On ranking and selection from independent truncated normal distributions

This paper develops probability statements and ranking and selection rules for independent truncated normal populations. An application to a broad class of parametric stochastic frontier models is considered, where interest centers on making probability statements concerning unobserved firm-level technical inefficiency. In particular, probabilistic decision rules allow subsets of firms to be deemed relatively efficient or inefficient at prespecified probabilities. An empirical example is provided.