Dergiler / Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2026 / Cilt: 16 Sayı: 31

YAŞLANAN NÜFUS VE SAĞLIK HARCAMALARININ ÇEVRESEL SÜRDÜRÜLEBİLİRLİK PERSPEKTİFİNDEN ANALİZİ: MEKÂNSAL BİR YAKLAŞIM

ANALYZING THE AGEING POPULATION AND HEALTHCARE EXPENDITURES FROM AN ENVIRONMENTAL SUSTAINABILITY PERSPECTIVE FOR THE EU COUNTRIES: A SPATIAL APPROACH

İbrahim Halil Polat(HAKKARİ ÜNİVERSİTESİ)0000-0001-9785-160X
Tunahan Aslan(VAN YÜZÜNCÜ YIL ÜNİVERSİTESİ)0000-0001-8958-699X
Sayfa
168–200
Yayın Tarihi
2025-06-27
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Bulgular, AB ülkeleri arasında mekânsal etkileşimler olduğunu göstermiştir.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Bu çalışmanın amacı, nüfus yaşlanması (AG), sağlık harcamaları (HE), kişi başına düşen GSYİH ve yenilenebilir enerji bütçelerinin (REB) çevre kalitesi (EQ) üzerindeki etkisini incelemektir.
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Temel Bulgular & Veri:Bu amaç doğrultusunda, 22 Avrupa Birliği (AB) ülkesinde 2005-2020 yılları arasındaki veriler mekânsal panel veri analizi ile incelenmiştir.
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Sonuç & Katkı:Bulgular, AB ülkeleri arasında mekânsal etkileşimler olduğunu göstermiştir.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:2005-2020 Verileri
⚙️Değişkenler:Sağlık harcamaları · Yaşlanan nüfus · çevresel sürdürülebilirlik

Özet

Bu çalışmanın amacı, nüfus yaşlanması (AG), sağlık harcamaları (HE), kişi başına düşen GSYİH ve yenilenebilir enerji bütçelerinin (REB) çevre kalitesi (EQ) üzerindeki etkisini incelemektir. Bu amaç doğrultusunda, 22 Avrupa Birliği (AB) ülkesinde 2005-2020 yılları arasındaki veriler mekânsal panel veri analizi ile incelenmiştir. Bulgular, AB ülkeleri arasında mekânsal etkileşimler olduğunu göstermiştir. Model belirleme testleri, sabit etkiler içeren panel mekânsal gecikme modelini desteklemiştir. Mekânsal etki katsayısı 0.53 olup, istatistiksel olarak anlamlıdır. AG ve REB, EQ üzerinde olumlu bir etkiye sahipken, HE ve kişi başına düşen GSYİH negatif etkiler göstermiştir. Sonuçlar, ekonomik, sosyal ve çevresel faktörler arasındaki karmaşık etkileşimleri ortaya koymuştur. Çalışma, AB ülkelerinin iklim hedeflerine ulaşmalarını desteklemek için politika önerileriyle sona ermektedir.

Abstract

The aim of this study is to analyze the impact of population aging (AG), healthcare expenditures (HE), per capita GDP, and renewable energy budgets (REB) on environmental quality (EQ). To achieve this, data from 22 European Union (EU) countries covering the period from 2005 to 2020 were examined using spatial panel data analysis. The findings indicate the presence of spatial interactions among EU countries. Model specification tests supported the spatial panel lag model with fixed effects. The spatial effect coefficient was found to be 0.53 and statistically significant. While AG and REB positively influenced EQ, HE and per capita GDP exhibited negative effects. The results highlight the complex interactions among economic, social, and environmental factors. The study concludes with policy recommendations aimed at supporting EU countries in achieving their climate goals.

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Bu Makaleye Atıf Yap

Polat, İ. H., Tosunoğlu, M., Aslan, T. (2025). YAŞLANAN NÜFUS VE SAĞLIK HARCAMALARININ ÇEVRESEL SÜRDÜRÜLEBİLİRLİK PERSPEKTİFİNDEN ANALİZİ: MEKÂNSAL BİR YAKLAŞIM. Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Cilt: 16 Sayı: 31, 168–200. https://doi.org/10.36543/kauiibfd.2025.007

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Kaynakça (91)

