The Impact of Climatic and Environmental Factors on the Frequency of Natural Disasters in the Insurance Sector in G7 Countries

Öz

In this study, the effects of temperature, precipitation, greenhouse gas emissions and load capacity factor (LCF), which is one of the environmental sustainability indices, on the frequency of natural disasters occurring in G7 countries between 1989-2022 were evaluated by panel data analysis method. The findings obtained show that increasing greenhouse gas emissions, precipitation and temperature due to climate change increase the number of natural disasters, while the decrease in the LCF factor increases the number of natural disasters. While Pedroni and Kao cointegration tests reveal the existence of a long-term relationship between the variables, the Panel Error Correction Model (ECM) results corrected with Driscoll-Kraay standard errors show that greenhouse gas emissions and the LCF factor, which seem to be ineffective in the short term, become determinants of the frequency of natural disasters in the long term. The increasing frequency and severity of natural disasters due to the impact of climate change and environmental factors reveal that insurance systems are an important risk management tool against such events. In the context of G7 countries, it is suggested that regulatory frameworks should be strengthened, public-private partnerships should be increased and advanced risk modeling techniques should be adopted to ensure the adaptation of the insurance sector to climate change. This study contributes to the literature by using LCF as an innovative factor in examining disaster dynamics and by presenting suggestions for the development of long-term risk management policies for the insurance sector.

Anahtar Kelimeler

• Natural Disaster Frequency
• Load Capacity Factor
• Temperature
• Rainfall
• Climate Change
• Insurance

G7 Ülkelerinde İklimsel ve Çevresel Faktörlerin Doğal Afetlerin Meydana Gelme Sıklığı Üzerindeki Etkisinin Sigortacılık Sektörüne Yansımaları

Öz

Bu çalışmada, 1989-2022 yılları arasında G7 ülkelerinde meydana gelen doğal afetlerin sıklığı üzerinde, sıcaklık, yağış, sera gazı emisyonları ve çevresel sürdürülebilirlik endekslerinden olan yük kapasite faktörünün (LCF) etkileri panel veri analizi yöntemiyle değerlendirilmiştir. Elde edilen bulgular, iklim değişikliği sebebiyle artan seragazı emisyonları, yağış ve sıcaklık miktarının doğal afet sayısını artırdığı, LCF faktörünün azalması ise meydana gelen doğal afet sayısını artırdığı gözlemlenmiştir. Pedroni ve Kao eşbütünleşme testleri, değişkenler arasında uzun vadeli bir ilişkinin varlığını ortaya koyarken, Driscoll-Kraay standart hatalarıyla düzeltilmiş Panel Hata Düzeltme Modeli (ECM) sonuçları, kısa vadede etkisiz gibi görünen sera gazı emisyonları ve LCF faktörünün uzun vadede doğal afet sıklığı üzerinde belirleyici hale geldiğini göstermektedir. İklim değişikliği ve çevresel faktörlerin etkisiyle artan doğal afet sıklığı ve şiddeti, sigorta sistemlerinin bu tür olaylar karşısında önemli bir risk yönetim aracı olduğunu ortaya koymaktadır. G7 ülkeleri bağlamında, sigorta sektörünün iklim değişikliğine adaptasyonunu sağlamak için düzenleyici çerçevelerin güçlendirilmesi, kamu-özel iş birliklerinin artırılması ve gelişmiş risk modelleme tekniklerinin benimsenmesi önerilmektedir. Bu çalışma, afet dinamiklerinin incelenmesinde yenilikçi bir faktör olarak LCF kullanımı ve sigortacılık sektörüne yönelik uzun vadeli risk yönetimi politikalarının geliştirilmesine yönelik öneriler sunarak literatüre katkı sağlamaktadır.

Anahtar Kelimeler

• Doğal Afet Sıklığı
• Yük Kapasite Faktörü
• Sıcaklık
• Yağış
• İklim Değişikliği
• Sigorta

Kaynakça

1. Alkan, G. (2019). İklim değişikliğinin katastrofik riskler üzerinde yarattığı etkilerin incelenmesi [Yüksek lisans tezi, Marmara Üniversitesi]. YÖK Ulusal Tez Merkezi. https://tez.yok.gov.tr/UlusalTezMerkezi
2. Baltagi, B. H. (2008). Econometric analysis of panel data (4. basım). John Wiley & Sons.
3. Birkmann, J., Cutter, S. L., Rothman, D. S., Welle, T., Garschagen, M., Van Ruijven, B., ... & Pulwarty, R. (2015). Scenarios for vulnerability: Opportunities and constraints in the context of climate change and disaster risk. Climatic Change, 133, 53–68.
4. Botzen, W. W., Deschenes, O., & Sanders, M. (2019). The economic impacts of natural disasters: A review of models and empirical studies. Review of Environmental Economics and Policy, 13(2), 167–341.
5. Browne, M. J., Hoyt, R. E., & Marais, J. C. (2022). A reexamination of excess returns and the underwriting cycle in the property-liability insurance market. https://www.fox.temple.edu/sites/fox/files/documents/Cummins%20Conference%202022/xs_returns_ uw_cycle_0328-paper.pdf
6. Carbon Dioxide Information Analysis Center. (2004). Global fossil carbon emissions. https://cdiac.ess-dive.lbl.gov/ Centre for Research on the Epidemiology of Disasters. (2025). Emergency Events Database (EM-DAT). https://www.emdat.be/
7. Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460.
8. Emanuel, K. (2005). Increasing destructiveness of tropical cyclones over the past 30 years. Nature, 436(7051), 686–688.

9. Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276.
10. Ferreira, S. (2024). Extreme weather events and climate change: Economic impacts and adaptation policies. Annual Review of Resource Economics, 16, 207–231.
11. Giuzio, M., Kapadia, S., Kumar, H., Mazzotta, L., Parker, M., Rousová, L., & Zafeiris, D. (2024). Climate change, catastrophes, uninsurability and the macroeconomy. https://www.comp-net.org/fileadmin/_compnet/user_upload/Finpro_4/Protection_gap__ 1___1__-_Linda_Rousova__2_.pdf
12. Global Footprint Network. (2022). National footprint accounts, ecological footprint. California, United States. https://data.footprintnetwork.org/
13. Herring, S. C., Christidis, N., Hoell, A., Hoerling, M. P., & Stott, P. A. (2021). Explaining extreme events of 2019 from a climate perspective. Bulletin of the American Meteorological Society, 102(1), 1–115.
14. Hsiao, C. (2014). Analysis of panel data. Cambridge University Press.
15. Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74.
16. Intergovernmental Panel on Climate Change. (2021). Climate change 2021: The physical science basis. Cambridge University Press. https://doi.org/10.1017/9781009157896
17. Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 90(1), 1–44.
18. Kossin, J. P., Knapp, K. R., Olander, T. L., & Velden, C. S. (2020). Global increase in major tropical cyclone exceedance probability over the past four decades. Proceedings of the National Academy of Sciences, 117(22), 11975–11980.
19. Kousky, C. (2017). Disasters as learning experiences or disasters as policy opportunities? Examining flood insurance purchases after hurricanes. Risk Analysis, 37(3), 517–530.
20. Kunreuther, H. C., Pauly, M. V., & McMorrow, S. (2013). Insurance and behavioral economics: Improving decisions in the most misunderstood industry. Cambridge University Press.
21. Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., ... & Sherstyukov, B. (2014). Flood risk and climate change: Global and regional perspectives. Hydrological Sciences Journal, 59(1), 1–28.
22. Kundzewicz, Z. W., Krysanova, V., Benestad, R. E., Hov, Ø., Piniewski, M., & Otto, I. M. (2018). Uncertainty in climate change impacts on water resources. Environmental Science & Policy, 79, 1–8.
23. Linnerooth-Bayer, J., & Hochrainer-Stigler, S. (2015). Financial instruments for disaster risk management and climate change adaptation. Climatic Change, 133, 85–100.
24. Mechler, R., & Bouwer, L. M. (2015). Understanding trends and projections of disaster losses and climate change: Is vulnerability the missing link? Climatic Change, 133(1), 23–35.
25. Michel-Kerjan, E. O., & Kousky, C. (2010). Come rain or shine: Evidence on flood insurance purchases in Florida. Journal of Risk and Insurance, 77(2), 369–397.
26. Nguyen, H., Feng, A., & Garcia-Escribano, M. M. (2025). Understanding the macroeconomic effects of natural disasters (WP/25/46). International Monetary Fund.
27. Nordhaus, W. D. (2010). The economics of hurricanes and implications of global warming. Climate Change Economics, 1(1), 1–20.
28. Nordhaus, W. D. (2013). The climate casino: Risk, uncertainty, and economics for a warming world. Yale University Press.
29. 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. European Journal of Health Economics, 22(9), 1427–1439.
30. Pata, U. K., & Samour, A. (2023). Assessing the role of the insurance market and renewable energy in the load capacity factor of OECD countries. Environmental Science and Pollution Research, 30(16), 48604–48616.
31. Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics, 61(S1), 653–670.
32. Shang, Y., Razzaq, A., Chupradit, S., An, N. B., & Abdul-Samad, Z. (2022). The role of renewable energy consumption and health expenditures in improving load capacity factor in ASEAN countries: Exploring new paradigms using advanced panel models. Renewable Energy, 191, 715–722. https://doi.org/10.1016/j.renene.2022.04.013
33. Siche, R., Pereira, L., Agostinho, F., & 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.
34. Singh, A., & Madaan, G. (2023). Sustainable climate change and its impact on the insurance sector. In K. Sood, S. Grima, P. Young, E. Ozen, & B. Balusamy (Eds.), The impact of climate change and sustainability standards on the insurance market (pp. 143–163). Wiley.
35. Stern, N. (2008). The economics of climate change. American Economic Review, 98(2), 1–37.
36. Surminski, S., & Oramas-Dorta, D. (2014). Flood insurance schemes and climate adaptation in developing countries. International Journal of Disaster Risk Reduction, 7, 154–164.
37. Tol, R. S. (2002). Estimates of the damage costs of climate change. Part 1: Benchmark estimates. Environmental and Resource Economics, 21, 47–73.
38. Torusdag, T., Tepeci, M., & Metin, İ. (2024). İklim değişikliğinin sigorta sektörü üzerindeki etkileri: Türkiye örneği. Doğal Afetler ve Çevre Dergisi, 10(2), 409–423.
39. Von Peter, G., von Dahlen, S., & Saxena, S. (2024). Unmitigated disasters? Risk sharing and macroeconomic recovery in a large international panel. Journal of International Economics, 149, Article 103920. https://doi.org/10.1016/j.jinteco.2024.103920
40. World Bank. (2024). Climate change knowledge portal: Historical precipitation and temperature data. 3 Ekim 2024’te https://climateknowledgeportal.worldbank.org/ adresinden alındı.
41. Yılmaz, Z. (2009). İklim değişikliği risklerinin sigorta sektörüne etkileri açısından incelenmesi [Yüksek lisans tezi, Marmara Üniversitesi]. YÖK Ulusal Tez Merkezi. https://tez.yok.gov.tr/UlusalTezMerkezi