Dergiler / Iğdır Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2026 / Sayı: 14

Reel Efektif Döviz Kuru Teknolojik Kapasitenin Çevresel Etkilerini Koşullandırıyor mu? OECD Ülkeleri Üzerine Kanıtlar

Does the Real Effective Exchange Rate Moderate the Environmental Effects of Technological Capacity? Evidence from OECD Countries

Sayfa
—
Yayın Tarihi
2026-10-30
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Bulgular, teknolojik kapasitenin karbon emisyonları üzerindeki etkisinin doğrusal olmadığını göstermektedir.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Teknolojik kapasitenin çevresel etkileri, ülkelerin ekonomik ve rekabetçi yapısına bağlı olarak farklılaşabilmektedir.
📊
Temel Bulgular & Veri:Ancak bu farklılaşmada reel efektif döviz kurunun oynadığı rol henüz yeterince açıklığa kavuşturulamamıştır.
💡
Sonuç & Katkı:Bulgular, teknolojik kapasitenin karbon emisyonları üzerindeki etkisinin doğrusal olmadığını göstermektedir.
🔬Tür:Araştırma Makalesi
📍Kapsam:2007–2023 Verileri
⚙️Değişkenler:Teknolojik Kapasite · Karbon Emisyonları · Reel Efektif Döviz Kuru

Özet

Teknolojik kapasitenin çevresel etkileri, ülkelerin ekonomik ve rekabetçi yapısına bağlı olarak farklılaşabilmektedir. Ancak bu farklılaşmada reel efektif döviz kurunun oynadığı rol henüz yeterince açıklığa kavuşturulamamıştır. Bu kapsamda çalışmada, teknolojik kapasitenin karbon emisyonları üzerindeki etkisini ve reel efektif döviz kuru düzeyinin bu ilişki üzerindeki koşullandırıcı rolünü incelemektedir. Analizde, 2007–2023 döneminde 20 OECD ülkesine ait panel veriler kullanılmıştır. Teknolojik kapasiteyi temsil etmek amacıyla, yüksek teknoloji ihracatı, Ar-Ge yoğunluğu ve teknoloji temelli patent göstergelerinden yararlanılarak, Temel Bileşenler Analizi (PCA) yöntemiyle bir bütünleşik teknolojik kapasite endeksi (BTKE) oluşturulmuştur. Değişkenler arasındaki dinamik ilişkiler ise iki aşamalı Sistem GMM yöntemiyle tahmin edilmiştir. Ayrıca, teknolojik kapasitenin farklı reel efektif döviz kuru düzeylerindeki etkisi koşullu marjinal etki analizi kullanılarak değerlendirilmiştir. Bulgular, teknolojik kapasitenin karbon emisyonları üzerindeki etkisinin doğrusal olmadığını göstermektedir. Reel efektif döviz kurunun düşük olduğu seviyelerde teknolojik kapasite karbon emisyonlarını artırırken, reel efektif döviz kuru yükseldikçe bu etki zayıflamakta ve belirli bir seviyeden sonra emisyonu azaltıcı hale gelmektedir. Sonuçlar, teknolojik gelişmelerin çevresel etkilerinin ülkelerin rekabet yapısı ve makroekonomik koşulları tarafından şekillendirildiğini ortaya koymaktadır.

Abstract

The environmental effects of technological capacity may vary depending on the economic and competitive structure of countries. However, the role played by the real effective exchange rate in this variation has not yet been sufficiently clarified. In this context, the study examines the effect of technological capacity on carbon emissions and the conditioning role of the level of the real effective exchange rate in this relationship. The analysis uses panel data for 20 OECD countries covering the period 2007–2023. In order to represent technological capacity, an Integrated Technological Capacity Index (ITCI) was constructed using the Principal Component Analysis (PCA) method based on high-technology exports, R&D intensity, and technology-based patent indicators. The dynamic relationships among the variables were estimated using the two-step System GMM method. In addition, the effect of technological capacity at different levels of the real effective exchange rate was evaluated using conditional marginal effects analysis. The findings indicate that the effect of technological capacity on carbon emissions is not linear. At low levels of the real effective exchange rate, technological capacity increases carbon emissions, whereas as the real effective exchange rate rises, this effect weakens and, beyond a certain level, becomes emission-reducing. The results reveal that the environmental effects of technological development are shaped by countries' competitive structures and macroeconomic conditions.