  1. Ahmad, M., Ahmed, Z., Gavurova, B., & Oláh, J. (2022). Financial risk, renewable energy technology budgets, and environmental sustainability: is going green possible?. Frontiers in Environmental Science, 10, 909190.
  2. Ahmad, M., Akram, W., Ikram, M., Shah, A. A., Rehman, A., Chandio, A. A., & Jabeen, G. (2021). Estimating dynamic interactive linkages among urban agglomeration, economic performance, carbon emissions, and health expenditures across developmental disparities. Sustainable Production and Consumption, 26, 239-255.
  3. Ahmed, Z., & Wang, Z. (2019). Investigating the impact of human capital on the ecological footprint in India: An empirical analysis. Environmental Science and Pollution Research, 26(26), 26782–26796.
  4. Ahmed, Z., Cary, M., Shahbaz, M., & Vo, X. V. (2021). Asymmetric nexus between economic policy uncertainty, renewable energy technology budgets, and environmental sustainability: Evidence from the United States. Journal of Cleaner Production, 313, 127723.
  5. Al Mustanyir, S. (2023). The role of government healthcare financing in carbon emissions and climate change. Sustainable Environment, 9(1), 2275690.
  6. Altıntaş, H., & Kassouri, Y. (2020). The impact of energy technology innovations on cleaner energy supply and carbon footprints in Europe: a linear andrsus nonlinear approach. Journal of Cleaner Production, 276, 124140.
  7. Anselin, L. (1988). Lagrange multiplier test diagnostics for spatial dependence and spatial heterogeneity. Geographical Analysis, 20(1), 1-17.
  8. Anselin, L. (2013). Spatial econometrics: methods and models (Vol. 4). Springer Science & Business Media.
  9. 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.
  10. Apergis, N., Gupta, R., Lau, C. K. M., & Mukherjee, Z. (2018). US state-level carbon dioxide emissions: does it affect health care expenditure?. Renewable and Sustainable Energy Reviews, 91, 521-530.
  11. Aslam, M., & Ahmad, E. (2018). Impact of ageing and generational effects on household energy consumption behavior: Evidence from Pakistan. Energies, 11(8), 2003.
  12. Aydın, Ş., Öztutuş, F., & Polat, İ. H. (2024). The Impact of Financial Development, Foreign Direct Investment and Geopolitical Risk on CO2 Emissions: Evidence from Turkey. Fiscaoeconomia, 8(3), 1617-1640.
  13. Aydin, M., & Bozatli, O. (2023). The impacts of the refugee population, renewable energy consumption, carbon emissions, and economic growth on health expenditure in Turkey: new evidence from Fourier-based analyses. Environmental Science and Pollution Research, 30(14), 41286-41298.
  14. Bilgili, F., Koçak, E., & Bulut, Ü. (2016). The dynamic impact of renewable energy consumption on CO2 emissions: a revisited Environmental Kuznets Curve approach. Renewable and Sustainable Energy Reviews, 54, 838-845.
  15. Bilgili, F., Kuşkaya, S., Khan, M., Awan, A., & 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.
  16. BP, 2023. British Petroleum statistical review of world energy. Available at https://www.bp.com/en/global/corporate/energy-economics.html. (Accessed: June 23, 2024)
  17. Burridge, P. (1981). Testing for a common factor in a spatial autoregression model. Environment and Planning A, 13(7), 795-800.
  18. Chaabouni, S., Zghidi, N., & Mbarek, M. B. (2016). On the causal dynamics between CO2 emissions, health expenditures and economic growth. Sustainable cities and society, 22, 184-191.
  19. Charfeddine, L., & Kahia, M. (2021). Do information and communication technology and renewable energy use matter for carbon dioxide emissions reduction? Evidence from the Middle East and North Africa region. Journal of Cleaner Production, 327, 129410.
  20. Chen, C., Pinar, M., & Stengos, T. (2022). Renewable energy and CO2 emissions: New evidence with the panel threshold model. Renewable Energy, 194, 117-128.
  21. Chu, L. K. (2024). The role of technological innovation and population aging in environmental degradation in the Organization for Economic Co-operation and Development countries. Environment, Development and Sustainability, 26(1), 735-773.
  22. CT, 2022. Climate Transparency. Available at https://www.climate-transparency.org/g20-climate-performance/g20report2022, (Accessed: June 23, 2024).
  23. Çetin, M. A. (2018). The Long Run Relationship between Health Expenditure and Renewable Energy Consumption in BRICS-T Countries: Panel ARDL Evidence. ICPESS 2018 PROCEEDINGS Volume 2: Economic Studies, 337.
