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GMM ve TODIM Yöntemlerinin Makroekonomik Değerlendirmelere Entegre Edilmesi: G20 Ülkeleri Üzerine Bir Analiz

Yıl 2025, Cilt: 9 Sayı: 1, 175 - 194, 30.01.2025
https://doi.org/10.29023/alanyaakademik.1527824

Öz

Bu çalışmada, temiz teknolojilerin ekonomik etkileri iki farklı açıdan incelenmektedir. Sistem GMM analizi, temiz teknolojinin GSYH üzerindeki doğrudan etkisini ölçerken, TODIM analizi daha geniş bir makroekonomik performans değerlendirmesi sunmaktadır. Bu ikili yaklaşım, konuyu hem spesifik (GSYH odaklı) hem de genel (makroekonomik performans) açıdan ele alarak, temiz teknolojilerin ekonomik etkilerini kapsamlı bir şekilde değerlendirmeyi amaçlamaktadır. Temiz teknolojilerin yaygınlaşması, yenilenebilir enerji kaynaklarına yapılan yatırımların artması, yüksek teknolojili ürünlerin ihracı ve ticari açıklığın artması ekonomik büyüme bağlamında GSYH’nin artışına katkı sağlamaktadır. Nüfus yoğunluğu ve sanayi katma değeri ise büyümenin verimliliğinde etkin rol oynayan kritik faktörler arasında yer almaktadır. Çalışmanın bulguları, temiz teknolojilerin kullanımının yaygınlaştırılmasıyla fosil yakıt tüketiminin azaldığını ve enerji maliyetlerinin minimize edildiğini göstermektedir. Daha düşük enerji maliyetleri ile üretim maliyetlerinin azalması, ekonomik verimliliğin artmasına ve dolayısıyla GSYH'nin genel durumu ve büyüme potansiyelinin iyileşmesine katkı sağlamaktadır. Sistem Genelleştirilmiş Momentler Metodu (GMM) kullanılarak yapılan analizler neticesinde, temiz teknolojilerin GSYH üzerinde anlamlı ve önemli etkileri olduğunu ortaya koymuştur. Ayrıca, Çok Kriterli Karar Verme (ÇKKV) yöntemlerinden Normalize Edilmiş Maksimum Değerler (NMD) tabanlı TODIM yöntemi kullanılarak yapılan değerlendirmeler, temiz teknolojilerin ekonomik performans üzerindeki olumlu etkilerini desteklemektedir. Bu sonuçlar, temiz teknolojilerin ekonomik büyüme ile arasındaki dengeyi sağlama potansiyeline işaret etmektedir.

Kaynakça

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  • Asumadu-Sarkodie, S., & Owusu, P. A. (2016). Carbon dioxide emissions, GDP, energy use, and population growth: A multivariate and causality analysis for Ghana, 1971–2013. Environmental Science and Pollution Research, 23(13), 13508–13520. https://doi.org/10.1007/s11356-016-6511-x
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Integrating GMM and TODIM Methods into Macroeconomic Assessments: An Analysis on G20 Countries

Yıl 2025, Cilt: 9 Sayı: 1, 175 - 194, 30.01.2025
https://doi.org/10.29023/alanyaakademik.1527824

Öz

In this study, the economic impacts of clean technologies are examined from two different perspectives. While System GMM analysis measures the direct impact of clean technology on GDP, TODIM analysis provides a broader macroeconomic performance assessment. This dual approach aims to comprehensively assess the economic impacts of clean technologies by addressing the issue from both specific (GDP-oriented) and general (macroeconomic performance) perspectives. The diffusion of clean technologies, increased investments in renewable energy sources, exports of high-tech products and increased trade openness contribute to the increase in GDP in the context of economic growth. Population density and industrial value added are among the critical factors that play an effective role in the efficiency of growth. The findings of the study show that the widespread use of clean technologies reduces fossil fuel consumption and minimizes energy costs. Lower energy costs and reduced production costs contribute to increased economic efficiency, which in turn improves the overall GDP situation and growth potential. The system analysis using the Generalized Method of Moments (GMM) reveals that clean technologies have significant and important effects on GDP. Moreover, evaluations using the Normalized Maximum Values (NMV) based TODIM method, a Multi-Criteria Decision Making (MCDM) method, support the positive effects of clean technologies on economic performance. These results point to the potential of clean technologies to balance economic growth.

