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Agricultural insurance and natural disasters: an assessment of the financial performance of the Turkish agricultural insurance pool (TARSIM) through selected criteria

Yıl 2023, Cilt: 5 Sayı: 2, 126 - 136, 30.12.2023
https://doi.org/10.58588/aru-jfeas.1393228

Öz

Agriculture is closely linked to weather and climatic conditions, rendering it vulnerable to the impact of natural disasters. While such risks are inherent in agricultural activities, the escalation in both frequency and severity of these disasters in recent years can be attributed to the interplay of climate change, global warming, and ecological degradation. In this context, agricultural insurances offer financial assistance to farmers by extending insurance coverage to mitigate potential production failures stemming from these hazards. In Turkey, the insurances included in the Agricultural Insurance Pool (TARSIM) range from crop, greenhouse, and poultry, to drought yield insurances. In this study, the financial performance of TARSIM during the period 2018-2022 has been evaluated by using Criteria Importance Through Intercriteria Correlation (CRITIC) objective criteria weighting with Evaluation based on Distance from Average Solution (EDAS) and Multi-Atributive Ideal-Real Comparative Analysis (MAIRCA) multi-criteria decision-making (MCDM) techniques. The analyses included seven financial ratios based on eight indicators, and as a result, the criterion with the highest weight was determined as the Total Premiums Received-Equity ratio, and by considering all utilized methods, the first two years with the best financial performance was identified as 2018 and 2019.

Kaynakça

  • Akbari, M. (2022). Measuring social sustainable development in Iranian metropolises using EDAS and MAIRCA technique. Geography and Planning, 26(79), 59-39. https://doi.org/10.22034/GP.2021.44916.2802
  • Aksoy, E. (2021). An analysis on Turkey's merger and acquisition activities: MAIRCA method. Gümüşhane Üniversitesi Sosyal Bilimler Dergisi, 12(1), 1-11. https://doi.org/10.36362/gumus.832590
  • Akyüz, G., Tosun, Ö. ve Aka, S. (2020). Performance evaluation of non-life insurance companies with best-worst method and TOPSIS. Uluslararası Yönetim İktisat ve İşletme Dergisi, 16(1), 108-125. https://doi.org/10.17130/ijmeb.700907
  • Akyüz, Y., & Kaya, Z. (2013). Türkiye'de hayat dışı ve hayat/emeklilik sigorta sektörünün finansal performans analiz ve değerlendirilmesi. Sosyal Ekonomik Araştırmalar Dergisi, 13(26), 355-371.
  • Alam, A. F., Begum, H., Masud, M. M., Al-Amin, A. Q., & Leal Filho, W. (2020). Agriculture insurance for disaster risk reduction: A case study of Malaysia. International Journal of Disaster Risk Reduction, 47, 101626. https://doi.org/10.1016/j.ijdrr.2020.101626
  • Alenjagh, R. S. (2013). Performance evaluation and ranking of insurance companies in Tehran stock exchange by financial ratios using ANP and PROMETHEE. European Online Journal of Natural and Social Sciences, 2(3), 3478-3486.
  • Bączkiewicz, A., Kizielewicz, B., Shekhovtsov, A., Wątróbski, J., & Sałabun, W. (2021). Methodical aspects of MCDM based E-commerce recommender system. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2192-2229. https://doi.org/10.3390/jtaer16060122
  • Badi, I., & Ballem, M. (2018). Supplier selection using the rough BWM-MAIRCA model: A case study in pharmaceutical supplying in Libya. Decision Making: Applications in Management and Engineering, 1(2), 16-33. https://doi.org/10.31181/dmame1802016b
  • Baldwin, K., Williams, B., Tsiboe, F., Effland, A., Turner, D., Pratt, B., … Hodges, L. (2023). US Agricultural policy review 2021. Washington DC.
  • Bao, X., Zhang, F., Deng, X., & Xu, D. (2021). Can trust motivate farmers to purchase natural disaster insurance? Evidence from earthquake-stricken areas of Sichuan, China. Agriculture, 11(8), 783. https://doi.org/10.3390/agriculture11080783
  • Berk, A., & Uçak, H. (2010). Development and structural changes in Turkish agricultural insurance policy. Acta Scientiarum Polonorum Oeconomia, 9(1), 5-14.
  • Bilbao Terol, A., Arenas Parra, M., Quiroga García, R., & Bilbao Terol, C. (2022). An extended best–worst multiple reference point method: Application in the assessment of non-life insurance companies. Operational Research, 22(5), 5323-5362. https://doi.org/10.1007/s12351-022-00731-z
  • Bülbül, S. E., & Köse, A. (2016). Türk sigorta sektörünün PROMETHEE yöntemi ile finansal performans analizi. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 38(1), 187-210. https://doi.org/10.14780/iibd.29194
  • Chatterjee, K., Pamucar, D., & Zavadskas, E. K. (2018). Evaluating the performance of suppliers based on using the R'AMATEL-MAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production, 184, 101-129. https://doi.org/10.1016/j.jclepro.2018.02.186
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Tarım sigortaları ve doğal afetler: Türk tarım sigortaları havuzu (TARSİM) finansal performansının seçili kriterler dâhilinde değerlendirilmesi

