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The purpose of this paper is to investigate the relationships among choice of risk management tools, perceived effectiveness of risk management tools, self-reported risk attitude, and farm and farmer characteristics.

A mail survey was used to collect information about utilization of risk management tools, perceived effectiveness of risk management tools, and factors that could influence choice of risk management tools by Illinois farmers. Cluster analysis, one-way ANOVA, χ2 tests of independence, and multinomial logistic regression were utilized to detect possible relationships among choice of risk management tools, perceived effectiveness of risk management tools, self-reported risk attitude, and farm and farmer characteristics.

Multinomial logistic regression analysis revealed that age and gross farm income (GFI) were the strongest predictors of the risk management tool utilization group to which an individual would be assigned. The number of risk management tools utilized decreased with age but increased with GFI. Neither self-reported risk attitude nor education was a significant independent variable in the multinomial logistic regression model, but both were strongly impacted by age. Younger farmers with higher GFI were the most likely users of hedging.

The results of this study provide support for the idea that farmers who are better able to generate revenue are better able to manage risk, but the direction of causality was not investigated.

Risk management service providers could benefit from this study as a benchmark for understanding their current and potential farmer clients’ risk management strategies.

This study used cluster analysis and multinomial logistic regression to address the complexity of decisions regarding multiple risk management tools. The number of tools utilized by individuals was investigated.

The purpose of this paper is to identify the perceptions of farmers on the major sources of risk and to examine the effectiveness of the risk management responses of rural smallholder farm households in the semi-arid region of Northern Ghana from the socioeconomic perspective.

Both descriptive statistics and exploratory factor analysis were used on a Likert scale question to rank and identify the important risk perceptions and management strategies of the farmers. The linear regression model was used to highlight the significant factors that affect the farmers’ risk perception and management responses.

The effects of the variations in crop yield, fertiliser prices and crop price on household income were perceived as the three most relevant sources of risk. Stabilising household income by growing different crops, storing feed/seed reserves and spreading sales were the most effective risk management strategies. Factor analysis identified market risk, production risk and human risk as major risk factors whereas diversification, financial strategy, and off-farm employment were perceived as the most effective risk management strategies. Farm and farmer characteristics were found to be significantly associated with risk perceptions and risk management strategies. Risk perceptions significantly increase the risk management strategy adopted by the smallholder rural farmers.

The findings of the paper call for the integration of farmers’ risk perceptions and management strategies in the development of agricultural policies for the semi-arid regions of Ghana.

This paper deviates from the traditional technology adoption studies by modelling rural household perceptions and management strategies using, using descriptive, factor analyses, and linear regression.

Crop insurance and hedging are two risk management strategies used by farmers to manage risk. Using a discrete choice model and farm‐level data, this study investigates the factors influencing farmers’ use of hedging and crop insurance as risk management strategies. In the case of crop insurance, results indicate that level of education, participation in other risk management strategies (such as renting land, commodity programs, spreading sales over the year), and controlling debt are positively related to a farmer’s decision to purchase crop insurance. For the hedging model, results suggest education, off‐farm income, forward contracting sales of crops and livestock, and computer use are positively related to a farmer’s articipation in hedging/futures markets.

The purpose of this paper is to analyze the determinants of agricultural insurance adoption in Bulgaria, using a purpose-built survey of 224 farmers interviewed in 2011. The insurance decision is analyzed conjointly with other risk management decisions on the farm such as having contracts with retailers or processors, diversifying farm activities and using irrigation.

The agricultural insurance sector in Bulgaria is presented in the broader context of the transition to a market-oriented economy and integration of Bulgarian agriculture into the EU Common Agricultural Policy. The recent developments on the determinants of farm insurance adoption in the agricultural economics and finance literature are discussed. A multivariate probit model is used in order to determine the factors explaining the adoption or non-adoption of various risk management tools by the surveyed farmers, including farm insurance.

The authors find that farmers with diversified activities, using irrigation or having contracts with retailers or processors, are more likely to adopt insurance, after controlling for farms and farmers’ structural characteristics. Additionally, the authors find that the main characteristics distinguishing farmers who purchase agricultural insurance from non-users are farm size and farm location. The existence of strong regional effect suggests the importance of adapting the insurance products to the different regional contexts in Bulgaria.

