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Premium subsidy rates were increased in 2019 and 2020 for livestock risk protection (LRP) insurance, which is price insurance for cattle producers. The authors examined if the LRP subsidy rate changes affected the LRP coverage levels purchased by feeder and fed cattle producers.

The authors collected the United States Department of Agriculture Risk Management Agency summary of business sales data for daily LRP purchases from 2015 to 2023. The authors estimated a multinomial logit model to determine if subsidy rate changes were associated with the likelihood of LRP policies being purchased at different coverage levels.

After the 2019 and 2020 subsidy rate changes, the likelihood of producers buying LRP-feeder cattle policies with coverage over 95% increased relative to the policies with coverage less than 89.99% but did not influence the likelihood of producers buying LRP-feeder cattle policies with coverage between 90 and 94.99% relative to policies with coverage less than 89.99%. Marginal effects show these subsidy rate changes increased the likelihood of buyers purchasing LRP-feeder cattle policies with greater than 95% coverage. The subsidy change did not affect the purchase of LRP-fed cattle policies.

The results demonstrate the influence of the recent LRP policy adjustments on insurance purchases, which could be important for agency officials and policy makers. This is the first study to explore the LRP policy purchases which provides the United States cattle industry insight into the LRP price insurance take-up, which can guide producer extension education on managing price risk.

Livestock Risk Protection (LRP) insurance can reduce losses from price declines for cattle producers, but LRP adoptions has been limited. In 2019 and 2020, LRP subsidies were increased to lower the cost, but it is unclear how much these changes lowered the cost. The objective of this research was to estimate the impact of the subsidy increase on the cost of LRP for feeder and fed cattle by month and for various insurance period lengths and levels.

The authors collected United States LRP offering data from 2017 to 2021. The authors estimated separate generalized least squares regression for feeder cattle and fed cattle with producer premium as the dependent variable. Independent variables were dummy variables for coverage level, insurance period, month and year as well as dummy variables in commodity years 2019 and 2020 when the LRP subsidy was increased.

The authors found the subsidy increases did reduce the cost of LRP policies for feeder and fed cattle LRP policies. Producer premiums for feeder cattle LRP polices have declined between $1.41 to $1.90 per cwt and $0.95 to $1.56 per cwt for fed cattle LRP policies depending on the coverage level. Results indicate these subsidy increases did lower the LRP premium costs to producers.

Results show policy implications from the subsidy increases and will be informative to producers when exploring the cost of LRP. This study extends the literature by estimating the reduction in subsidy costs while considering total premiums changed.

The purpose of this study is to examine empirically the conditional correlation between the major US indices (S&P500 index and Dow Jones Industrial index) and three selected meat commodities as: Feeder Cattle, Leen Hogs and Live Cattle during the period from July 22, 2010 to June 30, 2017.

In this study, the authors use for the first time the GARCH-DECO (1,1) to examine empirically the conditional nexus between the major US indices (S&P500 index and Dow Jones Industrial index) and three selected meat commodities as; Feeder Cattle, Leen Hogs and Live Cattle during the period from July 22, 2010 to June 30, 2017.

From the empirical findings, the authors conclude the existence of a highly significance of conditional heteroscedasticity parameters can demonstrate us to distinguish the nature of the volatility dependency between S&P500 index and Dow Jones Industrial index and three selected meat commodities indices.

This can find clear the significance of relationship in the process of financialization of the major US index and meat commodities indices in the case of this paper.

The Sertão, located in the Northeastern region of Brazil, is the most populous semi-arid region in the world. The region also faces the highest rates of poverty, food insecurity and climate risks in this country. Basic economic activities, such as extensive livestock and dairy farming, tend to be mainly affected by the increasing temperatures and recurrent droughts taking place in the past decades. This paper aims to analyze farmers’ responses to climatic variability in the Sertão.

Analyses are based on farm-level data of the Agricultural Census 2006 and on historical climate data gathered by meteorological stations. The climate impacts and the effectiveness of adaptive strategies are compared between three groups of farms, which discriminate different levels of social and environmental vulnerability. Four production functions are modeled (milk, cattle, goat and sheep) accounting for sample selectivity bias.

