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The Impacts of Renewable Energy Consumption on Unemployment: An Empirical Investigation on BRICS-T Countries

Year 2024, Volume: 23 Issue: 2, 633 - 653, 26.04.2024
https://doi.org/10.21547/jss.1412409

Abstract

Unemployment and environmental pollution are two significant obstacles to achieving long-term development goals in most countries. The literature generally agrees that shifting the basic dynamic of economic activity from fossil energy to renewable energy sources is necessary to solve these two problems simultaneously. This paper examines the dynamic influences of renewable energy (REN) consumption on unemployment in BRICS-T (Brazil, Russia, India, South Africa, and Türkiye) countries using annual data spanning from 1991 to 2021. To this end, the bootstrap LM test is first used to evaluate the cointegration relationship between REN consumption, fossil fuel utilization, economic growth, and unemployment variables included in the econometric model to be estimated in the study. Then, the short and long-term connections between the analyzed variables are explored using the cross-sectionally augmented ARDL (CS-ARDL) model, which can produce consistent results when there is cross-sectional dependence and slope heterogeneity and when the variables exhibit different stationarity properties. Findings from the bootstrap LM test provide evidence of a long run cointegration association between the variables. Moreover, the CS-ARDL model estimation results demonstrate a negative but statistically insignificant connection between REN consumption and unemployment and that economic growth and fossil fuel usage significantly reduce unemployment in the short and long run. These outcomes suggest that the proportion of REN in total energy consumption in BRICS-T nations has yet to reach a sufficient level to realize its potential to reduce unemployment and/or that the economies of these countries depend on traditional energy. The findings also confirm the validity of Okun's Law in the sample nations.

