Search

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco 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.)

Agricultural activities in many sub-Saharan African (SSA) countries are subject to various risk factors that the COVID-19 compounds. Earlier studies on the effect of COVID-19 on smallholders neglect the issue of comparison with non-farm households. The study uses micro-level household datasets to explore the impact of the COVID-19 pandemic on household welfare, with a focus on farm households relative to their non-farm counterparts. We employed a binary probit model and Propensity Score Matching (PSM) approach and demonstrated that farm households witnessed important income reductions during the COVID-19 pandemic in Uganda. The study contributes to the design of evidence-based approaches to reducing farmers' vulnerabilities to agricultural risks and pandemic-related shocks. Article highlights: Farm households witnessed significant income reductions during the COVID-19 period in Uganda. Most common coping strategies adopted by households amid the COVID-19 crisis were reliance on savings, and reducing food consumption. The study offers suggestions in designing evidence-based approaches to reducing farmers' vulnerabilities to agricultural or pandemic-related shocks. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Professional Business Review (JPBReview) is the property of Open Access Publications LLC 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 Revista de Ciências Agrárias is the property of Sociedade de Ciencias Agrarias de Portugal 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 Revista de Ciências Agrárias is the property of Sociedade de Ciencias Agrarias de Portugal 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.)

Agriculture plays a pivotal role in Africa's development and is essential for achieving the Sustainable Development Goals (SDGs). However, the agricultural sector is inherently exposed to production risks, and many farmers in the developing world lack access to reliable agricultural insurance coverage. This situation arises due to limited data and knowledge about farmers' insurance needs and the high costs associated with insuring against severe agricultural risks. Promoting agricultural insurance as an instrument can have several significant impacts, aligning with multiple SDGs. It can help stabilize farmers' income, thereby contributing to the goal of reducing poverty (SDG 1). Moreover, agricultural insurance can provide a safety net for food producers, helping them manage the impacts of climate-related risks and aligning with SDG 13, which addresses climate action. Additionally, by enhancing the resilience of farmers and ensuring more predictable income, agricultural insurance can contribute to addressing hunger (SDG 2) and ultimately create a more sustainable and prosperous agricultural sector in Africa. Therefore, this study evaluated agricultural insurance as an instrument for sustainable food supply systems in Nigeria. This study adopted a survey design. This study captured thoughts, experiences, and observations of selected agricultural underwriters in the Nigerian insurance industry through structured questionnaire. A descriptive statistic was employed in the data analysis. This study results indicated that aside from farmers' awareness which showed some level of yardstick with respect to farmers behavioural metrics, all other metrics played no significant roles. It was also recorded that why farmers' age, gender, family size and farming experience have no significant roles in the uptake of agricultural insurance, all other participatory factors have major effects. The study contributed significantly to knowledge with the graphical representations of the challenges confronting the agricultural insurers in Nigeria. The study provided suitable recommendations that endear achievable SDGs in Nigeria. [ABSTRACT FROM AUTHOR]

Food security is of great importance to all countries. Correspondingly, agricultural price insurance is an important tool to maintain food security. This study adopts the traditional spider web model to establish a mathematical framework for exploring the internal mechanism of agricultural price insurance, which can ease the volatility of the agricultural market. Then, the influence of agricultural price insurance on the supply of agricultural products is examined. The findings show that the supply elasticity of most agricultural products is greater than the demand elasticity, with agricultural product markets presenting a natural divergence. Agricultural price insurance changes the supply curve of agricultural products by reducing their supply elasticity, subsequently positively affecting the reduction of price fluctuation and the stabilisation of outputs. Agricultural price insurance can even change agricultural product markets under certain conditions, allowing a shift from divergence to convergence. Moreover, by adjusting the insurance parameters of agricultural prices, the equilibrium yield and price can be changed, and the planting area and income of farmers can be maximised. The mathematical basis for agricultural insurance derived in this study can support food security strategies at the national level and further provide a theoretical basis to formulate policies and departmental measures. [ABSTRACT FROM AUTHOR]

