Journal of Sustainable Development July, 2008
27
The Dynamic Optimization Model of Industrial Structure
with Energy-saving and Emission-reducing Constraint
Kun Dong
Department of Economic
Dalian University of Technology
Dalian 116023, China
E-mail: dong-kun@sohu.com
Abstract
In recent years, because of China's rapid economic growth, the contradiction between energy consumption,
environmental pollution and economic development has become acute increasingly. Energy-saving and
ejection-decreasing has become an important strategy target in China's "11th Five-Year Plan". The research on the
industrial structure optimization of China, should be given full consideration to all current energy and environmental
problems. The industrial structure optimization model in this paper containing energy-saving and ejection-decreasing,
shows its simulation results that through optimization of the industrial structure it would be realized that meeting energy
reduction demand, and also to maintain high economic growth rate.
Keywords: Optimization of industrial structure, Dynamic optimization, Energy-saving and emission-reducing
1. Introduction
China has made a tremendous achievement on economy since the reform and opening, the Gross of National Product
has been growing, and the people's standard of living has been markedly improving. Optimization of the industrial
structure aiming at economic growth enable the economic resources flowing from the low relatively productivity to
high relatively productivity of industries, and which will also drives the total economy efficiency growing, and
promotes the national economy. However, in recent years, at the same time of rapidly growing in economy, the conflict
between economy growing with energy consumption and environmental pollution has been become increasingly
vigorous, and therefore energy-saving and emission-reducing have been become a strategy target in China's "11th
Five-Year Plan". As thus, the study up on multi-objective optimization of China's industrial structure has been with
important theoretical and practical significance.
This paper constructs a dynamic optimization model of industrial structure with energy-saving and emission-reducing
constraints based on "11th Five-Year Plan"; optimizes the industrial structure to resolve the current problems of China's
economic development, energy and environmental issues.
2. Model Design
2.1 Objective Function
In this paper, the industrial structure optimization model continues to target for economic growth, and aims at meeting
the energy-saving and emission-reducing constraints of "11th Five-Year Plan" on the binding nature of energy-saving
emission reduction targets, while achieving higher levels of economic growth. So here set economic growth targets for
the total GDP maximization in the planning period, that is,
1
max ( ) '( )
T
t
f
=
= ∑t t t tx e x - A x
where 1 2( , , , ) 't t ntx x x= Ltx stands for the industry's gross output vector of period t, stands for direct consumption
coefficient matrix, and (1,1, ,1) '= Le stands for unit column vector.
Vol. 1, No. 2 Journal of Sustainable Development
28
2.2 Constraint Conditions
2.2.1Energy Consumption Constraints
tC ≥ t tc 'x
where 1 2( , , , ) 't t ntc c c= Ltc stands for energy consumption of the industry’s unit gross output of period t, and
stands for the indices of energy consumption of period t.
2.2.2 Environment Pollution Constraints
t
t
t
W
G
S
≥
≥
≥
t t
t t
t t
α 'x
β 'x
γ 'x
where 1 2( , , , ) 't t ntα α α= Ltα , 1 2( , , , ) 't t ntβ β β= Ltβ , 1 2( , , , ) 't t ntγ γ γ= Ltγ stand for pollution emission of the
industry’s unit gross output of period t, and tW , tG , tS stand for the indices of pollution emission, in wastewater,
waste gas and waste solid.
In addition, the economic operation is decided by inherent connection of the economic variables. The actual economic
operation mechanism decides the structure of model. So the model should include the economic operation constrains as
follows:
2.2.3 Dynamic Input-output Balance Constrains
1 1 2( )= t tt t t t t + tx A x + B x - x + y + y
where ( )ij n nb ×=tB stands for investment coefficient matrix, ijb stands for investment of the industry “i” to increase
the unit output of industry “j”, 1( )t t + tB x - x stands for capital formation vector, 1ty stands for final consumption
vector, and 2 ty stands for net export vector.
