Examining the Relationship between Electricity Consumption, Financial Development and Economic Growth in ASEAN Countries: Evidence from a Bayesian Analysis

Nội dung text: Examining the Relationship between Electricity Consumption, Financial Development and Economic Growth in ASEAN Countries: Evidence from a Bayesian Analysis

1. International Journal of Energy Economics and Policy ISSN: 2146-4553 available at http: www.econjournals.com International Journal of Energy Economics and Policy, 2021, 11(2), 49-56. Examining the Relationship between Electricity Consumption, Financial Development and Economic Growth in ASEAN Countries: Evidence from a Bayesian Analysis Canh Chi Hoang Faculty of Business Administration, University of Finance - Marketing, Ho Chi Minh City, Vietnam. *Email: canhchihoang@ufm.edu.vn Received: 21 September 2020 Accepted: 20 December 2020 DOI: ABSTRACT The literature has suggested that financial development and electricity consumption are key determinants of economic growth. However, existing studies usually was applied the frequentist inference, which is an outdated estimator. By applying the Bayesian approach via the Metropolis-Hasting and Gibbs samplers as the MCMC methods, the study aims to re-examine the impact of financial development and electricity consumption on economic growth in ASEAN+6 countries from 1980 to 2016. The obtained outcome shows that the impact of both financial development and electricity consumption is strong and positive on economic growth. There is a uni-directional causality running from economic growth to energy consumption, supported the Conversation hypothesis. Based on the empirical result, several policy implications are suggested for emerging countries, ASEAN+6 nations, in particular. Keywords: Financial Development, Energy Consumption, Economic Growth, Bayesian, ASEAN Countries JEL Classifications: F43, O13, O47, Q42, Q43 1. INTRODUCTION leads to a fixed interest rate, decreasing banking activities, increasing the real exchange rate, reducing export, discourage Physical capital accumulation is a crucial factor contributing the development of capital markets, and hurts economic growth. to economic growth (Romer, 1990; Stiglitz, 2000). Following the pioneering of Schumpeter (1912), majority of the economic Understanding and quantifying the relationship between energy researcher is persuaded that financial development allows foreign consumption and economic growth is one of the hot topics for direct investment flows, encourages the investment of enterprises, economics researchers and administrators. Energy is used as reduces costs of loans, boost household consumption, and an input in the production, transportation, and consumption of increase banking activities, less financial risks. The pressure of nearly all goods or services (Ha and Ngoc, 2020; Long et al., improving income per capita leads to pumping more money into 2018; Stern, 2000). The linkage between energy consumption and the financial system by Government. The consequence of more economic growth has been well-studied by several researchers. money is a high-inflation situation, and the financial crisis of 2008 Nevertheless, the conclusion of existing studies has failed to provided practical evidence to re-examine the benefit of financial provide a consistent answer. For example, Tang (2009) investigates development to growth. Now, the notion “more money, more the connection between electricity consumption, income, foreign oversight” has been supported by many governments worldwide. direct investment, and population in Malaysia from 1970 to However, a financial reduction is not good for economic growth. 2005. The obtained results by the ARDL approach shows that McKinnon (1974), Shaw (1974) argues that financial reduction economic growth has a positive impact on electricity consumption, This Journal is licensed under a Creative Commons Attribution 4.0 International License International Journal of Energy Economics and Policy | Vol 11 • Issue 2 • 2021 49
2. Hoang: Examining the Relationship between Electricity Consumption, Financial Development and Economic Growth in Asean Countries: Evidence from a Bayesian Analysis supported the Conversation hypothesis. However, Yoo (2005) because it will reduce the return rate of financial assets. Besides, used the cointegration and vector error correction model to it encourages people/enterprises to invest in non-financial assets analyzes the short- and long-run causality between electricity (e.g., gold, real estate) and generates back financial markets. consumption and economic growth in Korea from 1970 to 2002. Indeed, Bretschger and Steger (2004) showed two channels that The empirical outcome reveals that there is bi-directional causality financial development affects on economic growth, including (i) between economic growth and electricity, supported the Feedback the scale-effect channel; (ii) the factor-reallocation effect channel. hypothesis. Even using the panel data, the results of Chen et al. Accordingly, they confirmed that the efficiency banking