Çevresel inovasyon ve sağlık harcamalarının çevre kirliliği üzerindeki etkisi: Kantil panel yaklaşımı

Abstract

Sağlık harcamaları ve çevresel inovasyon düzeyindeki farklılıklar hem gelişmiş hem de gelişmekte olan ülkeler açısından çeşitli çevresel sonuçlar doğurabilmektedir. Çevresel sürdürülebilirliğin sağlanabilmesi noktasında bu faktörler oldukça ön plana çıkmaktadır. Bu çalışmanın amacı çevresel inovasyon ve sağlık harcamalarının çevre kirliliği üzerindeki etkisini araştırmaktır. Ampirik analizde 2000-2021 dönemine ve 5 ülkeye (Çin, Hindistan, Rusya, Japonya ve ABD) ait panel veriler kullanılmıştır. Çevre kirliliğinin göstergesi olarak literatürde sıklıkla CO2 emisyonu verisi kullanılmasına rağmen çeşitli avantajlarından dolayı bu çalışmada “yük kapasite faktörü” verisi kullanılmıştır. Çevresel inovasyonu temsilen “çevreyi korumaya yönelik teknoloji patent sayıları” verisi, sağlık harcamaları (%GSYH) ve kontrol değişken olarak kişi başına GSYH verisi kullanılmıştır. Değişkenler arasındaki eşbütünleşik ilişki Westerlund (2007) tarafından geliştirilen panel eşbütünleşme testi ile analiz edilmiştir. Ardından uzun dönem katsayılar geleneksel panel veri yöntemi Driscoll-Kraay Standart hatalar (DKSE) ve güncel bir yöntem olan Momentler Metodu Kantil Regresyon (MMQR) yöntemi ile tahmin edilmiştir. Her iki tahmin sonucu birbirine paralellik göstermektedir. Buna göre çevresel inovasyonun çevre kirliliğini arttırdığı, sağlık harcamalarının ise azalttığı sonucuna ulaşılmıştır. Kontrol değişken olarak modellere dahil edilen kişi başına GSYH ise çevre kirliliğini arttırdığı tespit edilmiştir. Son aşamada ilişkilerin yönü Kónya (2006) panel nedensellik testi ile tespit edilmiştir.

Keywords

• çevresel inovasyon
• sağlık harcamaları
• ekonomik büyüme
• çevre kirliliği

The impact of environmental innovation and health expenditures on environmental pollution: Quantile panel approach

Abstract

Differences in health expenditures and levels of environmental innovation can generate diverse environmental outcomes in both developed and developing economies. These factors play a critical role in achieving environmental sustainability. This study examines the impact of environmental innovation and health expenditures on environmental pollution using panel data for five major economies China, India, Russia, Japan, and the United States covering the period 2000–2021. While CO₂ emissions are typically used as a proxy for pollution, this study employs the load capacity factor because of its methodological advantages. Environmental innovation is measured by the number of patents related to environmentally friendly technologies, health expenditures are expressed as a percentage of GDP, and per capita GDP serves as a control variable. Cointegration among the variables is examined using Westerlund’s (2007) panel cointegration test. Long-run coefficients are estimated through both the Driscoll–Kraay standard error approach and the Method of Moments Quantile Regression (MMQR). The results from both methods are consistent, showing that environmental innovation increases environmental pollution, whereas health expenditures mitigate it. Per capita GDP, by contrast, is found to increase environmental pollution. Finally, causality directions are analyzed through Kónya’s (2006) panel causality test.

Keywords

• environmental innovation
• health expenditures
• economic growth
• environmental pollution