This study examines the impact of the row planting method on maize productivity and risk exposure using panel datasets from Ethiopia. A flexible moment-based production function is fitted to capture the expected yield, yield variance, and exposure to downside risk. A Mundlak–Chamberlain approach is combined with a switching regression treatment effects model to account for unobserved heterogeneity and endogeneity. The study shows that adopters of the row planting method significantly reduced exposure to downside risk while increasing expected yield. The analysis also identified some household and environmental conditions that affect the gain from the row planting method. [ABSTRACT FROM AUTHOR]

Assessing the risk to the agricultural system is important for agricultural sustainability. The present study analyses agricultural drought risk with respect to different drought severities. Different drought indices – namely, Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil moisture Index (SSI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI) – are used to evaluate the conditional probability. Non-stationary analysis is carried out for SPEI and SSI to incorporate the impact of large-scale oscillations and regional hydrological variability. Copula analysis is performed between drought conditions and various crop yield anomalies over Maharashtra, India, during 1998–2015. The outcomes suggest that SPEI is a significant drought indicator over the maximum number of districts in all the crops. Sea Surface Temperature (SST) and Indian Summer Monsoon Index (ISMI) are selected as suitable covariates to model the non-stationarity in the SPEI time series. The drought risk is estimated to increase with drought severity for all of the selected crops. It is observed that the exclusion of non-stationarity will underestimate the agricultural risk. [ABSTRACT FROM AUTHOR]

Weather index-based insurance schemes are gaining attention as instruments for agricultural risk management. A key difference between these insurance schemes and more traditional ones is that the former can cope more effectively with adverse selection and moral hazard issues, yielding less expensive insurance contracts. In this article, we argue that index-based crop insurance schemes can be particularly promising in Bolivia and discuss the essential technical requirements and methodological steps for igniting supply of these policies. Using daily rainfall data between 1967 and 2017, pilot insurance schemes for wheat and potato crops are developed for Anzaldo, one of Bolivia's poorest agricultural-dependent rural municipalities. These policies are compared with the country's current public fully subsidized crop-insurance program, which builds on traditional schemes. We prove that index-based schemes that offer variable reimbursing according to climate-induced crop damage allow to manage similar climate risks with significantly lower policy prices. [ABSTRACT FROM AUTHOR]

Impacts of climatic and non-climatic risks are on the rise in the major maize-growing counties of western Kenya. We conducted a questionnaire survey of sampled maize farmers in Nandi, West Pokot, Uasin Gishu and Trans Nzoia counties, achieving 210 responses. We used a stepwise regression model to evaluate the factors influencing farmers' perceptions of farming risks. Results show that most of the sampled farmers were aware of the risks, and perceived reduced rainfall with erratic patterns to be the major climatic risk in crop production. The non-climatic factors were identified as inadequate farm size, limited extension services, land degradation and low soil fertility. The determinant factors that influence farmers' perception of climatic and non-climatic risks affecting crop production were age, farm size, income, crop production cost, marital status, the highest level of education and farming experience. Understanding the risks faced in crop production and determinants of farmers' perceptions can be important in the development and dissemination of sustainable agronomic strategies tailored towards improving crop production. [ABSTRACT FROM AUTHOR]

The article discusses Australia an agricultural nation diverse climates which translates into significant sources of risk for agricultural production and subsequent farm revenues contributing to an increase in the vulnerability of crops. Topics include crop insurance products, including classical claim-based and index-based insurance, that allow exposed individuals to pool resources to spread risk; and the impact of multiple synoptic-scale climate mode indices on crop yield.

