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Weather index-based crop insurance is increasingly becoming important as a risk mitigation strategy that farmers may use to mitigate adverse climate shocks and natural disasters encountered during farming. While Europe, North America, and Asia account for 20.1%, 55%, and 19.5% of the total agricultural insurance premium worldwide, respectively, Africa accounts for only 0.5% of the world insurance industry. One of the key reasons advanced against the low index insurance participation rate in Africa is the failure to involve farm households at the initial conceptualization and design of pilot initiatives. Therefore, the main purpose of this paper is to design an improved participatory methodology that could help elicit information on the value placed by farm households in Southwestern Burkina Faso on a new weather index-based crop insurance management initiative. A key concept in the improved participatory methodology is that of the willingness to pay (WTP) of farm households for the scheme. Knowledge of the maximum amount that farmers are willing to pay for the scheme can help insurance policy providers and public policy makers to design and put in place measures that sustain index insurance schemes in a developing country context and improve welfare among participating farmers.

The objective of this paper is to develop an approach for integrating a gender dimension into Agricultural Sector Risk Assessments (ASRAs). The focus is on the approach because both agricultural risk and gender issues are contextual, thus the outcomes of a gender-based risk assessment are highly dependent on the social, cultural, geo-graphic, and economic contexts of the setting in which the assessment is applied. The organization of the paper reflects the challenges of incorporating a gender dimension into ASRAs. The conceptual framework and step-by-step illustrations presented herein are based on lessons learned by the World Bank and other institutions in assisting developing economies in conducting sector and key commodity supply chain risk assessments (World Bank 2015a). The paper also relies on recent work by international institutions and academic research that offer insights into the complexities of gender issues in relation to agricultural shocks. These experiences inform this paper’s case for a gender-based approach to Agriculture Risk Management (ARM) and help to illustrate a practical, stepwise approach for conducting gender-based ASRAs. This paper is arranged as follows: Chapter 2 offers a summary of the conceptual framework for risk management, including addressing why a gendered approach to ASRAs is essential; Chapter 3 shows the available evidence that agricultural risk has a gender-differentiated impact on farming households and that farming households adopt a gender-differentiated response to risk; Chapter 4 describes a step-by-step operational approach for doing so, and includes guidance for formulating gender-smart policies and strategies for strengthening agricultural systems’ resilience; and Chapter 5 presents a summary of findings and concluding remarks.

Agriculture is a unique sector because of its dependence on the climate and biological variables. Therefore, in agriculture it is vital to identify and evaluate risks to be sure that decisions made on the farm will bring positive results. Scientific literature describes a lot of risk evaluation methods. However it is not easy to see which methods should be used in the agricultural sector. This article describes the main types of risk in agriculture, their features and their relevance with respect to scientific theories. Secondly, it introduces the most popular risk evaluation methods and their potential use in agriculture and finally presents a logical framework of integrated risk evaluation.

Risk management of crop related exposures in coastal regions can be enhanced through a program of hazards modeling and real-time forecasting. As one component in the yield distribution of selected crops, typhoon-related hazards are a critical factor. Natural typhoon occurrence rates accentuate the extreme parts of the yield distribution, causing severe and correlated financial disruptions to invested interests. This paper outlines a suite of techniques focused on building a probabilistic understanding of crop risk from tropical cyclones. Several foundational technologies are discussed, including: Numerical Weather Prediction (NWP) of tropical cyclones; statistical consensus forecast models, such as the WeatherPredict Superensemble™; and the application of flood modeling techniques to typhoon landfall scenarios.