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.     

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.     

Utilising farm-level panel data to estimate climate change impacts and adaptation potentials

We combine farm accounting data with high-resolution meteorological data, and climate scenarios to estimate climate change impacts and adaptation potentials at the farm level. To do so, we adapt the seminal model of Moore and Lobell (2014) who applied panel data econometrics to data aggregated from the farm to the regional (subnational) level. We discuss and empirically investigate the advantages and challenges of applying such models to farm-level data, including issues of endogeneity of explanatory variables, heterogeneity of farm responses to weather shocks, measurement errors in meteorological variables, and aggregation bias. Empirical investigations into these issues reveal that endogeneity due to measurement errors in temperature and precipitation variables, as well as heterogeneous responses of farms toward climate change may be problematic. Moreover, depending on how data are aggregated, results differ substantially compared to farm-level analysis. Based on data from Austria and two climate scenarios (Effective Measures and High Emission) for 2040, we estimate that the profits of farms will decline, on average, by 4.4% (Effective Measures) and 10% (High Emission). Adaptation options help to considerably ameliorate the adverse situation under both scenarios. Our results reinforce the need for mitigation and adaptation to climate change.     

Classical decision rules and adaptation to climate change*

One approach to rationalising policies for addressing potentially catastrophic climate change when such policies may prove unnecessary is to suppose the policies provide a form of social insurance even in the presence of pure uncertainty. Then, provided the policies are effective, such insurance can be justified as a precautionary or minimax response. Even if the policies are potentially ineffective however, intervention can be justified as an attempt to minimise the regret experienced by future generations. This reasoning extends to justify ‘all weather’ policies provided such policies always reduce policy costs. If, however, policy decisions provide ‘all weather’ benefits in only certain states of the world, this rationale breaks down. Minimising regret can establish a case for ‘mixed’ policy responses provided adopting a policy mix precludes the chance that intervention will fail altogether. Precautionary policies and policies which minimise regret are computed for a simple, dynamic, adaptive climate change planning problem and sufficient conditions for policy maker pessimism provided.     

The adoption and impact of engineering‐type measures to address climate change: evidence from the major grain‐producing areas in China

Employing an endogenous switching regression model, we investigate the drivers underlying the adaptations made by farm households and their impacts on crop net incomes for adopters and nonadopters, based on a large panel survey data set across the major grain‐producing provinces in China. The results show that: (i) access to public climate information and technical or physical support increases the likelihood that farmers adapt to climate change by undertaking irrigation and/or drainage measures; and (ii) decisions to adapt increased crop yield, but they did not significantly increase crop profit margins. This point appears to have been ignored by previous studies. Based on these new empirical results, the paper suggests that government should continue to provide climate information and various types of supports to improve farmers’ adaptation abilities and help to reduce the levels of factor input by, for example, substituting organic for chemical fertiliser inputs. Such government‐led policies should be supported alongside the implementation of domestic agricultural supply‐side reform.     

模型模拟华北地区气候变化对冬小麦产量的影响

该文利用IPCC AR4模式资料和基于多年观测资料生成的格点数据,建立降水、最高/最低气温的统计降尺度关系,获取华北地区高分辨率未来气候情景空间分布;利用作物模型模拟IPCC-B1情景下冬小麦生长期和产量变化。结果表明:最高/最低气温模拟结果与观测值比较,相关系数(R2)大于0.70;降水模拟结果与观测值比较,相关系数最小为0.63;IPCC-B1情景下,华北地区冬小麦生长期总体上变短,产量下降。     

Farmers’ risk preferences and pesticide use decisions: evidence from field experiments in China

China faces health and environmental problems associated with the use of agricultural chemicals, including pesticides. While previous studies have found that risk aversion affects pesticide use in China, they have focused primarily on commercial cotton farmers. In this study, we consider the case of smaller, semisubsistence and subsistence farmers in a poor and landlocked province of China (Yunnan). We use a field experiment to measure risk aversion and collect detailed data on farm production and input use to specifically ask whether risk aversion affects pesticide use, and whether this effect differs for subsistence farmers producing exclusively for home consumption versus semisubsistence farmers who produce both for home and the market. We find that risk aversion significantly increases pesticide use, particularly for subsistence farmers and for market plots by semisubsistence farmers. Further, this effect of risk aversion significantly decreases with farm size for subsistence farmers, but not for semisubsistence farmers, implying that pesticide use may be used to ensure sufficient food supply for home consumption. Finally, we find barriers to the use of pesticides for subsistence farmers, both in terms of financial constraints and economies of scale. This finding implies that risk‐mitigation strategies, such as crop insurance, may not target food security concerns of subsistence farmers. Given these different motivations for pesticide use, policymakers may wish to consider effective tools to support rural food security for farmers in the poorer regions of China in order to decrease pesticide 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.     