References

  • Ağpak, F. ve Özçiçek, Ö. (2018). Bir istihdam politikası aracı olarak yenilenebilir enerji. Ömer Halisdemir Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 11(2), 112-128.
  • Alabed, Q. M. Q., Said, F. F., Karim, Z. A., Zaidi, M. A. S. and Mansour, M. (2022). Determinants of Unemployment in the MENA Region: New Evidence Using Dynamic Heterogeneous Panel Analysis. In International Conference on Advanced Machine Learning Technologies and Applications (s. 401-411). Cham: Springer International Publishing.
  • Álvarez, G. C., Jara, R. M., Julián, J. R. R. and Bielsa, J. I. G. (2010). Study of the effects on employment of public aid to renewable energy sources. Procesos de Mercado: Revista Europea de Economía Política, 7(1), 13-70.
  • Aminu, U., Abel, A. and Garba, A. R. (2022). Does the Okun's Law Hold in the BRICS Countries and Nigeria?. Economic and Financial Review, 60(2), 71-91.
  • Apergis, N. and Salim, R. (2015). Renewable energy consumption and unemployment: Evidence from a sample of 80 countries and nonlinear estimates. Applied Economics, 47(52), 5614-5633.
  • Arango, L. E. and Flórez, L. A. (2020). Determinants of structural unemployment in Colombia: A search approach. Empirical Economics, 58(5), 2431-2464.
  • Arvanitopoulos, T. and Agnolucci, P. (2020). The long-term effect of renewable electricity on employment in the United Kingdom. Renewable and Sustainable Energy Reviews, 134, 110322.
  • Aslani, A., Helo, P. and Naaranoja, M. (2014). Role of renewable energy policies in energy dependency in Finland: System dynamics approach. Applied Energy, 113, 758-765.
  • Azretbergenova, G. Ž., Syzdykov, B., Niyazov, T., Gulzhan, T. and Yskak, N. (2021). The relationship between renewable energy production and employment in European union countries: Panel data analysis. International Journal of Energy Economics and Policy, 11(3), 20-26.
  • Barros, J. J. C., Coira, M. L., de la Cruz López, M. P. and del Caño Gochi, A. (2017). Comparative analysis of direct employment generated by renewable and non-renewable power plants. Energy, 139, 542-554.
  • Biagi, F. and Lucifora, C. (2008). Demographic and education effects on unemployment in Europe. Labour Economics, 15(5), 1076-1101.
  • Böhringer, C., Keller, A. and Van der Werf, E. (2013). Are green hopes too rosy? Employment and welfare impacts of renewable energy promotion. Energy Economics, 36, 277-285.
  • Breitung, J. (2005). A parametric approach to the estimation of cointegration vectors in panel data. Econometric Reviews, 24(2), 151-173.
  • Breusch, T. S. and Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253.
  • Briggs, C., Atherton, A., Gill, J., Langdon, R., Rutovitz, J. and Nagrath, K. (2022). Building a ‘Fair and Fast’energy transition? Renewable energy employment, skill shortages and social licence in regional areas. Renewable and Sustainable Energy Transition, 2, 100039.
  • Cameron, L. and Van Der Zwaan, B. (2015). Employment factors for wind and solar energy technologies: A literature review. Renewable and Sustainable Energy Reviews, 45, 160-172.
  • Cheema, A. R. and Atta, A. (2014). Economic determinants of unemployment in Pakistan: Co-integration analysis. International Journal of Business and Social Science, 5(3), 209-221.
  • Chudik, A. and Pesaran, M. H. (2015). Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics, 188(2), 393-420.
  • Çağlar, A. E. (2021). Çevresel bozulmaların bir göstergesi olarak karbon emisyonlarının durağanlığı: Karbon Histeri Hipotezi. (Doktora tezi). YÖK Tez Merkezi veri tabanından erişildi. https://tez.yok.gov.tr/UlusalTezMerkezi/tezSorguSonucYeni.jsp
  • Çaglar, A. E. and Mert, M. (2022). Carbon hysteresis hypothesis as a new approach to emission behavior: A case of top five emitters. Gondwana Research, 109, 171-182.
  • Çaglar, A. E. and Yavuz, E. (2023). The role of environmental protection expenditures and renewable energy consumption in the context of ecological challenges: Insights from the European Union with the novel panel econometric approach. Journal of Environmental Management, 331, 117317.
  • Çaglar, A. E., Daştan, M., Bulut, E. and Marangoz, C. (2023a). Evaluating a pathway for environmental sustainability: The role of competitive industrial performance and renewable energy consumption in European countries. Sustainable Development.
  • Çaglar, A. E., Daştan, M., Mehmood, U. and Avci, S. B. (2023b). Assessing the connection between competitive industrial performance on load capacity factor within the LCC framework: Implications for sustainable policy in BRICS economies. Environmental Science and Pollution Research, 1-18.
  • Çelik, O. (2021). Assessment of the relationship between renewable energy and employment of the United States of America: Empirical evidence from spectral Granger causality. Environmental Science and Pollution Research, 28(11), 13047-13054.
  • Çoban, M. N. (2022). Yenilenebilir enerji tüketimi ve işsizlik arasındaki ilişki: ASEAN-5 ülkeleri için ekonometrik bir uygulama. Uluslararası Ekonomi ve Siyaset Bilimleri Akademik Araştırmalar Dergisi, 6(14), 1-10.
