47
Treatment model: Logit lasso              Number of treatment controls =    47
CATE model:      Random forest            Number of CATE variables     =    17
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
             {\VBAR}               Robust
      assets {\VBAR} Coefficient  std. err.      z    P>|z|     [95\% conf. interval]
\HLI{13}{\PLUS}\HLI{64}
GATES        {\VBAR}
        rank {\VBAR}
          1  {\VBAR}   14238.01   3335.108     4.27   0.000     7701.317     20774.7
          2  {\VBAR}   6565.533   1482.069     4.43   0.000     3660.732    9470.334
          3  {\VBAR}   6646.957   1294.802     5.13   0.000     4109.191    9184.723
          4  {\VBAR}   5190.023   2487.992     2.09   0.037     313.6494     10066.4
\HLI{13}{\PLUS}\HLI{64}
ATE          {\VBAR}
       e401k {\VBAR}
  (Eligible  {\VBAR}
         vs  {\VBAR}
Not elig..)  {\VBAR}   8164.364   1151.125     7.09   0.000       5908.2    10420.53
\HLI{13}{\PLUS}\HLI{64}
POmean       {\VBAR}
       e401k {\VBAR}
Not eligi..  {\VBAR}   13910.87   842.0945    16.52   0.000     12260.39    15561.34
\HLI{13}{\BOTT}\HLI{64}
