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The purpose of this paper is to provide an evaluation method for agricultural catastrophic risk.

Data on agricultural disaster loss are collected based on hectares covered by natural disasters, hectares affected by natural disasters, and hectares destroyed by natural disasters using the standard process. Peak over threshold (POT) approach based on the extreme value theory is used to model the distribution of agricultural catastrophic loss, and value at risk (VaR) is used to assess agricultural catastrophic risk.

This paper provides an approach for collecting agricultural loss data and modelling probability distribution of agricultural catastrophic loss, which is promising for agricultural catastrophic risk evaluating. As the quantified measurement of agricultural catastrophic risk, VaR is observed to be appropriate and feasible. Results of empirical research demonstrate that drought catastrophe negatively affects grain‐production in the northeast region of China; in particular, the drought catastrophic risk is severe within a 100‐year scenario and thus is expected to recur.

To provide an accurate agricultural catastrophic risk assessment, data collection based on disaster occurrence instead of crop yield, and VaR is used in this paper.

In the early stage of the COVID-19 pandemic, Vietnam imposed many drastic restrictions to curb the outbreak of this virus. Such restrictions interrupted the normal functioning of various economic sectors, including agriculture. This research examined disruptions to agricultural activities, income loss and perceived food insecurity among farm households during the pandemic, and then explored the relationships among these economic factors.

Household data from Vietnam and Generalized Structural Equation Model (GSEM) were used for empirical analysis.

Descriptive analyses found that only a small proportion of farm households suffered from the COVID-19 disruptions to their agricultural activities, a large percentage experienced income loss, and a medium number were worried about their food insecurity. GSEM results also revealed that the COVID-19 disruptions to agricultural activities significantly increased the likelihood of worrying about food insecurity, mediated by income loss.

Due to data limitations, the authors could not use better indicators to define and measure the variables of interest (e.g. COVID-19 disruptions to agricultural activities, income loss and food insecurity). Another similar concern was that our models did not account for unobservables, causing some estimation biases.

This research is among the first attempts that examined the direct and indirect (mediated by income loss) effects of the COVID-19 disruptions to agricultural activities on food insecurity.

A credit risk model suitable for agricultural lenders is identified. The model incorporates sector correlations and is applied to the loan portfolio of an agricultural credit association to create a distribution of loan losses. The distribution is used to derive the lender’s expected and unexpected losses. Results of the analysis indicate that the association is more than adequately capitalized based on 1997S2002 data. Since the capital position of the association is lower than that of most other associations in the Farm Credit System, this raises the issue of overcapitalization in the System.

Agricultural land loss is a severe issue that Australia faces, along with many other countries. Myriad research studies have discussed the reasons for such land loss, including urban sprawl as the main factor and factor's repercussions. However, there is a knowledge gap in understanding the impact of dwelling type on farming land reduction. Also, there is an application gap, particularly in the local context. The purpose of this study is to discover the effect of differing dwelling types (compact and non-compact) in metropolitan areas with a growing population (such as Craigieburn) toward potentially noticeable agricultural land loss.

This paper aims to fill these research and practice gaps through a case study using a mixed methods approach. A quantitative analysis was conducted of housing types, the types' growth and agricultural land area taken up by those different housing types over 18 years. Thematic analysis of policies, strategies, schemes and codes relevant to the case study enabled a better understanding of practice gaps.

The study revealed a significant loss of agricultural land. Separate housing was found to be the main culprit due to the number of houses and the area the houses require, thus exhibiting the lack of practical guidelines to prevent the houses' overdevelopment. The findings enabled the identification of opportunities for better practice through government intervention and potential industry alterations.

Previous literature has primarily explored the issues associated with urban sprawl and the sprawl's unsustainability. This research paper offers a more targeted insight into one of the key factors leading to urban sprawl: the types of dwellings being constructed.

This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.

This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.

This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.

This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.

The purpose of this paper is to examine whether Australian agricultural firms display big bath behaviour during droughts by recognising extraordinary and abnormal losses. It is hypothesised that Australian agricultural firms are more likely to report big bath losses in drought years than in non‐drought years and, in a given drought year, agricultural firms are more likely to report big bath losses than firms in other industries.

The authors analyse 405 firm‐years data for agricultural firms over 1980‐1995. For comparison, they also analyse matched‐pair samples of 17 and 30 non‐agricultural firms for the drought years of 1983 and 1995, and matched‐pair samples of 19 non‐agricultural firms for the non‐drought years of 1986 and 1990, respectively. Both univariate and multivariate analyses are used to test the hypotheses.

It is found that agricultural firms are more likely to take big baths in drought years than in non‐drought years. Further, in a given drought year, agricultural firms are more likely to take big baths than non‐agricultural firms. Further analyses of sales, profitability, and extraordinary and abnormal items support the idea that big baths reflect managerial opportunism rather than the economic consequences of droughts.