system (2007) are mixed in ten newly industrializing and developing is the vital factor for economic development due to its role in ASIAN countries. Accordingly, there is a uni-directional short- mobilizing and allocating saving and the funding of economic run causality running from economic growth to electricity activity investment. consumption and a bi-directional long-run causality between electricity consumption and economic growth if the panel data Regarding empirical studies, King and Levine (1993) found that procedure is implemented. the development of the financial sector is robustly related to per capita GDP growth, and it positively enhances the accumulation of The above mentioned previous studies indicate that the linkage physical capital. Likewise, Ben Jedidia et al. (2014) used the ARDL between financial development, electricity consumption, and approach to analyze the connection between financial development economic growth is an interesting topic, which is still the subject and economic growth in Tunisia from 1973 to 2008. The obtained of an ongoing debate (Omri, 2014; Tiba and Omri, 2017). The main result shows that domestic credit to the private sector positively aim of this work is to inspect the impact of financial development, affects economic growth, and financial development is a driver electricity consumption, and economic growth in ASEAN+6, of long term economic growth. The positive impact of financial including Indonesia, Malaysia, Philippines, Singapore, Thailand, development on economic growth is supported by the study of Vietnam during the period 1980-2016. Our study is different from Liang and Teng (2006), Komal and Abbas (2015), Salahuddin and several previous studies in multiple points, as follows: First, to Gow (2016). Another study by Alsamara et al. (2018) examines the best of our knowledge, the available studies analyzed in the the impact of financial development and trade openness on the case of ASEAN countries have drawn little attention. Second, real GDP per capita in Turkey during the period 1960-2014. The most previous studies have been conducted in a linear framework empirical result from the ARDL approach with structural break and used the frequentist inference. In the study, we employed the reveals that both the trade openness and financial development Bayesian inference approach through the integrated Markov chain have a positive impact on per capita real GDP. Accordingly, a 1% Monte-Carlo sampler to provide probabilistic interpretations of increase in money supply to GDP ratio leads to a 0.36% increase in model uncertainty and varying effects of financial development real GDP per capita. Using the non-linear framework, Masten et al. and electricity consumption on economic growth. The advantage of (2008), Law and Singh (2014) found that the impact of financial Bayesian inference compared to frequentist inference is presented development was depended on the critical threshold, exceed this in Section 3. To our knowledge, the obtained result could be critical threshold, the more money is not good for economic growth. enrichment in existing economic literature and for the ASEAN+6 countries in particular. Goldsmith (1969) was the first to work a positive correlation between economic growth and financial development in his 35 The rest of the study is organized as follows: Section 2 focuses on countries sample. Abid et al. (2016) used a multivariate vector present the literature and the existing studies. Section 3 describes autoregressive model to inspect the linkage between financial the model, data, and methodology. The obtained outputs are development (measured by the stock market return) and economic shown in section 4, while section 5 provides a conclusion and growth in ten MENA (the Middle East and North Africa) countries. policy implication. The result provides evidence that the GDP growth response to Qatar GDP growth shock is statistically significant for all countries, 2. LITERATURE REVIEW while the stock market response to Morocco stock market shock is insignificant in Qatar, Saudi Arabia, and UAE. The positive impact 2.1. Financial Development and Economic Growth of financial development on economic growth is confirmed by The role of the financial development and financial system is the study of Ibrahim and Alagidede (2018). Applying the system a vital one for any economy. The pioneering of Schumpeter GMM method, Ibrahim and Alagidede (2018) found that financial (1912) found that a developed financial system boost investment development supports economic growth. The extent of finance activities, increase transparency between lenders and borrowers, helps growth depends crucially on the simultaneous growth of real reduces costs of credits, and leads to beneficial for economic and financial sectors in 29 sub-Saharan African countries over the growth. Schumpeter (1912) stated that most of the enterprises need period 1980-2014. Greenwood and Jovanovic (1990) explained credit in order to buy material, machinery, and paying salaries. that individuals or enterprises