st: AW: new features for cmp and xtabond2

["Dithmer, Jan" <jdithme@food-econ.uni-kiel.de>]

Dear David,

I really like the idea to use principal components analysis to reduce the instrument count.
However, when the panel under scrutiny has many time periods, the instrument set may still be large.
Therefore, may the 'pca' option be combined with the 'collapse' or the 'laglimits' option to further reduce the number of instruments?

Best, Jan


-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von David Roodman (droodman@cgdev.org)
Gesendet: Tuesday, April 17, 2012 3:12 AM
An: statalist@hsphsun2.harvard.edu
Betreff: st: new features for cmp and xtabond2

I've added the following features:
* cmp now has a covariance option that makes it easier to impose certain constraints on the error covariance matrix for each level of a model. So in a two-level model "covariance(independent unstructured)" would specify that the random effects are not correlated across equations while leaving the covariances at the observation level unconstrainted. As another example, "covariance(exchangeable exchangeable)" specifies that at each level all correlations between pairs of errors are the same. See the help for xtmixed for more on these ideas.
* xtabond2 now accepts factor variables.
* xtabond2 now offers two options to use principal components analysis to reduce the instrument count. Option "pca" specifies that xtabond2 replace the "GMM-style" instruments with their principal components. By default, it keeps all components with eigenvalue greater than 1, or more if necessary to prevent underidentification. Option "components()" allows you to override this default. The help file contains an example.

Install each by typing "ssc install [program name], replace" and restarting Stata.
--David


David Roodman
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