This paper contributes to the (limited) literature on agricultural insurance adoption in transition countries, currently shifting from a system where compensation against natural hazards tended to come from a State damage mitigation fund, inherited from the centrally planned governments to private and voluntary agricultural insurance. This research provides a unique data source on the Bulgarian case study.

The purpose of this paper is to analyse how fish farmers manage climate-related risks and explore possible ways to strengthen risk management under current and future climate.

In total, 662 fish farmers in sites across Northern Thailand were interviewed about risks to the profitability of their fish farms and ways such risks were managed. Nonlinear canonical correlation analysis was used to relate risk factors to management practices at farm and river levels. In total, 68 in-depth interviews with farmers and other stakeholders provided additional information on climate risk management practices.

Farmers use a combination of adjustments to rearing practices, cropping calendars and financial and social measures to manage those risks, which they perceive as being manageable. Many risks are season, river and place specific; implying that the risk profiles of individual farms can vary substantially. Individual risks are often addressed through multiple practices and strategies; conversely, a particular management practice can have a bearing on several different risks. Farmers recognize that risks must be managed at farm and higher spatial and administrative scales. Social relations and information play critical roles in managing these complex combinations of risks.

This is one of the first papers to report in detail on how inland fish farmers manage climate-related risks. It underlines the need to consider multiple spatial and temporal scales and that farmers do not manage individual climate-related risks in isolation from other risks.

The agricultural sector is a critical component of global economic development, and its significance has grown significantly in recent years. The risks associated with agriculture and the behaviors of farmers in handling these risks are becoming increasingly important, given the sector’s increasing dependence worldwide. Various activities related to agriculture are vulnerable to multiple risks, which can have severe consequences for farmers’ livelihoods. The purpose of this systematic review is to present a comprehensive analysis of the sources of risk faced by farmers and their choices in adopting risk management strategies worldwide.

The Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol was utilized to select relevant literature, and a total of 102 studies were analyzed. Through the use of Venn diagrams and graphical methods, the authors provide a transparent overview of the risks faced by farmers and the adoption of risk management strategies in developed and developing countries.

From the analysis, the authors found that, in terms of risk management strategies, diversification, reserve credit and accumulated assets are frequently used in developing countries, while developed countries tend to rely on future/forward contracts, crop insurance and hedging. Diversification is the most widely used risk management strategy across both developed and developing countries. Our study also highlights the different perceptions of weather-related risks among growers in developed and developing countries.

This systematic review provides valuable insights into the risks associated with agriculture and farmers' strategies in managing these risks, which could inform policy decisions and promote sustainable agricultural practices. For instance, understanding the individualistic nature of farmers' risk perception and the varying risk sources and management strategies depending on the locality and provide assistance to the farmers accordingly.

The paper explains how farmers behave during uncertainty in terms of risk perception and their decision to adopt risk management strategies in developed and developing countries.

Building on the risk balancing theory and on recent discussions the appropriateness of using farm income maximization as behavioural assumption, this paper extends the risk balancing framework by accounting for business-household interactions. The purpose of this paper is to theoretically introduce the concept of farm household risk balancing, a theoretical framework in which the farm household sets a constraint on the total household-level risk and balances farm-level and off-farm-level risk.

The paper argues that the risk behaviour of farmers is better understood by considering risk at the household level. Using an analytical framework, equations are derived linking the farm activities, off-farm activities, consumption and business and private liquidity.

The framework shows that a farm household that wants to minimize the risk that total household cash flow falls below consumption needs, may exhibit a wide variety of behavioural responses to changes in the policy and economic environment.

The framework suggests multiple ways for policy makers and individual farmers to support risk management.

Risk management is at the core of the agricultural policy and it is of paramount importance to be able to understand behavioural responses to market and policy instruments. This paper contributes to that by suggesting that the focus of current risk analysis and management studies may be too narrowly focused at the farm level.

The purpose of this paper is to analyse the association between farm/farmer characteristics and unsubsidized farm insurance premium expenditure in Ireland. The distribution of farm insurance expenditures is wide, and it is important to understand the extent to which individual factors influence demand for different levels of insurance premium.

