Read, Laura Elizabeth (1998) A comparison of data envelopment analysis and stochastic frontiers as methods for assessing the efficiencies of organisational units. PhD thesis, University of Warwick.

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Abstract

This thesis gives an overall view of the two most commonly used
approaches for measuring the relative efficiencies of organisational
units. The two approaches, data envelopment analysis (DEA) and
stochastic frontiers (SF), are supposedly estimating the same
underlying efficiency values but the natures of the two methods are very
different. This can lead to different estimates for some, or all, of the
units in an analysis.
By identifying the nature of these differences this work shows that it is
possible to gain some insight into the nature of the underlying data and
to say more confidently which of the two estimates is closer to the true
efficiency for individual units.
In order to investigate the differences between the methods across
different facets of the technology two important dimensions are chosen.
Firstly differences across scale size are investigated. It is shown how it
is possible to define a measure of scale size in both the single output
and multiple input and output cases. This measure of scale size can
then be used to split the technology into regions of differing scale size
enabling, for example, tests for the true nature of returns to scale in
DEA. The measure of scale size developed in multiple dimensions
necessitates a method for estimating an homothetic, constant returns to
scale function.
Differences between the approaches across input mix are also
investigated. These differences may highlight the abilities of the
methods to correctly identify the elasticity of substitution between the
inputs.
The results of the comparisons between the methods are summarised.
This summary gives possible reasons for differences which may be
found between the results of the two approaches, and an indication of
what the nature of the estimates may be to the true efficiency values.
An algorithm is then developed for using a comparison of the results
from the two methods to help to identify the better estimates.

Item Type:	Thesis (PhD)
Subjects:	H Social Sciences > HA Statistics H Social Sciences > HF Commerce
Library of Congress Subject Headings (LCSH):	Data envelopment analysis, Industrial efficiency, Organization
Official Date:	September 1998
Dates:	Date Event September 1998 Submitted
Institution:	University of Warwick
Theses Department:	Warwick Business School
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Thanassoulis, Emmanuel
Extent:	xx, 272 leaves
Language:	eng

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