rwrr

CUADERNO Nº 3

. pscore p2000 agestm1 agestm2 agestm3 tohijos seguro edu1 edu2 edu3 pobr1 pobr2 pobr3 pobr4 unidas, pscore(ps_p2000) blockid
> (blocksfm) comsup level (0.001)

****************************************************
Algorithm to estimate the propensity score
****************************************************

The treatment is p2000

pertenece |
al p2000 |Freq. Percent Cum.
------------+-----------------------------------
no | 1,731 50.36 50.36
si | 1,706 49.64 100.00
------------+-----------------------------------
Total | 3,437 100.00



Estimation of the propensity score

Iteration 0: log likelihood = -2373.8503
Iteration 1: log likelihood = -2349.4865Iteration 2: log likelihood = -2349.4843

Probit regression Number of obs = 3425
LR chi2(13) = 48.73
Prob > chi2 = 0.0000
Log likelihood = -2349.4843 Pseudo R2 = 0.0103------------------------------------------------------------------------------
p2000 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
agestm1 | .3247271 .1372341 2.37 0.018 .0557532 .593701
agestm2 | .1524679 .1083777 1.41 0.159 -.0599485 .3648843
agestm3 | .1046557.1004579 1.04 0.298 -.0922381 .3015496
tohijos | .0511747 .0166227 3.08 0.002 .0185948 .0837547
seguro | -.1049384 .0550138 -1.91 0.056 -.2127634 .0028866
edu1 | .0290409 .1439517 0.20 0.840 -.2530992 .3111809
edu2 | .0025858 .0731002 0.04 0.972 -.1406878 .1458595
edu3 | -.1586256.0567169 -2.80 0.005 -.2697887 -.0474625
pobr1 | -.1712696 .0777537 -2.20 0.028 -.3236641 -.018875
pobr2 | -.2263771 .0747914 -3.03 0.002 -.3729656 -.0797887
pobr3 | -.2725319 .0721093 -3.78 0.000 -.4138635 -.1312002
pobr4 | -.076735 .0709434 -1.08 0.279 -.2157814 .0623115
unidas | .0821805.0599039 1.37 0.170 -.035229 .19959
_cons | -.1018397 .1323827 -0.77 0.442 -.361305 .1576255
------------------------------------------------------------------------------

Note: the common support option has been selected
The region of common support is [.31486561, .70208607]


Description of the estimated propensity score
in region of common supportEstimated propensity score
-------------------------------------------------------------
Percentiles Smallest
1% .3636385 .3148656
5% .400965 .3251283
10% .4203417 .3320378 Obs 3425
25% .4504303 .3320378 Sum of Wgt. 3425

50% .4999192 Mean .4949652Largest Std. Dev. .0593963
75% .5358588 .681892
90% .5729868 .6827142 Variance .0035279
95% .5883728 .7020861 Skewness .0095755
99% .6276784 .7020861 Kurtosis 2.679511


******************************************************
Step 1: Identification of the optimal number ofblocks
Use option detail if you want more detailed output
******************************************************

The final number of blocks is 7

This number of blocks ensures that the mean propensity score
is not different for treated and controls in each blocks

**********************************************************
Step 2: Test of balancing property of the propensity score
Use...