Understanding the Impact of Agriculture Insurance: Insights and Challenges of PMFY Scheme from Four States of India Using Pearson Correlation

In India, agriculture and the allied sector is one of the foremost sectors but it is highly dependent on weather, which makes it highly susceptible to climate change risks. Thus, building resilience in the sector becomes imperative. This paper will dwell on ex-post strategy of mitigative measure, by focusing on agricultural insurance (AIn). Currently, PMFBY 2.0, which was rolled out to stabilize farmers’ incomes against the increasing risks due to climate change and the SDGs. The review of the existing literature establishes a dire need for a comprehensive assessment of PMFBY on parameters such as awareness, satisfaction, and transparency. Thus, the present study attempts to fill this gap by measuring the perceived impact (PI) of PMFBY on three variables: awareness, satisfaction, and transparency. The study uses a sequential exploratory mixed-method research design, utilizing qualitative methods and quantitative methods. It uses 15 in-depth interviews and a questionnaire with dichotomous and matrix Likert scale questions to understand variables' effects on scheme performance in four states and their districts. The analysis was done using Pearson correlation to measure the linear correlation of PI of farmers on these variables. The results highlight multicollinearity among the factors, which indicates that PI has a positive relationship with the selected variables. Thus, provides a policy dimension to improve the effectiveness of the scheme through three interconnected variables. The study addresses the issue of the comprehensive assessment of PI on the PMFBY and provides a way forward for policymakers to create resilient policies in the sector.