The interplay between technological innovation, energy efficiency, and economic growth: Evidence from 30 European countries
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DOIhttp://dx.doi.org/10.21511/ppm.20(3).2022.36
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Article InfoVolume 20 2022, Issue #3, pp. 448-464
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It is assumed that technological progress plays a vital role in energy efficiency improvements when the effects of industrial restructuring, infrastructure, environmental challenges, and economic shocks seem more dubious. However, a limited number of studies have been conducted to examine the impact of technological innovation on countries’ energy efficiency levels. This study aims to explore the relationship between energy efficiency, technological innovation, and economic growth in 30 European countries by utilizing data from 2012 to 2020. To this end, a two-stage analysis is carried out. The first step involves estimating the total factor energy efficiency (TFEE) by the countries to illustrate the effects of energy parameters on economic growth and the environment, and technological innovation (TI) to estimate the innovation capability of each country by using data envelopment analysis (DEA) methodology. The second step includes a panel regression model to explore how technological innovation affects energy efficiency, considering the degree of government intervention, industrial structure, infrastructure, and economic openness.
The results indicate that the bottom-15 countries, whose TFEE scores were the lowest, are mainly countries of Central and Eastern Europe. Regarding the countries’ technological capability, the results were similar, but the score was lower than the TFEE.
Moreover, the regression analysis shows that a one percent increase in innovation activity contributes to an increase in energy efficiency by 0.27 percent. Hence, it confirms the notion of a positive impact of new technology on energy efficiency.
Acknowledgments
The study is supported by the grant from the Research Based Innovation “SFI Marine Operation in Virtual Environment (SFI-MOVE)” (Project No. 237929) in Norway.
- Keywords
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JEL Classification (Paper profile tab)O11, O32, Q43
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References33
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Tables6
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Figures10
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- Figure 1. Effects of technological change on the neoclassical production function
- Figure 2. Relationship between total factor energy efficiency (TFEE) and technological innovation (TI)
- Figure 3. The DEA case with one input and two outputs
- Figure 4. Estimated bi-annual values of TFEE, 2012–2020
- Figure 5. Estimated bi-annual values of TI, 2012–2020
- Figure 6. Growth rates of TFEE and TI, 2012–2020
- Figure 7. Average values of TFEE and TI, 2012–2020
- Figure 8. Correlation between TFEE and TI for 30 European economies, 2012–2020
- Figure 9. Energy consumption, GDP growth, and CO2 emissions from the energy sector, average for 30 European countries, 2012–2020
- Figure 10. R&D expenditures and patents granted, average for European countries, 2012–2020
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- Table 1. The top 15 and bottom 15 (TFEE)
- Table 2. The top 15 and bottom 15 (TI)
- Table 3. Correlation between TFEE and TI bi-annually, 2012–2020
- Table 4. Regression results, 2012–2020
- Table 5. Panel data (time series cross-section) analysis, 2012–2020
- Table 6. Cross-sectional data analysis, 2020
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- Bassanini, A., Scarpetta, S., & Visco, I. (2000). Knowledge, Technology and Economic Growth: Recent Evidence from OECD Countries (OECD Economics Department Working Papers No. 259). Paris: OECD Publishing.
- Carlin, W., & Soskice, D. (2015). Macroeconomics: Institutioins, Instability, and the Financial System (1st ed.) (638p.). Oxford.
- Charnes A., Cooper, W.W., & Rhodes, E.L. (1978). Measuring the Efficiency of Decision Making Units. European Journal of Operational Research, 2, 429-444.
- Dasgupta, S., & Roy, J. (2015). Understanding technological progress and input price as drivers of energy demand in manufacturing industries in India. Energy Policy, 83, 1-13.
- European Patent Office. (2022). European patent granted 2012-2021 per country of residence of the first named applicant.
- Eurostat. (2022). Data Browser.
- Giampietro, M., & Sorman, A. H. (2012). Are energy statistics useful for making energy scenarios? Energy, 37, 5-17.
- Grytten, O. H., Lindmark, M., & Minde, K. B. (2020). The wealth of nations and sustainable development: energy intensity and the environmental Kuznets curve. Environmental Economics, 11(1), 110-123.
- Hritonenko, N., & Yatsenko, Y. (2013). Modeling of Technological Change. In Mathematical Modeling in Economics, Ecology and the Environment (pp. 53-88). Boston, MA: Springer.
- Jin, T., & Kim, J. (2019). A comparative study of energy and carbon efficiency for emerging countries using panel stochastic frontier analysis. Scientific Reports, 9, 6647.
