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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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  • Mark Andor
  • Frederik Hesse
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    Abstract

    Based on the seminal paper of Farrell (1957), researchers have developed several methods for measuring eciency. 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.

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    Paper provided by Institute of Spatial and Housing Economics, Munster Universitary in its series Working Papers with number 201285.

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    Handle: RePEc:muc:wpaper:201285

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    Keywords: efficiency; stochastic non-smooth envelopment of data (StoNED); data envelopment analysis (DEA); stochastic frontier analysis (SFA); monte carlo simulation;

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