2.2.4 Capital Formation Constrains
1( ) ( ) ( )tt fs s+ ≥t t t t t + te' x - A x e'B x - x
where ts stands for saving rate, tfs stands for the GDP proportion of foreign capital inflow. The constraints show
that investment capital of next period composes of national savings and foreign capital inflow.
2.2.5 Consumer Demand Constrains
1(1 ) ( )ts− ≥ tt t te' x - A x e'y
2.2.6 Net Exports Constrains
2
( )
t
f
s ≥ −
t
t t t
e' x - A x e'y
2.2.7 Production Capacity Constrains
1 1 2 1q q≥ ≥t - t t -x x x
where 1 21 0q q> > > . The constraints will limit the industry's rapid growth or recession. First, the short-term industry
production capacity will not change too much; secondly, the excessive growth or recession of a particular industry will
lead to considerable changes in industrial structure, thus cause fluctuations in economic growth.
2.2.8 Nonnegative Constraints
1, 0≥ttx y
3. Data Processing
Industry classification of this paper is consistent with the 17 sector input-output table of the National Bureau of
Statistics. The data of model are from the “China Statistic Yearbook,” 2005 as annual base period. According to
historical data, the main parameters in model are set as follows:
0 0.43ts s= =
Journal of Sustainable Development July, 2008
29
0
0.05
tf f
s s= =
1 0.8q = , 2 1.2q =
According to the goal of "11th Five-Year Plan", we set tC 4% annual increase and tW , tG , tS 2% annual decline. In
addition,
0tA = A and 0tB = B need to be calculated according with the relevant data.
3.1 Direct Consumption Coefficient Matrix
Direct consumption coefficient is very important in the input-output model, particularly dynamic input-output model. It
reflects economic and technical relations among industries, and changes with economic environment, technical level,
etc. So, direct consumption coefficient of different periods is different. In practice, because of the lag of input-output
tables, the input-output analysis usually assumes that the industrial input-output relations have maintained a long period
of unchanged. Clearly, it is in contradiction with actual economic changing. Therefore, Direct Consumption Coefficient
matrix needs to be revised effectively.
Based on the RAS method, we construct diagonal matrix and representing the fabrication and substitution effects,
and set up the modification model of direct consumption coefficient matrix as follows:
05
05
02
,
05 02
05 05 05
min log( )
s.t.
ij
ij
i j ij
a
a
a
⎧⎪⎪⎪⎨⎪⎪⎪⎩
∑
A = RA S
A x = v
This model uses data of the gross output ( 05x ) and added value ( 05v )to revise direct consumption coefficient matrix,
makes a breakthrough to the continuity assumptions in changing of the relationship between input and output, and can
use known data farthest.
3.2 Investment coefficient matrix
In static input-output model, the investment as a final demand is exogenous variables, which dissevers production
targets and production capacity, can not accurately reflect the expand production of social product. Dynamic
input-output model makes variables exogenous by introducing investment coefficient matrix, and reflects the intrinsic
link between reproduction and productive investment. In the dynamic input-output analysis and application of the
model, the investment coefficient matrix is the key role; the accuracy of input-output analysis depends largely on
investment coefficient. We determine investment coefficient matrix as follows:
1
1
t t
t
t t
i ij
ij n
j ij
j
s a
b
x a
+
=
∆=
∆ ∑
where
ti
s∆ stands for the investment-increment of industry “i” of period t. The input-output model relates the static
and dynamic input-output model, and reflects the relationship between the investment allocation and the
output-increment.
4. Simulation Results
Table 1 gives the simulation results. In 2010 China's GDP will reach 29.72 trillion, in 2015 will rise to 46.64 trillion, in
2020 continued to rise to 71.85 trillion, with an average annual growth rate to reach 9-10%. Total energy consumption
and pollutant emissions are scheduled to meet the binding targets, in 2020 alone than the total energy consumption in
2005 increased by 75.1%, while the GDP increased by nearly three times. The three major industrial pollutant emissions
are achieved a slight decline, from 2010 to 2015 the average annual industrial waste solid discharge fell 5.6%, from
2015 to 2020 the average annual decline 6.1%, emission of pollutants has been effectively controlled.
