The future of food demand: understanding differences in global economic models

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.     

Why do global long‐term scenarios for agriculture differ? An overview of the AgMIP Global Economic Model Intercomparison

Recent studies assessing plausible futures for agricultural markets and global food security have had contradictory outcomes. To advance our understanding of the sources of the differences, 10 global economic models that produce long‐term scenarios were asked to compare a reference scenario with alternate socioeconomic, climate change, and bioenergy scenarios using a common set of key drivers. Several key conclusions emerge from this exercise: First, for a comparison of scenario results to be meaningful, a careful analysis of the interpretation of the relevant model variables is essential. For instance, the use of “real world commodity prices” differs widely across models, and comparing the prices without accounting for their different meanings can lead to misleading results. Second, results suggest that, once some key assumptions are harmonized, the variability in general trends across models declines but remains important. For example, given the common assumptions of the reference scenario, models show average annual rates of changes of real global producer prices for agricultural products on average ranging between ?0.4% and +0.7% between the 2005 base year and 2050. This compares to an average decline of real agricultural prices of 4% p.a. between the 1960s and the 2000s. Several other common trends are shown, for example, relating to key global growth areas for agricultural production and consumption. Third, differences in basic model parameters such as income and price elasticities, sometimes hidden in the way market behavior is modeled, result in significant differences in the details. Fourth, the analysis shows that agro‐economic modelers aiming to inform the agricultural and development policy debate require better data and analysis on both economic behavior and biophysical drivers. More interdisciplinary modeling efforts are required to cross‐fertilize analyses at different scales.     

Modeling climate change and agriculture: an introduction to the special issue

This issue of Agricultural Economics is a special issue containing articles on model performance in assessing the effects of climate change, bioenergy policy, and socioeconomics on agriculture. The contributions present results from a global economic model intercomparison activity undertaken as part of the AgMIP Project ( www.agmip.org ). The origins of the comparison activities can be traced to a project that was organized by the OECD in late 2010 to compare results from three models. The current phase of the research includes 10 models and was designed in part to support of the IPCC fifth assessment report (AR5). The special issue includes seven peer‐reviewed articles that present thematic results from a range of modeling strategies, with partial and general equilibrium modeling as a high level distinction but a myriad of differences within these two model types. A central common element is harmonization on biophysical effects using crop models and socioeconomic effects using drivers from the Shared Socioeconomic Pathways developed as part of the AR5 process. The special issue provides broad insights into how the modeling communities approached the interactions of climate, socioeconomics, bioenergy policy on agricultural outcomes, including land use, prices, consumption, and production.     

Land‐use change trajectories up to 2050: insights from a global agro‐economic model comparison

Changes in agricultural land use have important implications for environmental services. Previous studies of agricultural land‐use futures have been published indicating large uncertainty due to different model assumptions and methodologies. In this article we present a first comprehensive comparison of global agro‐economic models that have harmonized drivers of population, GDP, and biophysical yields. The comparison allows us to ask two research questions: (1) How much cropland will be used under different socioeconomic and climate change scenarios? (2) How can differences in model results be explained? The comparison includes four partial and six general equilibrium models that differ in how they model land supply and amount of potentially available land. We analyze results of two different socioeconomic scenarios and three climate scenarios (one with constant climate). Most models (7 out of 10) project an increase of cropland of 10–25% by 2050 compared to 2005 (under constant climate), but one model projects a decrease. Pasture land expands in some models, which increase the treat on natural vegetation further. Across all models most of the cropland expansion takes place in South America and sub‐Saharan Africa. In general, the strongest differences in model results are related to differences in the costs of land expansion, the endogenous productivity responses, and the assumptions about potential cropland.     

Projecting future crop productivity for global economic modeling

Assessments of climate change impacts on agricultural markets and land‐use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land‐use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10–38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change.     

