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Analyzing causality and cointegration of macroeconomics and energy-related factors of Nordic and SEE European countries

    Irina Alexandra Georgescu Affiliation
    ; Simona-Vasilica Oprea Affiliation
    ; Adela Bâra Affiliation

Abstract

Discrepancies between several South-Eastern European (SEE) countries and Nordic countries are investigated in this paper using an econometric analysis. Its aim is to examine the relationship between CO2 emissions, GDP per capita, urban population (URB) and electricity production from Renewable Energy Sources (RES) – EPREN, excluding hydroelectric for the two groups of EU countries located in the North and S-E of Europe. The data covers a period from 1990 to 2022, providing a comprehensive view over three decades. The relationship between the four variables is determined by various causality and cointegration tests. We check the unit root tests and conclude that the analyzed time series are stationary at first difference. Further, we estimate two models: Fully Modified and Dynamic Ordinary Least Squares and study causality and cointegration between variables. The results show that CO2 emissions are impacted by GDP, URB and EPREN for both regions. Testing causality, for SEE and Nordic countries, the bidirectional and causalities do exist.

Keyword : FMOLS and DOLS, macroeconomics, greenhouse gases, renewables, fossil fuels, energy-related factors

How to Cite
Georgescu, I. A., Oprea, S.-V., & Bâra, A. (2024). Analyzing causality and cointegration of macroeconomics and energy-related factors of Nordic and SEE European countries. Journal of Business Economics and Management, 25(3), 494–515. https://doi.org/10.3846/jbem.2024.21677
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Jul 4, 2024
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References

Androniceanu, A., Georgescu, I., Nica, I., & Chiriță, N. (2023). A comprehensive analysis of renewable energy based on integrating economic cybernetics and the autoregressive distributed lag model – The case of Romania. Energies, 16(16), Article 5978. https://doi.org/10.3390/en16165978

Baltagi, B. H. (2021). Econometric analysis of panel data (6 ed.). Springer. https://doi.org/10.1007/978-3-030-53953-5

Bâra, A., Oprea, S.-V., & Georgescu, I. A. (2023). Understanding electricity price evolution – day-ahead market competitiveness in Romania. Journal of Business Economics and Management, 24(2), 221–244. https://doi.org/10.3846/jbem.2023.19050

Bozkaya, Ş., Onifade, S. T., Duran, M. S., & Kaya, M. G. (2022). Does environmentally friendly energy consumption spur economic progress: empirical evidence from the Nordic countries? Environmental Science and Pollution Research, 29, 82600–82610. https://doi.org/10.1007/s11356-022-23452-4

Cancro, C., Delcea, C., Fabozzi, S., Ferruzzi, G., Graditi, G., Palladino, V., & Valenti, M. (2022). A profitability analysis for an aggregator in the ancillary services market: An Italian case study. Energies, 15(9), Ar­ticle 3238. https://doi.org/10.3390/en15093238

Carlsen, L., & Bruggemann, R. (2021). Inequalities in the European Union – a partial order analysis of the main indicators. Sustainability, 13(11), Article 6278. https://doi.org/10.3390/su13116278

Caroleo, F. E., Rocca, A., Neagu, G., & Keranova, D. (2022). NEETs and the process of transition from school to the labor market: A comparative analysis of Italy, Romania, and Bulgaria. Youth and Society, 54(2_suppl), 109S–129S. https://doi.org/10.1177/0044118X211056360

Choi, I. (2001). Unit root tests for panel data. Journal of International Money and Finance, 20(2), 249–272. https://doi.org/10.1016/S0261-5606(00)00048-6

Ciucu-Durnoi, A.-N., Florescu, M. S., & Delcea, C. (2023). Envisioning Romania’s path to sustainable development: A prognostic approach. Sustainability, 15(17), Article 12671. https://doi.org/10.3390/su151712671

Cota, B., Erjavec, N., & Jakšić, S. (2023). Economic complexity and income inequality in EU countries. Croatian Operational Research Review, 14(1), 77–86. https://doi.org/10.17535/crorr.2023.0007

Dagoumas, A. (2021). The European perspective on the energy developments in Eastern Mediterranean and South East Europe. In The new Eastern Mediterranean transformed: Emerging issues and new actors (pp. 159–177). Springer. https://doi.org/10.1007/978-3-030-70554-1_8

Destek, M. A., Balli, E., & Manga, M. (2016). The relationship between CO2 emission, energy consumption, urbanization and trade openness for selected CEECs. Research in World Economy, 7(1), 52–58. https://doi.org/10.5430/rwe.v7n1p52

Dogan, E., Seker, F., & Bulbul, S. (2017). Investigating the impacts of energy consumption, real GDP, tourism and trade on CO2 emissions by accounting for cross-sectional dependence: A panel study of OECD countries. Current Issues in Tourism, 20(16), 1701–1719. https://doi.org/10.1080/13683500.2015.1119103

Drysdale, D., Mathiesen, B. V., & Paardekooper, S. (2019). Transitioning to a 100% renewable energy system in Denmark by 2050: Assessing the impact from expanding the building stock at the same time. Energy Efficiency, 12, 37–55. https://doi.org/10.1007/s12053-018-9649-1