From the changes of added value proportion of three industries, in 2010, the proportion of three industries were 19.3%,
33.7% and 47.0%, compared with 2005 the proportion of primary industry rose 6.8 percentage point decline in the
proportion of secondary industry 13.8% proportion of the tertiary industry rose 7.1 percentage points. By 2015, the
primary industry, the proportion of secondary industry continues to decline, respectively, 10.4%, 29.8%, while the
tertiary industry rose to 59.8. 2020, the proportion of primary industry dropped to 3.0%, the secondary industry
accounted for by small pick-up , To 32.8%, the proportion of the tertiary industry continued to rise to 64.2%, the
three-industry structure is close to the level of developed countries.
Table 2 gives the simulation results of added value structure of 17 sectors. In 17 sectors, increased proportion of larger
Vol. 1, No. 2 Journal of Sustainable Development
30
industries are Textile, Sewing, Leather and Furs Products; Construction; Transportation, Postal and Telecommunication
Services; Real Estate, Leasing and Business Services; Other Services. And the remaining nine sectors largely decline in
the proportion. We can see that the 10 sectors, only Textile, Sewing, Leather and Furs Products increased proportion,
and 3 sectors have increased the proportion in the tertiary industry, and the increase in larger, industrial structure
softening trend is very clear.
This trend of industrial structure indicates that China's industrial structure in recent decades through the development
and adjustment, the overall already in the middle stage of industrialization, economic growth too dependent on the input
of capital and resources, high-value, low-power the tertiary industry development has been slow and the increasingly
serious environmental pollution, the development of sustainable capacity is not strong. In China's industrialization
process, the main driving force behind economic growth in the industry are mainly from the secondary industry, while
the secondary industry is the largest energy consuming industries, but also has brought more emissions. Therefore, the
energy of the emission reduction targets to achieve, is bound to accelerate the development of the tertiary industry, in
general, the tertiary industry in achieving rapid development, we do not need too many resources into, is in need of
more human capital and technical input . Although the reform and opening up, the Chinese Government has been
vigorously develop the tertiary industry, tertiary industry in the proportion of the national economy has maintained an
upward trend, from 1978's 24.2% rise in 2005 to 39.9%; However, from this model to optimize results, The goal of
reducing emissions and energy requirements, and the tertiary industry in the national economy as the proportion is still
low.
5. Conclusion
To change China's current economic development in the high energy consumption, high emission problem, we should
start from industrial structure optimization, optimize the industrial structure by reasonable policies and measures, the
realization of China's economic growth mode from the side of the extensive growth resources to the partial knowledge
Technology-intensive growth change. China's industrial structure optimization of the overall trend should be "softening",
that is, in the industry in the development of tangible products and resources and other production factors reduce the
growing role and knowledge, technology, services and information such as the role of soft factors of production
increasing, In various industries in the rapidly increasing input. High-tech industries and the continuous development of
the tertiary industry, especially the rapid development of information industry, China's economy should become the
future development trend. China's industrial structure optimization, to control the growth, speed up and eliminate
backward production capacity, improve the promotion of industrial restructuring policies and measures to actively
promote energy restructuring. On the one hand we must vigorously develop the tertiary industry, to improve the
professional division of labor and social efficiency, with the focus on positive developments in the production of
services; meet people's needs and to facilitate the life of the masses as the center and enhance the development of life
and services; On the other hand we must vigorously Development of high-tech industry, adhering to a new road to
industrialization and promoting the upgrading of traditional industries, improving high-tech industries in the proportion
of industries.
References
Dolezal, & Vaclav. (1995). Optimization of general nonlinear input-output systems. Nonlinear Analysis, 4, 441-468.
Karen R Polenske. (1995). Leontief's spatial economic analyses. Structural Change and Economic Dynamics, 3,
309-318.
Kurz Kalmbach, & Heinz D Peter. (1995). Micro-Electronics and Employment: A Dynamic Input-Output Study of the
West German Economy. Structural Change and Economic Dynamics, 2, 371-386.
