eyd Ekonomik Yaklaşım Derneği / Association

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eyd

Ekonomik Yaklaşım Derneği / Association

Ekonomik Yaklaşım 2021, 32(120): 249-266

www.ekonomikyaklasim.org doi: 10.5455/ey.19001

Renewable Energy Generation and Economic Growth: Evidence from Turkey

Müzeyyen Merve ŞERİFOĞLU¹

02 Aralık 2020’de alındı; 10 Temmuz 2021’de kabul edildi.

17 Eylül 2021’den beri erişime açıktır.

Received 02 December 2020; accepted 10 July 2021.

Available online since 17 September 2021.

Araştırma Makalesi/Original Article Abstract

The purpose of this paper is to investigate the long run relationship between renewable energy generation and economic growth in Turkey for 2013: q2-2020: q2 periods through Ordinary Least Square (OLS) and Dynamic Ordinary Least Square (DOLS) methods. To do this, we firstly analyzed effect of the percentage of total renewable energy in total energy on economic growth. Then, we tested the contribution of each renewable energy resources on economic growth as wind, solar, hydro, geothermal and biomass. The findings from OLS and DOLS show that total renewable energy generation has a positive impact on economic growth. Additionally, energy generation from geothermal and biomass have the highest impact on economic growth according to DOLS and OLS results.

Keywords: Renewable Energy, Dynamic Ordinary Least Square (DOLS), Economic Growth, Turkey, Energy Generation.

JEL Codes: Q42, Q43.

1 Türkiye Kalkınma ve Yatırım Bankası Saray Mahallesi, Dr. Adnan Büyükdeniz Cd. No10 34768 Ümraniye İstanbul.

Email: merve.serifoglu@kalkinma.com.tr http://orcid.org/0000-0002-5908-6772

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Özet

Yenilenebilir Enerji Üretimi ve Ekonomik Büyüme: Türkiye Örneği

Bu makalenin amacı Türkiye’de 2013: q2- 2020: q2 dönemi için En Küçük Kareler (EKK) ve Dinamik En Küçük Kareler (DEKK) yöntemi aracılığıyla yenilebilir enerji üretimi ve ekonomik büyüme arasında uzun dönemli ilişkiyi test etmektir. Bu amaçla, öncelikle toplam yenilenebilir enerji üretiminin toplam enerji kaynakları içindeki yüzdesinin ekonomik büyüme üzerindeki etkisi incelenmiştir. Daha sonra, rüzgâr, güneş, hidro, jeotermal ve biyokütle olmak üzere her bir yenilenebilir enerji kaynağının ekonomik büyüme üzerindeki etkisi analiz edilmiştir. EKK ve DEKK yöntemi ile elde edilen sonuçlarımız toplam yenilenebilir enerji üretiminin ekonomik büyümeyi pozitif etkilediğini göstermektedir. Ayrıca, EEK ve DEKK sonuçlarımıza göre, jeotermal ve biyokütleden elde edilen enerji üretimi ekonomik büyüme üzerinde en büyük etkiye sahiptir.

Anahtar Kelimeler: Yenilenebilir Enerji, Dinamik En Küçük Kareler Yöntemi (DEKK), Ekonomik Büyüme, Türkiye, Enerji Üretimi.

JEL Kodları: Q42, Q43.

Bu makalenin adını ve doi numarasını içeren aşağıdaki metni kolayca kopyalamak için soldaki QR kodunu taratınız.

Scan the QR code to the left to quickly copy the following text containing the title and doi number of this article.

Renewable Energy Generation and Economic Growth: Evidence from Turkey https://doi.org/10.5455/ey.19001

1. Introduction

Energy demand around the world is dramatically increasing. In the line with developments such as population growth, industrialization, increasing welfare and technological progress, it is expected that energy demand will be more increasing in the next years. However, fossil energy reserve is rapidly decreasing and does not naturally replenish. Additionally, it is obvious that the use of fossil energy cause to serious environmental problem in the world. So, renewable energy resources (solar, wind, geothermal, hydropower and biomass) is getting more and more important due to some reasons such as clean energy and replenishing through natural process.