Rainstorms are one of the frequent natural disasters which have significant impact on agricultural production and people's lives. Considering the comprehensive influence of various factors on the rainstorm events, this study extracts four elements of rainstorms in the Liaoning Province based on meteorological data collected between 1957 and 2015. Combined four elements of rainstorms by copula function, the cumulative probability of the rainstorm events and the probability of their return period can be analysed. The results show that the joint return period of multiple factors combination is less than the return period of a single factor. The degree of accuracy of the joint return period is higher, which is consistent with the actual situation. During periods of 5, 10, 20, and 50 years, the occurrence probability varies according to the idea 'the central region is higher, while the eastern and western regions are lower'. Special attention must be paid to the low values of the region in future rainstorm disaster prevention and mitigation work. Based on return periods, the agricultural risk grade can be divided into 5 levels. In ascending order, they are level I (Fuxin, Shenyang, Tieling), II (Dalian, Jinzhou, Panjin, Liaoyang), III (Huludao, Fushun), IV (Chaoyang, Yingkou, Anshan, Benxi), and V (Dandong). [ABSTRACT FROM AUTHOR]

Agriculture is a unique sector because of its dependence on climate and biological variables. Therefore, it is vital to identify and evaluate risks to be sure that decisions made on the farm will bring positive results in agriculture. Torbat Heydarieh is the most important center in saffron cultivation and production in the Khorasan Razavi province and Iran. This city is famous for its Saffron lands. It has the first rank in the world for producing Saffron. So, in this paper, we employed risk profile analysis to saffron risk management. By using previous literature, all of the risks of agricultural sector were identified and classified in nine categories. The information was collected from the university experts and Saffron union members. To design the risk profile, we used data from 67 saffron producers of Torbat Heydariyeh in 2016. To evaluate losses related to each risk component, two indices of frequency and severity of risk were calculated and based on that the risk matrix was created. The results showed that the greatest area of risk includes all of the risk of pests, diseases and weeds (Different types of weeds, Micro pests (Fungi and bacteria), Macro pests (Mice, ant, insect, grazing livestock)), economic risk (Brokers, market fluctuations, lack of liquidity of farmers), climate risk (drought, frost and freeze) and damage risk (Reduce yield due to farm life). [ABSTRACT FROM AUTHOR]

Detecting dispersal pathways is important both for understanding species range expansion and for managing nuisance species. However, direct detection is difficult. Here, we propose detecting these crucial pathways using a virtual ecology approach, simulating species dynamics using models, and virtual observations. As a case study, we developed a dispersal model based on cellular automata for the pest insect Stenotus rubrovittatus and simulated its expansion. We tested models for species expansion based on four landscape parameters as candidate pathways; these are river density, road density, area of paddy fields, and area of abandoned farmland, and validated their accuracy. We found that both road density and abandoned area models had prediction accuracy. The simulation requires simple data only to have predictive power, allowing for fast modeling and swift establishment of management plans. [ABSTRACT FROM AUTHOR]

Evaluating agricultural loss due to flooding is essential for defining an appropriate risk level in flood management projects. This research introduces a method for computing annual damage risk for rice fields with respect to both spatial and temporal pattern of floods, while considering the effect of crop growth stages on the total damage. For finding the spatial pattern of floods, HEC-RAS was employed to derive selected physical parameters of floods of interest and then a physical loss function was used to calculate the unconditional loss over flood prone areas. A time-dependent loss function was introduced for rice to determine the effect of growth on damages derived through the physical loss function. Due to the seasonal nature of agricultural risk, frequency analysis was performed for seasonal discharges for each growth stage of rice. A method was introduced to use the concept of Expected Annual Damage in agricultural fields. A method called “AGEAD” was introduced for evaluating short-term risk for agricultural activities considering their inherent spatial and temporal characteristics. Results showed that damages evaluated by employing AGEAD were completely different from what was obtained by applying a flood of defined return period, i.e. from the results of long-term risk evaluation. While it is common to attribute a unique predicted loss to all flood prone areas, AGEAD application showed that different zones in flooded paddy fields were subjected to different amount of damages from 100 to 0%. [ABSTRACT FROM AUTHOR]

Index insurance appeared recently in developing countries with the expectation to improve agricultural output and living standards in general. We investigate how experiencing extreme weather events affects farmers' decision to purchase index insurance in India. Extreme weather events are identified from historical precipitation data and matched with a randomised household panel. Excessive rainfall in previous years during the harvest increases the insurance demand, while lack of rainfall in the planting and growing periods has no effect. The latter can be explained by access to irrigation, underscoring the importance of the local context when developing insurance products to accommodate environmental risks. [ABSTRACT FROM AUTHOR]

Copyright of Agrociencia is the property of Colegio de Postgraduados 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.)

