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The StoNED age: The departure into a new era of efficiency analysis? An MC study comparing StoNED and the "oldies" (SFA and DEA)

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  • Andor, Mark
  • Hesse, Frederik
Abstract
Based on the seminal paper of Farrell (1957), researchers have developed several methods for measuring efficiency. Nowadays, the most prominent representatives are nonparametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA), both introduced in the late 1970s. Since decades, researchers have been attempting to develop a method which combines the virtues - both nonparametric and stochastic - of these oldies. The recently introduced Stochastic non-smooth envelopment of data (StoNED) by Kuosmanen and Kortelainen (2010) is a promising method. This paper compares the StoNED method with the two oldies DEA and SFA and extends the initial Monte Carlo simulation of Kuosmanen and Kortelainen (2010) in two directions. Firstly, we consider a wider range of conditions. Secondly, we also consider the maximum likelihood estimator (ML) and the pseudolikelihood estimator (PL) for SFA and StoNED, respectively. We show that, in scenarios without noise, the rivalry is still between the oldies, while in noisy scenarios, the nonparametric StoNED PL now constitutes a promising alternative to the SFA ML.

Suggested Citation

  • Andor, Mark & Hesse, Frederik, 2012. "The StoNED age: The departure into a new era of efficiency analysis? An MC study comparing StoNED and the "oldies" (SFA and DEA)," CAWM Discussion Papers 60, University of Münster, Münster Center for Economic Policy (MEP).
    • Handle: RePEc:zbw:cawmdp:60
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    2. Mark Andor & Christopher Parmeter, 2017. "Pseudolikelihood estimation of the stochastic frontier model," Applied Economics, Taylor & Francis Journals, vol. 49(55), pages 5651-5661, November.

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    More about this item

    Keywords

    efficiency; stochastic non-smooth envelopment of data (StoNED); data envelopment analysis (DEA); stochastic frontier analysis (SFA); monte carlo simulation;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • D2 - Microeconomics - - Production and Organizations
    • L5 - Industrial Organization - - Regulation and Industrial Policy
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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