Over the world, there has been progress in electricity generation from renewable energy sources in the last five years. In 2019, renewable energy installed capacity grew more than 200 GW and the share of electricity generation from renewable

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energy sources realized at around 26%. Also, renewable energy capacity installations and investment spread all over the world and the use of renewable energy system in electricity access and clean cooking services has increased in developed and emerging countries. Additionally, renewable energy has been recently preferred by private sector due to some reasons such as cost advantage, low carbon dioxide emissions (REN21, 2020). In this context, it is possible to say that the renewable energy has become popular energy source.

Following, we can see lots of study based on the effect of energy on economic activities in the literature. In this paper, the literature is classified into three parts:

studies on energy consumption- economic growth, electricity generation- economic growth and renewable electricity generation-economic growth. These studies attempt to explain the energy -economic growth nexus through various econometric methods including Autoregressive Distributed Lag Bound Test (ARDL), Granger Causality Test, Johansen cointegration test and panel data methods.

There is very extensive literature that focus on the relationship between energy consumption and economic growth. While majority of these studies have positive and significant correlation (Masih and Masih, 1998; Lee and Chang, 2008; Hondroyiannis et. al, 2012; Salim and Rafiq, 2012; Omri, 2013; Vidyarthi, 2013; Saidi and Hammami, 2014; Lin and Moubarek, 2014; Akay and Çağlayan, 2015; Kahia, 2016;

Özşahin et. al, 2016; Bakırtaş and Çetin, 2016; Ito, 2017; Destek and Sinva, 2020), there are rare studies that show negative or insignificant relationship between energy consumption and economic growth (Şentürk, 2012; Destek and Aslan, 2017). On the other hand, we can see that some authors focused on energy generation-economic growth link and found that there is long-run correlation between electricity generation and economic growth (Morimoto and Hope, 2004; Yoo and Kim, 2006; Gosh, 2009, Ellahi, 2011; Cerdeira, 2012; Khobai et. al, 2016). When we look at the studies conducted on renewable electricity generation-economic growth, there is not enough studies. Bayraktutan et al., (2011) analyzed the relationship between electricity

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generation from renewable sources and economic growth for OECD countries over 1980-2007 periods. They have used electricity generation obtained from total renewable energy sources as main indicator. Their findings obtained from panel data method show that electricity generation from renewable energy resources have positive effect on economic growth. Kazar and Kazar (2014) attempted to explain renewable electricity net generation and economic growth nexus for 154 countries from 1980 to 2010. In the model, Granger Causality test have been employed and there is a correlation between renewable energy generation and economic growth in short and long run. Atems and Hotaling (2018) examined the effect of renewable and nonrenewable electricity generation on economic growth for 174 countries over the period 1980-2012 through System Generalized Method of Moments (GMM). They find that there is positive and significant relationship between renewable electricity generation and growth. Dees and Auktor (2018) estimated the relationship between renewable energy and economic growth in the MENA region. They proved that there is positive correlation between renewable electricity and economic growth. In terms of studies on renewable energy generation and economic growth nexus in Turkey, Erdoğan et al., (2018) tested the effect of renewable electricity generation on economic growth in Turkey through Johansen Cointegration test and Vector Error Correction Model (VECM). Their study covers 1998-2015 periods and the percentage of total renewable energy in total electricity generation is used as determinant of energy variable. They have showed that there is long run relationship between renewable energy generation and economic growth and these variables are cointegrated. Usupbeyli and Uçak (2018) analyzed the contribution of renewable energy generation on economic growth from 1970 to 2017 for Turkey. Using ARDL model, they found that there is a positive correlation between renewable energy generation and economic growth. Temiz Dinç and Akdoğan (2019) reported that renewable energy generation positively affects economic growth in Turkey for 1980- 2016 periods by using VEC model. Özbek and Apaydın (2020) investigated the relationship between renewable energy generation and economic growth for the

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period of 1990-2017 through ARDL and showed that renewable energy production has positive effect on economic growth in Turkey.

