Geography of crop yield skewness

Analysis of crop yield distributions provides insights into better understanding how natural resources shape agricultural productivity. This study seeks to provide a rigorous theoretical and empirical understanding of the effects of exogenous geographic and climatic factors on the first three moments of crop yields with focus on the third moment. We hypothesize that exogenous factors having beneficial effects on crop production should make crop yield distributions less positively or more negatively skewed. We employ a large crop insurance data set for corn, soybean, and wheat to find general support for our natural‐resources‐determines‐skewness hypothesis. The proposed statistical method optimally uses correlations between the first three moments. It significantly improves estimation performance over existing methods, including the linear moment model which has been commonly applied in the literature.     

Crop Input Response Functions with Stochastic Plateaus

Agronomic research on crop response to nitrogen fertilizer suggests that a plateau function may be appropriate, but the plateau varies across fields and years. Available models that treat the plateau as a stochastic variable are not readily extendable to handle field or year random effects as seems to be appropriate based on the agronomic data. This article develops a method of estimating a response function with a stochastic plateau that can capture random effects. The method is then used to determine economically optimal levels of nitrogen fertilizer for wheat ( Triticum aestivum ).     

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.     

Mitigating rice production risks from drought through improving irrigation infrastructure and management in China

Rice, China's most important food crop, is highly dependent on irrigation, but an increasing number of extreme drought events have challenged rice production in many regions. This paper investigates the role of local irrigation infrastructure in improving farmers' ability to respond to drought and its effectiveness in mitigating the drought risk in rice production in China. The analysis relies on a moment‐based specification of the stochastic production function, capturing mean, variance and skewness effects. Using household survey data from 86 villages in five provinces, we jointly estimate farmers' adaptive irrigation decisions and their effects on rice yield and production risk. Our econometric analyses show that irrigation infrastructure in villages contributes to enhancing farmers' irrigation capacity in adapting to drought, and increased irrigation leads to a significant increase in mean yield and a reduction in exposure to risk as well as downside risk in rice production. The paper concludes with policy implications.     

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.     

An economic approach to soil fertility management for wheat production in north-eastern Australia

Soil fertility decline and soil management for crop production are important economic issues for grain growers in north-eastern Australia. In that region, there is evidence of soil fertility decline which is attributed to past crop management practices. The questions addressed in this article are first, whether components of soil fertility can be improved by better management and second, by how much soil fertility would change. Soil fertility for crop production is considered in terms of soil organic carbon and nitrogen. A stochastic dynamic economic analysis of soil fertility management for wheat production is presented. A sequential analysis of first deriving the optimal nitrogen stock and application rates is followed by an assessment of tillage, stubble, and fertilizer strategies to obtain an optimal level of soil organic carbon. The recommended management practices are consistent with emerging management trends in the region. The derivation of optimal levels of soil fertility for agricultural purposes has other policy implications, which we discuss.     

The impact of climate and price risks on agricultural land use and crop management decisions

This article aims to investigate the impacts of climate change and of lower and more volatile crop price levels as currently observed in the European Union (EU) on optimal management decisions, average income and income risks in crop production in Western Switzerland. To this end, a bioeconomic whole-farm model has been developed that non-parametrically combines the crop growth model CropSyst with an economic decision model using a genetic algorithm. The analysis focuses on the farm level, which enables us to integrate a wide set of potential adaptation responses, comprising changes in agricultural land use as well as crop-specific fertilization and irrigation strategies. Furthermore, the farmer's certainty equivalent is employed as objective function, which enables the consideration of not only impacts on average income but also impacts on income variability.The study shows that that the effects of EU crop prices on the optimal management decisions as well as on the farmer's certainty equivalent are much stronger than the effects of climate change. Furthermore, our results indicate that the impacts of income risks on the crop farm's optimal management schemes are of rather low importance. This is due to two major reasons: first, direct payments make up a large percentage of the agricultural income in Switzerland which makes Swiss farmers less vulnerable to market and climate volatility. Second, arable crop farms in Switzerland have by law to cultivate at least four different crops. Due to these diverse cropping systems and high government direct payments risk does neither under climate change, market liberalization nor combinations thereof, play a very decisive role in arable farming in Switzerland.     

