Renewable Energy Consumption and Economic Growth

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results of causality test indicate unidirectional causality from economic growth to renewable energy consumption in 4 countries: India, Iran, Pakistan, and Syrian ...
American Journal of Scientific Research ISSN 1450-223X Issue 35 (2011), pp.146-152 © EuroJournals Publishing, Inc. 2011 http://www.eurojournals.com/ajsr.htm

Renewable Energy Consumption and Economic Growth: The Case of 7 Asian Developing Countries Majid Mahmoodi Young Researchers Club, Zahedan Branch Islamic Azad University, Zahedan, Iran E-mail: [email protected] Elahe Mahmoodi Young Researchers Club, Zahedan Branch Islamic Azad University, Zahedan, Iran Abstract This paper examines the long-run and causal relationship between renewable energy consumption and economic growth for 7 Asian developing countries over the period 1985 to 2007 years. The ARDL-Bound test proposed by Pesaran et al. (2001) employed for investigate logn-run relationship and then modified version of the Granger causality test proposed by Toda and Yamamoto (1995) used for examining the causal relationship. The results of causality test indicate unidirectional causality from economic growth to renewable energy consumption in 4 countries: India, Iran, Pakistan, and Syrian Arab Republic. Results of Bangladesh and Jordan support bi-directional causality between renewable energy consumption and economic growth, but for Sri Lanka we cannot found evidence of causality. Keywords: Renewable Energy Consumption, Economic Growth, Causality JEL Classification Codes: C32, Q42, F43

1. Introduction Energy plays substantial role in economic, hence Relationship between energy consumption and economic growth is an important issue for economists and many studies worked in this topic. In recent year’s renewable resources used as alternative for non-renewable energy source, therefore the numbers of energy economic literatures focused on relationship between renewable energy and economic growth. The rapid increase in price of other energy source and concerns about the environmental consequences of carbon emissions are factors to the consumption of renewable energy. According to the International Energy Outlook (2010), renewable energy is the fastest growing world energy source, Total generation from renewable energy increase by 3% annually. Several econometric methods used by various studies to investigate the relationship between renewable energy consumption and economic growth. A large number of studies on the topic of renewable energy and economic growth carried by Apergis and Payne, in follow we show the results of these studies. Sadorsky (2009a) examined the relationship between renewable energy consumption and income for a panel of 18 emerging countries by estimating two empirical models. Cointegration results

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show that increase in real income have a positive impact on renewable energy consumption. In the long term, a 1 percent increase in real GDP per capita increase renewable energy per capita consumption between 3.93 and 3.45 percent. Apergis and Payne (2010a) studied the relationship between renewable energy consumption and economic growth for OECD countries during 1985 to 2005 years. Results of panel cointegration test indicate long run relationship between real GDP, renewable energy consumption, real gross fixed capital formation, and the labor force with positive coefficients. Evidence from panel VECM causality indicates bidirectional causality in short and long run. Apergis and Payne (2011a) employed a panel error correction model for examine the relationship between renewable energy consumption and economic growth for six Central American countries. Panel cointegration test showed a long run relationship and results of panel causality indicate bidirectional causality between renewable energy consumption and economic growth. Apergis and Payne (2011a) believe this results display that renewable energy serve as a catalyst for the modernization of the energy sector in meeting sustainability objectives specified by policy makers. The study of Sadorsky (2009b) estimates a model of renewable energy consumption for the G7 economies over the 1980 to 2005 years, by employing panel data. With respect to results of estimates, increases in real GDP per capita and CO2 per capita are found to be major drivers behind per capita renewable energy consumption. Apergis and Payne (2010b) examined the causal relationship between renewable energy consumption and economic growth for a panel of 13 Eurasia countries over the 1992 to 2007 years by employing a panel VECM framework. Empirical finding indicate bidirectional causality between renewable energy consumption and economic growth in both the short run and long run. Chien and Hu (2008) studied the effect of renewable energy on GDP for 116 countries by applying Structural Equation Modeling approach. Empirical evidence indicates that renewable energy has a positive and significant effect on capital formation but not has a significant effect on trade balance. They confirm the positive relationship between renewable energy and GDP through the increasing of capital formation. Apergis and Payne (2011b) studied the relationship between renewable and non-renewable energy consumption and economic growth for 80 countries during the 1990 to 2007 period by using panel VECM causality framework. The results indicate bidirectional causality between renewable and non-renewable energy consumption and economic growth. In addition, there is bidirectional causality between renewable and non-renewable energy, which show substitutability between the two energy sources. Chien and Hu (2007) examined the effects of renewable energy on the technical efficiency of 45 OECD abd non-OECD countries over the 2001 to 2002 period. The results show that increase in renewable energy consumption can improve technical efficiency, but increase in non-renewable energy decrease technical efficiency. The technical efficiency in OECD countries is higher than non-OECD countries, but non-OECD countries have a higher share of renewable energy. Apergis et al. (2010c) examined the causal relationship between carbon dioxide emissions, nuclear energy consumption, renewable energy consumption, and economic growth for 19 developed and developing countries over the 1984 to 2007 period by employing panel VECM causality. Empirical finding indicate that nuclear energy unlike renewable energy, plays an important role in reducing carbon dioxide emissions. Also, results show bidirectional causality between renewable energy consumption and economic growth. The study of Menegaki (2011) investigates the causality between economic growth and renewable energy for 27 European countries over the 1997 to 2007 years. Empirical model include final energy consumption, greenhouse gas emissions and employment as additional independent variables. The results of causality indicate there is not relationship between renewable energy and economic growth.

