Marginal effects in multivariate probit and kindred discrete and count outcome models, with applications in health economics
By: John Mullahy
Contributors: National Bureau of Economic Research
Series: NBER working paper series -- working paper 17588; Working paper series (National Bureau of Economic Research : Online) -- working paper no. 17588.
Publisher: National Bureau of Economic Research
Published: 2011
Place of publication: Cambridge, MA
Language: eng
Format: Electronic resource
Description: "The NBER Bulletin on Aging and Health provides summaries of publications like this.  You can sign up to receive the NBER Bulletin on Aging and Health by email.  Estimation of marginal or partial effects of covariates x on various conditional parameters or functionals is often the main target of applied microeconometric analysis.  In the specific context of probit models such estimation is straightforward in univariate models, and Greene, 1996, 1998, has extended these results to cover the case of quadrant probability marginal effects in bivariate probit models.The purpose of this paper is to extend these results to the general multivariate probit context for arbitrary orthant probabilities and to demonstrate the applicability of such extensions in contexts of interest in health economics applications.  The baseline results are extended to models that condition on subvectors of y, to count data structures that derive from the probability structure of y, to multivariate ordered probit data structures, and to multinomial probit models whose marginal effects turn out to be a special case of those of the multivariate probit model.  Simulations reveal that analytical formulae versus fully numerical derivatives result in a reduction in computational time as well as an increase in accuracy"--National Bureau of Economic Research web site.
Notes: Title from PDF file as viewed on 1/12/2012.

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