The Relationship between Hydropower Energy Consumption and Economic Growth

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Procedia Economics and Finance 38 ( 2016 ) 264 – 270

Peer-review under responsibility of the Organizing Committee of ICEF 2015. doi: 10.1016/S2212-5671(16)30198-8

ScienceDirect

Istanbul Conference of Economics and Finance, ICEF 2015, 22-23 October 2015, Istanbul,

Turkey

The Relationship Between Hydropower Energy Consumption and

Economic Growth

Melike Bildirici

a1

a _Prof.Dr._{Yıldız Technical University}_{, Department of Economics, Istanbul, Turkey}

Abstract

This paper will analyse the relationship between economic growth and hydropower energy consumption. According to the results of the short run causality, there is evidence to support the growth hypothesis in OECD countries with high incomes. There is evidence to support the conservation hypothesis for Brazil, Finland, France, Mexico, the U.S. and Turkey. The unidirectional causality goes from economic growth to energy consumption and suggests that the policy of conserving hydropower energy consumption may be implemented with little or no adverse effects on economic growth in less energy-dependent economies.

Peer-review under responsibility of the Organizing Committee of ICEF 2015.

Keywords: Economic Growth, Hydropower Energy Consumption, ARDL

1.Introduction

Pollution caused by non-renewable energy is an important issue because humans are facing the dual pressure of economic growth and environmental protection (See Zhang et.al: 2011).

Pollution caused by non-renewable energy revealed the dual pressure of economic growth and environmental protection (Zhang et.al 2011). In the late 1980s, the analytical paradigm was altered with concerns about environmentally sustainable economic growth. Sustainable economic growth policies are based on the level, quality and management of renewable and non-renewable natural resources. The states of the environment depends on the level and growth of pollution or waste streams, the environment’s natural assimilation of pollution or through clean up expenditures. As the concept of sustainable development emerged with the rise of green movements, hydropower energy became popular.

1_{Corresponding author. Tel.:+90-212-383-6818.}

E-mail address: bildiri@yildiz.edu.tr

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As electricity demand especially grew, the number and size of non-renewable energy increased. Early hydropower plants were much more reliable and efﬁcient than the non-renewable plants of the day (Baird:2006; Kumar et.all:2011). Unlike non-renewal energy sources, renewable hydropower energy can continuously produce energy (Margeta and Glasnovic. 2011).

According to the report of world bank (WB:2009), hydropower has a powerful contribution to make to regional cooperation and development and to the allocation of increasingly scarce water resources and it is complex and brings a range of economic, social and environmental risks (Schumann et.all R.2010).

This paper, will analyse the relationship between economic growth and hydropower energy consumption. The next section of the study will present studies about hydropower energy consumption and economic growth in the literature. Econometric theory and methodology is identified in the third section. The fourth section consists of the empirical results while the last section includes conclusions and policy implications.

2. The Literature of Energy Consumption and Economic Growth

Kraft and Kraft (1978), Berndt (1978), Akarca and Long (1980), Yu and Hwang (1984), Yu and Choi (1985), and Erol and Yu (1987) were among the first researchers examined the relation between GDP and energy consumption. In pursuit of their work, many paper analysed the relationship between energy consumption and economic growth. As result of these papers, it was obtained the different result on direction of causality. Different results on direction of causality allowed for four hypotheses: 1) the “neutrality hypothesis”; 2) the “conservation hypothesis”; 3) the ”growth hypothesis” and 4) the “feedback hypothesis’’.

The literature about the causal relationship between hydropower energy consumption and economic growth is very little when compared with the number of papers on other forms of renewable energy.

Sadorsky (2009) examined the relationship between renewable energy consumption and real GDP for 18 emerging countries and determined that an increase in real GDP should have a positive impact on renewable energy consumption.

Chien and Hu (2008) used the structural equation modeling approach to show the effects of renewable energy on the GDP of 116 countries. They determined that renewable energy has a positive and significant effect on capital formation and that there are relationships between renewable energy and GDP through the increase in capital formation. Chien and Hu (2007) examined the effects of renewable energy on the technical efficiency of 45 countries in 2001 and 2002. They found that the technical efficiency in OECD countries was higher than non-OECD countries, but non-OECD countries have a higher share of renewable energy.

Solarin and Öztürk(2015) examined the relationship between hydroelectricity consumption and economic growth in seven Latin America countries including Argentina, Brazil, Chile, Colombia, Ecuador, Peru and Venezuela. Their results determined long run bidirectional causality between hydroelectricity consumption and economic growth in Argentina and Venezuela. There is the evidence for long run unidirectional causality from hydroelectricity consumption to economic growth in Brazil, Chile, Colombia, Ecuador and Peru.