Climate change reduces the mitigation obtainable from sequestration in an Australian farming system

Agricultural research on climate change generally follows two themes: (i) impact and adaptation or (ii) mitigation and emissions. Despite both being simultaneously relevant to future agricultural systems, the two are usually studied separately. By contrast, this study jointly compares the potential impacts of climate change and the effects of mitigation policy on farming systems in the central region of Western Australia’s grainbelt, using the results of several biophysical models integrated into a whole‐farm bioeconomic model. In particular, we focus on the potential for interactions between climate impacts and mitigation activities. Results suggest that, in the study area, farm profitability is much more sensitive to changes in climate than to a mitigation policy involving a carbon price on agricultural emissions. Climate change reduces the profitability of agricultural production and, as a result, reduces the opportunity cost of reforesting land for carbon sequestration. Nonetheless, the financial attractiveness of reforestation does not necessarily improve because climate change also reduces tree growth and, therefore, the income from sequestration. Consequently, at least for the study area, climate change has the potential to reduce the amount of abatement obtainable from sequestration – a result potentially relevant to the debate about the desirability of sequestration as a mitigation option.     

Evaluating the impact of rising fertilizer prices on crop yields

Because of tensions on fossil energy and phosphorus markets, the rise in fertilizer prices observed during the last decades may continue in the future, putting into question production pathways relying heavily on crop intensification. To evaluate how, in this context, economic choices may alter crop yields, we first construct different fertilizer price scenarios to 2050 based on an econometric relation with oil and gas prices. Other possible scenarios, such as the continuation of historical trends, are also considered. The resulting changes in fertilizer price range between +0.8% and +3.6% per year over the 2005–2050 period. These scenarios are tested in a global land‐use model incorporating an endogenous representation of the land–fertilizer substitution. We find that the supply‐side response to rising fertilizer prices could lower crop yields in 2050 from ?6% to ?13%, with a corresponding increase in global cropland area ranging between 100 and 240 Mha if the demand for food and nonfood products has to be met. The sensitivity of these results is tested with regard to assumptions on food consumption, change in potential yield and nutrient use efficiency.     

Global food demand,productivity growth,and the scarcity of land and water resources: a spatially explicit mathematical programming approach

In the coming decades, an increasing competition for global land and water resources can be expected, due to rising demand for food and bio‐energy production, biodiversity conservation, and changing production conditions due to climate change. The potential of technological change in agriculture to adapt to these trends is subject to considerable uncertainty. In order to simulate these combined effects in a spatially explicit way, we present a model of agricultural production and its impact on the environment (MAgPIE). MAgPIE is a mathematical programming model covering the most important agricultural crop and livestock production types in 10 economic regions worldwide at a spatial resolution of three by three degrees, i.e., approximately 300 by 300 km at the equator. It takes regional economic conditions as well as spatially explicit data on potential crop yields and land and water constraints into account and derives specific land‐use patterns for each grid cell. Shadow prices for binding constraints can be used to valuate resources for which in many places no markets exist, especially irrigation water. In this article, we describe the model structure and validation. We apply the model to possible future scenarios up to 2055 and derive required rates of technological change (i.e., yield increase) in agricultural production in order to meet future food demand.     

Competition for land in the global bioeconomy

The global land use implications of biofuel expansion have received considerable attention in the literature over the past decade. Model‐based estimates of the emissions from cropland expansion have been used to assess the environmental impacts of biofuel policies. And integrated assessment models have estimated the potential for biofuels to contribute to greenhouse gas (GHG) abatement over the coming century. All of these studies feature, explicitly or implicitly, competition between biofuel feed stocks and other land uses. However, the economic mechanisms governing this competition, as well as the contribution of biofuels to global land use change, have not received the close scrutiny that they deserve. The purpose of this article is to offer a deeper look at these factors. We begin with a comparative static analysis which assesses the impact of exogenously specified forecasts of biofuel expansion over the period: 2006–2035. Global land use change is decomposed according to the three key margins of economic response: extensive supply, intensive supply, and demand. Under the International Energy Agency's “New Policies” scenario, biofuels account for nearly one‐fifth of global land use change over the 2006–2035 period. The article also offers a comparative dynamic analysis which determines the optimal path for first and second generation biofuels over the course of the entire 21st century. In the absence of GHG regulation, the welfare‐maximizing path for global land use, in the face of 3% annual growth in oil prices, allocates 225 Mha to biofuel feed stocks by 2100, with the associated biofuels accounting for about 30% of global liquid fuel consumption. This area expansion is somewhat diminished by expected climate change impacts on agriculture, while it is significantly increased by an aggressive GHG emissions target and by advances in conversion efficiency of second generation biofuels.     

