  In this paper we propose to make Bayesian inferences for the parameters of
the Lomax distribution using non-informative priors, namely the Jeffreys prior
and the reference prior. We assess Bayesian estimation through a Monte Carlo
study with 500 simulated data sets. To evaluate the possible impact of prior
specification on estimation, two criteria were considered: the bias and square
root of the mean square error. The developed procedures are illustrated on a
real data set.
