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This study investigated the nexus among the profitability, sales, and willingness to pay (WTP) more for weather index-based agricultural insurance premiums of flower farmers. In addition, the effect of sociodemographic and farm characteristics of flower farmers on their WTP more for insurance premiums was also estimated. A total of 160 flower farmers were selected from Bangladesh using the purposive random sampling technique. Propensity score matching technique was employed to identify the sales difference depending on WTP for insurance premiums while the profitability differences of flower farmers were assessed from different points of view. A binary logistic regression model was used to estimate the effect of sociodemographic and farm characteristics of flower farmers on their WTP more for insurance premiums, while a Likert scale was used to identify the major problems faced by flower farmers. Flower growers are willing to pay a higher premium for insurance when their sales decline. Farmers with lower profitability show a greater WTP higher insurance premiums, whereas those with relatively higher profitability are less inclined to do so. Farmers’ WTP more for insurance premiums decreases with age, education, and farm area, while farmers’ WTP more for insurance premiums increases with experience, training, earning members, marigold farming, and consciousness about natural calamities, pests, and diseases. The most significant problems faced in flower production are high input costs, demand fluctuation, pest and disease attacks, price fluctuation, and loss of production. Thus, the introduction of crop insurance in flower farming may increase profitability and reduce the exposure to risks involved in flower farming. The involvement of younger and more trained farmers in flower farming will increase their WTP more for insurance premiums.
This study investigated the nexus among the profitability, sales, and willingness to pay (WTP) more for weather index-based agricultural insurance premiums of flower farmers. In addition, the effect of sociodemographic and farm characteristics of flower farmers on their WTP more for insurance premiums was also estimated. A total of 160 flower farmers were selected from Bangladesh using the purposive random sampling technique. Propensity score matching technique was employed to identify the sales difference depending on WTP for insurance premiums while the profitability differences of flower farmers were assessed from different points of view. A binary logistic regression model was used to estimate the effect of sociodemographic and farm characteristics of flower farmers on their WTP more for insurance premiums, while a Likert scale was used to identify the major problems faced by flower farmers. Flower growers are willing to pay a higher premium for insurance when their sales decline. Farmers with lower profitability show a greater WTP higher insurance premiums, whereas those with relatively higher profitability are less inclined to do so. Farmers’ WTP more for insurance premiums decreases with age, education, and farm area, while farmers’ WTP more for insurance premiums increases with experience, training, earning members, marigold farming, and consciousness about natural calamities, pests, and diseases. The most significant problems faced in flower production are high input costs, demand fluctuation, pest and disease attacks, price fluctuation, and loss of production. Thus, the introduction of crop insurance in flower farming may increase profitability and reduce the exposure to risks involved in flower farming. The involvement of younger and more trained farmers in flower farming will increase their WTP more for insurance premiums.
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