Considering studies in the literature, it is clearly seen that they concentrate on energy consumption and economic growth link. This case is also valid for studies on Turkey.

There are limited studies on renewable electricity generation and economic growth nexus for Turkey and these studies are generally related to total renewable electricity generation. However, Turkey has a large potential in terms of renewable energy. It ranked fourth in the world for total geothermal power capacity. Also, it is the second country which grows the geothermal direct use for heating after China and takes place in ninth rank with 3% in terms of total global hydroelectricity capacity. Turkey is third rank in solar energy for heating purposes following China and United States (REN21, 2020). In this paper, we examine individually the effect of each renewable energy sources including wind, solar, hydro, geothermal, biomass in addition to total renewable electricity generation. Considering studies for Turkey, they are based on technical aspect of different types of renewable energy sources. So, we can say that this can be the first paper which shows the effect of renewable electricity sources by types on economic growth for Turkey through econometric methodology.

We employ Ordinary Least Square (OLS) and Dynamic Ordinary Least Square (DOLS) to check the long-term relationship between variables after determining stationary of series through Augmented Dickey Fuller (ADF) test (Dickey and Fuller, 1979). Based on ADF test results, all series are stationary at level (2). So, DOLS estimation method can be applied when the variables are stationary at level (2).

Although OLS is simple method, there can be some problems: OLS ignores dynamic structure in the model and produces inconsistent results for small samples (Akbaş and Şentürk, 2013). Firstly, our results from OLS and DOLS show that total renewable energy generation has positive and signification impact on economic growth. Also, we concluded that energy generation from geothermal and biomass contributes more than other renewables investigating in this paper. On the other hand, our findings

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Total (GWh) Production (Gross) Total (GWh) Consumption (Net)

indicate that the effect of wind energy resources on economic growth is lower than others. Following, we expect that our results lead to policy makers, energy authorities and regulatory institutions to determine renewable energy policies in Turkey. In this context, support-incentive methods should be developed for national companies and existing incentives should be made attractive for renewable energy generation.

This is five-section paper. Following introduction, Section 2 presents renewable energy generation in Turkey. Section 3 explains the data and model. Section 4 discusses empirical results and Section 5 concludes the paper.

2. Renewable Energy Generation in Turkey

In Turkey, energy consumption is rapidly grown in parallel to developments such as industrialization, increase in population and urbanization. Figure 1 shows the relationship between net energy consumption and gross energy generation.

Figure 1 Energy Consumption-Generation

Source: TURKSTAT (2020).

As seen in the Figure 1, energy generation has increased parallel to energy consumption, by years. In 2009, electricity generation and consumption amount

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1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Fossil Renewable Energy

decreased compared to previous year and generation and consumption amount realized 194,813 GWh and 156,894 GWh, respectively. In 2018, electricity generation was 304,802 GWh, electricity consumption was 258,232 GWh.

According to (TMMOB, 2020), 72.7% of consumption energy amount was obtained from import energy sources in 2018. In this context, Turkey aims to diversity of its energy resources to reduce this ratio. To do this, it carries out studies on potential of renewable energy sources as well as fossil energy resources. Figure 2 presents the percentage of fossil and renewable electricity generation in total energy generation from 1999 to 2018.

Figure 2 The Source of Electricity Generation (% total energy generation)

Source: TURKSTAT(2020).

While the share of energy generation from fossil is higher than renewable energy, the share of renewable energy has increased by years. The share of renewable energy sources in total energy production was 33.1% in 2017 and 29.6% in 2018. Figure 3 shows different types of renewable energy sources over 2017-2019 periods.

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Biomass Wind Solar Hydro Geothermal 2017 2018 2019

Figure 3 Renewable Energy Sources by Types

Source: TURKSTAT (2020).

When we look at the types of renewable energy sources, hydropower energy amount is higher than others (total hydropower amount; 88,822.80 GWh in 2019 and 59,938.00 GWh in 2018). Following hydropower, it is seen that wind power amount ranks second. After solar, it is seen that biomass and geothermal amount is lower than other renewables.

