st: a new robust variance-covariance estimator conditional on covariates

[László Sándor <sandorl@gmail.com>]

Hi,

I would like to get back to using the Abadie-Imbens-Zheng estimator.
(I did not do a great job with the exposition two days ago.) I would
be happy with an implementation under Stata 12 on unix (or any
previous version).

Though David Card advised Guido to relabel the paper "Lower Your
Standard Errors by 10%!", the paper does make a convincing point that
a sample does not need to be treated as having random covariates in
many cases, e.g. when we have the full population (where "errors" or
noise can come from an imaginary superpopulation, but the covariates,
like which are the states of the US or the proportion of male in the
population, are arguably given) or when the subsample is not a random
subsample of the population anyway ("convenience samples"). These
arguments are more more common in the program evaluation literature,
where people often discuss the different estimands of population
treatment effects or only on the treated etc.
http://www.nber.org/papers/w17442

So irrespective of the claims of many "modern" graduate econometrics
textbooks, in some cases the usual Huber-White sandwich/robust
standard errors are excessively conservative (the immediate response
to White [1980] did see the point, like Chow [1984].). Abadie, Imbens
and Zheng suggest an improvement.

I wonder what is a good approach to implement a new VCE in Stata and
how it is possible to use it across multiple commands. Or I need to
hack one ado file at a time, and use those?

Any thoughts on this will be greatly appreciated.

Thanks,

Laszlo


László Sándor
PhD candidate in Economics
Harvard University

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