Farmers’ risk preferences and their climate change adaptation strategies in the Yongqiao District,China

Farmers’ risk preferences play an important role in agricultural production decisions. This study characterizes risk preferences among farmers in Yongqiao and determines how these risk preferences are related to their choices regarding climate change adaptation strategies. We find that most farmers in the study area were aware of climate change. They were taking measures to protect their livelihoods against perceived changes to the local climate. The risk experiment result shows that the representative subject was risk averse, and women were more risk averse than men. The relationships between farmers’ risk preferences and different climate change adaptation choices were different. Farmers’ risk aversion was negatively and significantly related with adaptation strategies on planting new crop varieties and adopting new technology, but it had a significantly positive effect on purchasing weather index crop insurance. The results also indicate that the level of education, farming experience, farm size, household income and perception of climate change impacts influence farmers’ adaptation decisions.     

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.     

Evaluating the economic impacts of crop yield change and sea level rise induced by climate change on Taiwan's agricultural sector

This article investigates the effects of sea level rise and climate change induced crop yield alterations on Taiwan as well as possible adaptation strategies. For sea level rise of up to 5 meters, as much as 4.9% of total acreage and 16% of rice acreage would be lost. The empirical findings show that the sea level damages range from NT$ 0.84 to 4.10 billion while crop yield losses range from NT$ 1.79 to 2.55 billion. We investigate alternative adaptation strategies finding crop yield technological progress and tariff reduction could significantly mitigate these effects.     

Understanding the adoption of climate change adaptation strategies among smallholder farmers: Evidence from land reform beneficiaries in South Africa

Climatic change has a negative impact on people’s livelihoods, agriculture, freshwater supply and other natural resources that are important for human survival. Therefore, understanding how rural smallholder farmers perceive climate change, climate variability, and factors that influence their choices would facilitate a better understanding of how these farmers adapt to the negative impacts of climate change. A Zero-inflated double hurdle model was employed to estimate the factors influencing farmers’ adoption of adaptation strategies and intensity of adoption at the household level in South Africa. Different socioeconomic factors such as gender, age, and experience in crop farming, institutional factors like access to extension services, and access to climate change information significantly influenced the adoption of climate change adaptation strategies among beneficiaries of land reform in South Africa. Concerning intensity of adoption, age, educational level, farming experience, on-farm training, off-farm income, access to information through ICT and locational variables are the significant determinants of intensity of adaptation strategies. Thus, education attainment, non-farm employment, farming experience are significant incentives to enhance smallholder farmers' adaptive capacity through the adoption of many adaptation approaches. This study therefore concluded that farm-level policy efforts that aim to improve rural development should focus on farmers’ education, on-farm demonstration and non-farm employment opportunities that seek to engage the farmers, particularly during the off-cropping season. The income from non-farm employment can be plough-back into farm operations such as the adoption of soil and water conservation, use of improved planting varieties, insurance, among others to mitigate climate variability and subsequently increase productivity. Policies and investment strategies of the government should be geared towards supporting education, providing on-farm demonstration trainings, and disseminating information about climate change adaptation strategies, particularly for smallholder farmers in the country. Thus, the government, stakeholders, and donor agencies must provide capacity-building innovations around the agricultural extension system and education on climate change using information and communication technologies.     

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.     

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.     

Measuring impacts and adaptations to climate change: a structural Ricardian model of African livestock management1

This article develops a new cross‐sectional methodology that explicitly incorporates adaptation into an analysis of the impacts of climate change. The methodology examines how a farmer will change choices of species and number to adapt to climate. The approach is applied to study Africa, where the impacts of climate change are expected to be the most severe. The results indicate that in warmer places, African farmers switch from beef cattle to more heat‐tolerant goats and sheep. In wetter places, farmers switch from cattle and sheep to goats and chickens. The results indicate that large commercial livestock operations specializing in beef cattle will be hard hit from climate change whereas small farmers who can easily substitute to goats and/or sheep will be more resilient.     

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.     

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.     

Does social capital matter in climate change adaptation? A lesson from agricultural sector in Yogyakarta,Indonesia

Climate change increases the vulnerability of agricultural sector due to the increasing threat from pest attacks. Mitigation of a threat that results from climate change requires adaptation strategies. This study investigates farmers’ willingness to participate in the process of climate change adaptation in Yogyakarta, Indonesia; particularly in facing the increasing risk of pest attacks. Using a logistic regression model, we tested the impacts of social capital on farmers’ willingness to participate. The results showed that 70% of farmers were willing to contribute financially to the adaptation process. This participation was positively correlated with high social capital, which consists of high level of trust, community engagement, and personal relations with people in other villages. This study contributes to the literature by highlighting the potential roles of social capital in the process of climate change adaptation in agricultural sector.     

