Willingness to pay for cattle and buffalo insurance: an analysis of dairy farmers in central India

Abstract

In India, insurance market especially in agricultural sector is usually underdeveloped. The idea of livestock insurance emerged in India before three decades, yet, it has not operated in a significant way till date. It is well noted that livestock insurance scheme is the relevant strategy in managing different risks related to livestock farming but very little attention has been paid to address the livestock insurance needs of the dairy farmers. This study, therefore, addresses the basic question that how many people and to what extent they are willing to pay for livestock insurance and determine the main factors which influence insurance participation of dairy farmers. The data was collected from Gorakhpur district of Uttar Pradesh in India with a sample survey of 120 cattle and buffalo farmers. For eliciting willingness to pay, a contingent valuation scenario was presented to dairy animal owners in the group of five to six. A logit discrete binary regression model was used to know the factors influencing adoption of livestock insurance. The results suggest that most of the farmers were willing to participate in cattle and buffalo insurance. The amount of premium varies across different breeds of dairy animals. The low level of education of many dairy farmers have negatively influenced the decision to purchase livestock insurance. Farmers having more experience in rearing dairy animals are more likely to be willing to pay for cattle and buffalo insurance.

Evaluating the demand for aquaculture insurance: An investigation of fish farmers' willingness to pay in central coastal areas in China

“…The regression results are given in Table 3. It is noted that all of the variables demonstrate a significant correlation with the WTP, which is not in line with the results of previous studies (Hill et al, 2013;Khan et al, 2013). The results have revealed that the majority of fish farmers respond positively to the bids, and the negative coefficient of the bid value indicates that a lower price would be more affordable.…”

“…Demand-side subsidy would provide income support to motivate fish farmers' participation in aquaculture insurance. Although increasing the amount of the subsidies can be effective to increase motivation on both sides (Abbas et al, 2015;Khan et al, 2013;Zheng and Wang, 2015), it is more useful to set discriminated premiums based on risk levels as well as fish farmers' financial status and credit score. This can effectively reduce the risk of adverse selection in the market and improve fish farmers' affordability for aquaculture insurance and bring a relatively high degree protection to those who have a lower risk level.…”

Farmers’ perception on status of livestock insurance in Surkhet district, Nepal

“…New insurance schemes like provision of health insurance for farmers whose livestock are insured motivate them for adoption of the livestock insurance. Despite being livestock insurance scheme a relevant strategy to address different risks related to livestock rearing, less attention has been paid to the livestock insurance needs of the dairy farmers (Khan et al, 2013). Although livestock farming is general in Nepal, but still insurance coverage is low with 0.1 percent of the national herd (World Bank, 2009).…”

On consumer preferences and the willingness to pay for term life insurance

“…Furthermore, there is a large strand of the development economics literature aimed at assessing the WTP for health coverage in rural areas across Africa (see, e.g., Asenso-Okyere et al, 1997;Dong et al, 2003;Ichoku et al, 2010), Asia (see, e.g., Asgary et al, 2004;Zhang et al, 2006;Chen et al, 2011), India (see, e.g., Mathiyazaghan, 1998;Dror et al, 2007), as well as Latin America (see, e.g., Vargas Bustamante et al, 2008;Eckhardt et al, 2011). Besides, preferences and WTP have been studied for crop insurance (see, e.g., Sherrick et al, 2003;Heenkenda, 2011), livestock insurance (see, e.g., Shaik et al, 2008;Buchenrieder and Fischer, 2009;Khan et al, 2013), flood insurance (see, e.g., Botzen and Van den Bergh, 2012), health insurance (see, e.g., Booske et al, 1999;Kerssens and Groenewegen, 2005;Van den Berg et al, 2008), long-term care insurance (see, e.g., Costa-Font and Font, 2009;Jacobs-Lawson et al, 2010), interest rate guarantees in unit-linked life insurance (see, e.g., Gatzert et al, 2011), weather insurance (see, e.g., Fraser, 1992;Musshoff et al, 2008), as well as auto, home, and household insurance (Hansen et al, 2013).…”