Measuring Efficiency in the Banking Market. An Empirical Investigation of the Last Decade Performance
33 Pages Posted: 14 Aug 2020
Date Written: June 17, 2020
The purpose of this paper is to suggest some managerial and policy recommendations deriving from the observation of the determinants of the best efficiency levels achieved by the Euro Area banking groups. Referring to the period 2009–2018 a stochastic frontier model, based on the proxy coming from the inter-mediation approach, is employed to quantify the efficiency levels of the banking groups for each single year. Then, with a cluster analysis, we identify the most relevant efficiency determinants of the best practice banking groups. From the analysis, it is clear that the main determinants of the high level of efficiency are linked to a particular business model devoted to the traditional lending activity and to specific managerial choices, such as the achievement of a medium size together with a rational valuation of the number of firms belonging to the same banking group and to suitable cost rationalization policies and liquidity reserves optimization policies. These research findings have great micro and macro implications. Indeed, from our analysis some important reflections emerge regarding managerial and strategic choices and their impact on the results in terms of efficiency of each banking group, as well as some key factors that Regulators might take into account too. In the light of the structural changes that are transforming the physiognomy of the banking system, it is important to analyze the dynamics of efficiency. Few studies focused on such a particular topic after the 2008 Global Financial Crisis. In particular, the period involved is characterized by a strong turbulence within the financial markets and by many economic difficulties. Therefore, it can be considered a period able to represent well the complexity of the banking and financial markets in the last decade.
Keywords: Banking Groups, Efficiency Determinants, Stochastic Frontier Approach, Cluster Analysis, Managerial and Policy Implications
JEL Classification: C58, C23, D24, F65, G21
Suggested Citation: Suggested Citation