Duarte, R., Miranda-Buetas, S., & Sarasa, C. (2021). Household consumption patterns and income inequality in EU countries: Scenario analysis for a fair transition towards low-carbon economies. Energy Economics, 104, Article 105614. https://doi.org/10.1016/j.eneco.2021.105614

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

Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing [Co-integración y corrección de error: representación, estimación y prueba]. Econometrica, 55(2), 251–276. https://doi.org/10.2307/1913236

Georgescu, I., & Kinnunen, J. (2023). The role of foreign direct investments, urbanization, productivity, and energy consumption in Finland’s carbon emissions: An ARDL approach. Environmental Science and Pollution Research, 30, 87685–87694. https://doi.org/10.1007/s11356-023-28680-w

Grădinaru, G. I., & Maricuț, A. C. (2022). From the rebound effect to the perspective of circular economy: A structure changes analysis among EU countries. Economic Computation and Economic Cybernetics Studies and Research, 56(1), 257–272. https://doi.org/10.24818/18423264/56.1.22.16

Hatmanu, M., Cautisanu, C., & Iacobuta, A. O. (2022). On the relationships between CO2 emissions and their determinants in Romania and Bulgaria. An ARDL approach. Applied Economics, 54(22), 2582–2595. https://doi.org/10.1080/00036846.2021.1998328

Hsiao, C. (2007). Panel data analysis-advantages and challenges. Test, 16, 1–22. https://doi.org/10.1007/s11749-007-0046-x

Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74. https://doi.org/10.1016/S0304-4076(03)00092-7

Jåstad, E. O., & Bolkesjø, T. F. (2023). Modelling emission and land-use impacts of altered bioenergy use in the future energy system. Energy, 265, Article 126349. https://doi.org/10.1016/j.energy.2022.126349

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

Kao, C., & Chiang, M. H. (2000). On the estimation and inference of a cointegrated regression in panel data. In B. H. Baltagi, T. B. Fomby, & R. Carter Hill (Eds.), Advances in Econometrics: Vol 15. Nonstationary panels, panel cointegration, and dynamic panels (pp. 179–222). Emerald Group Publishing Limited, Leeds. https://doi.org/10.1016/S0731-9053(00)15007-8

Kasperowicz, R. (2015). Economic growth and CO2 emissions: The ECM analysis. Journal of International Studies, 8(3), 91–98.

Kleanthis, N., Stavrakas, V., Ceglarz, A., Süsser, D., Schibline, A., Lilliestam, J., & Flamos, A. (2022). Eliciting knowledge from stakeholders to identify critical issues of the transition to climate neutrality in Greece, the Nordic Region, and the European Union. Energy Research and Social Science, 93, Article 102836. https://doi.org/10.1016/j.erss.2022.102836

Knez, S., Štrbac, S., & Podbregar, I. (2022). Climate change in the Western Balkans and EU Green Deal: Status, mitigation and challenges. Energy, Sustainability and Society, 12, Article 1. https://doi.org/10.1186/s13705-021-00328-y

Kolluru, M., & Semenenko, T. (2021). Income inequalities in EU countries: Gini indicator analysis. Economics, 9(1), 125–142. https://doi.org/10.2478/eoik-2021-0007

Lee, G. (2007). Long run equilibrium relationship between inward FDI and productivity. Journal of Economic Development, 32(2), 183–192. https://doi.org/10.35866/caujed.2007.32.2.008

Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1–24. https://doi.org/10.1016/S0304-4076(01)00098-7

Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics, 61(S1), 631–652. https://doi.org/10.1111/1468-0084.0610s1631

Mark, N. C., & Sul, D. (1999). A computationally simple cointegration vector estimator for panel data. Ohio State University Manuscript.

Mitić, P., Fedajev, A., Radulescu, M., & Rehman, A. (2023). The relationship between CO2 emissions, economic growth, available energy, and employment in SEE countries. Environmental Science and Pollution Research, 30, 16140–16155. https://doi.org/10.1007/s11356-022-23356-3

Narayan, P. K., & Smyth, R. (2007). A panel cointegration analysis of the demand for oil in the Middle East. Energy Policy, 35(12), 6258–6265. https://doi.org/10.1016/j.enpol.2007.07.011

Ndoricimpa, A. (2014). Heterogeneous panel causality between exports and growth in COMESA countries. The Journal of Developing Areas, 48(4), 349–361. https://doi.org/10.1353/jda.2014.0074

Nycander, E., Söder, L., Olauson, J., & Eriksson, R. (2020). Curtailment analysis for the Nordic power system considering transmission capacity, inertia limits and generation flexibility. Renewable Energy, 152, 942–960. https://doi.org/10.1016/j.renene.2020.01.059

Onofrei, M., Vatamanu, A. F., & Cigu, E. (2022). The relationship between economic growth and CO2 emissions in EU countries: A cointegration analysis. Frontiers in Environmental Science, 10, Article 934885. https://doi.org/10.3389/fenvs.2022.934885