  • Destek, M. A., Ozsoy, F. N. and Ozpolat, A. (2020). Investigation on the job creation effect of green energy in OECD countries. Shahbaz, M. ve Balsalobre-Lorente, D. (Ed.) Econometrics of Green Energy Handbook: Economic and Technological Development, 131-149. Springer Nature, Switzerland.
  • Di Nallo, A., Lipps, O., Oesch, D. and Voorpostel, M. (2022). The effect of unemployment on couples separating in Germany and the UK. Journal of Marriage and Family, 84(1), 310-329.
  • Dincer, I. (2000). Renewable energy and sustainable development: A crucial review. Renewable and Sustainable Energy Reviews, 4(2), 157-175.
  • Dogan, E. and Seker, F. (2016). An investigation on the determinants of carbon emissions for OECD countries: Empirical evidence from panel models robust to heterogeneity and cross-sectional dependence. Environmental Science and Pollution Research, 23, 14646-14655.
  • Dünya Bankası (2023). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators.
  • El Moummy, C., Salmi, Y., and Baddih, H. (2021). The role of renewable energy sector in reducing unemployment: The Moroccan case. In E3S Web of Conferences (Vol. 234, p. 00101). EDP Sciences.
  • Energy Institute (2023). Statistical Review of World Energy. https://www.energyinst.org/statistical-review
  • Ferroukhi, R., Lucas, H., Renner, M., Lehr, U., Breitschopf, B., Lallement, D. and Petrick, K. (2013). Renewable energy and jobs. The International Renewable Energy Agency (IRENA).
  • Fragkos, P. and Paroussos, L. (2018). Employment creation in EU related to renewables expansion. Applied Energy, 230, 935-945.
  • Frondel, M., Ritter, N., Schmidt, C. M. and Vance, C. (2010). Economic impacts from the promotion of renewable energy technologies: The German experience. Energy Policy, 38(8), 4048-4056.
  • Garrett-Peltier, H. (2017). Green versus brown: Comparing the employment impacts of energy efficiency, renewable energy, and fossil fuels using an input-output model. Economic Modelling, 61, 439-447.
  • Halužan, M., Verbič, M. and Zorić, J. (2023). The crowding out of conventional electricity generation by renewable energy sources: Implications from Greek, Hungarian, and Romanian electricity markets. Environmental Science and Pollution Research, 1-22.
  • Hashmi, S. M., Khushik, A. G., Gilal, M. A. and Yongliang, Z. (2021). The impact of GDP and its expenditure components on unemployment within BRICS countries: Evidence of Okun’s law from aggregate and disaggregated approaches. SAGE Open, 11(2), 21582440211023423.
  • Hieu, V. M. and Mai, N. H. (2023). Impact of renewable energy on economic growth? Novel evidence from developing countries through MMQR estimations. Environmental Science and Pollution Research, 30(1), 578-593.
  • Ibragimov, M. and Ibragimov, R. (2017). Unemployment and output dynamics in CIS countries: Okun’s law revisited. Applied Economics, 49(34), 3453-3479.
  • Ibrahiem, D. M. and Sameh, R. (2020). How do clean energy sources and financial development affect unemployment? Empirical evidence from Egypt. Environmental Science and Pollution Research, 27, 22770-22779.
  • ILO (2021). Uncertain and uneven recovery expected following unprecedented labour market crisis. https://www.ilo.org/global/about-the-ilo/newsroom/news/WCMS_766949/lang--en/index.htm#2 ILO (2023). World Employment and Social Outlook: Trends 2023.
  • Im, K. S., Pesaran, M. H. and Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of econometrics, 115(1), 53-74.
  • Kasperowicz, R., Bilan, Y. and Štreimikienė, D. (2020). The renewable energy and economic growth nexus in European countries. Sustainable Development, 28(5), 1086-1093.
  • Khobai, H., Kolisi, N., Moyo, C., Anyikwa, I. and Dingela, S. (2020). Renewable energy consumption and unemployment in South Africa. International Journal of Energy Economics and Policy, 10(2), 170-178.
  • Kukharets, V., Hutsol, T., Kukharets, S., Glowacki, S., Nurek, T. and Sorokin, D. (2023). European Green Deal: The impact of the level of renewable energy source and gross domestic product per capita on energy import dependency. Sustainability, 15(15), 11817.
  • Lee, C. C. and Chang, C. P. (2008). New evidence on the convergence of per capita carbon dioxide emissions from panel seemingly unrelated regressions augmented Dickey–Fuller tests. Energy, 33(9), 1468-1475.
  • Lehr, U., Nitsch, J., Kratzat, M., Lutz, C. and Edler, D. (2008). Renewable energy and employment in Germany. Energy policy, 36(1), 108-117.
  • Levin, A., Lin, C. F. and Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of econometrics, 108(1), 1-24.
  • Liu, J., Ge, J. and He, H. (2023). The evolution of renewable energy and its impact on employment in China: Assessing the role of education. Environmental Science and Pollution Research, 1-13.
  • Markaki, M., Belegri-Roboli, A., Michaelides, P., Mirasgedis, S. and Lalas, D. P. (2013). The impact of clean energy investments on the Greek economy: An input–output analysis (2010–2020). Energy Policy, 57, 263-275.
  • Markandya, A., Arto, I., González-Eguino, M. and Román, M. V. (2016). Towards a green energy economy? Tracking the employment effects of low-carbon technologies in the European Union. Applied energy, 179, 1342-1350.
