Effects of financial development, economic growth and trade on electricity consumption: Evidence from post-Fukushima Japan

Effects of financial development, economic growth and trade on electricity consumption: Evidence from post-Fukushima Japan

Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084 Contents lists available at ScienceDirect Renewable and Sustainable Energy Reviews jour...

619KB Sizes 4 Downloads 122 Views

Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

Contents lists available at ScienceDirect

Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

Effects of financial development, economic growth and trade on electricity consumption: Evidence from post-Fukushima Japan Abdulkadir Abdulrashid Rafindadi a,n, Ilhan Ozturk b a b

Faculty of Social Sciences, Department of Economics Usmanu Danfodiyo University, Sokoto, Nigeria Faculty of Economics and Administrative Sciences Cag University, Adana -Mersin karayolu, 33800 Yenice, Turkey

art ic l e i nf o

a b s t r a c t

Article history: Received 11 May 2015 Received in revised form 12 July 2015 Accepted 19 October 2015

This study examines the long-run and short-run effects of financial development, economic growth, export, imports and capital on the Japanese energy predicaments as a result of the foregoing energy crisis in the country. To ensure a robust outcome, the study applied the extended Cobb–Douglas production function and used time series data from 1970 to 2012. Following to this, structural break unit root test, ARDL bounds test approach to cointegration and the Johansen cointegration test were applied. In addition, the VECM Granger causality framework was used in determining the causal relationship between the variables. The findings of the study establish that, in the long-run a 1% rise in financial development, economic growth, exports and imports in Japan will exert a significant pressure on the Japanese electricity consumption by 0.2429%; 0.5040%; 0.0921% and 0.2193% respectively. However, capital was found to decline energy consumption in all material respect. In the short-run, the study discovered how a 1% rise in the dynamics of financial development, economic growth, exports and imports to add to the Japanese electricity predicaments by 0.2210%; 0.5840%; 0.0521% and 0.2031% respectively. The existence of the feedback relationship between most of the variables was discovered, while, economic growth, exports, imports, and trade openness were found to Granger-cause electricity consumption. The study advocates the adoption of massive but competitive renewable energy system in Japan. How it should be done and why it should be done are carefully set by this study. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Financial development Growth Energy consumption Cobb–Douglas

Contents 1. 2. 3. 4.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Data and methodological framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results and discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Exports model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. The VECM Granger causality analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusion and policy implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction Multiplicity of energy economics literature have established that electricity consumption is a crucial element to national n

Corresponding author. E-mail addresses: aarafi[email protected] (A.A. Rafindadi), [email protected] (I. Ozturk). http://dx.doi.org/10.1016/j.rser.2015.10.023 1364-0321/& 2015 Elsevier Ltd. All rights reserved.

1073 1075 1076 1077 1080 1080 1081 1083

productivity. It is also argued that electricity consumption facilitates sustainable economic growth and ensures the continuity of national prosperity irrespective of the direction of causality. Following to this, the fast-growing need among nations for a significant rise in sustainable economic growth is increasingly becoming a competitive challenge considering the damages created by the periods of recent financial crises. In addition to that, the need to attract and sustain the huge volume of international

1074

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

investment inflow through FDI and other international investment mechanism constitute the cornerstone of every nation. This is because; investment without sufficient, efficient and sustainable energy is of no significant value. Equally important is the fact that the old existing economic literature which emphasized for countries to pursue international trade has now been condemned due to the recurring negative influence of unprecedented financial crisis Tang et al. [40]. Following to this, electricity is seen as a multifaceted development carrier in a modern global economy that has the embodiment and the characteristics of cementing and sustaining human welfare, investment, productivity, exports and imports. These factors in turn accelerate the tides of national economic growth and prosperity. In spite of key economic damages afflicted by the recent financial crisis to the Japanese economy which rendered the second global economic giant to drop to the third position, yet, Japan in 2011 was afflicted by a natural disaster. The 9.0 earthquake in Fukushima Daiichi was reported to have led to the shutdown of 8 nuclear plants. This development resulted in a considerable loss of electricity production, physical and human capital. The combined effect of this phenomenon caused additional stress on the country’s economic growth wherewithal. According to the Japanese ministry of trade and industry [17], the damages caused by this disaster were approximated to range between USD 195 billion to USD 305 billion. The latter amount (USD 305) was estimated to be equivalent to the quadruple cost of damages caused by Hurricane Katrina’s $81 billion, and almost equivalent to Greece’s GDP, and two times the GDP of the New Zealand Nanto et al. [26]. These are apart from insurance claims estimated at the tune of USD50 billion. While the cost of nuclear pollution and contaminants were to date not confirmed. Additional substantiation provided by the IHS Global Insight [14] pointed out that economic growth in Japan was envisaged to have a significant boost to an estimated level of 0.5%, after the 2007/2008 financial crisis; unfortunately, the Fukushima disaster overturned these expectations to a 0.0% level of economic growth in March 2011. These myriads of economic traumas plunged the Japanese economy into deep recession, making the economy to contract by 3.6%. Following this development, and to show that the level of economic recession had not improved much up to 2014, the Economic Watch [7] reported in the third quarter of the same year, that Japan was expecting 0.4% contraction in its economy, but disappointingly the outcome shows an exceeded figure to the range of 0.5%. In another related development, The International Business Outlook [41] reported that Japan’s national debt was estimated at 1 quadrillion Yen that is USD 10.46 trillion, in the second quarter of 2014. These figures were reported to be far greater than the German, France, and the United Kingdom economies combined. These massive debts were estimated to be 240% of the Japanese GDP. Parallel to this development and considering the contentious economic doldrums recorded in Japan during the Fukushima energy crisis, the value of the yen was reported to have deteriorated from 83.8 Yen/USD on February 15, 2011, to 122 Yen/USD in 2012, and down to 118.45 in 2015. To reduce the negative consequence of the devaluing position of the Yen on the Japanese trading relationship with the outside world, Nanto et al. [26] pointed out that the Bank of Japan injected $418 billion (i.e. 33 trillion Yen) into the financial markets, becoming a far more exceeding figure of what was injected to salvage the “too big to fail” companies in the US as a result of the 2008 financial crisis which is put at USD 300 billion [11]. The implication of a devaluing yen amidst crisis and shrinking economy was observed in the possibility of making the Japanese productive entities and exports weaker and less competitive in the world markets. In addition to that, since China's Yuan has been linked closely to the value of the dollar, the Chinese exporters are likely to gain further price competitiveness relative to those from

Japan and this will ultimately affect the Japanese exports and hence an increased balance of trade problems. To show the implication of this development, the Economic Watch [7] reported that the trade deficit in Japan as at September 2014 deteriorated to JPY 767 billion. In spite of the above economic adversities, Japan was said to be the second-highest electricity consumer in Asia. In 2012, the country's total electricity generation was put at less than 1000 Terawatts [13]. The IEA [13] continue to assert that the decomposition of that bloc figure shows that 338 TW h was obtained from coal, while 408 TW h from gas while only 14 TW h was generated from nuclear as against 274 TW h that was produced from the same nuclear energy in 2010. In addition to that 161 TW h was also produced from fossil fuel and this figure was found to increase by 94 TW h as against what was obtained in 2010. Similar to that line of development, 84 TW h was also found to have been produced from hydro. Surprisingly, the contribution of renewable energy in Japan in 2013 was found to be meager, and it was estimated in that period that solar energy contributed 10 TWh and 5 TW h from wind electricity generation. In addition to that, geothermal was found to contribute 2.6 TW h, biomass and waste 41 TW h. The EIA [8], continue to assert that in May 2012 Japan was found to have lost completely its wherewithal’s of producing nuclear energy power for the first time in over forty years and this was due to the devastation of the 2011 earthquake. In a bid to save the country from massive energy shortages, the government managed to operate two reactors in July, 2012 which produced an estimated nuclear energy of about 2.4 GW, following to other observed complications from the operation of these two reactors, the government decided to halt their operation in September, 2013, thus leaving Japan with a complete loss of nuclear energy for the second time in the history of the country. Following to this development, and considering the enormous electricity shortages Japan is suffering from the EIA [8] pointed out that Japan had to resort to massive rolling blackouts and at times the risks of unprecedented blackouts were also observed. This development reduced the outputs of major existing energy intensive companies operating in Japan. There was also a significant tension for the rise in the cost of electricity production and consumption in the country as claimed by the EIA [8]. From the foregoing development, the major contributions of this study is to examine the position of the long-run and short-run effects of the Japanese exports, imports, financial development and economic growth on the current electricity predicaments of the country. To ensure this, the study determines at what degree could the selected variables exert significant pressure on the country’s electricity demand and how could this be responsible to the slow piquing of the country’s economic growth prospects? In addition to that, the study also investigates if the current capital formation processes of the country have additional pressure to the electricity predicaments of the country? From these empirical findings, the study assesses the likely policy implications and offers some recommendations. To make this study unique and apart from its multivariate contributions, the study used the most extensive econometric estimation procedures and also ensured the application of up to date econometric methodology. In this new dimension, the study applied the extended Cobb–Douglas production function and used time series data for 1970–2012. It is remarkable to evaluate the case of Japan in order to establish if there is any positive outlook for the possibilities of the economic growth prospects for the former No. 2 world economic giant. The findings of this study will equally be a lesson to other countries with similar electricity and macroeconomic challenges. To ensure successful accomplishment of this study, this paper is organized in five sections: apart from the introduction above, section two provides recent empirical literature reviews linking energy

