A quantile-based approach for relative efficiency measurement

Paul M. Griffin, Paul H. Kvam

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)403-410
Number of pages8
JournalManagerial and Decision Economics
Issue number8
StatePublished - Dec 1999

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Strategy and Management
  • Management Science and Operations Research
  • Management of Technology and Innovation


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