  • Meyer, I. and Sommer, M. W. (2014). Employment effects of renewable energy supply-a meta-analysis. Policy Paper, 12.
  • Moreno, B. and Lopez, A. J. (2008). The effect of renewable energy on employment. The case of Asturias (Spain). Renewable and Sustainable Energy Reviews, 12(3), 732-751.
  • Mu, Y., Cai, W., Evans, S., Wang, C. and Roland-Holst, D. (2018). Employment impacts of renewable energy policies in China: A decomposition analysis based on a CGE modeling framework. Applied Energy, 210, 256-267.
  • Naqvi, S., Wang, J. and Ali, R. (2022). Towards a green economy in Europe: Does renewable energy production has asymmetric effects on unemployment?. Environmental Science and Pollution Research, 1-8.
  • Nasirov, S., Girard, A., Peña, C., Salazar, F. and Simon, F. (2021). Expansion of renewable energy in Chile: Analysis of the effects on employment. Energy, 226, 120410.
  • Nickell, S., Nunziata, L. and Ochel, W. (2005). Unemployment in the OECD since the 1960s. What do we know?. The Economic Journal, 115(500), 1-27.
  • Ocal, O. and Aslan, A. (2013). Renewable energy consumption–economic growth nexus in Turkey. Renewable and sustainable energy reviews, 28, 494-499.
  • Okumus, I., Guzel, A. E. and Destek, M. A. (2021). Renewable, non-renewable energy consumption and economic growth nexus in G7: Fresh evidence from CS-ARDL. Environmental Science and Pollution Research, 28(40), 56595-56605.
  • Okun, A. M. (1962). Potential GNP: Its Measurement and Significance. Reprinted as Cowles Foundation Paper 190.
  • Özmen, İ., Gerçeker, M. and Mucuk, M. (2022). How does increasing renewable energy and decreasing coal-based electricity generation affect the future of unemployment in developed countries: A heterogeneous panel data analysis?. Boğaziçi Journal, 36(1), 18-39.
  • Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. Cambridge Working Papers. Economics, 1240(1), 1.
  • 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.
  • Pesaran, M. H. and Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93.
  • Pesaran, M. H., Ullah, A. and Yamagata, T. (2008). A bias‐adjusted LM test of error cross‐section independence. The Econometrics Journal, 11(1), 105-127.
  • Rafiq, S., Salim, R. and Sgro, P. M. (2018). Energy, unemployment and trade. Applied Economics, 50(47), 5122-5134.
  • Rahman, M. R., Rahman, M. M., and Akter, R. (2023). Renewable energy development, unemployment and GDP growth: South Asian evidence. Arab Gulf Journal of Scientific Research.
  • Romero-Ávila, D. and Omay, T. (2022). Are CO2 emissions stationary after all? New evidence from nonlinear unit root tests. Environmental Modeling & Assessment, 27(4), 621-643.
  • Rueda, D. (2006). Social democracy and active labour-market policies: Insiders, outsiders and the politics of employment promotion. British Journal of Political Science, 36(3), 385-406.
  • Saboori, B., Gholipour, H. F., Rasoulinezhad, E. and Ranjbar, O. (2022). Renewable energy sources and unemployment rate: Evidence from the US states. Energy Policy, 168, 113155.
  • Seyfried, W. (2011). Examining the relationship between employment and economic growth in the ten largest states. Southwestern Economic Review, 32, 13-24.
  • Shin, Y., Yu, B. and Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. Festschrift in honor of Peter Schmidt: Econometric methods and applications, 281-314.
  • Stavropoulos, S. and Burger, M. J. (2020). Modelling strategy and net employment effects of renewable energy and energy efficiency: A meta-regression. Energy Policy, 136, 111047.
  • Usman, A., Ozturk, I., Naqvi, S. M. M. A., Ullah, S. and Javed, M. I. (2022). Revealing the nexus between nuclear energy and ecological footprint in STIRPAT model of advanced economies: Fresh evidence from novel CS-ARDL model. Progress in Nuclear Energy, 148, 104220.
  • Wei, M., Patadia, S. and Kammen, D. M. (2010). Putting renewables and energy efficiency to work: How many jobs can the clean energy industry generate in the US?. Energy Policy, 38(2), 919-931.
  • Westerlund, J. and Edgerton, D. L. (2007). A panel bootstrap cointegration test. Economics Letters, 97(3), 185-190.
  • Yalçinkaya, Ö., Daştan, M. and Karabulut, K. (2018). Okun Yasası bağlamında ekonomik büyüme ve işsizlik arasındaki ilişkinin ekonometrik analizi: Türkiye ekonomisinden kanıtlar (2000: Q1-2017: Q4). Uluslararası Ekonomi Siyaset İnsan ve Toplum Bilimleri Dergisi, 1(1), 8-27.
  • Yılancı, V., İslamoğlu, E., Yıldırımalp, S. and Candan, G. (2020). The relationship between unemployment rates and renewable energy consumption: Evidence from Fourier ADL cointegration test. Alphanumeric Journal, 8(1), 17-28.
  • Zafar, M. W., Saleem, M. M., Destek, M. A. and Caglar, A. E. (2022). The dynamic linkage between remittances, export diversification, education, renewable energy consumption, economic growth, and CO2 emissions in top remittance‐receiving countries. Sustainable Development, 30(1), 165-175.
  • Zhang, X., Liu, F., Wang, H. and Nazir, R. (2023). Influence of ecological innovation and green energy investment on unemployment in China: evidence from advanced quantile approach. Economic research-Ekonomska istraživanja, 36(2).