Biodrying was first used for treatment storage sludge by adding bulking agents to reduce its moisture content and improve its quality and stability. The influence on the stability and agricultural application of biodried products after adding bulking agents was investigated by analyzing the variation of the AT4 index, organic matter, and heavy metals of biodried products. Two treatments were considered: the addition of straw (trial A) and sawdust (trial B) to storage sludge as bulking agents before biodrying. After 18 d of biodrying, trial A with straw as bulking agent achieved the higher water-removal rate by 19.24% and also had the higher matrix temperature (57°C). Additionally, the content of protein decreased by 38.45%, while the polysaccharide content only decreased by 5.96%. Additionally, the content of humic substances increased by 48.58%. Further investigation showed that most of the heavy metals transformed from acid soluble fraction to oxidizable and residual fractions, the contents of heavy metals increased insignificantly (6.29%–10.81%), and Zn content exceeded the maximum permissible value stipulated for soil in China (GB 4284-1984). Thus, the risk for farm-oriented storage sludge still exists. [ABSTRACT FROM AUTHOR]

Securitization is an emerging alternative to transfer of insurance risk, especially in cases exceeding the capacity of reinsurance, thus extending the insurability of risks. The original subjects of securitization are the risks emerging from the aftermaths of natural disasters. The range of securitized risks has broaden rapidly over the past decade. The reason of securitization's feasibility in transfer of agricultural risks is the spatial correlation of harvests among the producers that can result in fatal loss suffered simultaneously by many producers and subsequent producer's insolvency to settle the insurance claims. The paper proposes the reduction of the insurer's risk exposure by its transfer to capital markets via catastrophe bonds. A catastrophic event is defined through the relative loss of the current national per hectare yield of the particular crop to the average yield from previous years. The number of years included in the average is subject to the minimization of the relative loss' fluctuation over the given period. The triggering probability of the catastrophe bond is calculated from the kernel estimation of the loss distribution, with the relative loss being the loss index. The general case is upgraded by the factor of soil quality. The insurer is proposed to offer the coverage according to the producers' soil. The soil classes are securitized separately, with the set of catastrophe bonds. Both cases are illustrated by the numerical example on the data set of wheat produced in the Slovak Republic over last 45 years. The outcome of the examples are the graphs of expected payoffs depending on various parameters. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to propose a general framework for modeling heterogeneous risk preferences of agricultural producers and identifying the underlying factors that affect risk preferences.Design/methodology/approach This paper nests the risk preference function in a general production decision framework to test and model producers’ risk preferences. The framework allows for both production and price risk, and accommodates potential inefficient behavior. Panel data and the GMM method are used in the empirical estimation.Findings The results in this study confirmed the hypothesis of heterogeneous risk preferences. Farmers are found to have decreasing absolute risk aversion. Both farmer characteristics and socioeconomic factors have significant impact on producers’ risk preferences. The results suggest that ignoring heterogeneity in risk preferences across individuals and how non-wealth variables could affect farmers’ risk preferences could result in biased economic behavior analysis.Originality/value It is generally assumed in the literature that risk preferences are homogeneous among farmers at given wealth. This is a strong assumption and there are abundant evidences that suggest otherwise. This paper makes contributions to the literature by proposing an approach to modeling heterogeneous risk preferences and identifying the factors that affect preferences. [ABSTRACT FROM AUTHOR]

In this study, we propose a method for estimating the risk of agricultural damage caused by an invasive species when species-specific information is lacking. We defined the 'risk' as the product of the invasion probability and the area of potentially damaged crop for production. As a case study, we estimated the risk imposed by an invasive weed, Sicyos angulatus, based on simple cellular simulations and governmental data on the area of crop that could potentially be damaged in Miyagi Prefecture, Japan. Simulation results revealed that the current distribution range was sufficiently accurate for practical purposes. Using these results and records of crop areas, we present risk maps for S. angulatus in agricultural fields. Managers will be able to use these maps to rapidly establish a management plan with minimal cost. Our approach will be valuable for establishing a management plan before or during the early stages of invasion. [ABSTRACT FROM AUTHOR]

