MSc

The research entitled “Mitigating production vulnerability of banana through weather based crop insurance: an economic analysis” was conducted in the Palakkad and Wayanad districts of Kerala during 2017-19. The objectives of the study were to assess vulnerability of agriculture in general and banana farmers in particular to climate change in Palakkad and Wayanad districts. To evaluate economic benefits of Weather Based Crop Insurance Scheme (WBCIS) for banana farmers and to study the problems and suggest measures for scaling up of WBCIS. Primary data was collected from the farmers of both the districts for the agricultural year 2017-18. Secondary data regarding weather parameters, socio-economic and physiographic factors were collected from various sources.
Climate change vulnerability in both districts was assessed by constructing a composite index. It consists of three major component indices: adaptive capacity, sensitivity and exposure and those components were constituted of 27 sub components based on the secondary data collected. The adaptive capacity index, sensitivity index and exposure index obtained for Palakkad district were 0.481, 0.312 and 0.136 and for Wayanad district they were 0.543, 0.345 and 0.166 respectively. The climate change vulnerability index for Palakkad district was 0.322 and for Wayanad it was 0.365. Higher the value of index higher is the vulnerability to climate change. All the indices were more for Wayanad district compared to Palakkad.
Same methodology was used to analyse the vulnerability of banana farmers to climate change in the study area. The 14 sub components of vulnerability index were selected based on the primary data collected during the survey. The adaptive capacity index, sensitivity index and exposure index obtained for Palakkad district were 0.618, 0.425 and 0.566 for Wayanad district were 0.622, 0.458 and 0.609 respectively. The vulnerability index obtained for Palakkad was 0.552 and Wayanad was 0.572. The banana farmers in Palakkad district exhibited slightly more vulnerability change when compared to Wayanad districts.
To evaluate economic benefits of WBCIS for banana farmers, comparison of was done using cost concepts. At Cost C, insured farmers had incurred more cost (₹ 3,86,021 ha-1) than uninsured farmers (₹3,50,910.06 ha-1). The net returns at Cost C for insured farmers were ₹3,56,261 ha-1 and for uninsured farmers it was ₹3,24,197 ha-1. Insured farmers had 9.89 per cent higher net return at Cost C than uninsured farmers. The BC ratio obtained for insured farmers (2.01) at Cost C were more than that of uninsured farmers (1.92). It was found that the insured farmers were having more economic benefits than uninsured farmers from banana cultivation.
The results of Cobb-Douglas production function revealed that R2 value for insured and uninsured farmers was 0.87 and 0.79 respectively, which indicated a good fit. The analysis of allocative efficiency for insured and uninsured farmers revealed that quantity of hired labour, family labour and quantity of manures, fertilizers and soil ameliorants were underutilized. Furthermore, quantity of plant protection materials was overutilized by both categories of farmers.
Binary logit regression was fitted to understand the influence of socioeconomic variables on the adoption of WBCIS. From the analysis it was understood that number of years of experience in banana farming had a positive and significant effect, which indicates that the probability of taking insurance increases with increase in the number of years of experience in banana farming. Odds ratio was found as 1.1, meaning that the likelihood of adoption of insurance by more experienced farmers was 1.1 times that of farmers having less experience.
Response of insured and uninsured farmers was studied to analyse different aspects associated with WBCIS. Regarding the awareness of insured farmers, majority of farmers were aware about the premium rate and subsidies available, still the overall awareness level was poor. It was found that 51.86 per cent of insured farmers showed involuntary participation in the scheme. Moreover, majority (51.67 per cent) had perception of premium rate as high. Majority of insured farmers expressed willingness to pay only up to 3 per cent of sum insured as premium. About 56.67 per cent of insured farmers were found dissatisfied with the scheme. The financial institution’s compulsion was ranked first among the factors influencing adoption of the scheme. Information from financial institutions was ranked the first as source of information about the scheme among the farmers. Insured farmers unanimously suggested the quick settlement of claims and increase in the indemnity level as a solution to improve the scheme.
The main constraint in the adoption of WBCIS was ‘less satisfaction with the indemnity level’ and then ‘lack of awareness about the scheme’. Among the uninsured farmers about 15 per cent farmers adopted the scheme in the previous years. Less indemnity level was the most common reason (75 per cent) for not availing the scheme among the uninsured farmers followed by lack of awareness about the scheme (68.33 per cent).
Thus, it can be concluded that Banana farmers in Wayanad district were more vulnerable to climate change compared to Palakkad district. Similar pattern was observed in the vulnerability of agriculture in general to climate change for both districts. WBCIS can be used as a good institutional mechanism for the farmers to adapt to vulnerability due to changes in climate.