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.     

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.     

Climate change: scenarios,impacts, policy,and development opportunities

This article is divided into three parts. First, it provides an overview of the main outcomes of the last IPCC assessment report, both in terms of economic drivers of greenhouse gas (GHG) emissions, and in terms of impacts of climate change, in particular for the agriculture sector. Then, it focuses on policy options and their optimal design, taking into account technological availability, international cooperation, and above all the stringency of the remaining carbon budget. Finally, it analyzes the size and direction of investment decisions required to stabilize GHG emissions and their implications for economic development.     

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.     

Conditioning trends shaping the agricultural and rural landscape in Africa

African countries continue to face deepening food crises that have been accentuated by the global food, energy, and financial crises. This situation is part of a long‐term structural problem: decades of under‐investments in agricultural sector and poor policies of support for smallholder farmers who form the bulk of the farming population. The inability of these farmers to achieve a supply response when commodity prices were high and market access was less of a problem suggests that there are multiple sets of binding constraints that continue to limit the potential of agricultural growth to reduce food security and poverty on the continent. This article reviews some of the historical trends that have hampered the performance of the agriculture sector. In addition, it reviews the impacts of more positive trends that could stimulate agricultural growth in Africa that could change the African agricultural landscape. The article however warns that there are more recent global developments and some continental challenges that could prevent or slow agricultural growth. These include the global financial crisis, public sector investments, inequities in global agricultural development policies, rush for agricultural lands by foreign investors, domestic commercial financing markets, climate change, and emerging carbon markets. The article argues that while opportunities for accelerated growth exists for African agriculture, new sets of policy instruments will be needed to support smallholder farmers to access new agricultural technologies, finance, reduce impacts of climate change, and adopt sustainable land use practices that can allow them to benefit from emerging global carbon markets.     

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.     

Comparing supply‐side specifications in models of global agriculture and the food system

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 scope—partial versus economy‐wide—and 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 specification—comparability 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.     

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.     

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.     

Climate change and Australia's comparative advantage in broadacre agriculture1

Australia has long been a major exporter of the products of broadacre agriculture, a production system well suited to the economic and climatic conditions of the country. Presumably, it holds a comparative advantage in these products, among which grain crops and grazing livestock predominate. However, the future plausibility of this proposition is sensitive to the projected impacts of climate change. This article develops a framework to quantify the future patterns of comparative advantage in broadacre agriculture, given the projections of several global climate models. We find empirical support for the conventional wisdom, and note substantial resilience and robustness in Australia's comparative advantage under a number of scenarios.     

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.     

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.     

Recent weather fluctuations and agricultural yields: implications for climate change

We summarize recent statistical analyses that link agricultural yields to weather fluctuations. Similar to other sectors, high temperatures play a crucial role in predicting outcomes. Climate change is predicted to significantly increase high temperatures and thereby reduce yields. How good are such models at predicting future outcomes? We show that a statistical model estimated using historic US data on corn and soybean yields from 1950 to 2011 is very capable of predicting aggregate US yields for the years 2012–2015, where 2012 was much hotter than normal and is expected to become the new normal under climate change. We conclude by discussing recent studies on the implication of predicted yield declines with a special focus on adaptation and commodity prices.     

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.     

Warming temperatures will likely induce higher premium rates and government outlays for the U.S. crop insurance program

Likely climate change impacts include damages to agricultural production resulting from increased exposure to extreme heat. Considerable uncertainty remains regarding impacts on crop insurance programs. We utilize a panel of U.S. corn yield data to predict the effect of warming temperatures on the mean and variance of yields, as well as crop insurance premium rates and producer subsidies. While we focus on corn, we demonstrate that the subsidy impacts are likely to carry over to other major program crops. We find that warming decreases mean yields and increases yield risk on average, which results in higher premium rates. Under a 1°C warming scenario, we find that premium rates at the 90% coverage level will increase by 39% on average; however, there is considerable statistical uncertainty around this average as the 95% confidence interval spans from 22% to 61%. We also find evidence of extensive cross‐sectional differences as the county‐level rate impacts range from a 10% reduction to a 63% increase. Results indicate that exposure to extreme heat and changes in the coefficient of variation are large drivers of the impacts. Under the 1°C warming scenario, we find that annual subsidy payments for the crop insurance program could increase by as much as $1.5 billion, representing a 22% increase relative to current levels. This estimate increases to 3.7 billion (57%) under a 2°C warming scenario. Our results correspond to a very specific counterfactual: the marginal effect of warming temperatures under current technology, production, and crop insurance enrollments. These impacts are shown to be smaller than the forecasted impacts under a commonly used end‐of‐century general circulation model for even the most optimistic CO₂ emissions projection.     

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.     

Impacts of changing water inflow distributions on irrigation and farm income along the Drâa River in Morocco

Irrigation water is essential for agriculture in the arid Drâa River basin in Morocco but climate change leads to increasingly unreliable water supply in the area. This article analyzes impacts of changing water inflow distributions on irrigation and farm income extending a conjunctive river basin model toward a stochastic modeling approach. Regional climate scenarios are used to derive a maximum likelihood density estimate of current and future water supplies. Based on these distributions, Monte Carlo simulations are performed to obtain stochastic model results on surface and groundwater irrigation as well as economic indicators for six oases along the river. The probability of farmers to receive revenues below the subsistence level is around 2% under current conditions, but this is likely to rise to rates of 6% to 15% depending on the underlying climate change scenario. The composition of water sources for irrigation will shift to more groundwater use. The river basin model is able to represent complex spatial interactions between oases as well as a partial complementarity between groundwater and surface water irrigation due to salinity management effects. Interestingly, the value of groundwater is not necessarily increasing under future climatic conditions as salinity problems are aggravated with expanded groundwater use.     

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.     

Impacts of prices and transactions costs on input usage in a liberalizing economy: evidence from Tanzanian coffee growers

Despite improvements in production incentives, agricultural output in Africa remained sluggish through the 1990s. Low use of purchased inputs may be part of the cause of persistently low productivity in African agriculture. This article analyzes the roles of relative prices and transactions costs in explaining low use of chemical inputs among Tanzanian coffee growers. A sample selection model indicates that output prices exert great influence on input purchases and that both fixed and variable transactions costs affect input use decisions. Travel costs in input and output markets have distinct effects on input usage, implying distinct avenues for interventions to promote more intensive use of agricultural inputs.     

Impacts of climate change on lower Murray irrigation*

This article evaluates irrigated agriculture sector response and resultant economic impacts of climate change for a part of the Murray Darling Basin in Australia. A water balance model is used to predict reduced basin inflows for mild, moderate and severe climate change scenarios involving 1, 2 and 4°C warming, and predict 13, 38 and 63% reduced inflows. Impact on irrigated agricultural production and profitability are estimated with a mathematical programming model using a two‐stage approach that simultaneously estimates short and long‐run adjustments. The model accounts for a range of adaptive responses including: deficit irrigation, temporarily following of some areas, permanently reducing the irrigated area and changing the mix of crops. The results suggest that relatively low cost adaptation strategies are available for a moderate reduction in water availability and thus costs of such a reduction are likely to be relatively small. In more severe climate change scenarios greater costs are estimated. Adaptations predicted include a reduction in total area irrigated and investments in efficient irrigation. A shift away from perennial to annual crops is also predicted as the latter can be managed more profitably when water allocations in some years are very low.