Yıl 2023, Cilt: 5 Sayı: 2, 126 - 136, 30.12.2023
https://doi.org/10.58588/aru-jfeas.1393228

Öz

Tarım, hava ve iklim koşullarına sıkı bir şekilde bağlı olması nedeniyle doğal afetlerin etkisine karşı savunmasızdır. Bu tür riskler tarımsal faaliyetlere içkin olsa da, son yıllarda bu felaketlerin hem sıklığında hem de şiddetinde yaşanan artışın, iklim değişikliği, küresel ısınma ve ekolojik bozulma arasındaki etkileşimle ilgili olduğu söylenebilir. Bu bağlamda, tarım sigortaları, çeşitli risklerden kaynaklanan potansiyel üretim başarısızlıklarını hafifletmek için tarım sektöründe çalışanlara finansal yardım sunarak potansiyel verim kayıplarına karşı güvence sağlamaktadır. Türkiye'de geleneksel tarım sigortasının kökleri 1957'ye kadar uzanmakta olup, 2005 yılında Tarım Sigortaları Havuzu’nun (TARSİM) kurulmasıyla önemli bir gelişme yaşanmıştır. Sigorta çeşitleri, bitkisel ürün, sera ve kümes hayvanlarından kuraklık verim sigortalarına kadar uzanmaktadır. Finansal performans değerlendirmelerinin sorunları tespit etmek ve yenilikçi stratejiler geliştirmek amacıyla kullanılmasına paralel olarak bu çalışmada, TARSİM'ın 2018-2022 dönemindeki finansal performansı, CRITIC objektif kriter ağırlıklandırma ile EDAS ve MAIRCA Çok Kriterli Karar Verme (ÇKKV) teknikleri kullanılarak değerlendirilmiştir. Model, bilançolar ve gelir tablolarından elde edilen sekiz göstergeye dayalı yedi finansal oran içermekte olup, elde edilen sonuçlara göre, en yüksek ağırlığa sahip kriterin Alınan Prim-Öz Sermaye oranı; ele alınan dönem dahilinde en iyi finansal performansa sahip ilk iki yılın ise 2018 ve 2019 yılları olduğu tespit edilmiştir.