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Apergis and Payne (2011c) examined the relationship between renewable and non-renewable electricity cosumption and economic growth for 16 emerging market economies. The results of pedroni panel cointegration tests indicate there is a relation between economic growth, renewable and nonrenewable electricity consumption, real gross fixed capital formation and the labor force. Finally, panel causality indicates bidirectional causality from economic growth to renewable electricity consumption in the long run. However, in this paper we examine the relationship between renewable energy consumption and economic growth in 8 Asian developing countries. The rest of this paper is organized as follows: Section 2 discussed data and methodology. Section 3 present empirical results and finally conclusion presented in Section 4.

2. Data and Methodology 2.1. Data Annual data of renewable energy consumption and real GDP over the 1985 to 2007 years, obtained from World Development Indicators and Energy Information Administration for 7 Asian developing countries includes: Bangladesh, India, Iran, Jordan, Pakistan, Sri Lanka, and Syrian Arab Republic. Renewable energy consumption (RE) defined as total renewable electricity net consumption in millions of kilowatt hours and real GDP measured in constant 2000 US dollars. Variables measured in natural logarithms. 2.2. Methodology 2.2.1. ARDL-Bounds Test This paper employed the recently developed Autoregressive Distributed Lag (ARDL) bounds test proposed by Pesaran et al. (2001) to examine the long run cointegration relationship between renewable energy consumption and economic growth. The ARDL approach, at first was present by Pesaran and Shin (1999) and then developed by Pesaran et al. (2001). An ARDL model is a general dynamic specification, which uses the lags of the dependent variable and the lagged and contemporaneous values of the independent variables, through which the short-run effects can be directly estimated, and the long-run equilibrium relationship can be indirectly estimated. The ARDL cointegration approach has numerous advantages in comparison with other cointegration methods. ARDL-Bunds test does not require knowledge of the order of integration of variables. This approach is not sensitive to the sample size and also ARDL technique provides unbiased estimates of the long-run model. The bounds test is based on F-statistic (or Wald statistic) used to test the significance of the lagged levels of the variables in a first-difference regression. The asymptotic distributions of these statistics are non-standard under the null hypothesis that there exists no level relationship between the dependent variable and the included repressors, irrespective of whether the regressors are I (0) or I(1). Two sets of asymptotic critical values are provided: One set assuming that all regressors are I (1), and another set assuming that they are all I (0). These two sets of critical values provide a band covering all possible classifications of the regressors into I(0), I(1) or mutually cointegrated. If the computed test statistic exceeds the upper critical value, then there is evidence of a long run relationship, if below the lower critical values, we cannot reject the null hypothesis of no cointegration and if it lies between these two bound, inference is inconclusive. The ARDL unrestricted error correction model (UECM) can be expressed as follows: n

n

GDPt  α 0  1GDPt 1   2 REt 1   3i GDPt i   4i REt i   t i 1

i 0

n

n

i 1

i 0

REt  β 0  β1 REt 1  β 2GDPt 1  β3i REt i  β 4i GDPt i  t

(1) (2)

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2.2.2. Toda-Yamamoto (1995) Approach This paper employed a modified version of Granger causality test proposed by Toda and Yamamoto (1995) for testing the causality between renewable energy consumption and economic growth. Toda and Yamamoto (1995) procedure based on augmented VAR system and a Wald test statistic that asymptotically has a chi square distribution. In Toda and Yamamoto (1995) approach, the augmented (k+dmax)th order of VAR estimated where k is the lag length of the system and dmax is the maximum order of integration. The Toda-Yamamoto model can be specified as following bi-variate VAR system: k d max k d max (3) GDP  c   GDP   GDP   RE   RE   t



0

1i

k

REt  c1  1i REt i  i 1



t i

i 1

t j

2i

j  k 1 d max



j  k 1

2i



t i

1i

i 1

k

d max

i 1

j  k 1

REt  j  1i GDPt i 



2i

t j

1t

j  k 1



2i

GDPt  j   2t

(4)

In Eq. (3), the null hypothesis of renewable energy consumption does not Granger cause GDP can be expressed as H0: γi = 0 ∀i ; similarly in Eq. (4), the null hypothesis of GDP does not Granger cause renewable energy consumption can be expressed as H0: φi = 0 ∀i.

