Search

This paper adopts the stochastic frontier production function with double heteroskedasticity to analyze technical inefficiency and production risk of intensive white-leg shrimp farming in Ninh Thuan, Vietnam. The result shows that feed is a risk-increasing input, while chemicals/drugs and electricity are risk-reducing inputs. This implies that an average risk-averse farmer will use less feed and more chemicals/drugs and electricity than a risk-neutral farmer from the study area. However, the results reveal that technical inefficiency is negatively related to feed and chemicals/drugs, and positively related to electricity, farm size, and labor. Moreover, the output elasticity of feed is highest among the inputs in the production mean function. In addition, the statistically negative influences on technical inefficiency in this type of farming are technical training and access to formal credit. Policies on the management of chemicals/drugs and technical training for their use in aquaculture practice should be the focus for Vietnam's intensive white-leg shrimp farming. [ABSTRACT FROM AUTHOR]

The research discusses management strategies for addressing production risks in the polyculture cultivation of milkfish and vaname shrimp in Bulukumba Regency. Effective management is necessary to minimize these risks and optimize profits for business operators. Production risk management is carried out using Value at Risk (VaR) analysis, based on observations and meetings with business operators and fisheries services. This approach helps identify and address sources of production risk in the polyculture of milkfish and vaname shrimp. The findings show that both the probability and impact of risk sources are higher for vaname shrimp than for milkfish. Feed is the largest source of risk for milkfish, while disease poses the greatest risk for vaname shrimp. Conversely, feed is a minor risk factor for vaname shrimp, and disease is a smaller concern for milkfish. Risk mitigation strategies include: (1) carefully monitoring the dosage of saponin poison used to eradicate pests; (2) ensuring the correct dosage and application of urea fertilizer, TSP, and feed; (3) controlling water quality; and (4) selecting high-quality seeds. [ABSTRACT FROM AUTHOR]

Background: One of Indonesia's largest producers of robusta coffee, Lampung Province still faces challenges and risks in coffee productivity. Coffee productivity in Lampung fluctuates and tends to decrease each year. Contract farming is one of the solutions to overcome these issues. Purpose: This research aims to analyze the impact of contract farming on production and production risk in robusta coffee farming in Lampung Province. Design/methodology/approach: The data used in this study is secondary data obtained from the Project Cooperation Agreement (PCA). This research uses a sample size of 99 contract farmers and 104 non-contract farmers. The research analysis method uses the OLS estimation approach to estimate the production function and MLE estimation for the production risk function. Findings/Result: The results showed that contract farming significantly and positively impacts coffee production outcomes. Conversely, contract farming has a significant and positive influence on production risk. Meanwhile, factors that reduce production risk include land area and labor. Contract farming increases production yields, but it also raises production risks. This insight is crucial for farmers considering contract farming, as it underscores the need for comprehensive risk management strategies and productivity enhancements. Conclusion: Contract farming in Lampung has successfully increased coffee production through input assistance and access to technology. However, it has also increased production risks due to the incomplete implementation of contracts by farmers. To mitigate these risks, attention must be given to factors such as land area and labor, which have been proven to reduce production risks. Originality/value (State of the art): Contract farming in Lampung has shown great potential in increasing coffee production. However, the incomplete implementation of contracts by farmers has increased production risks. This study emphasizes the importance of risk management in contract farming. To enhance effectiveness, full implementation of contract terms and better risk management are necessary [ABSTRACT FROM AUTHOR]

Garlic productivity in Indonesia is still low and fluctuates every year. The productivity fluctuations indicate production risks. This research aims to analyze the factors that influence the productivity and risks of garlic production in Indonesia. The data used in this study is secondary data from the Agricultural Census. Locations of this research were chosen purposively. They are in the three largest production centers, namely Central Java, West Nusa Tenggara, and East Nusa Tenggara. The total sample is 305 farmer respondents from 333 farmer respondents surveyed by the Statistic Center Agency. The method of analysis used in this study is production function with the Just and Pope model approach. Multiple linear regression analysis for the productivity function is estimated through the Ordinary Least Squares (OLS) method, whereas, for the production risk function, estimation is conducted using the Maximum Likelihood Estimation (MLE) method. The results showed that the risk level of garlic production in Indonesia was high. Factors significantly increased productivity, including seeds, labor, the dry season, and climate change. Meanwhile, factors that significantly reduced productivity are organic fertilizers and SP36 fertilizers. The risk-inducing production factor is climate change, while the risk-reducing factors are pest attacks and liquid pesticides. To boost productivity, farmers can cultivate garlic during the dry season, increase the use of high-quality seedlings and labor, and reduce the application of organic and SP36 fertilizers. To mitigate production risks, farmers can enhance the use of liquid pesticides following recommended usage standards. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the production and income risks of oil palm plantations in Lubuk Bento Village. This survey was conducted in Lubuk Bento township, Pondok Suguh sub-district, Mukomuko district. The method used was simple random sampling with a sample of 44 farmers out of 290 oil palm farmers in Lubuk Bento Village. Income analysis and CV coefficient of variation studies were used for data analysis. The results showed that the production risk was 0.08 (0.08

The egg production sector in the poultry industry in Kosovo is well developed, with intensive chicken farms that meet 99% of domestic demand (MAFRD, 2021). However, this industry is not without risks. As such, this research investigates the production risks faced by intensive chicken farms.

We examine the effects of the federal crop insurance program on crop production under extreme heat using farm‐level data from Kansas. We find that insured dryland corn is 38% more sensitive to extreme heat than uninsured dryland corn. Results also suggest that a uniform +1° C warming scenario leads to yield reductions of 16.7% (11.8%) for insured (uninsured) corn production; and 6.0% (4.4%) for insured (uninsured) wheat production. Warming had a stronger impact with reduced rainfall, especially on insured farms compared with uninsured farms, while altered growing seasons showed potential benefits for wheat but limited improvements for corn. [ABSTRACT FROM AUTHOR]

Cultivators who manage catfish farming businesses must consider the possibility of low production yields caused by both external and internal variables. The risks that catfish farmers confront may be to blame for the low output. The aims of this study were to determine the source of production risk and the level of risk correlated with catfish production. The method of determining the area of study is carried out intentionally (purposively). This research method is a descriptive and analytical method. The snowball sampling approach was used with a sample of 40 respondents. The data used is a combination of sources both primary and secondary. The analysis used includes variance, standard deviation, coefficient of variation, and risk level based on the risk map. Pests and diseases, weather and climate, the quality of catfish seeds, water quality, cannibalism, and human resources or cultivators who carried out the catfish cultivation process are all factors of production risk in Kediri Regency. The level of risk of catfish production is high, based on the variance value of 21.03, standard deviation of 4.59, and coefficient of variation of 1.61, while the production risk map reveals that the production risk faced by farmers is in the yellow zone, therefore it is included in the high-risk category.

