Authors: Kristína Kočišová; Peter Šugerek
Addresses: Faculty of Economics, Department of Banking and Investments, Technical University of Košice, Nemcovej 32, 04001, Košice, Slovak Republic ' Faculty of Economics, Department of Applied Mathematics and Business Informatics, Technical University of Košice, Nemcovej 32, 04001, Košice, Slovak Republic
Abstract: This paper uses data envelopment analysis (DEA) to compare efficiency estimated according to the traditional revenue model presented by Farrell (1957) and a new revenue model presented by Tone (2002). First, we estimated the revenue efficiency of 114 European banks during the period from 2010 to 2018. The results showed that the average traditional revenue efficiency ranged from 35.74% to 38.85%, and average new revenue efficiency ranged from 37.82% to 54.99%. The results of the analysis showed that banks located in Northern Europe and large banks seem to be most efficient. After the estimation of efficiencies, the nonparametric test for equality of densities was used to test whether two given distributions, estimated nonparametrically via kernel smoothing, differ statistically in terms of the size and geo-scheme for Europe. Based on the results of distribution hypothesis tests, we could confirm our research questions that depended on size, location and applied methodology.
Keywords: commercial banks; DEA; data envelopment analysis; distributional analysis; Europe; Li test; new revenue model; non-parametric methods; software R; traditional revenue model.
International Journal of Monetary Economics and Finance, 2021 Vol.14 No.1, pp.3 - 22
Received: 14 Nov 2019
Accepted: 10 Feb 2020
Published online: 19 Feb 2021 *