Hi. Below is the output on running the single flexpaneldid command. I would like to export only the final "Conditional Diff-in-Diff" table (at the very end of the output) into either excel or word, but have been unable to figure out how to do this. Can someone guide me here?
Code:
. flexpaneldid confirmed, id(state) treatment(stepone) time(weeknum) prepdataset(flex_pre.dta) statmatching(con(test
> ed pop_perkm2_2019)) outcometimerelstart(1) outcomedev(-1) test
********************************************************************************
************************* flexpaneldid *****************************************
********************************************************************************
--------------------------------------------------------------------------------
outcome: confirmed
id: state
treatment: stepone
time: weeknum
outcome_time_start: 1
outcome_time_end: .
outcome_dev: -1
cemmatching:
statmatching: con(tested pop_perkm2_2019)
test: test
outcomemissing:
didmodel:
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********************************************************************************
************************* Matching: STAT ***************************************
********************************************************************************
********************************************************************************
************************* flexpaneldid - Matching Summary **********************
********************************************************************************
| NT T
---------------+------------------------------
All | 20 15
Matched sample | 10 15
********************************************************************************
************************* ps-test **********************************************
********************************************************************************
------------------------------------------------------------------------------
| Mean | t-test | V(T)/
Variable | Treated Control %bias | t p>|t| | V(C)
------------------------+--------------------------+---------------+----------
tested | 6.4523 6.4725 -0.2 | -0.01 0.996 | 0.92
pop_perkm2_2019 | 1397.4 1040.8 11.8 | 0.32 0.749 | 1.73
outcome_dev | .338 .24577 18.2 | 0.50 0.622 | 1.89
------------------------------------------------------------------------------
* if variance ratio outside [0.34; 2.98]
----------------------------------------------------------------------
Ps R2 LR chi2 p>chi2 MeanBias MedBias B R %Var
----------------------------------------------------------------------
0.059 2.47 0.481 10.1 11.8 55.0* 1.57 0
----------------------------------------------------------------------
* if B>25%, R outside [0.5; 2]
********************************************************************************
************************* KS-Test **********************************************
********************************************************************************
ksmirnov tested , by(treated)
Two-sample Kolmogorov–Smirnov test for equality of distribution functions
Smaller group D p-value Corrected
--------------------------------------------------
0 0.1333 0.766
1 -0.0667 0.936
Combined K-S 0.1333 0.999 0.999
Note: Ties exist in combined dataset;
there are 27 unique values out of 30 observations.
ksmirnov pop_perkm2_2019 , by(treated)
Two-sample Kolmogorov–Smirnov test for equality of distribution functions
Smaller group D p-value Corrected
--------------------------------------------------
0 0.1333 0.766
1 -0.2667 0.344
Combined K-S 0.2667 0.660 0.551
Note: Ties exist in combined dataset;
there are 25 unique values out of 30 observations.
ksmirnov outcome_dev , by(treated)
Two-sample Kolmogorov–Smirnov test for equality of distribution functions
Smaller group D p-value Corrected
--------------------------------------------------
0 0.1333 0.766
1 -0.1333 0.766
Combined K-S 0.1333 0.999 0.999
********************************************************************************
************************* Conditional Diff-in-Diff *****************************
********************************************************************************
Average treatment effect for the treated
Estimator : Nearest neighbor No. of treated obs = 15
Distance metric : Statistical DF No. of unique controls = 10
Mean no. of matches = 1
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Outcome | mean Diff | DiD* |AI robust | z P>|z|
| treated | controls | | S.E. | |
------------+-----------+----------+----------+----------+----------+-----------
confirmed | 0.1286 | 0.0536 | 0.0750 | 0.0424 | 1.7703 | 0.0984
--------------------------------------------------------------------------------
* Consistent bias-corrected estimator as proposed in Abadie & Imbens (2006,2011).
.