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

consumption, trade openness, financial development and economic growth; Section 3 is the methodology section which introduce the data, the model specification, and the model estimation procedure; Section 4 contains the results and discussion. Finally, Section 5 presents the conclusion and policy implication.

2. Literature review The existence of overwhelming researches on electricity consumption and economic growth nexus in the energy economics literature has to date not determined an ending search or a balanced ground on electricity consumption and economic growth among continents. For instance, the assertions of Ozturk [31] and Omri [29] outlined a comprehensive literature survey on the determinants of energy growth nexus and also on the electricity growth nexus. This captivating development motivated early researchers to underscore the contributions of energy consumption to economic growth in advanced economies. For instance, Rafindadi [34] established how the effects of financial development and trade openness influence the German energy consumption. The findings of the author further uncovered economic growth to be the cardinal element that piques energy consumption in Germany. Other variables of the study used by the same author discovered how financial development, capital use, and trade openness tend to have a negative influence on the German energy demand. In contrast to the findings of [34,35], the author identified how the expanding economic growth prospects of the United Kingdom could pose a threat to the country’s existing energy predicaments. Although the results of the author indicated that economic growth is negatively linked with energy demand in the United Kingdom. In contrast to that, the study discovered how the negative trade balances of the United Kingdom to be the major additive factor to the country’s electricity predicaments. The comparative influence of these studies indicates that electricity consumption and economic growth have no single unified direction in which it contributes to a country’s economic growth prospects. These developments warrants endless searches in the field of energy economics in both tranquil and in energy crisis periods. Kwon et al. [21] analyzed the effects of induced reduction of electricity consumption through raising electricity tariffs in the short-run due to the escalation in electricity demand by most countries. The findings established that a reduction in electricity use affects economic activity, thereby, impacting negatively on the profitability, employment prospects, national output, and subsequently economic growth. Sun and Anwar [39] applied the context of trivariate vector autoregressive framework to study the relationship between entrepreneurship, electricity demand and industrial production outputs with respect to Singapore's manufacturing entities. The findings reveal the existence of a feasible long-run relationship between electricity demand and entrepreneurial output in Singapore. According to the results, the growth hypothesis concerning energy consumption and economic growth are validated in the case of Singapore. In another related development, using panel of 160 countries from 1980 to 2010, Karanfil and Li [18] concluded that high electricity consumption was found to be sensitive to regional differences, continental income variability, degree and level of urbanization attained and supply risks. Mouton [25] in his research contributions examined the impacts of electricity sector reforms in the Philippines, which took place in the year 2000. The aim of the author is to assess whether the impacts of the Philippines electricity sector reform could have an effect on the country’s electricity supply and tariffs. The findings of the study suggested the need for ensuring efficient electricity supply and clearer electricity regulatory framework which should

1075

be accompanied in the reform models if the impacts of the reform exercise are to permeate in all sectors of Philippines economy. Fukushige and Yamawaki [12] studied the factors that necessitate electricity supply constraint, electricity generation capacity and the factors accounting for electricity demand in Taiwan. The findings of the authors established that electricity consumption in Taiwan is fraught with key supply constraints in the early periods of 1959–1972. In 1973 electricity generation capacity was found to have attained an efficient level in Taiwan. Following this investigation, the authors established that the economic growth prospect of Taiwan came to be more robust during that period. The conclusion of the authors unanimously agreed that ordinary Granger causality approach are not in any way efficient and effective in revealing the relationship that may exist between electricity consumption and economic growth of a country. They further argued that in most parts of the developing world of today, electricity supply constraint sometimes plays a significant role when investigating the relationship between energy consumption and economic growth. Marques and Fuinhas [24] studied the comparative impacts of renewable sources of energy which they termed as special regime and the conventional sources of electricity which they termed as the ordinary regime using the Portuguese electricity generation network. In the first instance, the authors appraised the relationships that exist between the two regimes and the respective economic activities that ensued within them. The findings of their study established the existence of a complementary relationship between the two regimes. While key economic activities were found to cause significant rise in electricity consumption, however, in a more close analysis it was discovered that it is the special regime that causes more economic boom and contrary was found to be the case with respect to the ordinary regime. Using a panel of 224 cities in China from 2002 to 2007, Elliott et al. [9] assessed the possibilities of whether declining economic growth in China could be attributable to poor energy distribution network. To ensure robust outcome from this study, the authors applied the leading electricity network distribution theory. While the propositional law of power distribution was used as the main gauging factor in the study. The propositional law established that the size of an economy and its prospects of energy consumption could be measured on the basis of capital by capita and this should be anchored on the basis of the electricity consumption per capita. According to the authors, the law of efficient electricity distribution is based on the direction that if an exponential bound of ½ and ¾ is discovered in the study then the existence of distributional efficiency in China is quite certain. Following this establishment, the findings of the authors discovered a result that is a bit higher than 2/3 and these estimates were compared with similar finding of a US-based study conducted in 2011. This development compelled the authors to succumb to the fact that their study is more robust than the findings obtained with respect to that of the US. In conclusion the authors, however, noted the currency of the period in which they conducted their study and this made them draw an observation that by implication of their findings there exist significant drawbacks on the overall energy distributional efficiency network particularly at the tail end of the study period. Kim [19] conducted a study that aimed at developing an electricity convergence parameter with respect to the level of development attained by 109 continents. To ensure this, the modeling pattern of the case study areas were allowed to exhibit apparent heterogeneous properties using the log t test convergence methodology. From this analysis, the study reported that, the 109 samples converged at a point indicating significant electricity intensity but the finding did not explain the level of per capita electricity consumption of the continents in comparison with the