  24. 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, 1-15.
  25. De Meijer, C., Wouterse, B., Polder, J., & Koopmanschap, M. (2013). The effect of population aging on health expenditure growth: a critical review. European journal of ageing, 10, 353-361.
  26. Dorbonova, İ., & Sugözü, İ. H. (2024). Analyzıng The Relatıonshıp Between Health Expendıture, Renewable Energy and Lıfe Expectancy: Evıdence From Asıan Countrıes. ESAM Ekonomik and Sosyal Araştırmalar Dergisi, 5(1), 111-134.
  27. Elhorst, J. P. (2012). Dynamic spatial panels: models, methods, and inferences. Journal of Geographical Systems, 14(1), 5-28.
  28. Ertürk, S., & Koç, S. (2023). The Transition of Fertility Rates in the World: Regime Switching Model. Karamanoğlu Mehmetbey Üniversitesi Sosyal ve Ekonomik Araştırmalar Dergisi, 25(45), 1324-1335.
  29. EU, 2023. Eurostat. Available at https://ec.europa.eu/eurostat/databrowser/explore/all/all_themes, (Accessed: June 17, 2024).
  30. F A, Lee R, Network, N. (2022) Six ways population change will affect the global economy. Popul Dev Rev 48(1):51–73
  31. Feldstein M (1988) The effects of fiscal policies when incomes are uncertain: a contradiction to Ricardian equivalence. America Economic Review, American Economic Association 78(1):14–23.
  32. Gündüz, M. (2020). Healthcare expenditure and carbon footprint in the USA: evidence from hidden cointegration approach. The European Journal of Health Economics, 21(5), 801-811.
  33. Hitiris T, Posnett J (1992) The determinants and effects of health expenditure in developed countries. J Health Econ, 11(2): 173–181.
  34. Jerrett M, Eyles J, Dufournaud C, & Birch S (2003) Environmental influences on healthcare expenditures: an exploratory analysis from Ontario, Canada. J Epidemiol Community Health, 57(5):334–338
  35. Jiang, L., Chen, X., Jiang, Y., & Zhang, B. (2023). Exploring the Direct and Spillover Effects of Aging on Green Total Factor Productivity in China: A Spatial Econometric Approach. Sustainability, 15(8), 6709.
  36. Karaaslan, A., & Çamkaya, S. (2022). The relationship between CO2 emissions, economic growth, health expenditure, and renewable and non-renewable energy consumption: Empirical evidence from Turkey. Renewable Energy, 190, 457-466.
  37. Karimi Alavijeh, N., Ahmadi Shadmehri, M.T., Dehdar, F., Zangoei, S., & Nazeer, N. (2023). The role of renewable energy on life expectancy: evidence from method of moments quantile regression based on G-7 countries data. International Journal of Energy Sector Management, Vol. ahead-of-print No. ahead-of-print. https:// doi.org/10.1108/IJESM-11-2022-0001.
  38. Kumar, P., & Radulescu, M. (2024). CO2 emission, life expectancy, and economic growth: a triad analysis of Sub-Saharan African countries. Environment, Development and Sustainability, 1-28.
  39. LeSage, J. P. (2008). An introduction to spatial econometrics. Revue d'économie industrielle, (123), 19-44. LeSage, J., & Pace, R. K. (2009). Introduction to spatial econometrics. Chapman and Hall/CRC.
  40. Li, F., Chang, T., Wang, M. C., & Zhou, J. (2022). The relationship between health expenditure, CO 2 emissions, and economic growth in the BRICS countries—based on the Fourier ARDL model. Environmental Science and Pollution Research, 1-20.
  41. Li, S., Wang, Q., & Li, R. (2024). How aging impacts environmental sustainability—insights from the effects of social consumption and labor supply. Humanities and Social Sciences Communications, 11(1), 1-16.
  42. Liddle, B. (2011). Consumption-drivenenvironmental impact and age structure change in OECD countries: A cointegration-STIRPAT analysis. Demographic Research, 24, 749-770.
  43. Lin, D., Hanscom, L., Martindill, J., Borucke, M., Cohen, L., Galli, A., & Wackernagel, M. (2018). Working guidebook to the national footprint accounts. Global Footprint Network.
  44. Meadows Donella, H., Meadows Dennis, L., & Randers Jorgen, B. W. W. (1972). The limits to growth. A Report for the Club of Rome's Project on the Predicament.
  45. Meng, F., Liu, G., Hu, Y., Su, M., & Yang, Z. (2018). From production to consumption: a multi-city comparativestudy of cross-regional carbon emissions. Energy Procedia, 152, 744-749.