After a successful polymer injection pilot, Ecopetrol plans to deploy at full-field scale this enhanced oil recovery (EOR) technology on the Yariguí-Cantagallo field. Although a significant increase oil production is expected, the impact of the residual polymer on the produced water cycle should not be neglected. Indeed, after the polymer breakthrough, a significant part of the EOR chemical will be present in the produced fluids, and this may negatively impact the water/oil separation and the water treatment processes. An early review of this scenario provides an accurate vision of potential issues and, above all, enables to anticipate handling difficulties with produced fluids, and identifying mitigation strategies. This paper proposes a specific and comprehensive experimental methodology to assess production risks using laboratory equipment designed to mimic the current separation processes of the Yariguí-Cantagallo field, which were as representative as possible. The objective is to highlight the impact of the residual polymer first on water/oil separation processes with bottle tests, electrostatic dehydration tests, and polymer fouling evaluation on heat exchangers and, second, on water treatment using longterm gravity separation tests, Jar test, flotation column, and walnut shell filtration unit. The assessment considered different scenarios in terms of polymer concentration, water-cut, water composition and initial oil content in the produced water. The compatibility between the polymer and some oilfield chemicals, such as demulsifiers and water clarifiers, was also investigated.

Laying hens farming is one of the livestock industries that has the potential to develop in Indonesia. Raising laying hens, like other agricultural and food businesses, has many potential risks in its operations. The purpose of this research is to identify production risk sources, determine the likelihood of production risk in the aying hen business, and develop a management strategy for each source of risk in the laying hen business. A case study of laying hen breeders in Ringinrejo, Kandat District, Kediri Regency, was used as the research method. This location was chosen with care because it is a viable laying hen production area. Descriptive analysis is used to identify risk sources; z-score analysis is used to determine risk probability; and risk mapping is used for analysis to identify mitigation and prevention strategies. The research results show that the sources of risk found in this study are sources of disease risk and sources of drinking water risk. Production risks of significant value are obtained from disease risk sources, which have a probability value of 83.15% and drinking water has a probability of 13.57%. Alternative strategies, recommended for managing sources of disease risk are prevention strategies including the use of antibiotics and vitamins, as well as mitigation strategies implemented to reduce the occurrence of significant impacts by separating chickens identified as having disease and carrying out treatment. In summary, a prevention strategy is proposed by paying attention to drinking water quality raw materials and making efforts to filter the water to make it sterile.

The aim of this study was to investigate the impact of climatic variables (minimum temperature, maximum temperature, average precipitation, and precipitation deviation) on the yields of pistachio, banana, and mango in cold, hot–arid, hot–humid, and temperate–humid climates using the Just–Pope function. The Just–Pope function is a relatively new approach in this context. The most effective variables were identified by stepwise regression and the Feiverson algorithm. Data were collected for the period of 1998–2020 and were tested for stationarity. Finally, the coefficients of the Just–Pope function were estimated for the three crops in the four climates. The results showed that the variables affecting pistachio yield were different in each type of climate. Most variables were effective in warm and dry areas, while cropping area, production trend, and lag were effective in cold regions and in hot and humid areas; the maximum deviation and minimum temperature, production lag, cropping area, and production function were significant in hot and dry regions at the 90% level. The Just–Pope function for pistachio, mango, and banana showed that the impact of temperature and average rainfall was region-specific. Based on the results, a 1% increase in rainfall can increase the banana yield up to 0.032 ton/ha. As Iran experiences extensive climatic fluctuations, horticulturists are faced with difficult conditions. Such practices as the use of cultivars that are resistant to temperature and rainfall variations in the regions in order to alleviate the risk of yield variations in orchards are recommended. [ABSTRACT FROM AUTHOR]

Maize is one of the most versatile emerging crops having wider adaptability under varied agro-climatic conditions. Globally, maize is known as queen of cereals because of its highest genetic yield potential among the cereals. In addition to staple food for human being and quality feed for animals, maize serves as a basic raw material as an ingredient to thousands of industrial products. Growing area under maize and increasing MSP for maize will reflect importance of maize and its multiple benefits. In this study, the growth in area, production and productivity of maize in India and Karnataka and risks associated with maize production in Karnataka were analyzed. The primary data pertaining to study was collected from major maize growing districts of Karnataka and secondary data on area, production and productivity of India and Karnataka was collected from Indiastat.com and the Directorate of Economics and Statistics, Government of Karnataka. Significant growth rates in maize area (1.12), production (3.51) and productivity (2.36) were recorded in India as a whole for the period 1970-2019. The share of maize in total food grain production has increased from 3.40 per cent in 1950-51 to 9.98 per cent in 2020-21. The cumulative annual growth rate of maize area (4.80), production (6.08) and productivity (1.52) has showed positive significant scores in Karnataka. Water scarcity, non-availability of inputs at right time and unstable yield were major risks associated with maize production before the infestation of fall armyworm, but pest and disease, unwanted moisture in the field and low quality of fodder were major risks associated with maize production after the introduction of fall armyworm in the study area. [ABSTRACT FROM AUTHOR]

The agricultural sectors in many low‐ and middle‐income countries remain highly vulnerable to weather risk, a vulnerability that will only intensify under climate change. The globally trending public works programmes have the potential to impact weather‐related agricultural risk. I explore the impact of India's National Rural Employment Guarantee Act (NREGA) on weather‐related agricultural risk. My empirical strategy explores the staggered roll‐out of NREGA and random weather fluctuations. Using a nationwide panel of data, I find that NREGA makes crop yields more sensitive to low rainfall shocks. I posit that these results are consistent with a labour market channel, by which NREGA increases nonfarm labour supply in low rainfall years, and an income channel, by which NREGA leads to riskier agricultural practices. These results highlight the importance of understanding how social protection programmes shape agricultural risk. [ABSTRACT FROM AUTHOR]

