DEA methodologies for assessing the efficiency profiles of commercial banks under heterogeneity conditions
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Date
26/11/2019Item status
Restricted AccessEmbargo end date
26/11/2020Author
Carrales Escobedo, María Skarleth Atenea
Metadata
Abstract
Since the publication of the seminal paper by Charnes, Cooper and Rhodes in
1978, where the conventional CCR model of Data Envelopment Analysis
(DEA) has been proposed, DEA as a field has substantially evolved both
methodologically and in terms of applications. So far, efficiency and
productivity studies in the banking sector proved to be amongst the most
popular application areas. The popularity of DEA in this field, amongst others,
is due to its unique features such as its non-parametric nature, it benchmarks
against the best practice performers rather than the average performers. It
allows one to identify targets for improvement; it does not need any functional
specification of the relationship between inputs and outputs, and provides a
variety of efficiency measures most suitable for a variety of applications.
Moreover, it provides a wide range of models to perform analyses at the
aggregate level and the detailed level. In addition, DEA models allow one to
perform both Static and Dynamic analyses.
In this thesis, DEA is used to assess the efficiency profiles of commercial
banks under heterogeneity conditions. First, a new DEA-based analysis
framework with a regression-based feedback mechanism is proposed to deal
with the particular features of the UK banking sector, where regression
analysis provides DEA with feedback that informs about the relevance of the
inputs and the outputs chosen by the analyst. Unlike previous studies, the DEA
models used within the proposed framework could use both inputs and
outputs, only inputs, or only outputs, which proved necessary with UK data.
Second, to the best of our knowledge, no attempt has been made to investigate
the relative efficiency of operating environments of banks. This thesis aims at
filling this gap by analysing the efficiency of HSBC in different operating
environments or countries over time. The choice of a single bank; namely,
HSBC, is motivated by isolating the operating environment effect on efficiency
and thus avoiding any bias that would result from the relative efficiency of
different banks within the same operating environment. From a methodological
perspective, this analysis is performed using a variety of framework; namely,
A four-stage analysis is performed with Static black box SBM, Dynamic SBM,
Network SBM, and Dynamic-Network SBM DEA frameworks. Overall, this
thesis contributes to both the DEA field, through its methodological
contributions, and the banking sector, through its application of the
methodological contributions in assessing banks’ efficiency profiles.