In this note, we examine the boundary properties of Bernstein estimators of density and distribution functions. Specifically, we show that Bernstein density estimators have decreased bias, but increased variance in the boundary region. In the case of distribution function estimation, we show that Bernstein estimators experience an advantageous boundary effect. Indeed, we prove a particularly impressive property of Bernstein distribution function estimators: they have decreased bias and variance in the boundary region. Finally, we also pay attention to the impact of the so-called shoulder condition on the boundary behaviour of these estimators.