Ranking and selection, Truncated normal, Stochastic frontier
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.
Horrace, William C., "On Ranking and Selection from Independent Truncated Normal Distributions" (2004). Economics Faculty Scholarship. 15.
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.