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Assessing the long-term asymmetric relationship between energy consumption and CO2 emissions: Evidence from the Visegrad Group countries

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DOI:

https://doi.org/10.18559/ebr.2024.1.1082

Keywords:

asymmetric panel data, Visegrad Group, energy transition, asymmetric causality, renewable energy, CO2 emissions

Abstract

This study investigates the impact of renewable (REW) and non-renewable (NREW) energy usage, along with econom-ic growth (GDP), on carbon dioxide (CO2) emissions in the Visegrad countries, which rely heavily on traditional energy sources. Using data from 1991 to 2021, the analysis employs a panel asymmetric regression with Driscoll-Kraay and FGLS standard errors. The latent cointegration test reveals long-term relationships with asymmetry among the variables. Real GDP fluctuations exhibit a negative impact on CO2emissions for both positive and negative shocks. A reduc-tion in conventional energy source consumption leads to a greater CO2 emission reduction, confirming asymmetry. Conversely, an increase in consumption positively impacts CO2 reduction. However, non-conventional energy sources show no asymmetries. The OLS-based model proposed by Driscoll-Kraay showed reduced standard errors, but lower significance in the estimated parameters compared to the FGLS model. The findings recommend a sustainable energy transition for Visegrad countries by eliminating traditional sources and promoting renewable resources.

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References

Adedoyin, F. F., Ozturk, I., Bekun, F. V., Agboola, P. O., & Agboola, M. O. (2021). Renewable and non-renewable energy policy simulations for abating emissions in a complex economy: Evidence from the novel dynamic ARDL. Renewable Energy, 177, 1408–1420. https://doi.org/10.1016/j.renene.2021.06.018
View in Google Scholar DOI: https://doi.org/10.1016/j.renene.2021.06.018

Ahmad, M., Işık, C., Jabeen, G., Ali, T., Ozturk, I., & Atchike, D. W. (2021). Heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions across regional development levels. Science of The Total Environment, 765, 144527. https://doi.org/10.1016/j.scitotenv.2020.144527
View in Google Scholar DOI: https://doi.org/10.1016/j.scitotenv.2020.144527

Ali, F., Huang, S., & Cheo, R. (2020). Climatic Impacts on Basic Human Needs in the United States of America: A Panel Data Analysis. Sustainability, 12(4), Article 4. https://doi.org/10.3390/su12041508
View in Google Scholar DOI: https://doi.org/10.3390/su12041508

Allison, P. D. (2019). Asymmetric Fixed-effects Models for Panel Data. Socius, 5, 2378023119826441. https://doi.org/10.1177/2378023119826441
View in Google Scholar DOI: https://doi.org/10.1177/2378023119826441

Alvarado, R., Deng, Q., Tillaguango, B., Méndez, P., Bravo, D., Chamba, J., Alvarado-Lopez, M., & Ahmad, M. (2021). Do economic development and human capital decrease non-renewable energy consumption? Evidence for OECD countries. Energy, 215, 119147. https://doi.org/10.1016/j.energy.2020.119147
View in Google Scholar DOI: https://doi.org/10.1016/j.energy.2020.119147

Ambroziak, Ł., Chojna, J., Miniszewski, M., Strzelecki, J., Aleksander, S., Śliwowski, P., Święcicki, I., & Wąsiński, M. (2021). Visegrad Group—30 years of transformation, integration and development. Polish Economic Institute. https://pie.net.pl/grupa-wyszehradzka-30-lat-transformacji-integracji-i-rozwoju/
View in Google Scholar

Antonakakis, N., Chatziantoniou, I., & Filis, G. (2017). Energy consumption, CO2 emissions, and economic growth: An ethical dilemma. Renewable and Sustainable Energy Reviews, 68, 808–824. https://doi.org/10.1016/j.rser.2016.09.105
View in Google Scholar DOI: https://doi.org/10.1016/j.rser.2016.09.105

Apergis, N., & Ozturk, I. (2015). Testing Environmental Kuznets Curve hypothesis in Asian countries. Ecological Indicators, 52, 16–22. https://doi.org/10.1016/j.ecolind.2014.11.026
View in Google Scholar DOI: https://doi.org/10.1016/j.ecolind.2014.11.026

Baltagi, B. H., Feng, Q., & Kao, C. (2012). A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model. Journal of Econometrics, 170(1), 164–177. https://doi.org/10.1016/j.jeconom.2012.04.004
View in Google Scholar DOI: https://doi.org/10.1016/j.jeconom.2012.04.004

