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The effect of energy R&D expenditures on CO2 emission reduction: estimation of the STIRPAT model for OECD countries

  • Emrah KoçakEmail author
  • Zübeyde Şentürk Ulucak
Research Article
  • 73 Downloads

Abstract

Energy innovations are critical to combating global warming and climate change. In this context, we focus on the impact of energy research–development (R&D) expenditures, which are the input of energy innovations, on CO2 emissions. For this purpose, we investigate the effect of disaggregated energy R&D expenditures on CO2 emission in 19 high-income OECD countries over the period 2003–2015. The dynamic panel data method is followed for empirical analysis. The results of the study show that R&D expenditures for energy efficiency and fossil energy have an increasing effect on CO2 emissions. Contrary to expectations, there is no significant relationship between renewable energy R&D expenditures and CO2 emissions. Remarkably, there is strong evidence that the power and storage R&D expenditures have a reducing effect on CO2 emissions. In light of the empirical findings, policy implications and recommendations to potential readers and authorities are further discussed.

Keywords

Energy innovation STIRPAT Generalized method of moments (GMM) CO2 reduction OECD 

Notes

References

  1. Álvarez-Herránz A, Balsalobre-Lorente D, Shahbaz M, Cantos JM (2017a) Energy innovation and renewable energy consumption in the correction of air pollution levels. Energy Policy 105:386–397.  https://doi.org/10.1016/j.enpol.2017.03.009 CrossRefGoogle Scholar
  2. Álvarez-Herránz A, Balsalobre D, Cantos JM, Shahbaz M (2017b) Energy innovations-GHG emissions nexus: fresh empirical evidence from OECD countries. Energy Policy 101:90–100.  https://doi.org/10.1016/j.enpol.2016.11.030 CrossRefGoogle Scholar
  3. Amri F (2018) Carbon dioxide emissions, total factor productivity, ICT, trade, financial development , and energy consumption: testing environmental Kuznets curve hypothesis for Tunisia. pp 33691–33701Google Scholar
  4. Anderson TR, Hawkins E, Jones PD (2016) CO2, the greenhouse effect and global warming: from the pioneering work of Arrhenius and Callendar to today’s earth system models. Endeavour 40:178–187.  https://doi.org/10.1016/J.ENDEAVOUR.2016.07.002 CrossRefGoogle Scholar
  5. Arellano M, Bond S (1991) Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev Econ Stud 58:277.  https://doi.org/10.2307/2297968 CrossRefGoogle Scholar
  6. Arellano M, Bover O (1995) Another look at the instrumental variable estimation of error-components models. J Econom 68:29–51.  https://doi.org/10.1016/0304-4076(94)01642-D CrossRefGoogle Scholar
  7. Balsalobre D, Álvarez A, Cantos JM (2015) Public budgets for energy RD&D and the effects on energy intensity and pollution levels. Environ Sci Pollut Res 22:4881–4892.  https://doi.org/10.1007/s11356-014-3121-3 CrossRefGoogle Scholar
  8. Baum CF, Schaffer ME, Stillman S (2003) Instrumental variables and GMM: estimation and testing. Stata J 3:1–31CrossRefGoogle Scholar
  9. Bernardi L, Morales L, Lühiste M, Bischof D (2018) The effects of the Fukushima disaster on nuclear energy debates and policies: a two-step comparative examination. Environ Polit 27:42–68.  https://doi.org/10.1080/09644016.2017.1383007 CrossRefGoogle Scholar
  10. Bilgili F, Ulucak R (2018) The nexus between biomass – footprint and sustainable development. In: Reference module in materials science and materials engineering. ElsevierGoogle Scholar
  11. Bilgili F, Koçak E, Bulut Ü, Sualp MN (2016a) How did the US economy react to shale gas production revolution? An advanced time series approach. Energy 116:963–977.  https://doi.org/10.1016/j.energy.2016.10.056 CrossRefGoogle Scholar
