Discrete Poisson kernel density estimation - with an application to wildcat coal strikes

This paper proposes a nonparametric Poisson kernel density estimation techn ique for discrete distributions. Economists have been using continuous kern els to approximate discrete distributions. This work introduces a discrete kernel as more appropriate for approximating discrete distributions. Simula tion results are presented to compare with standard parametric approaches. We apply our discrete Poisson kernel estimator to approximate the distribut ion of coal mine wildcat strikes in the United States.