have many opportunities to invest In simple capital markets, the bank becomes the producer of this in several projects. The developed financial system, as mentioned commodity. Thus, the banking system plays the most critical by Schumpeter (1912) must mobilize and allocate saving capital channel, where intermediating financial activities are supported flows into projects, which have high productivity or output. That and enhance growth. Consistent with this view, McKinnon (1974) means stock market allocates these capital flows into priority and Shaw (1974) devote to financial liberalization. They pointed sectors, which have the highest return rate, and generates several out that the Government should not strictly control interest rates optimal stock lists. Greenwood and Jovanovic (1990) pointed out 50 International Journal of Energy Economics and Policy | Vol 11 • Issue 2 • 2021
3. Hoang: Examining the Relationship between Electricity Consumption, Financial Development and Economic Growth in Asean Countries: Evidence from a Bayesian Analysis that if individual or enterprises select an optimal stock list, which uni-directional causality in the short-run, a bi-directional causality leads to beneficial for economic growth. between per capita electricity consumption and per capita GDP in the long-run. Another study by Acaravci (2010) explores the However, some administrators and economics researchers are not short- and long-run causality between electricity consumption advocating for financial development. Edwards (2001), Okada and economic growth in Turkey from 1968 to 2005. The VECM (2013) argues that the overload of financial development leads to Granger causality shows that there is a uni-directional causality an increase in inflation, which harms economic growth in the long- running from electricity consumption to economic growth. run. Emerging markets have a low financial institution, and should be highly susceptible to the volatility of the global financial market, The conversation hypothesis was found by the pioneering study of which is especially severe for countries with an open capital account. Kraft and Kraft (1978). They examine the impact of economic growth Demetriades and Hussein (1996) used the VAR model to examines on electricity consumption in the United States over the period 1947- the influence of financial development on economic growth in 16 1974. The Granger causality provides that there is a uni-directional countries. The obtained result reveals that the money supply is the causality running from economic growth to electricity consumption. danger of economic growth. Likewise, Rousseau and Vuthipadadorn Likewise, Balcilar et al. (2019) used the Maki cointegration to inspect (2005) found that financial development has a dampening effect on the linkage between electricity consumption, real gross domestic investment and growth in ten ASIAN countries. Similarly, Ono (2017) product, and carbon dioxide emissions in Pakistan. A uni-directional found that there is no causality from money supply to economic causality running from economic growth to electricity consumption growth in the case of Russia during the period of 2009-2014. was found by the Toda-Yamamoto causality test, which supported the Conversation hypothesis. 2.2. Energy Consumption and Economic Growth In developing countries, administrators and economic researchers Some studies found the neutrality hypothesis. Ghosh (2009) does have advocated analysis of the linkage between energy not found the interaction between electricity supply, employment, consumption and economic growth with the expectation that and real GDP for India. Similarly, Payne (2009) applied the Toda- energy production and energy consumption are key determinants Yamamoto causality tests. The obtained result shows that the of economic growth. In fact, energy is a necessary input of absence of Granger-causality between renewable or non-renewable economic activities, such as transportation, production (Abosedra energy consumption and real GDP in the case of the United States et al., 2009; Chandran et al., 2010; Golam and Nazrul, 2011; from 1949 to 2006, which supports the neutrality hypothesis. Ngoc, 2019; Zhang et al., 2017). The energy-growth nexus has been well-studied in the energy economics literature. However, The impact of financial development and energy consumption on the available studies have failed to provide a consistent answer economic growth has been studied by several previous works, such (Ha and Ngoc, 2020; Tiba and Omri, 2017), and it is still the as Kahouli (2017), Rafindadi and Ozturk (2016), Burakov Burakov subject of an ongoing policy debate. There are four hypotheses and Freidin (2017), and Mahi et al. (2019). However, the conclusion found by existing works about the relationship between energy of these studies is not consistent, even ambiguous. To explain the consumption and economic growth, including the “Conversation,” different above-mentioned conclusion, Apergis and Payne (2010) point the “Growth,” the “Feedback” and the “Neutrality” hypothesis. out