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Çevresel Sürdürülebilirliğin Değerlendirilmesi: Dinamik Mekânsal Panel Veri Yaklaşımı

Year 2021, Volume: 23 Issue: 1, 53 - 90, 31.05.2021

Abstract

Sanayileşme ile birlikte artan enerji ihtiyacını karşılamak üzere kullanılan yenilenemeyen enerji kaynakları, modern kentleşme, nüfus artışı vb. gibi etkenler küresel ısınma, iklim değişiklikleri, hava-su-toprak kirliliği, atık ve çevresel tahribat gibi sorunlara ve biyolojik çeşitlilikte azalmaya neden olmaktadır. Kitlesel üretime geçilmesiyle birlikte ortaya çıkan hammadde(kaynak) kullanımının hızlanması, enerji kullanımında artış yaşanması ve küreselleşme sonucunda tüketim düzeylerinde ve bireysel alışkanlıklarda değişim yaşanması çevresel bozulmanın temelini oluşturmaktayken; yeşil-çevre dostu teknolojilere önem verilmemesi, politik düzenleme/yaptırım eksiliği vb. gibi faktörler belirli bölgelerde sınırlı kalan çevresel kirliliğin küresel boyutlara taşınmasını sağlayarak iklimsel ve eko-sistemik yapıda bozukluklara neden olmaktadır. Çevresel yapı üzerindeki olumsuz etkilerin ülke ekonomilerindeki belirli maliyet ve harcamalar ile doğrudan/dolaylı ilişki içerisinde olması, sanayileşmeyle birlikte ülke ekonomilerinin sürdürülebilir olmayan büyüme eğilimi göstermesi ve çevresel kirlilik faktörünün komşuluk ilişkilerinden etkilenmesi nedeniyle çevresel bozulma kavramı incelenirken mekânsal ilişkilerin gözetilmesi gerekliliği ortaya çıkmaktadır. Makale kapsamında, çevresel sürdürülebilirliğin kavramsal çerçevesine değinildikten sonra dinamik mekânsal panel veri analizi yönteminin modelleme ve tahminleme aşamasında kullanımı hakkında bilgi verilerek çevresel sürdürülebilirliğin değerlendirilmesinde kullanımının avantajlarına değinilmektedir.