1076

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

level of development that has been achieved in those continents. In this respect, the study proceeds to apply the multi-component model that decomposed the position of the selected continents. In that second stage analysis, the study discovered how 24 developed economies exhibited strong convergence with respect to all indicators. The study concluded that electricity consumption is a significant indicator to the rise in per capita income in those continents which in turn leads to economic development in the selected sample. On the aspect of electricity efficiency and competitiveness, the study of Nazemi and Mashayekhi [28] identified how the recently restructured Iranian electricity market impacted positively on the country’s energy production and distribution. In their study, the authors used 2006 and 2012 as the lead study periods. The findings indicated an insignificant contributions of the restructured electricity market in enhancing electricity production and competitiveness in the early periods. The study then proceeds to investigate the dynamics of electricity demand in the after restructuring periods i.e. 2012 and the effects generated by production efficiencies. The two periods were then compared to determine a common benchmark. The findings of the authors established a non-efficient tendency in both periods. This situation were found to be attributable to electricity marketing distortions commonly traceable to the learning curve effects in the postrestructuring periods, and this have greatly impacted on the newly restructured electricity market in Iran. Al-Mulali and Che Sab [1] examined the impact of energy consumption on the economic and financial development of 19 countries by taking the periods of 1980 to 2008. The results show that energy consumption enables these countries to achieve high economic and financial development. However, the high development that these countries have achieved in the late three decades increased the CO2 emission of the respective continents. Kyophilavong et al., [20] explored the relationship between energy consumption, trade openness and economic growth in case of Thailand. The findings of the authors showed how energy consumption could stimulate economic growth and how Trade openness could add to economic growth. Also, the findings of the authors established that the causal relationship between the variables in the case of Thailand showed energy consumption is the Granger-cause of economic growth in that country. Omri et al. [30] applied simultaneous equation modeling approach in a panel of 12 MENA countries from 1990–2011. The author aims to investigate the impacts of the relationship that may subsist between financial development, CO2 emissions, trade and economic growth. The results showed the existence of bidirectional causality between CO2 emissions and economic growth. In addition to that, the study further identified the existence of bidirectional causality suggesting the interrelationship between economic growth and trade openness. Moreover, the feedback hypothesis was discovered. These discoveries validated the existence of a perfect relationship to exist between trade openness and financial development. The causality relationship, on the other hand, reveals the existence of unidirectional causal relationship from financial development to economic growth and from trade openness to CO2 emissions. The authors concluded with assertion that the environmental Kuznets curve does exist in all continents and that policy makers have significant policy challenges of balancing the impacts and implications of the findings in order to ensure a balanced environmental benefits and efficient energy use in the respective MENA countries studied. From the perspective of the above reviews, there are very limited studies on the relationship between electricity consumption and economic growth in the case of Japan. To the best of our knowledge, there are only 5 studies in which electricity consumption-economic growth nexus has been examined for

Japan. In the four of these studies [23,3,37], discovered the existence of causality running from electricity consumption to economic growth and no causal relationship is found in the study of Narayan and Prasad [27]. In addition, Cheng [5] found the existence of a causal relationship from GDP to energy consumption, Erol and Yu [10] found bidirectional causality, and Soytas and Sari [38] found causality from energy consumption to GDP for Japan. Most of these studies were using only two variables (energy consumption and growth). In other words, they employed bivariate models that cause an omitted variable problem. To avoid this, the current study employed multivariate modeling approach and taking the post-Fukushima energy crisis in Japan which plunged the country into series of electricity and macroeconomic challenges. The aim of this study apart from its multivariate modeling approach is to figure out the long-run and short-run macroeconomic repercussion of electricity consumption on the Japanese economic growth prospects.

3. Data and methodological framework The study applied time series data from 1970 to 2012. The data sets were obtained from the World Bank Development Indicators [42] (CD-ROM). The variables used in this study are real GDP, energy consumption (kg of oil equivalent), real domestic credit to private sector, real exports, real imports and real capital stock; each in per capita terms. Fig. 1 below shows the trend of the selected variables in Japan. To examine the long-run effects between energy consumption and economic growth, the following Cobb–Douglas production function is employed in this study: G ¼ AEα1 K α2 Lα3 eu

ð1Þ

where, G is real domestic output; E, K and L denote, energy, capital and labor respectively. The term refers to technology and e the error term assumed N(iid). The output is elasticity with respect to energy consumption, capital and labor is and α3 respectively. Following to the direction of the Cobb–Douglas model, it is certain that when technology is restricted to (α1 þ α2 þ α3 ¼ 1) the result will be constant returns to scale. In the model developed by this study, technology was allowed to be endogenously determined by the level of financial development and international trade within an extended Cobb–Douglas production function. This is because, financial development promotes economic growth via capital formation that in turn makes capital more efficient in usage, in addition to that financial development, encourages FDI inflow and transfer of superior technology and managerial skills. International trade, on the other hand, helps technological advancements and 18 16 14 12 10 8 6 65

70

75

80

85

90

95

00

Year LEC LK LTR

LFD LEX

LY LIM

Fig. 1. Trends of variables in Japan.

05

10

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

þ π 5 ln TRt  1 þ π D DUM t þ u2t

its diffusion. The model can be written as: α

AðtÞ ¼ φ U TRðtÞ FðtÞ

δ

ð2Þ

where φ is time-invariant constant, TR is an indicator of trade openness and F is financial development. Substituting Eq. 2 into Eq. 1: GðtÞ ¼ φ:EðtÞδ1 FðtÞδ2 TRðtÞδ3 KðtÞβ LðtÞ1  β

ð3Þ

Following, Lean and Smyth [22], Rafindadi and Ozturk [36] and also Rafindadi [34,35], the study divide both sides by population and obtained each series in per capita terms. However, the impact of labor was left constant. By taking log, the linearized Cobb– Douglas production function is: ln Gt ¼

β1 þ β2 ln E t þ β3 ln F t þ β4 ln TRt þ β5 ln K t þ β6 ln Lt þ μt ð4Þ

where ln Gt , ln Et , ln F t , ln TRt and ln Lt, ln K t represent real GDP, energy consumption, real domestic credit to private sector as a proxy for financial development, real trade openness labor and real capital use respectively, each is transformed into logarithm and expressed in per capita terms. In this paper the study used three different indicators of trade openness in per capita terms; real exports, real imports, and real trade (exports plus imports as share of GDP ), which are then, estimated as separate equations. The term μt is a random error term. The specification also captures the relationship between energy use and economic growth where technology takes effect through the financial development and international trade. Prior to testing for cointegration, the stationarity of each series was checked using the ADF and the PP test with trend and intercept. The study noted that this test cannot capture the presence of structural breaks in the series. Following to this shortcomings and after the accomplishment of the ADF and the PP test, the study proceed to apply the Zivot and Andrew [43], and the Clemente et al. [6] unit root tests to identify the possibility of an existing structural break within the series. When these tests are accomplished, the Pesaran et al. [32] ARDL bounds testing approach to cointegration is applied in the determination of the long-run and the short-run dynamics of the variables. This test according to Inder [15] is found to have serial advantages over the Johansen cointegration techniques. These include, the provision of consistent results irrespective of the order of the variables in so far they are within the mix order of I(0) and I(1) or where there is mutual integration. This is in contrast with the Engle and Granger and the Johansen and Juslius [16] approaches. Inder [15] continues to maintain that the ARDL bounds test could effectively deal with the issue of endogeneity problem and is also best at reporting an unbiased test statistics even if the sample is small. In addition to that, the ARDL model can efficiently correct for omitted lag variable bias. In order to implement the ARDL bounds testing procedure in this study, Eq. (1) is transformed into the unconditional error correction model (UECM) as indicated below:

Δ ln EC t ¼ c0 þ

p X i¼1

þ

p X

p X

ci Δ ln EC t  i þ

di Δ ln Y t  i þ

i¼1

di Δ ln F t  i þ

i¼1 p X

p X

di Δ ln C t  i

i¼1

di Δ ln TRt  i

i¼1

þ π 1 ln EC t  1 þ π 2 ln F t  1 þ π 3 ln C t  1 þ π 4 ln Y t  1 þ π 5 ln TRt  1 þ π D DUM t þu1t