Yenilenebilir Enerji Tüketiminin İşsizlik Üzerindeki Etkileri: BRICS-T Ülkeleri Üzerine Ampirik Bir İnceleme

Year 2024, Volume: 23 Issue: 2, 633 - 653, 26.04.2024
https://doi.org/10.21547/jss.1412409

Abstract

İşsizlik ve çevre kirliliği, çoğu ülke için uzun vadeli kalkınma hedeflerinin önündeki en büyük engellerden ikisini teşkil etmektedir. Literatürde bu iki sorunun aynı anda çözülebilmesi için ekonomik aktivitenin temel dinamiğinin fosil enerji kaynaklarından yenilenebilir enerji kaynaklarına evrilmesinin gerekliliği hususunda genel bir uzlaşı bulunmaktadır. Bu çalışmada, 1991-2021 dönemini kapsayan yıllık veriler kullanılarak BRICS-T (Brezilya, Rusya, Hindistan, Güney Afrika ve Türkiye’de) ülkelerinde yenilenebilir enerji (YEN) tüketiminin işsizlik üzerindeki dinamik etkileri incelenmektedir. Bu amaç doğrultusunda, öncelikle çalışmada tahmin edilecek ekonometrik modele dahil edilen YEN tüketimi, fosil yakıt tüketimi, ekonomik büyüme ve işsizlik değişkenleri arasındaki eş bütünleşme ilişkisi, bootstrap LM testine dayalı olarak araştırılmaktadır. Ardından, değişkenler arasındaki kısa ve uzun dönemli etkileşimler, yatay kesit bağımlılığının ve eğim heterojenliğinin söz konusu olduğu ve değişkenlerin farklı durağanlık özellikleri sergilediği durumlarda tutarlı sonuçlar üretebilen kesitsel olarak genişletilmiş ARDL (CS-ARDL) modelinden faydalanılarak analiz edilmektedir. Bootstrap LM test sonuçları, değişkenler arasında uzun dönemli eş-bütünleşme ilişkisinin bulunduğu yönünde kanıt sunmaktadır. CS-ARDL model tahmininden elde edilen sonuçlar ise YEN tüketimi ile işsizlik arasında negatif yönlü ancak istatistiki açıdan anlamsız bir ilişkinin bulunduğunu, buna karşılık ekonomik büyüme ile fosil yakıt tüketiminin işsizliği kısa ve uzun dönemde anlamlı bir şekilde azalttığını ortaya koymaktadır. Bu sonuçlar, BRICS-T ülkelerinde YEN tüketiminin işsizliği azaltacak potansiyelini gerçekleştirebilmesi için toplam enerji tüketimi içerisindeki payının henüz yeterli düzeye ulaşmadığını ve/veya söz konusu ülke ekonomilerinin geleneksel enerjiye bağlı olduğunu göstermektedir. Sonuçlar ayrıca, BRICS-T ülkelerinde Okun Yasasının geçerli olduğunu doğrulamaktadır.

