2011 China located International Conference on Information Systems for Crisis Response and Management

Empirical Research on the Relationship between Energy Consumption and Economic Growth in Heilongjiang Province

WANG Si, DENG Li-hong, ZHOU Wen-tong, ZHU Zheng-yuan School of Economics and Management, Harbin Engineering University, P.R.China, 150001

Abstract: Energy is the essential material foundation of economic and social development for the subsistence and development of human beings. Nowadays, various countries are suffering from energy crisis which restricts economic development. This paper is based on the energy consumption and GDP data of Heilongjiang province from 1980 to 2009 of using unit root test, co integration analysis and Granger causality test, aiming at validating the relationship between Heilongjiang energy consumption and economic growth. Empirical analysis shows that energy consumption can be strongly driven by economic growth, however, energy consumption plays a relative small role on promoting economic growth, and then this paper puts forward countermeasures and suggestions.

Keywords: Cointegration test, Economic growth, Granger causality co integration, Primary energy

consumption

1 Introduction

In the context of global warming, "low-carbon economy" has become a global hot spot based on low power consumption and low pollution. On December 7th in 2009, "Copenhagen" reached in Copenhagen climate summit had brought a significant impact on various countries' formulating the national environmental policies [1] [2]. Chinese Government has presented the target that, until the year 2020, Chinese carbon dioxide emissions will decline about 40% to 45% per unit of GDP in comparison with carbon dioxide emissions in the year 2005, in view of economic development planning and sustainable development strategy. Various countries and regions are working on decreasing energy intensity and increasing energy saving, aiming at reducing the emission of greenhouse gases, which has brought new challenges to Heilongjiang province whose mainstay is

This research is supported by the Fundamental Research

Funds for the Central Universities (No. HEUCFlI0911);

Also, it is supported by Key Project of Science and Technology

Department of Heilongjiang Province of China ( No.

gzlOd201) .

978-1-4577-0368-3/11/$26.00 ©20111EEE 76

heavy industry [3]. Based on the status of Heilongjiang province, this

paper has done an empirical analysis on the primary energy consumption, labor force , capital and economic growth of Heilongjiang province in the way of unit root test, cointegration analysis and Granger causality test.

2 Energy consumption in Heilongjiang province

2.1 Overview of the status of energy consumption in

Heilongjiang Province

Heilongjiang is a high energy consumption province in China. In 2007, the province's total energy consumption is 93.740 million tons, up 7.4 percent over the previous year. Among them, the primary energy consumption is 79,579 million tons, up 3.9 percent over the previous year; coal consumption 52,505 million tons, up 5.2%; consumption of crude oil is 234.05 million tons, an increase of 1. 9%; natural gas consumption is 3.285 million tons, up 3.6%; water consumption of 384 million tons, down 24.7%. Coal-based energy consumption accounts for a large proportion of energy consumption, and it can be divided into industrial coal consumption and residential coal consumption. Tn Heilongjiang's energy consumption structure, the proportion of coal consumption dropped to 98.3% in 1952 to 66% in 2007, but still up to the top[4][5]. The main reason is that more than 70% of coking coal resources are in the Northeast China, concentrated in Jixi, Hegang, Shuangyashan and Qitaihe areas of Heilongjiang. And the province's coal reserves account for 70% of the province. Heilongjiang will hold the coal resource-advantage in the next two decades.

Oil Consumption in Heilongjiang province occupies a decisive position in the whole consumption structure, which stabilized at about 30% of total primary energy consumption over the years. In 2007, crude oil consumption is 23.405 million tons accounting for about 4.5% of nationwide oil consumption.

To the consumption of regional structure , the

natural gas is original based. concentrated in the southwest, northeast and northwest territories, namely,

November 27 -29,2011

Sichuan province, Heilongjiang province, Liaoning province and Xinjiang province, which account for more than 80% of consumption. Natural gas consumption in Heilongjiang province in 2007 is equivalent to 3.285 million tons of standard coal, accounting for about 3.5% of nationwide natural gas consumption. However, relative to the huge reserves, the current utilization of natural gas in Heilongjiang province is significantly lower, mainly due to the natural gas consumption in Heilongjiang province, mostly in civilian areas, less consumption. Natural gas consumption can be expanded to industrial, business and other fields.

