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Hoveid, Ø. (2015). A prototype dynamic stochastic equilibrium model of the global food system (Vol. 4).
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Hoveid, Ø. (2015). An economist’s wish list for soil and crop modelling (Vol. 5).
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
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Hoveid, Ø. (2015). A prototype stochastic dynamic equilibrium model of the global food system (Vol. 5).
Abstract: The risks of food consumption are primarily linked to those of food production due to stochastic weather. Other sources of risk are associated with break-down of food trade or transport for weather or political reasons. Hopefully, future cures against increased risk due to climate change may be found with new agricultural technologies, systems of storage from favorable to unfavorable periods, more flexible trade-arrangements between favorable and unfavorable places. However, in the short run one has to rely on the available technology, storage facilities and trade agreements. With a realistic model of the stochastic global food system, it should be possible to measure risks of certain extreme unfavorable events.A realistic case will have countries with different climate in different growing seasons. Markets will be open for trade at a number of points per year, in which decisions of production, storage, trade and consumption can be coordinated as a static equilibrium. Determinants of this equilibrium are the weather up to this date reflected in the state of crops, the available harvested stocks and the decision-maker’s preferences. With a global stochastic process of weather, a stochastic sequence of equilibria follows. No Label
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Hoveid, Ø. (2015). Prototype of stochastic equilibrium model of the food system (Vol. 6).
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
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Hoveid, Ø. (2014). Prototype stochastic general equilibrium model of a global food system. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: A model of a global food system need at least two points in time per year and two locations with different growing seasons so that planting and harvesting have different timing across locations. Moreover, planting decisions reflect soil states affected by stochastic weather since previous point in time, while harvest reflect the planting decisions and the stochastic weather through the growing season up to next point. Decisions on trade, storage and consumption are taken at every point in time. Despite stochastic influence, deterministic stationary general equilibrium is applicable. The world then runs in circles through a likely sequence of N given weather scenarios, while the decision-makers do not know the next scenario. The model will provide a setting in which the consequences of climate change can be assessed both with respect to expectations and variances. It will by construction be an integrated assessment model (IAM) in the sense that outcomes follow from agent choices in a world of biophysical processes. In this case the biophysical world is stochastic. At the prototype stage neither existing behavioral nor bio-physical models will be applied.
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