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Bayesian Analysis of Structural Effects in an Ordered Equation System

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  • Li Mingliang

    ()
    (State University of New York at Buffalo)

  • Tobias Justin L

    ()
    (Iowa State University)

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    Abstract

    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 (relative to the standard Gibbs sampler) 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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    Bibliographic Info

    Article provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.

    Volume (Year): 10 (2006)
    Issue (Month): 4 (December)
    Pages: 1-24

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    Handle: RePEc:bpj:sndecm:v:10:y:2006:i:4:n:7

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    Cited by:
    1. Klaus Moeltner & James J. Murphy & John K. Stranlund & Maria Alejandra Velez, 2007. "Processing Data from Social Dilemma Experiments: A Bayesian Comparison of Parametric Estimators," Working Papers 07-013, University of Nevada, Reno, Department of Economics & University of Nevada, Reno , Department of Resource Economics.
    2. Zhang, Xiaohui & Zhao, Xueyan & Harris, Anthony, 2009. "Chronic diseases and labour force participation in Australia," Journal of Health Economics, Elsevier, vol. 28(1), pages 91-108, January.
    3. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Monash Econometrics and Business Statistics Working Papers 3/10, Monash University, Department of Econometrics and Business Statistics.

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