3. Data and model

In this paper, the relationship between renewable electricity generation and economic growth is investigated in Turkey by using quarterly time series data for 2013:2-2020:2 due to data availability. Gross Domestic Product (GDP) is obtained from Turkish Statistical Institute (TURKSTAT, 2020) and all renewable energy generation data is from Electricity Transparency Platform (EPIAŞ, 2020). We have used index t =1,2, 3…, T to denote time. The baseline model can be shown as below:

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In the equation 1, we use logarithmic transformation of GDP and (RE) is set of renewable energy variables: the percentage of wind, solar, hydro, geothermal, biomass in total energy generation and the percentage of total renewable energy in

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total energy generation. is the error term. Table 1 summarizes the descriptive statistics of all variables in the model.

Table 1 Descriptive Statistic

Variable Obs Mean Std Min Max

LogGDP 29 8.856 0.135 8.648 9.082

Wind 29 5.387 2.154 0.638 9.120

Solar 29 0.216 0.040 0.000 0.177

Hydro 29 6.335 3.972 0.406 14.484

Geo 29 1.725 0.981 0.000 3.754

Bio 29 0.676 0.324 0.257 1.596

Total 29 14.146 6.214 1.586 27.805

According to Table 1, it is seen that average GDP growth in Turkey is 8.9%.

Additionally, total renewable energy generation has the higher value than other variables in the model. In terms of renewable energy variables, the highest average belongs to hydro (6.3%) and wind (5.4%), respectively while the lowest value is solar (0.2%).

4. Empirical results 4.1. Unit Root Test

In this study, ADF test (Dickey and Fuller, 1979) is employed to whether the series are stationary or not. The baseline equation is as follows:

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where is first difference, t=1,2…, T is time trend and z show the lag order of autoregressive process. Lag order has been determined by Akaike Information Criteria (AIC). In the ADF test statistic, refers that variable contains a unit root and shows that variable is stationary. Table 2 presents ADF test statistical results.

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Table 2 ADF test results with constant term

Variables Levels First Diff Second Diff

LogGDP -0.448 -1.532* -3.398**

Wind -2.041** -3.634*** -5.488***

Solar 3.331 2.508 -4.962***

Hydro -2.146** -2.041** -4.551***

Geo 1.084 -2.256** -2.425**

Bio 3.546 0.462 -3.917**

Total -1.42* -2.22** -4.789***

*, **, *** indicates significant at 0.10, 0.05 and 0.01 level.

According to unit root test results, all variables in the model are stationary at 5% level after second difference, while some variables are stationary at level (0) and level (1).

So, it can be concluded that logGDP, Wind, Solar, Hydro, Geo, Bio and Total are stationary at I(2).

4.2. Long Run Estimation Results and Discussions

Based on our unit root test results, this paper employs OLS and DOLS estimation methods to investigate long run relationship between variables. OLS estimation method is used commonly method in the regression analysis and this method is the base technique which used simple linear and multiple regression analysis. OLS estimators are consistent but, “t” statistic for non- stationary series is only approximately normal. Even though OLS is consistent estimator for large finite samples, the convergence of OLS can be low in large infinite samples. Since OLS estimator ignores the dynamic structure, heteroskedasticity autocorrelation problem can be appeared (Sharma et.al, 2020).

To overcome these problems, three approaches have been developed: Fully modified ordinary least squares (FMOLS) (Hansen, 1992), canonical correlation regression (CCR) and dynamic ordinary least square (DOLS). The applicability of these approaches depends on the stationary conditions of series (Wang and Wu, 2012).

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While CCR is employed at I (1) and I (2) and FMOLS at I(1) variables, DOLS produces consistent and efficient results when some variables are I(0) and remaining elements are I(1) and I(2) (Stock and Watson, 1993). Considering our ADF results, DOLS is applied to test the relationship between renewable energy generation and economic growth, after OLS estimation. The baseline DOLS equation is as follows:

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In the equation 3, is dependent variable, explanatory variables matrix, cointegrating vector which represents the long-run cumulative multipliers or long-run effect of change in X on Y, p lag length and q lead length and error correction.

