The Effect of Renewable Energy Consumption on Sustainable Economic Development: Evidence from Emerging and Developing Economies
Abstract
:1. Introduction
2. Literature Review
3. Materials and Methods
3.1. Definition of Renewable Energy and Sustainable Development
3.2. Description of Variables and Countries in the Research
3.3. Methodology
4. Results and Discussion
4.1. Panel Unit Root Test
4.2. Panel Co-Integration Test
4.3. Fully Modified Ordinary Least Square (FMOLS)
4.4. Dynamic Ordinary Least Square (DOLS)
4.5. Country-Specific FMOLS Long-Run Elasticity Analysis
4.6. Pair-Wise Dumitreschu and Hurlin Causality Test
5. Conclusions, Limitations and Further Scope of the Study
Author Contributions
Funding
Conflicts of Interest
References
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Study | Method | Period | Countries | Findings |
---|---|---|---|---|
Energy/Renewable Energy Consumption and Economic Growth Nexus | ||||
Kraft and Kraft (1978) [4] | Granger causality test | 1947–1974 | USA | Gross Domestic Product (GDP) determines energy consumption; (Conservation hypo.) |
Soytas et al. (2001) [5] | Co-integration methodology | 1960–1995 | Turkey | Energy consumption contributes to GDP growth (Growth hypo.) |
Ewing et al. (2007) [6] | Autoregressive Distributed Lag (ARDL) model | 2001–2005 | USA | GDP determines energy consumption (Conservation hypothesis) |
Akinlo A.E. (2008) [7] | Autoregressive Distributed Lag (ARDL) model, Granger causality test based on vector error correction model (VECM) | 1980–2003 | 11 Sub Saharan African countries | For Gambia, Ghana and Senegal, there is bi-directional causality between energy consumption and economic growth. |
Cheng et al. (2009) [8] | Panel co-integration test | 1997–2007 | 30 OECD countries | GDP determines energy consumption (Conservation hypo.) |
Sadorosky P. (2009) [9] | Fully Modified OLS (FMOLS) for panel | 1994–2003 | 18 emerging countries | GDP determines renewable energy consumption; (Conservation hypo.) |
Apergis and Payne (2010) [10] | Panel co-integration test | 1985–2005 | 20 OECD countries | Bi-directional relationship between GDP and energy consumption (Feedback hypo.) |
Payne (2010) [11] | Granger causality test | 1949–2007 | USA | Biomass energy consumption contributes to GDP growth (Growth hypo.) |
Apergis and Payne (2011) [12] | Panel co-integration test | 1980–2006 | 6 Central American countries | Energy consumption contributes to GDP growth (Growth hypo.) |
Menegaki A.N. (2011) [13] | Random effect model | 1997–2007 | 27 European countries | Energy consumption and economic growth are independent from each other (Neutrality hypothesis) |
Fang Y. (2011) [14] | Ordinary least square (OLS) | 1978–2008 | China | Renewable energy consumption contributes to GDP growth (Growth hypo.) |
Tiwari A.K. (2011) [15] | Structural vector autoregressive (VAR) analysis | 1960–2009 | India | Renewable energy consumption contributes to GDP growth (Growth hypo.) |
Shahbaz M. et al. (2012) [16] | Unit roots, Autoregressive Distributed Lag (ARDL) model and Granger causality | 1972–2011 | Pakistan | In both long and short run, energy consumption and economic growth has bi-directional causality (Feedback hypothesis). |
Bildirici (2014) [17] | Fully Modified OLS (FMOLS) for panel | 1990–2011 | Transition economies | Biomass energy consumption contributes to GDP growth (Growth hypo.) |
