A dynamic network DEA model for accounting and financial indicators: A case of efficiency in MENA banking

Abstract

Middle East and North Africa (MENA) countries present a banking industry that is well-known for regulatory and cultural heterogeneity, besides ownership, origin, and type diversity. This paper explores these issues by developing a Dynamic Network DEA model in order to handle the underlying relationships among major accounting and financial indicators. Firstly, a relational model encompassing major profit sheet, balance sheet, and financial health indicators is presented under a dynamic network structure. Subsequently, the dynamic effect of carry-over indicators is incorporated into it so that efficiency scores can be properly computed for these three substructures. The impact of contextual variables related to bank ownership, its type, and whether or not it has undergone a previous merger and acquisition process is tested by means of a stochastic non-linear model solved by differential evolution, which combines bootstrapped Simplex, Tobit, Beta, and Simar and Wilson truncated regression results. The results reveal that bank type, origin, and ownership impact efficiency levels differently in terms of profit sheet, balance sheet, and financial health indicators, although the impact of culture and regulatory barriers seem to prevail at the country level.