DOLS estimation consider small sample bias and endogeneity bias by including lags and leads of variables in the analysis and it eliminates the small sample problem and ignores the dynamic structure that occurs in the OLS (Sharma et al., 2020). For all DOLS models, the number of leads and lags are set to 2 as proposed by Stock and Watson (1993). Table 3 shows OLS and DOLS estimation results, respectively.

Table 3 OLS and DOLS test results

OLS DOLS

Variables

Wind 0.053*** 0.079***

(0.006) (0.005)

Solar 2.320*** 0.244

(0.478) (5.456)

Hydro 0.010 0.058*

(0.006) (0.035)

Geo 2.125*** 0.159***

(0.011) (0.003)

Bio 0.357*** 0.528***

(0.041) (0.037)

Total 0.014*** 0.034***

(0.003) (0.002)

const 8.571*** 8.806*** 8.795*** 8.641*** 8.615*** 8.651*** 8.414*** 8.792*** 8.488*** 8.566*** 8.544*** 8.343***

(0.037) (0.021) (0.046) (0.022) (0.030) (0.048) (0.040) (0.020) (0.240) (0.007) (0.013) (0.041)

Note: The standard error is in parentheses. *, **, *** indicates significant at 0.10, 0.05 and 0.01 level.

From Table 3, it is seen that the percentage of renewable energy in total energy has positive and significant impact on economic growth for results from OLS and DOLS.

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Also, our results obtained from two methods show that biomass and geothermal energy generation make the highest contribution on economic growth. As seen in the Table 3, a 1% increase in the geothermal energy generates approximately 0.2%-2.15% increase of economic growth. Additionally, a 1% increase in the biomass energy causes about 0.3%- 0.5% increase of economic growth. On the other hand, it is likely that the effect of wind energy generation on economic growth is lower than other variables excluding insignificant values, hydro value for OLS and solar value for DOLS.

Although the use of renewable energy increases in Turkey, the share of fossil energy is still quite high. However, the importance of renewable energy revealed due to limited fossil reserve amount. Our results also confirm the contribution of renewable energy on economic growth. In the line with our results and renewable potential of Turkey, renewable energy can be alternative to reduce energy import dependency for Turkey.

Geothermal energy is used various area including mainly electricity generation, residential heating, thermal-tourism treatment, and industry. Turkey, which has rich geothermal energy resources, is potentially seventh ranked in the world. It is estimated that Turkey’s geothermal heat potential is 31,500 MWt. On the other hand, Turkey is only used 3% of its geothermal energy potential (TMMOB, 2020). Considering our findings, geothermal energy is one of the renewables which have the highest effect on economic growth. Based on our results and Turkey’s geothermal energy potential, we can say that a part of Turkey’s energy needs can be met by geothermal energy.

Biomass has important place in global energy economy. It plays major role to reduce greenhouse emissions from especially transportation sector. It uses to produce transport fuel based on biomass. After solar energy sector, biomass energy sector is second ranked among renewable energy technologies in terms of employment (TMMOB, 2020). Our findings also support that there is a strong and positive relationship between biomass energy and economic growth. When we look at the Turkey’s energy policies, mainly Zero Waste project, the importance of biomass energy is gradually increasing. So, effective waste management policies should be developed based on our results and biomass potential.

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5. Conclusion

In the line with its growing economy and population, Turkey’s energy demand is rapidly increasing. The traditional resources to be used for energy generation is limited and Turkey depends on outside financial sources for oil and natural gas.

However, it has favorable geographic location in terms of diversity of renewable energy resources. The main renewable energy resources in Turkey are hydropower, biomass, wind, solar and geothermal.

In this study, we attempt to investigate the effect of different types of renewable energy and total renewable energy resources on economic growth for Turkey using quarterly data from 2013: q2 to 2020: q2. The main indicators in model are the percentage of total renewable energy resources in total energy sources and the percentage of each renewable energy sources (wind, solar, hydro, geothermal and biomass) in total energy sources. To do this, we firstly tested whether the series are stationary or not through ADF unit root test. After we determined that all series are stationary at level (2), we employed OLS and DOLS estimation methods. Our results obtained from two methods show that the percentage of renewable energy sources in total energy sources have positively impact on economic growth and renewable energy from biomass and geothermal make the highest contribution on economic growth considering types of renewable energy sources.