Kaynakça

  • Akbari, M. (2022). Measuring social sustainable development in Iranian metropolises using EDAS and MAIRCA technique. Geography and Planning, 26(79), 59-39. https://doi.org/10.22034/GP.2021.44916.2802
  • Aksoy, E. (2021). An analysis on Turkey's merger and acquisition activities: MAIRCA method. Gümüşhane Üniversitesi Sosyal Bilimler Dergisi, 12(1), 1-11. https://doi.org/10.36362/gumus.832590
  • Akyüz, G., Tosun, Ö. ve Aka, S. (2020). Performance evaluation of non-life insurance companies with best-worst method and TOPSIS. Uluslararası Yönetim İktisat ve İşletme Dergisi, 16(1), 108-125. https://doi.org/10.17130/ijmeb.700907
  • Akyüz, Y., & Kaya, Z. (2013). Türkiye'de hayat dışı ve hayat/emeklilik sigorta sektörünün finansal performans analiz ve değerlendirilmesi. Sosyal Ekonomik Araştırmalar Dergisi, 13(26), 355-371.
  • Alam, A. F., Begum, H., Masud, M. M., Al-Amin, A. Q., & Leal Filho, W. (2020). Agriculture insurance for disaster risk reduction: A case study of Malaysia. International Journal of Disaster Risk Reduction, 47, 101626. https://doi.org/10.1016/j.ijdrr.2020.101626
  • Alenjagh, R. S. (2013). Performance evaluation and ranking of insurance companies in Tehran stock exchange by financial ratios using ANP and PROMETHEE. European Online Journal of Natural and Social Sciences, 2(3), 3478-3486.
  • Bączkiewicz, A., Kizielewicz, B., Shekhovtsov, A., Wątróbski, J., & Sałabun, W. (2021). Methodical aspects of MCDM based E-commerce recommender system. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2192-2229. https://doi.org/10.3390/jtaer16060122
  • Badi, I., & Ballem, M. (2018). Supplier selection using the rough BWM-MAIRCA model: A case study in pharmaceutical supplying in Libya. Decision Making: Applications in Management and Engineering, 1(2), 16-33. https://doi.org/10.31181/dmame1802016b
  • Baldwin, K., Williams, B., Tsiboe, F., Effland, A., Turner, D., Pratt, B., … Hodges, L. (2023). US Agricultural policy review 2021. Washington DC.
  • Bao, X., Zhang, F., Deng, X., & Xu, D. (2021). Can trust motivate farmers to purchase natural disaster insurance? Evidence from earthquake-stricken areas of Sichuan, China. Agriculture, 11(8), 783. https://doi.org/10.3390/agriculture11080783
  • Berk, A., & Uçak, H. (2010). Development and structural changes in Turkish agricultural insurance policy. Acta Scientiarum Polonorum Oeconomia, 9(1), 5-14.
  • Bilbao Terol, A., Arenas Parra, M., Quiroga García, R., & Bilbao Terol, C. (2022). An extended best–worst multiple reference point method: Application in the assessment of non-life insurance companies. Operational Research, 22(5), 5323-5362. https://doi.org/10.1007/s12351-022-00731-z
  • Bülbül, S. E., & Köse, A. (2016). Türk sigorta sektörünün PROMETHEE yöntemi ile finansal performans analizi. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 38(1), 187-210. https://doi.org/10.14780/iibd.29194
  • Chatterjee, K., Pamucar, D., & Zavadskas, E. K. (2018). Evaluating the performance of suppliers based on using the R'AMATEL-MAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production, 184, 101-129. https://doi.org/10.1016/j.jclepro.2018.02.186
  • Chatterjee, P., Mandal, N., Dhar, S., Chatterjee, S., & Chakraborty, S. (2020). A novel decision-making approach for light weight environment friendly material selection. Materials Today: Proceedings, 22, 1460-1469. https://doi.org/10.1016/j.matpr.2020.01.504
  • Chen, R., & Wong, K. A. (2004). The determinants of financial health of Asian insurance companies. Journal of Risk and Insurance, 71(3), 469-499. https://doi.org/10.1111/j.0022-4367.2004.00099.x
  • Çakır, S. (2016). Türk sigortacılık sektöründe çok kriterli karar verme teknikleri (ÇKKV) ile performans ölçümü: BİST uygulaması. Çukurova Üniversitesi İİBF Dergisi, 20(1), 127-147.