Kaynakça

  • Akad, İ., & Kaya, A. (2023). Karbon emisyonu, enerji tüketimi ve gelir: Avrupa birliği ülkeleri için bir mekansal ekonometri analizi. Kırklareli Üniversitesi Sosyal Bilimler Dergisi, 7(2), Article 2. https://doi.org/10.47140/kusbder.1385185
  • Aneja, R., Yadav, M., & Gupta, S. (2024). The dynamic impact assessment of clean energy and green innovation in realizing environmental sustainability of G‐20. Sustainable Development, 32(3), 2454–2473. https://ideas.repec.org//a/wly/sustdv/v32y2024i3p2454-2473.html
  • Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29–51. https://doi.org/10.1016/0304-4076(94)01642-D
  • Asumadu-Sarkodie, S., & Owusu, P. A. (2016). Carbon dioxide emissions, GDP, energy use, and population growth: A multivariate and causality analysis for Ghana, 1971–2013. Environmental Science and Pollution Research, 23(13), 13508–13520. https://doi.org/10.1007/s11356-016-6511-x
  • Atella, V., & Scandizzo, P. L. (2024). Chapter 6 - covıd-19 macroeconomics: Are we using the right toolbox? In V. Atella & P. L. Scandizzo (Eds.), The covid-19 disruption and the global health challenge (pp. 201–225). Academic Press. https://doi.org/10.1016/B978-0-44-318576-2.00019-6
  • Bağcı, H., & Sarıay, İ. (2021). Halka açık piyasa değeri ve piyasa değerinin işletme performansındaki rolü: BİST halka arz endeksi’nde bir uygulama. Finansal Araştırmalar ve Çalışmalar Dergisi, 13(24), Article 24. https://doi.org/10.14784/marufacd.880613
  • Bakırtaş, İ., & Çetin, M. (2016). Yenilenebilir enerji tüketimi ile ekonomik büyüme arasındaki ilişki: G-20 ülkeleri. Sosyoekonomi, 24(28), Article 28. https://doi.org/10.17233/se.43089
  • Balcilar, M., Ekwueme, D. C., & Ciftci, H. (2023). Assessing the effects of natural resource extraction on carbon emissions and energy consumption in sub-saharan africa: A stırpat model approach. Sustainability, 15(12), Article 12. https://doi.org/10.3390/su15129676
  • Buluş, C. (2022). Doğrudan yabancı yatırımların ve ticari açıklığın ekonomik büyüme üzerindeki etkileri: CESEE ülkeleri örneği. Alanya Akademik Bakış, 6(2), 2085–2102. https://doi.org/10.29023/alanyaakademik.1008560
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  • Erdi̇nç, Z., & Aydinbaş, G. (2023). Sürdürülebilir kalkınma için çevre kirliliği ile ilişkili unsurların tespiti: Panel veri analizi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 25(3), 1050–1067. https://doi.org/10.32709/akusosbil.1081596
  • Eufrasio Espinosa, R. M., & Lenny Koh, S. C. (2024). Forecasting the ecological footprint of g20 countries in the next 30 years. Scientific Reports, 14(1), 8298. https://doi.org/10.1038/s41598-024-57994-z
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  • Gökgöz, F., & Yalçın, E. (2021). Investigating the environmental and economic performances of energy sector in oecd countries via mcdm approaches. In D. S.-K. Ting & A. Vasel-Be-Hagh (Eds.), Sustaining tomorrow (pp. 65–92). Springer International Publishing. https://doi.org/10.1007/978-3-030-64715-5_5
  • Haider, S., Anjum, N., Sufyan, M., Khan, F., & Ullah, A. (2018). Impact of macroeconomic variables on financial performance: Evidence of automobile assembling sector of pakistan stock exchange. Sarhad Journal of Management Sciences, 4(2), Article 2. https://doi.org/10.31529/sjms.2018.4.2.6
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  • Karahan, M., Çetintaş, F., & Karahan, M. S. (2021). Turkey and some eu countries’ economic performance analysis with multi-criteria decision making methods: Promethee gaıa application. Lecture Notes in Mechanical Engineering, 584–597. https://doi.org/10.1007/978-3-030-62784-3_50
