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
Post a Comment