3. Empirical Results 3.1. ARDL-Bounds Test Results The results of ARDL-Bounds test for null hypothesis of no long-run relationship between renewable energy consumption and economic growth are reported in table 1. Table 1:

ARDL-Bounds Test

Country/Dependent Variable F- Statistic W-Statistic Bangladesh 78.982** 112.965** GDP 3.611* 7.222* RE India 67.820** 135.640** GDP 3.134 6.269 RE Iran 4.968** 9.936** GDP 1.974 3.948 RE Jordan 13.428** 26.857** GDP 1.110 2.220 RE Pakistan 58.778** 117.557** GDP 2.669 5.338 RE Sri Lanka 54.536** 109.072** GDP 3.909* 7.818* RE Syrian Arab Republic 9.129** 18.258** GDP 1.290 2.581 RE Critical Values Lower Bound Upper Bound Lower Bound Upper Bound 5% 3.524 4.646 7.049 9.293 10% 2.637 3.514 5.274 7.029 Note: ** and * denote statistical significance at the 5% and 10% levels, respectively.

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When the real GDP is dependent variable, computed statistic is higher than upper bound at 5% significant for all seven countries, which means existence of cointegration. But when the renewable energy consumption is dependent variable the null hypothesis of no cointegration rejected only for Bangladesh and Sri Lanka, which means for other five countries we cannot find evidence of cointegration. 3.1. Toda-Yamamoto (1995) Causality Results Causality test carried out by using Toda-Yamamoto (1995) procedure. The first step in TodaYamamoto approach is to finding the maximum order of integration of the variables (dmax), for this purpose we need to perform unit root test. The results of Augmented Dickey-Fuller unit root test presented in table 2. Table 2:

ADF Unit Root Test

Country/Variable Level 1st difference Bangladesh 3.639 ** (2) GDP -1.150 (1) -6.835 *** (0) RE India 2.338 (0) 3.014 ** (0) GDP -0.169 (0) -4.351 *** (0) RE Iran -4.011 ** (2) GDP -1.470 (0) -3.190 ** (0) RE Jordan -3.748 ** (3) GDP -4.512 *** (0) RE Pakistan -2.164 (3) -2.859 * (0) GDP -1.751 (0) -4.089 *** (0) RE Sri Lanka -2.995 (3) -3.531 ** (0) GDP -2.227 (0) -3.969 *** (2) RE Syrian Arab Republic -2.464 (0) -5.820 *** (0) GDP -1.367 (3) -4.239 ** (2) RE Note: ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively. Optimum lags are in parenthesis.

We cannot reject the null hypothesis of unit root for levels of real GDP in India, Pakistan, Sri Lanka, and Syrian Arab Republic, while for other countries real GDP are stationary in levels. Renewable energy consumption is become stationary after first difference for all countries except Jordan. The results of unit root test indicate that maximum order of integration (dmax) for Jordan is zero and for other six countries is one. The next step in Toda-Yamamoto approach is to determining the optimal lag length (k), Akaike Information Criteria (AIC) and Hannan-Quinn (HQ) criteria indicate k=2 for Iran and Syrian Arab Republic, k=3 for Jordan and k=1 for other countries. After investigate integration of series and finding optimal lag, now we can perform TodaYamamoto causality test. The results of Toda-Yamamoto causality test reported in table 3.

Renewable Energy Consumption and Economic Growth: The Case of 7 Asian Developing Countries Table 3:

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Toda-Yamamoto (1995) Causality Test

From GDP to RE From RE to GDP χ2 Statistic P-Value χ2 Statistic P-Value Bangladesh 8.258 0.016 *** 4.161 0.124 * India 4.993 0.082 * 0427 0.807 Iran 4.613 0.112 * 0.022 0.999 Jordan 8.780 0.032 ** 30.271 0.000 *** Pakistan 4.426 0.109 * 2.607 0.271 Sri Lanka 3.476 0.175 1.499 0.472 Syrian Arab Republic 12.187 0.006 *** 1.426 0.699 Note: ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively. Country

The results of causality test indicate unidirectional causality from economic growth to renewable energy consumption in 4 countries: India, Iran, Pakistan, and Syrian Arab Republic. Results of Bangladesh and Jordan indicate bi-directional causality between economic growth and renewable energy consumption. For Sri Lanka we cannot find causality in any directions.

4. Conclusion The purpose of this paper is to investigate the causality relationship between renewable energy consumption and economic growth for 7 Asian developing countries (Bangladesh, India, Iran, Jordan, Pakistan, Sri Lanka, and Syrian Arab Republic) over the 1985 to 2007 years by employing ARDLBound test and Toda-Yamamoto (1995) approach. The results of ARDL-Bound test support existence of cointegration for all sample countries, when the real GDP is dependent variable. But, when the renewable energy consumption is dependent variable we can found cointegration only for Bangladesh and Sri Lanka. The results of unit root test indicate that maximum order of integration (dmax) for Jordan is zero and for other six countries is one. Also, lag length selection performed by using AIC and HQ criteria. Finally Toda-Yamamoto approach performed for all countries and indicates unidirectional causality from economic growth to renewable energy consumption for India, Iran, Pakistan, and Syrian Arab Republic and bi-directional causality for Bangladesh and Jordan, but for Sri Lanka we cannot found causality relationship between renewable energy consumption and economic growth.

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