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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 estimate the impact of financial derivatives on profitability in agricultural banks. Agricultural banks are new to the derivatives market and are unlikely to use financial derivatives for risk speculation. Thus, the paper also provides evidence on the effectiveness of financial derivatives as a risk management tool in small commercial banks.

The authors use call report data from Federal Reserve Bank of Chicago for 2006, 2008 and 2010 to estimate an endogenous switching model to evaluate how profitability of derivatives user and non‐user agricultural banks is affected by different risk factors. This approach allows banks' endogenous choices to use financial derivatives to be accounted for, and to build a counterfactual analysis – what user banks' profitability would have been if they did not participate in the derivatives activities.

Results indicate that risk management through financial derivatives in agricultural banks is effective and profitability of derivatives user agricultural banks is less affected by credit risk and interest risk in the sample period. Derivatives' activities have improved agricultural banks' profitability and these impacts were increasing over years. In particular, in 2010 without use of derivatives, user banks would have had one‐third lower profitability.

This research is the first to study the role of derivatives in agricultural banks and also provides empirical evidence on the effectiveness of risk management through financial derivatives in agricultural banks.

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 investigate whether community‐based wildlife conservation can potentially be added in rural farmers’ investment portfolio to diversify and consequently reduce agricultural risk.

The correlation coefficient is computed from national data on the rates of return on agricultural production and wildlife conservation, to find out whether wildlife conservation is a feasible hedge asset.

The correlation coefficient between the returns to agricultural production and wildlife conservation for the period 1989‐1999, for which data exist for both activities, is inferior to unity indicating that rural farmers could use wildlife conservation to reduce the risk they face by engaging in agricultural production only.

Data on communal agricultural production and community‐based wildlife conservation potentially suffer from at least three limitations. First, wildlife is a unique resource that does not require the usual cash investment to acquire and as such the rates of return on wildlife conservation will likely be overstated. Second, some benefits from wildlife are public and non‐monetised; this results in depressed rates of return on wildlife conservation. Lastly, both the data on agricultural production and wildlife conservation are likely to understate physical and human capital investments; this potentially results in abnormally high rates of return.

Even though the paper makes a case for community‐based wildlife conservation at a national level, the benefits of diversification into wildlife conservation are likely to be high only in those rural areas that can sustain wildlife populations sufficient to generate adequate returns from wildlife activities such as tourism, trophy hunting, live animal sales and meat cropping.

This paper empirically investigates whether the risk that rural farmers face could potentially be managed through diversification into community‐based wildlife conservation and provides paramount evidence that wildlife conservation is a hedge asset in rural Zimbabwe. More investment in community‐based wildlife conservation would also help efforts to conserve wildlife.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

The purpose of this paper is to suggest an integrated risk management service for agriculture, by identifying different risk management practices that may be offered in conjunction with crop insurance, to address the various problems and challenges being faced by farmers and by insurance companies.

The research is based on an inductive approach of developing theory from case studies using within‐case and cross‐case analysis. However, apart from exploring different elements from case studies, some of the existing concepts have been reviewed from the literature for their application in agricultural risk management.

An integrated framework for risk management in agriculture has been developed by inductively exploring the various elements that may be successfully interlinked with the crop insurance to tackle the various agricultural risks more efficiently and effectively.

This paper can act as a basis for new product development in agricultural risk management through the use of this integrated approach of risk management and the different elements that have been identified to improve the effectiveness of crop insurance.

This paper fulfils the identified need to develop a framework for an integrated risk management in agriculture.

The purpose of this study is to investigate the determinants of agricultural insurance adoption by farmers of the state of São Paulo, Brazil.

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.

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.

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.

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.

Agricultural and fishery disasters are rather obscure emergency management research topics. However, the Food and Agriculture Sector is one of only 16 critical infrastructure sectors included in the Robert T. Stafford Disaster Relief and Emergency Assistance Act of 1988, and the sector is a vital component of the United States economy. As climate change continues to increase the frequency and severity of agricultural and fishery disasters, the Food and Agricultural Sector must adapt to and cope with unprecedented levels of risk. This chapter provides an overview of federal agricultural and fishery disaster policy and explores whether such policies are consistent with Jerroleman’s (2019)principles of just recovery.

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 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.