氮肥减量及秸秆替代过量氮肥下冬小麦/夏玉米轮作体系氮素淋失风险研究

针对过量施用氮肥和地下水硝酸盐超标的现状,探索减量施氮、秸秆替代过量氮肥下土壤氮素的淋失风险,以期为降低氮素淋失风险提供科学依据。通过在河北省徐水县进行连续4年的冬小麦—夏玉米轮作体系田间定位试验,分析耕作(少耕和常规耕作)、施氮量(无机氮0、200和300 kg/hm~2)和秸秆(还田、不还田)等措施对作物收获后土壤无机氮累积、土壤—作物体系氮平衡状况以及冬小麦和夏玉米产量的影响。结果表明,小麦收获后,过量施氮处理0~100 cm土壤硝态氮累积量显著高于其它处理,高达221 kg/hm~2,过高的土壤残留硝态氮增加玉米高温多雨季氮素淋洗风险。3年氮平衡累积量比较显示,过量施氮、少耕/常规耕作减量施氮秸秆还田3处理的氮平衡值无显著性差异,以少耕减量施氮秸秆还田最低,为236 kg/hm~2,过量施氮处理最高,为281 kg/hm~2,三者均显著高于少耕/常规耕作减量施氮秸秆不还田处理。冬小麦—夏玉米轮作体系氮平衡值与0~100 cm土层的土壤无机氮、土壤硝态氮累积量呈显著正相关,说明氮素大量盈余会导致0~100 cm土壤剖面无机氮大量累积,尤其是硝态氮大量累积。少耕和常规耕作减量施氮秸秆还田处理的冬小麦、夏玉米产量与过量施氮无显著差异。综合考虑土壤无机氮累积量、氮平衡值和作物产量,少耕或者常规耕作下,可以利用秸秆氮替代过量无机氮,降低氮素淋洗风险。     

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.     

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.     

The genetic and economic impact of the CIMMYT wheat breeding program on local producers in the Yaqui Valley,Sonora Mexico

This article quantifies the productivity gain from CIMMYT‐released semidwarf bread wheat (Triticum aestivum) cultivars over time, using test plot data from Mexico's Yaqui Valley. Previous studies have shown a deceleration in irrigated wheat yield growth since the 1980s, which could be due to slowing increase in genetic potential. Our results suggest that CIMMYT cultivars contributed a 0.46% annual increase (about 38 kg/ha annually) to wheat yields in the Yaqui Valley, which raised local wheat producers’ revenue by an average of $4 million annually for the period 1990 to 2002, and by approximately $9 million in 2002.     

Impact of contract farming on yield,costs and profitability in low‐value crop: evidence from a low‐income country

Lentils, a low‐value and highly nutritious crop, are Nepal's largest pulse cash crop. However, the majority of the nation's smallholders produce lentils on very small plots of land. The large gap in lentil yields between Nepal and other lentil‐producing countries underscores the importance of improving yields and income of smallholders. When it comes to the financial viability of small farms, particularly in developing countries, and globalisation, contract farming (CF) may prove useful in achieving efficiency and profitability in smallholder lentil farms in Nepal. This study employs the propensity score matching approach to examine the effects of the adoption of CF on yields, profitability and costs of smallholder lentil farms in Nepal. Findings from this study reveal that contrary to popular belief, CF adoption by lentil producers in Nepal has a positive and significant effect on per‐hectare revenues, profits and yield and a negative impact on variable and transportation costs. The study finds that only very smallholder lentil farms (0.01‐0.05 ha) benefit from CF.     

An Evaluation of the Actuarial structure of manitoba crop Insurance Program and its Implications

Very little research has been done in evaluating the basic principles and assumptions of the actuarial structure for premium ratemaking in crop insurance programs. Therefore, the objectives of this study are: (a) to examine the Pearson probability distribution of actual crop yields as compared with an application of normal-curve theory to crop yields as compared with an application of normal-curve theory to crop yield distributions and in turn to crop insurance ratemaking which was suggested by Botts and Boles in 1958 [1]; (b) to evaluate the pure premium rates derived from estimated Pearson probability distributions for wheat yields in 14 crop districts of the province of Manitoba; and to establish an experience rating system for the crop insurance program based upon the estimated Pearson distribution of actual crop yields on the individual farm.     