Baum, C. F. (2001). Residual Diagnostics for Cross-section Time Series Regression Models. The Stata Journal, 1(1), 101–104. https://doi.org/10.1177/1536867X0100100108
View in Google Scholar DOI: https://doi.org/10.1177/1536867X0100100108

Bilgili, F., Koçak, E., & Bulut, Ü. (2016). The dynamic impact of renewable energy consumption on CO2 emissions: A revisited Environmental Kuznets Curve approach. Renewable and Sustainable Energy Reviews, 54, 838–845. https://doi.org/10.1016/j.rser.2015.10.080
View in Google Scholar DOI: https://doi.org/10.1016/j.rser.2015.10.080

Cialani, C. (2017). CO2 emissions, GDP and trade: A panel cointegration approach. International Journal of Sustainable Development & World Ecology, 24(3), 193–204. https://doi.org/10.1080/13504509.2016.1196253
View in Google Scholar DOI: https://doi.org/10.1080/13504509.2016.1196253

Coy, D., Malekpour, S., Saeri, A. K., & Dargaville, R. (2021). Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes. Energy Research & Social Science, 72, 101871. https://doi.org/10.1016/j.erss.2020.101871
View in Google Scholar DOI: https://doi.org/10.1016/j.erss.2020.101871

Daoud, J. I. (2017). Multicollinearity and Regression Analysis. Journal of Physics: Conference Series, 949(1), 012009. https://doi.org/10.1088/1742-6596/949/1/012009
View in Google Scholar DOI: https://doi.org/10.1088/1742-6596/949/1/012009

Debone, D., Leite, V. P., & Miraglia, S. G. E. K. (2021). Modelling approach for carbon emissions, energy consumption and economic growth: A systematic review. Urban Climate, 37, 100849. https://doi.org/10.1016/j.uclim.2021.100849
View in Google Scholar DOI: https://doi.org/10.1016/j.uclim.2021.100849

Dissanayake, H., Perera, N., Abeykoon, S., Samson, D., Jayathilaka, R., Jayasinghe, M., & Yapa, S. (2023). Nexus between carbon emissions, energy consumption, and economic growth: Evidence from global economies. PLOS ONE, 18(6), e0287579. https://doi.org/10.1371/journal.pone.0287579
View in Google Scholar DOI: https://doi.org/10.1371/journal.pone.0287579

Driscoll, J. C., & Kraay, A. C. (1998). Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data. The Review of Economics and Statistics, 80(4), 549–560.
View in Google Scholar DOI: https://doi.org/10.1162/003465398557825

Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. https://doi.org/10.1016/j.econmod.2012.02.014
View in Google Scholar DOI: https://doi.org/10.1016/j.econmod.2012.02.014

Flanker, R. (2016). The Paris Agreement and the new logic of international climate politics. International Affairs, 92(5), 1107–1125. https://doi.org/10.1111/1468-2346.12708
View in Google Scholar DOI: https://doi.org/10.1111/1468-2346.12708

Givens, J. E., Huang, X., & Jorgenson, A. K. (2019). Ecologically unequal exchange: A theory of global environmental injustice. Sociology Compass, 13(5), e12693. https://doi.org/10.1111/soc4.12693
View in Google Scholar DOI: https://doi.org/10.1111/soc4.12693

Granger, C. W. J., & Yoon, G. (2002). Hidden Cointegration (SSRN Scholarly Paper 313831). https://doi.org/10.2139/ssrn.313831
View in Google Scholar DOI: https://doi.org/10.2139/ssrn.313831

Haberl, H., Wiedenhofer, D., Virág, D., Kalt, G., Plank, B., Brockway, P., Fishman, T., Hausknost, D., Krausmann, F., Leon-Gruchalski, B., Mayer, A., Pichler, M., Schaffartzik, A., Sousa, T., Streeck, J., & Creutzig, F. (2020). A systematic review of the evidence on decoupling of GDP, resource use and GHG emissions, part II: Synthesizing the insights. Environmental Research Letters, 15(6), 065003. https://doi.org/10.1088/1748-9326/ab842a
View in Google Scholar DOI: https://doi.org/10.1088/1748-9326/ab842a

Hatemi-J, A. (2012). Asymmetric causality tests with an application. Empirical Economics, 43(1), 447–456. https://doi.org/10.1007/s00181-011-0484-x
View in Google Scholar DOI: https://doi.org/10.1007/s00181-011-0484-x