that the interaction between energy consumption and economic growth nexus is depended on the level of national development. In Supporting the Feedback hypothesis, based on the Cobb-Douglas poor countries, economic activities based on natural extraction (e.g., production function, Hamdi et al. (2014) inspect the linkages planting, fishing). Thus, the demand for energy is low, and the energy between electricity consumption, foreign direct investment, capital, consumption does not enhance economic growth. However, it is not and economic growth from 1980Q1 to 2010Q4 for the Kingdom true in developing or developed countries. The pressure improving of Bahrain. The empirical result from the ARDL bounds testing income per capita leads to many projects or policies were issued by and VECM causality shows that there exist a positive impact the Government, which requires more energy as a driving force of and bi-directional causality between electricity consumption production of goods or services. So, energy production and energy and economic growth. Likewise, Ibrahiem (2015) analyzes the consumption is an essential factor for development. relationship between renewable electricity consumption, foreign direct investment, and economic growth in Egypt from 1980 to Of course, the above-mentioned studies do not adequately 2011. The existence of cointegration among the examined variable represent all previous studies on financial development-energy is found by the ARDL bounds testing, and the Granger causal test consumption-growth nexus. Nevertheless, this review showed identifies the bi-directional causality between economic growth that most of the available studies use frequentist inference. No and renewable electricity consumption. The positive influence of studies apply Bayesian inference. It is a methodology gap, which electricity consumption on economic growth is confirmed by the this work want to address. study of Tang (2009) for Malaysia, Long et al. (2018) for Vietnam, or Zhang et al. (2017) for China’s economy. 3. RESEARCH MODEL AND About the growth hypothesis, Golam and Nazrul (2011) discover METHODOLOGY the connection between per capita electricity consumption and per capita GDP in the case of Bangladesh from 1971 to 2008. The The main aim of this study is to investigate the impact of financial obtained outcome reveals mixed results. Accordingly, there is a development and electricity consumption on economic growth International Journal of Energy Economics and Policy | Vol 11 • Issue 2 • 2021 51
4. Hoang: Examining the Relationship between Electricity Consumption, Financial Development and Economic Growth in Asean Countries: Evidence from a Bayesian Analysis in ASEAN+6 countries from 1980 to 2016, so the model is py()Mpjj()M preliminarily set as follows: pM()y = j py() (4)  LnGDPLit,,01iinECLti2 nFI ,t Since it is challenging to calculate p(y), a popular practice is to .( .) .  34Ln EC FI it, UBiit,,eit (1) compare two models, for example, Mj and Mk via posterior odds ratio: where, i is the country (1, , N: including Indonesia, Malaysia, ()() pM()j y pyMpjjM Philippines, Singapore, Thailand, Vietnam, respectively), t is PO , = = (5) jk pM()y py()Mp()M time (1, , T: from 1980 to 2016). υi are random intercepts, k kk e is an error. In Eq.1, LnFI variables is the logarithm of (i,t) If all models are equally plausible, that is p(Mj)=1/r, the posterior financial development (measured by M2 money supply, units: odds ratio is transformed into the Bayes factor, which is simply million U.S. dollar), LnEC variable is the logarithm of the ratios of marginal likelihoods (Jeffreys, 1962). electricity consumption per capita, unit: kWh/year), Ln(EC.FI) py()M is the interaction variable (= LnEC*LnFI), and UB is the rate j BFjk, = (6) of urbanization (unit: percentage), which plays as the control py()M k variable in the model. Annual data is collected from the IMF and The detailed process of estimation is acted through three steps, the World Bank. The dependent variable is LnGDP per capita as follows: (at the fixed price 2010, unit: U.S. dollar). This work used the First, we use the fixed-effect model (FEM) and the random-effect Bayesian inference, which has several advantages outperforms model (REM) to provide a general view of the influence of financial the Frequentist inference, as follows: development and electricity consumption on economic growth. First, Bayesian analysis is based on the Bayes rule and the posterior distribution results from updating the prior knowledge about model Second, we apply the Bayesian approach via the Metropolis- parameters with evidence from the observed data. The Bayesian Hasting and Gibbs samplers as the MCMC methods to estimate analysis rests on Bayes’ theorem of probability theory: the impact of financial development and electricity consumption py().