𝘛𝘩𝘦 𝘢𝘨𝘳𝘪𝘤𝘶𝘭𝘵𝘶𝘳𝘢𝘭 𝘴𝘦𝘤𝘵𝘰𝘳 𝘪𝘴 𝘢 𝘴𝘦𝘤𝘵𝘰𝘳 𝘵𝘩𝘢𝘵 𝘥𝘦𝘱𝘦𝘯𝘥𝘴 𝘰𝘯 𝘯𝘢𝘵𝘶𝘳𝘢𝘭 𝘤𝘰𝘯𝘥𝘪𝘵𝘪𝘰𝘯𝘴 𝘴𝘰 𝘵𝘩𝘢𝘵 𝘶𝘯𝘤𝘦𝘳𝘵𝘢𝘪𝘯𝘵𝘺 𝘢𝘯𝘥 𝘳𝘪𝘴𝘬 𝘪𝘯 𝘧𝘢𝘳𝘮𝘪𝘯𝘨 𝘢𝘭𝘸𝘢𝘺𝘴 𝘰𝘤𝘤𝘶𝘳𝘴. 𝘛𝘩𝘦 𝘴𝘰𝘶𝘳𝘤𝘦 𝘰𝘧 𝘳𝘪𝘴𝘬 𝘪𝘴 𝘱𝘳𝘦𝘥𝘪𝘤𝘵𝘦𝘥 𝘵𝘰 𝘤𝘰𝘯𝘵𝘪𝘯𝘶𝘦 𝘵𝘰 𝘨𝘳𝘰𝘸 𝘸𝘩𝘪𝘤𝘩 𝘨𝘳𝘦𝘢𝘵𝘭𝘺 𝘢𝘧𝘧𝘦𝘤𝘵𝘴 𝘵𝘩𝘦 𝘵𝘰𝘵𝘢𝘭 𝘢𝘨𝘳𝘪𝘤𝘶𝘭𝘵𝘶𝘳𝘢𝘭 𝘺𝘪𝘦𝘭𝘥. 𝘍𝘢𝘳𝘮𝘪𝘯𝘨 𝘳𝘪𝘴𝘬 𝘤𝘰𝘯𝘴𝘪𝘴𝘵𝘴 𝘰𝘧 𝘱𝘳𝘰𝘥𝘶𝘤𝘵𝘪𝘰𝘯 𝘳𝘪𝘴𝘬 𝘢𝘯𝘥 𝘱𝘳𝘪𝘤𝘦. 𝘗𝘳𝘰𝘥𝘶𝘤𝘵𝘪𝘰𝘯 𝘳𝘪𝘴𝘬 𝘪𝘴 𝘳𝘦𝘭𝘢𝘵𝘦𝘥 𝘵𝘰 𝘱𝘳𝘰𝘥𝘶𝘤𝘵𝘪𝘰𝘯 𝘶𝘯𝘤𝘦𝘳𝘵𝘢𝘪𝘯𝘵𝘺. 𝘗𝘳𝘪𝘤𝘦 𝘳𝘪𝘴𝘬 𝘪𝘴 𝘳𝘦𝘭𝘢𝘵𝘦𝘥 𝘵𝘰 𝘱𝘳𝘪𝘤𝘦 𝘧𝘭𝘶𝘤𝘵𝘶𝘢𝘵𝘪𝘰𝘯𝘴 𝘵𝘩𝘢𝘵 𝘤𝘢𝘶𝘴𝘦 𝘭𝘰𝘴𝘴𝘦𝘴 𝘵𝘰 𝘧𝘢𝘳𝘮𝘦𝘳𝘴 𝘣𝘦𝘤𝘢𝘶𝘴𝘦 𝘱𝘳𝘪𝘤𝘦𝘴 𝘢𝘳𝘦 𝘥𝘪𝘧𝘧𝘪𝘤𝘶𝘭𝘵 𝘵𝘰 𝘱𝘳𝘦𝘥𝘪𝘤𝘵. 𝘐𝘯𝘥𝘰𝘯𝘦𝘴𝘪𝘢 𝘪𝘴 𝘬𝘯𝘰𝘸𝘯 𝘧𝘰𝘳 𝘪𝘵𝘴 𝘥𝘪𝘷𝘦𝘳𝘴𝘪𝘵𝘺 𝘸𝘪𝘵𝘩 𝘯𝘦𝘢𝘳𝘭𝘺 300 𝘦𝘵𝘩𝘯𝘪𝘤𝘪𝘵𝘪𝘦𝘴. 𝘌𝘢𝘤𝘩 𝘦𝘵𝘩𝘯𝘪𝘤 𝘨𝘳𝘰𝘶𝘱 𝘩𝘢𝘴 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘵 𝘤𝘩𝘢𝘳𝘢𝘤𝘵𝘦𝘳𝘪𝘴𝘵𝘪𝘤𝘴 𝘪𝘯 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳, 𝘭𝘢𝘯𝘨𝘶𝘢𝘨𝘦 𝘢𝘯𝘥 𝘤𝘶𝘴𝘵𝘰𝘮𝘴. 𝘛𝘩𝘪𝘴 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘤𝘦 𝘪𝘴 𝘱𝘰𝘴𝘴𝘪𝘣𝘭𝘦 𝘵𝘰 𝘪𝘯𝘧𝘭𝘶𝘦𝘯𝘤𝘦 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯𝘴 𝘪𝘯 𝘮𝘢𝘯𝘢𝘨𝘪𝘯𝘨 𝘢 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴, 𝘪𝘯𝘤𝘭𝘶𝘥𝘪𝘯𝘨 𝘪𝘯 𝘥𝘦𝘢𝘭𝘪𝘯𝘨 𝘸𝘪𝘵𝘩 𝘧𝘢𝘳𝘮𝘪𝘯𝘨 𝘳𝘪𝘴𝘬𝘴. 𝘛𝘩𝘪𝘴 𝘴𝘵𝘶𝘥𝘺 𝘢𝘵𝘵𝘦𝘮𝘱𝘵𝘴 𝘵𝘰 𝘢𝘯𝘢𝘭𝘺𝘻𝘦 𝘵𝘩𝘦 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳 𝘰𝘧 𝘳𝘪𝘤𝘦 𝘧𝘢𝘳𝘮𝘦𝘳𝘴 𝘰𝘯 𝘵𝘩𝘦 𝘳𝘪𝘴𝘬 𝘰𝘧 𝘧𝘢𝘳𝘮𝘪𝘯𝘨 𝘢𝘮𝘰𝘯𝘨 𝘷𝘢𝘳𝘪𝘰𝘶𝘴 𝘦𝘵𝘩𝘯𝘪𝘤 𝘨𝘳𝘰𝘶𝘱𝘴 𝘪𝘯 𝘌𝘢𝘴𝘵 𝘑𝘢𝘷𝘢 𝘢𝘯𝘥 𝘧𝘢𝘤𝘵𝘰𝘳𝘴 𝘵𝘩𝘢𝘵 𝘪𝘯𝘧𝘭𝘶𝘦𝘯𝘤𝘦 𝘧𝘢𝘳𝘮𝘦𝘳 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳 𝘵𝘰𝘸𝘢𝘳𝘥𝘴 𝘧𝘢𝘳𝘮𝘪𝘯𝘨 𝘳𝘪𝘴𝘬. 