Environmental and Economic Determinants of Health Expenditures: A Empirical Analysis on Türkiye

Year 2026, Volume: 11 Issue: 1, 289 - 323, 28.02.2026

Gamze Çimen , Veli Burak Güler , Sercan Yavan

https://doi.org/10.25229/beta.1773038

https://izlik.org/JA43WF36NS

Abstract

This research focuses on Türkiye over the period 1975–2022, examining the interplay between health expenditures and key economic as well as environmental indicators, namely per capita income, industrial value added, natural resource rents, and CO₂ emissions. To capture the long-run linkages, the ARDL bounds testing framework was employed, while causal directions were explored through the Toda–Yamamoto procedure. Results suggest that in the long run, CO₂ emissions are positively and significantly linked to health expenditures, whereas industrial value added, natural resource rents, and per capita income have negative and significant impacts. Moreover, the causality analysis points to a one-way relationship running from natural resource rents to health expenditures, and another from health expenditures to industrial value added. These outcomes imply that environmental deterioration increases the demand for health services, whereas economic and structural indicators tend to constrain the financing capacity of health expenditures. Taken together, the evidence suggests that health spending cannot be explained solely through economic growth patterns; environmental dimensions are also indispensable. Accordingly, sustainable and health-oriented policymaking requires an integrated approach that simultaneously accounts for both environmental pressures and structural economic conditions.

Keywords

Health Expenditures , CO₂ Emissions , Economic Growth

Sağlık Harcamalarının Çevresel ve Ekonomik Belirleyicileri: Türkiye Üzerine Ampirik Bir Analiz

https://izlik.org/JA43WF36NS

Abstract

Bu araştırma, Türkiye’de 1975-2022 dönemine ait veriler kullanılarak sağlık harcamaları ile kişi başına gelir, endüstriyel katma değer, doğal kaynak rantı ve CO₂ emisyonu arasındaki ilişkileri incelemektedir. Çalışmada uzun dönemli bağlantılar ARDL sınır testi ile nedensellik yönleri ise Toda–Yamamoto yaklaşımı üzerinden analiz edilmiştir. Elde edilen bulgularda CO₂ emisyonlarının sağlık harcamalarını uzun vadede artırıcı ve istatistiksel olarak anlamlı bir etki oluşturduğu; endüstriyel katma değer, doğal kaynak rantı ve kişi başına gelir değişkenlerinin ise sağlık harcamaları üzerinde negatif ve anlamlı etkilere neden olduğu belirlenmiştir. Nedensellik testleri, doğal kaynak rantından sağlık harcamalarına ve sağlık harcamalarından endüstriyel katma değere doğru tek yönlü bir ilişki bulunduğunu ortaya koymuştur. Sonuçlar, çevresel bozulmaların sağlık hizmetlerine olan talebi artırdığına; buna karşılık ekonomik ve yapısal göstergelerin sağlık harcamalarının finansmanını sınırlandırıcı etkiler doğurabileceğine işaret etmektedir. Genel olarak elde edilen bulgular, sağlık harcamalarının yalnızca ekonomik büyüme dinamikleriyle açıklanamayacağını; çevresel faktörlerin de bu sürece dâhil edilmesi gerektiğini göstermektedir. Dolayısıyla, sürdürülebilir ve sağlığı merkeze alan politika tasarımlarında hem çevresel hem de yapısal unsurların bütüncül biçimde ele alınması önem arz etmektedir.