Δ ln C t ¼ c0 þ þ

p X

ci Δ ln C t  i þ

p X

i¼1 p X

i¼1 p X

i¼1

i¼1

di Δ ln Y t  i þ

di Δ ln EC t  i þ

p X

ð5Þ

di Δ ln F t  i

i¼1

di Δ ln TRt  i

þ π 1 ln C t  1 þ π 2 ln EC t  1 þ π 3 ln F t  1 þ π 4 ln Y t  1

1077

ð6Þ

where Δ denotes the first different operator, the c0 and d0 are the drift components, DUM is dummy variable to capture the structural break date, p is the maximum lag length and ut is the usual white noise residuals. The procedure of the ARDL bounds testing approach has two steps. The first step is F-test for the joint significance of the lagged level variables. The second step is the estimation of long-run and short-run parameters by using the error correction model (ECM). To ensure the convergence of the dynamics to the long-run equilibrium, the sign of the coefficient for the lagged error correction term (ECMt–1) must be negative and statistically significant. Further, the diagnostic tests comprise the testing for the serial correlation, functional form, normality, and the heteroscedasticity [33]. Once the variables are cointegrated for the long-run relation, then long-run and short-run causality can be investigated. The existence of a long-run relationship between financial development, economic growth, export, imports, capital and energy consumption requires us to detect the direction of causality between the variables by applying the VECM (vector error correction method) Granger causality framework. The vector error correction method (VECM) is as follows: 2 3 2 3 2 3 B11;1 B12;1 B13;1 B14;1 B15;1 b1 Δ ln EC t 6 7 6b 7 6B 7 6 Δ ln C t 7 6 2 7 6 21;1 B22;1 B23;1 B24;1 B25;1 7 6 7 6 7 6 7 6 Δ ln F t 7 ¼ 6 b3 7 þ 6 B31;1 B32;1 B33;1 B34;1 B35;1 7 6 7 6 7 6 7 6 7 6b 7 6B 7 4 Δ ln Y t 5 4 4 5 4 41;1 B42;1 B43;1 B44;1 B45;1 5 B51;1 B52;1 B53;1 B54;1 B55;1 b5 Δ ln TR 2 3 2 3 B11;m B12;m B13;m B14;m B15;m Δ ln EC t  1 6 Δ ln C 7 6B 7 6 6 21;m B22;m B23;m B24;m B25;m 7 t1 7 6 7 6 7 6 7 6 B B B B B Δ ln F 6 32;m 33;m 34;m 35;m 7 t  1 7 þ ::: þ 6 31;m 7 6 Δ ln Y 7 6B 7 4 4 41;m B42;m B43;m B44;m B45;m 5 t1 5 B51;m B52;m B53;m B54;m B55;m Δ ln TRt  1 2 3 2 3 2 3 μ1t ζ1 Δ ln EC t  1 6 Δ ln C 7 6 7 6μ 7 6 6 2t 7 t  1 7 6 ζ3 7 6 7 6 7 6 7 7 þ 6 ζ 3 7  ðECM t  1 Þ þ 6 μ3t 7 Δ ln F ð7Þ 6 t  1 6 7 6 7 6 7 6 Δ ln Y 7 6 7 6μ 7 4 4 4t 5 t  1 5 4 ζ4 5 μ5t ζ5 Δ ln TRt  1 where the difference in operator is ð1  LÞ, and the ECM t  1 is generated from the long-run relation. The long-run causality is indicated by the significance of the coefficient for the ECM t  1 by using the t-test statistic. The F statistic for the first-differenced lagged independent variables is used to test the direction of shortrun causality between the variables.

4. Results and discussions To make our investigation robust, the study starts with the assessment of the unit root test. This is in order to examine the stationarity properties of the variables. To ensure this, the study applied the ADF and PP unit root tests. The results of ADF and PP are presented in Table 1. The results show that all the variables are not stationary at a level. This development suggests the existence of a unit root problem within the series thereby, making it impossible to reject the null hypothesis of the unit root problem. However, after taking the first difference of all the variables, the series were found to be stationary with intercept and trend. This leads us to reject the null hypothesis of the unit root problem. At the end, the study found all variables to be stationary at the first difference and 1% level of significance. However, it is only the variable of trade openness that is found to be significant at 5%. The major problem with ADF and PP unit root tests is that they do not provide information on the structural breaks position of the

1078

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

series. This development could in actual sense provide an ambiguous result if no action is taken. To solve this problem, the study applied the Zivot and Andrew [43] unit root test. This test is best at accommodating single unknown structural break in the series. The selection of the break date is base on T-statistic and the break date is be selected where the evidence is favorable to the null hypothesis. In this test, the critical values of ADF unit root test are used. The results of the test are shown in Table 2, the finding from that Table shows how all the variables are non-stationary at a level in the presence of structural breaks. The test indicated the Table 1 Unit Root Analysis. Variable

ln Et ln Y t ln F t ln K t ln EX t ln IM t ln TRt Δ ln Y t Δ ln Et Δ ln F t Δ ln K t Δ ln EX t Δ ln IM t Δ ln TRt

ADF unit root test

P–P unit root test

T. statistic

Prob. value

T. statistic

Prob. value

 1.8304  2.3142  0.7294  1.8024  2.5126  2.7341  2.2186  4.7836  4.3590  4.4072  4.6636  6.5521  4.9639  3.6784

0.6752 0.4189 0.9651 0.6884 0.3211 0.2881 0.4693 0.0017 0.0058 0.0051 0.0024 0.0000 0.0010 0.0336

 1.7843 2.2995  1.4760  1.3119  2.6962  1.9758 2.2549  5.7041  5.8956  6.0785  4.3917  9.0342  6.3812  7.2991

0.6997 0.4265 0.8250 0.8737 0.2425 0.6002 0.4500 0.0058 0.0001 0.0000 0.0052 0.0000 0.0000 0.0000

(1) (3) (2) (2) (0) (1) (2) (1)a (1)a (1)a (1)a (2)a (1)a (1)b

(3) (3) (3) (6) (3) (3) (3) (3)a (3)a (3)a (3)a (3)a (3)a (3)a

a Indicates significant at 1% levels of significance. Lag length of variables is shown in small parentheses. b Indicates significant at 5% levels of significance. Lag length of variables is shown in small parentheses.

Table 2 Zivot–Andrews structural break trended unit root test. Variable

ln Et ln Y t ln F t ln K t ln EX t ln IM t ln TRt

At level

At 1st difference

T-statistic

Time break

T-statistic

 2.335  4.485  3.967  4.599  4.706  5.002  4.939

1999 1987 1988 1990 1986 1988 1988

 6.800  5.471  6.684  5.229  7.166  5.886  6.352

(1) (1) (1) (1) (1) (1) (1)

(2)a (1)b (1)a (1)b (2)a (1)a (1)a

Time break 1983 2000 1976 1992 2004 1984 2008

a Represents significance at 1%, levels respectively. The lag order is shown in parenthesis. b Represents significance at 5% levels respectively. The lag order is shown in parenthesis.

structural breaks dates to be 1999, 1987, 1988, 1990, 1986, 1988 and 1988. The structural break problems are found within the confines of the series of electricity consumption, economic growth, financial development, capital, exports, imports and trade openness respectively. However, at the first difference, the variables are found to be stationary. Following this development we conclude that the variables are integrated at I(1). The Zivot and Andrew unit root test accommodates information on a single unknown structural break in the series but ignore the role of other structural breaks that may exist within the series. To further investigate and solve this problem of two recurring structural breaks in the series, the Clemente–Montanes–Reyes (1998) test of dual structural breaks is used. The result of this test is indicated in Table 3. The findings from that table shows that in the presence of two structural breaks at the level, all variables are non-stationary, and there is a problem of unit root in all the variables in the case of Japan. However, in the presence of two structural breaks, all the variables of the model were found to be stationary at first difference. For this reason, we may conclude that our series have the same order of integration, and that is I(1). In investigating the existence of cointegration among the variables in the presence of structural breaks, this study applied the ARDL bounds testing approach to cointegration. In addition to that, the AIC is also used in the lag selection exercise. In this analysis, the study found the maximum lag length to be 2. Following to this ascertainment, the study proceeds to estimate the Fstatistic, which will confirm the existence of cointegration among the variables or otherwise. The commonest rule here is, if the calculated F-statistic is found to be greater than the critical bounds, then we may reject the hypothesis of no cointegration. The result of this analysis is reported in Table 4. The findings of the Table shows how the model; i.e. the calculated F-statistics to have exceeded the upper critical bounds, at 1% and 5% levels respectively. This development indicates that we had three cointegrating vectors when electricity consumption, financial development, and capital were used as dependent variables. The same inference is found in imports and trade openness models. Following to this, the study concludes for the existence of cointegration relationship between the variables in the presence of structural breaks in the series. The robustness of the long-run relationships is investigated by applying Johansen cointegration approach, and the results are reported in Table 5. The results show that both the Maximum Eigenvalue and Trace Statistics are significant. The null hypothesis of no cointegration is rejected in this respect, suggesting the existence of cointegrating vectors in three models. This confirms the presence of a long-run relationship between the variables. This finding is an attestation to the fact that our earlier finding using the ARDL model on the long run results are robust.

