I guess you already know most of the answers to this one.
Informally, if several different methods give you similar answers,
that's helpful.
Formally, you'd be pushed to interpret that in statistical inference
terms when presumably even different methods are hardly independent.
You've got to penalise yourself for firing a shotgun.
The problem is surely compounded if you are simultaneously on the
lookout for several discontinuities at once. If discontinuities can all
be tiny ones, what next?
I'd be happy to be called primitive, but my prejudice is that genuine
discontinuities are obvious on a well-chosen graph and are independently
supported by substantive evidence.
Nick
[email protected]
Jen Zhen
I have a set of Regression Discontinuity estimators none of which by
itself has enough power to give me statistically significant results
(because firstly most of the discontinuities are of limited size and
secondly my number of observations around each discontinuity is
limited). However, I suspect that if I could efficiently combine the
information from all (around 35-50) RD estimators, then the result
might actually have enough power.
So I have been considering whether I could combine them using a
Minimum Distance or Asymptotic Least Squares estimator.
However, I have not yet found out whether there is a good way to do
this in Stata. I am also not yet fully sure whether this method is
sensible in general, so any views on that would probably also be most
helpful.
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