Better insurance against rainfall risk could improve the security of hundreds of millions of agricultural households around the world. This paper theoretically and experimentally analyses an innovative financial product called a Weather Insurance Savings Account (WISA), which combines savings and rainfall insurance. We index the insurance share of the WISA by γ ϵ [0, 1] and use a standard model of intertemporal insurance demand to study preferences over γ . We then use a laboratory experiment to elicit participants' valuations of pure insurance, pure savings, and intermediate WISA types. Contrary to the standard model, within-subject comparisons show that many participants prefer both pure insurance and pure savings to any interior mixture of the two. Additional experimental and observational evidence distinguishes between several alternative explanations. One possibility that survives our additional tests is diminishing sensitivity to losses, as in prospect theory. [ABSTRACT FROM AUTHOR]

While agricultural production has always been a risky endeavour, it has become even more so in the current context of climatic change and increasing market uncertainty. Meanwhile, the rollback of state protections has rendered small-scale farmers, especially marginalized peasant producers in the Global South, particularly vulnerable to these contemporary stressors. This essay critically evaluates the contemporary roll-out of financial derivatives that purportedly aim to mitigate smallholder vulnerability. It gives particular attention to a novel type of derivative known as index-based agricultural insurance ( IBAI) that plays an increasingly prominent role in initiatives to 'climate proof' agriculture. The creation of IBAI markets has required significant work, including (1) technical interventions to debundle environmental risk from agricultural production and rebundle it in novel ways that support private financial capital and agricultural input suppliers, (2) extensive state support in the creation of risk markets, and (3) the construction of an accommodating 'insurance culture' among small-scale producers. In addition to mitigating weather-based risk, a primary objective of IBAI is to spur agricultural modernization. In promoting this agenda, IBAI initiatives may have the paradoxical effect of exposing smallholders to new risks while expanding their overall vulnerability to environmental and economic stressors. [ABSTRACT FROM AUTHOR]

Copyright of Jordan Journal of Agricultural Sciences is the property of University of Jordan 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 aimed to evaluate impacts of risk management (RM) on sheep production. It is based on Solvsamp Modeling, to analyze empirical data (2003-2011) obtained in two marketplaces. Results proved that RM was sometimes ineffective against natural agent severity or market prices fundamental elements (supply, demand) which would have caused strongly risks within season independently of one another. With government policies producers based their RM tools on the use of concentrated animal feed input and herd size management, either this last or herd mobility (nomadic, transhumant) and animal feed diversification, but the RM strategies and returns for individual farmer looked like at a point in time. RM ensured for producers the margin profit rate of 15 percent in winter to 33 percent (summer) and conversely high seasonal coefficient (1.25) in winter, low (0.86) in summer. RM must consider the seasonal, economic or policy factors and specificity of each breeding system to be more efficient. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to outline a pricing formula for the valuation of catastrophic (CAT) bonds as applied to multiple trigger drought risks in Kenya. Design/methodology/approach – The valuation model is designed around the multiple triggers of the Mexican Catastrophe bonds, but the valuation model is based on Jarrow’s (2010) closed form CAT Bond Pricing model. The authors outline the model structure, the multiple tranches with rainfall triggers, and simulate the model using Monte Carlo methods. Data input was synthesized from historical rainfall data in Kenya’s Moyale region as well as prevailing LIBOR and rates and conventional coupons. Findings – The authors compute the valuation model using Monte Carlo techniques. The authors found the pricing method to be robust and consistent under various parameter settings including trigger levels, time after launch, recovery rates, coupon spreads, and zero coupon curves. For example the higher the trigger rates, the lower will be the bond price at issue. With 50 percent recovery the CAT bond at issue would be around $702 with a high triggers and 976 with low triggers, but the valuation changes with parameters. Practical implications – As far as the authors know the use of multiple trigger CAT bonds has been very limited in practice. The valuation formula and methods outlined in this paper show how CAT bonds can be effectively designed to address CAT covariate risks in developing agricultural economies. Originality/value – This paper examines CAT bonds to investigate multi-trigger rainfall risks in Kenya. The paper shows how CAT bonds can be designed to meet specific and CAT risks. Using Jarrow’s (2010) closed form solution this paper is one of the first to apply it to the macro-management of agricultural risks. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to use simulation analysis to assess farmer choice between crop insurance and supplemental revenue options as proposed during development of the Agricultural Act of 2014. Design/methodology/approach – The certainty equivalent of wealth is used to rank farm choices and assess the effects of supplemental revenue options on the crop insurance plan and coverage level chosen by the producer under a range of farm attributes. The risk-reducing effectiveness of the select programs is also examined through their impact on the farm revenue distribution. The dependence structure of yield and prices is modeled by applying copula techniques on historical data. Findings – Farm program supplemental revenue programs generally have no effect on crop insurance choices. Crop insurance supplemental revenue programs typically reduce crop insurance coverage at high coverage levels. An individual plan of crop insurance combined with a supplemental revenue insurance plan may substitute for incumbent area crop insurance plans. Originality/value – The analysis provides insights into farmers’ possible choices by focussing on alternative crops and farm attributes and extensive scenarios, using current data, crop insurance plans and programs contained in the 2014 Farm Bill and related bills. The results should be of value to policy officials and producers in regards to the design and use of risk management tools. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius 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.)

