Abstract: It is a widely held belief (IPCC) that climate change bringsmore risks to the worldI Since the start of MACSUR, TradeM has had risk on theagenda, but few results have so far come out. It has beenclaimed though, that there is no evidence for more risk in theglobal wheat market (Steen and Gjølberg 2014) (TradeMworkshop at Hurdalssjøen)I I have myself had the ambition of creating a dynamicstochastic model of the food system in which risk would be anintegral part, but time has been too shortI I have also pointed to methods from finance to reveal insights,and that is the road to be followed here, guided by Bølviken &Benth (2000) Buyer’s risk larger than seller’s risk — due to asymmetricdistribution of returns. Large price jumps are more likely thanequally sized price falls.I Long term positions much more risky than short term ones —as expectedI Agricultural commodities much less risky than crude oilI Price risk are related to volatility, and their changes over timewill have similar causal explanationsI Risks of producers and consumers of agricultural commoditieswill to some extent be related to the price risk, and also totheir portfolios and the co-variance between returns

Abstract: A requirement for successful integration of soil, crop and economic models is a relevant interface of the three. Economic farming models deal with choice of crops, crop management during growing season and stock management after harvest. With detailed daily weather information the state of the soil might be simulated so that a suitable sowing date can be estimated. Moreover with rational beliefs with respect to future crop prices, and with a crop model which responds to management, the management during the growing season might be optimized with respect to choice of cultivar, fertilization and irrigation. So far, as reflected by Müller and Robertson (2014), predictions of future crop yields according to crop models take only to small extent such farmer responses into account, and might therefore overestimate the responses of crop harvests to climate.Comparison of soil, crop and economic simulations with observed weather and crop outcomes might lead to estimation/calibration of unobserved parameters in all models. Such exercises need generic soil, crop and economic models which do not leave modelling outcomes to the crop modeller’s or economist’s discretion. No Label

Abstract: Food security is an issue of risk. If climate change is not responded to with diet, technology and/or policy changes, it may lead to reduced food security for the world population, in particular the poorer part which in longer periods may not afford to purchase food in sufficient quantity and quality. In order to improve the situation, certain policy changes may be required.  In some cases are policy recommendations relatively obvious, while in other cases a deeper insight in the stochastic dynamics of food supply and storage is required to assess the consequences of policy proposals. The relatively obvious part is that farmers need be responsive in periods of low total production, so that sufficient supply restores quickly. Moreover, trade should allow local shortages to be covered. Many national policies with the goal of self-sufficiency aim in the opposite direction with stable prices and production and relatively less flexibility in production. The stochastic dynamics of food supply can be analysed in more detail with a dynamic stochastic general equilibrium model (DSGE). Although agriculture by nature is about taking decisions under uncertainty, quantitative stochastic dynamic models for policy analysis in agriculture have not yet emerged. The contribution in MACSUR is a formalization of a class of DSGE-s based on representation of biological processes managed with regard to outcomes due to uncertain nature. No Label