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A quantile‐based approach for relative efficiency measurement
Author(s) -
Griffin Paul M.,
Kvam Paul H.
Publication year - 1999
Publication title -
managerial and decision economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.288
H-Index - 51
eISSN - 1099-1468
pISSN - 0143-6570
DOI - 10.1002/1099-1468(199912)20:8<403::aid-mde956>3.0.co;2-e
Subject(s) - data envelopment analysis , quantile , econometrics , statistic , parametric statistics , ranking (information retrieval) , economics , stochastic frontier analysis , similarity (geometry) , nonparametric statistics , computer science , statistics , mathematics , microeconomics , artificial intelligence , production (economics) , image (mathematics)
Two popular approaches for efficiency measurement are a non‐stochastic approach called data envelopment analysis (DEA) and a parametric approach called stochastic frontier analysis (SFA). Both approaches have modeling difficulty, particularly for ranking firm efficiencies. In this paper, a new parametric approach using quantile statistics is developed. The quantile statistic relies less on the stochastic model than SFA methods, and accounts for a firm's relationship to the other firms in the study by acknowledging the firm's influence on the empirical model, and its relationship, in terms of similarity of input levels, to the other firms. Copyright © 1999 John Wiley & Sons, Ltd.