References

  • Ağpak, F. ve Özçiçek, Ö. (2018). Bir istihdam politikası aracı olarak yenilenebilir enerji. Ömer Halisdemir Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 11(2), 112-128.
  • Alabed, Q. M. Q., Said, F. F., Karim, Z. A., Zaidi, M. A. S. and Mansour, M. (2022). Determinants of Unemployment in the MENA Region: New Evidence Using Dynamic Heterogeneous Panel Analysis. In International Conference on Advanced Machine Learning Technologies and Applications (s. 401-411). Cham: Springer International Publishing.
  • Álvarez, G. C., Jara, R. M., Julián, J. R. R. and Bielsa, J. I. G. (2010). Study of the effects on employment of public aid to renewable energy sources. Procesos de Mercado: Revista Europea de Economía Política, 7(1), 13-70.
  • Aminu, U., Abel, A. and Garba, A. R. (2022). Does the Okun's Law Hold in the BRICS Countries and Nigeria?. Economic and Financial Review, 60(2), 71-91.
  • Apergis, N. and Salim, R. (2015). Renewable energy consumption and unemployment: Evidence from a sample of 80 countries and nonlinear estimates. Applied Economics, 47(52), 5614-5633.
  • Arango, L. E. and Flórez, L. A. (2020). Determinants of structural unemployment in Colombia: A search approach. Empirical Economics, 58(5), 2431-2464.
  • Arvanitopoulos, T. and Agnolucci, P. (2020). The long-term effect of renewable electricity on employment in the United Kingdom. Renewable and Sustainable Energy Reviews, 134, 110322.
  • Aslani, A., Helo, P. and Naaranoja, M. (2014). Role of renewable energy policies in energy dependency in Finland: System dynamics approach. Applied Energy, 113, 758-765.
  • Azretbergenova, G. Ž., Syzdykov, B., Niyazov, T., Gulzhan, T. and Yskak, N. (2021). The relationship between renewable energy production and employment in European union countries: Panel data analysis. International Journal of Energy Economics and Policy, 11(3), 20-26.
  • Barros, J. J. C., Coira, M. L., de la Cruz López, M. P. and del Caño Gochi, A. (2017). Comparative analysis of direct employment generated by renewable and non-renewable power plants. Energy, 139, 542-554.
  • Biagi, F. and Lucifora, C. (2008). Demographic and education effects on unemployment in Europe. Labour Economics, 15(5), 1076-1101.
  • Böhringer, C., Keller, A. and Van der Werf, E. (2013). Are green hopes too rosy? Employment and welfare impacts of renewable energy promotion. Energy Economics, 36, 277-285.
  • Breitung, J. (2005). A parametric approach to the estimation of cointegration vectors in panel data. Econometric Reviews, 24(2), 151-173.
  • Breusch, T. S. and Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253.
  • Briggs, C., Atherton, A., Gill, J., Langdon, R., Rutovitz, J. and Nagrath, K. (2022). Building a ‘Fair and Fast’energy transition? Renewable energy employment, skill shortages and social licence in regional areas. Renewable and Sustainable Energy Transition, 2, 100039.
  • Cameron, L. and Van Der Zwaan, B. (2015). Employment factors for wind and solar energy technologies: A literature review. Renewable and Sustainable Energy Reviews, 45, 160-172.
  • Cheema, A. R. and Atta, A. (2014). Economic determinants of unemployment in Pakistan: Co-integration analysis. International Journal of Business and Social Science, 5(3), 209-221.
  • Chudik, A. and Pesaran, M. H. (2015). Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics, 188(2), 393-420.
  • Çağlar, A. E. (2021). Çevresel bozulmaların bir göstergesi olarak karbon emisyonlarının durağanlığı: Karbon Histeri Hipotezi. (Doktora tezi). YÖK Tez Merkezi veri tabanından erişildi. https://tez.yok.gov.tr/UlusalTezMerkezi/tezSorguSonucYeni.jsp
  • Çaglar, A. E. and Mert, M. (2022). Carbon hysteresis hypothesis as a new approach to emission behavior: A case of top five emitters. Gondwana Research, 109, 171-182.
  • Çaglar, A. E. and Yavuz, E. (2023). The role of environmental protection expenditures and renewable energy consumption in the context of ecological challenges: Insights from the European Union with the novel panel econometric approach. Journal of Environmental Management, 331, 117317.
  • Çaglar, A. E., Daştan, M., Bulut, E. and Marangoz, C. (2023a). Evaluating a pathway for environmental sustainability: The role of competitive industrial performance and renewable energy consumption in European countries. Sustainable Development.
  • Çaglar, A. E., Daştan, M., Mehmood, U. and Avci, S. B. (2023b). Assessing the connection between competitive industrial performance on load capacity factor within the LCC framework: Implications for sustainable policy in BRICS economies. Environmental Science and Pollution Research, 1-18.
  • Çelik, O. (2021). Assessment of the relationship between renewable energy and employment of the United States of America: Empirical evidence from spectral Granger causality. Environmental Science and Pollution Research, 28(11), 13047-13054.
  • Çoban, M. N. (2022). Yenilenebilir enerji tüketimi ve işsizlik arasındaki ilişki: ASEAN-5 ülkeleri için ekonometrik bir uygulama. Uluslararası Ekonomi ve Siyaset Bilimleri Akademik Araştırmalar Dergisi, 6(14), 1-10.
  • Destek, M. A., Ozsoy, F. N. and Ozpolat, A. (2020). Investigation on the job creation effect of green energy in OECD countries. Shahbaz, M. ve Balsalobre-Lorente, D. (Ed.) Econometrics of Green Energy Handbook: Economic and Technological Development, 131-149. Springer Nature, Switzerland.
