Yes / Given that the probability of extreme weather has been dramatically increasing, this study contributes to the existing literature by bridging the relation between weather risks and global commodity prices with a secondary dataset (e.g., weather risks of Canada and the United States, agricultural raw materials price, gold price, and crude oil price). The results from the vector autoregression model and impulse response functions show that rising weather risks increase the price of agricultural raw materials and gold. However, the negative impact of weather risks on the crude oil price is found. Finally, the paper discusses the findings' potential implications (e.g., developing decarbonised supply chains) for decreasing weather risks' effects on commodity market uncertainties.

Most farmers in South Africa use standard insurance to protect their crops against natural disasters such as hail or strong winds. However, no South African insurance contracts exist to compensate for too much or too little rain (although floods are covered), or which will pay out if temperatures were too high or too low for a certain period of time for the relevant crop. Weather derivatives - which farmers may employ to ensure crops against adverse temperatures - do exist, but these are mostly available in foreign markets in the form of Heating Degree Days contracts and Cooling Degree Day contracts and are used chiefly by energy companies. Some South African over-the-counter weather derivatives are available, but trading in these is rare and seldom used. The goal of this dissertation is to establish a pricing equation for weather derivatives specifically for use in the South African market. This equation will be derived using a similar methodology to that employed for credit default swaps. The premium derived will be designed to compensate grape farmers from losses arising from two different climatic outcomes - in this case temperature and precipitation. These derivatives will be region and crop specific and the formulation will be sufficiently flexible as to allow for further climatic possibilities (which may be added at a later stage). These weather derivative premiums will then be compared to standard crop insurance to establish economic viability of the products and recommendations will be made regarding their usage. The possibility of the simultaneous use of these derivatives and standard crop insurance for optimal crop coverage will also be explored and discussed. / Thesis (M.Com. (Risk management))--North-West University, Potchefstroom Campus, 2011.

Most farmers in South Africa use standard insurance to protect their crops against natural disasters such as hail or strong winds. However, no South African insurance contracts exist to compensate for too much or too little rain (although floods are covered), or which will pay out if temperatures were too high or too low for a certain period of time for the relevant crop. Weather derivatives - which farmers may employ to ensure crops against adverse temperatures - do exist, but these are mostly available in foreign markets in the form of Heating Degree Days contracts and Cooling Degree Day contracts and are used chiefly by energy companies. Some South African over-the-counter weather derivatives are available, but trading in these is rare and seldom used. The goal of this dissertation is to establish a pricing equation for weather derivatives specifically for use in the South African market. This equation will be derived using a similar methodology to that employed for credit default swaps. The premium derived will be designed to compensate grape farmers from losses arising from two different climatic outcomes - in this case temperature and precipitation. These derivatives will be region and crop specific and the formulation will be sufficiently flexible as to allow for further climatic possibilities (which may be added at a later stage). These weather derivative premiums will then be compared to standard crop insurance to establish economic viability of the products and recommendations will be made regarding their usage. The possibility of the simultaneous use of these derivatives and standard crop insurance for optimal crop coverage will also be explored and discussed. / Thesis (M.Com. (Risk management))--North-West University, Potchefstroom Campus, 2011.

Die Anzahl der unterernährten Menschen in der Welt steigt seit 2017 wieder an. Der Klimawandel wird den Druck auf die Landwirtschaft und die Ernährungssicherheit weiter erhöhen, insbesondere für kleinbäuerliche und von Subsistenzwirtschaft geprägte Agrarsysteme in den Tropen. Um die Widerstandsfähigkeit der Ernährungssysteme und die Ernährungssicherheit zu stärken, bedarf es eines Klimarisikomanagements und Klimaanpassung. Dies kann sowohl die Antizipation als auch die Reaktion auf die Auswirkungen der globalen Erwärmung ermöglichen. Eine zentrale Rolle spielen in dieser Hinsicht landwirtschaftliche Modelle. Sie können die Reaktionen von Pflanzen auf Veränderungen in den Klimabedingungen quantifizieren und damit Risiken identifizieren. Diese Dissertation demonstriert anhand dreier in Peru, in Tansania und in Burkina Faso durchgeführten Fallstudien, wie statistische Ertragsmodelle das Klimarisikomanagement und die Anpassung in der tropischen Landwirtschaft unterstützen können. Während die erste Studie zeigt, wie Klimaanpassungsbestrebungen unterstützt werden können, werden in Studie zwei und drei statistische Modelle genutzt, um Ertrags- und Produktionsvorhersagen zu erstellen. Die Ergebnisse können dazu beitragen, Frühwarnsysteme für Ernährungsunsicherheit zu unterstützen. In den drei Veröffentlichungen werden neue Ansätze statistischer Ertragsmodellierung auf verschiedenen räumlichen Ebenen vorgestellt. Ein besonderer Fokus liegt hierbei auf der Weiterentwicklung von bisherigen Ertragsvorhersagen, insbesondere in Bezug auf unabhängige Modellvalidierungen, eine stärkere Berücksichtigung von Wetterextremen und die Übertragbarkeit der Modelle auf andere Regionen. / The number of undernourished people in the world has been increasing since 2017. Climate change will further exacerbate pressure on agriculture and food security, particularly for smallholder and subsistence-based farming systems in the tropics. Anticipating and responding to global warming through climate risk management is needed to increase the resilience of food systems and food security. Crop models play an indispensable role in this regard. They allow quantifying crop responses to changes in climatic conditions and thus identify risks. This dissertation demonstrates how statistical crop modelling can inform climate risk management and adaptation in tropical agriculture in the case studies of Peru, Tanzania and Burkina Faso. While the first study shows how statistical crop models can support climate adaptation, studies two and three provide yield and production forecasts. The results can contribute to supporting early warning systems on food insecurity. The three publications present novel approaches of statistical yield modelling at different spatial scales. A particular focus is on further developing existing yield forecasts, especially with regard to independent rigorous model validations, improved consideration of weather extremes, and the transferability of the models to other regions.