Production frontiers and efficiency measures : concepts and applications
Abstract
Two major criticisms have been levelled against the statistical approach to
measuring production efficiencies. First, the sampling distributional assumptions
artificially imposed on the one sided-error term used to characterize inefficiency
are somewhat restrictive. Moreover, alternative distributional assumptions can
lead to substantially different results for the estimated technical efficiencies; making
it difficult to provide an economic and practical justification of the choice of
a particular distribution. Within the spectrum of inefficiency sampling distributions
proposed in the literature, the half- or truncated normal has received a
relatively wider applications than others such as gamma and exponential. Quite
often the choice of the distributions is based on ease of empirical estimation.
Second, the specification of the stochastic frontier production function in the
statistical approach assumes that the effects of technical inefficiency on input
productivity (or elasticity) are the same for each input with the resultant neutral
shift of the frontier production function from the ‘average’ and firm-specific
realized production functions. In other words, the frontier and the other production
functions have identical slope coefficients (input elasticities) but different
intercepts so that they merely represent neutral shifts from one another.
While some attempts have been made recently in response to the first criticism,
the second one appears to have so far attracted very little attention in the
production frontier and efficiency literature. Thus the primary objective of this
thesis is to develop an alternative conceptual framework to production efficiency measurement that aims at obviating both of these criticisms. Empirical illustrations
based on survey agricultural data sets from Sri Lanka, China and India are
provided to show the workability of the proposed procedures.
The thesis format is as follows. Chapter 1 gives an overview of production
efficiency analysis with more emphasis on technical efficiency measurement.
Chapter 2 establishes for subsequent applications, the modelling, estimation and
testing procedures of linear models with heterogeneity in both intercepts and
slopes. Chapter 3 discusses and empirically demonstrates a method of measuring
firm- and input-specific technical efficiency within a varying coefficients production
function framework. Chapter 4 extends this method to a panel data context
and discusses the measurement of temporal firm-specific technical efficiency
and shifts over time of the frontier production functions (that is, technological
progress). Chapter 5 focusses on total factor productivity growth over time. It
explains a method to decompose the sources of total factor productivity growth
into technological progress and changes in technical efficiency within the framework
of the varying coefficients frontier production function approach discussed
in the preceding chapters. In chapter 6, a primal method based on a varying
coefficients production function is developed for estimating allocative efficiency.
An empirical illustration is provided. The concluding chapter highlights some of
the issues not explicitly addressed in the concluding final section of each chapter
and also points out some of the problems, mainly of empirical nature, that may
be encountered. Some directions for further investigations are briefly suggested.
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