Three-quarters of China's total consumption is industrial electricity. Heilongjiang industrial electricity consumption has occupied about 70% of the total community. Because of the strategy of revitalizing old

industrial base , Heilongjiang province has taken a series

of effective measures to construct the Harbin-Oaqing-Qiqihar Industrial Corridor and the eastern coal base ,which became a new growth point for the adjustment of industrial structure, industry concentration, and speeding up the industrial development[61. At the same time, electricity consumption has increased steadily. However, electricity consumption in Heilongjiang province is mainly coal-based consumption, and water consumption has a very low proportion. In 2007, water and electricity consumption accounted for only 0.5% of total energy consumption, equivalent to 384,000 million tons of standard coal. Hence there is a huge development potential in hydropower development[71.

3 Analysis on the relationship between energy consumption and economic growth in Heilongjiang Province

3.1 Model selection

To estimate the proportion between energy consumption and economic growth, this paper build the equation according to 3-factor production function by

Liu Chaoming, Zeng Sheng and Liu Bo (2006) [81:

y; = f(KI' Lt' NY;) (1)

Y is real GDP;K is real capital stock; L is total workforce; NY is primary energy consumption. Assume that Y, K, L and NY satisfy the Cobb-Douglas production

function, that is:

(2)

A, " and are unknown parameters. Make it

linearized by logarithmic transformation, then take the

log of both sides and take the time T for derivative:

dGDP 1 = a dK J.-+!3 dL �

+ dNY_l_

dt GDP dt K dt L r dt NY (3)

Add constant term and error term which meet the

77

standard assumptions:

f1GDP 11K M NY -- =C+ a

- +!3-+r-+Ut (4) GD� Kt Lt N�

The data of GOP, capitals, labor and primary total energy consumption are from 1980 to 2009 in Heilongjiang Statistical Yearbook. GOP and capital stock are in real terms (allowing for infiation)[81[91.Primary energy include raw coal, crude oil, natural gas and hydropower. Primary energy consumption is represented by standard coal equivalent.

The real GOP( 1978=100 )is based on the year 2000.

From figure 1, we can see that since 1980, the real GOP

has been going up steadily [101. And the unit is one hundred million yuan. This unit is used in all charts in this paper.

(100 million yuan) 9000.0 8000.0 7000.0 6000.0 5000.0 4000.0 3000.0 2000.0 1000.0

0 0 1111111111111111 ntIfIttIl 'ib� 'ib'" � 'ibio 'ib'" PI� PI'" PI'>< Plio PI'" �� �'" � �G �'" � ,"I ,"I � ,"I ,c; ,c; � ,c; ,c; ",'5 ",'5 ",'5 ",'5 ",'5

Fig. 1 Real GDP in Heilongjiang province

The base-period price of gross captial formation of

the real capital (1978= 1 00) is the price of the year 2000.

The gross fixed capital formation in the year 2000 is 922.4 billion yuan. We use the depreciation rate of 6%

per year, assumed by Young (2000) [Ill. With method of the perpetual inventory (PIM), this paper estimated

China's capital stock. In the course of modeling ,

according to K/GOP=3. 72 in the year 1978, we assume that the capital stock and regional gross product are still

at this rate. According to the Statistical Yearbook, we can get regional gross product each year in Heilongjiang

province, and then figure out the capital stock of the preceding year[121. We can see the results in figure 2.

(100 million yuan) 20000.0

15000.0

111111111111111 IOtttflllll 0 0

10000.0

5000.0

'ib� 'ib'" � 'ibG 'ib'" PI� PI'" PI'>< PIG PI'" �� �'" � �G �'" ,"I ,"I ,"I � ,"I ,c; ,c; � ,c; ,c; ",'5 ",'5 ",'5 ",'5 ",'5

Fig. 2 Capital stock in the past years in Heilongjiang province

The data of the workforce in Heilongjiang

province this paper use is from 1980 to 2009.

Population bonus is a decisive factor in sustainable economic growth. Figure 3 shows that over the past

decades, there are abundant cheap labor resources adding

dynamics to the economic development.

(10000 persons) 2000

1500

1000

500

o

\ c,'t>\ C,'t>'],\:0't>\ c,'t>\ C,'t>'t>\:0C,\ c,c,\ c,c)\ c,c,\ C,C,\ClCl\ClCl\ClCl\ClCl\ClCl't>

Fig. 3 Workforce in the past years in Heilongjiang province

3.2 Data stationary test

This paper takes the log of all the variable data to eliminate possible phenomenon of heteroscedasticity, then does the research on stationarity of sample sequence by way of augmented Dickey-Fuller test, also called ADF test.

11

Mt = a + j3Xt-1 + I B;Xt_1 + £t

;=1 (5)

When tested, we reject the null hypothesis. It means that is a stationary sequence.