𝘛𝘩𝘪𝘴 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘸𝘢𝘴 𝘤𝘰𝘯𝘥𝘶𝘤𝘵𝘦𝘥 𝘪𝘯 𝘗𝘢𝘮𝘦𝘬𝘢𝘴𝘢𝘯, 𝘕𝘨𝘢𝘸𝘪 𝘢𝘯𝘥 𝘗𝘢𝘴𝘶𝘳𝘶𝘢𝘯, 𝘸𝘩𝘦𝘳𝘦 𝘵𝘩𝘦𝘴𝘦 𝘵𝘩𝘳𝘦𝘦 𝘥𝘪𝘴𝘵𝘳𝘪𝘤𝘵𝘴 𝘳𝘦𝘱𝘳𝘦𝘴𝘦𝘯𝘵 𝘑𝘢𝘷𝘢𝘯𝘦𝘴𝘦, 𝘔𝘢𝘥𝘶𝘳𝘦𝘴𝘦, 𝘢𝘯𝘥 𝘔𝘢𝘥𝘶𝘳𝘢-𝘑𝘢𝘷𝘢𝘯𝘦𝘴𝘦 𝘦𝘵𝘩𝘯𝘪𝘤 𝘢𝘴𝘴𝘪𝘮𝘪𝘭𝘢𝘵𝘪𝘰𝘯. 𝘛𝘩𝘦 𝘥𝘢𝘵𝘢 𝘶𝘴𝘦𝘥 𝘢𝘳𝘦 𝘱𝘳𝘪𝘮𝘢𝘳𝘺 𝘥𝘢𝘵𝘢 𝘤𝘰𝘭𝘭𝘦𝘤𝘵𝘦𝘥 𝘧𝘳𝘰𝘮 49 𝘳𝘦𝘴𝘱𝘰𝘯𝘥𝘦𝘯𝘵𝘴 𝘪𝘯 𝘗𝘢𝘮𝘦𝘬𝘢𝘴𝘢𝘯 𝘙𝘦𝘨𝘦𝘯𝘤𝘺, 72 𝘪𝘯 𝘕𝘨𝘢𝘸𝘪 𝘙𝘦𝘨𝘦𝘯𝘤𝘺 𝘢𝘯𝘥 65 𝘪𝘯 𝘗𝘢𝘴𝘶𝘳𝘶𝘢𝘯 𝘙𝘦𝘨𝘦𝘯𝘤𝘺 𝘴𝘰 𝘵𝘩𝘢𝘵 𝘢 𝘵𝘰𝘵𝘢𝘭 𝘰𝘧 186 𝘳𝘦𝘴𝘱𝘰𝘯𝘥𝘦𝘯𝘵𝘴 𝘶𝘴𝘪𝘯𝘨 𝘵𝘩𝘦 𝘤𝘭𝘶𝘴𝘵𝘦𝘳 𝘴𝘢𝘮𝘱𝘭𝘪𝘯𝘨 𝘢𝘱𝘱𝘳𝘰𝘢𝘤𝘩. 𝘍𝘢𝘳𝘮𝘦𝘳𝘴' 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳 𝘵𝘰𝘸𝘢𝘳𝘥𝘴 𝘧𝘢𝘳𝘮 𝘳𝘪𝘴𝘬 𝘸𝘢𝘴 𝘢𝘯𝘢𝘭𝘺𝘻𝘦𝘥 𝘶𝘴𝘪𝘯𝘨 𝘵𝘩𝘦 𝘑𝘶𝘴𝘵 𝘢𝘯𝘥 𝘗𝘰𝘱𝘦 𝘳𝘪𝘴𝘬 𝘧𝘶𝘯𝘤𝘵𝘪𝘰𝘯 𝘮𝘰𝘥𝘦𝘭 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘶𝘵𝘪𝘭𝘪𝘵𝘺 𝘧𝘶𝘯𝘤𝘵𝘪𝘰𝘯 𝘢𝘱𝘱𝘳𝘰𝘢𝘤𝘩, 𝘸𝘩𝘪𝘭𝘦 𝘵𝘩𝘦 𝘢𝘯𝘢𝘭𝘺𝘴𝘪𝘴 𝘰𝘧 𝘧𝘢𝘤𝘵𝘰𝘳𝘴 𝘵𝘩𝘢𝘵 𝘪𝘯𝘧𝘭𝘶𝘦𝘯𝘤𝘦𝘥 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳 𝘵𝘰𝘸𝘢𝘳𝘥𝘴 𝘧𝘢𝘳𝘮 𝘳𝘪𝘴𝘬 𝘸𝘢𝘴 𝘤𝘢𝘳𝘳𝘪𝘦𝘥 𝘰𝘶𝘵 𝘶𝘴𝘪𝘯𝘨 𝘮𝘶𝘭𝘵𝘪𝘱𝘭𝘦 𝘳𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯. 𝘛𝘩𝘦 𝘳𝘦𝘴𝘶𝘭𝘵𝘴 𝘰𝘧 𝘵𝘩𝘦 𝘢𝘯𝘢𝘭𝘺𝘴𝘪𝘴 𝘴𝘩𝘰𝘸 𝘵𝘩𝘢𝘵 𝘵𝘩𝘦 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳 𝘰𝘧 𝘳𝘪𝘤𝘦 𝘧𝘢𝘳𝘮𝘦𝘳𝘴 𝘪𝘯 𝘗𝘢𝘮𝘦𝘬𝘢𝘴𝘢𝘯 𝘋𝘪𝘴𝘵𝘳𝘪𝘤𝘵 𝘸𝘪𝘵𝘩 𝘔𝘢𝘥𝘶𝘳𝘢 𝘦𝘵𝘩𝘯𝘪𝘤 𝘳𝘪𝘴𝘬 𝘴𝘦𝘦𝘬𝘦𝘳𝘴, 𝘪𝘯 𝘗𝘢𝘴𝘶𝘳𝘶𝘢𝘯 𝘙𝘦𝘨𝘦𝘯𝘤𝘺 𝘪𝘴 𝘢 𝘳𝘪𝘴𝘬 𝘢𝘷𝘦𝘳𝘴𝘦 𝘢𝘯𝘥 𝘪𝘯 𝘕𝘨𝘢𝘸𝘪 𝘙𝘦𝘨𝘦𝘯𝘤𝘺 𝘪𝘴 𝘢 𝘳𝘪𝘴𝘬 𝘴𝘦𝘦𝘬𝘦𝘳. 𝘙𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯 𝘢𝘯𝘢𝘭𝘺𝘴𝘪𝘴 𝘴𝘩𝘰𝘸𝘴 𝘵𝘩𝘢𝘵 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘤𝘦𝘴 𝘪𝘯 𝘦𝘵𝘩𝘯𝘪𝘤𝘪𝘵𝘺 𝘰𝘧 𝘧𝘢𝘳𝘮𝘦𝘳𝘴 𝘢𝘧𝘧𝘦𝘤𝘵 𝘵𝘩𝘦 𝘸𝘢𝘺 𝘳𝘪𝘤𝘦 𝘧𝘢𝘳𝘮𝘦𝘳𝘴 𝘥𝘦𝘢𝘭 𝘸𝘪𝘵𝘩 𝘧𝘢𝘳𝘮𝘪𝘯𝘨 𝘳𝘪𝘴𝘬𝘴

