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How the Black Swan damages the harvest: statistical modelling of extreme events in weather and crop production in Africa, Asia, and Latin America




Climate change constitutes a rising challenge to the agricultural base of developing countries. Most of the literature has focused on the impact of changes in the means of weather variables on mean changes in production and has found very little impact of weather upon agricultural production. Instead, a more recent stream of literature showed that we can assess the impact of weather on production by looking at extreme weather events. Based on this evidence, we surmise that there is a missing link in the literature consisting of relating the extreme events in weather with extreme losses in crop production. Indeed, extreme events are of the greatest interest for scholars and policy makers only when they carry extraordinary negative effects. We build on this idea and for the first time, we adapt a conditional dependence model for multivariate extreme values to understand the impact of extreme weather on agricultural production. Specifically, we look at the probability that an extreme event drastically reduces the harvest of any of the major crops. This analysis, which is run on data for six different crops and four different weather variables in a vast array of countries in Africa, Asia and Latin America, shows that extremes in weather and yield losses of major staples are associated events.

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  • Marmai, Nadin & Franco Villoria, Maria & Guerzoni, Marco, 2016. "How the Black Swan damages the harvest: statistical modelling of extreme events in weather and crop production in Africa, Asia, and Latin America," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201608, University of Turin.
  • Handle: RePEc:uto:dipeco:201608

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    References listed on IDEAS

    1. M. Moriondo & C. Giannakopoulos & M. Bindi, 2011. "Climate change impact assessment: the role of climate extremes in crop yield simulation," Climatic Change, Springer, vol. 104(3), pages 679-701, February.
    2. Janet E. Heffernan & Jonathan A. Tawn, 2004. "A conditional approach for multivariate extreme values (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(3), pages 497-546.
    3. Galindo, Luis Miguel & Samaniego, Joseluis, 2010. "The economics of climate change in Latin America and the Caribbean: stylized facts," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    4. Caroline Keef & Jonathan Tawn & Cecilia Svensson, 2009. "Spatial risk assessment for extreme river flows," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(5), pages 601-618.
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    1. Marmai, Nadine, 2016. "Farmers’ investments in innovative technologies in times of precipitation extremes: A statistical analysis for rural Tanzania," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201617, University of Turin.

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