agreed.
of course, you can change the cutpoints of your covariates and get a more
"balanced" number of treated and control units in each stratum.
but this shouldn't be your main goal: your goal should be to fix the cutpoints so
that the residual imbalance is irrelevant to your research.
Il 29/04/15 16:18, Thomas Omer <thomas.omer(a)unl.edu> ha scritto:
This issue is an adequate match. The extent to which they cannot be derived from a
single CEM run should be irrelevant if the purpose is to generate the best match.
Matching does not solve statistical problems it merely helps strengthen the arguments that
the treatment is the difference between the groups.
Sent from my iPad
On Apr 29, 2015, at 9:14 AM, pureum kim
<pureum.kim(a)usc.edu> wrote:
Dear CEM List members,
I have about 45 treatment firms and I am trying to create a control sample. Using that
control
sample, we plan to collect additional information about the firm, which would take some
time and
effort. I was wondering if I could use different CEM specifications for each treatment
firm to get the
most accurate control firms.
The issue is that for some treatment firms, I get a huge strata, on the other
hand, for other groups I have two control firms. I was wondering if I could use a more
stringent
matching criteria for those treatment firms with large number of control firms and a less
stringent
matching criteria for those that have a low number of control firms.
My concern is how would I run a regression later because the weights are derived from
different
matching specifications. Or does it matter?
Thank you for your time and consideration.
Kind Regards,
Pureum Kim
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