Previous studies have not investigated the impact of natural calamities like flood and drought on accounting choices. This paper makes an original contribution to the accounting literature by documenting evidence on the extent to which an act of nature, over which management has little or no control, can influence accounting choices.

The purpose of this paper is to present readers with information on the state of provision of agricultural insurance as a means of protecting financial investment in agricultural productivity in Ghana.

The paper reviews interventions in the provision of agricultural insurance in Ghana and then examines what is currently being done in this area. The paper looks at issues arising from empirical evidence on agricultural insurance provision and links them to scholarly articles on these issues.

This paper shows that there has been considerable effort from the German Development Cooperation, the Ghana National Insurance Commission and government ministries and agencies, the Insurance sector in Ghana and stakeholder institutions leading to the creation of an agricultural insurance provider in Ghana. It is, however, evident from the results that the system is facing major challenges resulting primarily from the inability of the state to provide the needed policy and regulatory support that will assist the insurance sector in the development and delivery of the agricultural insurance products.

Even though there has been some research that has touched on agricultural insurance in Ghana, none of them has actually examined the current systems of providing the insurance since its inception. The paper therefore fills the gap of providing information on the current ongoing interventions for the provision of agricultural insurance for individuals and organizations that invest in the agricultural sector in Ghana.

This article investigates the mechanism of the direct and indirect effects of epidemics on agricultural production and projects the impact of COVID-19 on agricultural output in China.

This article first adopts a dynamic panel model and spatial Durbin model to estimate the direct and indirect effects, followed by a growth accounting method to identify the channels by which epidemics affect agriculture; finally, it projects the overall impact of COVID-19 on agriculture.

The incidence rate of epidemics in a province has a negative impact on that province's own agricultural productivity, but the increase in the input factors (land, fertilizer and machinery) can make up for the loss and thus lead to insignificant direct effects. However, this “input-offset-productivity” mechanism fails to radiate to the surrounding provinces and therefore leads to significant indirect/spillover effects. It is projected that COVID-19 will lower China's agricultural growth rate by 0.4%–2.0% in 2020 under different scenarios.

It is crucial to establish a timely disclosure and sharing system of epidemic information across provinces, improve the support and resilience of agricultural production in the short run and accelerate the process of agricultural modernization in the long run.

Considering the infectivity of epidemics, this article evaluates the mechanism of the direct and indirect effects by introducing a spatial dynamic model into the growth accounting framework. Moreover, besides the impact on input portfolio and productivity, this article also investigates whether epidemics reshape agricultural production processes due to panic effects and control measures.

The purpose of this paper is to establish an effective risk assessment approach based on the conditional value-at-risk (CVaR) in the agricultural supply chain.

This study analyzes and assesses the risks of breeding, processing, transportation and warehousing in the agricultural supply chain. The ordered weighted averaging operator is used to sort risk control factors according to their importance and determine the main risk indicators of an enterprise. The CVaR model is utilized to establish the risk loss function, and an improved genetic algorithm is employed to identify the optimal risk control portfolios in the case of the smallest risk loss.

Based on the approach, the optimal combination of risk control to minimize risk losses is determined. Results show that the proportion of capital investment in risk control differs at three confidence levels, and a large amount of money needs to be invested in the production process at the source. Thus, any attempt to control the risks inherent in the agricultural supply chain must begin with the production process at the source.

Supply chain risk management has become increasingly important and significant to the operation and production of enterprises in recent years. The proposed method to assess the risk in the agricultural supply chain can benefit managers in making smart decisions to control total risk.

This study aims to explore how sustainable business models (SBM) can be developed within agri-innovation systems (AIS) and emphasize an integration of the two with a systemic understanding for reducing food loss and value loss in postharvest agri-food supply chain.

This study conducted longitudinal qualitative research in a developing country with food loss challenges in the postharvest supply chain. This study collected data through multiple rounds of fieldwork, interviews and focus groups over four years. Thematic analysis and “sensemaking” were used for inductive data analysis to generate rich contextual knowledge by drawing upon the lived realities of the agri-food supply chain actors.

First, this study finds that the value losses are varied in the supply chain, encompassing production value, intrinsic value, extrinsic value, market value, institutional value and future food value. This happens through two cumulative effects including multiplier losses, where losses in one model cascade into others, amplifying their impact and stacking losses, where the absence of data stacks or infrastructure pools hampers the realisation of food value. Thereafter, this study proposes four strategies for moving from the loss-incurring current business model to a networked SBM for mitigating losses. This emphasises the need to redefine ownership as stewardship, enable formal and informal beneficiary identification, strengthen value addition and build capacities for empowering communities to benefit from networked SBM with AIS initiatives. Finally, this study puts forth ten propositions for future research in aligning AIS with networked SBM.

This study contributes to understanding the interplay between AIS and SBM; emphasising the integration of the two to effectively address food loss challenges in the early stages of agri-food supply chains. The identified strategies and research propositions provide implications for researchers and practitioners seeking to accelerate sustainable practices for reducing food loss and waste in agri-food supply chains.