This study aims to analyze what factors affect the risk of superior rice production in tidal swamp land, Barito Kuala District. This research will be conducted in Barito Kuala District, South Kalimantan Province. This research will start from March-June 2022. The analytical tool used is the Just Pope function model. The results of the analysis show that the determinant of the risk of superior rice production in tidal swamp land is labor input. Labor input is risk decreasing, meaning that the use of labor input is able to reduce the risk or variation in the results achieved. If farmers add more labor, it means that the handling of farming will be more intensive starting from the process of seeding, fertilizing, controlling pests and diseases until the harvest period.

Marine litter has different impacts on fisheries by damaging gear, reducing catch, and necessitating time to repair or clean nets, making it a significant problem for this industry. This article explores the sources, types, and distribution of marine litter and how production risk and technical efficiency in the trawl fisheries in Vietnam are affected by the presence of litter. The empirical analysis is conducted using data collected from a sample of 208 trawl fishers in Phu Yen, Khanh Hoa, and Ninh Thuan provinces. Our analysis indicates that primary sources of marine litter as reported by fishers are tourism and land-based emissions, with plastic being the dominant type. Litter accounts for 20% of the catch, making it a risk-increasing factor for trawl fisheries and causing technical inefficiency. Our findings emphasize the importance of developing policies for Vietnamese fisheries to jointly address production risks, improve technical efficiency, and decrease marine litter pollution. [ABSTRACT FROM AUTHOR]

Cereal, oilseed, and protein (COP) production is an important sector contributing to Sustainable Development Goals (SDGs) in Tunisia. COP farms often diversify their production patterns to stabilize their income sources and spread production risk across crops. However, crop diversity may entail an inefficient use and management of resources to achieve the desired output. In addition, the COP sector still shows a low productivity level, depending on weather conditions in Tunisia. In this context, this study aimed to assess the relationship between the land use pattern and efficiency performance of farms. We used data envelopment analysis (DEA) in the presence of uncertainty based on state-contingent techniques. This approach has not previously been used to examine the links between crop pattern and efficiency. We found that specialized COP farms, on average, exhibited higher technical efficiency levels than those adopted mix cropping systems (83% and 60%, respectively), indicating an important margin to reduce inefficiency. Nevertheless, both diversified and specialized farms could reduce their inefficiency levels through more rational input use to attain the current level of production. Some practical implications were derived to target policy interventions to enhance agricultural productivity and resource use efficiency. [ABSTRACT FROM AUTHOR]

The purpose of this study is to evaluate the instruments utilized in agricultural risk management. The study’s goals are to highlight the hazards that Romanian farmers confront and to uncover strategies to mitigate these risks. In this regard, we present an analysis of agricultural risks, the role of agricultural insurance and the impact of risk management on the sustainability of agricultural holdings. The research methodology is based on various reports, official statistics, macroeconomic analysis, case studies, analysis of documents issued by organizations representing the SME sector and the agricultural business environment. After collecting the data, qualitative and quantitative methods were used to express the research results. The study emphasized the constraints that farmers face (depending on the size of the enterprise), the influence of climate change on agricultural output, the main financial risks (e.g., price risk, production risk), and suggested methods for implementing agricultural insurance (eg. production, income insurance). The study also shows that price and production risks such as price volatility and climate change have a significant impact on the sustainability of agricultural holdings. The main conclusion of the study shows that risk management tools encourage farmers to participate in sound risk management. Finally, the results of the research can provide important guidelines in substantiating the needs of risk management in the agricultural sector.

The productivity of beans has been boosted in recent decades all over the world. Nevertheless, bean production variability is observed from farm to farm indicating the presence of production risk and inefficiency in bean cultivation. This study aims to investigate the production risk and technical inefficiency of bean farms in Bangladesh. A total of 80 bean farmers were selected from Bangladesh using a purposive random sampling technique. The Kumbhakar model was employed to compute the risk and inefficiency of bean farmers. The result shows the significant production-increasing effect of irrigation and farm size while it also implies the significant production-decreasing effect of seed and fertilizer. In addition, the risk of bean production has increased with the farm labor, irrigation, and farm size while the risk of bean production has reduced with the fertilizer. The result of technical efficiency implies that farmers can significantly decrease their input use while maintaining the same level of output. In addition, technical inefficiency has increased with the age and training of farmers while it has decreased with the extension services received by the farmers. Adopting appropriate scientific management practices is imperative to increase efficiency and reduce the production risk of bean farmers. Additionally, the government should provide sufficient credit facilities and enough subsidies on expensive inputs that help to decrease the financial risk of bean growers.

