Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

# st: Propensity Score Matching

 From vikramfinavker To statalist@hsphsun2.harvard.edu Subject st: Propensity Score Matching Date Mon, 20 Feb 2012 02:53:02 -0800 (PST)

```Dear Statalisters,

First i apologise for not being clear and I thank you all for your replies.
I will try to explain what i want to do and where i am facing problem.

I am using psmatch2 with nearest neighbours matching with replacement.
Following is the command which i have used.

psmatch2 allheg10 vw1zscore vw1lnmva vw1mvgroslev vw1quickratio vw1fsaleds
d2-d11 yr_00-yr_10, n(1)

And following is the results of above command

Probit regression                                 Number of obs   =
3406
LR chi2(24)     =
548.41
Prob > chi2     =
0.0000
Log likelihood = -1007.6135                       Pseudo R2       =
0.2139

------------------------------------------------------------------------------
allheg10 |      Coef.   Std. Err.      z    P>|z|     [95% Conf.
Interval]
-------------+----------------------------------------------------------------
vw1zscore |   .0075111    .002529     2.97   0.003     .0025543
.0124678
vw1lnmva |   .3311453   .0249946    13.25   0.000     .2821568
.3801339
vw1mvgroslev |   1.457169   .1968683     7.40   0.000     1.071315
1.843024
vw1quickra~o |  -.0910223   .0231545    -3.93   0.000    -.1364042
-.0456404
vw1fsaleds |   .0026704   .0009382     2.85   0.004     .0008316
.0045091
d2 |  -.5984644   .2177925    -2.75   0.006     -1.02533
-.171599
d3 |   -.401803   .1907166    -2.11   0.035    -.7756007
-.0280053
d4 |  -.6046699   .1852172    -3.26   0.001     -.967689
-.2416508
d5 |  -.2739949   .1801271    -1.52   0.128    -.6270375
.0790477
d6 |  -.1714531   .1972053    -0.87   0.385    -.5579683
.2150621
d7 |  -.3407124    .190602    -1.79   0.074    -.7142855
.0328606
d8 |  -.4092481   .1824948    -2.24   0.025    -.7669314
-.0515648
d9 |  -.5232287   .3189424    -1.64   0.101    -1.148344
.1018868
d11 |   -.292377   .1768571    -1.65   0.098    -.6390105
.0542566
yr_00 |  -.1229459    .131999    -0.93   0.352     -.381659
.1357673
yr_01 |   .0223229   .1407681     0.16   0.874    -.2535775
.2982233
yr_02 |   .1623231   .1470985     1.10   0.270    -.1259846
.4506308
yr_03 |  -.1825395   .1357505    -1.34   0.179    -.4486057
.0835267
yr_04 |  -.1473961   .1367151    -1.08   0.281    -.4153527
.1205606
yr_05 |  -.1815719   .1393327    -1.30   0.193     -.454659
.0915152
yr_06 |  -.0916688   .1448511    -0.63   0.527    -.3755717
.1922342
yr_07 |  -.1135523   .1495029    -0.76   0.448    -.4065726
.1794681
yr_08 |  -.0781585   .1607199    -0.49   0.627    -.3931636
.2368467
yr_09 |  -.1666735   .1575016    -1.06   0.290    -.4753711
.1420241
_cons |  -2.987349   .3787435    -7.89   0.000    -3.729673
-2.245026
------------------------------------------------------------------------------

Now let me explain my variables. The dependent variable is Hedging dummy
(i.e. 1 if a firm is uses foreign currency contracts or interest rate swaps
and 0 otherwise). Other independent variables are determinants of hedging.
THis regression will tell me what influences firms to hedge. So, Now i
assume that the above method has created some kind of score which identifies
firms that are similar on all independent factors but their choice of
hedging. So, after identifying these firms i want to do following.

I have different risk measures and i want to do a mean difference test for
matched firms on these risk measures.
I want to do like this;

Control Gropup	Treatment Group
Variable	N	Mean	Median	Mean 	Median	Diff in Means
Risk 1	XYZ	0	0	0	0	0
Risk2	yxz	0	0	0	0	0

​
Earlier some one told me to use pstest after running psmatch2. BY doing that
i get the following results.

. pstest vw1edf1jun vw1eqvol eqvolomvol

----------------------------------------------------------------------------
|       Mean               %reduct |     t-test
Variable     Sample | Treated Control    %bias  |bias| |    t    p>|t|
------------------------+----------------------------------+----------------
vw1edf1jun  Unmatched | .98219   2.3953    -31.0         |  -7.61  0.000
Matched | .98219     2.31    -29.1     6.0 | -11.24  0.000
|                                  |
vw1eqvol  Unmatched | .39455   .49404    -41.3         |  -8.83  0.000
Matched | .39455   .44392    -20.5    50.4 |  -9.13  0.000
|                                  |
eqvolomvol  Unmatched | 2.3454   3.0729    -44.5         | -10.12  0.000
Matched | 2.3454   2.7199    -22.9    48.5 | -10.34  0.000
|                                  |
----------------------------------------------------------------------------
For the above table i don't understand why the mean for treated group is
same for unmatched and matched sample and how do i get number of
observations.

Is there any way i can identify which firm is matched against which firm?

If its still confusing please forgive me. I am referring the following paper
to do this " The Effects of Derivatives on Firm risk and Value" by  Sohnke
Bartram, Gregory Brown and Jennifer Conrad.

--
Regards,

Vikram Finavker

--
View this message in context: http://statalist.1588530.n2.nabble.com/Propensity-Score-Matching-tp7300864p7300864.html
Sent from the Statalist mailing list archive at Nabble.com.

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/
```