🔖

Bu Makaleye Atıf Yap

Aslan, M. B. (2026). Reel Efektif Döviz Kuru Teknolojik Kapasitenin Çevresel Etkilerini Koşullandırıyor mu? OECD Ülkeleri Üzerine Kanıtlar. Iğdır Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Sayı: 14. https://doi.org/10.58618/igdiriibf.2007086

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (45)

  1. Acemoglu, D., Aghion, P., Bursztyn, L., & Hemous, D. (2012). The environment and directed technical change. American Economic Review, 102(1), 131–166. https://doi.org/10.1257/aer.102.1.131
  2. Ahmad, M., Jabeen, G., Shah, S. A. A., Rehman, A., Ahmad, F., & Işik, C. (2022). Assessing long- and short-run dynamic interplay among balance of trade, aggregate economic output, real exchange rate, and CO₂ emissions in Pakistan. Environment, Development and Sustainability, 24(5), 7283–7323. https://doi.org/10.1007/s10668-021-01747-9
  3. Akyol, M., & Mete, E. (2021). Çevresel teknolojik inovasyonların CO₂ emisyonu üzerindeki etkisi: OECD ülkeleri örneği. İstanbul İktisat Dergisi, 71(2), 569–590. https://doi.org/10.26650/ISTJECON2021-935480
  4. Archibugi, D., & Coco, A. (2004). A new indicator of technological capabilities for developed and developing countries (ArCo). World Development, 32(4), 629–654. https://doi.org/10.1016/j.worlddev.2003.10.008
  5. Archibugi, D., & Coco, A. (2005). Measuring technological capabilities at the country level: A survey and a menu for choice. Research Policy, 34(2), 175–194. https://doi.org/10.1016/j.respol.2004.12.002
  6. 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
  7. Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. https://doi.org/10.1016/S0304-4076(98)00009-8 Castellacci, F., & Natera, J. M. (2013). The dynamics of national innovation systems: A panel cointegration analysis of the coevolution between innovative capability and absorptive capacity. Research Policy, 42(3), 579–594. https://doi.org/10.1016/j.respol.2012.10.006
  8. Cheng, C., Ren, X., Dong, K., Dong, X., & Wang, Z. (2021). How does technological innovation mitigate CO₂ emissions in OECD countries? Heterogeneous analysis using panel quantile regression. Journal of Environmental Management, 280, 111818. https://doi.org/10.1016/j.jenvman.2020.111818
  9. Cinelli, C., Forney, A., & Pearl, J. (2024). A crash course in good and bad controls. Sociological Methods & Research, 53(3), 1071–1104. https://doi.org/10.1177/00491241221099552
  10. Costantini, V., & Mazzanti, M. (2012). On the green and innovative side of trade competitiveness? The impact of environmental policies and innovation on EU exports. Research Policy, 41(1), 132–153. https://doi.org/10.1016/j.respol.2011.08.004
  11. Copeland, B. R., & Taylor, M. S. (2004). Trade, growth, and the environment. Journal of Economic Literature, 42(1), 7–71. https://doi.org/10.1257/002205104773558047
  12. Daştan, M. (2024). The role of renewable energy, technological innovation, and human capital on environmental quality in Türkiye: Testing the LCC hypothesis with smooth structural shifts. Yüzüncü Yıl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 65, 76–91. https://doi.org/10.53568/yyusbed.1480175
  13. Derindag, O. F., & Aldawsari, S. H. (2025). Trade openness and the energy–carbon nexus: policy ımplications for emerging and advanced economies. Sustainability, 17(23), 10762. https://doi.org/10.3390/su172310762
  14. Ehigiamusoe, K. U., Dogan, E., Ramakrishnan, S., & Binsaeed, R. H. (2024). How does technological innovation moderate the environmental impacts of economic growth, natural resource rents and trade openness? Journal of Environmental Management, 371, 123229. https://doi.org/10.1016/j.jenvman.2024.123229
  15. Fagerberg, J., Srholec, M., & Verspagen, B. (2018). The role of innovation in development. In J. Fagerberg, Innovation, Economic Development and Policy: Selected Essays (2nd ed., Vol. 1, pp. 64–92). Edward Elgar Publishing. https://doi.org/10.4337/9781788110266.00009
  16. Furman, J. L., Porter, M. E., & Stern, S. (2002). The determinants of national innovative capacity. Research Policy, 31(6), 899–933. https://doi.org/10.1016/S0048-7333(01)00152-4
  17. Ghazouani, T., Ouechtati, I., & Abidi, Z. (2026). Do financial development, technological innovation and carbon emissions exhibit time-dynamic relationships? Evidence from OECD countries. Journal of Climate Finance, 15, 100088. https://doi.org/10.1016/j.jclimf.2026.100088
  18. Grossman, G. M., & Krueger, A. B. (1991). Environmental impacts of a North American Free Trade Agreement (NBER Working Paper No. 3914). National Bureau of Economic Research. https://doi.org/10.3386/w3914
  19. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson.
  20. Jemberu, E. T., & Metzker, Z. (2026). The impact of national technological capabilities on foreign direct investment inflows: An empirical analysis. Business Process Management Journal. https://doi.org/10.1108/BPMJ-11-2025-1914
  21. Jolliffe, I. T. (2002). Principal component analysis (2nd ed.). Springer. https://doi.org/10.1007/b98835