  • Karakiş, E., & Göktolga, Z. G. (2016). Comparison of the economic performance turkish republics in central asia with analytic hierarchy process and vise kriterijumska optimizacija ı komprom. Uluslararası Avrasya Ekonomileri Konferansı. https://doi.org/10.36880/c07.01534
  • Kazanasmaz, E., Demi̇rel, B. L., Karatepe, S., & Hizarci, A. E. (2023). Ekonomik büyüme, elektrik tüketimi ve karbon emisyonu ilişkisi: Türkiye örneği. Muhasebe ve Finans İncelemeleri Dergisi, 6(2), 248–265. https://doi.org/10.32951/mufider.1356297
  • Kazak, H., Çiftçi, T.E., Akcan, A.T. et al. Is taxation a curse or a blessing? The case of Turkiye. Humanit Soc Sci Commun 11, 1432 (2024). https://doi.org/10.1057/s41599-024-03942-1
  • Keskin, G. (2024). Todim masaüstü uygulaması. Todım (tomada de decisao ınterativa multicriterio) method desktop application. https://github.com/gulsenkeskin
  • Kılıçarslan, A. (2023). Büyüyen şirketler hisse senedi fonu endeksinde işlem gören şirketlerin finansal performans analizi. Trakya Üniversitesi İktisadi ve İdari Bilimler Fakültesi E-Dergi, 12(2), Article 2. https://doi.org/10.47934/tife.12.02.04
  • Kılıçarslan, A., & Özmen, A. (2023). Yerel yönetimlerde finansal performans yönetimi: İstanbul ve kocaeli büyükşehir belediyeleri örneği. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 18(1), Article 1. https://doi.org/10.17153/oguiibf.1231749
  • Kulkarni, N. D., Saha, A., & Kumari, P. (2024). Utilizing multicriteria decision-making approach for material selection in hybrid polymer nanocomposites for energy-harvesting applications. Polymer Composites, 45(7), 6264–6277. https://doi.org/10.1002/pc.28194
  • Lei, F., Cai, Q., Liao, N., Wei, G., He, Y., Wu, J., & Wei, C. (2023). Todım-vıkor method based on hybrid weighted distance under probabilistic uncertain linguistic information and its application in medical logistics center site selection. Soft Computing, 27(13), 8541–8559. https://doi.org/10.1007/s00500-023-08132-w
  • Li, J., Zeng, J., Ye, Z., & Huang, X. (2021). Are clean technologies more effective than end-of-pipe technologies? Evidence from chinese manufacturing. International Journal of Environmental Research and Public Health, 18(8), Article 8. https://doi.org/10.3390/ijerph18084012
  • Liao, N., Wei, G., & Chen, X. (2022). Todım method based on cumulative prospect theory for multiple attributes group decision making under probabilistic hesitant fuzzy setting. International Journal of Fuzzy Systems, 24(1), 322–339. https://doi.org/10.1007/s40815-021-01138-2
  • Liu, S., He, X., Chan, F. T. S., & Wang, Z. (2022). An extended multi-criteria group decision-making method with psychological factors and bidirectional influence relation for emergency medical supplier selection. Expert Systems with Applications, 202. https://doi.org/10.1016/j.eswa.2022.117414
  • Liu, X., Chen, P., & Wen, S. (2023). Green GDP: The key to sustainable development. Highlights in Business, Economics and Management, 8, 541–547. https://doi.org/10.54097/hbem.v8i.7268
  • Mao, Q., Guo, M., Lv, J., Chen, J., & Tian, M. (2023). A multi-criteria group decision-making framework for investment assessment of offshore floating wind-solar-aquaculture project under probabilistic linguistic environment. Environmental Science and Pollution Research, 30(14), 40752–40782. https://doi.org/10.1007/s11356-022-24786-9
  • Mikulčić, H., Baleta, J., & Klemeš, J. J. (2022). Cleaner technologies for sustainable development. Cleaner Engineering and Technology, 7, 100445. https://doi.org/10.1016/j.clet.2022.100445
  • Nzuza, Z. W., & Msomi, T. S. (2023). The relationship between macroeconomic factors and profitability of reinsurance companies in africa: An application of system gmm-model. International Journal of Environmental, Sustainability, and Social Science, 4(5), Article 5. https://doi.org/10.38142/ijesss.v4i5.768