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  • Günay, F., & Ecer, F. (2022). A comparative analysis of the real sector in Turkey from the economic and financial perspectives with the CRITIC-MAIRCA method, Ekonomi Politika ve Finans Araştırmaları Dergisi, 7(1), 186-219. https://doi.org/10.30784/epfad.1065471
  • Haq, R. S. U., Saeed, M., Mateen, N., Siddiqui, F., & Ahmed, S. (2023). An interval-valued neutrosophic based MAIRCA method for sustainable material selection. Engineering Applications of Artificial Intelligence, 123, 106177. https://doi.org/10.1016/j.engappai.2023.106177
  • Hao, M., Lu, C., Zhou, X., & Xu, J. (2023). How agricultural farmers respond to risks during the COVID-19 pandemic: An exploration through the dual social capitals approach. Agriculture, 13(2), 485. https://doi.org/10.3390/agriculture13020485
  • Hezam, I. M., Vedala, N. R. D., Kumar, B. R., Mishra, A. R., & Cavallaro, F. (2023). Assessment of biofuel industry sustainability factors based on the intuitionistic fuzzy symmetry point of criterion and rank-sum-based MAIRCA method. Sustainability, 15(8), 6749. https://doi.org/10.3390/su15086749
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  • Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria ınventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3), 435-451. http://dx.doi.org/10.15388/Informatica.2015.57
  • Kostyuchenko, T. N., Sidorova, D. V., Eremenko, N. V., & Chernikova, L. I. (2015). Insurance as a tool for managing risks in agriculture. Mediterranean Journal of Social Sciences, 6(5), 220.
  • Köse, A. ve Dikme, B. (2021). Türk sigorta sektöründe hayat dışı branşlarda faaliyet gösteren şirketlerin performanslarının değerlendirilmesi. Finansal Araştırmalar ve Çalışmalar Dergisi, 13(24), 171-188. https://doi.org/10.14784/marufacd.880627
  • Ksenija, M., Boris, D., Snežana, K., & Sladjana, B. (2017). Analysis of the efficiency of insurance companies in Serbia using the fuzzy AHP and TOPSIS methods. Economic Research-Ekonomska Istraživanja, 30(1), 550-565. http://dx.doi.org/10.1080/1331677X.2017.1305786
  • Mahul, O., & Stutley, C. J. (2010). Government Support to Agricultural Insurance: Challenges and Options for Developing Countries. World Bank Publications. https://elibrary.worldbank.org/doi/abs/10.1596/978-0-8213-8217-2
  • Ministry of Treasury and Finance (2015). Regulation on the measurement and evaluation of the capital adequacy of insurance and reinsurance companies and pension companies. https://egm.org.tr/Sites/1/upload/files/Sigorta-Ve-Reasurans-Ile-Emeklilik-Sirketlerinin-Sermaye-Yeterliliklerinin-Olculmesine-Ve-Degerlendirilmesine-Iliskin-Yonetmelik-2252.pdf
  • Narayanamoorthy, S., Brainy, J. V., Shalwala, R. A., Alsenani, T. R., Ahmadian, A., & Kang, D. (2023). An enhanced fuzzy decision-making approach for the assessment of sustainable energy storage systems. Sustainable Energy, Grids and Networks, 33, 100962. https://doi.org/10.1016/j.segan.2022.100962
  • Odu, G. O. (2019). Weighting methods for multi-criteria decision-making technique. Journal of Applied Sciences and Environmental Management, 23(8), 1449-1457. https://doi.org/10.4314/jasem.v23i8.7
  • OECD/FAO. (2020). OECD-FAO agricultural outlook 2020-2029. https://doi.org/10.1787/1112c23b-en: OECD.
  • Oguz, C., & Diyanah, S. M. (2021). Farmers’ perceptions of agricultural ınsurance: a case study of Altınekin district, Konya, Turkey. OP Conference Series: Earth and Environmental Science, 803(1), 1-9, https://doi.org/10.1088/1755-1315/803/1/012052.
  • Özmen, M., & Aydoğan, E. K. (2020). Robust multi-criteria decision-making methodology for real life logistics center location problem. Artificial Intelligence Review, 53, 725-751. https://doi.org/10.1007/s10462-019-09763-y
