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.     

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.     

Soil and water conservation technologies: a buffer against production risk in the face of climate change? Insights from the Nile basin in Ethiopia

This study investigates the impact of different soil and water conservation (SWC) technologies on the variance of crop production in Ethiopia to determine the risk implications of the different technologies in different regions and rainfall zones. Given the production risks posed by climate change, such information can be used by decision makers to identify appropriate agricultural practices that act as a buffer against climate change. Results show that SWC investments perform differently in different rainfall areas and regions of Ethiopia and that the effectiveness of technologies such as irrigation, fertilizer, and improved seeds often depends on whether these investments are coupled with SWC measures. These results underscore the importance of the selection of appropriate combinations of technologies and careful geographical targeting when promoting and scaling up SWC technologies for adaptation to climate change.     

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.     

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.     

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.     

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.     

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.     

Tenure security, resource poverty, public programs, and household plot-level conservation investments in the highlands of northern Ethiopia

Land degradation poses a serious problem for the livelihoods of rural producers. Furthermore, there is rarely enough private investment taking place to commensurate the scale of the problem. This article examines the role of tenure insecurity, resource poverty, risk and time preferences, and community‐led land conservation on differentiated patterns of household investment in land conservation in northern Ethiopia. We control for biophysical, household characteristics, market access conditions, and village level factors. Investments in soil bunds and stone terraces are specifically studied so as to capture the link between these various factors and the durability of conservation investments. We introduce the distinction between the determinants of the decision to invest and how much to invest in conservation. Regression results show that publicly led conservation programs seem to significantly stimulate private investment. A host of plot‐level variables and household perceptions of returns on conservation investments, expressed in terms of perceived improvements in land quality and increased crop yields, were found to be critical to the decision to invest and intensify soil conservation. The evidence on the significance of households' attitudes toward risk aversion suggests the important role of risk and the household's risk‐bearing capacity in the decision to intensify conservation measures. At the same time, tenure security indicators and households' resource endowments (resource poverty) had weaker effects in increasing willingness to invest and the level of investment made. The policy implications of these results point to the importance of agricultural research and extension efforts that target technologies which reduce household risk and poverty while enabling sustainable investments in conservation measures by individual households.     

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.     

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.     

Motivations to grow energy crops: the role of crop and contract attributes

Perennial energy crops are a promising source of bioenergy whose production involves production risks, long‐term commitment of land and need for crop‐specific investments without the coverage of crop insurance potentially available for conventional crops. We conduct a choice experiment in five states in the Midwestern and South‐central regions of the U.S. to examine the effect of crop‐contract attributes on the joint discrete‐continuous choice decisions to adopt an energy crop and convert acres to it from a status quo use, while controlling for the effect of various farmers’ risk and time preferences, sociodemographic characteristics, and availability of crop insurance for conventional crops. We find robust evidence that high discount rates, high upfront establishment costs and need for crop‐specific investments create disincentives for adoption and allocation of land to energy crop production. The effects of riskiness of returns and risk aversion are less robust across specifications. The effect of conventional crop insurance on the energy crop adoption decision differs across types of insurance; in particular, farmers with revenue insurance are statistically significantly less likely to adopt an energy crop. Our results have implications for the design of effective contracts and policy incentives to induce the production of energy crops.     

Small U.S. dairy farms: can they compete?

The U.S. dairy industry is undergoing rapid structural change, evolving from a structure including many small farmers in the Upper Midwest and Northeast to one that includes very large farms in new production regions. Small farms are struggling to retain competitiveness via improved management and low‐input systems. Using data from USDA's Agricultural Resource Management Survey, we determine the extent of U.S. conventional and pasture‐based milk production during 2003–2007, and estimate net returns, scale efficiency, and technical efficiency associated with the systems across different operation sizes. We compare the financial performance of small conventional and pasture‐based producers with one another and with large‐scale producers. A stochastic production frontier is used to analyze performance over the period for conventional and pasture technologies identified using a binomial logit model. Large conventional farms generally outperformed smaller farms using most economic measures—technical efficiency, various profitability measures, and returns to scale.     

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.     