Bildirici (2015) investigated the relationship between CO2 environmental pollution, hydropower energy consumption, and economic growth in for Austria, Belgium, Denmark, Finland, France, Germany (1970–2011), Iceland, Italy, Ireland, Portugal, Spain, Sweden, Switzerland (1981–2011), Turkey, and the United Kingdom utilizing the ARDL method in the period from 1961 to 2011. According to her causality results, for Germany the conservation hypothesis determines the unidirectional causality running from GDP to hydropower energy consumption. For Austria, the growth hypothesis suggests unidirectional causality running from hydro energy consumption to GDP. For the United Kingdom, the neutrality hypothesis was determined. For other countries, a bidirectional causality hypothesis was determined.

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3. Data and Econometric Methodology

3.1. Data

The annual data used in this study cover the period from 1980 to 2011 for Brazil, Canada, Finland, France, Japan, Mexico, USA, UK, Turkey, countries with high growth in world, countries:Non-OECD with high growth in world and countries with high Income in OECD countries. Since data did not obtained for all of high growth countries, average value for countries with high growth in world, countries:Non-OECD with high growth in world and countries with high Income in OECD countries was used to analyses

The variables in this study are hydro energy consumption (hec) and real GDP (py). Data are taken as hy=log(hec) and py=log(py). Hydro energy consumption is obtained from Word Bank and Real GDP measured in constant 2005 US dollars comes from the World Bank World Development Indicators (WDI 2012).

3.2. Methodology

In the ARDL analysis, the variables of the model are allowed to possess mixed order of integration. The ARDL model for the standard log-linear functional specification of long-run relationship between variables with OLS estimation technique is presented as,

0 1 1 2 1 1 0 m n i t i i t i t t t i i y D E y I hec G y G hec H '

¦

'

¦

' (1)

where ' and

H

_t are the first difference operator and the white noise term. The bounds testing procedure is based on the joint F-statistic or Wald statistic that tests the null hypothesis of no cointegration. The null hypothesis of no cointegration among the variables in Eq. (1) are H₀ :

G

₁

G

₂ 0 against the alternative hypothesis

1: 1 2 0

H

G

z

G

z .One set of critical values assumes that all variables in the ARDL model are I(0), while the other is calculated on the assumption that the variables are I(1).

In the second step, if cointegration is established, the conditional ARDL long-run model for hec can be estimated as:

m n

0 i t-i i t

i=1 i=0

y=O +

¦

D y +

¦

-hec+u (2)

In the third stage, the short-run dynamic parameters are obtained by estimating an error correction model associated with the long-run estimates:

m n

0 i t-i i t-i 1 t

i=1 i=0

Δy=F +

¦

EΔy +

¦

TΔhec +] ECMt +e (3)

where residuals et is independently and normally distributed with zero mean and constant variance and ECMt-1 is the error correction term.

]

is a parameter that indicates the speed of adjustment to the equilibrium level after a shock.

3.3. Granger Causality

ARDL approach tests if the existence or absences of long-run relationship but it doesn’t determine the direction of causality. It was used the two-step procedure from the Engle and Granger (1987) model to examine the causal relationship between hydroenergy consumption and the real GDP (see Bildirici: 2015; Bildirici and Kayıkcı:2012).

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Vector Error Correction model that was used to analyze the short run relationships between the variables is constructed as follows, 0 1 2 3 1 1 0 m n i t i i t i t t i i y D b y b hec b ECM e '

¦

'

¦

' (4) 0 1 2 3 1 1 0 p q i t i i t i t t i i

hec D d hec d y d ECM e

'

¦

'

¦

' (5)

where residuals, et is independently and normally distributed with zero mean and constant variance and ECMt-1 is the

error correction term resulting from the long-un equilibrium relationship and d’s are parameters to be estimated.

Granger causality can be examined in two ways in the paper. First, short run or weak Granger causalities are tested by H₀ :b₂_i 0 and H₀ :d₂i 0 in Equations (4) and (5). Second, long run Granger causalities are tested from the ECTs in those equations. Long-run causalities are tested by H₀ :b₃ 0 and H₀ :d₃ 0 . Strong causalities are tested by H₀:b₂_i b₃ 0 and

H

₀

:

d

₂_i

d

₃

0

4. Econometric Result

According to the F-statistics, we have enough evidence to reject the null hypothesis of no cointegration at a 1 percent significance level between hydropower energy consumption and economic growth for Brazil, Canada, Finland, France, Japan, Mexico, the U.S., UK, and Turkey, countries with high growth rates, non-OECD countries with high growth rates, and OECD countries with high income.

Table 1: Bounds Testing for Cointegration

Fy(y|hec) Fhec(hec|y)

Brazil 1.8569 6.2448* Canada 1.6029 6.1349* Finland 1.9502 7.6400* France 20.6718* 2.0013 Japan 23.7512* 1.3036 Mexico 1.9371 7.5321* UK 2.5251 0.1145 USA 1.1142 9.8998* Turkey .13309 7.3900* High Income ++ 11.8062* 1.7235

High Income: Non-OECD 10.8380* 1.11425 High Income: OECD 6.8997* 2.1174

This simply means that the computed F-statistics for these models are above the upper bound critical value. Fy (y|hec) was determined for France, Japan, high income: non-OECD and high income: OECD Fhec(hec|y ) for Brazil, Canada, Finland, Mexico, UK, U.S. and Turkey. The results of the ARDL bounds test suggest the rejection of the null hypothesis of no long-run relationship at the 1 percent level of significance.

