Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison

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.     

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.     

Inter‐ and intra‐seasonal crop acreage response to international food prices and implications of volatility

Understanding how producers make decisions to allot acreage among crops and how decisions about land use are affected by changes in prices and their volatility is fundamental for predicting the supply of staple crops and, hence, assessing the global food supply situation. This study makes estimations of monthly (i.e., seasonal) versus annual global acreage response models for the world's principal staple food crops: wheat, corn, soybeans, and rice. Primary emphasis is given to the magnitude and speed of the allocation process. Estimation of intra‐annual acreage elasticity is crucial for expected food supply and for input demand, especially in the light of the recent short‐term volatility in food prices. The econometric results indicate that global crop acreage responds to crop prices and price risks, input costs as well as a time trend. Depending on respective crop, short‐run elasticities are about 0.05 to 0.40; price volatility tends to reduce acreage for some of the crops; comparison of the annual and the monthly acreage response elasticities suggests that acreage adjusts seasonally around the globe to new information and expectations. Given the seasonality of agriculture, time is of an essence for acreage response. The analysis indicates that acreage allocation is more sensitive to prices in the northern hemisphere spring than in winter and the response varies across months.     

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.     

Effect of changes in population density and crop productivity on farm households in Malawi

This study examines the ex‐ante farm‐household effects of changes in family size, yield potential, and yield gaps using a farm‐household simulation model that reflects the economic and biophysical conditions of central Malawi. Disparities between growth in human population and crop yields present challenges for farm‐household crop production and income in sub‐Saharan Africa. We focus on the effect of growth in yield potential and a more efficient use of livestock manure as approaches to improving crop production and incomes in the face of looming population pressures. Our results suggest that, even without considering climate change, expected changes in population density and crop prices in 2050 mean that per person crop production and income may fall by 21% compared to 2013 values if yield potential and yield gaps remain constant. However, per person crop production and income could increase in 2050 by 8% compared to 2013 values if (1) growth rates of yield potential rise for maize by 1.13% each year and for legumes rise by at least 0.4% each year, and (2) farmers use livestock manure more efficiently. Our foresight approach to considering crop production at the farm‐household scale supplements macro‐scale analyses of the production dimension of food security.     

The impacts of biofuels targets on land‐use change and food supply: A global CGE assessment

We analyze the long‐term impacts of large‐scale expansion of biofuels on land‐use change, food supply and prices, and the overall economy in various countries or regions using a multi‐country, multi‐sector global computable general equilibrium model augmented with an explicit land‐use module and detailed biofuel sectors. We find that an expansion of biofuel production to meet the existing or even higher targets in various countries would slightly reduce GDP at the global level but with mixed effects across countries or regions. Significant land re‐allocation would take place with notable decreases in forest and pasture lands in a few countries. The expansion of biofuels would cause a moderate decrease in world food supply and more significant decreases in developing countries like India and Sub‐Saharan Africa. Feedstock commodities (sugar, corn and oil seeds) would experience significant increases in their prices in 2020, but other price changes are small.     

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.     

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.     

Factors explaining the low and variable profitability of fertilizer application to maize in Zambia

It is widely recognized that an “African green revolution” will require greater use of inorganic fertilizers. Often‐made comparisons note that fertilizer use rates in Africa are just 10–20% of those in Asia, Europe and the Americas. Most attempts to explain relatively low‐adoption of fertilizer assume yield responses to inorganic fertilization warrant higher application rates and hypothesize that observed use rates are limited by market‐based factors. Another explanation may be that application rates are low because African yields are less responsive to inorganic fertilizer than yields in other regions, and less responsive than analysts perceive. Examining the case of Zambia, we evaluate whether yield response to fertilizers could explain adoption and application rates. A model of yield response is constructed and a combination of estimators is employed to mitigate potential biases related to correlation between fertilizer use and unobserved heterogeneity as well as stochastic shocks. Results indicate higher fertilization rates would be marginally profitable or unprofitable in many cases given commercial fertilizer and maize prices. Phosphoric fertilizer is particularly unprofitable on acidic soils, which are common in Zambia and other areas of sub‐Saharan Africa. We propose feasible recommendations for diversifying the current government strategy to enhance crop productivity.     