Table 3 Clemente–Montanes–Reyes detrended structural break unit root test. Variable

ln EC t ln Y t ln F t ln K t ln EX t ln IM t ln TRt a

Innovative outliers

Additive outlier

T-statistic

TB1

TB2

Decision

 4.188  3.076  4.352  3.401  4.175  3.080  4.089

1974 1983 1975 1974 1986 1986 1976

1985 2000 1983 1982 1998 2000 1998

Unit Unit Unit Unit Unit Unit Unit

(2) (3) (3) (1) (1) (3) (2)

Root Root Root Root Root Root Root

T-statistic Exists Exists Exists Exists Exists Exists Exists

 6.490  6.110  6.834  6.026  6.546  7.271  8.401

Indicates significant at 1% level of significance. The lag length of variables is shown in small parentheses.

(2)a (3)a (3)a (3)a (2)a (5)a (2)a

TB1

TB2

Decision

1981 1990 1986 1984 1986 1986 1991

1996 2000 1990 2000 1989 1991 1995

Stationary Stationary Stationary Stationary Stationary Stationary Stationary

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

1079

Table 4 The results of ARDL cointegration test. Bounds testing to cointegration

Diagnostic tests

Estimated models

Optimal lag length

Structural break

F-statistics

χ 2NORMAL

χ 2ARCH

χ 2RESET

χ 2SERIAL

F E ðE=Y; F; K; EXÞ F Y ðY=E; F; K; EXÞ F F ðF=Y; E; K; EXÞ F K ðK=Y; E; F; EXÞ F EX ðEX=Y; E; F; KÞ F E ðE=Y; F; K; IMÞ F Y ðY=E; F; K; IMÞ F F ðF=Y; E; K; IMÞ F K ðK=Y; E; F; IMÞ F IM ðIM=Y; E; F; KÞ F E ðE=Y; F; K; TRÞ F Y ðY=E; F; K; TRÞ F F ðF=Y; E; K; TRÞ F K ðK=Y; E; F; TRÞ F TR ðTR=Y; E; F; KÞ Significant level

2, 2, 2, 2, 2 2, 2, 2, 2, 2 2, 2, 2, 1, 2 2, 2, 2, 2, 2 2, 1, 2, 2, 2 2, 1, 2, 2, 2, 2, 2, 1, 2, 2 2, 1, 2, 2, 2 2, 2, 2, 2, 2 2, 1, 2, 2, 2, 2, 1, 2, 2, 2 2, 2, 2, 2, 2 2, 1, 2, 2, 2 2, 2, 2, 2, 2 2, 1, 2, 2, 2 Critical values (T ¼43)# Lower bounds I(0) 6.053 4.450 3.740

1999 1987 1988 1990 1986 1999 1987 1988 1990 1988 1999 1987 1988 1990 1988

7.478a 1.652 6.991b 5.571b 1.925 5.756b 1.3682 13.7594a 5.7221a 1.9948a 5.4261a 1.9409 7.9616a 5.4261c 2.5015

0.8383 0.6504 7.4470 3.5465 5.0645 2.6653 0.0332 1.2541 0.3980 0.6014 0.5313 0.2153 1.65404 3.0124 0.5385

[1]: [1]: [1]: [1]: [1]: [1]: [1]: [1]: [4]: [1]: [1]: [1]: [1]: [1]: [2]:

[1]: [2]: [2]: [2]: [1]: [1]: [1]: [1]: [3]: [1]: [1]: [1]: [4]: [1]: [4]:

[1]: [2]: [1]: [1]: [1]: [1]: [1]: [4]: [1]: [1]: [1]: [1]: [1]: [1]: [1]:

1% level 5% level 10% level

0.0567 0.0090 2.0034 0.1571 1.5098 1.4913 0.7103 5.5309 0.8680 0.0632 0.5672 0.9201 3.5300 0.4815 0.2304

0.8237 0.0267 0.3787 0.4171 0.0010 0.4437 1.8734 2.9821 2.5997 0.0759 1.1742 0.5040 1.7404 5.8061 1.6662

1.6304 0.0359 0.3966 1.5246 6.0886 0.4838 0.1816 0.5487 0.4327 0.5663 0.5304 0.7601 1.6573 0.2616 0.7830

Upper bounds I(1) 7.458 5.560 4.780

a Denotes the significant at 1% levels, respectively. The optimal lag length is determined by AIC. [ ] is the order of diagnostic tests. # Critical values are collected from Narayan (2005). b Denotes the significant at 5% levels, respectively. The optimal lag length is determined by AIC. [ ] is the order of diagnostic tests. # Critical values are collected from Narayan (2005). c Denotes the significant at 10% levels, respectively. The optimal lag length is determined by AIC. [ ] is the order of diagnostic tests. # Critical values are collected from Narayan (2005).

The long-run results are presented in Table 6, and the findings of the study established that financial development has positive and significant impact on electricity consumption in Japan. To support the direction of this claim the study discovered that a 1% increase in financial development will lead to a corresponding increase of 0.2429% in electricity demand in Japan keeping other things constant. In another related development that compliments the earlier finding, the study discovered how economic growth in Japan to be totally reliant on electricity consumption. Specifically, the study found the Japanese economic growth prospects to be positively and statistically related with electricity consumption. The findings of this study discovered how a 1% increase in economic growth will lead to a corresponding increase of 0.5040% in electricity consumption in Japan. Surprisingly, the impact of capital on electricity consumption is found to be negative, and it is statistically significant at 1% level. The result further indicates that a 1% increase in physical capital decreases electricity demand by 0.2142% if all other things remain the same. The Japanese exports were, on the other hand, found to be positively related with electricity demand. The result of the long-run analysis indicates that any 1% increase in the Japanese exports will have a significant impact on electricity demand by a cumulative rise of 0.0921%. Similar to this line of development, the study further discovered the existence of positive and significant relationship between imports in Japan and electricity demand in Japan. This finding reveals that a 1% increase in imports will lead to 0.2193% rise in electricity demand. Similar to that, Trade openness was equally discovered to influence the Japanese electricity consumption positively, and it is statistically significant at 1%. The results of the short-run analysis are also reported in the lower level of Table 6. The results indicate that financial development has positive and significant relationship with electricity demand. As a result a 1% increase in financial development increases electricity consumption by 0.2210 in the short-run. Similar to the long-run finding, the study further discovered economic growth to exhibit a persistent long-run and short-run

Table 5 Results of Johansen cointegration test. Hypothesis Y t ¼ f ðEt ; F t ; K t ; EX t Þ R ¼0 R r1 R r2 R r3 R r4 Y t ¼ f ðEt ; F t ; K t ; IM t Þ R ¼0 R r1 R r2 R r3 R r4 Y t ¼ f ðEt ; F t ; K t ; T t Þ R ¼0 R r1 R r2 R r3 R r4 a b

Trace Statistic

Maximum Eigen Value

106.1547a 66.6680a 41.4104 21.8843 6.6941

39.4866b 25.2575 19.5260 15.1901 6.6941

131.1673a 82.7933a 46.2450b 27.5315b 11.3959

48.3739b 36.5483b 18.7134 16.1356 11.3959

113.6845a 74.4694a 44.9533b 21.8179 5.2067

39.2150b 29.5157 23.1358 16.6111 5.2067

Shows significant at 1% levels of significance. Shows significant at 5% levels of significance.

positive and significant relationship with electricity consumption, but capital is still found to be negatively linked with electricity consumption as the case in the long-run finding. The impact of exports on electricity consumption is positive, but it is statistically insignificant in the short-run. This development is in contrast to the long-run finding. The study also discovered the existence of a positive and significant relationship between imports and electricity demand in Japan. The association between trade openness and electricity consumption is positive, and it is statistically significant. The value of the ECM is found to be negative and statistically significant. The estimates of exports, imports and trade models are  0.1650,  0.4279 and  0.2279 respectively. This suggests that short-run deviations toward long-run would be corrected by 16.50%, 42.79% and 22.79% in the models of exports,

1080

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

Table 6 Long and short runs results. Dependent variable ¼ ln EC t Long Run Analysis Variables

Coefficient

T-statistic

Coefficient

T-statistic

Coefficient

T-statistic

Constant ln F t ln Y t ln K t ln EX t ln IM t ln TRt Short-Run Analysis Variables Constant ln F t ln Y t ln K t ln EX t ln IM t ln TRt ECM t  1