Hierarchical Bayesian Estimation of a Stochastic Plateau Response Function: Determining Optimal Levels of Nitrogen Fertilization

This article seeks to determine the optimal level of nitrogen to apply to winter wheat. The article makes two methodological contributions. One is to extend the estimation of a stochastic plateau function to the case where the plateau has a beta distribution instead of a normal distribution. The second is to adapt hierarchical Bayesian methods as an alternative to the frequentist approach to estimate wheat yield response to nitrogen fertilizer. The economically optimal rate of nitrogen varies between 64 and 169 kg/ha and is consistently higher with the Bayesian method and higher under most scenarios when nonnormality is assumed for the plateau parameter. Based on the likelihood odds ratio, the normal distribution is preferred with maximum likelihood estimation. But, based on the deviance information criterion, the beta model is preferred with the Bayesian estimation. Cet article a pour objectif de déterminer le niveau optimal d'azote à appliquer au blé d'hiver. L'article apporte deux contributions méthodologiques. L'un consiste à étendre l'estimation d'une fonction de plateau stochastique au cas où le plateau a une distribution bêta au lieu d'une distribution normale. La seconde consiste à adapter les méthodes bayésiennes hiérarchiques comme alternative à l'approche classique pour estimer la réponse du rendement du blé à l'engrais azoté. Le taux d'azote économiquement optimal varie entre 64 kg ha‐1 et 169 kg ha‐1 et est toujours plus élevé avec la méthode bayésienne et plus élevé dans la plupart des scénarios lorsque la non‐normalité est supposée pour le paramètre plateau. Selon le rapport de probabilité, la distribution normale est préférée avec l'estimation du maximum de vraisemblance. Mais, en fonction du critère d'information de déviance, le modèle bêta est préféré en utilisant la méthode d'estimation bayésienne.     

Wheat variety yield data: Do commercial and public performance tests provide the same information?

Wheat yields from reported performance test results are of economic importance to wheat producers, since their profits depend on selecting the optimal variety for their location. However, our data shows differences in absolute and relative wheat yields between commercial and public wheat breeding program's performance test data in Kansas. Newly available data are used to test if the difference in yields arose from potential selectivity bias, and to determine the contribution of private and public wheat breeding programs to varietal yield improvement during 2007–2012. Both Heckman selection models and multiple regression showed no statistical evidence of the potential presence of selectivity bias rather, managerial practices, agronomic conditions, field location, and inherent genetic traits of the seed variety were identify as the source of yield differences.     

Time‐varying Hedge Ratios: A Principal‐agent Approach

We use the classic agency model to derive a time‐varying optimal hedge ratio for low‐frequency time‐series data: the type of data used by crop farmers when deciding about production and about their hedging strategy. Rooted in the classic agency framework, the proposed hedge ratio reflects the context of both the crop farmer's decision and the crop farmer's contractual relationships in the marketing channel. An empirical illustration of the Dutch ware potato sector and its futures market in Amsterdam over the period 1971–2003 reveals that the time‐varying optimal hedge ratio decreased from 0.34 in 1971 to 0.24 in 2003. The hedging effectiveness, according to this ratio, is 39%. These estimates conform better with farmers’ interest in using futures contracts for hedging purposes than the much higher estimates obtained when price risk minimisation is the only objective considered.     

Does carbon farming provide a cost‐effective option to mitigate GHG emissions? Evidence from China

In this study, we apply a whole farm bioeconomic analysis to explore the changes in land use, farm practices and on‐farm greenhouse gas (GHG) emission under varying levels of agricultural greenhouse gas abatement incentives in the form of a carbon tax for a semi‐arid crop‐livestock farming system in China's Loess Plateau. Our results show that the optimised agricultural enterprises move towards being cropping‐dominated reducing on‐farm emission since livestock perform is the major source of emission. Farmers employ less oats‐based and rapeseed‐based rotations but more dry pea‐based rotations in the optimal enterprise mix. A substantial reduction in on‐farm greenhouse gas emission can be achieved at low cost with a small increase in carbon incentives. Our estimates indicate that crop‐livestock farmers in China's Loess Plateau may reduce their on‐farm GHG emission between 16.6 and 33 per cent with marginal abatement costs <￥100/t CO₂e and ￥150/t CO₂e in 2015 Chinese Yuan. The analysis implies that reducing greenhouse gas emission in China's semi‐arid crop‐livestock agriculture is potentially a low‐cost option.     