Hatemi-J, A. (2020). Hidden panel cointegration. Journal of King Saud University - Science, 32(1), 507–510. https://doi.org/10.1016/j.jksus.2018.07.011
View in Google Scholar DOI: https://doi.org/10.1016/j.jksus.2018.07.011

Hatemi-J, A. (2022). Dynamic Asymmetric Causality Tests with an Application. Engineering Proceedings, 18(1), Article 1. https://doi.org/10.3390/engproc2022018041
View in Google Scholar DOI: https://doi.org/10.3390/engproc2022018041

Hatemi-J, A., & El-Khatib, Y. (2016). An extension of the asymmetric causality tests for dealing with deterministic trend components. Applied Economics, 48(42), 4033–4041. https://doi.org/10.1080/00036846.2016.1150950
View in Google Scholar DOI: https://doi.org/10.1080/00036846.2016.1150950

Inglesi-Lotz, R., & Dogan, E. (2018). The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub- Saharan Africa’s Βig 10 electricity generators. Renewable Energy, 123, 36–43. https://doi.org/10.1016/j.renene.2018.02.041
View in Google Scholar DOI: https://doi.org/10.1016/j.renene.2018.02.041

Iqbal, S., Wang, Y., Shaikh, P. A., Maqbool, A., & Hayat, K. (2022). Exploring the asymmetric effects of renewable energy production, natural resources, and economic progress on CO2 emissions: Fresh evidence from Pakistan. Environmental Science and Pollution Research, 29(5), 7067–7078. https://doi.org/10.1007/s11356-021-16138-w
View in Google Scholar DOI: https://doi.org/10.1007/s11356-021-16138-w

Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 90(1), 1–44. https://doi.org/10.1016/S0304-4076(98)00023-2
View in Google Scholar DOI: https://doi.org/10.1016/S0304-4076(98)00023-2

LaBelle, M. C., Tóth, G., & Szép, T. (2022). Not Fit for 55: Prioritizing Human Well-Being in Residential Energy Consumption in the European Union. Energies, 15(18), Article 18. https://doi.org/10.3390/en15186687
View in Google Scholar DOI: https://doi.org/10.3390/en15186687

Mardani, A., Streimikiene, D., Cavallaro, F., Loganathan, N., & Khoshnoudi, M. (2019). Carbon dioxide (CO2) emissions and economic growth: A systematic review of two decades of research from 1995 to 2017. Science of The Total Environment, 649, 31–49. https://doi.org/10.1016/j.scitotenv.2018.08.229
View in Google Scholar DOI: https://doi.org/10.1016/j.scitotenv.2018.08.229

McGee, J. A., & York, R. (2018). Asymmetric relationship of urbanization and CO2 emissions in less developed countries. PLOS ONE, 13(12), e0208388. https://doi.org/10.1371/journal.pone.0208388
View in Google Scholar DOI: https://doi.org/10.1371/journal.pone.0208388

Muço, K., Valentini, E., & Lucarelli, S. (2021). The Relationships between GDP growth, Energy Consumption, Renewable Energy Production and CO2 Emissions in European Transition Economies. International Journal of Energy Economics and Policy, 11(4), Article 4.
View in Google Scholar DOI: https://doi.org/10.32479/ijeep.11275

Muhammad, B., & Khan, S. (2019). Effect of bilateral FDI, energy consumption, CO2 emission and capital on economic growth of Asia countries. Energy Reports, 5, 1305–1315. https://doi.org/10.1016/j.egyr.2019.09.004
View in Google Scholar DOI: https://doi.org/10.1016/j.egyr.2019.09.004

Naqvi, S., Wang, J., & Ali, R. (2022). Towards a green economy in Europe: Does renewable energy production has asymmetric effects on unemployment? Environmental Science and Pollution Research, 29(13), 18832–18839. https://doi.org/10.1007/s11356-021-17093-2
View in Google Scholar DOI: https://doi.org/10.1007/s11356-021-17093-2

Naseer, S., Song, H., Chupradit, S., Maqbool, A., Hashim, N. A. A. N., & Vu, H. M. (2022). Does educated labor force is managing the green economy in BRCS? Fresh evidence from NARDL-PMG approach. Environmental Science and Pollution Research, 29(14), 20296–20304. https://doi.org/10.1007/s11356-021-16834-7
View in Google Scholar DOI: https://doi.org/10.1007/s11356-021-16834-7

