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Valin, H., Sands, R. D., van der Mensbrugghe, D. and, Nelson, G. C., Ahammad, H., Blanc, E., et al. (2014). The future of food demand: Understanding differences in global economic models. Agric. Econ., 45(1), 51–67.
Abstract: Understanding the capacity of agricultural systems to feed the world population under climate change requires projecting future food demand. This article reviews demand modeling approaches from 10 global economic models participating in the Agricultural Model Intercomparison and Improvement Project (AgMIP). We compare food demand projections in 2050 for various regions and agricultural products under harmonized scenarios of socioeconomic development, climate change, and bioenergy expansion. In the reference scenario (SSP2), food demand increases by 59-98% between 2005 and 2050, slightly higher than the most recent FAO projection of 54% from 2005/2007. The range of results is large, in particular for animal calories (between 61% and 144%), caused by differences in demand systems specifications, and in income and price elasticities. The results are more sensitive to socioeconomic assumptions than to climate change or bioenergy scenarios. When considering a world with higher population and lower economic growth (SSP3), consumption per capita drops on average by 9\% for crops and 18% for livestock. The maximum effect of climate change on calorie availability is -6% at the global level, and the effect of biofuel production on calorie availability is even smaller.
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Schönhart, M., Mitter, H., Schmid, E., Heinrich, G., & Gobiet, A. (2014). Integrated analysis of climate change impacts and adaptation measures in Austrian agriculture. German Journal of Agricultural Economics, 63(3), 156–176.
Abstract: An integrated modelling framework (IMF) has been developed and applied to analyse climate change impacts and the effectiveness of adaptation measures in Austrian agriculture. The IMF couples the crop rotation model CropRota, the bio-physical process model EPIC and the bottom-up economic land use model PASMA at regional level (NUTS-3) considering agri-environmental indicators. Four contrasting regional climate model (RCM) simulations represent climate change until 2050. The RCM simulations are applied to a baseline and three adaptation and policy scenarios. Climate change increases crop productivity on national average in the IMF. Changes in average gross margins at national level range from 0% to + 5% between the baseline and the three adaptation and policy scenarios. The impacts at NUTS-3 level range from -5% to + 7% between the baseline and the three adaptation and policy scenarios. Adaptation measures such as planting of winter cover crops, reduced tillage and irrigation are effective in reducing yield losses, increasing revenues, or in improving environmental states under climate change. Future research should account for extreme weather events in order to analyse whether average productivity gains at the aggregated level suffice to cover costs from expected higher climate variability.
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Gutierrez, L., Piras, F., & Roggero, P. P. (2015). A global vector autoregression model for the analysis of wheat export prices. American Journal of Agricultural Economics, 97(5), 1494–1511.
Abstract: Food commodity price fluctuations have an important impact on poverty and food insecurity across the world. Conventional models have not provided a complete picture of recent price spikes in agricultural commodity markets, and there is an urgent need for appropriate policy responses. Perhaps new approaches are needed to better understand international spill-overs, the feedback between the real and the financial sectors, as well as the link between food and energy prices. In this article, we present the results from a new worldwide dynamic model that provides the short and long-run impulse responses of the international wheat price to various real and financial shocks.
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Robinson, S., van Meijl, H., Willenbockel, D., Valin, H., Fujimori, S., Masui, T., et al. (2014). Comparing supply-side specifications in models of global agriculture and the food system. Agric. Econ., 45(1), 21–35.
Abstract: This article compares the theoretical and functional specification of production in partial equilibrium (PE) and computable general equilibrium (CGE) models of the global agricultural and food system included in the AgMIP model comparison study. The two model families differ in their scopepartial versus economy-wideand in how they represent technology and the behavior of supply and demand in markets. The CGE models are deep structural models in that they explicitly solve the maximization problem of consumers and producers, assuming utility maximization and profit maximization with production/cost functions that include all factor inputs. The PE models divide into two groups on the supply side: (1) shallow structural models, which essentially specify area/yield supply functions with no explicit maximization behavior, and (2) deep structural models that provide a detailed activity-analysis specification of technology and explicit optimizing behavior by producers. While the models vary in their specifications of technology, both within and between the PE and CGE families, we consider two stylized theoretical models to compare the behavior of crop yields and supply functions in CGE models with their behavior in shallow structural PE models. We find that the theoretical responsiveness of supply to changes in prices can be similar, depending on parameter choices that define the behavior of implicit supply functions over the domain of applicability defined by the common scenarios used in the AgMIP comparisons. In practice, however, the applied models are more complex and differ in their empirical sensitivity to variations in specificationcomparability of results given parameter choices is an empirical question. To illustrate the issues, sensitivity analysis is done with one global CGE model, MAGNET, to indicate how the results vary with different specification of technical change, and how they compare with the results from PE models.
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Lotze-Campen, H., von Lampe, M., Kyle, P., Fujimori, S., Havlik, P., van Meijl, H., et al. (2014). Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison. Agric. Econ., 45(1), 103–116.
Abstract: Integrated Assessment studies have shown that meeting ambitious greenhouse gas mitigation targets will require substantial amounts of bioenergy as part of the future energy mix. In the course of the Agricultural Model Intercomparison and Improvement Project (AgMIP), five global agro-economic models were used to analyze a future scenario with global demand for ligno-cellulosic bioenergy rising to about 100 ExaJoule in 2050. From this exercise a tentative conclusion can be drawn that ambitious climate change mitigation need not drive up global food prices much, if the extra land required for bioenergy production is accessible or if the feedstock, for example, from forests, does not directly compete for agricultural land. Agricultural price effects across models by the year 2050 from high bioenergy demand in an ambitious mitigation scenario appear to be much smaller (+5% average across models) than from direct climate impacts on crop yields in a high-emission scenario (+25% average across models). However, potential future scarcities of water and nutrients, policy-induced restrictions on agricultural land expansion, as well as potential welfare losses have not been specifically looked at in this exercise.
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