Abstract #300288

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JSM 2003 Abstract #300288
Activity Number: 293
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Stat. Sciences
Abstract - #300288
Title: A Bayesian Instrumental Variables Analysis with a Categorical Endogenous Covariate
Author(s): Susan M. Paddock*+
Companies: RAND Corporation
Address: Statistics Group, Santa Monica, CA, 90401-3208,
Keywords: Instrumental variable ; Bayesian statistics ; multinomial probit ; Causal inference ; endogeneity
Abstract:

Observational data from surveys and administrative databases are commonly used to evaluate the impact of public policies, programs, and treatments. A well-known obstacle to drawing inferences about treatment effectiveness from these data sources is that treatment assignment may be correlated with the outcome of interest. Instrumental variables (IV) methods are widely used to account for this selection bias. I will discuss an IV approach that accommodates an unordered categorical endogenous covariate through a multinomial probit model (MNP) to account for selection bias. I will discuss the difficulties associated with using MNP when jointly modeling outcomes and selection.

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Revised March 2003