This research investigates the efficiency of pineapple production in Malaysia using the stochastic frontier model with flexible risk features and a sample of 290 pineapple farms by smallholders in Johor. The results of the study indicate that the trans log model is the best match for the mean output function, while input factors, such as sucker, fertilizer, agrochemicals, labor, and hormones, have a positive effect on pineapple yield with rising returns to scale. The study also finds that fertilizers and hormones are risk increasing inputs, whilst sucker is classified as a risk decreasing input. The total farm-specific characteristics account for the difference in the mean technical efficiency, which is estimated to be 68.1%. The study shows that, on average, 31.9 percent of the potential output is wasted owing to technical inefficiency and production risks in inputs. However, the optimal production of pineapple is facilitated by the application of the best agricultural techniques. [ABSTRACT FROM AUTHOR]

In the condition of rapid production intensification based on an increasingly complete and rational use of technical, material and labor resources, improvement of the production organization and labor, improvement of the system and management and planning methods, there is a need for an operational analysis of the current situation, improvement of methods for regulating, managing and reducing the anthropogenic, man-made and natural character risks. In the oil and gas sector, the distinctive features of which are the multi-connectedness and multidimensionality of their constituent technological apparatuses, industrial, environmental and economic risks are especially high. Considering that the technological processes basis is thermal processes occurring in apparatuses, in connection with this, the abstracts pay attention to topical automation issues, regulation and control of increased fire and explosion hazard processes occurring in a tube furnace, ensuring a reduction in the risk of the aforementioned emergencies. [ABSTRACT FROM AUTHOR]

近年来国际重大突发事件频发, 严重威胁了中国及全球粮食安全。文章从生产、消费、流通 3 个环节 分析重大突发事件对粮食安全造成的主要风险。在生产环节, 重大突发事件将限制劳动力和农资的投入, 进 而直接制约粮食的生产;在消费环节, 重大突发事件的爆发往往会导致粮食价格的上涨、居民收入水平的下 降和食品加工的受阻, 进而削弱人们的粮食购买能力和消费能力;在流通环节, 重大突发事件可能导致国内 粮食运输受阻, 以及国际贸易中断, 进而阻碍粮食生产和粮食需求的有效对接, 加剧粮食危机爆发的风险。 中国粮食的高自给率不仅有力地保障了国内粮食安全, 更为国际粮食供需安全创造了空间。文章最后对中国 粮食安全提出了相应的政策建议. In recent years, the probability and frequency of international major emergencies are on the rise, which have threatened the global food security. The study decomposes the food supply chain into production section, consumption section, and circulation section; and then analyzes the risks of food security in each section when facing the major emergencies. In the production section, major emergencies restrict the inputs of labor and agricultural production materials, limiting food supply directly. In the consumption section, major emergencies usually increase the food price and decrease the resident income, and thus, decline the purchasing power of food and exacerbate the food crisis. In the circulation section, major emergencies may lead to the block of domestic food transportation and the interruption of international trade, which mismatches the food production and food consumption. In addition, the study puts forward that China's high grain self-sufficiency rate not only ensures Chinese food security, but also contributes to the global food security. The suggestions are proposed in the end to Chinese and global food security, respectively. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic in 2020 caused unprecedented shocks to agricultural food systems, including increased risk to worker health, labor‐related input costs, and production uncertainty. Despite employer precautions, there were numerous worksite outbreaks of COVID‐19. This paper examines the relationship between month‐to‐month variation in historical agricultural employment and changes in the incidence of confirmed COVID‐19 cases and deaths within U.S. counties from April to August 2020. The results show that employment of 100 additional workers in fruit, vegetable, and horticultural production was associated with 4.5% more COVID‐19 cases within counties or an additional 18.65 COVID‐19 cases and 0.34 additional COVID‐19 deaths per 100,000 individuals in the county workforce. [ABSTRACT FROM AUTHOR]

The current indiscriminate use of antibiotics for veterinary is irresponsible and misguided; it causes antibiotic resistance and adversely affects public health. The terms “habit” and “path dependence” are often used to explain the “excessive” use of agrochemicals. Yet, no research explored where the habit comes from and how it changes. This study investigates how veterinary antibiotic use changed with the production risk based on the multi-period production data set of 1,526 broiler contract farmers. The results show that the production risk has a ratchet effect on farmers' antibiotic use, leading to path dependence of farmers. Specifically, it showed a farmers' habit of steadily increasing antibiotic use and confirmed that the historical broilers' peak mortality was a key determinant to the continuation of this habit. It implies that higher the historical peak mortality, higher the current antibiotic use by farmers. Likewise, the impact of historical peak mortality on antibiotic use gradually increased with the farming experience. The increased historical peak mortality increased farmers' antibiotic use every time. Furthermore, large-scale farmers were more sensitive to historical peak mortality and therefore they increased antibiotic use excessively. The study suggests that improving farmers' production risk management capabilities, especially large-scale farmers, might help prevent extreme events. Moreover, this work contributes to the theoretical and empirical evidence on the ratchet effect, habit formation and farmers' antibiotic use and offers coherent insights for stakeholders to limit antibiotic use.

Farmers in developing countries face different rice production risks, influencing yield variability. This study investigates the technical efficiency (TE) and production risk of Boro and Aman rice in Bangladesh. A stochastic production frontier has been used assuming a true random effect (TRE) model with flexible risk properties using two-year seasonal plot-level panel data of 5088 observations for Boro rice and 5638 observation for Aman rice. The empirical result of the risk model shows that labor, fertilizer, seed, and farm capital have a significant risk-decreasing effect for Boro rice. In contrast, the cultivated area of rice and average mean temperature have a significant risk-increasing effect on Boro rice. Labor and pesticide have significant risk-decreasing effects, whereas cultivated area, fertilizer and seed has a significant risk-increasing effect on Aman rice production. The average TE was 76% and 72% for Boro and Aman rice, respectively. Results suggest a high degree of variability in TE estimates, and the average farmer could increase rice yield by 24% and 28% by improving technical management without increasing the existing inputs. Large farms are more technically efficient than other farm categories. It is also observed that small farms and medium farms significantly decrease technical efficiency for Boro rice while significantly increasing for Aman rice. Moreover, technical efficiency declined over time for Boro rice, while it improved for Aman rice in Bangladesh. Production risk, however, declined over time for both Boro and Aman rice.

Copyright of Journal of Indonesian Agribusiness / Jurnal Agribisnis Indonesia is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rainfed lowland farming production is generally lower than irrigated lowland rice due to area differentiation regional features. Rainfed lowland rice farming can only produce rice during the rainy season because lowland rice cannot be planted in the dry season. The purposes of this study are (1) to analyze the risk of production and income of rice farming in rainfed lowland farming and (2) to investigate the factors influencing the risk of rice farming in rainfed lowland farming. Data were collected from 100 respondents of rice farmers in four sub-districts in Maros Regency using the multi-stage cluster random sampling technique. The analysis of production and income risks were performed using multiple linear regression with the heteroscedastic method. The results have shown that rice farming in rainfed lowland farming poses a risk to production and income. The variables that significantly influence the rainfed lowland rice farming are land area, the number of seeds, the amount of urea fertilizer and the amount of pesticide. Farmers are required to manage risk by prioritizing the effectiveness and efficiency production factors as needed. Similarly the government is expected to assist farmers in maintaining the level of rice selling prices.

