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

Aizaki, Hideo; Furuya, Jun; Sakurai, Takeshi; Mar, Swe Swe

doi:10.1007/s10333-020-00838-z

Cited by 8 publications

(6 citation statements)

References 50 publications

(49 reference statements)

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“…These studies indicate that preference heterogeneity is related to not only social-economic features [15,18,21] but also geographical location [20]. Moreover, Aizaki et al [22] further show the heterogeneity in preference for insurance packages in Myanmar. They find that farmers are more likely to buy insurance covering extreme weather than other disasters (e.g., salt damage), suggesting that the preference for insurance varies with crop types and geographical conditions.…”

Section: Literature Reviewmentioning

confidence: 90%

Willingness to Pay for Weather-Indexed Insurance: Evidence from Cambodian Rice Farmers

Wang

Soksophors²,

Barlis

et al. 2022

Sustainability

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This study examines Cambodian rice farmers’ willingness to pay for the weather-indexed insurance (WII) proposed to manage the financial impact of shifting monsoon rainfall patterns in Battambang Province in north-western Cambodia. Detailed interviews are conducted in the districts of Bavel and Thma Koul. We first analyse farmer respondents’ socioeconomic and demographic characteristics, climate change perceptions and experience, risk attitudes, and awareness of insurance. The binary logistic model is used to identify factors that significantly impact farmers’ willingness to pay (WTP) for WII. Our results show that farmers in general had lower awareness of how to use innovative financial products to adapt to extreme weather. The results also demonstrate that farmer respondents’ marital status, the number of off-farm labourers, and the farm size have a positive effect, whereas the number of children in the household has a negative effect on farmers’ WTP for WII. Specifically, being married, an increase of one off-farm labourer, and an increase of one hectare (ha) of farmland increase the probability of demand for WII by 38.6%, 21.4%, and 5.1%, respectively. In contrast, an increase of one child reduces the probability of WII demand by 9.7%. We also identify challenges confronted by Cambodian farmers for participating in the proposed WII scheme and provide relevant recommendations to overcome these challenges.

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Section: Literature Reviewmentioning

confidence: 90%

Willingness to Pay for Weather-Indexed Insurance: Evidence from Cambodian Rice Farmers

Wang

Soksophors²,

Barlis

et al. 2022

Sustainability

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show abstract

“…The loss expectation can be determined using historical burn rate method (HBR), which is the mean historical losses (Guerrero-Baena and Gómez-Limón, 2019; Hohl et al, 2020;Mortensen and Block, 2018;Shirsath et al, 2019).This method is widely applied in the insurance industry, however, requires sufficient data in order to be accurate. For smaller datasets considering uncertainty, expected values can be evaluated by fitting loss data to a probability density function (Aizaki et al, 2021;Bokusheva, 2018;Bucheli et al, 2021;Eze et al, 2020;Kath et al, 2019;Salgueiro, 2019;Sacchelli et al, 2018;Vroege et al, 2021;Ward et al, 2020).…”

Section: Financial Methods and Risk Pricingmentioning

confidence: 99%

“…Deterministic models were applied for income reduction impacts, especially for crop insurance. Additionally, some models were related only with one explanatory variable (one index) was the most common solution found in the in-depth analysis (Aizaki et al, 2021;Bokusheva, 2018;Bucheli et al, 2021;Hohl et al, 2020;Kath et al, 2019;Mortensen and Block, 2018;F et al, 2020;Vroege and Finger, 2020;Ward and Makhija, 2018). There is evidence that machine learning techniques improve loss modeling from different sources and present different time and spatial scales (Eze et al, 2020).…”

Section: Vulnerability Analysismentioning

confidence: 99%

Review article: Design and Evaluation of Weather Index Insurance for Multi-Hazard Resilience and Food Insecurity

Benso

Gesualdo²,

Silva³

et al. 2022

Preprint

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Abstract. The urgency of accelerating disaster risk resilience also promotes preferred systematic reviews of the methods for design and evaluation of risk transfer tools. This paper aims to provide a state-of-art weather index insurance design, thereby including methods for natural hazards’ indices calculation, vulnerability assessment and risk pricing. We applied the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) using the Scopus database. First, 364 peer-reviewed articles from 2010 to present were screened for a bibliometric analysis and then, the 34 most cited articles from the past five years were systematically analyzed. Our results demonstrate that despite a great research effort on index insurance, the majority of them focused on food insecurity through agricultural and crop insurance. Also, climate change and basis risks were found highly relevant for weather index insurance, but weakly developed, suggesting challenges around food insecurity. Special focus was given to drought hazards, while other hazards such as temperature variation, excessive rainfall and wildfires were slightly covered. Emerging areas, namely agricultural, hydrological, and sustainable index insurance found promissory for insurance. Also, current state-of-the-art lacks methods for incorporating multi-hazard risk evaluation in vulnerability assessment and risk pricing. Most studies considered only single-hazard risk, and the multi-hazard risk studies assumed independence between hazards. Thus, we summarized the most common methods for calculating indices, estimating losses using indices, pricing risks, and evaluating insurance index policies. This review promotes a starting point in weather index insurance design towards a multi-hazard resilient society.

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“…Basic information supporting the proposal for a new WII included price, coverage, and types of target disaster. Secondly, discrete choice experiments were used to investigate demand for WII related to the three attributes (Aizaki et al 2021).…”

Section: Section 2: Economic Analysismentioning

confidence: 99%

“…Identifying which disaster commands the attention of farmers is necessary for designing the WII. Aizaki et al (2021) conducted discrete choice experiments of WII on farmers in the ten village tracts in Labutta township. This experiment revealed the farmers' preference of premiums and coverage for WII for the disasters of four types.…”

Section: Demand For Wiismentioning

confidence: 99%

Toward the development of a weather index insurance for rice farmers in the coastal region of Myanmar

Furuya

Omori

Aizaki

2021

Paddy Water Environ

Self Cite

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Climate change is expected to exacerbate damage to agricultural production from natural disasters. Examination of measures to adapt to the damage represents an urgent matter for agriculture. A multidisciplinary research project aimed at providing effective information related to development a weather index insurance (WII) system was conducted for rice farmers in a coastal region of Myanmar to achieve sustainable rice farm management in the country, which is among the world’s poorest and most disaster prone. For lower income countries, WII is one adaptation measure to mitigate damage by climate change. Using remote sensing and statistical data, changes in tracks of cyclones in the Bay of Bengal, the duration of damage by cyclone disasters, and areas affected by saltwater intrusion were analyzed to ascertain risk levels for disasters in the target area: Labutta township in the Ayeyarwady region. Furthermore, demand analysis of WII using discrete choice experiments, a question-based statistical survey method, revealed that farmers’ demand of WIIs for cyclone landfall, flood, and drought is relatively greater than that for saltwater intrusion. This finding indicates that saltwater intrusion might not be a crucially important matter for farmers who cultivate rainfed rice, whereas inland water floods caused by cyclone landfall and drought caused for changing the weather patterns represent a threat for these farmers. Results of econometric model analysis for designing a WII indicate that if a regular farmer in the township were to pay 41.5 US dollars per year to purchase WII for flood damage, their expected income will be stable.

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

Cited by 8 publications

References 50 publications

Willingness to Pay for Weather-Indexed Insurance: Evidence from Cambodian Rice Farmers

Willingness to Pay for Weather-Indexed Insurance: Evidence from Cambodian Rice Farmers

Review article: Design and Evaluation of Weather Index Insurance for Multi-Hazard Resilience and Food Insecurity

Toward the development of a weather index insurance for rice farmers in the coastal region of Myanmar

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