References

1. Adebayo, T. S., ve Kirikkaleli, D. (2021). Impact of renewable energy consumption, globalization, and technological innovation on environmental degradation in Japan: application of wavelet tools. Environment, Development and Sustainability, 23(11), 16057-16082. https://doi.org/ 10.1007/s10668-021-01322-2.
2. Ahmad, N., Youjin, L., Žiković, S., ve Belyaeva, Z. (2023). The effects of technological innovation on sustainable development and environmental degradation: Evidence from China. Technology in Society, 72, 102184. https://doi.org/10.1016/j.techsoc.2022.102184.
3. Ali, E. B., Shayanmehr, S., Radmehr, R., Amfo, B., Awuni, J. A., Gyamfi, B. A., ve Agbozo, E. (2023). Exploring the impact of economic growth on environmental pollution in South American countries: how does renewable energy and globalization matter?. Environmental Science and Pollution Research, 30(6), 15505-15522. . https://doi.org/ 10.1007/s11356-022-23177-4.
4. Álvarez-Herránz, A., Balsalobre, D., Cantos, J. M., ve Shahbaz, M. (2017). Energy innovations-GHG emissions nexus: fresh empirical evidence from OECD countries. Energy policy, 101, 90-100. . https://doi.org/ 10.1016/j.enpol.2016.11.030.
5. Apergis, N., Jebli, M. B., ve Youssef, S. B. (2018). Does renewable energy consumption and health expenditures decrease carbon dioxide emissions? Evidence for sub-Saharan Africa countries. Renewable energy, 127, 1011-1016. https://doi.org/10.1016/j.renene.2018.05.043.
6. Apergis, N., Bhattacharya, M., ve Hadhri, W. (2020). Health care expenditure and environmental pollution: a cross-country comparison across different income groups. Environmental Science and Pollution Research, 27(8), 8142-8156. https://doi.org/10.1007/s11356-019-07457-0.
7. Başar, S., ve Tosun, B. (2021). Environmental Pollution Index and economic growth: evidence from OECD countries. Environmental Science and Pollution Research, 28(27), 36870-36879. https://doi.org/ 10.1007/s11356-021-13225-w.
8. Behera, P., ve Sethi, N. (2022). Nexus between environment regulation, FDI, and green technology innovation in OECD countries. Environmental Science and Pollution Research, 29(35), 52940-52953. https://doi.org/ 10.1007/s11356-022-19458-7.

