Predicting Health Care Expenditures with the MCMC Procedure

نویسنده

  • Greg Watson
چکیده

Substantial variation, excess zeros, skew and extreme outliers make fitting and predicting health care expenditures rather difficult. This paper presents a Bayesian model that uses the first year of the fourteenth panel (2009-2010) of the nationally representative Medical Expenditures Panel Survey (MEPS) to predict health care expenditures for individuals in the second year. The merits of a Bayesian approach are examined and compared to classical alternatives. Implementation in the MCMC procedure is presented in detail, and model diagnostics and validation are discussed.

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تاریخ انتشار 2013