Li, Mingliang; Tobias, Justin

Studies in Nonlinear Dynamics and Econometrics (2006) (Originally published as WP #05005, February 2005)

We describe a new simulation-based algorithm for Bayesian
estimation of structural effects in models where the outcome of interest
and an endogenous treatment variable are ordered.
Our algorithm makes use of a reparameterization, suggested
by Nandram and Chen (1996) in the context of a single equation
ordered-probit model, which significantly improves the mixing
of the standard Gibbs sampler. We illustrate the improvements afforded
by this new algorithm in a generated data experiment and also make use of our methods in an
empirical application. Specifically, we take data from the National
Longitudinal Survey of Youth (NLSY) and investigate the impact of
maternal alcohol consumption on early infant health. Our results show clear evidence
that the health outcomes of infants whose mothers drink while pregnant are worse
than the outcomes of infants whose mothers never consumed alcohol while pregnant. In addition,
the estimated parameters clearly suggest the need to control for the endogeneity of
maternal alcohol consumption.

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