Ozarisoy, B., & Altan, H. (2021). Developing an evidence-based energy-policy framework to assess robust energy-performance evaluation and certification schemes in the South-eastern Mediterranean countries. Energy for Sustainable Development, 64, 65–102. https://doi.org/10.1016/j.esd.2021.08.001

Parr, N. (2023). Immigration and the prospects for long-run population decreases in European countries. In Vienna yearbook of population research. https://doi.org/10.1553/p-8jf5-7cdc

Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics, 61(S1), 653–670. https://doi.org/10.1111/1468-0084.61.s1.14

Pedroni, P. (2000). Fully modified ols for heterogeneous cointegrated panels. In Nonstationary panels, panel cointegration and dynamic panels. https://doi.org/10.1016/S0731-9053(00)15004-2

Pedroni, P. (2001). Purchasing power parity tests in cointegrated panels. Review of Economics and Statistics, 83(4), 727–731. https://doi.org/10.1162/003465301753237803

Pedroni, P. (2004). Panel cointegration: Asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory, 20(3), 597–625. https://doi.org/10.1017/S0266466604203073

Popescu, M. F., Constantin, M., & Chiripuci, B. C. (2022). Transition to a sustainable energy production and consumption model – mapping the patterns of success. Journal of Business Economics and Management, 23(4), 915–936. https://doi.org/10.3846/jbem.2022.17022

Rahman, M. M., Nepal, R., & Alam, K. (2021). Impacts of human capital, exports, economic growth and energy consumption on CO2 emissions of a cross-sectionally dependent panel: Evidence from the newly industrialized countries (NICs). Environmental Science and Policy, 121, 24–36. https://doi.org/10.1016/j.envsci.2021.03.017

Ranta, T., Laihanen, M., & Karhunen, A. (2020). Development of the bioenergy as a part of renewable energy in the Nordic countries: A comparative analysis. Journal of Sustainable Bioenergy Systems, 10, 92–112. https://doi.org/10.4236/jsbs.2020.103008

Reyes, J. A. L. (2022). Willingness to share information for energy efficiency: Exploring differences and drivers across the Nordic countries. Energy, Sustainability and Society, 12, Article 38. https://doi.org/10.1186/s13705-022-00363-3

Rowe, F., Bell, M., Bernard, A., Charles-Edwards, E., & Ueffing, P. (2019). Impact of internal migration on population redistribution in Europe: Urbanisation, counterurbanisation or spatial equilibrium? Comparative Population Studies, 44. https://doi.org/10.12765/CPoS-2019-18

Sabău-Popa, D. C., Bolos, M. I., Scarlat, E., Delcea, C., & Bradea, I. A. (2014). Effects of macroeconomic variables on stock prices of the bucharest stock exchange (BSE). Economic Computation and Economic Cybernetics Studies and Research, 48(4), 103–114.

Scarlat, N., Prussi, M., & Padella, M. (2022). Quantification of the carbon intensity of electricity produced and used in Europe. Applied Energy, 305, 117901. https://doi.org/10.1016/j.apenergy.2021.117901

Tchapchet-Tchouto, J. E., Koné, N., & Njoya, L. (2022). Investigating the effects of environmental taxes on economic growth: Evidence from empirical analysis in European countries. Environmental Economics, 13(1), 1–15. https://doi.org/10.21511/ee.13(1).2022.01

Văduva, A.-G., Munteanu, M., Oprea, S.-V., Bâra, A., & Niculae, A.-M. (2023). Understanding climate change and air quality over the last decade: Evidence from news and weather data processing. IEEE Access, 11, 144631–144648. https://doi.org/10.1109/ACCESS.2023.3345466

Wang, X. C., Klemeš, J. J., Long, X., Zhang, P., Varbanov, P. S., Fan, W., Dong, X., & Wang, Y. (2020). Measuring the environmental performance of the EU27 from the Water-Energy-Carbon nexus perspective. Journal of Cleaner Production, 265, Article 121832. https://doi.org/10.1016/j.jclepro.2020.121832

Wu, L., Adebayo, T. S., Yue, X. G., & Umut, A. (2023). The role of renewable energy consumption and financial development in environmental sustainability: Implications for the Nordic Countries. International Journal of Sustainable Development and World Ecology, 30(1), 21–36. https://doi.org/10.1080/13504509.2022.2115577

Xiao, L., Guan, Y., Guo, Y., Xue, R., Li, J., & Shan, Y. (2022). Emission accounting and drivers in 2004 EU accession countries. Applied Energy, 14, Article 118964. https://doi.org/10.1016/j.apenergy.2022.118964

Yang, B., Wu, Q., Sharif, A., & Uddin, G. S. (2023). Non-linear impact of natural resources, green financing, and energy transition on sustainable environment: A way out for common prosperity in NORDIC countries. Resources Policy, 83, Article 103683. https://doi.org/10.1016/j.resourpol.2023.103683

Zlateva, P., Yordanov, K., Tudorache, A., & Cirtina, L. M. (2020). An analysis of energy resources in Bulgaria and Romania. In 2020 21st International Symposium on Electrical Apparatus and Technologies, SIELA 2020 – Proceedings. IEEE. https://doi.org/10.1109/SIELA49118.2020.