Use of Stochastic Production Frontiers for Measuring Learning Efficiency: Evidence from a State University in Sri Lanka

Type Conference Paper - First International Economic Research Conference of the Sri Lanka forum of university economists
Title Use of Stochastic Production Frontiers for Measuring Learning Efficiency: Evidence from a State University in Sri Lanka
Author(s)
Publication (Day/Month/Year) 2012
City Colombo
URL http://slfue.org/images/SLFUE_downloads/2012/2012.8.Human_Development.pdf
Abstract
Efficiency of State education is a significant research issue since it consumes a
substantial amount of public money in developing countries. Therefore, investigating
the efficiency of State higher education systems is essential in the context of
accountability of State funds and Sri Lanka is no exception. Recently, the performance
of Sri Lankan State university education has been the subject of considerable scrutiny.
The system has undergone significant changes over the years, in the process of
improving undergraduates? performance. However, undergraduates? performance in
social sciences stream is still lagging behind the accepted standards (World Bank,
2009). One explanation is that students and educational institutions are not utilising
resources efficiently. There may be productive or technical inefficiencies in teaching or
in the learning processes. The emphasis of this study is the latter since no such studies
has been carried out for Sri Lankan.
Farrell (1957) provided the definition and conceptual framework for technical
efficiency (TE) which refers to failure to operate on the production frontier. Stochastic
Frontier Analysis (SFA) is one of the techniques1 widely used for the estimation of TE
which is used in this study. Aigner et al (1977), Kumbhakar and Lovell (2000), and
Battese and Coelli (1988, 1995) demonstrated the development of SFA and its uses in
estimating TE. The basic idea behind the SFA is that the error term is composed of two
parts: (i) systematic component that captures the effect of measurement error, statistical
noise, and (ii) one-sided error component that captures the effects of inefficiency (Knox
and Lovell, 2000). This study utilises Battese and Coelli?s (1995) approach which
estimate the stochastic frontier and inefficiency effect model simultaneously.
Chakraborty (2009) is a significant application of this model for the education sector.

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