(p ) on economic growth. py()  (2) py() Finally, we use Dumitrescu and Hurlin (2012) test to check the where, θ stands for a set of unknown parameters, y represents a causality between energy consumption and economic growth. marginal distribution of data, p(θ) denotes the prior distribution of the parameters θ (pre-existing information such as expert opinion, theory, or other external resources), p(y|θ) is a likelihood 4. EMPIRICAL RESULTS distribution, p(y) is the marginal distribution of y, and p(y|θ) denotes the posterior distribution, which is the probability of the parameters 4.1. Descriptive Statistic In two past decades, the ASEAN+6 countries, including Indonesia, θ conditional on the data x. Equation (2) may be expressed as: Malaysia, Philippine, Singapore, Thailand, and Vietnam, have changed rapidly in most socio-economic fields. Rapid growth leads py() py()p() (3) to a change in the structure of the economy. The industry sector is focused on investing by the Government. Also, urbanization leads to where, ∝ implies “proportional to.” The posterior is proportional a great demand for energy. Acknowledge that financial development to the prior multiplied by the likelihood. and energy consumption are actively contributing to growth in these Second, the frequentist inference assumes that all parameters countries. The descriptive statistic of all variables is shown in Table 1. are considered unknown but fixed quantities, while Bayesian inference allows all parameters are random quantities and thus 4.2. Model Comparison can incorporate prior knowledge. Hence, Bayesian analysis yields This subsection compares five posterior regression models, where an entire probability distribution of a parameter, while frequentist the respective Gaussian prior distributions specified are N(0,1), results are point estimates. Also, the Bayesian paradigm allows N(0,10), N(0,100), N(0,1000), and N(0,10000). for probability statements, such as a variable is likely or unlikely to impact on another, or the true value of a parameter falls into The results of the model comparison are presented in Tables 2 and 3. a certain interval with a pre-specified probability (Bernardo and In general, the less the DIC value, the more the log(ML) and Smith, 1994; Thompson, 2012). log(BF) estimate, the better a model fits the data. P(My) shows the posterior model probability. Consequently, model 1 is the best. Because our data sample size is sufficiently large, noninformative priors are enough for our model specification. For comparison Table 1: The descriptive statistic of all variables purposes, we also specify informative priors for the model Variables Mean Maximum Minimum Std. error parameters. Accordingly, we conduct five posterior simulations. LnGDP 8.128 10.885 5.735 1.234 A sensitivity analysis to prior choice will be performed through LnEC 6.763 9.088 3.832 1.358 a Bayes factor test and a model test. We assume to have models LnFI 2.573 4.275 -1.472 0.725 LnECFI 17.301 31.028 -11.528 4.734 Mj parameterized by vectors θj,j=1,2, r. By applying Bayes’s theorem, we calculate the posterior model probabilities: UB 50.26 100 19.25 25.56 52 International Journal of Energy Economics and Policy | Vol 11 • Issue 2 • 2021
5. Hoang: Examining the Relationship between Electricity Consumption, Financial Development and Economic Growth in Asean Countries: Evidence from a Bayesian Analysis 4.3. MCMC Convergence Test The model summary reports the rate of acceptance and algorithm In the application of an MCMC method, a convergence check is efficiency as initial indicators of MCMC convergence. The needed before proceeding to inference. Once chain convergence is acceptance rate is the number of proposals accepted in the total established, the model parameters have converged to equilibrium proposals, whereas algorithm efficiency is the mixing properties of values. To avoid pseudo convergence, in this study, we simulate MCMC sampling. Concerning the chosen model 2, the acceptance three MCMC chains and verify whether the results satisfy the rate of 0.84 is larger than the minimum level of 0.1, whereas convergence rule. This is because pseudo convergence takes place average efficiency is equivalent to 0.35, which is more than the when the chains have seemingly converged, but indeed, they acceptable level of 0.01. This implies that the obtained results explored only a portion of the domain of a posterior distribution. from Bayesian multilevel regression are reliable. As demonstrated in Table 4, the maximum Gelman-Rubin statistic Rc of 1.0001 is close to 1.1, indicating MCMC convergence. Additionally, it is useful to conduct a graphical inspection. For this, CUSUM plots as an accessible tool are applied. As shown in Table 2: Bayesian information criteria Figure 1, the CUSUM plots of the parameters corresponding to Model Gaussian distribution DIC log(ML) log(BF) three chains are jagged, not smooth, running across the X-axis. So 1 N(0,1) 103.8528 −75.6626 MCMC chains for the model parameters are well-mixed, which 2 N(0,10) 104.0392 −79.5551 -3.8924 is a sign of sequence convergence. 