Measuring farmers’ preferences for weather index insurance in the Ayeyarwady Delta, Myanmar: a discrete choice experiment approach

Paddy and Water Environment - Tập 19 - Trang 307-317 - 2021
Hideo Aizaki1, Jun Furuya2, Takeshi Sakurai3, Swe Swe Mar4
1Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
2Social Sciences Division, Japan International Research Center for Agricultural Sciences, Tsukuba, Japan
3Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo, Japan
4Department of Soil and Water Science, Yezin Agricultural University, Yezin, Nay Pyi Taw, Myanmar

Tóm tắt

This study examines farmers’ preferences for weather index insurance (WII) in the Ayeyarwady Delta, Myanmar, using discrete choice experiments. It employs data taken from a survey of 317 rice farmers in the district of Labutta in the Ayeyarwady Region, which was conducted in March 2019. After being informed about WII and the trigger conditions, farmers were asked to answer discrete choice questions on WII packages. The hypothetical WII packages consisted of three attributes: the types of disaster that the insurance covers, the insurance coverage rate, and the annual insurance premium rate. A random parameter logit model analysis of the responses reveals that farmers prefer the WII packages covering cyclones, floods, and droughts to that for salt damage. The probabilities of selecting 64 hypothetical WII packages calculated from the estimates indicate that more than 50% of farmers can be expected to purchase seven WII packages for cyclones, floods, and droughts.

