Investigating the effective factors on the acceptance of climate-based insurance by orange growers in Darab city

Subject Areas : Agricultural Economics Research

فاطمه علیجانی ¹ , Shahrokh Shajari ² , Asiye Montazeri ³ , Mehrdad Bagheri ⁴

1 - عضو هیات علمی دانشگاه پیانور
2 - 2. Associate Professor of Agricultural Economics, Agricultural Research,Education and Extension Organization
3 - 3. Ph.D. Student, Agricultural Economics, Payame Noor University University of Tehran
4 - 4. Assistant Professor of Agricultural Economics, Payame Noor University University of Tehran

Received: 2021-07-16 Accepted : 2023-10-17 Published : 2024-01-21

Keywords: orange, Choice Experiment model, Climate-based insurance, Darab city,

Abstract :

Introduction: Agricultural insurance, such as climate-based insurance, is one of the most important mechanisms for securing investment and reducing the effects of natural disasters.

Methods: The effective factors on the acceptance of the proposed climate index insurance plan by gardeners in Darab city were investigated using a Choice Experiment model with four characteristics of climate-based index insurance (the number of climate indicators covered type of orange, payment method and insurance premium per hectare).

Findings: If the insurance plan for Valencia Orange and insurance premiums is paid in installments, and on the other hand, if the insurance plan includes more climate indicators, gardeners are more likely to participate. Also, the number of indices (three indices) and the type of orange (Valencia) with 93112 and 24425 Tomans, respectively, have the highest willingness to pay among the various characteristics.

Conclusion: The Agricultural Insurance Fund, based on the important features of the Climate Index Insurance Plan, can provide complete information to gardeners to increase their participation in this plan.

References:

1. Adamowicz W, Boxall P, Williams M, Louviere J. Stated preference approaches for measuring passive use values: choice experiments and contingent valuation. American journal of agricultural economics. 1998; 80(1): 64-75. [https://doi.org/10.2307/3180269]


2. Afrasyabi S, Ghahremanzadeh M, Dashti G, Hussein Zad J. Factors affecting the participation of wheat farmers in the proposed weather index-based insurance in Ahar County. Journal of Agricultural Science and Sustainable Production. 2014; 23(4): 71-84. https://sustainagriculture.tabrizu.ac.ir/m/article_783.html?lang=en


3. Ali A. Farmers’ willingness to pay for index-based crop insurance in Pakistan: a case study on food and cash crops of rain-fed areas. Agricultural Economics Research Review. 2013; 26(2): 241-248. https://ageconsearch.umn.edu/record/162145/files/9-Akhter-Ali.pdf


4. Alpizar F, Carlsson F, Martinsson P. Using choice experiments for non-market valuation. Working papers in economics/Göteborg University, Dept. of Economics. 2001; No: 52 .https://idl-bnc-idrc.dspacedirect.org/bitstream/handle/10625/31484/118103.pdf?sequence=1


5. Ben-Akiva M, Morikawa T. Estimation of switching models from revealed preferences and stated intentions. Transportation Research Part A: General. 1990; 24(6): 485-495. [https://doi.org/10.1016/0191-2607(90)90037-7]


6. Birol E, Karousakis K, Koundouri P. Using a choice experiment to account for preference heterogeneity in wetland attributes: The case of Cheimaditida wetland in Greece. Ecological economics. 2006; 60(1): 145-156. [https://doi.org/10.1016/j.ecolecon.2006.06.002]


7. Bokusheva R. Measuring the dependence structure between yield and weather variables. 2010. https://mpra.ub.unimuenchen.de/22786/1/MPRA_paper_22786.pdf


8. Budhathoki N K, Lassa J A, Pun S, Zander K K. Farmers’ interest and willingness-to-pay for index-based crop insurance in the lowlands of Nepal. Land use policy. 2019; 85: 1-10. [https://doi.org/10.1016/j.landusepol.2019.03.029]


9. Castellani D, Viganò L. Does willingness-to-pay for weather index-based insurance follow covariant shocks? International Journal of Bank Marketing. 2017; 35(3): 516-539. https://www.emerald.com/insight/content/doi/10.1108/IJBM-10-2016-0155/full/html


10. Cheraghi-Sohi S, Hole A R, Mead N, McDonald, R, Whalley D, Bower P, Roland M. What patients want from primary care consultations: a discrete choice experiment to identify patients’ priorities. The Annals of Family Medicine. 2008; 6(2): 107-115. [DOI: https://doi.org/10.1370/afm.816]


11. Fleisher B. Agricultural risk management. Lynne Rienner.Publishers.1990. https://doi.org/10.1515/9781685855901


12. Fund A. Report on the performance of the Agricultural Products Insurance Fund in recent years. Management and planning services group. 2013.