Bildirici and Ozaksoy (2014) [18] | Granger causality test | 1980–2011 | European transition economies | GDP determines renewable energy consumption; (Conservation hypo.) for Slovenia and Slovakia; Renewable energy consumption contributes to GDP growth for Bulgaria and Romania (Growth hypo.) |
Caraiani Chirata et al. (2015) [19] | Engle and Granger causality tests | 1980–2013 | 5 emerging European countries | GDP determines renewable energy consumption for Hungary, Poland and Turkey (Conservation hypo.); Renewable energy consumption contributes to GDP growth for Romania (Growth hypo.) |
Bildirici and Ersin (2015) [20] | Causality test | 1970–2013 | UK, Canada, Germany, Austria, Finland, France, Italy, Mexico, Portugal and the USA | In USA bi-directional relationship between GDP and renewable energy consumption (Feedback hypo.) and for other countries, GDP determines renewable energy consumption; (Conservation hypo.) |
Bloch H. et al. (2015) [21] | Autoregressive Distributed Lag (ARDL) model and vector error correction model (VECM) | 1969, 1973, 1997, 1998, 2001, 2002, 2003 | China | Bi-directional causality between renewable, non-renewable energy consumption and economic growth (Feedback hypo.) |
Paramati R. Sudarshan et al. (2017) [22] | Panel unit root test, panel co-integration and Fully Modified OLS (FMOLS) | 1980–2012 | 17 countries of the G20 | Both renewable and non-renewable energy consumption have significant positive impact on economic output and the impact of renewable energy consumption on economic growth is more than non-renewable energy consumption. |
GDP, Energy Consumption and Emissions Nexus | ||||
Kaygusuz et al. (2007) [23] | Analysis of reports of European Commission and European Energy Council | 2001–2004 | EU-15 Member States | Wind energy plays significant role in reducing emissions. |
Sadorosky P. (2009) [9] | Pedroni co-integration test and Granger causality test | 1994–2003 | 18 emerging countries | In the long run there exists conservation hypothesis, while in the short run neutrality hypothesis between energy consumption and emissions |
Menyah and Wolde-Rufael (2010) [24] | Granger causality test | 1960–2007 | USA | Unidirectional causal flow from economic growth to carbon emissions. |
Apergis (2010) [25] | Causal dynamics | 1984–2007 | 19 developing countries | Feedback hypothesis between renewable energy consumption and emissions. |
Odhiambo (2012) [26] | Causal dynamics | 1970–1997 | South Africa | Unidirectional causal flow from economic growth to carbon emissions. |
Farhani S. (2013) [27] | Panel co-integration test | 1975–2008 | 12 Middle East and North African (MENA) countries | In short term, growth hypothesis and in long-term conservation hypothesis between energy consumption and emissions. |
Omri A. (2013) [28] | Ordinary least square (OLS) | 1990–2011 | Middle East and North African (MENA) countries | GDP has positive and significant impact, but financial development and capital have negative impact on emissions. |
Zeb R. et al (2014) [29] | Panel granger causality and Fully Modified OLS (FMOLS) | 1975–2010 | 5 SAARC countries (Bangladesh, India, Nepal, Pakistan, and Sri Lanka) | Granger causality results suggest about neutrality hypothesis between renewable electricity production and
