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Working Paper

Technical Efficiency in Korea

페이스북
커버이미지
  • 저자 유승민(劉承旻)
  • 발행일 1991/01/01
  • 시리즈 번호 9106
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요약 In this paper, we attempted to answer some of the questions
on the technical efficiency of Korea's manufacturing industries.
We started by clarifying the relationship among the various
concepts of efficiency, and found that our estimates of technical
efficiency are in fact related to factor price efficiency as well.
We employed an empirical model called the stochastic frontier
production function which divides the disturbance term into two
components- one with a symmetric distribution for pure white
noise and the other for technical inefficiency with an asymmetric
distribution. A translog production function was assumed for the
functional relationship between inputs and output, and was
estimated by the corrected ordinary least squared method.

The data used for estimating technical efficiency were found
in the Census of Manufactures for the year 1978. However we
had to refine the raw data in order to exclude those plants and
industries not suitable for our analysis. For this purpose, we
imposed a set of criteria on the raw data, which resulted in the
data set used for estimation. The estimation results necessitated
first dividing the entire range of our sample industries into two
groups, depending on whether or not the empirical distribution of
estimated regression residuals allows a successful estimation of
technical efficiency. For the "success" industries, our analyses
focuses mainly on any robustness and consistency observed from
the relationship between alternative measures of technical
efficiency and also between different specifications of the
production functions, so that we could provide certain qualitative
conclusions on the validity of our estimates.

A tentative conclusion is that the issue is not one of choice
among the four alternative measures of technical efficiency but
one of what specification of the production function is used, that
causes a problem. For this reason, we defer a decisive
conclusion until we find more evidence on the validity of our
efficiency estimates.

A cross-section analysis was also carried out in this paper
to investigate the interindustry determinants of technical
efficiency. It is interesting to observe a certain degree of
similarity as well as differentiation between the cross-section
evidence on Korea's manufacturing industries and that on the
U.S. and Japanese industries, as discussed in detail in chapter
Ⅳ. Another finding that interests us is that the evidence
becomes consistently strong when we use the efficiency
estimates based on gross output instead of value added, which
provides us with an ex post empirical criterion to choose an
output measure between the two in estimating the production
frontier.

The empirical evidence obtained on the interindustry
determinants of technical efficiency can be regarded as a
counterpart to the findings in Caves and Barton (1990) on the
U.S. case and those in Uekusa and Torii (1987) on the Japanese
case. The set of regressors were chosen and hypotheses were
posed in such a way that our result could be made comparable
to these studies. Therefore, one may suspect that we have not
made sufficient efforts to develop hypotheses and to find
evidence on peculiarly Korean determinants of technical
efficiency.

It is not fair, however, to overemphasize the importance of
Korea-specific conditions., if any, in explaining the industry
average of technical efficiency. It has already been confirmed in
the preceding discussions that many of the hypotheses relating
technical efficiency to competitive conditions, heterogeneity, the
occurrence of change and innovation, organizational influences,
size, etc., are applicable to Korean industries to a certain extent.

Nevertheless, it still remains worthwhile to attempt to
propose any new hypothetical assertions in a Korean context.
These include, among others, issues associated with rapid
development and establishments embodying different degrees of
modernization, the effects of the chaebols' (big business
conglomerates in Korea) presence in many industries, and other
Korea-specific institutional conditions. The issues associated with
establishments at different degrees of modernization must be
related to the evidence we found on the effect of size, to the
extent that the degree of modernization varies with the relative
size of establishments. The effects of chaebols' presence are also
partly related to what we found on the effect of organizational
influences.

Likewise, we can say that many Korea-specific institutional
conditions have partly been taken into account by variables
under the categories of competitive conditions, and organizational
and institutional influences. There would exist, however, new
additional variables which capture well the unexplored effects of
Korea-specific institutions, thus presenting an agenda for further
research. The study by Lee(1986) deserves allocated to each
industry, in addition to the familiar ones like effective protection
and economies of scale, in analyzing the technical and allocative
efficiencies of Korean industries.

We did a similar experiment by regressing EFF(GO) and
EFF(VA) on effective rate of protection (EPR1 of EPR2), scale
economies (average shipments of larger establishments
accounting for 50 percent of industry shipments divided by
industry shipments), and subsidized credit (the amount of bank
loans and foreign loans, divided by value added). We only
confirmed the positive and significant effect of scale economies,
i.e., relative size, on technical efficiency, and the other two
explanatory variables revealed insignificant effects.

In chapter V, we conducted exploratory analyses on the
stability of the estimates of technical efficiency in Korea's
manufacturing industries. Though the method of testing stability
employed in this chapter is never a complete one, we could not
find strong evidence that our efficiency estimates are stable over
time. This outcome is both surprising and disappointing. We
could also show that the instability of technical efficiency over
time is partly explained by the way we constructed our
measures of efficiency.

To the extent that our efficiency estimates depend upon the
shape of the empirical distribution of regression residuals, any
movements or the production frontier over time are not reflected
in the estimates, and possibilities exist of associating a high
level of technical efficiency with a downward movement of the
production frontier over time, and so on. Thus, we found that
efficiency measures that take into account not only the
distributional changes, but also the shifts of the production
frontier over time, increase the extent of stability, and are more
appropriate for use in a dynamic context.

The remaining portion of the instability of technical
efficiency over time was not explained satisfactorily in this
paper. Although there could be many ways to look further into
the question of stability, we propose the following approach for
future investigations.

It is strongly suggested that we should develop a
methodology for testing the stability of technical efficiency,
which involves not only devising appropriate testing techniques
but also doing further research on the factors, if any, that
should be controlled when we test for stability. We believe that
the factors to be controlled are any time-dependent components
of the output and inputs that may not be associated with
technical efficiency, but affect the level of our efficiency
estimates. Any factors that are deemed to contribute to changes
over time in the shape of the distribution of plants in the
input-output space, must be considered seriously in explaining
the intertemporal discrepancies of our efficiency estimates. The
interindustry determinants of technical efficiency introduced in
cross-section analysis will become important again in a new
dynamic context.

One last comment goes to the industries missing from our
sample, due to their small numbers of establishments and high
concentration. However, contrary to the suspicion that the
large-scale modern export industries are missing from our
sample, simple calculations reveal that for the year 1979, 124
industries excluded from our sample (31.9% of the entire
manufacturing industries) occupy 20.8% of the total shipments,
19.5% of the total value added and only 5.9% of the total
employment of the Korean manufacturing sector.
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