 0.7904 0.2429a 0.5040a  0.2142a 0.0921c … …

 0.5307 2.9832 3.2792  2.7787 2.1352 … …

1.0630 0.2145a 0.2007b  0.1018c … 0.2193a …

1.1416 5.2765 1.8243  2.0300

0.7463 0.2112a 0.2833b  0.1272b … … 0.1687a

0.6172 4.2586 1.8580  1.9275 … … 2.8002

Coefficient  0.0017 0.2210c 0.5840c  0.1468b 0.0521 … …  0.1650c 0.57

T-statistic  0.2986 2.2522 2.6074  1.8038 0.8924 … …  2.1150

Coefficient  0.0071 0.2469a 0.7053a  0.2685c … 0.2031a …  0.4279c 0.6485

T-statistic  1.1983 2.8944 2.8433  2.3547 … 2.7555 …  2.0929

Coefficient  0.0071 0.2469a 0.7053a  0.2685c … … 0.2031a  0.2279c 0.6485

T-statistic  1.1983 2.8944 2.8433  2.3547 … … 2.7555  2.0731

R2 F-statistic 9.6648a D. W 1.5208 Short Run Diagnostic Tests Test F-statistic 3.9608 χ 2 NORMAL 1.9900 χ 2 SERIAL 1.6083 χ 2 ARCH 0.9394 χ 2 WHITE 0.9691 χ 2 REMSAY a b c

5.1538 …

13.2854a 1.5412 Prob. value 0.0907 0.1523 0.3522 0.5129 0.3391

13.2854a 1.7489

F-statistic 0.8459 2.3153 0.6510 1.2267 2.1242

Prob. value 0.1680 2.8339 5.4234 1.1495 0.1346

F-statistic 0.1143 2.1153 4.0156 2.2789 1.2721

Prob. value 0.3282 0.1362 0.0483 0.0339 0.2117

Shows significant at 1% level of significance. Shows significant at 10% level of significance. Shows significant at 5% level of significance.

imports and trade openness respectively. The results of diagnostic tests indicate that the error terms of the short-run model are normally distributed in all models. There is no heteroskedasticity, serial correlation, and also no ARCH problem. The value of the Ramsey reset test shows that the functional form for the short-run models is well specified.

15 10 5 0 -5 -10

4.1. Exports model In finding the stability of the long-run and short-run parameters of exports model, the cumulative sum (CUSUM) and the cumulative sum of squares (CUSUMsq) are used as proposed by Brown et al. [4]. The plot of the CUSUM is found to be within the line and significant at 5%. However, the plot of the CUSUMsq did not lie within the line after 2001 and is not significant at 5% level of significance. This indicates the presence of a structural break in 2001. The imports and trade models show consistent and efficient parameters of the long-and-short-run as confirmed by the CUSUM and CUSUMsq in Figs. 2 and 3 for the export model, same stability test for CUSUM and CUSUMsq was conducted with respect to the import and trade models and are presented in Figs. 4 and 5, and Figs. 6 and 7 respectively. To confirm the stability, we have applied Chow breakpoint test that confirmed the absence of no break point over selected period (Table 7). This shows that our estimated model is a good fit. 4.2. The VECM Granger causality analysis The VECM Granger causality test is applied in this study in order to establish the direction of causality between the variables

-15 92

94

96

98

00 CUSUM

02

04

06

08

10

12

5% Significance

Fig. 2. (Export model) Plot of cumulative sum of recursive residuals.

of the model. The direction of the causal relationship between the variables is helpful in designing comprehensive economic, financial and trade policies to control energy demand for sustainable economic growth. The results are reported in Table 8. The findings in that Table reveal the existence of both long and short run causal relationships. In the long-run, the study discovered the existence of bidirectional causality between financial development and electricity consumption, electricity consumption and capital. Following to this, the feedback effect was found to exist between financial development and capital. In another development, the study found the existence of unidirectional causality running from economic growth, exports, imports and trade to electricity consumption. These respective findings confirm the existence of an economic growth led electricity consumption, exports-led electricity consumption, imports-led electricity consumption, and trade-led electricity consumption in Japan. In the short-run, the relationship between economic growth and electricity consumption is bidirectional. Financial

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 -0.2 -0.4

1081

15 10 5 0 -5 -10 92

94

96

98

00

02

04

CUSUM of Squares

06

08

10

12

-15 92

94

96

98

00

02

04

06

08

10

12

5% Significance

CUSUM

Fig. 3. (Export model) Plot of cumulative sum of squares of recursive residuals.

5% Significance

Fig. 6. (Trade model) Plot of cumulative sum of recursive residuals. 15 10 5 0 -5 -10 -15

92

94

96

98

00

02

CUSUM

04

06

08

10

12

1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 -0.2 -0.4 92

5% Significance

94

96

98

00

02

04

CUSUM of Squares

Fig. 4. (Import model) Plot of cumulative sum of recursive residuals.

06

08

10

12

5% Significance

Fig. 7. (Trade model) Plot of cumulative sum of squares of recursive residuals. 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 -0.2 -0.4

Table 7 Chow Forecast Test. Chow Forecast Test: Forecast from 2001 to 2012 F-statistic Log likelihood ratio 92

94

96

98

00

02

04

CUSUM of Squares

06

08

10

12

5% Significance

Fig. 5. (Import model) Plot of cumulative sum of squares of recursive residuals.

development was found to Granger cause economic growth and capital. In addition to that financial development is also found to Granger cause electricity consumption in Japan. The feedback effect was detected between capital and economic growth. Economic growth, on the other hand, is Granger-cause of exports. Import Granger cause electricity consumption, capital, and economic growth. Trade openness Granger causes electricity consumption and capital in Japan.

5. Conclusion and policy implications This paper investigated the relationship between economic growth and electricity consumption by incorporating financial development, capital, and trade openness (exports and imports) using an extended Cobb–Douglas production function. The time span of the study is 1970–2012 using time series data for the Japanese economy. In this study, the traditional and structural break unit root tests were applied before determining the integrating properties of the variables. The cointegration relationship between the variables was tested using the ARDL bounds testing approach to cointegration and was further validated using the Johansen cointegration method. The causality relationship between the variables was, on the other hand, investigated using the VECM Granger causality framework. The findings of the study established that electricity consumption, economic growth, financial development, capital, and trade openness are cointegrated for the long-run relationship. Following this

3.6025 75.6132

Probability Probability

0.3212 0.0000

development, the study discovered that financial development stimulates electricity consumption in Japan. Economic growth adds to electricity demand, but capital declines it. Exports, imports and trade openness were equally found to create a significant increase in electricity consumption. In another related development, the study detected the existence of feedback effect between financial development and electricity consumption and the same inference is noted between capital and economic growth. Economic growth, exports, imports, and trade openness were on the other hand found to Granger-cause electricity consumption in Japan. The major distinguishing features of this study with past studies lies in its ability to uncover the degrees of the impact of each macroeconomic variable used in this study on the Japanese electricity consumption amidst the country's level of electricity predicaments. Following to this, the study discovered that in the longrun a 1% rise in the financial development prospects of Japan will exert considerable pressure on the country's electricity consumption by 0.2429%. Additionally, a 0.5040% increase in the Japanese energy predicaments was also observed to be as a result of any 1% increase in the country’s economic growth. Similar cases were found with respect to the Japanese exports and imports. In these two instances, it was discovered that any 1% increase in exports and imports in the country will add significant pressure on the Japanese electricity demand by 0.0921% and 0.2193% respectively. These findings signify that the Trade openness in Japan affects electricity consumption. Surprisingly, however, the study discovered that capital declines energy consumption in the country in both the long-run and the short-run. Similar discoveries were observed with respect to the short-run dynamic effects of financial development, economic growth, exports and imports on the electricity predicaments of Japan. In those relationships the

1082

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

Table 8 VECM Granger causality analysis. Dependent variable

Type of causality Short Run P

Δ ln Et  1

Δ ln Et



Δ ln Y t

13.5611b [0.0000] 4.5392a [0.0252] 2.2345 [0.1244] 0.8618 [0.4323] P Δ ln Et  1 –