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.     

Evidence of climate change impacts on crop comparative advantage and land use

Relative agricultural productivity shocks emerging from climate change will alter regional cropland use. Land allocations are sensitive to crop profits that in turn depend on yield effects induced by changes in climate and technology. We develop and apply an integrated framework to assess the impact of climate change on agricultural productivity and land use for the U.S. Northern Great Plains. Crop-specific yield–weather models reveal crop comparative advantage due to differential yield impacts of weather across the region's major crops, that is, alfalfa, wheat, soybeans, and maize. We define crop profits as a function of the weather-driven yields, which are then used to model land use allocation decisions. This ultimately allows us to simulate the impact of climate change under the RCP4.5 emissions scenario on land allocated to the region's major crops as well as to grass/pasture. Upon removing the trends effects in yields, climate change is projected to lower yields by 33–64% over 2031–2055 relative to 1981–2005, with soybean being the least and alfalfa the most affected crops. Yield projections applied to the land use model at present-day input costs and output prices reveals that Dakotas’ grass acreage will increase by up to 23%, displacing croplands. Wheat acreage is expected to increase by up to 54% in select southeastern counties of North Dakota and South Dakota, where maize/soy acreage had increased by up to 58% during 1995–2016.     

Rural credit and agricultural supply in Brazil

The objective of this study is to determine the financing impact of total expenditure on the use of agriculture inputs (fertilizers, labor, and pesticides), and the output of cotton, rice, beans, corn, soybean, and wheat in Brazil. We study the period 1976–2005. The analysis is based on duality applied to the production theory. The output supplies and conditioned input demands are estimated from a translog multi‐output, multi‐input restricted profit function, where the total production credit is used as proxy of the total expenditure. Farmer expectations with respect to crop prices are incorporated to the estimation based on the quasi‐rational expectation model. The output and input responses to the total expenditure are positive and statistically significant except for cotton, wheat, fertilizer, and pesticides. The short‐run output supply response to own prices is inelastic, except for wheat, which presents elastic response to its price. Acreage has a positive impact on the output supply and it is influenced by land productivity. The main conclusion is that farmers face budget restrictions to purchase inputs, and a government credit program might increase the agricultural supply.     

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.     

Factors influencing the profitability of fertilizer use on maize in Zambia

Fertilizer use remains very low in most of Africa despite widespread agreement that much higher use rates are required for sustained agricultural productivity growth. This study uses longitudinal farm survey data to estimate maize yield response functions in a relatively high-potential zone of Zambia to determine the profitability of fertilizer use under a range of small-farm conditions found within this zone. The theoretical framework used in this study incorporates agronomic principles of the crop growth process. We generalize the asymmetric production models and define a concept of yield scaling factors. The model distinguishes different roles of inputs and non-input factors in crop production. We estimate the effects of conventional production inputs as well as of household characteristics and government programs on maize yield. The results indicate that recommended fertilizer application rates in the two specific years were often unprofitable, given observed price conditions and the yield response to fertilizer. However, there was substantial variability in yield response to fertilizer based upon the rate of application, the timeliness of fertilizer availability, the use of animal draught power during land preparation, and whether the household incurred the death of an adult member in the past three years. These modifying factors, as well as variations in input and output prices due to proximity to roads and markets, substantially affected the profitability of fertilizer use on maize.     