Liew J Chung. (2000). The dynamic variable input-output model: An advancement from the Leontief dynamic
input-output model. The Annals of Region Science, 4, 591-614.
Pardalos. (2000). Recent developments and trends in global optimization. Journal of Computational and Applied
Mathematics, 124, 209-228.
Stone R. (1961). Input-Output and National Accounts. Paris: OEEC.
Journal of Sustainable Development July, 2008
31
Table 1. Industrial Structure and the Main Macroeconomic Indicators (100 million Yuan, %)
2005 2010 2015 2020
Gross Output 496791 665584 888193 1255387
GDP 183868 297150 466433 718471
Proportion of Primary Industry 12.5% 19.3% 10.4% 3.0%
Proportion of Secondary Industry 47.5% 33.7% 29.8% 32.8%
Proportion of Tertiary Industry 39.9% 47.0% 59.8% 64.2%
Growth Rate of Gross Output 6.0% 5.9% 7.2%
Growth Rate of GDP 10.1% 9.4% 9.0%
Energy Consumption 199926 243240 295939 350440
Industrial Wastewater Discharge 145344 131379 118757 107347
Industrial Waste Gas Discharge 265203 239723 216690 195871
Industrial Waste Solid Discharge 1490 1347 1007 734
Table 2. Changes of Industrial Added Value and the Proportion of 17 Sectors (100 million Yuan)
2005 2010 2015 2020
Added
value
%
Added
value
%
Added
value
%
Added
value
%
Agriculture 23070 12.5 57407 19.3 48322 10.4 21839 3.0
Mining and Quarrying 10318 5.6 9133 3.1 4563 1.0 1495 0.2
Foodstuff 7499 4.1 9012 3.0 6037 1.3 1978 0.3
Textile, Sewing, Leather and Furs Products 5887 3.2 14649 4.9 35548 7.6 51637 7.2
Other Manufacturing 3693 2.0 1221 0.4 400 0.1 131 0.0
Production and Supply of Electric Power, Heat
Power and Water
2082 1.1 682 0.2 335 0.1 834 0.1
Coking, Gas and Petroleum Refining 8692 4.7 5842 2.0 1943 0.4 637 0.1
Chemical Industry 2950 1.6 967 0.3 317 0.1 104 0.0
Building Materials and Non-metal Mineral Products 9874 5.4 15740 5.3 21428 4.6 20636 2.9
Metal Products 19442 10.6 12335 4.2 4170 0.9 1366 0.2
Machinery and Equipment 6795 3.7 5272 1.8 1727 0.4 566 0.1
Construction 10134 5.5 25216 8.5 62746 13.5 156132 21.7
Transportation, Postal and Telecommunication
Services
10836 5.9 25352 8.5 32279 6.9 30681 4.3
Wholesale and Retail Trades, Hotels and Catering
Services
17728 9.6 9630 3.2 3156 0.7 1034 0.1
Real Estate, Leasing and Business Services 11156 6.1 27760 9.3 69077 14.8 171885 23.9
Banking and Insurance 6307 3.4 8738 2.9 7034 1.5 2305 0.3
Other Services 27406 14.9 68194 22.9 167353 35.9 255211 35.5
本文档为【The Dynamic Optimization Model of Industrial Structure with energy saving and emission-reducing】,请使用软件OFFICE或WPS软件打开。作品中的文字与图均可以修改和编辑,
图片更改请在作品中右键图片并更换,文字修改请直接点击文字进行修改,也可以新增和删除文档中的内容。
该文档来自用户分享,如有侵权行为请发邮件ishare@vip.sina.com联系网站客服,我们会及时删除。
[版权声明] 本站所有资料为用户分享产生,若发现您的权利被侵害,请联系客服邮件isharekefu@iask.cn,我们尽快处理。
本作品所展示的图片、画像、字体、音乐的版权可能需版权方额外授权,请谨慎使用。
网站提供的党政主题相关内容(国旗、国徽、党徽..)目的在于配合国家政策宣传,仅限个人学习分享使用,禁止用于任何广告和商用目的。