Δ ln F t Δ ln K t Δ ln EX t

Δ ln Et Δ ln Y t Δ ln F t Δ ln K t Δ ln IM t

Δ ln Et Δ ln Y t Δ ln F t Δ ln K t Δ ln TRt

a b c

11.7378b [0.0000] 4.4232a [0.0204 3.6540a [0.0376] 3.6596a [0.0291] P Δ ln Et  1 – 12.5353b [0.0000] 2.4475 [0.1030] 2.6010c [0.0903] 5.8989b [0.0057]

Long Run P

Δ ln Y t  1 a

3.3985 [0.0463] – 0.5792 [0.5663] 18.5600b [0.0000] 2.1180 [0.1373] P Δ ln Y t  1 2.5272c [0.0925] – 0.4844 [0.6206] 10.8970b [0.0000] 3.1892a [0.0519] P Δ ln Y t  1 2.9231c [0.0685] – 0.4255 [0.6572] 12.5826b [0.0000] 0.4242 [0.6571]

P

Δ ln F t  1

2.2841 [0.1187] 16.1355b [0.0000] – 4.1411a [0.0225] 0.2570 [0.7750] P Δ ln F t  1 3.6425a [0.0379] 15.9987b [0.00000] – 5.2871a [0.0108] 0.1326 [0.6782] P Δ ln F t  1 1.7828 [0.1850] 17.1352b [0.0000] – 4.4651a [0.0205] 0.3945 [0.6766]

P

Δ ln K t  1

1.0507 [0.3618] 18.7825b [0.0000] 2.8311c [0.0743] – 0.3117 [0.7345] P Δ ln K t  1 1.3792 [0.2668] 24.8490b [0.0000] 4.9821a [0.0133] – 13.1310b [0.0000] P Δ ln K t  1 0.8358 [0.4431] 14.9809b [0.0000] 3.3311a [0.0489] – 2.0421 [0.1431]

P

Δ ln EX t  1

1.5009 [0.2388] 3.0620c [0.0579] 0.2067 [0.8143] 1.8410 [0.1756] –

ECT t  1  0.0386a [  2.2109] –  0.2528c [  1.7900]  0.2617b [  3.1365] –

P

Δ ln IM t  1 3.5812a [0.0399] 3.6939a [0.0337] 2.1598 [0.1324] 9.8632b [0.0005] – P Δ ln TRt  1 2.7646c [0.0786] 0.6057 [0.5506] 1.5401 [0.2303] 4.8000a [0.0153] –

 0.6213a [  2.7600] –  0.2887a [  2.0563]  0.1813a [  2.5214] –

 0.1232b [  5.4563] –  0.2631c [  1.8802]  0.2493b [  3.2602] –

Denotes the significance at the 5% level. Denotes the significance at the 1% level. Denotes the significance at the 10% level.

statistical indicators reveals that a 1% rise in the Japanese financial development prospects, economic growth, export, and import will lead to 0.2210%; 0.5840%; 0.0521% and 0.2031% short-run pressure on the country’s existing electricity position respectively. The most nostalgic discovery in this study was the finding on the positions of the error correction model in Table 6, in that table our findings established how the values of the error correction model indicated slow adjustment prospects towards the long-run equilibrium in response to shocks in industrial productions in the Japanese export sector, import, and the financial development sectors. The study attributed this to the rolling outage that applies to most of the energy-intensive production entities in the country and series of other macroeconomic shocks. These situations further suggest that productivity is greatly affected in Japan. This development justified the reason behind the continued fall in revenue generation in Japan, necessitated by a significant fall in export and other economic productivities. In addition to that, the wide existing trade deficits, dwindling value of the Japanese Yen, massive unemployment and the resultant decline in economic growth could all be attributed to the persistent economic shocks that was further aggravated by poor electricity supply that is required to sustain steady production activities in Japan and hence reduce unemployment. The implications of these findings to the Japanese economy is that it will continue to lead to the shrinkage of the country’s economic productivities. This is because efficient electricity supply means competitive industrial output and vice-versa. In addition to

that, if this situation continued to the long-run it will pose tremendous effects on the country’s macroeconomic development prospects by constricting the possibilities of economic growth in both the long-run and the short-run. This is because as industrial productivities are threatened by insufficient and inefficient energy supply, the phenomenon will undoubtedly lead to the decline in competitive industrial wherewithal. In addition to that, the huge cost used in generating electricity via the use of fossil fuel lead to high electricity tariffs, and this significantly lead to the rise in the cost of productivities. Following this development, it is essential to point out that an ailing and inefficient energy system breeds loopholes in a country’s planning prospects. With reference to this development electricity conservation policies currently in force in Japan will significantly affect the rate and the thriving of all formulated plans towards placing the country back on the path of sustainable economic growth particularly in a situation where the country host industrial outlets that are energy intensive. From the foregoing analysis, and with reference to the findings of this study it was discovered that energy consumption Granger cause economic growth and that export, imports, and financial development were also found to lead to an increase in the country’s electricity consumption. This means that any significant reduction in efficient and effective electricity supply in Japan, it will automatically impact negatively on this key economic activities which will in turn affect economic growth prospects of the country. To ameliorate the nostalgic energy predicament issues in Japan, and place the Japanese economy towards a sustainable path of affluence

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

already attained, we argue for strong commitment on the side of policy makers to embrace alternative long-run and short-run measures that are aimed at prioritizing huge investment into the country’s renewable energy sector. The impacts of renewable energy to Japan can be seen from the successful consolidative economic gains and the provisions of energy security attained by the Germans' renewable energy system. For instance, Rafindadi [36] reported that Germany is currently the world's largest operator of non-hydro renewable energy capacity in the world and the world's second-largest generator of wind energy. According to the author, nuclear power in Germany currently accounts for only 17.7% of the nation’s electricity supply in 2011, which is very minimal when compared with 22.4% in 2010. Rafindadi [36] continue to point out that, the proportion of electricity generated from renewable energy in Germany rose from 6.3% in 2000 to more than 25% in the initial half of 2012, thus generating 65.7 GW and that is equivalent to what 20 nuclear reactors could generate. This development according to the author provided significant energy and environmental security for the Germans'. From this lesson, we argue that Japan should borrow from the German initiative considering the incessant historical earthquakes that besieged the country in recent years. Complementing the established findings of Rafindadi [36], Marques and Fuinhas [26] in their study also supported the need for a significant boost of renewable energy system if sustainable and meaningful economic growth is to be achieved in a country. In addition to that, this study is of the believe that if this initiative is adopted in Japan it will greatly help in solving the high electricity demand by industrial and household consumers and will also help in reducing the low capacity of crude oil storage which the country suffers from. Similar to this, the attendant volatility in fossil fuel prices and its epileptic supply from regions that are incessantly affected by European sanctions such as Iran and the Arab springs that cumulatively add cost to the Japanese energy prospects could all be eliminated. We argue in this study that the Fukushima energy disaster should be seenas a lesson and challenge towards green energy revolution and revitalization in Japan. To ensure this, our study recommends heavy investment but competitive renewable energy system and should be the goal orientation with respect to all energy initiative in the country. However, it may be burdensome to achieve this line of development unilaterally and overnight. Following to this, and in order to ensure the curtailment of cost and time, we argue for the need of Japan to open its doors for the wide influx of FDI strictly within its renewable energy sector and to proceed with the invention of massive indigenous industrial outlets that promote the manufacture of renewable energy components in the country. In addition to that, collective and supportive effort should also be provided by the country’s energy authorities and intending stakeholders. Apart from the above long-run policy options energy authorities in Japan could also embark on a penalty-based approach aimed at encouraging prudential electricity use in the country. This can be ensured by making the government promulgate a policy for goods and services tax (GST). This development was recently launched by the Malaysian government in its 2014 budget. In that instance as reported by Bekhet and Ivy-Yap [2] the authors pointed out that beginning from 1 April, 2015, Malaysian electricity authorities will be charging 6% on every 201st unit of electricity and above that is consumed by household in a month. This policy is aimed at making electricity cost dearer to a household that consume more than 200 units of electricity per month in Malaysia. This is expected to amplify the cost of wasteful electricity consumption. This development if implemented in Japan will not only palliate the Japanese’s energy predicaments in the contemporary time but will equally ensure a balanced energy

1083

production and usage, environmental quality attainment through a significant reduction in energy emission from the fossil fuel currently used in generating power. The earlier initiative will equally help in costs saving, conserve energy and at the same time serving to sustain the welfare position of the Japanese citizens through reduction in carbon dioxide emission, and significant reduction if not total elimination of rolling outage. While ensuring the accomplishment of these policy options, the study believe the foregoing arguments will assist with the simultaneous satisfaction of efficient and balanced energy production and usage by consumers. Finally we argue that Japan should not afford to see a continued decline of its economic growth prospects as this will continue to impede on its manufacturing and other productive outlets that are the cardinal pillars of its economic growth. In essence going entirely green in energy is the current best option for the country.