4.1.Results of Long-Run and Short Run Elasticities

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Table 2. Long and Short Run Coefficients for ARDL

Long Run Coefficients Short Run Coefficients

hec y dhec dY ECM

Brazil -.49381 (3.4143) -.10917 (4.0887) -.22108 (2.8808) Canada -.38044 (8.1172) -.11289 (2.31961) -.29673 (2.9025) Finland -1.2550 (12.9174) -.72376 (3.86519 -.57669 (4.1633) France -.22772 (1.98752) -.013822 (2.2023) -.060699 (3.2916) Japan -.21309 (0.54973) -.015006 (2.41528) -.081952 (2.6108) Mexico -2.2836 (3.4309) -.68919 (1.8724) -.30180 (2.4041) USA -1.1981 (15.4839) -.74160 (4.518) -.61898 (4.9005) Turkey .55197 (2.1475) 1.3168 (1.827) -.31015 (2.9235) High Income -.85292 (-4.7628) - -.25428 (4.3928) -.092471 (-1.983) High Income: Non-OECD -.87436

(-5.1348)

-.25082 (4.3172)

-.099318 (-1.9830) High Income: OECD -1.5541

(-5.3136)

-.56927 (-2.5039)

-.36631 (3.1044) It is given t value in parenthesis

It is possible to forecast the long-run relationships and short-run dynamic effects by using ARDL approach. Table 2 shows the long-run elasticities for the ARDL model.

In Table 2, when it is analysed the relation between hydropower energy consumption to income, it is seen that the income elasticity of hydropower energy demand has a negative sign for Brazil, Canada, Finland, Mexico, USA. For Brazil, Canada, Finland, Mexico, USA, the estimated income elasticities of hydropower energy demand has a negative sign. For Turkey, a positive income elasticity of hydropower energy demand is associated with normal good.

The ECMs in Table 2 indicate that there is a mechanism to correct the disequilibrium between economic growth and hydropower energy consumption. The sign of the coefficient of the error correction term must be negative. The ECMs change between -.092471 and -.61898 to provide stability for the model. An interesting result for ECM was found as <1 % for high income countries and non-OECD high income countries. The error correction term was negatively and statistically significant, showing a low speed of adjustment of any disequilibrium toward a long-run equilibrium state.

4.2. The Results for Granger Causality Test

Table 3 summarizes the causality relationship between hydropower energy consumption and economic growth.

Table 3. Granger Causality

Δy→Δ hec,

Δ hec →Δy, ECT→ Δ hecECT→ Δy

'

y, ECT →

'

hec

'

hec, ECT→

'

y Brazil 51.859 0.90876 16.0012 0.19896 41.0801 35.189 Canada 34.7937 15.4397 11.7713 16.0245 56.6688 55.6278 Finland 18.598 2.4448 21.510 16.7442 85.1171 94.987

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France 92.8843 .45038 .45038 28.7280 48.9276 98.045 Japan 31.3367 173.3739 13.543 34.9095 74.2482 93.1996 Mexico 22.4077 1.2756 14.652 30.0789 68.1345 67.9913 Turkey 14.5076 1.0075 18.972 17.023 47.219 56.843 USA 8.7671 2.1829 21.7467 11.1167 40.61464 26.8758

High Income in World 58.0 2.5076

56.9161 22.7322

58.77254 38.0418

High Income: Non-OECD 1.9354 79.760

29.1598 22.5291

87.0554 110.875

High Income: OECD 1.934 79.760

139.4769 237.1658

91.1517 75.685

The short-run causality results determined that there is unidirectional causality from y to hec for Brazil, France, Mexico and Turkey, countries with high growth and bidirectional causality for Canada, Finland, Japan and US, non-OECD countries with high growth. The short-run causality result found support for the growth hypothesis for non-OECD countries with high income. The long-run causality determined the conversation hypothesis for France, growth hypothesis for Brazil and feedback hypothesis for other countries. According to the strong Granger causality result, there is bidirectional causality for all countries.

5. Conclusion

According to the results of the short run causality, there is evidence to support the growth hypothesis in OECD countries with high income. There is evidence to support the conservation hypothesis for Brazil, France, Mexico Turkey and countries with high growth. The conservation hypothesis suggests that the policy of conserving hydropower energy may be implemented with little or no adverse effects on economic growth, such as in a less energy-dependent economy. Therefore this is not the theoretically expected outcome for developing countries.

According to the long-run causality result, there is evidence to support bidirectional causality for all countries except Brazil and France. Hydropower energy consumption and economic growth are complementary and an increase in energy consumption stimulates economic growth, and vice-versa.

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