The importance of ‘extremely unlikely’ events: tail risk and the costs of climate change

In assessing the risks associated with climate change, ‘tail risks’ (low‐probability extreme events) often play a much larger role than their probability alone might indicate. There are three main reasons for this: the linear relationship between sensitivity and warming; the convexity of the damage function; and the concavity of the utility function. Ignoring the upper tail of the distribution of possible outcomes will result in serious underestimates of the social cost of carbon dioxide (CO₂) emissions and of the socially optimal price for emissions.     

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.     

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.     

The impacts of climate change on Australia and New Zealand: a Gross Cell Product analysis by land cover*

This paper examines the newly constructed geographically scaled economic output measure, Gross Cell Product (GCP), of Australia and New Zealand to quantify the impacts of climate change in the region. The paper discusses advantages of using the GCP instead of the Gross Domestic Product. The paper reveals that the GCP falls sharply as temperature increases in the region. A 1°C increase in temperature would decrease the productivity with an elasticity of ?2.4. A 1 per cent decrease in precipitation would decrease productivity with an elasticity of ?2.3. However, forest vegetation on the coasts will benefit from initial warming. We find that the changes in climate means are potentially more harmful than changes in climate variability. In the long term, a 3.4° warming coupled with 6.6 mm decrease in rainfall would decrease the GCP by 34 per cent by 2060. The damage is largely accounted for by population effects. The paper confirms that Australia is highly constrained by climate and geographic factors.     

Climate Risk and Technology Adoption in the Midstream of Crop Value Chains: Evidence from Nigerian Maize Traders

Climate induced events exacerbate food production and distribution risks, posing a threat to global food security. Though many studies focus on farmer adaptation to climate change, there are few studies of actors in the middle of agricultural value chains such as traders, logistics providers, and processors. The activities of these actors, referred to as the ‘hidden middle’, are key determinants of the prices received by farmers and the price and quality of food products for consumers. We explore how climate events and risk perceptions affect the adoption of value‐adding and damage control strategies among maize traders in Nigeria, Africa’s largest economy and most populous country. We find consistent evidence that climate events and climate risk perception discourage the adoption of value‐adding practices including storage. This potentially affects the availability and price of maize for consumers (household and industry) in the lean season. However, once traders store maize, climate risk does not affect the adoption of damage control, but training and social networks do. These findings suggest that actors in the midstream of food value chains are responding to climate change and more attention needs to be paid to these actors to maintain the availability of affordable and safe maize products throughout the year. There is also a need for strategies to reduce the risks of trading activities due to climate change.     

Declining inflows and more frequent droughts in the Murray–Darling Basin: climate change,impacts and adaptation*

It is likely that climate change will be associated with reductions in inflows of water to the Murray–Darling Basin. In this study, we analyse the effects of climate change in the Murray–Darling Basin using a simulation model that incorporates a state‐contingent representation of uncertainty. The severity of the impact depends, in large measure, on the extent to which climate change is manifested as an increase in the frequency of drought conditions. Adaptation will partially offset the adverse impact of climate change.     

Impacts of agricultural price support policy on price variability and welfare: Evidence from China's soybean market

China is a predominant soybean importer; thus, its domestic soybean policies have a large impact on world soybean market dynamics. We develop the first aggregate structural econometric model of China's soybean market and link it to the rest of the world (ROW), which allows us to analyze the impacts of China's soybean price support policy that ran from 2008 to 2013. We investigate the impacts of China's policy on the variability of their domestic and world soybean prices, and adopt a Monte Carlo simulation to evaluate the effects on distributional and aggregate welfare. Our results indicate: (a) after China's soybean price support policy, price transmission elasticity decreases, China's domestic price variability decreases, and world price variability increases; (b) China's producer surplus increases, consumer surplus decreases and the net welfare change in their domestic market is negative; and (c) although soybean exporting countries in the ROW experience significant welfare gains, the world net welfare change is negative.     

