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Re: st: Balance for PSM


From   Jorge Eduardo Pérez Pérez <jorge_perez@brown.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Balance for PSM
Date   Mon, 2 Dec 2013 16:27:54 -0500

I meant
" You have few controls"
--------------------------------------------
Jorge Eduardo Pérez Pérez
Graduate Student
Department of Economics
Brown University


On Mon, Dec 2, 2013 at 4:26 PM, Jorge Eduardo Pérez Pérez
<jorge_perez@brown.edu> wrote:
> Carlos,
>
> You are not supposed to send attachments to Statalist. I did not open it.
>
> You are also supposed to say that psmatch2 is an user written command from SSC.
>
> Having said that, you may want to rethink your problem. Do you think
> that informality is as good as randomly assigned to workers after
> controlling for the limited set of covariates you have? I think not:
> you lack quite few controls. Are workers within some industries more
> likely to be informal than others? Are workers in different cities
> more likely to be informal than others? I could go on and on, but this
> is the Stata list, not the economics one.
>
> Your results show that your covariates are not balanced in either your
> unmatched or matched sample, with the exception of gender which seems
> balanced according to the t-test (which has it's own problems, see
> http://imai.princeton.edu/research/files/matchse.pdf) . So you need to
> redefine your model before estimating ATE or ATT before proceeding
> with the matching.
>
> It seems that what you ran was a nearest neighbour matching. Radius
> matching can be more computationally demanding, but before buying a
> new computer I would change the propensity score specification, make
> sure I have balance, and then start obtaining matching estimates. And
> before doing that, I would think about whether propensity score
> matching is the right tool to use.
>
> Regards, Jorge Pérez.
> --------------------------------------------
> Jorge Eduardo Pérez Pérez
> Graduate Student
> Department of Economics
> Brown University
>
>
> On Mon, Dec 2, 2013 at 3:27 PM, Carlos Tendilla González
> <carlos.tendilla@imss.gob.mx> wrote:
>> Hi,
>>
>> I am using Stata 13. I am doing a study about Informality and its effect on Wage. The data base contains information about employees and their work status, and also some personal characteristics  (age, sex, state, civil status and others).
>>
>> I have to perform the Propensity Score Matching for NN, Startification, Radius and Kernel Matching. I started doing a PS Match using psmatch2.ado, and the results I had were (also available in attached):
>>
>> . pstest familiar casado hombre edad edad2 escolaridad escolar2 edadsexo, raw t(totalformal)
>> . probit totalformal familiar casado hombre edad edad2 escolaridad escolar2 edadsexo
>> . predict double ps
>> . psmatch2 totalformal, outcome (lsalhora) pscore(ps) ate
>> . pstest familiar casado hombre edad edad2 escolaridad escolar2 edadsexo, both
>>
>> ------------------------------------------------------------------------------
>>                 Unmatched |       Mean               %reduct |     t-test
>>     Variable      Matched | Treated Control    %bias  |bias| |    t    p>|t|
>> --------------------------+----------------------------------+----------------
>>      familiar   Unmatched | .47932 .29533     38.5         |  59.46  0.000
>>                  Matched  | .47932   .48352     -0.9    97.7 | -61.65  0.000
>>                           |                                  |
>>        casado   Unmatched |   .545   .37322     35.0         |  54.35  0.000
>>                  Matched  |   .545   .54642     -0.3    99.2 | -55.63  0.000
>>                           |                                  |
>>        hombre   Unmatched |  .6161   .62242     -1.3         |  -2.03  0.043
>>                  Matched  |  .6161   .62591     -2.0   -55.0 |  -0.86  0.390
>>                           |                                  |
>>          edad   Unmatched | 35.085   31.907     26.9         |  42.43  0.000
>>                  Matched  | 35.085   34.781      2.6    90.4 | -38.79  0.000
>>                           |                                  |
>>         edad2   Unmatched | 1348.2   1179.4     19.4         |  30.44  0.000
>>                  Matched  | 1348.2   1322.7      2.9    84.9 | -27.09  0.000
>>                           |                                  |
>>   escolaridad   Unmatched | 11.209   7.9337     57.0         |  88.51  0.000
>>                  Matched  | 11.209   11.156      0.9    98.4 | -95.41  0.000
>>                           |                                  |
>>      escolar2   Unmatched | 159.96   94.585     14.8         |  22.94  0.000
>>                  Matched  | 159.96   156.09      0.9    94.1 | -27.02  0.000
>>                           |                                  |
>>      edadsexo   Unmatched |  21.85   19.616     11.9         |  18.39  0.000
>>                  Matched  |  21.85   22.111     -1.4    88.3 | -18.50  0.000
>>                           |                                  |
>> ------------------------------------------------------------------------------
>>
>> I thought the results were ok, since the bias in all cases is less than 5%. But then I tried to run a Radius Matching doing the same steps I did before, but this time including radius in the command
>>
>> . psmatch2 totalformal, outcome (lsalhora) pscore(ps) ate radius
>>
>> The issue I had is that Stata never ended processing the command after 24 hrs. So then I tried to use pscore.ado and Stata reported that the Sample does not Satisfies the Balance condition so I have to redefine the model to achieve balance.
>>
>> In conclusion I have 2 questions:
>>
>> 1) The first results I had with psmatch2.ado were wrong (unbalanced)?
>> 2) If the answer is no, do I have to get a better PC to process Radius Matching with psmatch2.ado?
>> 3) If the answer is yes, why psmatch2.ado worked without Radius and did not worked with Radius?
>> 4) Is it possible that my sample is not good for PSM?
>>
>> Thanks and regards.
>>
>>
>>
>>
>>
>> Email secured by Check Point
>>

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