Maximum likelihood and two-step estimation of an ordered-probit selection model

We discuss the estimation of a regression model with an ordered-probit selection rule. We have written a Stata command, oheckman, that computes two-step and full-information maximum-likelihood estimates of this model. Using Monte Carlo simulations, we compare the performances of these estimators under various conditions.


Issue Date:
2007
Publication Type:
Journal Article
DOI and Other Identifiers:
st0123 (Other)
PURL Identifier:
http://purl.umn.edu/119266
Published in:
Stata Journal, Volume 07, Number 2
Page range:
167-182
Total Pages:
16

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 Record created 2017-04-01, last modified 2017-08-26

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