THE RELATIONSHIP BETWEEN ECONOMIC FREEDOM AND ECOLOGICAL FOOTPRINT IN G-7 COUNTRIES: ANALYSIS WITH QRPD METHOD

Year 2024, Volume: 15 Issue: 29, 163 - 187, 28.06.2024

Ömer Faruk Biçen , Mustafa Necati Çoban

https://doi.org/10.36543/kauiibfd.2024.007

Abstract

This study aims to investigate the effect of economic freedom on ecological footprint in G-7 countries. To achieve this goal, we used annual data of G-7 countries during the period 1998-2018. In the analysis, quantile regression estimator for panel data (QRPD) with nonadditive fixed effects by Powell (2022) was applied as a newly developed method. In the study, ecological footprint was used as the dependent variable and Economic Freedom Index was used as the independent variable. As a result of the analyses performed, it was found that economic freedom increases the ecological footprint in G-7 countries for all three quantiles.

Keywords

Economic freedom, ecological footprint, QRPD

G-7 ÜLKELERİNDE EKONOMİK ÖZGÜRLÜK İLE EKOLOJİK AYAK İZİ İLİŞKİSİ: QRPD YÖNTEMİ İLE ANALİZ

Abstract

Bu çalışmada G-7 ülkelerinde ekonomik özgürlüğün ekolojik ayak izine etkisinin araştırılması amaçlanmaktadır. Belirtilen bu amaç doğrultusunda G-7 ülkeleri için 1998-2018 dönemini kapsayan yıllık veriler analize dahil edilmiştir. Analizin gerçekleştirilmesinde güncel bir yöntem olarak Powell (2022) tarafından geliştirilen QRPD (quantile regression for panel data with non-additive fixed effects) uygulanmıştır. Çalışmada bağımlı değişken olarak ekolojik ayak izi, bağımsız değişken olarak Ekonomik Özgürlük Endeksi kullanılmıştır. Yapılan analizler sonucunda araştırılan tüm kantil düzeyleri için G-7 ülkelerinde ekonomik özgürlüğün ekolojik ayak izini artırdığı bulgusu elde edilmiştir.