References [1] Al-Mulali U, Che Sab CNB. The impact of energy consumption and CO2 emission on the economic and financial development in 19 selected countries. Renew Sustain Energy Rev 2012;16(7):4365–9. [2] Bekhet HA, Ivy-Yap LL. Highlighting energy policies and strategies for the residential sector in Malaysia. Int J Energy Econ Policy 2014;4:448–56. [3] Bildirici ME, Bakirtas T, Kayikci Fazıl. Economic growth and electricity consumption: autoregressive distributed lag analysis. J Energy South Afr 2012;23 (4):29–45. [4] Brown RL, Durbin J, Evans JM. Techniques for testing the constancy of regression relations over time. J R Stat Soc B 1975;37:149–92. [5] Cheng BS. Energy consumption, employment and causality in japan: a multivariate approach. Indian Econ Rev 1998;33(1):19–29. [6] Clemente J, Antonio M, Marcelo R. Testing for a unit root in variables with a double change in the mean. Econ Lett 1998;59:175–82. [7] Economic Watch. China and Japan's economic data does not impress; 2014. 〈http://www.economywatch.com/features/China-and-Japans-Economic-DataDoes-Not-Impress.12-08-14.html〉. [8] EIA (2014) Analyisis, 〈http://www.eia.gov/countries/cab.cfm?fips ¼ ja〉. [9] Elliott RJ, Sun P, Xu Q. Energy distribution and economic growth: an empirical test for China. Energy Econ 2015;48:24–31. [10] Erol U, Yu ESH. On the causal relationship between energy and income for industrialized countries. J Energy Dev 1988;13(1):113–22. [11] Filger S. Global economic financial crisis; 2008. [online] Available at: 〈http:// www.globaleconomiccrisis.com/blog/2010/6/archives/category/global-eco nomic-crisis〉. [12] Fukushige M, Yamawaki H. The relationship between an electricity supply ceiling and economic growth: an application of disequilibrium modeling to Taiwan. J Asian Econ 2015;36:14–23. [13] IEA. Key World Energy Statistics; 2013. 〈http://www.iea.org/publications/free publications/〉. [14] IHS. Global insight, Japan: Japan—interim annual forecast. 〈http://www.ihs. com〉; 2011 [retrieved 9.02.15]. [15] Inder B. Estimating long-run relationship in economics: a comparison of different approaches. J Econ 1993;57:53–68. [16] Johansen S, Juselius K. Maximum likelihood estimation and inference on cointegration with application to the demand for money. Oxf Bull Econ Stat 1990;52:169–210. [17] Japan, Ministry of Economy, Trade and Industry, Japan’s Nuclear Emergency— Update, April 6, 2011 available at: http://www.jtuc-rengo.org/information/ data/japans_nuclear_emergency.pdf [retrieved 30.1.15]. [18] Karanfil F, Li Y. Electricity consumption and economic growth: exploring panel-specific differences. Energy Policy 2015;82:264–77. [19] Kim YS. Electricity consumption and economic development: are countries converging to a common trend? Energy Econ 2015;49:192–202. [20] Kyophilavong P, Shahbaz M, Anwar S, Masood S. The energy-growth nexus in Thailand: does trade openness boost up energy consumption? Renew Sustain Energy Rev 2015;46:265–74. [21] Kwon S, Cho SH, Roberts RK, Kim T, Yu TE. Effects of changes in electricity price on electricity demand and resulting effects on manufacturing output. In: Proceedings of 2015 annual meeting. Southern Agricultural Economics Association. Atlanta, Georgia (No. 196850); January 31–February 3, 2015. [22] Lean HH, Smyth R. On the dynamics of aggregate output, electricity consumption and exports in Malaysia: evidence from multivariate Granger causality tests. Appl. Energy 2010;87(6):1963–71. [23] Lee CC. The causality relationship between energy consumption and GDP in G-11 countries revisited. Energy Policy 2006;34:1086–93. [24] Marques AC, Fuinhas JA. The role of Portuguese electricity generation regimes and industrial production. Renew Sustain Energy Rev 2015;43:321–30.

1084

A.A. Rafindadi, I. Ozturk / Renewable and Sustainable Energy Reviews 54 (2016) 1073–1084

[25] Mouton M. The Philippine electricity sector reform and the urban question: how metro Manila's utility is tackling urban poverty. Energy Policy 2015;78:225–34. [26] Nanto DK, Cooper W, Donnelly JM, Renée JR. Japan's 2011 Earthquake and Tsunami: economic effects and implications for the United States. Congressional research service 7-5700; www.crs.gov. Research paper no. R41702; 2011. [27] Narayan PK, Prasad A. Electricity consumption-real GDP causality nexus: evidence from a bootstrapped causality test for 30 OECD countries. Energy Policy 2008;36:910–8. [28] Nazemi A, Mashayekhi M. Competitiveness assessment of Iran’s restructured electricity market. Energy Econ 2015;49:308–16. [29] Omri A. An international literature survey on energy-economic growth nexus: evidence from country-specific studies. Renew Sustain Energy Rev 2014;38:951–8. [30] Omri A, Daly S, Rault C, Chaibi A. Financial development, environmental quality, trade and economic growth: what causes what in MENA countries. Energy Econ 2015;48:242–52. [31] Ozturk I. Literature survey on energy-growth nexus. Energy Policy 2010;38:340–9. [32] Pesaran MH, Shin Y, Smith RJ. Bounds testing approaches to the analysis of level relationships. J Appl Econ 2001;16:289–326. [33] Pesaran B, Pesaran MH. Time series econometrics using Microfit 5.0. 1st edition. England: Oxford University Press; 2009. [34] Rafindadi AA. Econometric prediction on the effects of financial development and trade openness on the German Energy consumption: a startling new revelation from the data set. Int J Energy Econ Policy 2015;5:182–96.

[35] Rafindadi AA. Could the expanding economic growth and trade openness of the United Kingdom pose a threat to its existing energy predicaments? Int J Energy Econ Policy 2015;5:121–37. [36] Rafindadi, Ozturk. Natural gas consumption and economic growth nexus: is the 10th Malaysian plan attainable within the limits of its resource? Renew Sustain Energy Rev 2015;49:1221–32. [37] Sami J. Multivariate cointegration and causality between exports, electricity consumption and real income per capita: recent evidence from Japan. Int J Energy Econ Policy 2011;3(1):59–68. [38] Soytas U, Sari R. Energy consumption and GDP: causality relationship in G-7 countries and emerging markets. Energy Economics 2003;25:33–7. [39] Sun S, Anwar S. Electricity consumption, industrial production and entrepreneurship in Singapore. Energy Policy 2015;77:70–8. [40] Tang CF, Lai YW, Ozturk I. How stable is the export-led growth hypothesis? Evidence from Asia's Four Little Dragons Econ Model 2015;44:229–35. [41] The International Business Outlook. Japan's economic outlook: 7 themes to watch in 2014. 〈http://www.ibtimes.com/japans-economic-outlook-7-themeswatch-2014-1519012〉; 2014 [retrieved 23.01.15]. [42] World Bank. World development indicators. Washington, D.C: World Bank; 2012. [43] Zivot E, Andrews D. Further evidence of great crash, the oil-price shock, and unit root hypothesis. J Bus Econ Stat 1992;10:251–70.