  22. Johnstone, N., Haščič, I., & Popp, D. (2010). Renewable energy policies and technological innovation: Evidence based on patent counts. Environmental and Resource Economics, 45(1), 133–155. https://doi.org/10.1007/s10640-009-9309-1
  23. Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. https://doi.org/10.1177/001316446002000116
  24. Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. https://doi.org/10.1007/BF02291575
  25. Kim, J., Sovacool, B. K., Bazilian, M., Griffiths, S., & Yang, M. (2024). Energy, material, and resource efficiency for industrial decarbonization: A systematic review of sociotechnical systems, technological innovations, and policy options. Energy Research & Social Science, 112, 103521. https://doi.org/10.1016/j.erss.2024.103521
  26. Lall, S. (1992). Technological capabilities and industrialization. World Development, 20(2), 165–186. https://doi.org/10.1016/0305-750X(92)90097-F
  27. Liao, T., Yan, J., & Zhang, Q. (2024). The impact of green technology innovation on carbon emission efficiency: The intermediary role of intellectual capital. International Review of Economics & Finance, 92, 1014–1032. https://doi.org/10.1016/j.iref.2024.02.016
  28. Lee, J., & Yue, C. (2017). Impacts of the US dollar (USD) exchange rate on economic growth and the environment in the United States. Energy Economics, 64, 170–176. https://doi.org/10.1016/j.eneco.2017.03.006
  29. Lundvall, B.-Å. (Ed.). (1992). National systems of innovation: Towards a theory of innovation and interactive learning. Pinter Publishers.
  30. Nelson, R. R. (Ed.). (1993). National innovation systems: A comparative analysis. Oxford University Press.
  31. Nickell, S. (1981). Biases in dynamic models with fixed effects. Econometrica, 49(6), 1417–1426. https://doi.org/10.2307/1911408
  32. Park, D., & Ridley, W. (2025). How do exchange rates affect environmental quality? Canadian Journal of Economics/Revue canadienne d'économique, 58(1), 356–384. https://doi.org/10.1111/caje.12748
  33. Popp, D. (2002). Induced innovation and energy prices. American Economic Review, 92(1), 160–180. https://doi.org/10.1257/000282802760015658
  34. Radin, A., Scobell, A., Treyger, E., Williams, J. D., Ma, L., Shatz, H. J., Zeigler, S. M., Han, E., & Reach, C. (2021). China-Russia cooperation: Determining factors, future trajectories, implications for the United States. RAND Corporation, Research Report RR-3067-A.
  35. Ricci, L. A., Milesi-Ferretti, G. M., & Lee, J. (2013). Real exchange rates and fundamentals: A cross-country perspective. Journal of Money, Credit and Banking, 45(5), 845–865. https://doi.org/10.1111/jmcb.12027
  36. Rodrik, D. (2008). The real exchange rate and economic growth. Brookings Papers on Economic Activity, 39(2), 365–412. https://doi.org/10.1353/eca.0.0020
  37. Roodman, D. (2009). A note on the theme of too many instruments. Oxford Bulletin of Economics and Statistics, 71(1), 135–158. https://doi.org/10.1111/j.1468-0084.2008.00542.x
  38. Sakilu, O. B., & Chen, H. (2026). Do green technology innovation and trade openness drive carbon neutrality in developing countries? Examining the mediating role of energy consumption. Sustainable Development, 34(1), 240–261. https://doi.org/10.1002/sd.70208
  39. Saqib, N., Usman, M., Mahmood, H., Abbas, S., Ahmad, F., Mihai, D., & Mallek, R. S. (2023). The moderating role of technological innovation and renewable energy on CO₂ emission in O.E.C.D. countries: Evidence from panel quantile regression approach. Economic Research-Ekonomska Istraživanja, 36(3), 2168720. https://doi.org/10.1080/1331677X.2023.2168720
  40. Smaili, S. M., & Gam, I. (2023). Dynamic effect of exchange rate depreciation on carbon emission in the Mediterranean basin: Fresh insights from linear and non-linear ARDL approaches. Environmental Science and Pollution Research, 30(21), 59481–59498. https://doi.org/10.1007/s11356-023-26674-2
  41. Stern, N. (2007). The economics of climate change: The Stern review. Cambridge University Press.
  42. Ullah, A., Dogan, M., Pervaiz, A., Bukhari, A. A. A., Akkus, H. T., & Dogan, H. (2024). The impact of digitalization, technological and financial innovation on environmental quality in OECD countries: Investigation of N-shaped EKC hypothesis. Technology in Society, 77, 102484. https://doi.org/10.1016/j.techsoc.2024.102484
  43. World Intellectual Property Organization. (2026). WIPO IP statistics data center. Retrieved May 2026, from https://www3.wipo.int/ipstats/
  44. Yıldırım, D. Ç., Esen, Ö., & Yıldırım, S. (2022). The nonlinear effects of environmental innovation on energy sector-based carbon dioxide emissions in OECD countries. Technological Forecasting and Social Change, 182, 121800. https://doi.org/10.1016/j.techfore.2022.121800
  45. Zhang, Y., & Zhang, S. (2018). The impacts of GDP, trade structure, exchange rate and FDI inflows on China's carbon emissions. Energy Policy, 120, 347–353. https://doi.org/10.1016/j.enpol.2018.05.056