A two‐stage inverse data envelopment analysis approach for estimating potential merger gains in the US banking sector

Abstract

Mergers and acquisitions are mainly due to financial and technological innovations but could also be due to changes in the structure of the economy, which alters the optimal production functions of banks. Banks that seek to be operationally efficient would focus more on expanding their asset size, in the face of bad loans, leading to the acquisition of less efficient banks. This paper develops two‐stage inverse data envelopment analysis (DEA) models for estimating potential gains from bank mergers for the top US commercial banks. The results show additional intermediate and final outputs at different predefined target levels of technical efficiencies.