It is an undisputed fact that weather risk increases over time due to climate change. However, qualification of this statement with regard to the type of weather risk and geographical location is needed. In this paper we compare alternative tests for trend detection and discuss their sensitivity. We use local t tests, change point tests and Mann-Kendall tests to analyze the trends of weather risk indices that are relevant from an agricultural viewpoint. Local test procedures offer more information about the timing and the kind of change in weather risk than global tests do. We also use quantile regression to analyze changes in the tails of weather index distributions. These methods are applied to temperature and rainfall based weather indices in three different climatic zones. Our results show that weather risk follows different patterns depending on the type of risk and the location. We also find differences in the sensitivity of the statistical test procedures. [ABSTRACT FROM AUTHOR]

We theoretically a farmer’s optimal use of area and individual crop insurance when area and individual losses are positively but imperfectly correlated. If premium rates for both plans are actuarially fair, the farmer will demand full individual insurance and no area insurance. If area insurance is free and individual insurance is offered at an actuarially fair rate, area insurance replaces a portion of individual insurance demand. If individual insurance is offered as a wrap around the area plan at an actuarially fair rate and area insurance is free, the farmer will demand excess individual insurance and some area insurance. [ABSTRACT FROM AUTHOR]

Soybean rust (SBR) is a disease of significant impact to Brazilian soybean production. Twenty-four locations in a major growing region in southern Brazil, where long-term (30 years) weather information was available, were selected to estimate the risk of SBR epidemics and identify potential predictors derived from El Niño 3.4 region. A rainfall-based model was used to predict SBR severity in an 'epidemic development window' (the months of February and March for the studied region) in the time series. Twenty-eight daily simulations for each year-location ( n = 720) were performed considering each day after 31 January as a hypothetical detection date (HDD) to estimate a severity index (SBRindex). The mean SBRindex in a single year was defined as the 'growing season severity index' (GSSI) for that year. A probabilistic risk assessment related GSSI and sea surface temperatures (SST) at the El Niño 3.4. region (here categorized as warm, cold or neutral phase) in October-November-December (OND) of the same growing season. Overall, the median GSSI across location-years was 34.5%. The risk of GSSI exceeding 60% was generally low and ranged from 0 to 20 percentage points, with the higher values found in the northern regions of the state when compared to the central-western. During a warm OND-SST phase, the probability of GSSI exceeding its overall mean (locations pooled) increased significantly by around 25 percentage points compared to neutral and cold SST phases, especially over the central western region. This study demonstrates the potential to use El Niño/Southern Oscillation information to anticipate the risk of SBR epidemics up to 1 month in advance at a regional scale. [ABSTRACT FROM AUTHOR]

Copyright of Cuadernos de Desarrollo Rural is the property of Pontificia Universidad Javeriana 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.)

