Swiss Cantonal Banks: A DEA Efficiency and Productivity Analysis

Abstract

This paper applies a data envelopment analysis (DEA) to study the efficiency and productivity changes in the Swiss cantonal bank sector in the period 2006-2014. The efficiency analysis is conducted by applying the production input-oriented DEA variable returns to scale model in a three-stage procedure. The productivity is studied by estimating a DEA-based Malmquist Productivity Index (MPI) that provides evidence of increasing productivity growth on average for the sector in the studied period. The main source of productivity growth as per the components of the Banker, Charnes and Cooper (BCC) MPI model is related to a frontier-shift (technological innovation) rather than to improvements in the technical efficiency. The decreasing average DEA scores in the post-global financial crisis period of 2008-2014 further support this finding. In the second stage of the efficiency analysis, the environmental factors influencing the productivity growth are analysed by conducting a general method of moments (GMM) regression. The results provide evidence of a positive and statistically significant relationship between the new annual residences per canton and technical efficiency. In the third stage, the environmental variables from the second-stage regression are included within the constraints of the first-stage DEA model as proposed by Ray [1]. The third-stage DEA scores support the evidence of slightly decreasing average post-global crisis technical efficiency. The overall average technical efficiency in the Swiss cantonal banking sector, however, remains at a relatively high level in the studied period.