The quantile regression approach and farm accountancy data from the Teagasc National Farm Survey are used to model the association between farm/farmer characteristics and farm insurance demand in Ireland.

Asset values (livestock, buildings and machinery) are positively associated with total insurance expenditure. Both forestry area and crop area are significantly associated with farm insurance expenditure with a stronger influence on the middle and upper part of the distribution. The interaction between farm income and farmer age is positively associated with insurance expenditure pointing to the importance of farm income protection.

The research is mainly concerned with insuring against substantive risks, which are capable of threatening the asset base and continuation of the farm business. Future research can integrate questions in relation to farm safety and farmer health with research on the economic survival of the farm business.

Farmers in Ireland adopt unsubsidized farm insurance as a risk management tool. This situation is relevant to other EU member states including Belgium, Denmark, Germany and Sweden. The findings can be used to inform stakeholders and policymakers about the relative impact of different factors on insurance expenditure.

Previous research has typically focused on the linear relationship between farm/farmer characteristics and insurance demand without accounting for variability across the size distribution. This research is based on the quantile regression approach where the association between farm/farmer characteristics and farm insurance expenditure can be assessed at different points of the distribution.

Large-scale farm management in China has developed rapidly in recent years. Large-scale farmers face substantial operating risks, requiring extensive price risk management. However, the agricultural insurance and futures markets in China are incomplete. This study aims to analyze the price-risk-management behaviors of large-scale farmers under incomplete market conditions, with a focus on the interconnections between large scale farmers' subjective preferences (risk preferences, time preferences), liquidity constraints and their price risk management.

The authors construct an analysis framework to reveal the impact of large-scale farmers' risk preferences, time preferences and liquidity conditions on their price-risk-management behaviors under incomplete market conditions. Using data from field surveys and subjective preference experiments involving 409 large-scale grain farmers in China, an empirical analysis was conducted using the bivariate probit model.

The results show that risk-averse farmers will use risk transfer (such as contract farming) and risk diversification (such as multi-period sales) to avoid price risk. However, farmers subject to liquidity constraints and strong time preferences will not choose risk diversification, and the interaction between time preferences and liquidity constraints will strengthen this decision. The larger the farm-management scale, the greater the impact.

The authors focus on rapidly developed large-scale farm management in China. Appropriate price risk management is required by large-scale farmers due to their substantial operating risks. Considering the incomplete conditions of agricultural insurance and futures markets, the results of this study will help identify behavioral characteristics of large-scale farmers and optimize their price-risk-management strategies, further stabilizing large-scale farm management.

The purpose of this paper is to assess how direct payments (DPs) of the Common Agricultural Policy affect income and revenue variability faced by Italian farmers.

Balanced farm-level panel data are used to construct coefficients of variation over the period 2003-2012. Nonlinear robust regression techniques are used to measure the effect of DP, farm size, fixity in resources, labor intensity, farm production orientation, and specialization on the variability of farm income (FI) and farm revenue. This is done on the overall sample as well as on subsamples of farms located in different regions and belonging to different types of farming.

DPs have mixed effects on the variability of FI. While a negative and significant relationship is found on the whole national sample, this is not generally the case when models are run on the considered subsamples. On the contrary, DPs have always significant variability increasing effects on revenue. This suggests that DPs reduce the degree of risk that farmers face allowing them to engage in riskier activities. Thus, DPs are less effective than expected in terms of income stabilization because these distort farmers’ risk management behavior. Because of this, DPs could constrain the development of markets for risk management instruments and reduce the effectiveness of policies supporting the use of these instruments.

The analysis is inspired by El Benni et al. (2012) but uses a different approach, applies it to a different country, and yields different results. Volatility measures are calculated over more years, and the paper accounts for differences in farm production orientation and is not based on an unbalanced panel of farms. Because of these differences, the authors obtained different results regarding the correlation between DP and income and, even more, revenue variability. Finally, comparing the results of models referring to FI and farm revenue improves the author’s understanding of the impact of DP on farmers’ risk management behavior and allows interesting policy considerations.