Impacts in Uganda of rising global food prices: the role of diversified staples and limited price transmission

This study assesses the potential impact of rising world food prices on the welfare of Ugandan households. While Uganda experienced sharply higher food prices in 2008, as a landlocked, food‐exporting country the causes of those price changes were mainly regional and indirect rather than directly transmitted from global markets. Using trade volumes, food prices, and household survey data we describe how Uganda, unlike some other countries, is partially shielded from direct impacts of global food price movements. Although the majority of Ugandans are net food buyers, the adverse impact at household‐level of rising global prices is moderated by the relatively large quantity and range of staples consumed that come from home production. Moreover, several of these are not widely traded. Some population groups in Uganda are vulnerable to rising food prices, however, primarily those for whom maize is an important staple, including those dependent upon humanitarian relief and the urban poor. Only a relatively small group of Ugandan households will benefit directly and immediately from rising food prices—the significant net sellers of food crops constituting between 12% and 27% of the population. In this assessment we do not estimate the level and extent of wider second round effects from these higher prices.     

Cropland use,yields, and droughts: spatial data modeling for Burkina Faso and Niger

For countries with recurrent droughts, the design of drought impact mitigation measures could benefit from analyses of determinants of yields and prices of local crops at regional and district level. This study applies dynamic spatial panel data regression models to yields and prices of four major food crops across regions of Burkina Faso and Niger, over sample periods between 1984 and 2006. Results lend support to mainly simultaneous spatial spillovers, particularly for millet and cowpea prices and sorghum yields in Niger, and maize yields in Burkina Faso. After accounting for these effects, most crop yields are found to be weakly price‐responsive, as envisaged by a supply‐side geographical diffusion hypothesis. Seasonal rainfall elasticity estimates suggest that dominant food crops have slight advantage margins in terms of relative resilience to rainfall shortages. However, this result is to be weighed against low millet yields in Niger, and marked drops in sorghum yields during officially declared droughts in Burkina Faso.     

Does sustainable intensification of maize production enhance child nutrition? Evidence from rural Tanzania

Food insecurity, child malnutrition, and land degradation remain persistent problems in sub‐Saharan Africa. Agricultural sustainable intensification (SI) has been proposed as a possible solution to simultaneously address these challenges. Yet there is little empirical evidence on if agricultural management practices and inputs that contribute to SI from an environmental standpoint do indeed improve food security or child nutrition. We use three waves of data from the nationally‐representative Tanzania National Panel Survey to analyze the child nutrition effects of rural households’ adoption of farming practices that can contribute to the SI of maize production. We group households into four categories based on their use of three soil fertility management practices on their maize plots: “Nonadoption”; “Intensification” (use of inorganic fertilizer only); “Sustainable” (use of organic fertilizer, maize–legume intercropping, or both); and “SI” (joint use of inorganic fertilizer with organic fertilizer and/or maize–legume intercropping). The results from multinomial endogenous treatment effects models with the Mundlak–Chamberlain device suggest that use of practices in the “SI” category is associated with improvements in children's height‐for‐age and weight‐for‐age z‐scores relative to “Nonadoption,” particularly for children aged 25–59 months. These effects appear to come through improvements in both crop income and productivity.     

Post–Uruguay Round price linkages between developed and developing countries: the case of rice and wheat markets

The Uruguay Round Agreement on agriculture attempted to lower distortions in global agricultural markets. However, the significant fall in commodity prices in the late 1990s may have reduced the incentives for both developed and developing countries to better integrate into world markets. This study analyzes price linkages and adjustment between developed and developing countries during the post–Uruguay Round period. Prices of two key commodities, long‐grain rice and medium‐hard wheat, are assembled for major exporters and producers. Results of multivariate cointegration analysis suggest partial market integration between developed and developing countries in the post–Uruguay Round period. Developed countries are found to be price leaders in these two markets, and in most cases, changes in their prices have relatively large impacts on those of the developing countries. Developing countries (e.g., Vietnam and Argentina) have faced considerable price adjustment due to changes in the developed countries' prices.     

The potential impact of climate change on Taiwan's agriculture

This paper intends to estimate the potential impact of climate change on Taiwan's agricultural sector. Yield response regression models are used to investigate the climate change's impact on 60 crops. A price‐endogenous mathematical programming model is then used to simulate the welfare impacts of yield changes under various climate change scenarios. Results suggest that both warming and climate variations have a significant but non‐monotonic impact on crop yields. Society as a whole would not suffer from warming, but a precipitation increase may be devastating to farmers.     

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.