References

  • Anselin, L. (1988). Spatial econometrics: Methods and models. Kluwer Academic. Boston, MA.
  • Anselin, L., Le Gallo, J., & Jayet, H. (2008). Spatial panel econometrics. In The econometrics of panel data (pp. 625-660). Springer, Berlin, Heidelberg.
  • Arellano, M. (2003). Panel data econometrics. Oxford University press.
  • Arundel, A., & Kemp, R. (2009). Measuring eco-innovation.
  • Baltagi, B.H., (2005). Econometric Analysis of Panel Data. (3. Baskı), Chichester: John Wiley & Sons Ltd.
  • Barduchi, C., Falguera, F. P. S., de Oliveira Gobbo, S. C., & Mariano, E. B. (2020). Economic, Political and Technological Aspects of Development and Eco-Efficiency: A Global Quantitative Analysis. In International Congress on Engineering and Sustainability in the XXI Century (pp. 552-567). Springer, Cham
  • Boons, F., & Wagner, M. (2009). Assessing the relationship between economic and ecological performance: Distinguishing system levels and the role of innovation. Ecological Economics, 68(7), 1908-1914.
  • Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: methods and applications. Cambridge university press.
  • Darmofal, D. (2006). Spatial econometrics and political science. Society for Political Methodology Working Paper Archive: http://polmeth.wustl.edu/workingpapers. php.
  • Debarsy, N., Ertur, C., & LeSage, J. P. (2012). Interpreting dynamic space–time panel data models. Statistical Methodology, 9(1-2), 158-171.
  • Dereli, M., Boyacıoğlu, E.Z., Terzioğlu, M.K. (2019). İklim Değişikliği ve Turizm Sektörü Arasındaki İlişkinin Dinamik Panel Veri Analizi ile İncelenmesi. Türk Turizm Araştırmaları Dergisi. Journal of Turkish Tourism Research, 3(4), 1228-1243.
  • Dünya Sürdürülebilir Kalkınma İş Konseyi (WBCSD), “Eco-efficiency: learning module”. Geneva 2006.
  • Eko-İnovasyon Gözlemevi (EIO) (2012). Europe in Transition: Paving the Way to a Green Economy through Eco-Innovation. European Commission: Paris, Fransa.
  • Ekonomik Kalkınma ve İş birliği Örgütü (OECD) (2012). The Future of Eco Innovation: The Role of Business Models in Green Transformation. OECD/European Commission/Nordic Innovation Joint Workshop.
  • Ekonomik Kalkınma ve İş birliği Örgütü (OECD), (2009). Green Growth: Overcoming the Crisis and Beyond. OECD Publishing. 15-21.
  • Elhorst, J. P. (2003). Specification and estimation of spatial panel data models. International regional science review, 26(3), 244-268.
  • Elhorst, J. P. (2010). Applied spatial econometrics: raising the bar. Spatial economic analysis, 5(1), 9-28.
  • Elhorst, J. P. (2014). Spatial econometrics: from cross-sectional data to spatial panels (Vol. 479, p. 480). Heidelberg: Springer.
  • Fernando, Y., & Wah, W. X. (2017). The impact of eco-innovation drivers on environmental performance: Empirical results from the green technology sector in Malaysia. Sustainable Production and Consumption, 12, 27-43.
  • Fussler, C., & James, P. (1996). Driving eco-innovation: a breakthrough discipline for innovation and sustainability. Financial Times/Prentice Hall.
  • Getis, A., & Aldstadt, J. (2004). Constructing the spatial weights matrix using a local statistic. Geographical analysis, 36(2), 90-104.
  • Ghisellini, P., Cialani, C., & Ulgiati, S. (2016). A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems. Journal of Cleaner production, 114, 11-32.
  • Gumprecht, D. (2007). Spatial methods in econometrics (Doctoral dissertation, WU Vienna University of Economics and Business).
  • Jo, J. H., Roh, T. W., Kim, S., Youn, Y. C., Park, M. S., Han, K. J., & Jang, E. K. (2015). Eco-innovation for sustainability: Evidence from 49 countries in Asia and Europe. Sustainability, 7(12), 16820-16835.
  • Le Gallo, J. (2002). Econométrie spatiale: l'autocorrélation spatiale dans les modèles de régression linéaire. Economie prevision, (4), 139-157.
  • LeSage, J. P. (1999). The theory and practice of spatial econometrics. University of Toledo. Toledo, Ohio, 28(11).
  • LeSage, J. P., & Pace, R. K. (2014). The biggest myth in spatial econometrics. Econometrics, 2(4), 217-249.
  • Mota, R., & Scott, D. (2014). Education for innovation and independent learning. Elsevier.
  • Pezzey, J. (1989). Economic analysis of sustainable growth and sustainable development. World Bank, Washington, DC (EUA). Environment Dept..
  • Porter, M. E., & Van der Linde, C. (1995). Toward a new conception of the environment-competitiveness relationship. Journal of economic perspectives, 9(4), 97-118.
  • Schiederig, T., Tietze, F., & Herstatt, C. (2012). Green innovation in technology and innovation management–an exploratory literature review. R&d Management, 42(2), 180-192.
  • Terzioğlu, M. K., Yücel, M. A., Demirkıran, S., & Acaroğlu, D. Kentsel İnovasyonun Kentleşme Üzerine Mekansal Etkisi. İDEALKENT, 11(30). DOI: 10.31198/idealkent.683583
  • Verspagen, B. (1997). Measuring intersectoral technology spillovers: estimates from the European and US patent office databases. Economic Systems Research, 9(1), 47-65.
  • Yücel, M.A. (2021). Sürdürebilir Kalkınma Çerçevesinde Eko-Verimlilik ve Eko-İnovasyon: Dinamik Mekansal Etkileşim. (Yüksek Lisans Tezi), Trakya Üniversitesi Sosyal Bilimler Enstitüsü Ekonometri Anabilim Dalı