Turkey has high renewable energy potential and aims to total 56,804 MW installed capacity based on renewable energy resources including 10,000 MW in solar, 11,883 MW in wind, 32,037 MW in hydro, 2,884 MW in biomass and geothermal in 2023 (Enerji ve Tabii Kaynaklar Bakanlığı, 2019). Based on our results, we can also say that renewable energy has positive and significant on economic growth. When we look at the development of renewable energy sources in Turkey, in addition to Ministry of Energy and Natural Resources, some regulations have been made since 2000s.In 2003, establishment of Energy Market Regulatory Authority is the first step

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in this direction. Following, it can be said that the enacting of law on the Utilization of Renewable Energy Sources (RES) in 2005 is an important progress for generating energy from renewable energy sources. RES Act consist of incentive and support mechanisms for renewable energy investments. In this context, Renewable Energy Resources Area (YEKA) and Renewable Energy Support Mechanism (YEKDEM) are two main support mechanism which have important role in increasing of installed capacity. While the YEKDEM guarantees the purchase through foreign exchange, the YEKA aims to create large scale renewable energy investment (1,000 MW of installed capacity) and state provides limited time purchase guarantee for electricity generated. Although all these developments are important for generating of energy from renewable energy sources, existing regulations may be developed and created new financing and incentive mechanisms, which support for renewable energy should be more effective. Electricity market legislation should be arranged to give priority to renewable energy. Instead of thermal power plants, the finance should be provided to renewable energy sources. Additionally, renewable energy should be part of industry policy in Turkey like China, Germany, Denmark. In parallel with the use of renewable energy in these countries, there has been an increase in manufacture, export and employment related to renewable energy sector (WWF & BNEF, 2014). On the other hand, Turkey is a country which rich in geothermal energy resources. As in 2018, Turkey and Indonesia ranked first for new geothermal power generating capacity in 2019 (REN21, 2020). Additionally, our results indicate that the contribution of geothermal and biomass energy on economic growth are higher than other renewables. Considering that geothermal energy is used in the various area including electricity generation, heating, industrial, thermal, geothermal energy exploration activities should be extended and both technical and financial support should be provided by relevant authorities. In terms of biomass potential, Turkey’s annual recoverable bioenergy potential has been determined 16.92 million TEP (TMMOB, 2020). Effective waste segregation system should be applied for recycling and waste disposal. Also, waste import should be prevented (TMMOB, 2020). Hence, energy

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generation from renewable energy sources in Turkey should be supported through various mechanisms including renewable energy policies, incentives, and financing mechanism.

References

Akay, Ç. E., & Abdieva, R., & Oskonbaeva, Z. (2015). Yenilenebilir Enerji Tüketimi, İktisadi Büyüme ve Karbondioksit Emisyonu Arasındaki Nedensel İlişki : Orta Doğu ve Kuzey Afrika Ülkeleri Örneği. International Conference on Eurasiasin Economies, Kazan, Rusya, 628–636.

Akbaş, Y. E. & Ş. M. (2013). Mena ülkelerı nde elektrı k tüketı mı ı le ekonomı k büyüme arasindakı karşilikli ı lı şkı nı n analı zı . Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 41, 45–67.

Atems, B., & Hotaling, C. (2018). The effect of renewable and nonrenewable electricity generation on economic growth. Energy Policy, 112, 111–118. https://doi.org/10.1016/j.enpol.2017.10.015 Bakırtaş, İ., & Çetin, M. A. (2016). Yenilenebilir Enerji Tüketimi İle Ekonomik Büyüme Arasındaki

İlişki: G-20 Ülkeleri. Sosyoekonomi, 24(28). https://doi.org/10.17233/se.43089.