  46. Menz, T., & Welsch, H. (2012). Population aging and carbon emissions in OECD countries: Accounting for life-cycle and cohort effects. Energy Economics, 34(3), 842-849.
  47. Metu, A., Kalu, C., Ezenekwe, U., & Maduka, O. (2018). Does greenhouse gas emission have any relevance to per capita health expenditure? Empirical evidence from Nigeria. African Journal of Sustainable Development, 7(3), 17-36.
  48. MS, 2023. Morgan Stanley. Available at https://www.morganstanley.com/ideas/economic-outlook-mid-year-2023-global-gdp-slowing, (Accessed: June 17, 2024).
  49. Muntean, M., Guizzardi, D., Schaaf, E., Crippa, M., Solazzo, E., Olivier, J., & Vignati, E. (2018). Fossil CO2 emissions of all world countries. Luxembourg: Publications Office of the European Union, 2.
  50. Narayan, P. K., & Narayan, S. (2008). Does environmental quality influence health expenditures? Empirical evidence from a panel of selected OECD countries. Ecological economics, 65(2), 367-374.
  51. Nathaniel, S. P. (2021). Ecological footprint, energy use, trade, and urbanization linkage in Indonesia. GeoJournal, 86(5), 2057-2070.
  52. Nawab, T., Muneza, C., & Afghan, M. (2021). Impact of renewable energy consumption and health expenditure on air pollutants: Implications for sustainable development in ASEAN countries. iRASD Journal of Energy & Environment, 2 (2), 78-89.
  53. OECD, 2024. Organisation for Economic Co-operation and Development. Available at https://www.oecd.org/, (Accessed: June 23, 2024).
  54. Pammolli, F., Riccaboni, M., & Magazzini, L. (2012). The sustainability of European health care systems: beyond income and aging. The European Journal of Health Economics, 13, 623-634.
  55. Pan, C., Wang, H., Guo, H., & Pan, H. (2021). How do the population structure changes of China affect carbon emissions? An empirical study based on ridge regression analysis. Sustainability, 13(6), 3319.
  56. Pascual-Saez, M., Cantarero-Prieto, D., & Manso, J. R. P. (2020). Does population ageing affect savings in Europe?. Journal of Policy Modeling, 42(2), 291-306.
  57. Polat, İ. H., Yapraklı, S., & Çamkaya, S. (2024). Impact of Nuclear and Renewable Energy on CO2 Emissions in OECD countries Under the STIRPAT model: Evidence from the CS-ARDL Model. International Journal of Contemporary Economics and Administrative Sciences, 14(1), 258-283.
  58. Qi, T., Zhang, X., & Karplus, V. J. (2014). The energy and CO2 emissions impact of renewable energy development in China. Energy Policy, 68, 60-69.
  59. Qureshi, M. I., Khan, N. U., Rasli, A. M., & Zaman, K. (2015). The battle of health with environmental evils of Asian countries: promises to keep. Environmental Science and Pollution Research, 22, 11708-11715.
  60. Sabău-Popa, C. D., Perțicaș, D. C., Florea, A., Rus, L., & Juma, H. W. (2024). Is Younger Population Generating Higher CO2 Emissions? A Dynamic Panel Analysis on European Countries. Sustainability, 16(17), 7791.
  61. Shahnazi, R., & Shabani, Z. D. (2021). The effects of renewable energy, spatial spillover of CO2 emissions and economic freedom on CO2 emissions in the EU. Renewable Energy, 169, 293-307.
  62. Shi, Z., Wu, L., & Zhou, Y. (2023). Predicting household energy consumption in an aging society. Applied Energy, 352, 121899.
  63. Siti Khalijah, Z. (2015). The impact of environmental quality on public health expenditure in Malaysia. Universiti Utara, Malaysia.
  64. Sui, B., Sharma, S. S., Yao, L. Y., Ni, G. H., & Chang, C. P. (2024). Does aging affect renewable energy? The role of extreme events and economic development. Energy Economics, 133, 107491.
  65. Tobler, W. R. (1970). A computer movie simulating urban growth in the detroit region. Economic Geography, 46(sup1), 234-240.
  66. Tosunoğlu, M. (2024). The Relationship between Technological Innovation and Economic Growth in EU Countries: A System GMM Approach. Verimlilik Dergisi, 58(4), 651-662.
  67. Tosunoğlu, M., & Uçal, H. THE RELATIONSHIP BETWEEN ENERGY CONSUMPTION AND ECONOMIC GROWTH: COINTEGRATION AND CAUSALITY APPROACHES. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (67), 177-193.
  68. Triki, R., Kahouli, B., Tissaoui, K., & Tlili, H. (2023). Assessing the link between environmental quality, green finance, health expenditure, renewable energy, and technology innovation. Sustainability, 15 (5), 4286.