Evaluation of Environmental Sustainability: Spatial Dynamic Panel Data Approach

Year 2021, Volume: 23 Issue: 1, 53 - 90, 31.05.2021

Abstract

Factors such as non-renewable energy resources, modern urbanization, population growth, which are used to meet the increasing energy need with industrialization, cause problems such as global warming, climate changes, air-water-soil pollution, waste and environmental damage, and a decrease in biodiversity.The acceleration of the use of raw materials (resources), the increase in energy use, and the change in consumption levels and individual habits as a result of globalization, which emerged with the transition to mass production, are the basis of environmental degradation. Factors such as not paying attention to green-environment-friendly technologies, lack of political regulation/enforcement cause environmental pollution that is limited in certain regions to global dimensions, causing disturbances in the climatic and eco-systemic structure. Due to the fact that the negative effects on the environmental structure are directly/indirectly related to certain costs and expenditures in the country economies, the country's economies show an unsustainable growth trend with industrialization and the environmental pollution factor is affected by neighborhood relations, spatial relations should be considered while examining the concept of environmental degradation. Within the scope of the article, after mentioning the conceptual framework of environmental sustainability, information about the use of dynamic spatial panel data analysis method in the modeling and estimation phase, and the advantages of its use in the evaluation of environmental sustainability are mentioned.

