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Re: st: Pstest and Sensatt
From
Fernando Rios Avila <[email protected]>
To
[email protected]
Subject
Re: st: Pstest and Sensatt
Date
Tue, 4 Mar 2014 08:23:55 -0500
Hi Isobel,
So, Im not familiar with the sensatt, but regarding the pstest, keep
in mind that what you want is either small absolute biases (after
matching) and/or non significant t-stats.
The t stats reported are the test for whether or not any particular
variable is statistically different between control and treatment
sample, after matching the information. The rule of thumb should be
the same as when you read the significance of a coefficient on a
regression (they should be smaller than 2).
Regarding the bias, i would not pay attention on the bias change or
bias reduction, but the absolute bias after matching. The rule of
thumb here is usually to have all biases after match lower than 20%.
Ideally all your variables should have small biases, or small t-stats,
to "accept" the model. If not, you need to modify the specification of
the propensity score model.
HTH
Fernando
On Tue, Mar 4, 2014 at 4:54 AM, Isobel Williams <[email protected]> wrote:
> Dear All,
>
> I am having some trouble interpreting my -pstest- (a user-written SSC programme) results. Most of my t-statistics are insignificant, and the most absolute biases are at less than 10% after matching. The mean absolute bias is 3.8% after matching. Is this permissible in the model? I am using 80+ parameters so I thought that a small bias of 3.8% and 24 significant t-statistics would be tolerable in the model. However, of all of these 24 significant t-statistics, the highest absolute bias level is 14%
>
> I am also trying to carry out the sensatt test (also a user-written SSC programme by Becker and Ichino, 2002) on the model, however I always get the error message 'matsize too small'. I have the IC13.1; I set the matsize to 800 and I am still getting that error message. Is there any other way I can carry out the test?
>
> Many thanks,
> Isobel Williams
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