- Karali, N., Park, W. Y., & McNeil, M. (2017). Modeling technological change and its impact on energy savings in the U.S. iron and steel sector. Applied Energy, 202, 447-458.
- Koilo, V. (2019). Evidence of the Environmental Kuznets Curve: Unleashing the Opportunity of Industry 4.0 in Emerging Economies. Journal of Risk and Financial Management, 12(3), 122.
- Konan, Y. S., & Aklobessi, K. (2021). Revisiting the environmental Kuznets curve: Evidence from West Africa. Environmental Economics, 12(1), 64-75.
- Lestari, D., Lesmana, D., Yudaruddin, Y. A., & Yudaruddin, R. (2022). The impact of financial development and corruption on foreign direct investment in developing countries. Investment Management and Financial Innovations, 19(2), 211-220.
- Li, Y., Chiu, Y., & Lin, T. (2019). Energy and Environmental Efficiency in Different Chinese Regions. Sustainability, 11(4), 1216.
- Li, Y., Sun, L., Feng, T., & Zhu, C. (2013). How to reduce energy intensity in China: A regional comparison perspective. Energy Policy, 61, 513-522.
- Lissitsa, A., & Babiéceva, T. (2003). Data Envelope Analysis (DEA) – Modern Method of Determination Production Efficiency (Discussion Paper No. 50). Institute of Agricultural Development in Central and Eastern Europe (IAMO). (In Russian).
- Melao, N. (2005). Data envelopment analysis revisited: a neophyte’s perspective. International Journal of Management and Decision Making, 6(2), 158-179.
- Nthangu N. D., & Bokana, K. G. (2022). Foreign capital inflows, trade openness and output performance in selected sub-Saharan African countries. Investment Management and Financial Innovations, 19(1), 236-246.
- OECD. (2011). Towards Green Growth: Monitoring Progress. OECD Indicators. New York.
- Olsson, L. E. (1994). Energy-Meteorology: A new Discipline. Renewable Energy, 5(5-8), 1243-1246.
- Ouyang, X., & Lin, B. (2015). Analyzing energy savings potential of the Chinese building materials industry under different economic growth scenarios. Energy and Buildings, 109, 316-327.
- Paço, C. L., & Pérez, J. M. C. (2013). The use of DEA (Data Envelopment Analysis) methodology to evaluate the impact of ICT on productivity in the hotel sector. Via Tourism Review, 3.
- Petrushenko, M., Burkynskyi, B., Shevchenko, S., & Baranchenko, Y. (2021). Towards sustainable development in a transition economy: The case of eco-industrial parks in Ukraine. Environmental Economics, 12(1), 149-164.
- Shang, Y., Liu, H., & Lv, Y. (2020). Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generation. Journal of King Saud University – Science, 32(3), 1925-1931.
- Shao, S., Yang, Z., Yang, L., & Ma, S. (2019). Can China’s Energy Intensity Constraint Policy Promote Total Factor Energy Efficiency? Evidence from the Industrial Sector. The Energy Journal, 40(4), 101-128.
- Solow, R.M. (1957). Technical Change and the Aggregate Production Function. Review of Economics and Statistics, 39, 312-320.
- Versal, N., & Sholoiko, A. (2022). Green bonds of supranational financial institutions: On the road to sustainable development. Investment Management and Financial Innovations, 19(1), 91-105.
- Wang, C.-N., Le, A. L., & Hou, C.-C. (2019). Applying Undesirable Output Model to Security Evaluation of Taiwan. Mathematics, 7(11), 1023.
- Wang, H., & Wang, M. (2020). Effects of technological innovation on energy efficiency in China: Evidence from a dynamic panel of 284 cities. Science of The Total Environment, 709, 136172.
- Zeraibi, A., Balsalobre-Lorente, D., & Shehzad, K. (2020). Examining the Asymmetric Nexus between Energy Consumption, Technological Innovation, and Economic Growth; Does Energy Consumption and Technology Boost Economic Development? Sustainability, 12(21), 8867.
- Zhang, R., & Fu, Y. (2022). Technological progress effects on energy efficiency from the perspective of technological innovation and technology introduction: An empirical study of Guangdong, China. Energy Reports, 8, 425-437.
- Zhu, W., Zhang, Z., Li, X., Feng, W., & Li, J. (2019). Assessing the effects of technological progress on energy efficiency in the construction industry: A case of China. Journal of Cleaner Production, 238, 117908.