case selection is ubiquitous in public management research. the manner by which scholars select sample of conduct their analyses can have profound consequences on their ability both to draw valid causal inferences and to estimate accurate relationships. with specific attention to their manifestation in empirical public management research. The article first reviews the threats to causal inference presented by case selection, focusing on their implications for internal and external validity. We then summarize a standard set of solutions to address potential problems for empirical models caused by non-random case selection. then illustrate several techniques that have been developed to overcome specific problems to show their utility for public management research