Keywords

Ekonomik özgürlük, Ekolojik ayak izi, QRPD

References

• Acar, T. & Topdağ, D. (2022). OECD ülkelerinde sefalet endeksi ve ekonomik kalkınma ekseninde sağlık harcamalarının belirleyicileri: Toplamsal olmayan sabit etkili panel kantil regresyon yaklaşımı, Sosyal Siyaset Konferansları Dergisi, 82, 267-286. https://doi.org/10.26650/jspc.2022.82.946640.
• Adesina, K. S., & Mwamba, J. W. M. (2019). Does economic freedom matter for CO2 emissions? Lessons from Africa. The Journal of Developing Areas, 53(3).
• Akadırı, S.S., Alola, A.A. & Usman, O. (2021). Energy mix outlook and the EKC hypothesis in BRICS countries: A perspective of economic freedom vs. economic growth. Environmental Science and Pollution Research, 28, 8922–8926. https://doi.org/10.1007/s11356-020-11964-w
• Alharthi, M., Dogan, E., & Taskin, D. (2021). Analysis of CO2 emissions and energy consumption by sources in MENA countries: Evidence from quantile regressions, Environmental Science and Pollution Research, 28, 1-8.
• Al-Mulali, U., Tang, C.F. & Ozturk, I. (2015). Estimating the environment Kuznets curve hypothesis: Evidence from Latin America and the Caribbean countries, Renewable and Sustainable Energy Reviews, 50, 918–924.
• Alola, A.A., Alola, U.V., Akdag, S. & Yildirim, S. (2022). The role of economic freedom and clean energy in environmental sustainability: Implication for the G-20 economies, Environmental Science and Pollution Research, 29, 36608–36615. https://doi.org/10.1007/s11356-022-18666-5.
• Amegavi, G.B., Langnel, Z., Ahenkan, A. & Buabeng, T. (2022). The dynamic relationship between economic globalisation, institutional quality, and ecological footprint: Evidence from Ghana”, Journal of International Trade and Economic Development, 31(6), 1–18. https://doi.org/10.1080/ 09638199.2022.2033303
• Amin, S., Li, C., Khan, Y.A & Bibi, A. (2022). Fishing grounds footprint and economic freedom indexes: Evidence from Asia-Pacific, PLoS ONE, 17(4), 1-16, e0263872. https://doi.org/10.1371/journal.pone.0263872
• Antweiler, W., Copeland, B. R., & Taylor, M. S. (2001). Is free trade good for the environment?. American Economic Review, 91(4), 877-908.
• Ashraf, J. (2022). The spillover effects of political risk, financial risk, and economic freedom on ecological footprint: Empirical evidence from belt and road initiative countries, Borsa Istanbul Review, 22, 873– 885. https://doi.org/10.1016/j.bir.2022.06.004.
• Aygören, H. & Uyar, U. (2016). The analysis of financial beta behaviour via panel quantile regression approach, Journal of Economics, Finance and Accounting, 3(4), 255-265.
• Bektur, Ç. (2023). The role of economic freedom in achieving the environmental sustainability for the highest economic freedom countries: Testing the environmental Kuznets curve hypothesis, Environmental Science and Pollution Research, https://doi.org/10.1007/s11356-023-29120-5
• Belaid, F., Elsayed, A. H. & Omri, A. (2021). Key drivers of renewable energy deployment in the MENA Region: Empirical evidence using panel quantile regression, Structural Change and Economic Dynamics, 57,225-238, https://doi.org/10.1016/j.strueco.2021.03.011.
• Binder, M., & Coad, A. (2011). From average Joe’s happiness to Miserable Jane and Cheerful John: Using quantile regressions to analyze the full subjective well-being distribution, Journal of Economic Behavior & Organization, 79(3), 275-290
• Boubellouta, B. & Kusch-Brandt, S. (2022). Driving factors of e-waste recycling rate in 30 European countries: New evidence using a panel quantile regression of the EKC hypothesis coupled with the STIRPAT model, Environment, Development and Sustainability, 25, https://doi.org/10.1007/s10668-022-02356-w
• Bucak, Ç. (2022). Ekonomik özgürlük endeksi, insani gelişme endeksi ve ekolojik ayak izi: E7 Ülkeleri İçin Ampirik Bir Analiz , Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi , 12 (23), 141-158 . DOI: 10.53092/duiibfd.992572
• Cade, B. S., & Noon, B. R. (2003). A gentle introduction to quantile regression for ecologists, Frontiers in Ecology and the Environment, 1(8), 412– 420.
