Skip to main content

Advertisement

SpringerLink
Log in

Determinants of renewable and non-renewable energy consumption in hydroelectric countries

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

In the past decades, renewable energy consumption has grown considerably because of environmental degradation caused by non-renewable energy consumption. This research aims to find the causal link between renewable and non-renewable energy consumption, human capital, and non-renewable energy price for the 53 most renewable energy-consuming countries worldwide (hydroelectric) during the period 1990–2017. We use data collected from the World Bank (http://data.worldbank.org/data-catalog/world-development-indicators, 2018) and Statistical Review of World Energy (https://www.bp.com/, 2018). We test simultaneously two types of regressions in order to measure the degree of elasticity of the two types of energy by using econometric techniques for panel data. The results of the GLS models indicate that human capital has a stronger significant effect on renewable energy consumption at the global level, in the middle high-income countries and low-middle income countries, compared with non-renewable energy consumption. Besides, at the global level, there is a positive and statistically significant relationship between the non-renewable energy price and the two types of energy consumption. There is a long-run consumption of both types of energy. On the other hand, the one-way relationship between human capital and non-renewable energy price and renewable energy consumption is stronger than the relationship with non-renewable energy consumption. The policy implications derived from this study should be designed to promote human capital development in order to promote renewable energy consumption and increase the investment in renewable energy sources to guarantee their access to lower prices that reduce non-renewable energy consumption.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19(6):716–723

    Google Scholar 

  • Al-Maamary HM, Kazem HA, Chaichan MT (2017) The impact of oil price fluctuations on common renewable energies in GCC countries. Renew Sust Energ Rev 75:989–1007

    Google Scholar 

  • Al-Mulali U (2014) Investigating the impact of nuclear energy consumption on GDP growth and CO2 emission: a panel data analysis. Prog Nucl Energy 73:172–178

    CAS  Google Scholar 

  • Alizadeh S, Brandt MW, Diebold FX (2002) Range based estimation of stochastic volatility models. The Journal of Finance 57(3):1047–1091

  • Alvarado R, Ponce P, Criollo A, Córdova K, Khan MK (2018) Environmental degradation and real per capita output: new evidence at the global level grouping countries by income levels. J Clean Prod 189:13–20

    Google Scholar 

  • Alvarado R, Ponce P, Alvarado R, Ponce K, Huachizaca V, Toledo E (2019) Sustainable and non-sustainable energy and output in Latin America: a cointegration and causality approach with panel data. Energy Strategy Reviews 26:100369

    Google Scholar 

  • Bildirici M (2016) The relationship between hydropower energy consumption and economic growth. Procedia economics and finance 38:264–270

    Google Scholar 

  • Bildirici M, Ersin Ö (2015) An investigation of the relationship between the biomass energy consumption, economic growth and oil prices. Procedia Soc Behav Sci 210:203–212

    Google Scholar 

  • BP (2018) BP Statistical Review of World Energy. https://www.bp.com/

  • Breitung, J. (2001). The local power of some unit root tests for panel data. In Nonstationary panels, panel cointegration, and dynamic panels (pp. 161-177). Emerald Group Publishing Limited

  • Brini R, Amara M, Jemmali H (2017) Renewable energy consumption, international trade, oil price and economic growth inter-linkages: the case of Tunisia. Renew Sust Energ Rev 76:620–627

    Google Scholar 

  • Cornillie J, Fankhauser S (2004) The energy intensity of transition countries. Energy Econ 26(3):283–295

    Google Scholar 

  • Dong K, Sun R, Hochman G, Zeng X, Li H, Jiang H (2017) Impact of natural gas consumption on CO2 emissions: panel data evidence from China’s provinces. J Clean Prod 162:400–410

    Google Scholar 

  • Dumitrescu EI, Hurlin C (2012) Testing for Granger non-causality in heterogeneous panels. Econ Model 29(4):1450–1460

    Google Scholar 

  • Dutta A (2017) Oil price uncertainty and clean energy stock returns: New evidence from crude oil volatility index. J Clean Prod 164:1157–1166

  • Eder L, Provornaya I, Filimonova I, Kozhevin V, Komarova A (2018) World energy market in the conditions of low oil prices, the role of renewable energy sources. Energy Procedia 153:112–117

    Google Scholar 

  • Fang Z, Chang Y (2016) Energy, human capital and economic growth in Asia Pacific countries—evidence from a panel cointegration and causality analysis. Energy Econ 56:177–184

    Google Scholar 

  • Fang Z, Chen Y (2017) Human capital and energy in economic growth–evidence from Chinese provincial data. Energy Econ 68:340–358

