A Monte Carlo Study of Efficiency Estimates from Frontier Models
Center for Policy Research Working Paper No. 97
34 Pages Posted: 21 Apr 2011 Last revised: 14 Mar 2015
Date Written: August 1, 2007
Parametric stochastic frontier models yield firm-level conditional distributions of inefficiency that are truncated normal. Given these distributions, how should one assess and rank firm-level efficiency? This study compares the techniques of estimating a) the conditional mean of inefficiency and b) probabilities that firms are most or least efficient. Monte Carlo experiments suggest that the efficiency probabilities are more reliable in terms of mean absolute percent error when inefficiency has large variation across firms. Along the way we tackle some interesting problems associated with simulating and assessing estimator performance in the stochastic frontier environment.You can download a PDF version of the paper and view it and print it using a FREE copy of Adobe Acrobat Reader.
Keywords: Truncated Normal, Stochastic Frontier, Efficiency, Multivariate Probabilities
JEL Classification: C12, C16, C44, D24
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