13. Gebre M B. Analyses of the willingness to pay for weather index insurance. 2014. https://www.duo.uio.no/handle/10852/40988


14. Ghahramanzadeh M, Dashti G, Afrasyabi S, Hosseinzade J, Hayati B. Finding the Background of Proposed Climate Index Insurance in Dryland Wheat Crop of Ahar County. Iran Economic Research and Agricultural. 2014; 45: 383-393. https://journals.ut.ac.ir/article_52174.html


15. Ghanbari S, shayan M, Rashidi S, Ebrahimipour F, Raesi M K. Agricultural Development Abilities in Darab County and Predicting Its Results on Rural Development. Geography and Environmental Sustainability. 2019; 9(2): 67-82. [https://doi.org/10.22126/ges.1970.1158]


16. Hashemibonab S, Sharzei G, Yazdani S. Estimating Value of Non-Use Services of Agricultural Lands for Residents with Choice Experiment Method (Case of Mazandaran Province). Agricultural Economics. 2012; 6(3): 177-209. https://www.iranianjae.ir/article_9305_144732bd22e51ada32b325c8349fec43.pdf


17. Hausman J, McFadden D. Specification tests for the multinomial logit model. Econometrica: Journal of the econometric society. 1984: 1219-1240. [https://doi.org/10.2307/1910997]


18. Hensher D, Louviere J, Swait J. Combining sources of preference data. Journal of Econometrics. 1998; 89(1-2): 197-221. [https://doi.org/10.1016/S0304-4076(98)00061-X]


19. Jørgensen S L, Termansen M, Pascual U. Natural insurance as condition for market insurance: Climate change adaptation in agriculture. Ecological economics. 2020; 169: 106489. [https://doi.org/10.1016/j.ecolecon.2019.106489]


20. Kadas A, Khan T, Kishore A. Willingness to pay for weather-based crop insurance in Punjab. 2018. https://ageconsearch.umn.edu/record/277516/


21. Lancaster K J. A new approach to consumer theory. Journal of political economy. 1966; 74(2): 132-157. http://pombo.free.fr/lancaster66b.pdf


22. Liu X, Tang Y, Miranda M J. Does past experience in natural disasters affect willingness-to-pay for weather index insurance? Evidence from China. 2015.


23. Louviere J J, Hensher D A, Swait J D. Stated choice methods: analysis and applications. Cambridge university press. 2000. https://www.academia.edu/download/24862915/00023024.pdf


24. Louviere JJ, Woodworth G. Design and analysis of simulated consumer choice or allocation experiments: an approach based on aggregate data. Journal of marketing research. 1983; 20(4): 350-367. [https://doi.org/10.1177/002224378302000403]


25. Manski C F. The structure of random utility models. Theory and decision. 1977; 8(3): 229. https://search.proquest.com/openview/7acf07ef00e4d7b837b4de87994aed40/1?pq-origsite=gscholar&cbl=1818302


26. McFadden D. Conditional logit analysis of qualitative choice behavior. 1973. https://eml.berkeley.edu/reprints/mcfadden/zarembka.pdf


27. Mohammadi H, Farajzadeh Z, Dehbashi V, Shahraki I. Analysis of Citrus Marketing in Fars Province. Agricultural Economics and Development. 2014; 22(2): 1-30. [https://doi.org/10.30490/aead.2014.58921]


28. Morrison M, Bennett J, Blamey, R. Valuing improved wetland quality using choice modeling. Water resources research. 1999; 35(9): 2805-2814. [ https://doi.org/10.1029/1999WR900020]