emissions. The evidence of growth hypothesis between them in FMOLS approach. |
Payne et al. (2014) [30] | Panel co-integration and vector error correction model (VECM) | 1980–2011 | 25 OECD countries | The evidence of feedback hypothesis between renewable energy consumption and emissions. |
Mbarek, M.B (2014) [31] | Autoregressive Distributed Lag (ARDL) bounds testing approach to co-integration and error correction model (ECM) | 1980–2010 | Tunisia | Unidirectional relationship between GDP and emissions in the short run. |
Bouznit, M. et al. (2016) [32] | Autoregressive Distributed Lag (ARDL) model | 1970–2010 | Algiers | A co-integration relationship between emissions, real GDP and energy use. |
Mitic Petar et al. (2017) [33] | Dynamic Ordinary Least Squares (DOLS) and Fully Modified OLS (FMOLS) | 1997–2014 | 17 transitional economies | Statistically significant long run co-integrating relationship between emissions and GDP. |
Y | REC | NREC | K | L | |
---|---|---|---|---|---|
82.75 *** | 39.20 *** | 59.21 *** | 64.85 *** | 93.33 *** | 63.52 *** |
(0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) |
Y | REC | NREC | K | L | ||
---|---|---|---|---|---|---|
Level | 0.922 (0.800) | 3.127 (0.999) | 3.605 (0.999) | 0.980 (0.792) | 1.734 (0.959) | 0.758 (0.690) |
First difference | −2.924 *** (0.002) | −2.904 *** (0.002) | −3.612 *** (0.000) | −1.173 ** (0.030) | −2.694 *** (0.004) | −3.125 *** (0.001) |
Statistics | Probability | Weighted Statistics | Probability | |
---|---|---|---|---|
Panel v-Statistic | 0.804310 | 0.2106 | 0.064938 | 0.4741 |
Panel ρ-Statistic | 4.941484 | 1.0000 | 4.115011 | 1.0000 |
Panel PP-Statistic | −1.46635 ** | 0.04417 | −1.724000 ** | 0.0362 |
Panel ADF-Statistic | −3.713810 *** | 0.0001 | −1.902167 ** | 0.0286 |
Statistics | Probability | |
---|---|---|
Group ρ-Statistic | 6.183689 | 1.0000 |
Group PP-Statistic | −3.057068 *** | 0.0011 |
Group ADF-Statistic | −1.314386 ** | 0.0244 |
Statistics | Probability | Weighted Statistics | Probability | |
---|---|---|---|---|
Panel v-Statistic | 0.686047 | 0.2463 | 1.909063 | 0.9719 |
Panel ρ-Statistic | 1.947982 ** | 0.0257 | 1.066686 | 0.1431 |
Panel PP-Statistic | −7.742661 *** | 0.0000 | −6.996249 *** | 0.0000 |
Panel ADF-Statistic | −4.600051 *** | 0.0000 | −5.659427 *** | 0.0000 |
Statistics | Probability | |
---|---|---|
Group ρ-Statistic | 0.535848 | 0.7040 |
Group PP-Statistic | −8.371437 *** | 0.0000 |
Group ADF-Statistic | −5.158757 *** | 0.0001 |
Dependent Variable | Independent Variable | Co-Efficient | Probability |
---|---|---|---|
Model-I | |||
Log Y | Log REC | 0.176 *** | 0.002 |
Log NREC | 0.253 *** | 0.001 | |
Log L | 0.702 *** | 0.000 | |
Log K | 0.368 *** | 0.000 | |
Model-II | |||
Log | Log Y | 0.436 *** | 0.000 |
Log REC | −0.107 ** | 0.019 | |
Log NREC | 0.558 *** | 0.000 |
Dependent Variable | Independent Variable | Co-Efficient | Probability |
---|---|---|---|
Model-I | |||
Log Y | Log REC | 0.201 *** | 0.002 |
Log NREC | 0.285 *** | 0.000 | |
Log L | 0.533 *** | 0.000 | |
Log K | 0.254 *** | 0.000 | |
Model-II | |||
Log CO2 | Log Y | 0.378 *** | 0.000 |
Log REC | −0.103 ** | 0.047 | |
Log NREC | 0.662 *** | 0.000 |
Region | Country | Log REC | Log NREC | Log L | Log K | R² | Adj. R² |