  • Di Nallo, A., Lipps, O., Oesch, D. and Voorpostel, M. (2022). The effect of unemployment on couples separating in Germany and the UK. Journal of Marriage and Family, 84(1), 310-329.
  • Dincer, I. (2000). Renewable energy and sustainable development: A crucial review. Renewable and Sustainable Energy Reviews, 4(2), 157-175.
  • Dogan, E. and Seker, F. (2016). An investigation on the determinants of carbon emissions for OECD countries: Empirical evidence from panel models robust to heterogeneity and cross-sectional dependence. Environmental Science and Pollution Research, 23, 14646-14655.
  • Dünya Bankası (2023). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators.
  • El Moummy, C., Salmi, Y., and Baddih, H. (2021). The role of renewable energy sector in reducing unemployment: The Moroccan case. In E3S Web of Conferences (Vol. 234, p. 00101). EDP Sciences.
  • Energy Institute (2023). Statistical Review of World Energy. https://www.energyinst.org/statistical-review
  • Ferroukhi, R., Lucas, H., Renner, M., Lehr, U., Breitschopf, B., Lallement, D. and Petrick, K. (2013). Renewable energy and jobs. The International Renewable Energy Agency (IRENA).
  • Fragkos, P. and Paroussos, L. (2018). Employment creation in EU related to renewables expansion. Applied Energy, 230, 935-945.
  • Frondel, M., Ritter, N., Schmidt, C. M. and Vance, C. (2010). Economic impacts from the promotion of renewable energy technologies: The German experience. Energy Policy, 38(8), 4048-4056.
  • Garrett-Peltier, H. (2017). Green versus brown: Comparing the employment impacts of energy efficiency, renewable energy, and fossil fuels using an input-output model. Economic Modelling, 61, 439-447.
  • Halužan, M., Verbič, M. and Zorić, J. (2023). The crowding out of conventional electricity generation by renewable energy sources: Implications from Greek, Hungarian, and Romanian electricity markets. Environmental Science and Pollution Research, 1-22.
  • Hashmi, S. M., Khushik, A. G., Gilal, M. A. and Yongliang, Z. (2021). The impact of GDP and its expenditure components on unemployment within BRICS countries: Evidence of Okun’s law from aggregate and disaggregated approaches. SAGE Open, 11(2), 21582440211023423.
  • Hieu, V. M. and Mai, N. H. (2023). Impact of renewable energy on economic growth? Novel evidence from developing countries through MMQR estimations. Environmental Science and Pollution Research, 30(1), 578-593.
  • Ibragimov, M. and Ibragimov, R. (2017). Unemployment and output dynamics in CIS countries: Okun’s law revisited. Applied Economics, 49(34), 3453-3479.
  • Ibrahiem, D. M. and Sameh, R. (2020). How do clean energy sources and financial development affect unemployment? Empirical evidence from Egypt. Environmental Science and Pollution Research, 27, 22770-22779.
  • ILO (2021). Uncertain and uneven recovery expected following unprecedented labour market crisis. https://www.ilo.org/global/about-the-ilo/newsroom/news/WCMS_766949/lang--en/index.htm#2 ILO (2023). World Employment and Social Outlook: Trends 2023.
  • Im, K. S., Pesaran, M. H. and Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of econometrics, 115(1), 53-74.
  • Kasperowicz, R., Bilan, Y. and Štreimikienė, D. (2020). The renewable energy and economic growth nexus in European countries. Sustainable Development, 28(5), 1086-1093.
  • Khobai, H., Kolisi, N., Moyo, C., Anyikwa, I. and Dingela, S. (2020). Renewable energy consumption and unemployment in South Africa. International Journal of Energy Economics and Policy, 10(2), 170-178.
  • Kukharets, V., Hutsol, T., Kukharets, S., Glowacki, S., Nurek, T. and Sorokin, D. (2023). European Green Deal: The impact of the level of renewable energy source and gross domestic product per capita on energy import dependency. Sustainability, 15(15), 11817.
  • Lee, C. C. and Chang, C. P. (2008). New evidence on the convergence of per capita carbon dioxide emissions from panel seemingly unrelated regressions augmented Dickey–Fuller tests. Energy, 33(9), 1468-1475.
  • Lehr, U., Nitsch, J., Kratzat, M., Lutz, C. and Edler, D. (2008). Renewable energy and employment in Germany. Energy policy, 36(1), 108-117.
  • Levin, A., Lin, C. F. and Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of econometrics, 108(1), 1-24.
  • Liu, J., Ge, J. and He, H. (2023). The evolution of renewable energy and its impact on employment in China: Assessing the role of education. Environmental Science and Pollution Research, 1-13.
  • Markaki, M., Belegri-Roboli, A., Michaelides, P., Mirasgedis, S. and Lalas, D. P. (2013). The impact of clean energy investments on the Greek economy: An input–output analysis (2010–2020). Energy Policy, 57, 263-275.
  • Markandya, A., Arto, I., González-Eguino, M. and Román, M. V. (2016). Towards a green energy economy? Tracking the employment effects of low-carbon technologies in the European Union. Applied energy, 179, 1342-1350.
  • Meyer, I. and Sommer, M. W. (2014). Employment effects of renewable energy supply-a meta-analysis. Policy Paper, 12.
  • Moreno, B. and Lopez, A. J. (2008). The effect of renewable energy on employment. The case of Asturias (Spain). Renewable and Sustainable Energy Reviews, 12(3), 732-751.