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.     

Agriculture and climate change in global scenarios: why don't the models agree

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.     

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.     

Payments for environmental services to promote “climate‐smart agriculture”? Potential and challenges

Payments for environmental services (PES) have gained wide popularity as approaches to promote environmentally friendly land use or agricultural production practices. Yet academics have also voiced concerns against seeing PES as a panacea. This article discusses whether PES is an appropriate and promising approach to promote so‐called “climate‐smart agriculture” (CSA) practices, which we define as agricultural production practices that contribute to CO₂ emission reductions and/or removals and provide benefits to farmers via increased productivity and profits and reduced vulnerability to climate change. PES appears most promising for the promotion of CSA practices in small‐scale farming contexts with low incomes. Effective design, however, requires solid estimates of cost and benefit flows from CSA adoption over time, accounting for differences in socioeconomic and ecological conditions, and addressing the risk of leakage. Funding for such PES will likely have to come from public sources, and seems most promising where synergies with other objectives such as agricultural development, food security, and climate adaptation or other environmental services exist. The potential of alternative approaches for CSA support such as taxation with rebates for CSA practices, CSA‐related investment support such as microcredits, and hybrid approaches such as conditional microcredit should be further investigated.     

How collective efficacy makes a difference in responses to water shortage due to climate change in southwest Iran

Climate change impacts the water sector in a manner that reduces the harvest and income of farmers, thereby exacerbating poverty and many other social problems. However, through adaptation measures, farmers can manage climate change impacts and thus reduce their vulnerability. To design effective public adaptation strategies, it is crucial to understand farmers’ behaviors at the farm level in response to water shortage due to climate change. Thus, the aim of this research is to accrue empirical evidence about farmers’ perceptions of and responses to water shortage due to climate change, using the Protection Motivation Theory. To increase the predictive power of the model, this paper added the collective efficacy variable to the model. The population of interest consisted of farmers from Shushtar, a county in Khuzestan Province, southwestern Iran. A total of 251 farmers were selected using a multi-stage, clustered, random sampling method. The results of structural equation modeling revealed that model variables accounted for 39 % of variance in farmers’ adaptation behaviors. The inclusion of collective efficacy in the original model increased its predictive power and produced a model of a better fit; the proportion of variance accounted for an increase of about 11 %. These findings are expected to yield recommendations for public policy, as well as agricultural extension and education recommendations for stimulating successful adaptation behaviors among Iranian farmers.     

Distributional heterogeneity in climate change impacts and adaptation: Evidence from Indian agriculture

This study estimates the distributional heterogeneity in the effects of climate change on yields of three major cereal crops: rice, maize, and wheat in India using district-level information for the period 1966–2015. We distinguish between the effects of changes in growing season weather from those due to changes in long-term climate trends and the heterogeneity in these effects across the distribution of crop yields by estimating naïve and climate penalty inclusive models using fixed-effect quantile panel models. We observe an absence of adaptation against rising temperatures for rice and wheat. However, we find a statistically significant presence of adaptation for wheat and maize for changes in precipitation, though the magnitude is small. Moreover, we find that the effects are asymmetric, and are larger at the lower tail of productivity distribution and smaller at the upper tail of the distribution. A 1°C increase in temperature lowers rice and wheat productivity by 23% and 9%, respectively at the first quantile, but the damage is only 6% and 5% at the ninth quantile. Heterogeneity in impacts and adaptation estimates over the yield distribution curve and across crops suggests the importance of customizing strategies for adaptation to changing weather and climate conditions across regions, crops, and current productivity levels.     

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.     

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.     

Determinants of climate change adaptation strategies and its impact on the net farm income of rice farmers in south-west Nigeria

A multivariate probit (MVP) model was used to analyse the determinants of strategies adopted for adapting to climate change in a sample of smallholder rice farmers in south-west Nigeria. An efficient endogenous switching regression model (ESRM) was used to estimate the impact of climate change adaptation strategy on the net income of rice farmers. The MVP results show that the socio-economic factors, the institutional factors, and locational variables of some households statistically influenced the choice of climate change adaptation strategies employed. Complementarities among all the adaptation strategies used by the farmers were revealed by the positive pair-wise correlation matrix of the MVP model. The study also indicated that farmers affected by prolonged drought and incidences of flood were more likely to adopt adaptation strategies on their farmlands. The ESRM treatment effect indicated that the average net income per rice farm of those who adopted the strategies was significantly higher than that of those who did not. Thus, the government, stakeholders, and donor agencies must provide capacity-building innovations related to agricultural extension systems and climate change education through information and communication technologies. This investment in education is essential for development and would encourage farmers to adopt appropriate climate change adaptation strategies.     

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.