Academic journal article Agricultural and Resource Economics Review

Weather Index Insurance and Common Property Resources

Academic journal article Agricultural and Resource Economics Review

Weather Index Insurance and Common Property Resources

Article excerpt

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Since many low-income households worldwide rely on common property resources such as pastures and water bodies, maintaining the health of those resources is vital for their survival. However, reductions in uncertainty through programs providing insurance, an often critical element in efforts to improve human welfare, can damage those vital resources. Works by Sandler and Sterbenz (1990) and McCarthy (2000) show that when agents are risk-averse, production risk and uncertainty reduce the use of common property resources and thus conserve these assets. Thus, risk-mitigation tools such as insurance can intensify exploitation of common property resources and potentially exhaust them. If the reduction in risk needed to keep low-income households from failing destroys the environmental resources on which they depend, tools like weather index insurance, intended for development and adaptation, could backfire.

Weather index insurance is a risk-mitigation tool that is rapidly gaining popularity in low-income agricultural areas around the world as part of efforts to enhance the welfare of low-income households. The distinguishing characteristic of weather index insurance is that the insurance payoff triggers are based on weather indicators such as rainfall and satellite-based greenness indices that clients cannot manipulate. The insurance is designed to reduce risks posed by adverse weather for clients while addressing problems associated with moral hazard and adverse selection for lenders relative to traditional yield-based insurance (Turvey 2001, Barnett, Barrett, and Skees 2008, Hellmuth et al. 2009). Since credit is often constrained in low-income regions and insurance could reduce defaults following damaging states of nature, links to credit often play a central role in projects aimed at improving the lives of low-income individuals.

Despite concerns about limited demand for index insurance (Banerjee and Duflo 2011, Cole et al. 2012, Giné and Yang 2009, Hazell et al. 2010), several recently established index insurance projects for low-income developing countries are growing dramatically, scaling up quickly from only a few hundred clients to tens of thousands of clients in two or three years (Oxfam 2011, Syngenta Foundation for Sustainable Agriculture 2011). In India, subsidized index insurance expanded to cover millions of farmers in less than ten years (Clarke et al. 2012). Given the dramatic growth of such projects, the potential for both desired outcomes and unintended negative consequences is large. Some index insurance projects have directly targeted common property pastoralists (Barrett et al. 2008b, Hellmuth et al. 2009) so it is important to understand the potential consequences that these types of tools may have on common property resources.

Research to date pertaining to weather index insurance has primarily focused on hurdles to its implementation, such as insurance uptake (Cole, Tobacman, and Topalova 2007, Giné, Townsend, and Vickery 2007, 2008) and the performance, benefits, and drawbacks of products for protected farmers (Barrett et al. 2008a, Kalavakonda and Mahul 2005). None of the studies have assessed potential effects of the insurance on the common property resources used in production processes.

Most closely related to our work is Müller et al. (2011). Their numerical bio-agricultural simulation model analyzed plausible impacts of rainfall-based weather index insurance on the sustainability of private property range land. Although they did not address common property resource issues, their ecological simulation modeling shows that high strike levels (frequent insurance payouts) can lead to adoption of less sustainable grazing practices while low to medium strike levels can enhance farmers' well-being without impairing sustainable practices for private range lands. Given the complexity of the dynamic simulation models, it is difficult to know what is missing from traditional theoretical analyses. …

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