Keywords

Sağlık Harcamaları , CO₂ Emisyonu , Ekonomik Büyüme

References

• Abdullah, H., M., Azam, And S. K., Zakariya. The impact of environmental quality on public health expenditure in Malaysia. Asia Pacific Journal of Advanced Business and Social Studies (APJABSS) 2.2 (2016): 365-379.
• Akalin, G., Özbek, R. İ., & Çifçi, İ. (2018). Türkiye’de gelir dağılımı ve ekonomik büyüme arasındaki ilişki: ARDL sınır testi yaklaşımı. Kastamonu Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 20(4), 59-76.
• Akbar, M., Hussain, A., Akbar, A., & Ullah, I. (2021). The dynamic association between healthcare spending, CO₂ emissions, and human development index in OECD countries: Evidence from panel VAR model. Environment, Development and Sustainability, 23(7), 10470–10489. https://doi.org/10.1007/s10668-020-01066-5
• Ansari, T. H., & Ansari, Z. I. (2023). Impact of CO₂ emission, GDP, and energy consumption on health expenditures in India: ARDL bounds testing approach. International Journal of Energy, Environment, and Economics, 30(4).
• Anwar, M. A., Madni, G. R., & Yasin, I. (2021). Environmental quality, forestation, and health expenditure: A cross-country evidence. Environment, Development and Sustainability, 23(11), 16454–16480. https://doi.org/ 10.1007/s10668-021-01364-6
• Apergis, N., Bhattacharya, M., & 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
• Apergis, N., Gupta, R., Lau, C. K. M., & Mukherjee, Z. (2018). State-level carbon dioxide emissions: Does it affect health care expenditure? Renewable and Sustainable Energy Reviews, 91, 521–530. https://doi.org/10.1016/j.rser.2018.03.035
• Atuahene, S. A., Yusheng, K., & Bentum-Micah, G. (2020). Health expenditure, CO₂ emissions, and economic growth: China vs. India. Preprint – Submit Working Paper, 2020090384.
• Awais, M., Khan, A., & Ahmad, M. S. (2021). Determinants of health expenditure from global perspective: A panel data analysis. Liberal Arts and Social Sciences International Journal, 5(1), 482–497. https://doi.org/10.47264/idea.lassij/5.1.31
• Dağ, M., & Kızılkaya, F. (2021). Türkiye için sağlık harcamaları, CO₂ emisyonları ve ekonomik büyüme ilişkisinin incelenmesi. Journal of Management and Economics Research, 19(3), 211–229.
• Demir, S., Demir, H., Karaduman, C., & Cetin, M. (2023). Environmental quality and health expenditures efficiency in Türkiye: The role of natural resources. Environmental Science and Pollution Research, 30(6), 15170-15185. https://doi.org/10.1007/s11356-022-23187-2
• Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427–431.
• Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057-1072.
• Doru, Ö., & Düşünceli, F. (2021). Türkiye’de ticari dışa açıklık ve enflasyon ilişkisi: ARDL sınır testi ve nedensellik analizi. Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(23), 37–54.
• Dritsaki, M., & Dritsaki, C. (2023). The relationship between health expenditure, CO₂ emissions, and economic growth in G7: Evidence from heterogeneous panel data. Journal of the Knowledge Economy, 15(1), 4886-4911. https://doi.org/10.1007/s13132-023-01349-y
• Dumrul, Y. (2019). Sağlık harcamaları ve çevre kirliliği: ASEAN-5 ülkeleri üzerine bir panel veri analizi. IBAD Sosyal Bilimler Dergisi, 396-407. https://doi.org/10.21733/ibad.612184
• Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251-276.
• Esen, E., Yıldırım, S., & Kostakoğlu, S. F. (2012). Feldstein–Horioka hipotezinin Türkiye ekonomisi için sınanması: ARDL modeli uygulaması. Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 7(1), 251-267.
• Eyüboğlu, S., & Eyüboğlu, K. (2018). Borsa İstanbul sektör endeksleri ile döviz kurları arasındaki ilişkilerin incelenmesi: ARDL modeli. Ömer Halisdemir Üniversitesi İİBF Dergisi, 11(1), 8-28.
• Fan, V. Y., & Savedoff, W. D. (2014). The health financing transition: A conceptual framework and empirical evidence. Social Science & Medicine, 105, 112-121. https://doi.org/10.1016/j.socscimed.2014.01.014
• Göktaş, P., Pekmezci, A., & Bozkurt, K. (2018). Ekonometrik serilerde uzun dönem eşbütünleşme ve kısa dönem nedensellik ilişkileri. Ankara: Gazi Kitabevi.