  12. Bilgili F, Öztürk İ, Koçak E, Bulut Ü, Pamuk Y, Muğaloğlu E, Bağlıtaş HH (2016b) The influence of biomass energy consumption on CO2 emissions: a wavelet coherence approach. Environ Sci Pollut Res 23:19043–19061.  https://doi.org/10.1007/s11356-016-7094-2 CrossRefGoogle Scholar
  13. Bilgili F, Koçak E, Bulut Ü, Kuşkaya S (2017) Can biomass energy be an efficient policy tool for sustainable development? Renew Sust Energ Rev 71:830–845.  https://doi.org/10.1016/j.rser.2016.12.109 CrossRefGoogle Scholar
  14. Blundell R, Bond S (1998) Initial conditions and moment restrictions in dynamic panel data models. J Econom 87:115–143.  https://doi.org/10.1016/S0304-4076(98)00009-8 CrossRefGoogle Scholar
  15. Chen W, Xu R (2010) Clean coal technology development in China. Energy Policy 38:2123–2130.  https://doi.org/10.1016/J.ENPOL.2009.06.003 CrossRefGoogle Scholar
  16. Cheng Z, Li L, Liu J (2017) The emissions reduction effect and technical progress effect of environmental regulation policy tools. J Clean Prod 149:191–205.  https://doi.org/10.1016/j.jclepro.2017.02.105 CrossRefGoogle Scholar
  17. Cho JH, Sohn SY (2018) A novel decomposition analysis of green patent applications for the evaluation of R&D efforts to reduce CO2 emissions from fossil fuel energy consumption. J Clean Prod 193:290–299.  https://doi.org/10.1016/j.jclepro.2018.05.060 CrossRefGoogle Scholar
  18. Croissant Y, Millo G et al (2008) Panel data econometrics in {{R}}: {{The}} plm package. J Stat Softw 27:1–43CrossRefGoogle Scholar
  19. Danish KN, Baloch MA et al (2018) The effect of ICT on CO2 emissions in emerging economies: does the level of income matters? Environ Sci Pollut Res 25:22850–22860.  https://doi.org/10.1007/s11356-018-2379-2 CrossRefGoogle Scholar
  20. Das T, Krishnan V, McCalley JD (2015) Assessing the benefits and economics of bulk energy storage technologies in the power grid. Appl Energy 139:104–118.  https://doi.org/10.1016/J.APENERGY.2014.11.017 CrossRefGoogle Scholar
  21. de Sisternes FJ, Jenkins JD, Botterud A (2016) The value of energy storage in decarbonizing the electricity sector. Appl Energy 175:368–379.  https://doi.org/10.1016/j.apenergy.2016.05.014 CrossRefGoogle Scholar
  22. Ehrlich PR, Holdren JP (1971) Impact of population growth on JSTOR. Science (80- ) 171:1212–1217CrossRefGoogle Scholar
  23. EIA (2012) Annual Energy Outlook 2012: With Projections to 2035Google Scholar
  24. EIA (2017) International Energy Agency, Global Energy & CO2 Status Report 2017. https://www.iea.org/newsroom/news/2018/march/global-energy-demand-grew-by-21-in-2017-and-carbon-emissions-rose-for-the-firs.html. Accessed 10 June 2018
  25. Ellabban O, Abu-Rub H, Blaabjerg F (2014) Renewable energy resources: current status, future prospects and their enabling technology. Renew Sust Energ Rev 39:748–764.  https://doi.org/10.1016/j.rser.2014.07.113 CrossRefGoogle Scholar
  26. Fan Y, Liu L-C, Wu G, Wei Y-M (2006) Analyzing impact factors of CO2 emissions using the STIRPAT model. Environ Impact Assess Rev 26:377–395.  https://doi.org/10.1016/J.EIAR.2005.11.007 CrossRefGoogle Scholar
  27. Fantazzini D (2016) The oil price crash in 2014/15: was there a (negative) financial bubble? Energy Policy 96:383–396.  https://doi.org/10.1016/J.ENPOL.2016.06.020 CrossRefGoogle Scholar
  28. Fernández FY, López FMA, Blanco OB (2018) Innovation for sustainability: the impact of R&D spending on CO2 emissions. J Clean Prod 172:3459–3467.  https://doi.org/10.1016/j.jclepro.2017.11.001 CrossRefGoogle Scholar
  29. Garrone P, Grilli L (2010) Is there a relationship between public expenditures in energy R&D and carbon emissions per GDP? An empirical investigation. Energy Policy 38:5600–5613.  https://doi.org/10.1016/j.enpol.2010.04.057 CrossRefGoogle Scholar