Appraising agricultural greenhouse gas mitigation potentials: effects of alternative assumptions

There is interest in society in general and in the agricultural and forestry sectors concerning a land‐based role in greenhouse gas mitigation reduction. Numerous studies have estimated the potential supply schedules at which agriculture and forestry could produce greenhouse gas offsets. However, such studies vary widely in critical assumptions regarding economic market adjustments, allowed scope of mitigation alternatives, and region of focus. Here, we examine the effects of using different assumptions on the total emission mitigation supply curve from agriculture and forestry in the United States. To do this we employ the U.S.‐based Agricultural Sector and Mitigation of Greenhouse Gas Model and find that variations in such factors can have profound effects on the results. Differences between commonly employed methods shift economic mitigation potentials from –55 to + 85%. The bias is stronger at higher carbon prices due to afforestation and energy crop plantations that reduce supply of traditional commodities. Lower carbon prices promote management changes with smaller impacts on commodity supply.     

Logs or permits? Forestry land use decisions in an emissions trading scheme

Negative carbon emissions options are required to meet long-term climate goals in many countries. One way to incentivise these options is by paying farmers for carbon sequestered by forests through an emissions trading scheme (ETS). New Zealand has a comprehensive ETS, which includes incentives for farmers to plant permanent exotic forests. This research uses an economy-wide model, a forestry model and land use change functions to measure the expected proportion of farmers with trees at harvesting age that will change land use from production to permanent forests in New Zealand from 2014 to 2050. We also estimate the impacts on carbon sequestration, the carbon price, gross emissions, GDP and welfare. When there is forestry land use change, the results indicate that the responsiveness of land owners to the carbon price has a measured impact on carbon sequestration. For example, under the fastest land use change scenario, carbon sequestration reaches 29.93 Mt CO₂e by 2050 compared to 23.41 Mt CO₂e in the no land use change scenario (a 28% increase). Even under the slowest land use change scenario, carbon sequestration is 25.89 Mt CO₂e by 2050 (an 11% increase compared with no land use change). This is because, if foresters decide not to switch to permanent forests in 1 year, carbon prices and ultimately incentives to convert to permanent forests will be higher in future years.     

The research cost of adapting agriculture to climate change: A global analysis to 2050

Investments in agricultural research and development (R&D) made over the next few decades will likely prove critical in offsetting adverse climate change impacts on the global food system. In this study, we offer cost estimates of public R&D-led adaptation to climate change grounded in an explicit framework relating the flow of annual R&D expenditures to building knowledge capital and thereby raising productivity in agriculture. Our research uses a comprehensive collection of historical public agricultural R&D expenditure and a literature review of elasticity estimates linking knowledge stocks to agricultural productivity growth for key world regions. Given climate-driven crop yield projections generated from extreme combinations of crop and global circulation models, we find that offsetting crop yield losses projected by climate and crop models over 2006–2050 would require increased R&D adaptation investments of between $187 billion and $1,384 billion (in 2005 $PPP) if we invest between 2020 and 2040. This is 16–118% higher than global R&D investment if present spending trends continue. Although these costs are significant, worldwide R&D-led climate adaptation could offer favorable economic returns. Moreover, R&D-led adaptation could deliver gains in food security and environmental sustainability by mitigating food price increases and slowing cropland expansion.     

Mitigation potential and costs for global agricultural greenhouse gas emissions1

Agricultural activities are a substantial contributor to global greenhouse gas (GHG) emissions, accounting for about 58% of the world's anthropogenic non‐carbon dioxide GHG emissions and 14% of all anthropogenic GHG emissions, and agriculture is often viewed as a potential source of relatively low‐cost emissions reductions. We estimate the costs of GHG mitigation for 36 world agricultural regions for the 2000–2020 period, taking into account net GHG reductions, yield effects, livestock productivity effects, commodity prices, labor requirements, and capital costs where appropriate. For croplands and rice cultivation, we use biophysical, process‐based models (DAYCENT and DNDC) to capture the net GHG and yield effects of baseline and mitigation scenarios for different world regions. For the livestock sector, we use information from the literature on key mitigation options and apply the mitigation options to emission baselines compiled by EPA.     

