Hi Haakon, thanks for your note. If you match (i.e.,prune further) within
and respecting CEM's strata, then you keep all the bias and model
dependence reducing properties of CEM. The weights I think would have to be
adjusted by using the same formulas we give, with whatever observations
that are left after your second stage procedure. see j.mp/CEMweights on
weights in general.
Gary
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On Thu, Feb 8, 2018 at 4:46 PM, Haakon Gjerløw <haakon.gjerlow(a)stv.uio.no>
wrote:
Dear all,
I have a question concerning the correct way to combine CEM with other
matching procedures. Specifically, I am trying to match a data set with
CEM, and then apply Entropy balancing to the remaining sample (
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1904869). It seems
such two-step balancing is hinted at in both Iacus, King, Porro (2011) and
Hainmuller (2012)
My questions concerns the correct way to us the weights in regressions
after both procedures are done.
My intuition says that this is basically a two-step sampling procedure,
and that the correct way to use the weights is to multiply the weights from
CEM with the weights from Entropy (Solution A).
However, it might also be that the Entropy Balancing is overriding the
weights from CEM, and the observations should only be weighted by the
weights from Entropy (Solution B)
Have any of you investigated this in a more systematic/formal fashion?
All the best,
Haakon Gjerløw | Phd fellow
Department of Political Science | University of Oslo