  30. Grafton RQ, Kompas T, Van LN, To H (2014) US biofuels subsidies and CO2 emissions: an empirical test for a weak and a strong green paradox. Energy Policy 68:550–555.  https://doi.org/10.1016/J.ENPOL.2013.11.006 CrossRefGoogle Scholar
  31. Gu X, Huang B (2014) Does inequality lead to a financial crisis? Revisited. Rev Dev Econ 18:502–516.  https://doi.org/10.1111/rode.12099 CrossRefGoogle Scholar
  32. Hall PJ, Bain EJ (2008) Energy-storage technologies and electricity generation. Energy Policy 36:4352–4355.  https://doi.org/10.1016/j.enpol.2008.09.037 CrossRefGoogle Scholar
  33. Hayakawa K (2018) Alternative over-identifying restriction test in the GMM estimation of panel data models. Econ Stat.  https://doi.org/10.1016/J.ECOSTA.2018.06.002
  34. Herring H, Roy R (2007) Technological innovation, energy efficient design and the rebound effect. Technovation 27:194–203.  https://doi.org/10.1016/J.TECHNOVATION.2006.11.004 CrossRefGoogle Scholar
  35. Huhtala A, Remes P (2017) Quantifying the social costs of nuclear energy: perceived risk of accident at nuclear power plants. Energy Policy 105:320–331.  https://doi.org/10.1016/j.enpol.2017.02.052 CrossRefGoogle Scholar
  36. Ibrahim H, Ilinca A, Perron J (2008) Energy storage systems—characteristics and comparisons. Renew Sust Energ Rev 12:1221–1250.  https://doi.org/10.1016/J.RSER.2007.01.023 CrossRefGoogle Scholar
  37. International Energy Agency (IEA) (2018) World energy outlookGoogle Scholar
  38. Jevons WS (1865) On the variation of prices and the value of the currency since 1782. J Stat Soc London 28:294.  https://doi.org/10.2307/2338419 CrossRefGoogle Scholar
  39. Jin L, Duan K, Shi C, Ju X (2017) The impact of technological progress in the energy sector on carbon emissions: an empirical analysis from China. Int J Environ Res Public Health 14:1–14.  https://doi.org/10.3390/ijerph14121505 Google Scholar
  40. Kahouli B (2018) The causality link between energy electricity consumption, CO2 emissions, R&D stocks and economic growth in Mediterranean countries (MCs). Energy 145:388–399.  https://doi.org/10.1016/j.energy.2017.12.136 CrossRefGoogle Scholar
  41. Keen S, Ayres RU, Standish R (2019) A note on the role of energy in production. Ecol Econ 157:40–46.  https://doi.org/10.1016/J.ECOLECON.2018.11.002 CrossRefGoogle Scholar
  42. Khoshnevis Yazdi S, Shakouri B (2018) The renewable energy, CO2 emissions, and economic growth: VAR model. Energy Sour B Econ Plan Pol 13:53–59.  https://doi.org/10.1080/15567249.2017.1403499 CrossRefGoogle Scholar
  43. Kilian L (2016) The impact of the shale oil revolution on U.S. oil and gasoline prices. Rev Environ Econ Policy 10:185–205.  https://doi.org/10.1093/reep/rew001 CrossRefGoogle Scholar
  44. Koçak E, Şarkgüneşi A (2018) The impact of foreign direct investment on CO2 emissions in Turkey: new evidence from cointegration and bootstrap causality analysis. Environ Sci Pollut Res 25:790–804.  https://doi.org/10.1007/s11356-017-0468-2 CrossRefGoogle Scholar
  45. Kwon DS, Cho JH, Sohn SY (2017) Comparison of technology efficiency for CO2 emissions reduction among European countries based on DEA with decomposed factors. J Clean Prod 151:109–120.  https://doi.org/10.1016/j.jclepro.2017.03.065 CrossRefGoogle Scholar
  46. Lantz V, Feng Q (2006) Assessing income, population, and technology impacts on CO2 emissions in Canada: where’s the EKC? Ecol Econ 57:229–238.  https://doi.org/10.1016/j.ecolecon.2005.04.006 CrossRefGoogle Scholar
  47. Lee KH, Min B (2015) Green R&D for eco-innovation and its impact on carbon emissions and firm performance. J Clean Prod 108:534–542.  https://doi.org/10.1016/j.jclepro.2015.05.114 CrossRefGoogle Scholar
  48. Li W, Wang W, Wang Y, Qin Y (2017) Industrial structure, technological progress and CO2 emissions in China: analysis based on the STIRPAT framework. Nat Hazards 88:1545–1564.  https://doi.org/10.1007/s11069-017-2932-1 CrossRefGoogle Scholar