Tài liệu tham khảo

Adjabui JA, Tozer PR, Gray DI (2019) Willingness to participate and pay for index-based crop insurance in Ghana. AgricFinanc Rev 79(4):491–507. https://doi.org/10.1108/AFR-01-2019-0001 Aizaki H (2012) Basic functions for supporting an implementation of choice experiments in R. J Stat Softw 50(C2):1–24. https://doi.org/10.18637/jss.v050.c02 Aizaki H (2016) support.CEs: basic functions for supporting an implementation of choice experiments. R package version 0.4–1. https://CRAN.R-project.org/package=support.CEs Aizaki H, Nakatani T, Sato K (2014) Stated preference methods using R. Chapman and Hall/CRC Press, New York Aizaki H, Sato K, Osari H (2006) Contingent valuation approach in measuring the multifunctionality of agriculture and rural areas in Japan. Paddy Water Environ 4:217–222. https://doi.org/10.1007/s10333-006-0052-8 Akter S, Krupnik TJ, Khanam F (2017) Climate change skepticism and index versus standard crop insurance demand in coastal Bangladesh. Reg Environ Chang 17:2455–2466. https://doi.org/10.1007/s10113-017-1174-9 Akter S, Krupnik TJ, Rossi F, Khanam F (2016) The influence of gender and product design on farmers’ preferences for weather-indexed crop insurance. Glob Environ Chang 38:217–229. https://doi.org/10.1016/j.gloenvcha.2016.03.010 Barnett B, Mahul O (2007) Weather index insurance for agriculture and rural areas in lower-income countries. Am J Agric Econ 89:1241–1247. https://doi.org/10.1111/j.1467-8276.2007.01091.x Beck M, Gyrd-Hansen D (2005) Effects coding in discrete choice experiments. Health Econ 14:1079–1083. https://doi.org/10.1002/hec.984 Bennett J, Birol E (eds) (2010) Choice experiments in developing countries: implementation, challenges and policy implications. Edward Elgar, Cheltenham, UK. https://doi.org/10.4337/9781781000649 Carson RT (2012) Contingent valuation: a comprehensive bibliography and history. Edward Elgar, Northampton, MA Castellani D, Viganò L, Tamre B (2014) A discrete choice analysis of smallholder farmers’ preferences and willingness to pay for weather derivatives: evidence from Ethiopia. J Appl Bus Res 30:1671–1692. https://doi.org/10.19030/jabr.v30i6.8882 Chen B, Qiu Z, Usio N, Nakamura K (2018) Conservation and contingent valuation of farming landscape amenities by visitors: a case study of terraced paddy fields in Central Japan. Paddy Water Environ 16:561–570. https://doi.org/10.1007/s10333-018-0648-9 Chiueh YW, Chen MC (2008) Environmental multifunctionality of paddy fields in Taiwan: an application of contingent valuation method. Paddy Water Environ 6:229–236. https://doi.org/10.1007/s10333-008-0110-5 Chrzan K, Orme B (2000) An overview and comparison of design strategies for choice-based conjoint analysis. In: Proceedings of the Sawtooth Software Conference. Sawtooth Software. 161–177. https://www.sawtoothsoftware.com/support/technical-papers/conference-proceedings/proceedings2000/. Accessed 12 July 2020 Collier B, Skees J, Barnett B (2009) Weather index insurance and climate change: opportunities and challenges in lower income countries. The Geneva Pap Risk Insur Issues Pract 34:401–424. https://doi.org/10.1057/gpp.2009.11 Cooper JC (1997) Combining actual and contingent behavior data to model farmer adaption of water quality protection practices. J AgricResour Econ 22(1):30–43 Food and Agriculture Organization of the United Nations (2009) Myanmar: Post-Nargis recovery and rehabilitation programme Strategy. pp.20. http://www.fao.org/resilience/resources/resources-detail/en/c/171208/. Accessed 1 June 2020 Franzén F, Dinnétz P, Hammer M (2016) Factors affecting famers’ willingness to participate in eutrophication mitigation: a case study of preferences for wetland creation in Sweden. Ecol Econ 130:8–15. https://doi.org/10.1016/j.ecolecon.2016.05.019 Geweke J (2012) Nonparametric Bayesian modelling of monotone preferences for discrete choice experiments. J Econom 171:185–204. https://doi.org/10.1016/j.jeconom.2012.06.003 Greatrex H, Hansen J, Garvin S, Diro R, Blakeley S, Le Gue M, Rao K, Osgood D (2015) Scaling up index insurance for smallholder farmers: Recent evidence and insights. CCAFS Report No.14 Copenhagen: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). https://hdl.handle.net/10568/53101. Accessed 1 June 2020 Grömping U (2018) R package DoE.base for factorial experiments. J Stat Softw 85(5):1–41. https://doi.org/10.18637/jss.v085.i05 Gu, Y (2018) Rice production risk and demand for saline water insurance in Ayeyarwady Delta of Myanmar. Master Thesis, The University of Tokyo Hensher DA, Greene WH (2003) The mixed logit model: the state of practice. Transportation (Amst) 30:133–176. https://doi.org/10.1023/A:1022558715350 Hensher DA, Rose JM, Greene WH (2015) Applied choice analysis, 2nd edn. Cambridge University Press, Cambridge, UK Hess S, Palma D (2019) Apollo: a flexible, powerful and customisable freeware package for choice model estimation and application. J Choice Model 32:100170. https://doi.org/10.1016/j.jocm.2019.100170 Hess S, Palma D (2020) Apollo: a flexible, powerful and customisable freeware package for choice model estimation and application. Choice Modelling Centre. R package version 0.1.0. http://www.ApolloChoiceModelling.com/ Hollin IL, Peay HL, Bridges JFP (2015) Caregiver preferences for emerging Duchenne muscular dystrophy treatments: a comparison of best-worst scaling and conjoint analysis. Patient 8:19–27. https://doi.org/10.1007/s40271-014-0104-x Holmes TP, Adamowicz WL, Carlsson F (2017) Choice experiments. In: Champ PA, Boyle KJ, Brown TC (eds) A primer on nonmarket valuation. Springer, Dordrecht, pp 133–186 Hong B, Takahashi Y, Yabe M (2017) Determinants of marketability for organic biomass liquid fertilizer from human waste in Da Nang City, Vietnam. J Environ Prot 8:1354–1371. https://doi.org/10.4236/jep.2017.811083 International Fund for Agricultural Development (2011) Weather index-based insurance in agricultural development: a technical guide. International Fund for Agricultural Development, Roma, Italy. https://www.ifad.org/en/web/knowledge/publication/asset/40239811. Accessed on 16 Sep 2020 Jaspersen JG (2016) Hypothetical