---|---|---|---|---|---|---|---|
South Asia | India | 1.390 *** | 0.618 *** | 0.773 *** | 0.044 | 0.999 | 0.999 |
Bangladesh | 0.542 *** | −0.031 | 0.799 *** | 0.823 *** | 0.999 | 0.999 | |
Pakistan | 1.722 *** | 0.210 * | 0.265 | 0.190 *** | 0.997 | 0.996 | |
Sri Lanka | −0.114 | 0.276 ** | 0.391 | 0.669 *** | 0.987 | 0.983 | |
Nepal | 0.379 ** | 0.031 | 1.259 *** | 0.140 ** | 0.996 | 0.994 | |
Bhutan | 1.900 *** | 0.073 *** | 0.625 *** | 0.034 ** | 0.998 | 0.998 | |
Asia | Malaysia | −0.179 *** | 0.368 *** | 0.889 *** | 0.180 *** | 0.996 | 0.995 |
Indonesia | 0.396 *** | −0.046 | 0.992 *** | 0.476 *** | 0.996 | 0.994 | |
China | 0.501 ** | 0.127 | 1.106 ** | 0.721 *** | 0.997 | 0.997 | |
Philippine | −0.040 | 0.318 ** | 1.030 *** | 0.553 *** | 0.997 | 0.966 | |
Thailand | 0.373 *** | 0.307 ** | 0.986 *** | 0.087 *** | 0.994 | 0.992 | |
Korea | −0.032 | 0.112 *** | 4.090 *** | 0.110 | 0.988 | 0.984 | |
Latin America | Columbia | 0.058 | 0.617 *** | 0.643 *** | 0.127 *** | 0.995 | 0.994 |
Ecuador | 0.019 | 0.347 *** | 0.385 *** | 0.239 *** | 0.990 | 0.988 | |
Peru | 0.112 | 0.208 ** | 0.736 ** | 0.227 *** | 0.995 | 0.994 | |
Costa Rica | 0.105 ** | −0.118 | 0.893 *** | 0.342 | 0.982 | 0.977 | |
Bolivia | 0.074 | 1.853 *** | 1.179 *** | 1.194 *** | 0.996 | 0.995 | |
Africa | Ghana | 0.516 *** | 0.186 ** | 2.780 *** | 0.195 ** | 0.989 | 0.987 |
Mozambique | 0.026 | −0.083 | 3.116 *** | 0.040 | 0.992 | 0.990 | |
Senegal | −0.035 | 0.274 ** | 0.366 | 0.243 | 0.990 | 0.987 | |
Chad | −3.608 ** | 0.313 *** | 3.101 *** | 0.056 | 0.980 | 0.976 | |
Nigeria | 0.210 ** | 0.478 *** | 0.232 | 0.321 *** | 0.985 | 0.981 | |
Kenya | 0.002 | −0.201 | 0.631 | 0.369 *** | 0.990 | 0.988 | |
Zimbabwe | 1.976 *** | 1.036 *** | 0.951 | 0.062 *** | 0.887 | 0.857 | |
Tunisia | 0.281 *** | 0.281 ** | 1.290 *** | 0.063 | 0.997 | 0.996 | |
South Africa | 1.072 *** | 0.0035 | 0.006 | 0.269 *** | 0.997 | 0.996 | |
Uganda | −0.253 ** | −0.082 | 1.586 *** | 0.228 *** | 0.997 | 0.996 | |
Cameroon | 0.134 ** | −0.054 | 1.408 *** | 0.010 | 0.997 | 0.996 | |
Caribbean | Haiti | 0.018 | −0.038 | 0.100 | 0.190 *** | 0.891 | 0.862 |
Jamaica | −0.050 | 0.074 *** | 0.632 *** | 0.188 *** | 0.913 | 0.890 |
Region | Country | Log Y | Log REC | Log NREC | R² | Adj. R² |
---|---|---|---|---|---|---|
South Asia | India | 0.394 * | −1.237 | 0.935 *** | 0.995 | 0.994 |
Bangladesh | 0.040 | −0.000 | 1.133 *** | 0.996 | 0.995 | |
Pakistan | 0.044 | 0.093 | 1.127 *** | 0.993 | 0.991 | |
Sri Lanka | 0.312 *** | −0.702 ** | 1.159 *** | 0.981 | 0.977 | |
Nepal | 2.172 *** | −2.752 *** | 0.716 *** | 0.993 | 0.921 | |
Bhutan | 0.603 ** | 1.851 * | 1.114 *** | 0.976 | 0.970 | |
Asia | Malaysia | 1.103 *** | −1.295 *** | −0.137 | 0.957 | 0.949 |
Indonesia | 0.738 *** | −0.973 | 0.798 | 0.902 | 0.896 | |
China | 0.041 | −0.144 | 1.084 *** | 0.997 | 0.996 | |
Philippine | 0.393 *** | 0.159 | 0.796 *** | 0.926 | 0.912 | |
Thailand | 0.093 | −0.153 ** | 1.138 *** | 0.995 | 0.994 | |
Korea | 0.598 *** | −0.167 *** | 0.865 *** | 0.965 | 0.959 | |
Latin America | Columbia | 0.055 | 0.164 | 1.458 *** | 0.917 | 0.902 |
Ecuador | 1.032 ** | −0.187 | 0.120 | 0.913 | 0.897 | |
Peru | 0.774 *** | 0.047 | 0.329 | 0.950 | 0.937 | |
Costa Rica | 0.023 | 0.235 *** | 0.758 ** | 0.952 | 0.944 | |
Bolivia | 0.817 *** | 0.385 | 0.032 | 0.907 | 0.890 | |
