Author

Dading Li

Date of Award

6-1991

Degree Type

Thesis

Degree Name

Doctor of Philosophy (PhD)

Department

Economics / Economic Policy

Supervisor

A. Leslie Robb

Co-Supervisor

M.W. Luke Chan

Committee Member

Dean Mountain

Abstract

Pursuing efficiency is a fundamental characteristic of
economic activity. correspondingly, efficiency measurement
seems an eternal interest of production economists. The
present dissertation is a comparative study of alternative
technical efficiency estimation methods. Two recently
developed methods based on different methodologies, namely,
data envelopment analysis (DFA) and the stochastic frontier
approach (SF) are studied. In this dissertation we review the
production and efficiency structure defined by modern
production theory. Based an earlier works of Afriat, we
discuss a set of propositions underpinning the non-parametric
programming approach (or DEA). Further, we demonstrate the
relationship between non-parametric and parametric production
frontiers as references for technical efficiency measurement.
We also explore the corresponding relationships between
various versions of the DEA model and their implications
regarding returns to scale properties. On the side of the SF approach, we work out a conditional estimation model to
extract technical efficiency from a composite error structures. The main empirical contribution is a simulation stUdy that is carried out to examine the capabilities of both approaches under various circumstances. In the first set of experiments
we examine the performances of the two methods under assorted
efficiency profiles, by which we describe the industry's
efficiency distribution. Then, in a second set of experiments
we investigate the performance of the two methods when the
experimental data has different returns to scale prcperties.
Finally, we test the robustness of the two models in regards
to varied magnitudes of random noise. Our results indicate
that though the SF model often leads the competition by a
small margin in our experimental environment, both methods
have reasonable performances.


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