The significance of different realms of value for agricultural land in Sweden

The demand for additional agricultural land is expected to rise by approximately 50 per cent by 2050 on a global level, and agricultural land of high quality needs to be preserved to ensure future food security. However, agricultural land per capita is decreasing. One of the main reasons for this in the EU and globally is the building of houses or infrastructure on agricultural land. There is a possibility that the Swedish agricultural sector will grow in the future and supply more regions than its own territory with food due to, e.g., climate change. Although appropriate regulations exist to support local decision makers in protecting agricultural land in Sweden, the potential to provide such protection is not fully utilised. This paper aims to contribute to explaining why Swedish municipalities build on agricultural land through an analysis of the values behind the arguments for preserving and exploiting agricultural land at the municipal level and the implications of these values for the preservation of agricultural land in Sweden. Assuming value pluralism, we analyse 30 municipal comprehensive plans through a framework of nine realms of value. We find that municipalities deploy at least eight of the nine realms of value to motivate the preservation of agricultural land, but the economic realm is more dominant among arguments to exploit agricultural land. Most plans do not consider food security. Municipalities could become better prepared to handle unexpected events if they worked with longer-term future scenarios. Further research is needed regarding how different values are weighed against each other in actual exploitation issues.     

Addressing Uncertainty in Efficient Mitigation of Agricultural Greenhouse Gas Emissions

The agricultural sector, as an important source of greenhouse gas (GHG) emissions, is under pressure to reduce its contribution to climate change. Decisions on financing and regulating agricultural GHG mitigation are often informed by cost‐effectiveness analysis of the potential GHG reduction in the sector. A commonly used tool for such analysis is the bottom‐up marginal abatement cost curve (MACC) which assesses mitigation options and calculates their cumulative cost‐effective mitigation potential. MACCs are largely deterministic, typically not reflecting uncertainties in underlying input variables. We analyse the uncertainty of GHG mitigation estimates in a bottom‐up MACC for agriculture, for those uncertainties capable of quantitative assessment. Our analysis identifies the sources and types of uncertainties in the cost‐effectiveness analysis and estimates the statistical uncertainty of the results by propagating uncertainty through the MACC via Monte Carlo analysis. For the case of Scottish agriculture, the uncertainty of the cost‐effective abatement potential from agricultural land, as expressed by the coefficient of variation, was between 9.6% and 107.3% across scenarios. This means that the probability of the actual abatement being less than half of the estimated abatement ranged from <1% (in the scenario with lowest uncertainty) to 32% (in the scenario with highest uncertainty). The main contributors to uncertainty are the adoption rate and abatement rate. While most mitigation options appear to be ‘win–win’ under some scenarios, many have a high probability of switching between being cost‐ineffective and cost‐effective.     

Addressing climate change cause and effect on land cover and land use in South Asia

This paper evaluates the role of trade liberalization and agricultural intensification in mitigating climate change cause and effects on land use and emissions using a computable general equilibrium model. Our results indicate that cropland expansion triggered by climate-induced crop productivity changes results in deforestation and increases emissions in South Asia and globally. Global full trade liberalization on all goods is the optimum policy for South Asia despite significant global deforestation, but for the world, unilateral partial trade liberalization on all goods is a more appropriate policy while ensuring a considerable emissions reduction for South Asia. These results indicate that mitigation responses to climate change are location specific and no one trade policy is suitable at the regional and global levels. Lastly, agricultural intensification by improving productivity growth is the best strategy in land-based emissions mitigation, thereby avoiding the transformation of forest and pasture lands for agricultural cultivation both at regional and global levels.     

Developing land use scenarios for stakeholder participation in Russia

Land use change, climate change, and the politics of accelerated agricultural growth shape contemporary land use in Russia. This factor combination urgently calls for exploring viable opportunities for sustainable land management in rural areas, which remains low on the political agenda. We address this task by bringing together various dimensions of future land use and state regulation and develop land use scenarios for the Tyumen region in Western Siberia up to 2050. Schematised maps of future land use make the scenarios spatially explicit and stakeholder-engaging. As part of the scenario process, we conducted stakeholder interviews and organised two scenario workshops on the ground. We present the scenarios as a tool that could be used to support participatory processes in a post-Soviet context.     

