Joseph B. Kadane, Elias Moreno, Maria Eglee Perez and Luis Raul Pericchi
This paper explores the usefulness of robust Bayesian analysis in the
context of an applied problem, finding priors to model judicial
neutrality in an age discrimination case. We seek large classes of
prior distributions without trivial bounds on the posterior
probability of a key set, that is, without bounds that are independent
of the data. Such an exploration shows qualitatively where the prior
elicitation matters most, and quantitatively how sensitive the
conclusions are to specified prior changes. The novel non-parametric
and studied here represent judicial netrality and are reasonably
wide so that when a clear conclusion emerges from the data at hand,
this is arguably
beyond a reasonable doubt.
Keywords: discrimination, elicitation, law, linearization, moment problem.
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