Here is an example illustrating the source of my confusion.
Code:
. use http://www.stata-press.com/data/r13/cattaneo2, clear
(Excerpt from Cattaneo (2010) Journal of Econometrics 155: 138-154)
. tab mbsmoke
1 if mother |
smoked | Freq. Percent Cum.
------------+-----------------------------------
nonsmoker | 3,778 81.39 81.39
smoker | 864 18.61 100.00
------------+-----------------------------------
Total | 4,642 100.00
. teffects nnmatch (bweight mage prenatal1 mmarried fbaby) (mbsmoke), nn(1)
Treatment-effects estimation Number of obs = 4,642
Estimator : nearest-neighbor matching Matches: requested = 1
Outcome model : matching min = 1
Distance metric: Mahalanobis max = 139
----------------------------------------------------------------------------------------
| AI Robust
bweight | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
ATE |
mbsmoke |
(smoker vs nonsmoker) | -240.3306 28.43006 -8.45 0.000 -296.0525 -184.6087
----------------------------------------------------------------------------------------
.
.
. tebalance summarize
note: refitting the model using the generate() option
Covariate balance summary
Raw Matched
-----------------------------------------
Number of obs = 4,642 9,284
Treated obs = 864 4,642
Control obs = 3,778 4,642
-----------------------------------------
-----------------------------------------------------------------
|Standardized differences Variance ratio
| Raw Matched Raw Matched
----------------+------------------------------------------------
mage | -.300179 -.0040826 .8818025 .9815517
prenatal1 | -.3242695 -2.78e-16 1.496155 1
mmarried | -.5953009 -2.42e-16 1.335944 1
fbaby | -.1663271 2.24e-16 .9430944 1
-----------------------------------------------------------------
0 Response to sample used by teffects matching estimators
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