    Google Scholar 

  • Ferrer R, Shahzad S, López R, Jareño F (2018) Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices. Energy Econ 76:1–20

    Google Scholar 

  • Flores-Chamba J, López-Sánchez M, Ponce P, Guerrero-Riofrío P, Álvarez-García J (2019) Economic and spatial determinants of energy consumption in the European Union. Energies 12(21):4118

    Google Scholar 

  • Granger CW (1988) Causality, cointegration, and control. J Econ Dyn Control 12(2–3):551–559

    Google Scholar 

  • Greene WH (2003) Econometric analysis. Pearson Education India

  • Hausman JA (1978) Specification tests in econometrics. Journal of the Econometric Society, Econometrica, pp 1251–1271

    Google Scholar 

  • Havranek T, Irsova Z, Janda K (2012) Demand for gasoline is more price-inelastic than commonly thought. Energy Econ 34(1):201–207

    Google Scholar 

  • He G, Kammen DM (2014) Where, when and how much wind is available? A provincial-scale wind resource assessment for China. Energy Policy 74:116–122

    Google Scholar 

  • He G, Zhang H, Xu Y, Lu X (2017) China’s clean power transition: current status and future prospect. Resour Conserv Recycl 121:3–10

    Google Scholar 

  • Inglesi-Lotz R, del Corral Morales LD (2017) The effect of education on a country’s energy consumption: evidence from developed and developing countries. Retrieved from https://ideas.repec.org/p/pre/wpaper/201733.html

  • IRENA RES (2018) International Renewable Energy Agency. Renewable Energy highlights, Abu Dhabi. https://www.irena.org/

  • Jimenez C, Moncada L, Ochoa-Jimenez D, Ochoa-Moreno WS (2019) Kuznets environmental curve for Ecuador: an analysis of the impact of economic growth on the environment. Sustainability 11(21):5896

    Google Scholar 

  • Kasman A, Duman YS (2015) CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: a panel data analysis. Econ Model 44:97–103

    Google Scholar 

  • Keček D, Mikulić D, Lovrinčević Ž (2019) Deployment of renewable energy: economic effects on the Croatian economy. Energy Policy 126:402–410

    Google Scholar 

  • Khan M, Yasmeen T, Shakoor A, Khan N, Muhammad R (2017) 2014 oil plunge: causes and impacts on renewable energy. Renew Sust Energ Rev 68(2):609–622

    Google Scholar 

  • Kharbach M, Chfadi T (2018) Oil prices and electricity production in Morocco. Energy Strategy Rev 22:320–324

    Google Scholar 

  • Kumari A, Sharma AK (2018) Causal relationships among electricity consumption, foreign direct investment and economic growth in India. Electr J 31(7):33–38

    Google Scholar 

  • Le Corff A (2018) Did oil prices trigger an innovation burst in biofuels? Energy Econ 75:547–559

    Google Scholar 

  • Li S, Wang Q (2019) India's dependence on foreign oil will exceed 90% around 2025-the forecasting results based on two hybridized NMGM-ARIMA and NMGM-BP models. J Clean Prod 232:137–153

    Google Scholar 

  • Liddle B (2012) The importance of energy quality in energy intensive manufacturing: evidence from panel cointegration and panel FMOLS. Energy Econ 34(6):1819–1825

    Google Scholar 

  • Lucas H, Pinnington S, Cabeza L (2018) Education and training gaps in the renewable energy sector. Sol Energy 173:449–455

    Google Scholar 

  • Nguyen KH, Kakinaka M (2019) Renewable energy consumption, carbon emissions, and development stages: some evidence from panel cointegration analysis. Renew Energy 132:1049–1057

    Google Scholar 

  • Papież M, Śmiech S, Frodyma K (2018) Determinants of renewable energy development in the EU countries. A 20-year perspective. Renew Sust Energ Rev 91:918–934

    Google Scholar 

  • Pesaran MH (2007) A simple panel unit root test in the presence of cross-section dependence. J Appl Econ 22:265–312

    Google Scholar 

  • Pesaran MH (2015) Testing weak cross-sectional dependence in large panels. Econ Rev 34(6–10):1089–1117

    Google Scholar 

  • Ponce P, Alvarado R (2019) Air pollution, output, FDI, trade openness, and urbanization: evidence using DOLS and PDOLS cointegration techniques and causality. Environ Sci Pollut Res 26(19):19843–19858

    Google Scholar 

  • Sadorsky P (2009) Renewable energy consumption and income in emerging economies. Energy Policy 37(10):4021–4028

    Google Scholar 

  • Salim R, Yao Y, Chen GS (2017) Does human capital matter for energy consumption in China? Energy Econ 67:49–59

    Google Scholar 

  • Shah IH, Hiles C, Morley B (2018) How do oil prices, macroeconomic factors and policies affect the market for renewable energy? Appl Energy 215:87–97

    Google Scholar 

  • Shahbaz M, Sbia R, Hamdi H, Ozturk I (2014) Economic growth, electricity consumption, urbanization and environmental degradation relationship in United Arab Emirates. Ecol Indic 45:622–631

    CAS  Google Scholar 

  • Shahbaz M, Zakaria M, Shahzad SJH, Mahalik MK (2018) The energy consumption and economic growth nexus in top ten energy-consuming countries: Fresh evidence from using the quantile-on-quantile approach. Energy Econ 71:282–301.