  • Oussama, Z., Ahmed, H., & Nabil, C. (2024). Comparison of macroeconomic performance of mena countries with topsıs method. Operations Research Forum, 5(1), 21. https://doi.org/10.1007/s43069-024-00306-y
  • Pata, U. K., Caglar, A. E., Kartal, M. T., & Kılıç Depren, S. (2023). Evaluation of the role of clean energy technologies, human capital, urbanization, and income on the environmental quality in the United States. Journal of Cleaner Production, 402, 136802. https://doi.org/10.1016/j.jclepro.2023.136802
  • Polasky, S., Kling, C. L., Levin, S. A., Carpenter, S. R., Daily, G. C., Ehrlich, P. R., Heal, G. M., & Lubchenco, J. (2019). Role of economics in analyzing the environment and sustainable development. Proceedings of the National Academy of Sciences, 116(12), 5233–5238. https://doi.org/10.1073/pnas.1901616116
  • Rosli, N. N. N. C., & Yusoff, B. (2023). Generalized todım method and its application in material selection process. AIP Conference Proceedings, 2484(1), 030007. https://doi.org/10.1063/5.0109942
  • Sethi, T., & Kumar, S. (2023). Todim-vikor methods with pythagorean fuzzy ınformation based emergency decision support model for economic growth factor selection. 2023 13th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 340–345. https://doi.org/10.1109/Confluence56041.2023.10048890
  • Setyadi, S., Didu, S., Indriyani, L., Fitri, A. K., & Wiidiastuti, A. (2023). Modeling life expectancy in ındonesia using system gmm model. Review of Applied Socio-Economic Research, 25(1), Article 1. https://doi.org/10.54609/reaser.v25i1.338
  • Shaheen, F., Lodhi, M. S., Rosak-Szyrocka, J., Zaman, K., Awan, U., Asif, M., Ahmed, W., & Siddique, M. (2022). Cleaner technology and natural resource management: an environmental sustainability perspective from china. Clean Technologies, 4(3), Article 3. https://doi.org/10.3390/cleantechnol4030036
  • Smulders, S., Bretschger, L., & Egli, H. (2011). Economic growth and the diffusion of clean technologies: Explaining environmental kuznets curves. Environmental and Resource Economics, 49(1), 79–99. https://doi.org/10.1007/s10640-010-9425-y
  • Song, C., Xu, Z., & Zhang, Y. (2023). An enhanced ınteractive and multi-criteria decision-making (todım) method with probabilistic dual hesitant fuzzy sets for risk evaluation of arctic geopolitics. Cognitive Computation, 16, 1–13. https://doi.org/10.1007/s12559-023-10229-1
  • Sun, H., Yang, Z., Cai, Q., Wei, G., & Mo, Z. (2023). An extended exp-todım method for multiple attribute decision making based on the z-wasserstein distance. Expert Systems with Applications, 214. https://doi.org/10.1016/j.eswa.2022.119114
  • Sun, M., Yan, S., Cao, T., & Zhang, J. (2024). The impact of covıd-19 pandemic on the world’s major economies: based on a multi-country and multi-sector cge model. Frontiers in Public Health, 12, 1338677. https://doi.org/10.3389/fpubh.2024.1338677
  • Tănasie, A. V., Năstase, L. L., Vochița, L. L., Manda, A. M., Boțoteanu, G. I., & Sitnikov, C. S. (2022). Green economy—green jobs in the context of sustainable development. Sustainability, 14(8), Article 8. https://doi.org/10.3390/su14084796
  • Tian, J., Yu, L., Xue, R., Zhuang, S., & Shan, Y. (2022). Global low-carbon energy transition in the post-covıd-19 era. Applied Energy, 307, 118205. https://doi.org/10.1016/j.apenergy.2021.118205
  • Topcu, B. A., & Oralhan, & B. (2019). Türkiye ve oecd ülkeleri’nin temel makroekonomik göstergeler açısından çok kriterli karar verme yöntemleri ile karşılaştırılması. Journal of Academic Value Studies (JAVStudies), 3(14), Article 14. https://doi.org/10.23929/javs.304
  • Uysal, F., & Tosun, Ö. (2014). Multi criteria analysis of the residential properties in antalya using todım method. Procedia - Social and Behavioral Sciences, 109, 322–326. https://doi.org/10.1016/j.sbspro.2013.12.465