Macro–micro feedback links of water management in South Africa: CGE analyses of selected policy regimes

The pressure on an already stressed water situation in South Africa is predicted to increase significantly under climate change, plans for large industrial expansion, ongoing rapid urbanization, and government programs to provide access to water to millions of previously excluded populations. This article employs a general equilibrium approach to examine the economy‐wide impacts of selected macro and water‐related policy reforms on water use and allocation, rural livelihoods, and economy at large. The analyses reveal that implicit crop‐level water quotas reduce the amount of irrigated land allocated to higher‐value horticultural crops and create higher shadow rents for production of lower‐value water‐intensive field crops, such as sugarcane and fodder. Accordingly, liberalizing local water allocation within irrigation agriculture is found to work in favor of higher‐value crops, and expand agricultural production and exports and farm employment. Allowing for water trade between irrigation and nonagricultural uses fuelled by higher competition for water from urbanization leads to greater water shadow prices for irrigation water with reduced income and employment benefits to rural households and higher gains for nonagricultural households. The analyses show difficult trade‐offs between general economic gains and higher water prices, which place serious questions on subsidizing water supply to irrigated agriculture, i.e., making irrigation subsidies much harder to justify.     

Land use and climate change in the UK

This paper reviews the relationships between land use and climate change. It explores how land use decisions will be affected by future changes in the climate, but also the feedbacks from land use change to the global climate system through greenhouse gas (GHG) fluxes. Past changes in land use were characterised by decreasing areas of agricultural use and increasing areas of forested and urbanised land. This has led to UK land use being a net sink for GHGs, mostly due to forestation. However, existing forests have on average passed their age for maximum net removals of carbon from the atmosphere. In the next decade at least, net removals from UK forests are likely to decrease significantly.Longer term scenarios of future land use change are consistent in their expectation of further declines in the agricultural area used for food production – offset to some extent by increased bioenergy cropping – along with increases in forested and urban areas. These trends are broadly consistent with the observed past land use change, but are calculated from various assumptions about future changes in drivers rather than by extrapolation from the past. Socio-economic and technological changes are likely to be the most important drivers for land use, with climate change having a smaller influence. The land use changes represented in these scenarios would likely reduce GHG emissions and enhance carbon sinks. These trends would be reinforced by small future changes in the climate, but large climatic changes are likely to cause net GHG fluxes to switch from being a sink to a source. Land use change will also be moderated by potential policy goals that seek to reduce GHG emissions from land and/or increase the size of land-based sinks. This includes strategies to reduce carbon and nitrogen emissions through increased efficiency, afforestation and biofuel production.     

The Impact of Pillar II Funding: Validation from a Modelling and Evaluation Perspective

We extend the Common Agricultural Policy Regionalised Impact Modelling System (CAPRI) with a regional computational general equilibrium (CGE) model to estimate the effects of the Pillar II of the Common Agricultural Policy. Our aim is to assess the modeling approach by comparing the scenario results with observations from the evaluation reports for rural development, supplemented with expert interviews and findings from the literature. For this purpose, an ex‐post scenario is developed for Germany that models the effect of the Pillar II measures in 2006. We observe a moderate impact, namely, an increase in agricultural income (5%) and agricultural land use (0.15%), particularly grassland, and a substitution of arable land with grassland. This effect leads to a total increase in agricultural production, particularly of beef, and to an increase in total greenhouse gas emissions and total nitrogen surplus for Germany. Greenhouse gas emissions and nutrient surpluses per ha, however, are reduced. We observe that farm investment programmes displace private investment. The evaluation reports confirm the moderate impact and our major results, as does the comparison with other literature. However, the conclusions about agri‐environment measures and their impact on income differ. The most important difference between our results and the evaluation reports and majority of the present literature is that we also quantify the joint effect between the whole economy and policy measures, with some contradictory effects.