• Chen, L. (2005). An introduction to quantile regression and the QUANTREG procedure, Statistics and Data Analysis, 213-230, SUGI30 Proceedings, available at children and adolescents. Conference on Quantitative Social Science Research Using R. available at http://www.cis.fordham.edu/QR2009/presentations/RefGrowthCharts.pdf (Erişim Tarihi: 12.06.2023).
• CRED (2008). EM-DAT: emergency events database. Available at http://www.emdat.be/, (Erişim: 30.03.2023).
• Destek, M. A., & Sinha, A. (2020). Renewable, non-renewable energy consumption, economic growth, trade openness and ecological footprint: Evidence from organisation for economic Co-operation and development countries. Journal of Cleaner Production, 242, 118537.
• Dogan, E., Ulucak, R., Kocak, E. & Isik, C. (2020). The use of ecological footprint in estimating the environmental Kuznets curve hypothesis for BRICST by considering cross-section dependence and heterogeneity, Science of the Total Environment, 723, 1-8, 138063.
• Ferng, J. J. (2001). Using composition of land multiplier to estimate ecological footprints associated with production activity, Ecological Economics, 37, 159– 172.
• Galli, A., Kitzes, J., Niccolucci, V., Wackernagel, M., Wada, Y. & Marchettini, N.(2012). Assessing the global environmental consequences of economic growth through the ecological footprint: A focus on China and India. Ecological Indicators, 17, 99–107.
• Global Footprint Network (2019). Advancing the science of sustainability”, http://data.footprintnetwork.org/?_ga=2.128662604.1393481519.1589555821-401373056.1547219594#/countryTrends?type=BCtot,EFCtot&cn=351. (Erişim: 25.03.2023).
• Global Footprint Network (2024). Ecological Footprint, 07 Mart 2024 tarihinde https://www.footprintnetwork.org/our-work/ecological-footprint/ adresinden erişildi.
• Güriş, S., & Şak, N. (2019). Çevresel kuznets eğrisi hipotezinin toplamsal olmayan sabit etkili panel kantil yöntemiyle incelenmesi, Business and Economics Research Journal, 10(2), 327–340.
• Gyamfi, B. A., Bein, M. A., Ozturk, I. & Bekun, F. V. (2020). The moderating role of employment in an environmental kuznets curve framework revisited in G7 countries. Indonesian Journal of Sustainability Accounting and Management,4(2), 241–248. https://doi.org/10.28992/ijsam.v4i2.283.
• Heath, Y., & Gifford, R. (2006). Free-market ideology and environmental degradation. Environment and Behavior, 38(1), 48–71. doi:10.1177/0013916505277998.
• Hemmati, R. & Khosroshahi, M. K. (2020). The interaction of economic freedom and governance on ecological footprint (selected developing countries)”, Iranian Energy Economics, 37(10), 159-182.
• Heritage Foundation (2024). Index of Economic Freedom, 07 Mart 2024 tarihinde https://www.heritage.org/index/pages/report adresinden erişildi.
• Jiang, Y., Zhou, Z. & Liu, C. (2019). The impact of public transportation on carbon emissions: A panel quantile analysis based on Chinese provincial data, Environmental Science and Pollution Research, 26, 4000–4012. https://doi.org/10.1007/s11356-018-3921-y.
• Joshi, P. & Beck, K., (2018). Democracy and carbon dioxide emissions: Assessing the interactions of political and economic freedom and the environmental Kuznets curve, Energy Research & Social Science, 39, 46–54. https://doi.org/10.1016/j. erss.2017.10.020.
• Karimi, M., Khezri, M., Khan, Y.A. & Razzaghi, S. (2022). Exploring the influence of economic freedom index on fishing grounds footprint in environmental Kuznets curve framework through spatial econometrics technique: evidence from Asia-Pacific countries, Environmental Science and Pollution Research, 29, 6251–6266. https://doi.org/10.1007/s11356-021-16110-8
• Koenker R., & Bassett, G. Jr. (1978). Regression quantiles, Econometrica, 46(1), 33-50 Koenker, R. (2005). Quantile regression, USA: Cambridge University Press.
• Kratena, K., & Streicher, G. (2012). Spatial welfare economics versus ecological footprint: A sensitivity analysis introducing strong sustainability, Environmental and Resource Economics, 51, 617– 622.
• Lenzen, M., Borgstrom Hansson, C., & Bond, S. (2007). On the bioproductivity and land-disturbance metrics of the ecological footprint, Ecological Economics, 61, 6– 10.