  • Mu, Y., Cai, W., Evans, S., Wang, C. and Roland-Holst, D. (2018). Employment impacts of renewable energy policies in China: A decomposition analysis based on a CGE modeling framework. Applied Energy, 210, 256-267.
  • Naqvi, S., Wang, J. and Ali, R. (2022). Towards a green economy in Europe: Does renewable energy production has asymmetric effects on unemployment?. Environmental Science and Pollution Research, 1-8.
  • Nasirov, S., Girard, A., Peña, C., Salazar, F. and Simon, F. (2021). Expansion of renewable energy in Chile: Analysis of the effects on employment. Energy, 226, 120410.
  • Nickell, S., Nunziata, L. and Ochel, W. (2005). Unemployment in the OECD since the 1960s. What do we know?. The Economic Journal, 115(500), 1-27.
  • Ocal, O. and Aslan, A. (2013). Renewable energy consumption–economic growth nexus in Turkey. Renewable and sustainable energy reviews, 28, 494-499.
  • Okumus, I., Guzel, A. E. and Destek, M. A. (2021). Renewable, non-renewable energy consumption and economic growth nexus in G7: Fresh evidence from CS-ARDL. Environmental Science and Pollution Research, 28(40), 56595-56605.
  • Okun, A. M. (1962). Potential GNP: Its Measurement and Significance. Reprinted as Cowles Foundation Paper 190.
  • Özmen, İ., Gerçeker, M. and Mucuk, M. (2022). How does increasing renewable energy and decreasing coal-based electricity generation affect the future of unemployment in developed countries: A heterogeneous panel data analysis?. Boğaziçi Journal, 36(1), 18-39.
  • Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. Cambridge Working Papers. Economics, 1240(1), 1.
  • 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.
  • Pesaran, M. H. and Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93.
  • Pesaran, M. H., Ullah, A. and Yamagata, T. (2008). A bias‐adjusted LM test of error cross‐section independence. The Econometrics Journal, 11(1), 105-127.
  • Rafiq, S., Salim, R. and Sgro, P. M. (2018). Energy, unemployment and trade. Applied Economics, 50(47), 5122-5134.
  • Rahman, M. R., Rahman, M. M., and Akter, R. (2023). Renewable energy development, unemployment and GDP growth: South Asian evidence. Arab Gulf Journal of Scientific Research.
  • Romero-Ávila, D. and Omay, T. (2022). Are CO2 emissions stationary after all? New evidence from nonlinear unit root tests. Environmental Modeling & Assessment, 27(4), 621-643.
  • Rueda, D. (2006). Social democracy and active labour-market policies: Insiders, outsiders and the politics of employment promotion. British Journal of Political Science, 36(3), 385-406.
  • Saboori, B., Gholipour, H. F., Rasoulinezhad, E. and Ranjbar, O. (2022). Renewable energy sources and unemployment rate: Evidence from the US states. Energy Policy, 168, 113155.
  • Seyfried, W. (2011). Examining the relationship between employment and economic growth in the ten largest states. Southwestern Economic Review, 32, 13-24.
  • Shin, Y., Yu, B. and Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. Festschrift in honor of Peter Schmidt: Econometric methods and applications, 281-314.
  • Stavropoulos, S. and Burger, M. J. (2020). Modelling strategy and net employment effects of renewable energy and energy efficiency: A meta-regression. Energy Policy, 136, 111047.
  • Usman, A., Ozturk, I., Naqvi, S. M. M. A., Ullah, S. and Javed, M. I. (2022). Revealing the nexus between nuclear energy and ecological footprint in STIRPAT model of advanced economies: Fresh evidence from novel CS-ARDL model. Progress in Nuclear Energy, 148, 104220.
  • Wei, M., Patadia, S. and Kammen, D. M. (2010). Putting renewables and energy efficiency to work: How many jobs can the clean energy industry generate in the US?. Energy Policy, 38(2), 919-931.
  • Westerlund, J. and Edgerton, D. L. (2007). A panel bootstrap cointegration test. Economics Letters, 97(3), 185-190.
  • Yalçinkaya, Ö., Daştan, M. and Karabulut, K. (2018). Okun Yasası bağlamında ekonomik büyüme ve işsizlik arasındaki ilişkinin ekonometrik analizi: Türkiye ekonomisinden kanıtlar (2000: Q1-2017: Q4). Uluslararası Ekonomi Siyaset İnsan ve Toplum Bilimleri Dergisi, 1(1), 8-27.
  • Yılancı, V., İslamoğlu, E., Yıldırımalp, S. and Candan, G. (2020). The relationship between unemployment rates and renewable energy consumption: Evidence from Fourier ADL cointegration test. Alphanumeric Journal, 8(1), 17-28.
  • Zafar, M. W., Saleem, M. M., Destek, M. A. and Caglar, A. E. (2022). The dynamic linkage between remittances, export diversification, education, renewable energy consumption, economic growth, and CO2 emissions in top remittance‐receiving countries. Sustainable Development, 30(1), 165-175.
  • Zhang, X., Liu, F., Wang, H. and Nazir, R. (2023). Influence of ecological innovation and green energy investment on unemployment in China: evidence from advanced quantile approach. Economic research-Ekonomska istraživanja, 36(2).
There are 81 citations in total.

Details

Primary Language Turkish
Subjects Applied Macroeconometrics
Journal Section Economics
Authors

Muhammet Daştan 0000-0001-6067-8946

Publication Date April 26, 2024
Submission Date December 30, 2023
Acceptance Date March 25, 2024
Published in Issue Year 2024 Volume: 23 Issue: 2

Cite

APA Daştan, M. (2024). Yenilenebilir Enerji Tüketiminin İşsizlik Üzerindeki Etkileri: BRICS-T Ülkeleri Üzerine Ampirik Bir İnceleme. Gaziantep Üniversitesi Sosyal Bilimler Dergisi, 23(2), 633-653. https://doi.org/10.21547/jss.1412409