Africa | Ghana | 0.764 ** | 0.202 | 0.118 | 0.906 | 0.889 |
Mozambique | 0.216 | −0.529 | 1.730 *** | 0.961 | 0.953 | |
Chad | 0.393 ** | 1.075 | 0.418 *** | 0.990 | 0.989 | |
Nigeria | 0.881 *** | −0.661 *** | 0.143 | 0.977 | 0.973 | |
Kenya | 0.841 * | −1.790 *** | 1.180 *** | 0.936 | 0.924 | |
Tunisia | 0.444 *** | −0.220 *** | 0.620*** | 0.993 | 0.991 | |
South Africa | 0.457 | −0.896 ** | 0.739 *** | 0.923 | 0.909 | |
Uganda | 0.654 ** | 0.088 | 0.646 ** | 0.993 | 0.992 | |
Cameroon | 0.420 | 0.527 | 1.180 *** | 0.910 | 0.897 | |
Senegal | 2.00 *** | 0.251 | 0.834 *** | 0.830 | 0.800 | |
Zimbabwe | 0.042 | −0.156 | 1.230 *** | 0.824 | 0.792 | |
Caribbean | Haiti | 0.245 | 0.378 *** | 0.761 *** | 0.991 | 0.990 |
Jamaica | 2.224 *** | −0.142 | 0.718 *** | 0.892 | 0.863 |
Null Hypothesis | Zbar-Stat | Probability |
---|---|---|
Log REC does not homogeneously cause Log Y | 2.257 ** | 0.0240 |
Log Y does not homogeneously cause Log REC | 4.427 *** | 0.0001 |
Log NREC does not homogeneously cause Log Y | 1.996 ** | 0.0459 |
Log Y does not homogeneously cause Log NREC | 6.464 *** | 0.0000 |
Log K does not homogeneously cause Log Y | 3.306 *** | 0.0009 |
Log Y does not homogeneously cause Log K | 9.349 *** | 0.0000 |
Log L does not homogeneously cause Log Y | 4.942 *** | 0.0000 |
Log Y does not homogeneously cause Log L | 7.848 *** | 0.0000 |
Log NREC does not homogeneously cause Log REC | 2.978 *** | 0.0029 |
Log REC does not homogeneously cause Log NREC | 2.830 *** | 0.0047 |
Log K does not homogeneously cause Log REC | 0.904 | 0.3661 |
Log REC does not homogeneously cause Log K | 3.488 *** | 0.0005 |
Log L does not homogeneously cause Log REC | 30.49 *** | 0.0000 |
Log REC does not homogeneously cause Log L | 3.817 *** | 0.0010 |
Log K does not homogeneously cause Log NREC | 5.971 *** | 0.0000 |
Log NREC does not homogeneously cause Log K | 2.248 ** | 0.0246 |
Log L does not homogeneously cause Log NREC | 7.069 *** | 0.0000 |
Log NREC does not homogeneously cause Log L | 5.446 *** | 0.0000 |
Log L does not homogeneously cause Log K | 7.993 *** | 0.0000 |
Log K does not homogeneously cause Log L | 3.717 *** | 0.0002 |
Log Y does not homogeneously Cause Log CO2 | 10.748 *** | 0.0000 |
Log CO2 does not homogeneously Cause Log Y | 3.203 *** | 0.0014 |
Log REC does not homogeneously Cause Log CO2 | 1.396 | 0.1627 |
Log CO2 does not homogeneously Cause Log REC | 2.000 ** | 0.0455 |
Log NREC does not homogeneously Cause Log CO2 | 4.822 *** | 0.0000 |
Log CO2 does not homogeneously Cause Log NREC | 2.475 ** | 0.0133 |
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Ahmed, M.M.; Shimada, K. The Effect of Renewable Energy Consumption on Sustainable Economic Development: Evidence from Emerging and Developing Economies. Energies 2019, 12, 2954. https://doi.org/10.3390/en12152954
Ahmed MM, Shimada K. The Effect of Renewable Energy Consumption on Sustainable Economic Development: Evidence from Emerging and Developing Economies. Energies. 2019; 12(15):2954. https://doi.org/10.3390/en12152954
Chicago/Turabian StyleAhmed, Mun Mun, and Koji Shimada. 2019. "The Effect of Renewable Energy Consumption on Sustainable Economic Development: Evidence from Emerging and Developing Economies" Energies 12, no. 15: 2954. https://doi.org/10.3390/en12152954