• Liu, X., Razzaq, A., Shahzad, M. & Irfan, M. (2022). Technological changes, financial development and ecological consequences: A comparative study of developed and developing economies, Technological Forecasting and Social Change, 184, 122004, ISSN 0040-1625, https://doi.org/10.1016/j.techfore.2022.122004.
• Mamkhezri, J., Muhamad, G. M. & Khezri, M. (2022). Assessing the spatial effects of economic freedom on forest-products, grazing-land, and cropland footprints: The case of Asia-Pacific countries, Journal of Environmental Management, 316, ISSN 0301-4797, https://doi.org/10.1016/j.jenvman.2022.115274.
• National Research Council. (1999). Global environmental change: Research pathways for the next decade, Washington, DC: National Academy Press.
• Numan, U., Ma, B., Aslam, M., Bedru, H.D., Jiang, C. & Sadiq, M. (2023). Role of economic complexity and energy sector in moving towards sustainability in the exporting economies, Energy Strategy Reviews, 45, 101038 https://doi.org/10.1016/j. esr.2022.101038.
• Ozler, S. I. & Obach, B. (2009). Capitalism, state economic policy, and ecological footprint: An international comparative analysis, Global Environmental Politics, 9, 79-108.
• Ponce, P., Álvarez-García, J., Álvarez, V., & Irfan, M. (2023). Analysing the influence of foreign direct investment and urbanization on the development of private financial system and its ecological footprint, Environmental Science and Pollution Research, 30, 9624–9641. https://doi.org/10.1007/s11356-022-22772-9
• Powell, D. (2022). Quantile regression with nonadditive fixed effects. Empirical Economics, 63(5), 2675-2691.
• Rees, W. E. (1992). Ecological footprints and appropriated carrying capacity: What urban economics leaves out, Environment and Urbanization, 4(2), 121–130. https://doi.org/10.1177/095624789200400212.
• Shahbaz, M. & Sinha, A. (2019). Environmental kuznets curve for CO2 emissions: A literature survey, Journal of Economic Studies, 46(1), 106-168. https://doi.org/10.1108/JES-09-2017-0249.
• Shen, Y., & Yue, S. (2023). Does ecological footprint affect biocapacity? Evidence from the experiences of G20 countries, Natural Resource Modeling, 36(3), e12369.
• Sofuoğlu, E., Kirikkaleli, D. (2023). The effect of mineral saving and energy on the ecological footprint in an emerging market: Evidence from novel Fourier based approaches, Letters in Spatial and Resource Sciences, 16(3), 1-16. https://doi.org/10.1007/s12076-023-00328-w
• Sukmaningrum, P. S. (2022). Political freedom, economic freedom and Co2 emission in long run: Evidence from ASEAN countries, Asian Bulletin of Contemporary Issues in Economics and Finance, 2(2), 36-47.
• Tekin, B. & Bastak, S. N. (2022). Panel kantil regresyon yaklaşımı ile getiriyi etkileyen içsel faktörlerin modellenmesi: BIST 100 örneği . Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi , 24(42) , 194-208 .
• Usman, A., Ozturk, I. Naqvi, S. M. M. A., Ullah, S. & 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, ISSN 0149-1970, https://doi.org/10.1016/j.pnucene.2022.104220.
• Wackernagel, M. (1995). Our ecological footprint: Reducing human impact on the Earth, Population and Environment, 1(3), 171– 174.
• Wackernagel, M., Monfreda, C., Schulz, N. B., Erb, K. H., Haberl, H., & Krausmann, F. (2004). Calculating national and global ecological footprint time series: Resolving conceptual challenges, Land Use Policy, 21, 271– 278.
• World Bank (2019). World Bank annual reports & financial statements, https://openknowledge.world bank.org/handle/10986/2127 (Erişim: 10.01.2023).
• WWF (2018). Living planet report 2018, World Wide Fund for Nature. https://www.worldwildlife.org/pages/living-planet-report-2018 (Erişim: 12.02.2023).
• Yeo, M. J., & Kim, Y. P. (2016). Changes of the carbon dioxide emissions and the overshoot ratio resulting from the implementation of the 2nd energy master plan in the Republic of Korea, Energy Policy, 96, 241– 250.
• Yu, K., Zudi, L., & Stander, J. (2003). Quantile regression: Applications and current research areas. Journal of the Royal Statistical Society: Series D (The Statistician). 52, 331-350. doi: 10.1111/1467-9884.00363