  • Vasylieva, T., Lyulyov, O., Bilan, Y., & Streimikiene, D. (2019). Sustainable economic development and greenhouse gas emissions: the dynamic ımpact of renewable energy consumption, gdp, and corruption. Energies, 12(17), Article 17. https://doi.org/10.3390/en12173289
  • Vatansever, K., & Kazançoğlu, Y. (2014). Integrated usage of fuzzy multi criteria decision making techniques for machine selection problems and an application. International Journal of Business and Social Science, 5(9), 12–24.
  • Wang, C.-N., Nhieu, N.-L., Dao, T.-H., & Huang, C.-C. (2024). Simulation-based optimized weighting todım decision-making approach for national oil company global benchmarking. IEEE Transactions on Engineering Management, 71, 1215–1229. https://doi.org/10.1109/TEM.2022.3152486
  • Wang, Z., Cai, Q., & Wei, G. (2023). Enhanced todım based on vıkor method for multi-attribute decision making with type-2 neutrosophic number and applications to green supplier selection. Soft Computing. https://doi.org/10.1007/s00500-023-08768-8
  • Wu, P., Zhou, L., & Martínez, L. (2022). An integrated hesitant fuzzy linguistic model for multiple attribute group decision-making for health management center selection. Comput. Ind. Eng., 171(C). https://doi.org/10.1016/j.cie.2022.108404
  • Yapa, K., Durmus, M., Tayyar, N., & Akbulut, I. (2022). Comparison of the european union countries and turkey’s macroeconomic indicators with best worst method. In Research Anthology on Macroeconomics and the Achievement of Global Stability (pp. 675–690). https://doi.org/10.4018/978-1-6684-7460-0.ch037
  • Yerdelen Tatoglu, F. (2020). İleri panel veri analizi, stata uygulamalı (4.). Beta Basım Yayım Dağıtım A.Ş.
  • Ying, F., Farouk, A. F. B. A., & Lin, L. Q. (2024). Impact analysis of bilateral trade openness and income inequality based on the system gmm method: A case study of transnational dynamic panel data. International Journal of Applied Economics, Finance and Accounting, 18(2), Article 2. https://doi.org/10.33094/ijaefa.v18i2.1479
  • Zhang, C. (2014). The ımpact of clean energy on economic growth: An econometrics approach. Pepperdine Policy Review, 7(1), 1–19. https://digitalcommons.pepperdine.edu/cgi/viewcontent.cgi?referer=&httpsredir=1&article=1093&context=ppr
  • Zhang, W., Luo, W., Gao, X., Zhang, C., & Wang, K. (2023). Todım multi-attribute decision-making method based on spherical fuzzy sets. In N. Xiong, M. Li, K. Li, Z. Xiao, L. Liao, & L. Wang (Eds.), advances in natural computation, fuzzy systems and knowledge discovery (pp. 428–436). Springer International Publishing. https://doi.org/10.1007/978-3-031-20738-9_49
  • Zhao, L., & Du, S. (2023). An improved todım-topsıs method for quality evaluation of college students employment and entrepreneurship education with probabilistic hesitant fuzzy sets. Journal of Intelligent and Fuzzy Systems, 45(5), 7547–7562. https://doi.org/10.3233/JIFS-233929
  • Zhou, E., Wang, G., & Wang, S. (2023). Improved training of gmm-based tsk fuzzy system from stability perspective. 2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 62–70. https://doi.org/10.1109/ISKE60036.2023.10480988
Toplam 67 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ekonomik Modeller ve Öngörü, Panel Veri Analizi , Yeşil Ekonomi
Bölüm Makaleler
Yazarlar

Zekiye Örtlek 0000-0003-0547-3782

Abdullah Kılıçarslan 0000-0002-7251-9990

Yayımlanma Tarihi 30 Ocak 2025
Gönderilme Tarihi 4 Ağustos 2024
Kabul Tarihi 18 Kasım 2024
Yayımlandığı Sayı Yıl 2025 Cilt: 9 Sayı: 1

Kaynak Göster

APA Örtlek, Z., & Kılıçarslan, A. (2025). GMM ve TODIM Yöntemlerinin Makroekonomik Değerlendirmelere Entegre Edilmesi: G20 Ülkeleri Üzerine Bir Analiz. Alanya Akademik Bakış, 9(1), 175-194. https://doi.org/10.29023/alanyaakademik.1527824