The quality of potato seeds is important to support increased production. The majority of farmers do not certify potato seeds, which can result in various risks for potato seed production activities. This research aims to identify the risks of potato seed production and formulate risk control strategies for potato seeds production. The research uses house of risk method. The results of this study show thirty-nine identified risk events. The most impactful risk event was rotten potato. Thirty-two identified risk agents with two priorities must be handled first. The most effective ways in handling strategy are training, the certification of potato seed breeder farmers, potato seed certification, as well as purchasing breeder seeds from vegetable crop research center and from other seed breeders. This research suggests the needs to produce quality potato seeds by certifying potato seed and to update the competency certification of potato seed breeders.

Purpose – The purpose of this study is to investigate the determinants of agricultural insurance adoption by farmers of the state of São Paulo, Brazil. Design/methodology/approach – Primary data from the 2015/2016 crop season was collected from a sample of 175 farmers. Logit econometric models were applied to identify the variables that affect the probability of agricultural insurance adoption. Findings – The empirical results show that the education level, access to technical assistance, use of management tools and farm size positively affect the probability of adopting agricultural insurance. In addition, farmers who produce soybean and/or corn are more likely to use insurance. On the other hand, the higher the farmers’ propensity to take risk the lower the likelihood of using insurance. Research limitations/implications – The empirical analysis is based on cross-sectional data of a sample of 175 farmers of the state of São Paulo. The use of panel data with a larger sample of farmers, considering a period of years, could provide additional information. Originality/value – To the best of the knowledge, this is the first empirical analysis about determinants of agricultural insurance adoption by Brazilian farmers, considering behavioral factors. The findings provide useful insights for policymakers in formulating risk management programs in the Brazilian agricultural markets. A better understanding about the determinants of insurance adoption is also relevant for private companies that sell insurance to farmers. Therefore, the paper may contribute with the diffusion of rural insurance as risk management tool in Brazilian agriculture.

Data envelopment analysis (DEA) is an analytical method for measuring, benchmarking, and improving efficiency performance. While DEA has traditionally been a deterministic ex-post approach, when operational data are not available, it can be positioned to represent an ex-ante perspective, if it is feasible to simulate production behaviors. However, there are two limitations of ex-ante DEA. First, is the representation of uncertainties associated with the contextual conditions and their impact on production. Second, is the inability to incorporate risk preferences that relate to the organizations' attitude towards production uncertainty. This paper addresses these two gaps through a method that integrates Monte-Carlo simulations, the Subjective Expected Utility Theory, and ex-ante DEA. Our method allows to explicitly model and incorporate the uncertainties associated with the contextual variables and the production behavior, while facilitating the representation of risk preferences. We demonstrate our method through a case study that is framed around a hypothetical community evaluating Micro-Grid (MG) design alternatives. We utilize the National Renewable Energy Lab data to model the stakeholder energy demand and environmental uncertainties; and use the engineering specifications for the MG technology to populate the production possibility set. We then investigate the distribution of efficiency scores by using various stakeholder risk attitudes and find that DEA rankings are insensitive to risk preferences. The proposed method and the documented risk insensitivity are significant contributions as they allow to reposition ex-ante DEA as a nonparametric alternative to multi-criteria decision-making, which can be generalized across different application areas, including uncommon DEA applications such as engineering. [ABSTRACT FROM AUTHOR]

Impacts of climate change can differ from one region to another. We combine the household-level panel data with weather and climate data to examine the heterogeneity of the impacts of climate change on crop yields across different crops and agro-ecologies in Ethiopia. Our results show that climate change will induce an increase in coffee and teff yields by 31% and 8.3%, respectively, at high altitudes by the years 2041–2060 compared to 1988–2018, under a medium emissions scenario. Conversely, it will reduce coffee yield by 3% at low altitudes, and barley, maize, and wheat yield by 22.7%, 48%, and 10%, respectively, at high altitudes. These findings suggest that tailoring agricultural development programs and climate adaptation strategies to address location and crop-specific sensitivity to climate change may help to build resilience and improve the livelihood of smallholder farmers. [ABSTRACT FROM AUTHOR]

The productivity of wheat is low on smallholder farms in Rwanda. Although mineral fertiliser use is being promoted as a sustainable intensification (SI) pathway, little is known about the nutrient use efficiency and profitability of various fertiliser inputs in Burera, Musanze and Nyamagabe districts of Rwanda. The objective of this study was to assess the use of combinations of nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), zinc (Zn) and boron (B) in wheat production in terms of nutrients management specifically, crop yield, production risk, input use efficiency and economic returns on smallholder farms. The study was conducted in three wheat-growing regions of Rwanda (i.e., Nyamagabe, Musanze and Burera districts) with contrasting soil conditions. The treatments included combinations of different levels of N (0, 30, 60, 90 and 120 kg ha-1) with P (0, 7.5, 15 and 22.5 kg ha-1) and K (10, 20 and 30 kg ha-1) and the control with no applied nutrients. A diagnostic treatment composed of 90 kg N, 15 kg P, 20 kg K, 10 kg Mg, 2.5 kg Zn and 0.5 kg B ha-1 was also included. Mean grain yield and its variability, rainfall use efficiency (RUE), agronomic use efficiency (AE) of N and P and the value cost ratios (VCRs) were calculated to assess the sustainability of the nutrient rates. Across all sites, wheat grain yield and RUE increased with increase in N rates up to 90 kg N ha-1, beyond which no further increase was observed. The highest wheat yield (5.5 t ha-1) and RUE (6.6 kg ha-1 mm-1) with the lowest production risk (coefficient of variation [CV] = 20%) were recorded in the diagnostic treatment. Although the highest AEN and AEP were recorded at lower N and P levels, the CVs of VCR were high (>64%), indicating higher production risk to wheat farmers. In all cases, an optimum VCR (5.6), with the lowest CV (44.4%), was recorded in the diagnostic treatment. We conclude that application of 90 kg N, 15 kg P, 20 kg K, 10 kg Mg, 2.5 kg Zn and 0.1 kg B can guarantee a more SI of wheat production in Burera, Musanze and Nyamagabe districts of Rwanda. [ABSTRACT FROM AUTHOR]

This study was aims to 1) determine the amount of shallot farming income, 2) analyze the risk of production and income of shallot farming. The location of the research was purposively conducted. The type of data is primary data obtained from 80 samples farmers in the study area. Farming analysis was applied to knowing shallot farming income. Furthermore, coefficient of variation (CV) was applied to knowing the risk of production and income. The results showed that R/C ratio as many as 2.11. With that result, it can be said that shallot farming in Malang Regency is feasible. The level of production risk is 37.54% and the level of risk income is 40%. It can be concluded that the risk of production and income of shallot farming during the dry season in Malang Regency is included in the low category.