surveys and experimental studies of insurance demand: a review. J Risk Insur 83:217–255. https://doi.org/10.1111/jori.12100 Jensen N, Barrett C (2017) Agricultural index insurance for development. Appl Econ Perspect Policy 39:199–219. https://doi.org/10.1093/aepp/ppw002 Johnson FR, Kanninen B, Bingham M, Özdemir S (2007) Experimental design for stated choice studies. In: Kanninen BK (ed) Valuing environmental amenities using stated choice studies. Springer, Netherlands, pp 159–202 Just A, Wellmann R, Bennewitz J (2018) Estimation of relative economic weights and the marginal willingness to pay for breeding traits of Brown Swiss cattle using discrete choice experiments. J Dairy Sci 101:5207–5213. https://doi.org/10.3168/jds.2017-14012 Kikushima R, Nakajima S, Takano M, Ito N (2018) Hong Kong consumer preferences for Japanese beef: label knowledge and reference point effects. AnimSci J 89:1519–1529. https://doi.org/10.1111/asj.13085 Kunimitsu Y (2009) Measuring the implicit value of paddy irrigation water: application of RPML model to the contingent choice experiment data in Japan. Paddy Water Environ 7(3):177–185. https://doi.org/10.1007/s10333-009-0159-9 Louviere JJ, Hensher DA, Swait JD (2000) Stated preference methods: analysis and application. Cambridge University Press, UK Louviere JJ, Islam T (2008) A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best-worst scaling. J Bus Res 61:903–911. https://doi.org/10.1016/j.jbusres.2006.11.010 Lutta AI, Robinson LW, Wasonga OV, Ruto E, Sircely J, Nyangito MM (2020) Economic valuation of grazing management practices: discrete choice modeling in pastoral systems of Kenya. J Environ Plan Manag 63:335–351. https://doi.org/10.1080/09640568.2019.1584097 Mahul O, Stutley CJ (2010) Government support to agricultural insurance: challenges and options for developing countries. The World Bank, Washington, D.C Maruyama T, Takimoto H (2008) An economic evaluation of Kanazawa and Shichika irrigation water’s multi-functional roles using CVM. Paddy Water Environ 6:309–318. https://doi.org/10.1007/s10333-008-0121-2 McGurk E, Hynes S, Thorne F (2020) Participation in agri-environmental schemes: a contingent valuation study of farmers in Ireland. J Environ Manag 262:110243. https://doi.org/10.1016/j.jenvman.2020.110243 McIntosh C, Sarris A, Papadopoulos F (2013) Productivity, credit, risk, and the demand for weather index insurance in smallholder agriculture in Ethiopia. Agric Econ 44:399–417. https://doi.org/10.1111/agec.12024 Ministry of Agriculture and Irrigation (2015) Myanmar rice sector development strategy. pp 95. http://books.irri.org/MRSDS_content.pdf. Accessed 1 June 2020 Miranda MJ, Farrin K (2012) Index insurance for developing countries. Appl Econ Perspect Policy 34:391–427. https://doi.org/10.1093/aepp/pps031 Miura K, Sakurai T (2012) Who purchases weather index insurance?: results from a field experiment in rural Zambia. J Rural Econ Spec Issue 2012:442–449 (In Japanese) Oishi T, Nakano R, Matsuno Y (2019) Perception and valuation of paddy field dam functions by rural communities: a CVM approach. Paddy Water Environ 17:383–390. https://doi.org/10.1007/s10333-019-00733-2 Perni A, Martínez-Paz JM (2017) Measuring conflicts in the management of anthropized ecosystem: evidence from a choice experiment in a human-created Mediterranean wetland. J Environ Manage 203:40–50. https://doi.org/10.1016/j.jenvman.2017.07.049 R Core Team (2020) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ Rakatama A, Pandit R, Iftekhar S, Ma C (2018) Heterogeneous public preference for REDD+ projects under different forest management regimes. Land Use Policy 78:266–277. https://doi.org/10.1016/j.landusepol.2018.07.004 Rao VR (2014) Applied conjoint analysis. Springer, Heidelberg Rigby D, Alcon F, Burton M (2010) Supply uncertainty and the economic value of irrigation water. Eur Rev Agric Econ 37:97–117. https://doi.org/10.1093/erae/jbq001 Rose JM, Bliemer MCJ (2009) Constructing efficient stated choice experimental designs. Transp Rev 29:587–617. https://doi.org/10.1080/01441640902827623 Scarpa R, Rose JM (2008) Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why. Aust J AgricResour Econ 52:253–282. https://doi.org/10.1111/j.1467-8489.2007.00436.x Sibiko KW, Veettil PC, Qaim M (2018) Small farmers’ preferences for weather index insurance: insights from Kenya. Agric Food Secur 7:53. https://doi.org/10.1186/s40066-018-0200-6 SOMPO Holdings (2019) Adaptation to climate change. https://www.sompo-hd.com/en/csr/action/community/content4/. Accessed 1 June 2020 Tadesse MA, Alfnes F, Erenstein O, Holden ST (2017) Demand for a labor-based drought insurance scheme in Ethiopia: a stated choice experiment approach. Agric Econ 48:501–511. https://doi.org/10.1111/agec.12351 Train K (2009) Discrete choice methods with simulation, 2nd edn. Cambridge University Press, NY. https://doi.org/10.1017/CBO9780511805271 Wakamatsu H, Fukui S, Miwa K (2019) Heterogeneous preferences for micro health insurance attributes in rural Cambodia: latent class analysis. Econ Bull 39(4):2963–2975 Walker JL, Wang Y, Thorhauge M, Ben-Akiva M (2018) D-efficient or deficient? a robustness analysis of stated choice experimental designs. Theory Dec 84:215–238. https://doi.org/10.1007/s11238-017-9647-3 Ward PS, Makhija S (2018) New modalities for managing drought risk in rain-fed agriculture: evidence from a discrete choice experiment in Odisha, India. World Dev 107:163–175. https://doi.org/10.1016/j.worlddev.2018.03.002 World Bank (2011) Weather index insurance for agriculture: guidance for development practitioners. Agricultural and rural development discussion paper 50. World Bank Group, Washington, D.C. https://openknowledge.worldbank.org/handle/10986/26889. Accessed on 18 Sep 2020 Wu X, Hu B, Xiong J (2020) Understanding heterogeneous consumer preferences in Chinese milk markets: a latent class approach. J Agric Econ 71:184–198. https://doi.org/10.1111/1477-9552.12327 Zuo A, Hou L, Huang Z (2020) How does farmers’ current usage of crop straws influence the willingness-to-accept price to sell? Energy Econ 86:104639. https://doi.org/10.1016/j.eneco.2019.104639