THE IMPACT OF COAL-ELECTRICITY LINKAGE POLICY ON THE COST
EFFICIENCY OF CHINA’S THERMAL POWER PLANTS
Na Duan, Tianjin University, Phone + 86-13821213380, E-mail: duanna1206@tju.edu.cn
Jun-Peng Guo, Tianjin University, Phone +86-13602053107, Email: guojp@tju.edu.cn
Bai-Chen Xie, Tianjin University, Phone +86-13312188917, E-mail: xiebaichen@tju.edu.cn
Overview
Under the dual track mechanism of ‘market coal and plan electricity’ in the 1990s, China’s power price cannot be
timely adjusted according to the changes of fuel prices. The power plants formulate their production plans to achieve
more economic beneifts other than to meet the power supply. Under some cases, the more theremal power the plants
produce, the bigger financial loss they may face when the price of coal jump up dramatically. As a result, this
mechanism leads to economic loss for the society and the decrease of energy efficiency. Power shortage and surplus
occurred frequently in past decades.
The government put forward the policy of coal electricity linkage to overcome this dilemma in 2004. To
measure the the price effect and to find the source of efficiency changes, this study evaluates the cost efficiency of
1137 thermal power plants in China during the period from 2002 to 2011 from both static and dynamic perspectives.
The results may provide some constructive suggestions for the further power policy reforms related to the
distribution and retailing sections.
Methods
The data envelopment analysis method based on the directional distance function approach may present not only the
input surplus but also the ouput deficit information. We employ this approach to measure the cost efficiency of the
sample plants over the study period. In order to avoid the arbitratiness and subjectivity, the directional vectors are
generated endogenously rather than determined by solving the models in advance.
In order to make the evaluation results more completive and objective, we construct a productivity index to
estimate the efficiency changes over time. Then we decompose the productivity indexes into technical efficiency
change, pure technological change and scale change to explore the critical driving forces for the productivity
improvements.
The number of decision making units (DMUs) may affect the efficiency results significantly. Boostrap is one
approach developed to decrease the influence of extreme DMU. This study employs the double bootstrap regression
approach to study the influences of such covariates as plant scale, vintage, utilization rate and captive or public
consumption on the efficiencies.
Results
We employ the double boostrap method to simulate the scenario when the policy of coal-electricity linkage was
firmly carried out. Compared with the actual situation, the power plants performed better under the simulated
scenario from the static perspective, comparatively, and their corresponding bootstrapped total factor cost
efficiencies changed slightly. This demonstrates that the policy has a lag effect and it may influence the efficiencies
greatly.
The plants are classified into state owned plants and non-state owned plants, plants with big installed capacities
and small ones. Although in some cases, the non-state owned thermal plants performed better, there is no significant
efficiency difference between them and the state owned ones under most situations. However, the plants with bigger
installed capacity always performed better than smaller ones as they can always take use of advanced technology. It
may indicate that the influence of coal-electricity linkage policy vary greatly among different kinds of thermal power
palnts during the study period.
Compared to the traditional approach, the resluts of double bootsrapped method changed slightly and there are
less extreme values observed. However, the estimated results estimated by traditional directional distance functions
vary from one directional vector to another. Under the double boostrapped approach, the direction vectors are
generated endogenously, which may avoid the infulence of decision makers. Comparatively, the traditional approach
may lead to subjective results, under which the directional distance function is predetermined, and we have no way to
get rid of the influence of the extreme inputs and outputs.
Conclusions
The bootstrap procedure is indispensable because the original results may only be the artifacts of sampling noise. To
some extent, the boostrap approach enrichs the application of the DEA method and its extended models as the results
are less dependent on the sample units.
Compared to the predetermined directional vector approach and the traditonal boostrap method, the proposed
double bootstrapped endogenous optimal vector method makes the estimated productivity efficiency perform better
in objectivity, feasibility, and differentiation.
Coal-electricity linkage gained its sucess in the short term. It not only is conducive to straighten out the
relationship between coal and power prices, but also helps enhance the cost efficiency of the plants. Combined with
the policy of ‘promoting the big and suppressing the small’, it may further improve the management efficiencies of
power plants
The advanced techonolgy played an important role in pushing the production frontier upward. The plants with
bigger installed capacities performed better than the smaller ones under almost the all the conditions. Therefore, to
introduce new technologies and increase research and development inputs will be an effective way to improve the
cost efficiency .
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