Social Capital,Income Diversification and Climate Change Adaptation: Panel Data Evidence from Rural Ethiopia

The choice between specialisation and diversification of income is driven by multiple, interacting factors, such as economies of scale and scope, risk considerations, context, and household characteristics. Using panel data from Ethiopia, we investigate the role of social capital and the covariate risk of climate change and their interaction. We find that households with greater social capital tend to be more specialised, implying that diversification and informal insurance are substitutes in the mitigation of risk. We also find that this effect is significantly weaker in regions more prone to climate change, which is consistent with the average farmer being aware that informal insurance is not an effective protection against risks that affect the entire social network. We use instrumental variable random effects estimation to account for the plausible endogeneity of social capital and we also establish that our results do not depend on the poorest and most constrained individuals in our sample.     

The impact of population growth and climate change on food security in Africa: looking ahead to 2050

Providing nutritious and environmentally sustainable food to all people at all times is one of the greatest challenges currently facing society. This problem is particularly acute in Africa where an estimated one in four people still lack adequate food to sustain an active and healthy life. In this study, we consider the potential impact of future population growth and climate change on food security in Africa, looking ahead to 2050. A modelling framework termed FEEDME (Food Estimation and Export for Diet and Malnutrition Evaluation) was used which was characterized to model the impacts of future climate changes (utilizing the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios projections) and projected population growth on food availability and subsequent undernourishment prevalence in 44 African countries. Our results indicate that projected rapid population growth will be the leading cause of food insecurity and widespread undernourishment across Africa. Very little to no difference in undernourishment projections were found when we examined future scenarios with and without the effects of climate change, suggesting population growth is the dominant driver of change. Various adaptation options are discussed, such as closing the yield gap via sustainable intensification and increasing imports through trade and aid agreements. These strategies are likely to be critical in preventing catastrophic future food insecurity.     

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.     

Barriers and requirements to climate change adaptation of mountainous rural communities in developing countries: The case of the eastern Qinghai-Tibetan Plateau of China

Systematically identifying the barriers and requirements to adaptation is critical to the successful implementation of climate adaptation planning and policies at the local level, especially in the mountainous rural communities of developing countries with limited resources and technology. We conducted an empirical study of the barriers and requirements to adapting to climate change of 539 peasant households in an ecologically vulnerable area of China to enhance their resilience to climate change by improving our understanding of adaptation process and decision-making. Our findings indicated that farmers in the Gannan Plateau face multiple adaptation barriers, of which normative, information and technology barriers were more serious, such as lack of meteorological information service, infrastructure and technology extension in agriculture or animal husbandry. Adaptation requirements are an important way to effectively reduce or eliminate obstacles and improve farmers' adaptive capacity to climate change. The survey found that local households have an urgent requirement for infrastructure, information and production technologies, such as water, electricity, transportation facilities, disaster warning information, employment information and farming or breeding techniques. In addition, due to the influence of economic level, education level, years of farming, gender and other factors, differences exist in the adaptation barriers and requirements faced by farmers in different regions. These findings extend empirical evidence in favor of formulating a reasonable adaptation framework and choosing optimal adaptation strategies, which are essential for enacting well-targeted regional adaptation policies.     

土地供给结构、财政压力与房价——来自广东省的经验分析

研究目的:实证检验地方政府土地供给结构对区域房价的影响。研究方法:在分析土地供给结构影响房价机理的基础上,提出本文的研究假说;基于广东省21个地级及以上城市2009—2015年的统计数据,运用面板数据模型加以检验。研究结果:土地供给结构显著影响房价水平,静态和动态面板数据模型估计表明住宅用地供给比例提高1%,房价分别下降0.126%和0.103%;基础设施用地供给比例提高1个百分点,房价分别上升0.062%和0.051%;工业用地供给比例提高1个百分点,房价则分别上升0.116%和0.110%。地方政府财政压力在土地供给结构与房价的因果链条中起到重要的调节效应,即财政压力越大的地区,提高住宅用地供给比例对房价的抑制效果微弱,而基础设施和工业用地供给比例的增加则对房价的抬升效应更大。研究结论:为抑制过快上涨的房价,保障城市居民住有所居,在加快土地供给侧结构性改革,优化土地供给结构,加大住宅用地供应的同时,也应深化财税体制改革,使地方政府对土地财政的依赖逐步向持有环节的房地产税转变,以降低财政压力对土地供给侧结构性改革抑制房价过快上涨的扭曲效应。