• Gövdeli, T. (2019). Health expenditure, economic growth, and CO₂ emissions: Evidence from the OECD countries. Adıyaman Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 31, 488-516.
• Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438.
• Haseeb, M., Kot, S., Hussain, H. I., & Jermsittiparsert, K. (2019). Impact of economic growth, environmental pollution, and energy consumption on health expenditure and R&D expenditure of ASEAN countries. Energies, 12(19), 3598. https://doi.org/10.3390/en12193598
• Ivankova, V., Gavurova, B., & Khouri, S. (2022). Understanding the relationships between health spending, treatable mortality and economic productivity in OECD countries. Frontiers in Public Health, 10, 1036058. https://doi.org/10.3389/fpubh.2022.1036058
• Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration—with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52(2), 169–210.
• Katircioglu, S. (2024). The effects of an abundance of natural resources on the healthcare industry: The global evidence. Natural Resources Forum, 1-20.
• Khoshnevis Yazdi, S., & Khanalizadeh, B. (2017). Air pollution, economic growth and health care expenditure. Economic Research–Ekonomska Istraživanja, 30(1), 1181-1190.
• Kızılkaya, O., Sofuoğlu, E., & Karaçor, Z. (2016). Türkiye’de turizm gelirleri–ekonomik büyüme ilişkisi: ARDL sınır testi yaklaşımı. Yönetim ve Ekonomi, 23(1), 203-215.
• Kripfganz, S., & Schneider, D. C. (2023). ARDL: Estimating autoregressive distributed lag and equilibrium correction models. The Stata Journal, 23(4), 983-1019.
• Künü, S., & Levent, C. (2023). Sağlık harcamaları, CO₂ emisyonu ve ekonomik büyüme ilişkisi: Seçilmiş AB ülkeleri örneği. Uluslararası Ekonomi ve Yenilik Dergisi, 9(1), 95-110. https://doi.org/10.20979/ueyd.1202332
• Li, L., Du, T., & Zhang, C. (2020). The impact of air pollution on healthcare expenditure for respiratory diseases: Evidence from the People’s Republic of China. Risk Management and Healthcare Policy, 13, 1723-1738. https://doi.org/10.2147/RMHP.S270587
• Meçik, O., & Koyuncu, T. (2020). Türkiye’de göç ve ekonomik büyüme ilişkisi: Toda–Yamamoto nedensellik testi. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 9(3), 2618-2635.
• Medetoğlu, B., & Doğru, E. (2022). Toda–Yamamoto testi ile nedensellik ilişkisi tespiti: Değerli metaller üzerine bir uygulama. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 7(4), 747-757.
• Mehmood, A., Azam, A., & Mahr, M. A. (2022). Impact of industrial production and FDI on CO₂ emissions in Pakistan. Pakistan Journal of Economic Studies, 5(1), 257-272.
• Nikzadian, A., Agheli, L., Arani, A. A., & Sadeghi, H. (2019). The effects of resource rent, human capital and government effectiveness on government health expenditure in OPEC countries. International Journal of Energy Economics and Policy, 9(2), 381-389.
• Nwani, C., & Adams, S. (2021). Environmental cost of natural resource rents based on production and consumption inventories of carbon emissions: Assessing the role of institutional quality. Resources Policy, 74, 102282.
• Nyika, F., Anyikwa, I., Mhaka, S., & Mhlanga, D. (2024). Does environmental degradation matter for healthcare expenditure and health outcomes? Evidence from the Caucasus region and Russia (2000–2020). BRICS Journal of Economics, 5(3), Article 3. https://doi.org/10.3897/brics-econ.5.e127270
• OECD. (2017). Tackling wasteful spending on health. Paris: OECD Publishing.
• Öcal, O., Han, V., & Üstün, Ö. (2025). Sağlık harcamaları ve çevresel sürdürülebilirlik: BRICS-T ülkelerinde ekonomik büyüme ve enerji politikalarının rolü. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 15(1), 290–307. https://doi.org/10.30783/nevsosbilen.1574451
• Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
• Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.
• Polat, M. A., & Ergun, S. (2018). Yapısal kırılma altında Türkiye’de ekonomik büyüme, CO₂ emisyonu ve sağlık harcamaları ilişkisi. Business and Economics Research Journal, 9(3), 481-498.