  • Özsayın, D. (2017). An evaluation of livestock (cattle) ınsurance in Turkey. Agriculture & Food, 5, 517-523.
  • Pamučar, D., Vasin, L., & Lukovac, L. (2014). Selection of railway level crossings for investing in security equipment selection of railway level crossings for investing in security equipment using hybrid DEMATEL-MARICA model, Proceedings of the XVI International Scientific-Expert Conference on Railway RAILCON, 9-10 Ekim 2014, Niš, Serbia, 89-92.
  • Pehlivan, E., & Akpınar, Ö. (2022). Çok kriterli karar verme teknikleri ile TARSİM özelinde bir uygulama. Başkent Üniversitesi Ticari Bilimler Fakültesi Dergisi, 6(2), 132-151.
  • Peng, D., Wang, J., Liu, D., & Liu, Z. (2022). An improved EDAS method for the multi-attribute decision making based on the dynamic expectation level of decision makers. Symmetry, 14(5), 979. https://doi.org/10.3390/sym14050979
  • Perçin, S., & Sönmez, Ö. (2018). Bütünleşik entropi ağırlık ve TOPSIS yöntemleri kullanılarak Türk sigorta şirketlerinin performansının ölçülmesi. Uluslararası İktisadi ve İdari İncelemeler Dergisi, (18. EYİ Özel Sayısı), 565-582. https://doi.org/10.18092/ulikidince.347924
  • Prasada, D. V. (2020). Performance and potential of agricultural insurance: Global and Sri Lankan perspectives. In B. Marambe, J. Weerahewa & W. Dandeniya (Eds), Agricultural research for sustainable food systems in Sri Lanka (pp. 369-389). Springer. https://doi.org/10.1007/978-981-15-2152-2
  • Puška, A., Lukić, M., Božanić, D., Nedeljković, M., & Hezam, I. M. (2023). Selection of an insurance company in agriculture through hybrid multi-criteria decision-making. Entropy, 25(6), 959. https://doi.org/10.3390/e25060959
  • Qahtan, S. A., Zaidan, A. A., Deveci, M., Pamucar, D., Delen, D., & Pedrycz, W. (2023). Evaluation of agriculture-food 4.0 supply chain approaches using fermatean probabilistic hesitant-fuzzy sets-based decision-making model. Applied Soft Computing, 138, 110170. https://doi.org/10.1016/j.asoc.2023.110170
  • Rahmati, S., & Darestani, S. A. (2022). Performance evaluation of insurance sector using balanced scorecard and hybrid BWM-TOPSIS: evidence from Iran. International Journal of Productivity and Quality Management, 36(3), 382-402. https://doi.org/10.1504/IJPQM.2022.124729
  • Smith, V. H., & Glauber, J. W. (2012). Agricultural insurance in developed countries: where have we been and where are we going? Applied Economic Perspectives and Policy, 34(3), 363-390. https://doi.org/10.1093/aepp/pps029
  • Sogue, B., & Akcaoz, H. (2017). Risk management in agriculture: examples from some countries. Tarım Ekonomisi Dergisi, 23(1), 69-83, https://doi.org/10.24181/tarekoder.325621.
  • TARSIM. (2022). Annual Report 2022. https://www.tarsim.gov.tr/staticweb/krm-web/dergi/faaliyet-raporlari/2022_1.pdf
  • TARSIM. (2021). Annual Report 2021. https://www.tarsim.gov.tr/staticweb/krm-web/dergi/faaliyet-raporlari/2021.pdf
  • TARSIM. (2020). Annual Report 2020. https://www.tarsim.gov.tr/staticweb/krm-web/dergi/faaliyet-raporlari/2020.pdf
  • TARSIM. (2019). Annual Report 2019. https://www.tarsim.gov.tr/staticweb/krm-web/dergi/faaliyet-raporlari/2019.pdf
  • TARSIM. (2018). Annual Report 2018. https://www.tarsim.gov.tr/staticweb/krm-web/dergi/faaliyet-raporlari/2018.pdf
  • Tayyar, N., Yapa, K., Durmuş, M., & Akbulut, İ. (2018). Referans ideal metodu ile finansal performans analizi: BIST sigorta şirketleri üzerinde bir uygulama. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 7(4), 2490-2509. https://doi.org/10.15869/itobiad.418429
  • Tekin, A., Karli, B., & Gul, M. (2017). Development of implementation of agricultural insurance in Turkey. Scientific Papers: Management, Economic Engineering in Agriculture & Rural Development, 17(2), 355-364.