29. Navrud S, Vondolia G K. Farmers′ preferences for reductions in flood risk under monetary and non-monetary payment modes. Water Resources and Economics. 2020; 30: 100151. [https://doi.org/10.1016/j.wre.2019.100151]


30. Nikbakht Shahbazi A. Investigation of Crop Evapotranspiration and Precipitation changes under Climate Change RCPs Scenarios in Khouzestan province. Journal of Water and Soil Conservation. 2019; 25(6): 123-139. https://jwsc.gau.ac.ir/article_4466_ed1cc4b8cb66f1b162be750ae0e3ac27.pdf


31. Orme B. Sample size issues for conjoint analysis studies. Sequim: Sawtooth Software Technical Paper. 1998.


32. Pishbahar E. Weather-Based Crop Insurance (WBCI) Premium for Rainfed Wheat in Miyaneh County: D-Vine Copula Approach Application. Agricultural Economics. 2015; 9(3): 37-62. https://www.iranianjae.ir/article_14513_2a54b538f2fa8a397c0c248c175aa2ab.pdf


33. Rolfe J, Bennett J, Louviere J. Choice modelling and its potential application to tropical rainforest preservation. Ecological economics. 2000; 35(2): 289-302. [https://doi.org/10.1016/S0921-8009(00)00201-9]


34. Shahiki Tash M N, Yazdani F, Gholipor E. The Effect of Advertisement on the Probability of Acceptance Insurance by Pistachio Growers in Kerman. Journal of Pistachio Science and Technology. 2018; 1(1): 58-68. https://pistachio.vru.ac.ir/article_62727_5f9dc65c142241b78b03aaacd9e2dbef.pdf?lang=en


35. Shee A, Turvey C G, Marr A. Heterogeneous Demand and Supply for an Insurance‐linked Credit Product in Kenya: A Stated Choice Experiment Approach. Journal of Agricultural Economics. 2021; 72(1): 244-267. [https://doi.org/10.1111/1477-9552.12401]


36. Skees J R, Varangis P, Larson D F, Siegel P B. Can financial markets be tapped to help poor people cope with weather risks? Available at SSRN 636095. 2002. https://ssrn.com/abstract=636095


37. sobhanian s m h, mehrara m. Study of Factors inFluencing Physician Decision to Enter the Family Physician Program; A Case Study of Tehran [Applicable]. Journal of Economic Modeling Research. 2016; 7(26): 7-40. [https://doi.org/10.18869/acadpub.jemr.7.26.7]


38. Stoppa A, Hess U. Design and use of weather derivatives in agricultural policies: the case of rainfall index insurance in Morocco. International Conference “Agricultural Policy Reform and the WTO: Where are we heading”, Capri (Italy), 2003. https://www.farmd.org/app/uploads/2019/05/Design-and-Use-of-Weather-Derivatives-Morocco.pdf.


39. Tadesse M A, Alfnes F, Erenstein O, Holden, S. T. Demand for a labor‐based drought insurance scheme in Ethiopia: a stated choice experiment approach. Agricultural Economics. 2017; 48(4): 501-511. https://doi.org/10.1111/agec.12351


40. Torabi S, Dourandish A, Daneshvar Kakhki M, KianiRad A, Mohammadi H. The Computation of Weather-Based Index Insurance Premium and Indemnity function for Apple in Damavand County: The Application of Different Types of Elliptical and Archimedean Copulas. Iranian Journal of Agricultural Economics and Development Research. 2018; 49(1): 23-41. [https://doi.org/10.22059/IJAEDR.2018.235412.668447]


41. Turvey C G, Kong R, Belltawn B. Weather risk and the viability of weather insurance in western China. 2009. https://ageconsearch.umn.edu/record/49362/files/Weather%20Risk%20in%20China.aaea.Paper.pdf.


42. Vojáček O, Pecáková I. Comparison of discrete choice models for economic environmental research. Prague economic papers. 2010; 19(1): 35-53. [https://www.academia.edu/download/86956783/download.pdf]


43. Yazdani S. Income insurance; New model in crop risk management. Agricultural Economics and Development. 2004; 12: 47-67. https://sid.ir/paper/367068/fa