Test: sandbox

[Katy Red]

Help with xxx

* Example generated by -dataex-. For more info, type help dataex
clear
input float(logdisclsize electionyear landslide) long ein float year str16 state
 10.84887 0 0 10248780 2011 "ME"
10.694057 0 0 10248780 2013 "ME"
10.795568 1 0 10248780 2014 "ME"
10.870756 0 0 10248780 2015 "ME"
 11.00408 0 0 10248780 2016 "ME"
10.983002 1 0 10248780 2018 "ME"
11.102217 0 0 10248780 2019 "ME"
 10.12475 0 0 10270690 2013 "ME"
11.652548 0 0 10270690 2015 "ME"
  11.8213 0 0 10270690 2016 "ME"
12.106854 0 0 10270690 2017 "ME"
12.061775 1 0 10270690 2018 "ME"
12.056853 0 0 10270690 2019 "ME"
10.518646 0 0 10317679 2012 "ME"
 10.63246 0 0 10317679 2013 "ME"
10.839287 1 0 10317679 2014 "ME"
 10.85532 0 0 10317679 2015 "ME"
10.849357 0 0 10317679 2016 "ME"
10.888838 0 0 10317679 2017 "ME"
11.097547 1 0 10317679 2018 "ME"
end

output:

. reghdfe logdisclsize electionyear closeelection size  wins_ExecComp wins_leverage w
> ins_ContribReliance, absorb (ein year) cluster(state) 
(dropped 550 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,506
Absorbing 2 HDFE groups                           F(   6,     49) =       2.57
Statistics robust to heteroskedasticity           Prob > F        =     0.0301
                                                  R-squared       =     0.9857
                                                  Adj R-squared   =     0.9827
                                                  Within R-sq.    =     0.0010
Number of clusters (state)   =         50         Root MSE        =     0.5813

                                       (Std. err. adjusted for 50 clusters in state)
------------------------------------------------------------------------------------
                   |               Robust
      logdisclsize | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
      electionyear |   .0172858   .0112746     1.53   0.132    -.0053714     .039943
     closeelection |  -.0052555   .0202606    -0.26   0.796    -.0459708    .0354597
              size |   .0274611   .0123293     2.23   0.031     .0026844    .0522378
     wins_ExecComp |   .0447626   .0661768     0.68   0.502    -.0882246    .1777498
     wins_leverage |   .0610303   .0284481     2.15   0.037     .0038618    .1181989
wins_ContribReli~e |   .0122862     .03129     0.39   0.696    -.0505935    .0751659
             _cons |   7.541963   .1793516    42.05   0.000     7.181543    7.902384
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         ein |      5085           0        5085     |
        year |         9           1           8     |
-----------------------------------------------------+

. reghdfe logdisclsize electionyear closeelection size wins_ExecComp wins_leverage w
> ins_ContribReliance, absorb (ein year) cluster(state)
(dropped 550 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression Number of obs = 29,506
Absorbing 2 HDFE groups F( 6, 49) = 2.57
Statistics robust to heteroskedasticity Prob > F = 0.0301
R-squared = 0.9857
Adj R-squared = 0.9827
Within R-sq. = 0.0010
Number of clusters (state) = 50 Root MSE = 0.5813

(Std. err. adjusted for 50 clusters in state)
------------------------------------------------------------------------------------
| Robust
logdisclsize | Coefficient std. err. t P>|t| [95% conf. interval]
-------------------+----------------------------------------------------------------
electionyear | .0172858 .0112746 1.53 0.132 -.0053714 .039943
closeelection | -.0052555 .0202606 -0.26 0.796 -.0459708 .0354597
size | .0274611 .0123293 2.23 0.031 .0026844 .0522378
wins_ExecComp | .0447626 .0661768 0.68 0.502 -.0882246 .1777498
wins_leverage | .0610303 .0284481 2.15 0.037 .0038618 .1181989
wins_ContribReli~e | .0122862 .03129 0.39 0.696 -.0505935 .0751659
_cons | 7.541963 .1793516 42.05 0.000 7.181543 7.902384
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
Absorbed FE | Categories - Redundant = Num. Coefs |
-------------+---------------------------------------|
ein | 5085 0 5085 |
year | 9 1 8 |
-----------------------------------------------------+