Farmers in India continue to face production risks due to climate abnormalities, resulting in low productivity and fluctuating agricultural incomes. In order to withstand such risks and to smoothen consumption, farmers utilise a range of farm financial management options such as borrowing from formal and informal sources, selling assets and cattle, disinvestment, purchasing formal insurance, etc.
Some of the measures are found ineffective during covariate shocks as they impact all the farmers in a particular locality by lowering asset prices and increasing interest rates for informal loans. Both development economics and climate change economics discourses have considered crop insurance as one of the most effective risk coping mechanisms to mitigate covariate risks.
Previous studies have pointed out several ways through which crop insurance enhances farmers' wellbeing, and these are: (i) improves farmers' creditworthiness and serves as collateral for crop loans, (ii) investing in high-risk and high-profit crops, (iii) increase expenditure on agricultural inputs, and thus, higher amount of agricultural output, and (iv) smoothen the farm household's consumption by guaranteeing a minimum income from agriculture.
Further, the climate change adaptation studies related to farm households highlight the positive impact of crop insurance in driving uptake of several farm-level adaptation options that possibly could increase farmers' resilience capacity.
Despite decades of sustained efforts by both the national and state governments to enhance the adoption of crop insurance in India, a low adoption rate is continuously reported. Hence, this has become a research issue over the years, and various studies have identified determinants and barriers related to social, economic, educational, and structural factors. There is a dearth of research in the context of behavioural aspects in India, while several empirical pieces of evidence have emerged in this domain from developing and developed countries.
This study ‘Why are farmers not insuring crops against risks in India? A review’ published in the journal Progress in Disaster Science aims to review these two strands of studies by posing two relevant questions: (a) how do different social, economic, educational, and structural factors affect crop insurance adoption in India? and (b) how do different behavioural anomalies affect farmers' decision to adopt crop insurance?
In doing so, this study by Biswal and Bahinipati has brought out various research avenues for future studies to be undertaken in India and elsewhere. Despite its several benefits, restructuring of insurance products to accommodate loss to agricultural crops from both covariate and idiosyncratic risks and subsidised to a great extent, a low adoption is often reported not only in India but also in the developing nations. India is yet to achieve the goal of 50% gross cropped area coverage under PMFBY, which covered just 30% of India's gross cropped area in 2016–17.
In sum, crop insurance uptake has barely increased despite low premiums and significant government subsidies. Henceforth, the notion of ‘low adoption’ has appeared as an area of inquiry for several studies, not only in India but also across the developing nations, over the past couple of decades.
In the section on ‘Determinants of crop insurance adoption in India’, the authors have organised all the studies into four categories: economic factors (price or premium, liquidity, credit constraint, wealth, and income), social and demographic characteristics (caste, gender, age, and household size), educational factors (education, financial literacy, training, and awareness), and structural factors (land documents, basis risk, crop loss, timely indemnity payment, and crop diversification).
Crop insurance adoption in India is primarily influenced by economic factors such as liquidity constraints, wealth/income of farmers, credit constraints, and the premium/price of the insurance. Because the majority of farmers in India are small and marginal and are frequently located in impoverished households, their lack of income becomes a critical barrier to the purchase of crop insurance.
Farm households purchase crop insurance during the sowing season when there are numerous competing demands on limited funds. High insurance premiums could be detrimental to crop insurance adoption. Crop insurance premiums are prohibitively high for marginal and small farmers.
Several empirical studies on crop insurance have discovered an inverse link between crop insurance and its premiums. For instance, crop insurance has a negative price elasticity of 0.58, making it less adaptable in times of high premiums. Field evidence from Gujarat and Andhra Pradesh shows that a 10% reduction in the premium increases the likelihood of insurance enrolment by 10–12%.
Further, Gaurav et al. have introduced a money-back guarantee scheme in crop insurance among farmers in Gujarat, India, which is comparable to a price reduction of an insurance product by approximately 40%, which subsequently drove an increase in crop insurance demand by 7%.
In contrast, Matsuda and Kurosaki found that the price or premium of temperature and rainfall insurance is insensitive in influencing farmers' decisions to purchase crop insurance; instead, other non-price factors such as age of the farmer, household size, mathematical ability and land holding influence farmers' insurance purchasing decisions in Madhya Pradesh, India.
Structural factors
The structure of a crop insurance scheme is a determinant of its adoption; in particular, this includes the nature of the crop insurance scheme, the documents required to access crop insurance, loss measurement approach, indemnity payment process, and other risk-sharing instruments clubbed under structural factors.
The accessibility of crop insurance in India is based on either access to crop loans or land documents. A farmer having their own land with proper documents can easily avail of crop loans and, by default, get crop insurance. Hence, farmers with more land have a greater chance of adopting crop insurance; this indicates that large and medium farmers have a high chance of adopting crop insurance.
Crop insurance adoption is also influenced by the availability of ex-ante and ex-post risk-management techniques. Farmers in drought-prone locations are more likely to diversify their production by employing conventional risk-management techniques such as intercropping, crop diversification, and planting drought-resistant cultivars.
Behavioural anomalies in crop insurance adoption
Aside from the socio-economic, educational, and structural factors mentioned, multiple studies using behavioural economics principles illustrate how different behavioural biases drive crop insurance adoption. These studies on the adoption of various types of crop insurance schemes have been carried out in India and many developing countries.
They use field experiments, lab-in-field experiments, randomised control trials, field games, frame field experiments, and survey methods. All the behavioural biases have been discussed under four broad categories: framing effect, ambiguity aversion, cognitive bias, and trust.
Concluding observations
While the factors outlined in the paper are crucial for crop insurance adoption, behavioural biases in crop insurance adoption can complement them. Hence, the second group of literature explores several behavioural biases such as ambiguity aversion, certainty effect, overconfidence bias, hyperbolic discounting, availability bias, loss aversion, and trust, which all affect crop insurance adoption.
A few studies undertaken in India investigated the behavioural biases that drive farmers' decisions to purchase crop insurance, revealing a significant research gap. The certainty effect, loss aversion, and hyperbolic discounting lower crop insurance demand since farmers perceive purchasing insurance as a loss of wealth because they believe the insurance premium to be fixed and obligatory while the expected indemnity is uncertain.
In order to overcome these behavioural biases in crop insurance, the insurance premium must be reframed or redesignated. In this regard, rebate frame insurance has had much success in various developing countries. In the context of India, Lampe and Würtenberger observed that farmer education is a panacea for overcoming loss aversion.
Further, ambiguity aversion in crop insurance has not received much attention in India. Evidence from studies conducted in developing countries shows that ambiguity aversion is a potential cause of poor crop insurance adoption, which can be eliminated by lowering the basis risk and adjusting the weather index. Cognitive biases like an overconfidence bias and availability bias in crop insurance are hardly studied in India, but these factors have a potential impact on crop insurance adoption. Providing financial literacy to farmers could reduce an overconfidence bias and availability bias in crop insurance adoption.
Finally, trust in the insurance market is critical; building trust among farmers by issuing timely insurance payouts and selling insurance through a local agent raises the possibility of crop insurance adoption.
In the Indian context, the trust factor plays a vital role; selling insurance through a trusted agent raises the demand for crop insurance. In the end, we suggest that the effect of behavioural biases on crop insurance adoption should be thoroughly investigated in India to provide tangible evidence. Policymakers should be cautious about behavioural biases while developing and implementing crop insurance programmes in India.
The full paper can be accessed here
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