Bayraktutan, Y., & Yilgör, M., & Uçak, S. (2011). Renewable electricity generation and economic growth: Panel-data analysis for OECD members. International Research Journal of Finance and Economics, 66, 59–66.

Cerdeira, J. B. (2012). The role of foreign direct investment in the renewable electricity generation and economic growth nexus in Portugal: a cointegration and causality analysis. MPRA, 41533, 0–

33.

https://mpra.ub.uni-muenchen.de/41533/1/MPRA_paper_41533.pdf (Accessed date:15.11.2020)

Deeds, P., & Auktor, G. V. (2018). Renewable energy and economic growth in the MENA region:empirical evidence and policy implications. Middle East Development Journal, 10(2), 225–247.

Destek, M. A., & Çetin, M. A. (2017). Renewable and non-renewable energy consumption and economic growth in emerging economies:evidence from bootstrap panel causality. Renewable Energy, 111, 757–763.

Destek, M. A., & Sinha, A. (2020). Renewable, non-renewable energy consumption, economic growth, trade openness and ecological footprint:evidence from organisation for economic co-operation and development countries. Journal of Cleaner Production, 242.

Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series

(16)

with a unit root. Journal of the American Statistical Association, 74, 427–431.

Ellahi, N. (2011). Testing the relationship between electricity supply, development of industrial sector and economic growth: An empirical analysis using time series data for Pakistan. International Journal of Management Science and Engineering Management, 6(4), 272–277.

https://doi.org/10.1080/17509653.2011.10671173

Enerji ve Tabii Kaynaklar Bakanlığı. (2019). Enerji ve Tabii Kaynaklar Bakanlığı Stratejik Plan:

2019-2023. https://sp.enerji.gov.tr/ETKB_2019_2023_Stratejik_Plani.pdf (Accessed date:

11.11.2020)

Erdoğan, S., & Dücan, E.,& Şentürk, M., & Şentürk, A. (2018). Türkiye’de Yenı lenebı lı r Enerji Üretı mı ve Ekonomı k Büyüme İlı şkı sı Üzerı ne Ampı rı k Bulgular. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 11(2), 233–246.

https://doi.org/10.25287/ohuiibf.382686

EPIAŞ (2020). Gerçekleşen Üretim. https://seffaflik.epias.com.tr/transparency/(Accessed date:11.11.2020)

Gosh, S. (2009). Electricity supply employment and real GDP cointegration and Granger causality tests. Energy Policy, 37, 2926–2929.

Hansen, B. E. (1992). Tests for parameter instability in regressions with I(1) processes. Journal of Business and Economic Statistics, 10, 321–335.

Hondroyiannis, G., & Lolos, S., & Papapetrou, E. (2002). Energy consumption and economic growth:

assesing the evidence from Greece. Energy Economics, 24(2), 319–336.

Ito, K. (2017). CO2 emissions, renewable and non-renewable energy consumption, and economic growth, evidence from panel data for developing countries. International Economics, 151, 1–

6.

Kahia, M., & Aissa, M. S. B., & Charfeddine, L. (2016). Impact of renewable and nonrenewable energy cınsumption on economic growth: new evidence from the MENA net oil exporting countries (NOECs). Energy, 116, 102–115.

Kazar, G., & Kazar, A. (2014). The renewable energy production-economic development Nexus.

International Journal of Energy Economics and Policy, 4(2), 312–319.

Khobai, H., & Abel, S., & Le Roux, P. (2016). Co-integration between electricity supply and economic growth in South Africa. International Journal of Energy Economics and Policy, 6(3), 637–

645.

Lee, C., & Chang, C. (2008). Energy consumption and economic growth in Asian economies:a more comprehensive analysis using panel data. Resource and Energy Economics, 30, 50–65.

Lin, B., & Moubarek,M. (2014). Renewable energy consumption-economic growth nexus for China.

Energy Reviews, 40, 111–117.

(17)

Masih, M. M., & Masih, R. (1998). Energy consumption,real income and temporal causality :results from a multi-country study based on co-integration and error-correction modeling techniques.

Energy Economics, 18, 165–183.

