While I am not an expert on CEM I will provide some responses.   

1.  You are attempting  to match so consider what provides your best match.  there is no magic that provides the specific cutoffs if your goal is matching (which I presume it is).
2.  If the imbalance or bias is low then you have a reasonable match.
3.  I would hope for L1 less than .5 to make myself feel reasonable about the matching.
4. This is an issue concerning matching with replacement versus one to one matching without replacement.  I prefer one to one matching unless I have few controls and there are arguments for both possibilities.  I would check out some papers by Elizabeth Stuart that provide discussion of the costs and benefits of one-to-one w/o replacement versus with replacement.  In observing studies in my discipline, I find that authors fail to acknowledge or inform the extent to which there are duplicate matches in the sample and by default the control that is used multiple times induces correlation in the control sample that should be acknowledged for at least controlled for but few take those extra steps.  Using a control multiple times can induce bias that has an unobservable effect on testing between treatment and control.
On Apr 23, 2015, at 12:53 AM, pureum kim <pureum.kim@usc.edu> wrote:

Dear CEM List members,

My research question examines whether firms adopting fair value accounting for their 

pensions change their pension plan  assets. I was wondering if you could help me with the following 

quick questions about Coarsened Exact Matching.

1. What is the best practice for selecting the cut points? (I have read that Scott and Freedman-Diaconnis are the preferred methods.) 

2. My treatment sample is very small and using Scott or Freedman-Diaconnis leads  me to lose many treated firms. So I use deciles for certain matching variables instead of the Scott or FD.  Would this still be a concern if the imbalance is low? 

3. Is there a reasonable value for L1? I know that the lower value means less imbalance but is there a rule of thumb?

4. After creating a matched sample, are there any practical guides on how to run the regression? Some treated firms are matched with multiple control firms, and I believe that it is not a problem to run the regression even if some firms are matched with more control firms. Is there an issue if we don't have exact number of paired  treated and controlled firms?

Thank you so much for your time and consideration.

Kind Regards,


Pureum Kim
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