st: sample size: linear probability vs probit

[David K Evans <dkevans@fas.harvard.edu>]

I understand why the probit model drops variables which predict an outcome
perfectly even if they aren't perfectly correlated with the outcome (e.g.
if X=1 always implies Y=1, even if X=0 may not imply that Y=1).

However, the linear probability model does not drop those variables.

Why the discrepancy?

Thanks,
David

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PhD student, Harvard Economics Department
Phone: (O) 617-495-5634, (H) 617 - 493 - 1536
Address: Currier Mail Center #554, Cambridge, MA 02138
Website: www.people.fas.harvard.edu/~dkevans

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