The rise and fall of public sector plant breeding in the United Kingdom: a causal chain model of basic and applied research and diffusion

This paper examines the barley and wheat breeding programmes of the Plant Breeding Institute (PBI), which was the most successful public plant breeding institute in the UK, until privatization in 1987. The PBI's shares in barley and wheat seed sales are explained, showing that the success with barley was largely a matter of serendipity, whereas the wheat programme followed a more normal pattern. For wheat, the causal chain, or recursive, model decomposes the well-documented link between research expenditures and increases in agricultural productivity into three stages. These are the effects of R&D expenditures on basic research output, measured by publications, the effect of publications and applied R&D expenditures on trial plot yields, and the diffusion of the trial plot technologies, which raises yields on farms. Applying the model to the FBI's wheat varieties allows estimation of the lag structures. In contrast to the results for aggregate agricultural research, for a single plant breeding programme alone there is a considerable lead time before there is any response, followed by a lag distribution only a few years long. The returns to the R&D investments are calculated from the causal chain model, from single equation estimates and by evaluating the yield advantage of the PBI varieties. All three approaches give consistent results, which show that the returns to barley and wheat alone were sufficient to support the entire PBI budget and still give rates of return to applied research of between 14 and 25%. The return to the basic science expenditures of the John Innes Institute has a lower bound of 17%, but must have been even higher than for the PBI if the other Institutes were taken into account. The paper concludes by commenting on the effects of the privatization of the PBI.     

Tropospheric Ozone and Winter Wheat Production in England and Wales: A Note

Tropospheric ozone is an air pollutant thought to reduce crop yields across Europe. Much experimental scientific work has been completed or is currently underway to quantify yield effects at ambient ozone levels. In this research, we seek to directly evaluate whether such effects are observed at the farm level. This is done by intersecting a farm level panel dataset for winter wheat farms in England & Wales with information on ambient ozone, and estimating a production function with ozone as a fixed input. Panel data methods, Generalised Method of Moments (GMM)techniques and nested exogeneity tests are employed in the estimation. The results confirm a small, but nevertheless statistically significant negative effect of ambient ozone levels on wheat yields.     

A meta-analysis of intercropping in Africa: impacts on crop yield,farmer income,and integrated pest management effects

Poverty and hunger in Africa are prevalent and will increase in absolute terms with population growth and continued land degradation. Therefore, there is a need for sustainable agricultural strategies, such as conservation agriculture (CA) and integrated pest management (IPM). Among CA practices, intercropping holds the promise of providing benefits to smallholders through increased crop yields and income as well as improved resource use. We review intercropping’s effects on crop yield, income, and output of IPM practices in Africa. On average, intercropping increases crop yields by 23% and gross income by 172 USD/ha, but effects vary significantly depending on management practices and agro-ecological factors. There was no evidence that yields and gross income for intercropping treatments increase when leguminous intercropping combinations, minimum/reduced tillage, pesticides, or fertilizers were utilized. Dual use of herbicides and intercropping practices garnered 1442 USD/ha more in gross income and yielded 1422 kg/ha more compared to those in conventionally managed fields, signifying the positive influence supplemental inputs can have on intercropping’s effects. Although IPM practices increased yields by 20%, on average, IPM systems integrated with intercropping yielded 24% less than IPM systems that did not. This meta-analysis indicates that intercropping is an advantageous sustainable agricultural practice, but that its effective implementation would depend on considering other factors such as adequate control of competing vegetation. There is a clear need for more scientific studies which examine intercropping’s role in complex sustainable agricultural systems, in order to understand its effects in differential environmental and socioeconomic situations and to optimize the practice’s transfer and benefits.