  • Shahbaz M, Gozgor G, Hammoudeh S (2019) Human capital and export diversification as new determinants of energy demand in the United States. Energy Econ 78:335–349

    Google Scholar 

  • Takii K, Tanaka R (2009) Does the diversity of human capital increase GDP? A comparison of education systems. J Public Econ 93(7–8):998–1007

    Google Scholar 

  • Troster V, Shahbaz M, Uddin GS (2018) Renewable energy, oil prices, and economic activity: a Granger-causality in quantiles analysis. Energy Econ 70:440–452

    Google Scholar 

  • Verkruijsse N, Pennink B, Westerman W (2015) Renewable energy in Indonesia: integrating human capital and money flows. In: Dorsman A, Westerman W, Simpson J (eds) Energy technology and valuation issues. Springer, Cham

    Google Scholar 

  • Wang Q, Ge S (2020) Uncovering the effects of external demand on China’s coal consumption: a global input–output analysis. J Clean Prod 245:118877

    Google Scholar 

  • Wang Q, Li S, Li R (2018) Forecasting energy demand in China and India: using single-linear, hybrid-linear, and non-linear time series forecast techniques. Energy 161:821–831

    Google Scholar 

  • Wang Q, Su M, Li R, Ponce P (2019a) The effects of energy prices, urbanization and economic growth on energy consumption per capita in 186 countries. J Clean Prod 225:1017–1032

    Google Scholar 

  • Wang Q, Jiang XT, Ge S, Jiang R (2019b) Is economic growth compatible with a reduction in CO2 emissions? Empirical analysis of the United States. Resour Conserv Recycl 151:104443

    Google Scholar 

  • Wang Q, Jiang XT, Yang X, Ge S (2020) Comparative analysis of drivers of energy consumption in China, the USA and India–a perspective from stratified heterogeneity. Sci Total Environ 698:134117

    CAS  Google Scholar 

  • Westerlund J (2007) Testing for error correction in panel data. Oxf Bull Econ Stat 69(6):709–748

    Google Scholar 

  • Wooldridge JM (2002) Econometric analysis of cross section and panel data. MIT press, Cambridge, MA

  • World Bank. (Ed.) (2018) World development indicators: 2018, Washington DC http://data.worldbank.org/data-catalog/world-development-indicators

  • World Economic Forum (2017) https://www.weforum.org/

  • Yao Y, Ivanovski K, Inekwe J, Smyth R (2019) Human capital and energy consumption: evidence from OECD countries. Energy Econ 84:104534

    Google Scholar 

  • Yuan C, Liu S, Wu J (2010) The relationship among energy prices and energy consumption in China. Energy Policy 38(1):197–207

    Google Scholar 

  • Zakarya GY, Mostefa B, Abbes SM, Seghir GM (2015) Factors affecting CO2 emissions in the BRICS countries: a panel data analysis. Procedia Economics and Finance 26:114–125

    Google Scholar 

  • Zhang LX, Yang ZF, Chen B, Chen GQ, Zhang YQ (2009) Temporal and spatial variations of energy consumption in rural China. Commun Nonlinear Sci Numer Simul 14(11):4022–4031

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Carrera de Economía, Universidad Nacional de Loja, 11050, Loja, Ecuador

    Pablo Ponce, Michelle López-Sánchez, Patricia Guerrero-Riofrío & Jorge Flores-Chamba

Authors
  1. Pablo Ponce
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michelle López-Sánchez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Patricia Guerrero-Riofrío
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jorge Flores-Chamba
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pablo Ponce.

Additional information

Responsible editor: Muhammad Shahbaz

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Table 8 Countries used in the study
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ponce, P., López-Sánchez, M., Guerrero-Riofrío, P. et al. Determinants of renewable and non-renewable energy consumption in hydroelectric countries. Environ Sci Pollut Res 27, 29554–29566 (2020). https://doi.org/10.1007/s11356-020-09238-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-020-09238-6

Keywords

JEL classification

Search

Navigation