Cereal, oilseed, and protein (COP) production is an important sector contributing to Sustainable Development Goals (SDGs) in Tunisia. COP farms often diversify their production patterns to stabilize their income sources and spread production risk across crops. However, crop diversity may entail an inefficient use and management of resources to achieve the desired output. In addition, the COP sector still shows a low productivity level, depending on weather conditions in Tunisia. In this context, this study aimed to assess the relationship between the land use pattern and efficiency performance of farms. We used data envelopment analysis (DEA) in the presence of uncertainty based on state-contingent techniques. This approach has not previously been used to examine the links between crop pattern and efficiency. We found that specialized COP farms, on average, exhibited higher technical efficiency levels than those adopted mix cropping systems (83% and 60%, respectively), indicating an important margin to reduce inefficiency. Nevertheless, both diversified and specialized farms could reduce their inefficiency levels through more rational input use to attain the current level of production. Some practical implications were derived to target policy interventions to enhance agricultural productivity and resource use efficiency.

Copyright of Polish Statistician / Wiadomości Statystyczne is the property of State Treasury - Statistics Poland and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Agricultural Economics Researches is the property of Islamic Azad University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes a nonparametric approach for estimation of stochastic production functions with categorical and continuous variables, and then develops procedures that allow for inference on production risk. The estimation is based on the kernel method and the inference is based on a bootstrapping approach. We establish the asymptotic properties of our proposed estimator. Monte Carlo simulation results suggest that our proposed nonparametric procedure is more robust and outperforms other existing parametric and nonparametric methods. In addition, we empirically illustrate the proposed nonparametric approach using long‐run corn production data from university field trials in Wisconsin that examines the performance of genetically modified corn varieties. Specifically, the proposed nonparametric procedure is used to empirically examine the production risk effects of categorical genetically modified variety variables and a continuous planting density variable. [ABSTRACT FROM AUTHOR]

This paper proposes supply chain (SC) risk readiness and resiliency measures and formulates a model for planning and controlling select internal business factors to create desired risk resiliency in order to avert potential risks and mitigate their after-effect. SCs may be exposed to events that affect their business operations, and primarily impact the production processes (i.e. production-related risks), or events (such as natural calamities or terrorism) that affect the way the business interacts with the market, and primarily impact the transportation and distribution processes (i.e. market-related risks). Although a business cannot control such disasters as natural calamities or terrorism, it is possible to identify and control the factors that are responsible for production-related risks and that influence several market-related risks or disasters. The proposed model and the measures will guide SCs through the process of identification, planning and controlling the internal factors that make the chain resilient to these various risks. The resiliency measures and the mixed integer programming model will also enable SCs to conduct what-if analyses of cost and performance trade-off options. A numerical example illustrates the planning in typical scenarios. [ABSTRACT FROM PUBLISHER]

Even if there exists an extensive literature on the modeling of farmers' behavior under risk, actual measurements of the quantitative impact of risk aversion on input use are rare. In this article, we use simulations to quantify the impact of risk aversion on the optimal quantity of input and farmers' welfare when production risk depends on how much of the input is used. The assumptions made on the technology and form of farmers' risk preferences were chosen such that they are fairly representative of crop farming conditions in the USA and Western Europe. In our benchmark scenario featuring a traditional expected utility model, we find that less than 4% of the optimal pesticide expenditure is driven by risk aversion and that risk induces a decrease in welfare that varies from −1.5 to −3.0% for individuals with moderate to normal risk aversion. We find a stronger impact of risk aversion on quantities of input used when farmers' risk preferences are modeled under the cumulative prospect theory framework. When the reference point is set at the median or maximum profit, and for some levels of the parameters that describe behavior toward losses, the quantity of input used that is driven by risk preferences represents up to 19% of the pesticide expenditure. [ABSTRACT FROM AUTHOR]

Red chilies have good demand prospects but still have problems. Apart from the fact that production is seasonal, so it often faces crop failure, it also experiences fluctuating prices, there is no certainty of selling, weak market access and risks are interrelated. In this regard, research has been carried out in Garut Regency, West Java, which is one of the development of red chili clusters. This paper has the aim of looking at the linkages of risks that occur and proposing policy scenarios in mitigating possible risks. This research was designed qualitatively and quantitatively with a case study method through a soft system dynamic methodology (SSDM) approach. The results showed that the risks that occur in the red chili agribusiness cluster can be indicated in the production risk, market risk, and institutional risk which are interrelated and have an impact on financial risk. The simulation results of the implementation of policy scenarios through agricultural insurance on red chili commodities increased farmer liquidity of about 20 percent starting from the 292nd day.This has a tendency for red chili farmers to mitigate risks. Meanwhile, the application of insurance is currently limited to rice commodities. [ABSTRACT FROM AUTHOR]

A number of improved feeding practices such as stall feeding, rotational grazing, and tethering can help increase livestock productivity in Ethiopia. The main aim of this paper is to determine what factors affect the adoption of on such improved feeding practice; i.e. Stall Feeding (SF) and the choice of animal or season for its application. A bivariate probit model was estimated using observations from 367 rural farmers in Northern Ethiopia. Production risk and the frequency of shock are found to be key determinants. As expected, the results from bivariate model revealed that the expected yield positively influenced SF adoption decision and its full-year application while yield variability and risk of yield failure had a negative effect on SF adoption decision and its full-year application. Likewise, previous animal shocks positively contribute to SF adoption. The major contribution of this paper is its explicit treatment of production risk, shock and time preference in the decision to adopt and apply SF. Expected benefits that the farmer can derive from low production risk due to SF adoption should be included in the promotion agenda of SF practice. The implication is that intervention that reduces the variance of return and exposure to downside risk are some desirable in the adoption and choice decision.