Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/79849 
Year of Publication: 
2013
Series/Report no.: 
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2013: Wettbewerbspolitik und Regulierung in einer globalen Wirtschaftsordnung - Session: Mathematical and Quantitative Methods No. F20-V3
Publisher: 
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft, Kiel und Hamburg
Abstract: 
Based on the seminal paper of Farrell (1957), researchers have developed several methods for measuring e fficiency. Nowadays, the most prominent representatives are nonparametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA), both introduced in the late 1970s. 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 such 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 several directions. We show, among others, 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.
JEL: 
C14
D24
L51
Document Type: 
Conference Paper

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