9. Berkhout, P. H., Muskens, J. C., ve Velthuijsen, J. W. (2000). Defining the rebound effect. Energy policy, 28(6-7), 425-432. https://doi.org/10.1016/S0301-4215(00)00022-7.
10. Bilgili, F., Kuşkaya, S., Khan, M., Awan, A., ve Türker, O. (2021). The roles of economic growth and health expenditure on CO2 emissions in selected Asian countries: a quantile regression model approach. Environmental Science and Pollution Research, 28(33), 44949-44972. https://doi.org/ 10.1007/s11356-021-13639-6.
11. Breusch, T. S., ve A. R. Pagan (1980). The lagrange multiplier test and its applications to model specification in econometrics, Review of Economic Studies 47, 239-253.
12. Carrión-Flores, C. E., ve Innes, R. (2010). Environmental innovation and environmental performance. Journal of Environmental Economics and Management, 59(1), 27-42. https://doi.org/10.1016/j.jeem.2009.05.003.
13. Cheng, C., Ren, X., ve Wang, Z. (2019). The impact of renewable energy and innovation on carbon emission: an empirical analysis for OECD countries. Energy Procedia, 158, 3506-3512. https://doi.org/ 10.1016/j.egypro.2019.01.919.
14. Chien, F., Ajaz, T., Andlib, Z., Chau, K. Y., Ahmad, P., ve Sharif, A. (2021). The role of technology innovation, renewable energy and globalization in reducing environmental degradation in Pakistan: a step towards sustainable environment. Renewable Energy, 177, 308-317. https://doi.org/ 10.1016/j.renene.2021.05.101.
15. Choi, J. Y., ve Han, D. B. (2018). The links between environmental innovation and environmental performance: Evidence for high-and middle-income countries. Sustainability, 10(7), 2157. https://doi.org/ 10.3390/su10072157.
16. Conley, H. A. ve Newlin, C. (2021, January 13). Climate Change Will Reshape Russia, Center For Strategic & International Studies (CSIS), https://www.csis.org/analysis/climate-change-will-reshape-russia.
17. Çobanoğulları, G. (2024). Exploring the link between CO2 emissions, health expenditure, and economic growth in Türkiye: evidence from the ARDL model. Environment, Development and Sustainability, 26(11), 29605-29619. https://doi.org/10.1007/s10668-024-04835-8.
18. Das, R. C., ve Ivaldi, E. (2021). Is pollution a cost to health? Theoretical and empirical inquiry for the world’s leading polluting economies. International Journal of Environmental Research and Public Health, 18(12), 6624. https://doi.org/10.3390/ijerph18126624.
19. Ding, Q., Khattak, S. I., ve Ahmad, M. (2021). Towards sustainable production and consumption: assessing the impact of energy productivity and eco-innovation on consumption-based carbon dioxide emissions (CCO2) in G-7 nations. Sustainable Production and Consumption, 27, 254-268. https://doi.org/10.1016/j.spc.2020.11.004.
20. Driscoll, J. C., ve Kraay, A. C. (1998). Consistent covariance matrix estimation with spatially dependent panel data. The Review of Economics and Statistics, 80(4), 549-560.
21. Eren, M. (2023). OECD ülkelerinde küreselleşmenin kayıt dışı ekonomi üzerindeki rolü: Momentler kantil regresyon yönteminden kanıtlar. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 18(1), 104-128. https://doi.org/10.17153/oguiibf.1145945.
22. Gao, X., ve Fan, M. (2023). The role of quality institutions and technological innovations in environmental sustainability: Panel data analysis of BRI countries. Plos one, 18(6), e0287543. https://doi.org/10.1371/journal.pone.0287543.
23. Griliches, Z. (1990). Patent statistics as economic indicators: a survey. In R&D and productivity: the econometric evidence (pp. 287-343). University of Chicago Press.
24. Guloglu, B., Caglar, A. E., ve Pata, U. K. (2023). Analyzing the determinants of the load capacity factor in OECD countries: evidence from advanced quantile panel data methods. Gondwana Research, 118, 92-104. https://doi.org/10.1016/j.gr.2023.02.013.
25. Haščič, I., ve Migotto, M. (2015). Measuring environmental innovation using patent data. OECD Environment Working Papers, No. 89.
26. Hoa, P. X., Xuan, V. N., ve Thu, N. T. P. (2023). Nexus of innovation, renewable consumption, FDI, growth and CO2 emissions: The case of Vietnam. Journal of Open Innovation: Technology, Market, and Complexity, 9(3), 100100. https://doi.org/10.20944/preprints202304.0120.v1.
27. Johnstone, N., Haščič, I., ve Popp, D. (2010). Renewable energy policies and technological innovation: evidence based on patent counts. Environmental and Resource Economics, 45, 133-155. https://doi.org/ 10.1007/s10640-009-9309-1.
28. Juhl, T., ve Lugovskyy, O. (2014). A test for slope heterogeneity in fixed effects models. Econometric Reviews, 33(8), 906-935. https://doi.org/10.1080/07474938.2013.806708.
29. Kahuthu, A. (2006). Economic growth and environmental degradation in a global context. Environment, Development and Sustainability, 8, 55-68. https://doi.org/ 10.1007/s10668-005-0785-3.
30. Kaplan, S. B., ve Forst, L. (2017). Linking environmental sustainability, health, and safety data in health care: A research roadmap. New Solutions: A Journal of Environmental and Occupational Health Policy, 27(2), 189-209. https://doi.org/ 10.1177/1048291117710784.
31. Kemp, R., ve Pearson, P. (2007). Final report MEI project about measuring eco-innovation. UM Merit, Maastricht, 10(2), 1-120.
