Bayesian Models and Methods in Public Policy and Government Settings

Details Bayesian Models and Methods in Public Policy and Government Settings Bayesian Models and Methods in Public Policy and Government Settings

2011-08-10

arxiv.org/abs/1108.2177v1

Statistical Science 2011, Vol. 26, No. 2, 212-226

Statistics

Methodology

Published in at http://dx.doi.org/10.1214/10-STS331 the Statistical Science (http://www.imstat.org/sts/) by the Institute of M

Scientific paper

10.1214/10-STS331

Starting with the neo-Bayesian revival of the 1950s, many statisticians argued that it was inappropriate to use Bayesian methods, and in particular subjective Bayesian methods in governmental and public policy settings because of their reliance upon prior distributions. But the Bayesian framework often provides the primary way to respond to questions raised in these settings and the numbers and diversity of Bayesian applications have grown dramatically in recent years. Through a series of examples, both historical and recent, we argue that Bayesian approaches with formal and informal assessments of priors AND likelihood functions are well accepted and should become the norm in public settings. Our examples include census-taking and small area estimation, US election night forecasting, studies reported to the US Food and Drug Administration, assessing global climate change, and measuring potential declines in disability among the elderly.

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