Pastukhova, M., & Westphal, K. (2020). Governing the Global Energy Transformation. In M. Hafner & S. Tagliapietra (Eds.), The Geopolitics of the Global Energy Transition (pp. 341–364). Springer International Publishing. https://doi.org/10.1007/978-3-030-39066-2_15
View in Google Scholar DOI: https://doi.org/10.1007/978-3-030-39066-2_15

Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics, 22(2), 265–312. https://doi.org/10.1002/jae.951
View in Google Scholar DOI: https://doi.org/10.1002/jae.951

Rahman, M. M., & Kashem, M. A. (2017). Carbon emissions, energy consumption and industrial growth in Bangladesh: Empirical evidence from ARDL cointegration and Granger causality analysis. Energy Policy, 110, 600–608. https://doi.org/10.1016/j.enpol.2017.09.006
View in Google Scholar DOI: https://doi.org/10.1016/j.enpol.2017.09.006

Sadiq, M., Chau, K. Y., Ha, N. T. T., Phan, T. T. H., Ngo, T. Q., & Huy, P. Q. (2023). The impact of green finance, eco-innovation, renewable energy and carbon taxes on CO2 emissions in BRICS countries: Evidence from CS ARDL estimation. Geoscience Frontiers, 101689. https://doi.org/10.1016/j.gsf.2023.101689
View in Google Scholar DOI: https://doi.org/10.1016/j.gsf.2023.101689

Şanlı, D., Muratoğlu, Y., Songur, M., & Uğurlu, E. (2023). The asymmetric effect of renewable and non-renewable energy on carbon emissions in OECD: New evidence from non-linear panel ARDL model. Frontiers in Environmental Science, 11. https://www.frontiersin.org/articles/10.3389/fenvs.2023.1228296
View in Google Scholar DOI: https://doi.org/10.3389/fenvs.2023.1228296

Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281–314). Springer. https://doi.org/10.1007/978-1-4899-8008-3_9
View in Google Scholar DOI: https://doi.org/10.1007/978-1-4899-8008-3_9

Suproń, B., & Myszczyszyn, J. (2023). Impact of Renewable and Non-Renewable Energy Consumption and CO2 Emissions on Economic Growth in the Visegrad Countries. Energies, 16(20), Article 20. https://doi.org/10.3390/en16207163
View in Google Scholar DOI: https://doi.org/10.3390/en16207163

Toumi, S., & Toumi, H. (2019). Asymmetric causality among renewable energy consumption, CO2 emissions, and economic growth in KSA: Evidence from a non-linear ARDL model. Environmental Science and Pollution Research, 26(16), 16145–16156. https://doi.org/10.1007/s11356-019-04955-z
View in Google Scholar DOI: https://doi.org/10.1007/s11356-019-04955-z

Ullah, S., Ozturk, I., Usman, A., Majeed, M. T., & Akhtar, P. (2020). On the asymmetric effects of premature deindustrialization on CO2 emissions: Evidence from Pakistan. Environmental Science and Pollution Research, 27(12), 13692–13702. https://doi.org/10.1007/s11356-020-07931-0
View in Google Scholar DOI: https://doi.org/10.1007/s11356-020-07931-0

White, H. (1980). A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity. Econometrica, 48(4), 817–838. https://doi.org/10.2307/1912934
View in Google Scholar DOI: https://doi.org/10.2307/1912934

Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data. The MIT Press. https://www.jstor.org/stable/j.ctt5hhcfr
View in Google Scholar

York, R., & Light, R. (2017). Directional Asymmetry in Sociological Analyses. Socius, 3, 2378023117697180. https://doi.org/10.1177/2378023117697180
View in Google Scholar DOI: https://doi.org/10.1177/2378023117697180

Zoundi, Z. (2017). CO2 emissions, renewable energy and the Environmental Kuznets Curve, a panel cointegration approach. Renewable and Sustainable Energy Reviews, 72, 1067–1075. https://doi.org/10.1016/j.rser.2016.10.018
View in Google Scholar DOI: https://doi.org/10.1016/j.rser.2016.10.018

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2024-03-29

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Vol. 10 No. 1 (2024)

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Research article- regular issue

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Suproń, B. (2024). Assessing the long-term asymmetric relationship between energy consumption and CO2 emissions: Evidence from the Visegrad Group countries. Economics and Business Review, 10(1). https://doi.org/10.18559/ebr.2024.1.1082

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