References

  • Anselin, L. (1988). Spatial econometrics: Methods and models. Kluwer Academic. Boston, MA.
  • Anselin, L., Le Gallo, J., & Jayet, H. (2008). Spatial panel econometrics. In The econometrics of panel data (pp. 625-660). Springer, Berlin, Heidelberg.
  • Arellano, M. (2003). Panel data econometrics. Oxford University press.
  • Arundel, A., & Kemp, R. (2009). Measuring eco-innovation.
  • Baltagi, B.H., (2005). Econometric Analysis of Panel Data. (3. Baskı), Chichester: John Wiley & Sons Ltd.
  • Barduchi, C., Falguera, F. P. S., de Oliveira Gobbo, S. C., & Mariano, E. B. (2020). Economic, Political and Technological Aspects of Development and Eco-Efficiency: A Global Quantitative Analysis. In International Congress on Engineering and Sustainability in the XXI Century (pp. 552-567). Springer, Cham
  • Boons, F., & Wagner, M. (2009). Assessing the relationship between economic and ecological performance: Distinguishing system levels and the role of innovation. Ecological Economics, 68(7), 1908-1914.
  • Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: methods and applications. Cambridge university press.
  • Darmofal, D. (2006). Spatial econometrics and political science. Society for Political Methodology Working Paper Archive: http://polmeth.wustl.edu/workingpapers. php.
  • Debarsy, N., Ertur, C., & LeSage, J. P. (2012). Interpreting dynamic space–time panel data models. Statistical Methodology, 9(1-2), 158-171.
  • Dereli, M., Boyacıoğlu, E.Z., Terzioğlu, M.K. (2019). İklim Değişikliği ve Turizm Sektörü Arasındaki İlişkinin Dinamik Panel Veri Analizi ile İncelenmesi. Türk Turizm Araştırmaları Dergisi. Journal of Turkish Tourism Research, 3(4), 1228-1243.
  • Dünya Sürdürülebilir Kalkınma İş Konseyi (WBCSD), “Eco-efficiency: learning module”. Geneva 2006.
  • Eko-İnovasyon Gözlemevi (EIO) (2012). Europe in Transition: Paving the Way to a Green Economy through Eco-Innovation. European Commission: Paris, Fransa.
  • Ekonomik Kalkınma ve İş birliği Örgütü (OECD) (2012). The Future of Eco Innovation: The Role of Business Models in Green Transformation. OECD/European Commission/Nordic Innovation Joint Workshop.
  • Ekonomik Kalkınma ve İş birliği Örgütü (OECD), (2009). Green Growth: Overcoming the Crisis and Beyond. OECD Publishing. 15-21.
  • Elhorst, J. P. (2003). Specification and estimation of spatial panel data models. International regional science review, 26(3), 244-268.
  • Elhorst, J. P. (2010). Applied spatial econometrics: raising the bar. Spatial economic analysis, 5(1), 9-28.
  • Elhorst, J. P. (2014). Spatial econometrics: from cross-sectional data to spatial panels (Vol. 479, p. 480). Heidelberg: Springer.
  • Fernando, Y., & Wah, W. X. (2017). The impact of eco-innovation drivers on environmental performance: Empirical results from the green technology sector in Malaysia. Sustainable Production and Consumption, 12, 27-43.
  • Fussler, C., & James, P. (1996). Driving eco-innovation: a breakthrough discipline for innovation and sustainability. Financial Times/Prentice Hall.
  • Getis, A., & Aldstadt, J. (2004). Constructing the spatial weights matrix using a local statistic. Geographical analysis, 36(2), 90-104.
  • Ghisellini, P., Cialani, C., & Ulgiati, S. (2016). A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems. Journal of Cleaner production, 114, 11-32.
  • Gumprecht, D. (2007). Spatial methods in econometrics (Doctoral dissertation, WU Vienna University of Economics and Business).
  • Jo, J. H., Roh, T. W., Kim, S., Youn, Y. C., Park, M. S., Han, K. J., & Jang, E. K. (2015). Eco-innovation for sustainability: Evidence from 49 countries in Asia and Europe. Sustainability, 7(12), 16820-16835.
  • Le Gallo, J. (2002). Econométrie spatiale: l'autocorrélation spatiale dans les modèles de régression linéaire. Economie prevision, (4), 139-157.
  • LeSage, J. P. (1999). The theory and practice of spatial econometrics. University of Toledo. Toledo, Ohio, 28(11).
  • LeSage, J. P., & Pace, R. K. (2014). The biggest myth in spatial econometrics. Econometrics, 2(4), 217-249.
  • Mota, R., & Scott, D. (2014). Education for innovation and independent learning. Elsevier.
  • Pezzey, J. (1989). Economic analysis of sustainable growth and sustainable development. World Bank, Washington, DC (EUA). Environment Dept..
  • Porter, M. E., & Van der Linde, C. (1995). Toward a new conception of the environment-competitiveness relationship. Journal of economic perspectives, 9(4), 97-118.
  • Schiederig, T., Tietze, F., & Herstatt, C. (2012). Green innovation in technology and innovation management–an exploratory literature review. R&d Management, 42(2), 180-192.
  • Terzioğlu, M. K., Yücel, M. A., Demirkıran, S., & Acaroğlu, D. Kentsel İnovasyonun Kentleşme Üzerine Mekansal Etkisi. İDEALKENT, 11(30). DOI: 10.31198/idealkent.683583
  • Verspagen, B. (1997). Measuring intersectoral technology spillovers: estimates from the European and US patent office databases. Economic Systems Research, 9(1), 47-65.
  • Yücel, M.A. (2021). Sürdürebilir Kalkınma Çerçevesinde Eko-Verimlilik ve Eko-İnovasyon: Dinamik Mekansal Etkileşim. (Yüksek Lisans Tezi), Trakya Üniversitesi Sosyal Bilimler Enstitüsü Ekonometri Anabilim Dalı
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Details

Primary Language Turkish
Journal Section Articles
Authors

Mehmet Ali Yücel 0000-0002-5474-3307

Publication Date May 31, 2021
Submission Date April 2, 2021
Published in Issue Year 2021 Volume: 23 Issue: 1

Cite

APA Yücel, M. A. (2021). Çevresel Sürdürülebilirliğin Değerlendirilmesi: Dinamik Mekânsal Panel Veri Yaklaşımı. Bilgi Sosyal Bilimler Dergisi, 23(1), 53-90.

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