This paper examines the economics and pricing of weather derivatives in Ontario and argues that weather derivatives and weather insurance can be used as a form of agricultural insurance. Using historical data, the relationship between crop productivity and weather is examined. Then a variety of put and call options for rain-and heat-based weather risk are discussed and numerically evaluated. The evaluation examines in detail the pricing of insurance contracts at a given location and across space.

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Global insurance markets are vast and diverse, and may offer many opportunities for remote sensing. To date, however, few operational applications of remote sensing for insurance exist. Papers claiming potential application of remote sensing typically stress the technical possibilities, without considering its contribution to customer value for the insured OPEN ACCESS Remote Sens. 2014, 6 10889 or to the profitability of the insurance industry. Based on a systematic search of available literature, this review investigates the potential and actual support of remote sensing to the insurance industry. The review reveals that research on remote sensing in classical claim-based insurance described in the literature revolve around crop damage and flood and fire risk assessment. Surprisingly, the use of remote sensing in claim-based insurance appears to be instigated by government rather than the insurance industry. In contrast, insurance companies are offering various index insurance products that are based on remote sensing. For example, remotely sensed index insurance for rangelands and livestock are operational, while various applications in crop index insurance are being considered or under development. The paper discusses these differences and concludes that there is particular scope for application of remote sensing by the insurance industry in index insurance because (1) indices can be constructed that correlate well with what is insured; (2) these indices can be delivered at low cost; and (3) it opens up new markets that are not served by claim-based insurance. The paper finally suggests that limited adoption of remote sensing in insurance results from a lack of mutual understanding and calls for greater cooperation between the insurance industry and the remote sensing community.

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper to develop an empirical methodology for managing spatial basis risk in weather index insurance by studying the fundamental causes for differences in weather risk between distributed locations. Design/methodology/approach -The paper systematically compares insurance payouts at nearby locations based on differences in geographical characteristics. The geographic characteristics include distance between stations and differences in altitude, latitude, and longitude. Findings -Geographic differences are poor predictors of payouts. The strongest predictor of payout at a given location is payout at nearby location. However, altitude has a persistent effect on heat risk and distance between stations increases payout discrepancies for precipitation risk. Practical implications -Given that payouts in a given area are highly correlated, it may be possible to insure multiple weather stations in a single contract as a "risk portfolio" for any one location. Originality/value -Spatial basis risk is a fundamental problem of index insurance and yet is still largely unexplored in the literature.

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This article addresses the problem of collateral-free lending in the context of agricultural development. We investigate a viable alternative to traditional credit products through the development of risk-contingent credit for operating loans and farm mortgages and apply the concept to agricultural loans for pulse crops in India. Risk-contingent credit mitigates business and financial risk by reducing debt obligations depending on the embedded commodity options whose payoffs are linked with commodity price fluctuations. We analyze daily commodity spot prices for pulse crops in India and show how risk-contingent structured financial instruments can be priced in practice.JEL classifications: G13, O53, Q12, Q14