In this paper we pursue a novel application of Bayesian empirical likelihood methods to estimate the canonical stochastic frontier model. We utilize this new framework to study technical efficiency, scale economies and technological change in the United States nuclear energy generation sector....

Monte Carlo (MC) simulations are one of the dominant approaches to compare statistical methods. To date, there is no standard procedure for MC simulations. Although internally valid, they exhibit a certain degree of arbitrariness through the various choices that researchers make. In this paper,...

We consider shape constrained kernel-based probability density function (PDF) and probability mass function (PMF) estimation. Our approach is of widespread potential applicability and includes, separately or simultaneously, constraints on the PDF (PMF) function itself, its integral (sum), and...