32. Khan, Z., Ali, S., Umar, M., Kirikkaleli, D., ve Jiao, Z. (2020). Consumption-based carbon emissions and international trade in G7 countries: the role of environmental innovation and renewable energy. Science of the Total Environment, 730, 138945. https://doi.org/ 10.1016/j.scitotenv.2020.138945.
33. Khasanova, S. S., ve Saydulgerieva, M. A. (2024). Environmental pollution and implementation of sustainable development goals. BIO Web of Conferences, 82, 1-5.
34. Koons, E. (2024). Japan Environmental Issues 2024. https://energytracker.asia/environmental-issues-in-japan-and-solutions/
35. Kónya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic modelling, 23(6), 978-992. https://doi.org/10.1016/j.econmod.2006.04.008.
36. Machado, J. A., ve Silva, J. S. (2019). Quantiles via moments. Journal of Econometrics, 213(1), 145-173. https://doi.org/10.1016/j.jeconom.2019.04.009.
37. Milindi, C. B., ve Inglesi-Lotz, R. (2022). The role of green technology on carbon emissions: does it differ across countries’ income levels?. Applied Economics, 54(29), 3309-3339. https://doi.org/ 10.1080/00036846.2021.1998331.
38. Pata, U. K. (2021). Do renewable energy and health expenditures improve load capacity factor in the USA and Japan? A new approach to environmental issues. The European Journal of Health Economics, 22(9), 1427-1439. https://doi.org/ 10.1007/s10198-021-01321-0.
39. 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. https://doi.org/ 10.1002/jae.951.
40. Pesaran, M. H. (2021). General diagnostic tests for cross-sectional dependence in panels. Empirical Economics, 60(1), 13-50. https://doi.org/ 10.1007/s00181-020-01875-7.
41. Porter, M. E. (1991). Towards a dynamic theory of strategy. Strategic Management Journal, 12(2), 95-117. https://doi.org/ 10.1002/smj.4250121008.
42. Porter, M., ve Van der Linde, C. (1995). Green and competitive: ending the stalemate. The Dynamics of the eco-efficient economy: environmental regulation and competitive advantage, 33, 120-134.
43. Qiu, L. Y., ve He, L. Y. (2017). Are Chinese green transport policies effective? A new perspective from direct pollution rebound effect, and empirical evidence from the road transport sector. Sustainability, 9(3), 429. https://doi.org/10.3390/su9030429.
44. Rasool, H., Malik, M. A., ve Tarique, M. (2020). The curvilinear relationship between environmental pollution and economic growth: Evidence from India. International Journal of Energy Sector Management, 14(5), 891-910. https://doi.org/ 10.1108/IJESM-04-2019-0017.
45. Ruan, Y., ve Zhang, A. (2024). The spatial spillover effect of green technology innovation on water pollution–evidence from 283 Chinese cities. Frontiers in Environmental Economics, 3, 1393583. https://doi.org/ 10.3389/frevc.2024.1393583.
46. Sachs, J. D., Lafortune, G. ve Fuller, G. (2024). The SDGs and the UN Summit of the Future. Sustainable Development Report 2024. Paris: SDSN, Dublin: Dublin University Press. doi:10.25546/108572. https://doi.org/ 10.25546/108572.
47. Santra, S. (2017). The effect of technological innovation on production-based energy and CO2 emission productivity: evidence from BRICS countries. African Journal of Science, Technology, Innovation and Development, 9(5), 503-512.https://doi.org/ 10.1080/20421338.2017.1308069.
48. Shang, Y., Razzaq, A., Chupradit, S., An, N. B., ve Abdul-Samad, Z. (2022). The role of renewable energy consumption and health expenditures in improving load capacity factor in ASEAN countries: Exploring new paradigm using advance panel models. Renewable Energy, 191, 715-722. https://doi.org/ 10.1016/j.renene.2022.04.013.
49. Saqib, N., Usman, M., Ozturk, I., ve Sharif, A. (2024). Harnessing the synergistic impacts of environmental innovations, financial development, green growth, and ecological footprint through the lens of SDGs policies for countries exhibiting high ecological footprints. Energy Policy, 184, 113863. https://doi.org/10.1016/j.enpol.2023.113863.
50. Schumpeter, J. A. (1934). The theory of economic development. Harvard University Press: Cambridge MA.
51. Siche, R., Pereira, L., Agostinho, F., ve Ortega, E. (2010). Convergence of ecological footprint and emergy analysis as a sustainability indicator of countries: Peru as case study. Communications in Nonlinear Science and Numerical Simulation, 15(10), 3182-3192. https://doi.org/10.1016/j.cnsns.2009.10.027. S uki, N. M., Suki, N. M., Sharif, A., Afshan, S., ve Jermsittiparsert, K. (2022). The role of technology innovation and renewable energy in reducing environmental degradation in Malaysia: A step towards sustainable environment. Renewable Energy, 182, 245-253.https://doi.org/ 10.1016/j.renene.2021.10.007.
52. Sun, J., Wang, J., Wang, T., ve Zhang, T. (2019). Urbanization, economic growth, and environmental pollution: Partial differential analysis based on the spatial Durbin model. Management of Environmental Quality: An International Journal, 30(2), 483-494. https://doi.org/10.1108/MEQ-05-2018-0101.
53. Szymczyk, K., Şahin, D., Bağcı, H., ve Kaygın, C. Y. (2021). The effect of energy usage, economic growth, and financial development on CO2 emission management: an analysis of OECD countries with a High environmental performance index. Energies, 14(15), 4671. https://doi.org/ 10.3390/en14154671.