  49. Lin S, Wang S, Marinova D, Zhao D, Hong J (2017) Impacts of urbanization and real economic development on CO2 emissions in non-high income countries: empirical research based on the extended STIRPAT model. J Clean Prod 166:952–966.  https://doi.org/10.1016/j.jclepro.2017.08.107 CrossRefGoogle Scholar
  50. Luo X, Wang J, Dooner M, Clarke J (2015) Overview of current development in electrical energy storage technologies and the application potential in power system operation. Appl Energy 137:511–536.  https://doi.org/10.1016/j.apenergy.2014.09.081 CrossRefGoogle Scholar
  51. Mensah CN, Long X, Boamah KB, Bediako IA, Dauda L, Salman M (2018) The effect of innovation on CO2 emissions of OCED countries from 1990 to 2014. Environ Sci Pollut Res 25:29678–29698.  https://doi.org/10.1007/s11356-018-2968-0 CrossRefGoogle Scholar
  52. Munasinghe M (2002) The sustainomics trans-disciplinary meta-framework for making development more sustainable: applications to energy issues. Int J Sustain Dev 5:125.  https://doi.org/10.1504/IJSD.2002.002563 CrossRefGoogle Scholar
  53. Najam A, Cleveland CJ (2003) Energy and sustainable development at global environmental summits: an evolving agenda. Environ Dev Sustain 5:117–138.  https://doi.org/10.1023/A:1025388420042 CrossRefGoogle Scholar
  54. Ockwell DG, Haum R, Mallett A, Watson J (2010) Intellectual property rights and low carbon technology transfer: conflicting discourses of diffusion and development. Glob Environ Chang 20:729–738.  https://doi.org/10.1016/j.gloenvcha.2010.04.009 CrossRefGoogle Scholar
  55. Oikonomou V, Flamos A, Grafakos S (2010) Is blending of energy and climate policy instruments always desirable? Energy Policy 38:4186–4195.  https://doi.org/10.1016/j.enpol.2010.03.046 CrossRefGoogle Scholar
  56. Park Y, Meng F, Baloch MA (2018) The effect of ICT, financial development, growth, and trade openness on CO2 emissions: an empirical analysis. Environ Sci Pollut Res 25:30708–30719.  https://doi.org/10.1007/s11356-018-3108-6 CrossRefGoogle Scholar
  57. Prest BC (2018) Explanations for the 2014 oil price decline: supply or demand? Energy Econ 74:63–75.  https://doi.org/10.1016/j.eneco.2018.05.029 CrossRefGoogle Scholar
  58. Sorrell S (2007) The rebound effect: an assessment of the evidence for economy-wide energy savings from improved energy efficiencyGoogle Scholar
  59. Sorrell S, Dimitropoulos J, Sommerville M (2009) Empirical estimates of the direct rebound effect: a review. Energy Policy 37:1356–1371.  https://doi.org/10.1016/j.enpol.2008.11.026 CrossRefGoogle Scholar
  60. Tang E, Peng C, Xu Y (2018) Changes of energy consumption with economic development when an economy becomes more productive. J Clean Prod 196:788–795.  https://doi.org/10.1016/J.JCLEPRO.2018.06.101 CrossRefGoogle Scholar
  61. Tokic D (2015) Working Paper n°: 2015-107-02. p 85Google Scholar
  62. World Bank (2018) World Development Indicators (WDI). https://datacatalog.worldbank.org/dataset/world-development-indicators. Accessed 12 July 2018
  63. York R, Rosa EA, Dietz T (2003) STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts. Ecol Econ 46:351–365.  https://doi.org/10.1016/S0921-8009(03)00188-5 CrossRefGoogle Scholar
  64. Zhang YJ, Peng HR, Liu Z, Tan W (2015) Direct energy rebound effect for road passenger transport in China: a dynamic panel quantile regression approach. Energy Policy 87:303–313.  https://doi.org/10.1016/j.enpol.2015.09.022 CrossRefGoogle Scholar
  65. Zhou Z, Ye X, Ge X (2017) The impacts of technical progress on sulfur dioxide Kuznets curve in China: a spatial panel data approach. Sustain 9.  https://doi.org/10.3390/su9040674

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Economics and Administrative Sciences, Department of EconomicsErciyes UniversityKayseriTurkey

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