Existing
literature related to efficiency measurement and productivity analysis of banks
is swarmed with the input-output classification of banks based on using
accounting conventions. This usage varies from paper to paper. No two research papers are in consensus as to which
classification should be used. This present work, however, uses the
input-output classification of banks based on Barnett’s generalized model of
production for financial intermediaries originally proposed in Barnett (1987)？[1]. This
model is based on economic theory definitions of inputs and outputs of a bank.
Using this classification, the paper applies Data Envelopment Analysis to US
banks during 2006-2016. This new methodology seeks to resolve and fix the issue
of lack of consensus regarding which inputs and outputs to use for productivity
analysis of banks. Furthermore, a standardized way of measuring productivity
across banks is developed which can be used all over the world. This is
accomplished by using the Malmquist Index of Productivity which is a tool used
under Data Envelopment Analysis. The paper further establishes the connection
of this tool with Barnett’s generalized model of production for financial
intermediaries. Results indicate very high efficiency levels for US banks even
post financial crisis. The reason for this performance is the cleansing of the
financial system as unhealthy banks either left the scene or were merged.
Better risk management, cost management and efficiency of structure of funding
are some other reasons for high efficiency.
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