Tab. 1 ADF Test Results

Thresho Thresho Threshol Concl ADF Id 1% Id 5% d 10% us IOn

LOG(G 0.309 -4.3943 -3.6121 -3.24307 unstab DP) 200 09 99 9 Ie DLOG( -4.69 -4.3393 -3.5875 -3.22923 GDP) 4177 30 27 0 stable

-2.99 -4.3239 -3.5806 -3.22533 un stab LOG(L) 4118 79 23 4 Ie DLOG( -3.57 -3.6998 -2.9762 -2.62742 L) 3014 71 63 0 stable LOG(K 0.323 -4.4407 -3.6328 -3.25467 unstab ) 938 39 96 1 Ie DLOG( -5.02 -4.4407 -3.6328 -3.25467 K) 0188 39 96 stable LOG(N -1.95 -4.3098 -3.5742 -3.22172 un stab Y) 1563 24 44 8 Ie DLOG( -4.36 -3.6891 -2.9718 -2.62512 NY) 1771 94 53 1 stable

Table I reports the results of the ADF test for unit roots based on time series analysis of sample spacing. At the confidence level 95 %, hypothesis can be rejected. Each of the original sequence is in the stable after a

first-order difference, and they are all entire sequence of

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the first-order single. In other words, regression analysis can not be used

for data processing to avoid losing a lot of important information in metadata. The data ,meetind the conditions of co-integration analysis ,are carried out EO cointegration test as well as the Johansen multiple cointegration te[13l. 3.3 EG Cointegration Test

Johansen cointegration test is based on the VAR model. Firstly, we must establish the VAR model between variables, aiming at determining the lag time of variable[14l. According to Ale criterion and Schwarz information criterion, VAR model of the maximum lag order we selected is 5 after repeated calculation and analysis. Variable should be in linear trend and cointegration equation has the form of the intercept.

Tab. 2 Johansen cointe�ration test results

Hypothesiz ed Trace 0.05 No. of Eigenvalu Critical CE(s) e statistic value

47.85613 None * 0.992978 204.5574

29.79707 At most 1 * 0.887773 80.58904

15.49471 At most 2 * 0.621466 25.90828

3.841466 At most 3 0.062821 1.622030

Tab. 3 Johansen cointegration test results

Hypothesiz Max-Eige � n O.M No. of Eigenval Critical CE(s) ue Statistic value

27.58434 None * 0.992978 123.9684

21.13162 At most 1 * 0.887773 54.68076

14.26460 At most 2 * 0.621466 24.28625

3.841466 At most 3 0.062821 1.622030

Prob.* *

0.0000

0.0000

0.0010

0.2028

Prob.* *

0.0000

0.0000

0.0010

0.2028

Table 2 and table 3 reports the results of EG bivariate test for cointegration. The four test hypothesis were listed by Eviews, among them which reject the null are marked with "*". Trace test and maximum eigenvalue tests show that there are three co integrating relationships between variables.

After a standardized test, the estimating value of cointegration coefficient was given by Johansen test. What we care about is the cointegration coefficient which is under the assumption of one co integration relationship. LOGGDP -1.986453 * LOGL -0.879838 * LOGK + 0.395441 * LOGNY = 0 (6)

Tab.4 Johansen cointe�ration test results

Normalized cointegrating coefficients (standard error In parentheses)

LOGGDP LOGL LOGK LOGNY

1.000000 -1.986453 -0.879838 0.395441

(0.01763) (0.00257) (0.00841 )

From the Table 4, we can see that there is a long-term stable proportion relationship in sample.

Secondly, we use the Dickey-Fuller to test the smoothness of the error term, in order to verify the existence of cointegration. The co integration relationship does exit on condition that error term is smooth and steady[15][16]. And the error term can be used as explanatory variables of differential equations. Test results are listed as below. Table 5 and figure 4 reports the results that there is co integration relationship between GDP, primary energy consumption, labor and capital stock.

Tab. 5 Test Resu Its of Error Term

E C

Augmented Dickey-Fuller statistics

M -4.319208

test 1% level

5% level

10% level

-1.6 -2.65 -1.95 0957 3401 3858 1

Conc lusio n

Stabl e

.04 ,---------------------,

.02

. 00

-.02

-.04

-.06 -t--.��..,...,��..,...,��..,..__r��_,__r��.,..,_�---j 1980 1985 1990 1995 2000 2005

Fig. 4 Error Term

Based on the analysis above, we use differential equations to establish error correction model (ECM) to analyze impact of the short-term fluctuations in energy on GOP growth[17]. Test results are listed as below.

Tab. 6 results of error correction model

Variable Coefficient Std. Error t- Statistic Prob.

