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When, where and how to perform efficiency estimation
Author(s) -
Badunenko Oleg,
Henderson Daniel J.,
Kumbhakar Subal C.
Publication year - 2012
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/j.1467-985x.2011.01023.x
Subject(s) - estimator , data envelopment analysis , econometrics , monte carlo method , kernel (algebra) , nonparametric statistics , statistics , parametric statistics , stochastic frontier analysis , mathematics , sample (material) , sample size determination , computer science , economics , chemistry , chromatography , combinatorics , production (economics) , macroeconomics
Summary. We compare two flexible estimators of technical efficiency in a cross‐sectional setting: the non‐parametric kernel stochastic frontier analysis estimator of Fan, Li and Weersink with the non‐parametric bias‐corrected data envelopment analysis estimator of Kneip, Simar and Wilson. We assess the finite sample performance of each estimator via Monte Carlo simulations and empirical examples. We find that the reliability of efficiency scores critically hinges on the ratio of the variation in efficiency to the variation in noise. These results should be a valuable resource to both academic researchers and practitioners.