Several criteria that produce rankings of risk management strategies are evaluated. The criteria considered are expected return, value at risk, the Sharpe ratio, the necessary condition for first-degree stochastic dominance with a risk-free asset, and the necessary condition for second-degree stochastic dominance with a risk-free asset. The criteria performed relatively well in that the most desirable strategy under each criterion was always at least a member of the second-degree stochastic dominance efficient set. There was also a relatively high degree of consistency between the highest ranked strategies under the various criteria. The effectiveness of the criteria increases as decision makers are assumed to be more risk averse and have greater access to financial leverage [ABSTRACT FROM AUTHOR]

Much farm financial risk research has involved the application of "credit-scoring" models. We approach the issue of measuring financial risk by using the actual interest rates charged on agricultural loans reported in the USDA's ARMS survey as market-based measures of the financial risk associated with individual farm operations. A simultaneous equations model relates rates to several farm, producer, and lender characteristics. Because individual loans in our sample have different dates of origination, deviations of individual rates from market rates are considered. Our results indicate that risk (as perceived by lenders) tends to be higher for farms with less wealth (net worth) and more loans. Farm operators who live on their operations are considered by lenders to be less risky. Farm diversification appears to be correlated with less financial risk. Significant differences in agricultural lending rates across different types of lenders were also revealed, with the highest rates being charged by commercial banks and savings and loans. A key element of our analysis is development of a probability-weighted bootstrap estimator that permits consistent inferences to be drawn from the stratified ARMS data. [ABSTRACT FROM AUTHOR]

Rural livelihoods in most developing countries are threatened by climate-related risks such as drought, flood, heat waves, storms, and so on. Although farmers have adopted several adaptation strategies, they have proven less effective than hoped. Hence, index-based livestock insurance, an innovation that significantly assists farmers to acclimatise to climate-related risks, has been proposed; and its adaptability has attracted a notable increase in other African countries. However, the success of its adoption is dependent on the inclination of the farmers to pay for the service. Accordingly, this study investigates their willingness to pay for index-based livestock insurance and its determinants, and the factors influencing the total livestock units to be insured in the North West province of South Africa. Cross-sectional data were obtained from 277 cattle farmers, drawn randomly from the study area. The contingent valuation method was applied to determine the farmers' willingness to pay; and only 10.8% were willing to pay. Simultaneously, the Heckit sample selection model was used to analyse the data to identify the factors responsible for farmers' willingness to pay and total livestock units to insure. The findings revealed that farmer's experience, age, education, marital status, awareness of insurance and household dependents were statistically significant, and influenced the maximum price R600 ($42, max willingness to pay, WTP) of those who accepted index-based livestock insurance. However, by implication, the study concluded that to adopt index-based livestock insurance in the study area among the livestock farmers, there should be policies to cater for the aforementioned factors. [ABSTRACT FROM AUTHOR]

Copyright of Journal of the Chinese Society of Animal Science is the property of Chinese Society of Animal Science 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 Ekonomika APK is the property of Economy of Argo-Industrial Complex 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.)

Weather index-based crop insurance is increasingly becoming important as a risk mitigation strategy that farmers may use to mitigate adverse climate shocks and natural disasters encountered during farming. While Europe, North America, and Asia account for 20.1%, 55%, and 19.5% of the total agricultural insurance premium worldwide, respectively, Africa accounts for only 0.5% of the world insurance industry. One of the key reasons advanced against the low index insurance participation rate in Africa is the failure to involve farm households at the initial conceptualization and design of pilot initiatives. Therefore, the main purpose of this paper is to design an improved participatory methodology that could help elicit information on the value placed by farm households in Southwestern Burkina Faso on a new weather index-based crop insurance management initiative. A key concept in the improved participatory methodology is that of the willingness to pay (WTP) of farm households for the scheme. Knowledge of the maximum amount that farmers are willing to pay for the scheme can help insurance policy providers and public policy makers to design and put in place measures that sustain index insurance schemes in a developing country context and improve welfare among participating farmers. [ABSTRACT FROM AUTHOR]