C 0.041375 0.015472 2.674123 0.0133

DLOG(K) 0.523214 0.080828 6.47321 0.0000

DLOG(L) 0.280484 0.191953 1.461214 0.1569

DLOG(NY) 0.009856 0.081544 0.12087 0.9048

ECM (-1) 7.0IE-05 0.000532 0.131735 0.8963

79

Model without difference shows the long-term equilibrium relationship, while the model after difference reflects the decision of short-term fluctuations[18]. Among them, the error term reflects the influence on the short-term fluctuations by long-run equilibrium.

3.4 Granger causality test Cointegration only indicates the relationship

between economic growth and energy consumption, which is failed to indicate the direction of causality [19]. In order to further analyze it, we need to do Granger causality test of GOP and NY. The results are in Table 7.

Tab. 7 Granger causality test of GDP and NY F-statist Probabili

Hypothesis lC ty LOGNY does not Granger Cause

LOGGDP 0.30988 0.8989 LOGGDP does not Granger Cause

LOGNY 0.99670 0.4547

Significance level expresses the probability of acceptance for null hypothesis. The smaller the number is, the stronger the ability of explaining the dependent variable by dependent variable is[20] [21]. Table 7 reports the results that Granger cause of NY constituted by GOP is significant, while the opposite is less significant. It means that primary energy consumption is not the Granger cause of GDP. Through the analysis, we can see that, from 1980 to 2009, there is one-way causality from energy consumption to economic growth: economic growth has resulted in an increase in energy consumption, while the increasing energy consumption does not promote the growth of economic aggregate .

4 Policy recommendations

From the analysis above we may reasonably come to the conclusion that there has been a close relationship between the economic development and

energy consumption in Heilongjiang province. Besides, the goal of economic development can be achieved without using substantial consumption of

primary energy. Therefore in the environment of advocating a low-carbon economy, we should improve

energy efficiency, develop clean energy and exploit

new energy sources not to affect economic development.

Firstly, technological innovation should be

implemented and the role of the government control should be developed to accelerate the pace of

industrial restructuring. Heilongjiang should effectively change the economic growth points from

the perspective of long-term economic and social

development: the industrial structure adjustment should be on the basis of technical innovation. Shorten the cycle of technical renovation and elimination of

backward technology as far as possible use of

advanced technology and equipment. Tn addition,

governments at all levels shall guide and support the development of low-power, high efficiency and

high-tech industry, appropriate incentives to promote the adjustment of industrial structure from the direction of capital, energy-intensive to

technology-intensive. Secondly, strategy of energy diversification and

optimize energy consumption structure should be

implemented. Through making great efforts to develop clean energy, green energy resource and proper import

of oil, gas, etc., the government shall gradually implement energy optimization strategy and take the

path of energy diversification. Tn addition,

Heilongjiang should speed up the adjustment of energy consumption structure and improve the

proportion of high energy pace: resting on resource-advantage in Heilongjiang province, determine the developing direction and function

positioning of different regions. Transform the heavy

use of the limited coal, oil and gas into other energy sources such as solar, biomass, wind and other

renewable energy sources, which is of great

significance of sustainable development on the economic and environment in Heilongjiang province.

Thirdly, new energy efficiency standards should

be enacted and conservation activities of resources

should be carried out. For example, enact the fixed

standards of product consumption and advanced energy-saving standards on the key industry such as Steel industry, non-ferrous metal industry and

petroleum chemical industry which can provide an institutional guarantee. Tn addition, through carrying

out a wide range of energy and resource conservation

activities by mobilizing various social forces in Heilongjiang province, we should establish a scientific

and rational consumer attitude and make efforts to create a resource-saving and environment-friendly

society.

5 Conclusion

Supported by statistics, based on the stability test and cointegration test, the in-depth study has been

done on the causal, dynamic and quantitative

relationship between energy consumption and economic growth through the Granger causality test. Thus, we get a conclusion as below:

Granger causality test shows that energy consumption is the Granger cause of GDP, but the

opposite does not hold in Heilongjiang province. It means that there exists the causal relationship between

economic growth and the energy consumption. That is,

during 1980--2009 years, economic growth has resulted in an increase in energy consumption, while

the increasing energy consumption does not promote

80

the growth of economic aggregate. This kind of

cointegration relationship between energy and GDP is also verified in this way. Therefore, Heilongjiang's

economy development doesn't depended on the

energy consumption. It can be predicted that for a long period of time, this kind of economy will not change

fundamentally. From now on, during a very long

period of time, our government should focus on

clarifYing the relationship between economic growth and energy consumption, develop the labor-and

capital-intensive economy vigorously. And we should be open-minded on energy issues and search for new

economy growth.

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