  69. 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. The International journal of health planning and management, 35(4), 818-831.
  70. UN, 2024. United Nations. Available at https://unstats.un.org/sdgs/report/2024/, (Accessed: June 23, 2024). uz Zaman, Q., Wang, Z., Zaman, S., & Rasool, S. F. (2021). Investigating the nexus between education expenditure, female employers, renewable energy consumption and CO2 emission: evidence from China. Journal of Cleaner Production, 312, 127824.
  71. Van de Kaa, D. J. (1999). Europe and its population: the long view. In European populations: Unity in diversity (pp. 1-49). Dordrecht: Springer Netherlands.
  72. Vangerven, P., & Crombez, C. (2012). Spatial models of European Union politics. KU Leuven-Faculty of Business and Economics Research Paper No. OR1225.
  73. Wang, J., & Azam, W. (2024). Natural resource scarcity, fossil fuel energy consumption, and total greenhouse gas emissions in top emitting countries. Geoscience Frontiers, 15(2), 101757.
  74. Wang, Q., Li, L., & Li, R. (2023). Uncovering the impact of income inequality and population aging on carbon emission efficiency: an empirical analysis of 139 countries. Science of The Total Environment, 857, 159508.
  75. Watts, N., Adger, W. N., Agnolucci, P., Blackstock, J., Byass, P., Cai, W., & Costello, A. (2015). Health and climate change: policy responses to protect public health. The lancet, 386(10006), 1861-1914.
  76. WDI, 2024. World Devleopment Indicators. Available at https://databank.worldbank.org/source/world-development-indicators. (Accessed: June 23, 2024)
  77. WHO, Health, The Green Economy, 2015. http://www.who.int/hia/green_ economy/en/index.html Wu, R. (2019). The carbon footprint of the Chinese health-care system: an environmentally extended input–output and structural path analysis study. The Lancet Planetary Health, 3(10), e413-e419.
  78. Xue, Q. (2022). Increasing commitment to the sustainable development goals across universities worldwide. Sustainable Horizons, 2, 100021.
  79. Yadav, M., Aneja, R., & Ahmed, W. (2023). Do clean energy transition, environment degradation, and energy efficiency influence health expenditure: empirical evidence from emerging countries. Journal of Cleaner Production, 428, 139355.
  80. Yahaya, A., Nor, N. M., Habibullah, M. S., Ghani, J. A., & Noor, Z. M. (2016). How relevant is environmental quality to per capita health expenditures? Empirical evidence from panel of developing countries. SpringerPlus, 5, 1-14.
  81. Yang, T., & Wang, Q. (2020). The nonlinear effect of population aging on carbon emission-Empirical analysis of ten selected provinces in China. Science of the Total Environment, 740, 140057.
  82. Yang, X., Li, N., Mu, H., Ahmad, M., & Meng, X. (2022). Population aging, renewable energy budgets and environmental sustainability: does health expenditures matter?. Gondwana Research, 106, 303-314.
  83. Yang, X., Li, N., Mu, H., Pang, J., Zhao, H., & 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.
  84. Yang, Y., Zhao, T., Wang, Y., & Shi, Z. (2015). Research on impacts of population-related factors on carbon emissions in Beijing from 1984 to 2012. Environmental Impact Assessment Review, 55, 45-53.
  85. York, R. (2007). Demographic trends and energy consumption in European Union Nations, 1960–2025. Social science research, 36(3), 855-872.
  86. Yu, M., Meng, B., & Li, R. (2022). Analysis of China's urban household indirect carbon emissions driandrs under the background of population aging. Structural change and economic dynamics, 60, 114-125.
  87. Yu, Y., Deng, Y. R., & Chen, F. F. (2018). Impact of population aging and industrial structure on CO2 emissions and emissions trend prediction in China. Atmospheric Pollution Research, 9(3), 446-454.
  88. Zaidi, S., & 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.
  89. Zhang, C., & Tan, Z. (2016). The relationships between population factors and China's carbon emissions: does population aging matter?. Renewable and Sustainable Energy Reviews, 65, 1018-1025.
  90. Zheng, H., Long, Y., Wood, R., Moran, D., Zhang, Z., Meng, J., & Guan, D. (2022). Ageing society in developed countries challenges carbon mitigation. Nature Climate Change, 12(3), 241-248.
  91. Zweifel, P., Felder, S., & Meiers, M. (1999). Ageing of population and health care expenditure: a red herring?. Health economics, 8(6), 485-496.