• Raihan, A., Farhana, S., Muhtasim, D. A., Hasan, M. A. U., Paul, A., & Faruk, O. (2022). The nexus between carbon emission, energy use, and health expenditure: Empirical evidence from Bangladesh. Carbon Research, 1(1), 30. https://doi.org/10.1007/s44246-022-00030-4
• Rana, R. H., Alam, K., & Gow, J. (2020). Health expenditure and gross domestic product: Causality analysis by income level. International Journal of Health Care Finance and Economics, 20(1), 55-77. https://doi.org/10.1007/s10754-019-09270-1
• Sabra, M. (2022). Health expenditure, life expectancy, fertility rate, CO₂ emissions and economic growth: Do public, private and external health expenditures matter? International Journal of Economic Sciences, 11(2), 179-191. https://doi.org/10.52950/ES.2022.11.2.010
• Sancar, C., & Polat, M. A. (2021). CO₂ emisyonları, ekonomik büyüme ve sağlık harcamaları ilişkisi: Türkiye ve seçilmiş ülke örnekleri için ampirik bir uygulama. MANAS Sosyal Araştırmalar Dergisi, 10(1), 236-252.
• Slathia, P., Vashishtha, A., Jena, P. K., & Sahu, P. K. (2024). Examining the dynamic impact of carbon emissions, renewable energy and economic growth on healthcare expenditure in Asian countries. Heliyon, 10(9), e30136.
• Sorenson, C., Drummond, M., & Bhuiyan Khan, B. (2013). Medical technology as a key driver of rising health expenditure: Disentangling the relationship. ClinicoEconomics and Outcomes Research, 5, 223-234. https://doi.org/10.2147/CEOR.S39634
• Szymańska, A. (2025). The relationship between health expenditure, income, and environmental degradation: Evidence from OECD economies. Economic Analysis and Policy, 87, 2183-2201.
• Şahin, D., & Durmuş, S. (2019). OECD ülkelerinde ekonomik büyüme ve çevre kirliliğinin sağlık harcamaları üzerine etkisinin analizi. Finans Politik & Ekonomik Yorumlar, 56(647).
• Tayyar, A. E. (2018). Endojen para arzının politik yönü: Türkiye için Toda–Yamamoto nedensellik analizinin uygulanması. The Journal of Social Sciences, 26(26). https://doi.org/10.16990/SOBIDER.4369
• Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250.
• Uğurlu, E. (2009). Durağanlık ve birim kök sınamaları. Ders Notları, 1, 1–17. Ullah, I., Ali, S., Shah, M. H., Yasim, F., Rehman, A., & Al-Ghazali, B. M. (2019). Linkages between trade, CO₂ emissions and healthcare spending in China. International Journal of Environmental Research and Public Health, 16(21), 4298. https://doi.org/10.3390/ijerph16214298
• Ullah, I., Rehman, A., Khan, F. U., Shah, M. H., & Khan, F. (2020). Nexus between trade, CO₂ emissions, renewable energy, and health expenditure in Pakistan. International Journal of Health Planning and Management, 35(4), 818-831. https://doi.org/10.1002/hpm.2912
• Wang, Z., Asghar, M. M., Zaidi, S. A. H., & Wang, B. (2019). Dynamic linkages among CO₂ emissions, health expenditures, and economic growth: Empirical evidence from Pakistan. Environmental Science and Pollution Research, 26(15), 15285-15299. https://doi.org/10.1007/s11356-019-04876-x
• Xing, Z., & Liu, X. (2022). Health expenditures, environmental quality, and economic development: State-of-the-art review and findings in the context of COP26. Frontiers in Public Health, 10, 996473. https://doi.org/10.3389/fpubh.2022.954080
• Yacour, S., Soumbara, S. A., & El Ghini, A. (2023). Environmental quality, economic growth, and healthcare expenditure nexus for North Africa: A panel cointegration analysis. Environmental Modeling & Assessment, 1-15.
• Zaidi, S., & Saidi, K. (2018). Environmental pollution, health expenditure and economic growth in Sub-Saharan African countries: A panel ARDL approach. Sustainable Cities and Society, 41, 833-840. https://doi.org/10.1016/j.scs.2018.04.034
• Zeng, J., & He, Q. (2019). Does industrial air pollution drive health care expenditures? Spatial evidence from China. Journal of Cleaner Production, 218, 400–408. https://doi.org/ 10.1007/s11356-024-32342-w
• Zhang, C., & Zhang, L. (2024). The relationship between toxic air pollution, health expenditure, and economic growth in the European Union: Fresh evidence from the PMG-ARDL model. Environmental Science and Pollution Research, 31(14), 21107-21123. https://doi.org/10.1007/s11356-024-32342-w