Farm-level adaptation to climate change in Western Bangladesh: An analysis of adaptation dynamics,profitability and risks

Using long-term district-level climate data and a case study from a drought-prone village in western Bangladesh, this research explored trends in climate change, and analysed farmers’ adaptation dynamics, profitability and risks. This is the first study of its kind for drought-prone areas in Bangladesh.Farmers perceived climate changes included increases in temperature and decreases in rainfall which were as consistent with the trends of Chuadanga climate records. Farmers’ adaptation measures included changes in cropping systems, cropping calendars, crop varieties, agronomic practices, crop diversification and improved animal husbandry. Reducing environmental stress, ensuring self-sufficiency in staple crops (mainly rice) and other crop production practices, and enhancing economic viability of farm enterprises have underpinned these adaptations. Off-farm and non-farm wage employment, temporary migration, self-employment and educating children, constituted the core non-farm adaptation strategies.Emerging cropping systems like maize/cucumber and maize/stem amaranth/rice were economically more viable than the traditional rice/rice and rice/maize systems. Despite some uncertainties, farming was preferred to off-farm work, generating higher returns to labour for all cropping systems. Limited access to stress-tolerant varieties, extension services and affordable agricultural credit, combined with high production costs, variability in crop yields and output prices, are the main barriers to adaptation. Stronger agricultural research and support services, affordable credit, community-focussed farming education and training are critically important for effective adaptation to climate change.     

Did the Federal Crop Insurance Reform Act Alter Farm Enterprise Diversification?

We estimate how much United States farms changed enterprise diversification in response to a marked increase in crop insurance coverage brought about by the 1994 Federal Crop Insurance Reform Act, which substantially increased insurance subsidies. The analysis exploits farm‐level panel census data to compare farm‐specific changes in enterprise diversification over time. By examining diversification decisions of the same farms over time, we control for time‐invariant unobserved individual heterogeneity. We then use pooled cross‐sectional data from the United States Department of Agriculture (USDA) Agricultural Resource Management Survey to estimate the relationship between farm diversification and average returns. We find that the insurance subsidies caused a modest increase in enterprise specialisation and production efficiency. Estimated efficiency gains are far less than the subsidies.     

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.     

Climate change impacts on investment in crop sowing machinery*

A model of investment in crop sowing machinery is applied to wheat production under current and projected climatic conditions at several locations in south‐western Australia. The model includes yield responses to time of sowing at each location given current and projected climatic conditions. These yield relationships are based on wheat growth simulation modelling that in turn draws on data from a down‐scaled global circulation model. Wheat price distributions and cost of production data at each location, in combination with the time of sowing yield relationships are used to determine a farmer's optimal investment in crop sowing work rate under each climate regime. The key finding is that the impacts of climate change on profit distributions are often marked, yet mostly modest changes in investment in work rate form part of the profit‐maximising response to climate change. The investment response at high versus low rainfall locations mostly involves increases and decreases in work rates, respectively. However, changes to investment in work rate within a broadly similar rainfall region are not always uniform. The impacts of climate change on investments in work rate at a particular location are shown to require knowledge of several factors, especially how climate change alters the pattern of yield response to the time of sowing at that location.     

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.     

Effects of subsidized crop insurance on crop choices

This study focuses on how subsidized crop insurance affects crop choices. Crop insurance may change farm investments by reducing risks and providing subsidies. First, actuarially fair insurance reduces risks in crop production and marketing, holding the expected return constant. Second, insurance subsidies encourage farms to purchase crop insurance, which increases the expected return to insured risky crops. Farms also have many self‐insurance mechanisms such as crop diversification or working off the farm. We derive conditions under which (1) unsubsidized and actuarially fair crop insurance or (2) insurance premium subsidies lead to more investment in a risky higher return crop. We then examine the role of self‐insurance for these conditions. The impact of premium subsidies is decomposed into a direct profit effect and an indirect coverage effect. These effects are explained by substitutions between market insurance and self‐insurance and between a risky crop and a safe crop. We discuss each effect as a combination of subsidy and risk effects. Numerical illustrations show that an insurance subsidy has a larger impact on risky crop investments compared to that of an input subsidy when farms are more risk‐averse and have high costs of self‐insurance. The framework provides a novel way to evaluate subsidized crop insurance programs.