Crop Insurance, Premium Subsidy and Agricultural Output

Abstract

In this paper, we study the effects of crop insurance on agricultural output in an economic growth model. Based on Ramsey-Cass-Koopmans (RCK) model, we develop a basic model of agriculture economic growth. Extending the basic model to incorporate uncertainty and insurance mechanism, we build a risk model and a risk-insurance model to study the influences of risk and crop insurance on agricultural output. Comparing the steady states of the three models, we get the results that: (i) agricultural output decreases if we introduce uncertainty into the risk-free model; (ii) crop insurance promotes agriculture economic growth if insurance mechanism is introduced into the risk model; (iii) premium subsidy constantly improves agricultural output. Our contribution is that we study the effects of crop insurance and premium subsidy from the perspective of economic growth in a dynamic framework, and prove the output promotion of crop insurance theoretically.

Exploring Sustainability Features and Determinants of Agricultural Insurance Programmes in Low-income Countries

“…I agree with those arguing for public support for AI programmes to some extent. I particularly identify with Banerjee and Bergs's (2012) argument because the five world-leading AI countries in both developed and developing countries-the US, China, Canada, Spain, and India in that order (Xu & Pu, 2014) are subsidizing their AI schemes. These countries have their AI programmes subsidised within the range of 50%-80% of the total premiums or cultivated areas while reimbursing private insurance companies with A&O costs and at the same time providing reinsurance protection (Shields, 2009;Mahul & Stutley, 2010).…”

“…Whereas some researchers, practitioners and policymakers think that public and donor agency subsidization of insurance premiums, provision of technical and financial support in addition to reinsurance guarantees may contribute to the sustainability of index insurance programmes, others believe this may rather contribute to the unsustainability of insurance programmes. Those in favour of public support for index-based insurance programmes in developing countries (e.g., Mahul & Stutley, 2010;Clarke et al, 2012;Hossain, 2013;Xu & Pu, 2014) maintain that these financial and technical support systems will not only make index insurance contracts affordable but will also help deal with systemic risks through reinsurance and reimbursement programmes as being done under the US Federal Crop Insurance Programme (FCIP) (see Shields, 2009). Despite this recognition in the AI literature, the opposing camp (e.g., Goodwin, 2001;McLeman & Smit, 2006;Nnadi et al, 2013;Panda, 2013a) is against governments' support and subsidization of AI programmes.…”

Agricultural Insurance and Agricultural Economic Growth: The Case of Zhejiang Province in China

“…The AI subsidy policy encourages farmers to expand their production scale by mitigating production risks [ 22 ]. Crop insurance promotes agricultural economic growth if the insurance mechanism is introduced into the risk model; premium subsidies constantly improve AO [ 23 ]. The development of AI, induced by premium subsidies, significantly promotes primary industry production, and primarily affects agriculture and husbandry among the four subindustries of the primary industry [ 24 ].…”

Remote sensing in an index-based insurance design for hedging economic impacts on rice cultivation

“…Agricultural insurance is an effective tool for transferring production risk from farmers to other entities. It allows farmers to meet their credit obligations and minimize the effect of extreme climatic events on their revenue (Xu and Liao, 2014). Moreover, agricultural insurance contributes to keeping farmers in the agricultural business, improving their resilience and preserving food security (Bullock et al, 2017;Patt et al, 2009).…”