3 N(0,100) 104.0978 −85.1067 -9.4441 4 N(0,1000) 104.1043 −90.8425 −15.1799 5 N(0,10000) 104.1050 −96.5969 −20.9342 4.4. FEM, REM and Bayesian Estimation The estimation of the Eq.1 by frequentist and Bayesian inference is presented in Table 5. The obtained outcome from FEM and Table 3: Bayesian model tests REM model shows that there is a positive impact of electricity Model Gaussian distribution log(ML) P(M) P(My) consumption on economic growth. Accordingly, a 1% increase 1 N(0,1) −75.6626 0.2000 0.9799 in electricity consumption leads to 0.747% increase in economic 2 N(0,10) −79.5551 0.2000 0.0200 growth. Besides, financial development is helpful to economic 3 N(0,100) −85.1067 0.2000 0.0001 4 N(0,1000) −90.8425 0.2000 0.0000 growth (P_value = 0.000). A 1% increase in financial development 5 N(0,10000) −96.5969 0.2000 0.0000 leads to 0.629% increase in economic growth. With the Bayesian inference, the result in the lower section of Table 4: Gelman-rubin convergence diagnostic Table 5 reveals that both the influence of electricity consumption Max gelman-rubin Rc=1.000142 Rc value and financial development is beneficial for economic growth. With 0 Equal-tailed (95% Cred. Interval) Dependent variable: LnGDP LnEC 0.7951 0.0691 0.0004 1 (0.6587, 0.9315) LnFI 1.0226 0.1652 0.0009 1 (0.6983, 1.3473) LnECFI -0.1469 0.0230 0.0001 1* (−0.1919, −0.1019) UB 0.0251 0.0016 0.0000 1 (0.0221, 0.0280) Intercept 1.3753 0.4849 0.0028 0.99 (0.4216, 2.3275) * is probability of mean < 0 International Journal of Energy Economics and Policy | Vol 11 • Issue 2 • 2021 53
6. Hoang: Examining the Relationship between Electricity Consumption, Financial Development and Economic Growth in Asean Countries: Evidence from a Bayesian Analysis Figure 1: CUSUM plots of model parameters Table 6: Results of the causality test 6. CONCLUSION Null hypothesis: No causality W-bar Z-bar P-value LnEC does not granger cause LnGDP 1.9879 1.711 0.087 The study applies the Bayesian approach via the Metropolis- LnGDP does not granger cause LnEC 4.6660 6.3549 0.000 Hasting and Gibbs samplers as the MCMC methods to investigate the impact of financial development and electricity consumption is one, we can state that urbanization is a good contribution to on economic growth in ASEAN+6 countries over the period 1980 economic growth in examined countries. to 2016. Five simulations are conducted with Gaussian prior distributions ranging from (0,1) to (0,10000). As shown by model 4.5. The Causality Test comparison results via a Bayes factor and a model test, the model with a noninformative, namely, N(0,1) prior fits the best. According Finally, the study used Dumitrescu and Hurlin (2012) test to to the estimation results, we claim in view of the probability that examine the causality relationship between energy consumption both electricity consumption and financial development strongly and economic growth. Both the W-bar and Z-bar statistic test and positively affects economic growth. presented in Table 6 provides evidence in favor of the rejection of the null hypothesis (P_value < 0.05). This result implies that Based on the empirical results, some policy implications are there is a uni-directional causality running from economic growth suggested, as detailed: to energy consumption in examined countries, which supported the Conversation hypothesis. Firstly, electricity consumption is beneficial for growth, so the Government should intend to expand energy supply through the 5. DISCUSSION development of renewable or green energies, such as solar, wind, biofuels, and geothermal power. The empirical result shows that the impact of financial development and electricity consumption on economic growth is Secondly, financial development will drive economic growth if beneficial. These results are in line with the conclusion by Ben the country has a transparent and efficient financial system. Thus, Jedidia et al. (2014) for Tunisia, Sarkar et al. (2019) for Malaysia, the rate of the money supply should be calculated corresponding Glasure and Lee (1997) for South Korea and Singapore, or Long to the rate of growth. A deficiency in the money supply will result in a decrease in economic growth, negatively impacting other et al. (2018); Ngoc (2019); Nguyen and Ngoc (2020) for Vietnam. economic activities. Physical capital accumulation and a developed financial system will enhance economic growth through the process of mobilizing and allocating the saving capital flows into projects, which have REFERENCES high productivity or output. All six countries in our sample are developing or developed countries, so the demand for production, Abid, F., Bahloul, S., Mroua, M. (2016), Financial development and economic growth in MENA countries. Journal of Policy Modeling, distribution, or household consumption is rapid growth. According 38(6), 1099-1117. to the forecasting of the International Energy Agency, the energy Abosedra, S., Dah, A., Ghosh, S. (2009), Electricity consumption and demand is growing by 1.4% per year until 2035. This is valid for economic growth, the case of Lebanon. Applied Energy, 86(4), both emerging or developed countries. 429-432. 54 International Journal of Energy Economics and Policy | Vol 11 • Issue 2 • 2021
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