  • Torkayesh, S. E., Amiri, A., Iranizad, A., & Torkayesh, A. E. (2020). Entropy based EDAS decision making model for neighborhood selection: A case study in Istanbul. Journal of Industrial Engineering and Decision Making, 1(1), 1-11.
  • Torkayesh, A. E., Deveci, M., Karagoz, S., & Antucheviciene, J. (2023). A state-of-the-art survey of evaluation based on distance from average solution (EDAS): Developments and applications. Expert Systems with Applications, 119724. https://doi.org/10.1016/j.eswa.2023.119724
  • Trung, D., &Thinh, H. (2021). A Multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS Methods: A comparative study. Advances in Production Engineering & Management, 16(4), 443-456. https://doi.org/10.14743/apem2021.4.412
  • Tsiboe, F., & Turner, D. (2023). The crop insurance demand response to premium subsidies: Evidence from US agriculture. Food Policy, 119, 102505. https://doi.org/10.1016/j.foodpol.2023.102505
  • Vilhelm, V., Špička, J., & Valder, A. (2015). Public support of agricultural risk management–situation and prospects. Agris on-line Papers in Economics and Informatics, 7(2), 93-102. https://doi.org/10.22004/ag.econ.207069
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  • Yalaz, H. Ö. (2023). Compulsory earthquake insurance and insurance subsidy in Turkey, Preprint, https://doi.org/10.20944/preprints202305.1233.v1
  • Yusuf, M. Y., Fadhil, R., Bahri, T. S., Maulana, H., & Firmansyah, J. (2022). Design of islamic agricultural insurance model: Evidence from Indonesia. International Journal of Sustainable Development & Planning, 17(8), 2375-2384. https://doi.org/10.18280/ijsdp.170804
  • Zhang, J., Wang, J., Chen, S., Tang, S., & Zhao, W. (2022). Multi-hazard meteorological disaster risk assessment for agriculture based on historical disaster data in Jilin province, China. Sustainability, 14(12), 7482. https://doi.org/10.3390/su14127482
  • Zhichkin, K. A., Nosov, V. V., & Zhichkina, L. N. (2023). Agricultural insurance, risk management and sustainable development. Agriculture, 13(7), 1317. https://doi.org/10.3390/agriculture13071317
  • Zhong, L., Liu, L., & Liu, Y. (2010). Natural disaster risk assessment of grain production in Dongting Lake Area, China. Agriculture and Agricultural Science Procedia, 1, 24-32. https://doi.org/10.1016/j.aaspro.2010.09.004
  • Zhong, L., Nie, J., Yue, X., & Jin, M. (2023). Optimal design of agricultural ınsurance subsidies under the risk of extreme weather. International Journal of Production Economics, 263, 108920. https://doi.org/10.1016/j.ijpe.2023.108920
  • Žižović, M., & Marinković, D. (2020). Objective methods for determining criteria weight coefficients: a modification of the CRITIC method, Decision Making: Applications in Management and Engineering, 3(2). https://doi.org/10.31181/dmame2003149z
  • Zou, B., Ren, Z., Mishra, A. K., & Hirsch, S. (2022). The role of agricultural insurance in boosting agricultural output: An aggregate analysis from Chinese provinces. Agribusiness, 38(4), 923-945. https://doi.org/10.1002/agr.21750
Toplam 72 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Nicel Karar Yöntemleri, Bankacılık ve Sigortacılık (Diğer)
Bölüm Araştırma Makaleleri
Yazarlar

Hasan Arda Burhan 0000-0003-4043-2652

Yayımlanma Tarihi 30 Aralık 2023
Gönderilme Tarihi 20 Kasım 2023
Kabul Tarihi 14 Aralık 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 5 Sayı: 2

Kaynak Göster

APA Burhan, H. A. (2023). Agricultural insurance and natural disasters: an assessment of the financial performance of the Turkish agricultural insurance pool (TARSIM) through selected criteria. Ardahan Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 5(2), 126-136. https://doi.org/10.58588/aru-jfeas.1393228