Morimoto, R., & Hope, C. (2004). The impact of electricity supply on economic growth in SriLanka.

Journal of Energy Economics, 26, 77–85.

Omri, A. (2017). CO2 emissions, Energy Consumption and Economic Growth Nexus in MENA countries : Evidence from Simultaneous Equations Model. Energy Economics, 40, 657-664.

Özbek, R. & Apaydın, Ş. (2020). The Role of Renewable Energy Generation in Sustainable Economic Growth: The Case of Turkey. Fiscaoeconomia, 4(3), 554-567.

Özşahin, Ş., & Mucuk, M., & Gerçeker, M. (2016). Yenilenebilir Enerji ve Ekonomik Büyüme Arasındaki İlişki: BRICS-T Ülkeleri Üzerine Panel ARDL Analizi. Siyaset, Ekonomi ve Yönetim Araştırmaları Dergisi, 4(4), 111–130.

REN21 (2020). Renewables Global Status Report.

https://www.ren21.net/wp-content/uploads/2019/05/gsr_2020_full_report_en.pdf (Accessed date:15.11.2020)

Saidi, K., & Hammami, S. (2014). Energy Consumption and Economic Growth Nexus: Empirical Evidence from Tunisia. American Journal of Energy Research, 2(4), 81–89.

https://doi.org/10.12691/ajer-2-4-2

Salim, R. A., & Rafiq, S. (2012). Why do some emerging economies proactively accelerate the adoption of renewable energy? Energy Economics, 34(4), 1051–1057.

https://doi.org/10.1016/j.eneco.2011.08.015

Sharma, R. K., & Bakshi, A., & Chhabra, S. (2020). Determinants of behaviour of working capital requirements of BSE listed companies: An empirical study using co-integration techniques and generalised method of moments. Cogent Economics and Finance, 8(1), 1–30.

https://doi.org/10.1080/23322039.2020.1720893

Stock, J. H., &Watson, M. W. (1993). A simple estimator of cointegrating vectors in higher order integrated systems. Econometrica, 61(4), 783–820.

Şentürk, İ. (2012). Kaynaklarına göre Enerji Tüketiminin Ekonomik Büyümeye Etkileri (Doctoral dissertation). Available from Hacettepe Üniversitesi Sosyal Bilimler Enstitüsü İktisat A.B.D.

Temiz Dinç,D., & Akdoğan, E. (2019). Renewable Energy Production, Energy Consumption and Sustainable Economic Growth in Turkey: A VECM Approach. Sustainability, 11(5), 1-14.

https://doi.org/10.3390/su11051273.

TMMOB (2020). Türkiye’nin Enerji Görünümü 2020. https://www.mmo.org.tr/kitaplar/turkiyenin- enerji-gorunumu-2020 (Accessed date:15.11.2020)

TURKSTAT (2020). Çevre ve Enerji İstatistikleri. https://data.tuik.gov.tr/ Accessed date:8.11.2020)

(18)

Usupbeyli, A., & Uçak, S. (2018). Türkiye'de Yenilenebilir Enerji-Büyüme İlişkisi. MCBÜ Sosyal Bilimler Dergisi , 16(4), 223–238. https://doi.org/10.18026/cbayarsos.505977.

Vidyarthi, H. (2013). Energy consumption, carbon emissions and economic growth in India. World Journal of Science,Technology and Sustainable Development, 10(4), 278–287.

Wang, Q., & Wu, N. (2012). Long-run covariance and its applications in cointegration regression. Stata Journal, 12(3), 515–542. https://doi.org/10.1177/1536867x1201200312.

WWF & BNEF (2014). Türkiye’nin Yenilenebilir Gücü: Türkiye için Alternatif Elektrik Enerjisi Arz Senaryoları.

http://awsassets.wwftr.panda.org/downloads/wwf_turkiye_turkiye_nin_yenilenebilir_gucu_raporu_1.p df (Accessed date:8.11.2020)

Yoo, S. H., & Kim, Y. (2006). Electricity generation and economic growth in Indonesia. Energy Policy, 34, 2890–2899.