54. Swamy, P. A. V. B. (1970). Efficient inference in a random coefficient regression model. Econometrica, 38(2), 311-323.
55. Töbelmann, D., ve Wendler, T. (2020). The impact of environmental innovation on carbon dioxide emissions. Journal of Cleaner Production, 244, 118787. https://doi.org/10.1016/j.jclepro.2019.118787.
56. Wager, E., McGough, M., Rakshit, S. ve Cox, C. (2025). How does health spending in the U.S. compare to other countries?. Health System Tracker, The Peterson Center on Healthcare & KFF.
57. Wang, G., Feng, L., ve Zhao, P. (2024). New approaches for testing slope homogeneity in large panel data models. Communications in Mathematics and Statistics, 1-31. https://doi.org/10.1007/s40304-023-00371-5.
58. Wang, A., Rauf, A., Ozturk, I., Wu, J., Zhao, X., ve Du, H. (2024). The key to sustainability: In-depth investigation of environmental quality in G20 countries through the lens of renewable energy, economic complexity and geopolitical risk resilience. Journal of Environmental Management, 352, 120045. https://doi.org/ 10.1016/j.jenvman.2024.120045.
59. Waris, U., Mehmood, U., ve Tariq, S. (2023). Analyzing the impacts of renewable energy, patents, and trade on carbon emissions evidence from the novel method of MMQR. Environmental Science and Pollution Research, 30(58), 122625-122641. https://doi.org/ 10.1007/s11356-023-30991-x.
60. Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics, 69(6), 709-748. https://doi.org/10.1111/j.1468-0084.2007.00477.x.
61. Westerlund, J., Hosseinkouchack, M., ve Solberger, M. (2014). The local power of the CADF and CIPS panel unit root tests. Econometric Reviews, 35(5), 845-870. https://doi.org/ 10.1080/07474938.2014.977077.
62. Tiwari, S., Sharif, A., Sofuoğlu, E., ve Nuta, F. (2025). A step toward the attainment of carbon neutrality and SDG-13: Role of financial depth and green technology innovation. Research in International Business and Finance, 73, 102631. https://doi.org/10.1016/j.ribaf.2024.102631.
63. Toplicianu, V., ve Toplicianu, S. (2014). The Impact of environmental degradation on health expenditure. Annals-Economy Series, 172-177.
64. Vankar, P. (2025). Health expenditure as a percentage of gross domestic product (GDP) in selected countries as of 2023, https://www.statista.com/statistics/268826/health-expenditure-as-gdp-percentage-in-oecd-countries/
65. Viglioni, M. T. D., Calegario, C. L. L., Viglioni, A. C. D., ve Bruhn, N. C. P. (2024). Foreign direct investment and environmental degradation: Can intellectual property rights help G20 countries achieve carbon neutrality?. Technology in Society, 77, 102501. https://doi.org/ 10.1016/j.techsoc.2024.102501.
66. Xie, P., ve Jamaani, F. (2022). Does green innovation, energy productivity and environmental taxes limit carbon emissions in developed economies: Implications for sustainable development. Structural Change and Economic Dynamics, 63, 66-78. https://doi.org/ 10.1016/j.strueco.2022.09.002.
67. Xin, D., Zhi Sheng, Z., ve Jiahui, S. (2022). How technological innovation influences environmental pollution: Evidence from China. Complexity, 2022(1), 5535310. https://doi.org/10.1155/2022/5535310.
68. Yang, B. Usman, M. ve Jahanger, A. (2021). Do industrialization, economic growth and globalization processes influence the ecological footprint and healthcare expenditures? Fresh insights based on the STIRPAT model for countries with the highest healthcare expenditures. Sustainable Production and Consumption, 28, 893-910. https://doi.org/10.1016/j.spc.2021.07.020.
69. Yang, X., Li, N., Mu, H., Pang, J., Zhao, H., ve Ahmad, M. (2021). Study on the long-term impact of economic globalization and population aging on CO2 emissions in OECD countries. Science of the Total Environment, 787, 147625. https://doi.org/ 10.1016/j.scitotenv.2021.147625.
70. Yamak, R. ve Köseoğlu, M. (2006). Uygulamalı istatistik ve ekonometri (3. baskı). Celepler Matbaacılık, Trabzon.
71. Yerdelen Tatoğlu, F. (2013). Panel veri ekonometrisi-stata uygulamalı. Beta Yayınevi, 2. Baskı, İstanbul.
72. Yerdelen Tatoğlu, F. (2018). Panel zaman serileri analizi. Beta Yayınevi, 2. Baskı, İstanbul.
73. Zaidi, S., ve Saidi, K. (2018). Environmental pollution, health expenditure and economic growth in the Sub-Saharan Africa countries: Panel ARDL approach. Sustainable cities and society, 41, 833-840. https://doi.org/10.1016/j.scs.2018.04.034.
74. Zellner, A. (1962). An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias, Journal of the American Statistical Association, 57, 348-368.
75. Zhao, X., Long, L., Yin, S., ve Zhou, Y. (2023). How technological innovation influences carbon emission efficiency for sustainable development? Evidence from China. Resources, Environment and Sustainability, 14, 100135. https://doi.org/10.1016/j.resenv.2023.100135.
76. Zhou, D., Obobisa, E. S., ve Ayamba, E. C. (2024). Achieving carbon neutrality goal in European countries: The role of green technology innovation, renewable energy, and financial development. Environment, Development and Sustainability, 1-31. https://doi.org/ 10.1007/s10668-024-04989-5.