In response to increasing temperatures, farmers tend to shift their activities mainly to cattle and dairy farming. But the overall productivity tends to reduce with the recurrence of droughts. Decreasing precipitation affects mainly the production of milk of smallholder family farmers and the cattle herd of non-family farmers.

Analyses do not account for short- and medium-run productive impacts of extreme droughts, which usually have devastating socioeconomic effects in the region.

Smallholder family farmers are the most vulnerable group who deserve more social and technical intervention, as they lack basic social and technological resources that can greatly improve their productivities and overcome the impacts of decreasing precipitation.

Climate change and its imminent threat to human survival adversely impact the agriculture sector. In an impoverished country like The Gambia, economic costs of climate change are colossal. This study aims to establish a computable general equilibrium (CGE) model for The Gambia’s agriculture sector to examine the effects of climate change on crops, livestock and sea-level rise.

This study used a CGE model with other climate change impact models to compute the impacts of climate change on The Gambia’s agriculture sector. The social accounting matrix calibrates the results from the various models, thereby generating the baseline results which exemplify a “steady-state” and policy shock results illustrating the medium- and long-term effects of climate change on the country’s agriculture sector.

The baseline results indicate the status quo showing the neglect of the agriculture sector due to limited investment in the sector. Hence, the sector is the “hardest hit” sector as a result of climate change. When the model factored in climate change in the medium term (2055) and long term (2085), the macroeconomic indicators of gross domestic product, national savings, wages, disposable income and consumer price index deteriorated, elucidating the vulnerability of the economy to climate change. The consumption of groundnuts, cattle and fish will decline by 5%, 5% and 4%, respectively, in the long term. However, the production of all agricultural commodities will decline by an average of 35% for the same period. The results for international trade show that exportation would decline while importation will increase over time. The general price level for agricultural commodities would increase by 3% in 2055 and 5% in 2085. Generally, the results manifest the severity of climate change in the agriculture sector which will have a multiplier effect on the economy. The impact of climate change would result in agriculture and economic decline causing hunger, poverty and human misery.

The caveat of this study revealed the nuances not captured by previous Gambian climate change studies, thus the novelty of the study.

The nature of farm animals in the marginalized group of people is varying hurriedly. Livestock is used to add to cash earnings and increase food security, hence helping as a vital component in the household’s source of revenue strategies, particularly at marginal planter’s level. The present study was conducted to assess the numbers of livestock farmers in the study areas, their livelihood options, the value chain of the farmers in different marketing channels and recommendation for the sustainable value chain of the livestock production cycle.

The study precise the baseline condition of marginal livestock farmers for access to value chain activities in terms of inputs, outputs, support services, production, yield, income and enabling environment to enhance livestock farming in the study area. The study was conducted through stratified random sampling of the context using some research tools like in-depth interviews, household surveys, expert opinions and focus group discussions. Structured questionnaires were developed to address issues, such as current livestock farming practices, access to support services, capacity and income.

The study revealed that this particular context is lagging behind to establish goat value chain activities in the targeted areas. The farmers do not have basic knowledge of goat farming, and the value chain actors are not working properly. The support services are not appropriate to turn the goat farming production to a standard level. Value chain of livestock and livestock products and their goals are essential to develop an idea on learning, investment, market access, sales assurance and quality. Variation in institutional contexts of end markets is linked to different types of coordination and control of enabling environment throughout the chains.

Livestock is an integral component of the complex farming system in Bangladesh as it serves as not only a source of meat protein but also a major source of farm power services as well as employment. Strong private sector alliance along with public–private ventures can bring sustainable agriculture value chain development in these most vulnerable coastal communities in Bangladesh. Strengthening the weak financial structure, reducing power imbalances in the governance structures and low political intervention in community-level organizations, and resolving socio-cultural and environmental concerns are the major concerns on the development of value chains in Bangladesh.

Geographical position and climatic condition of Bangladesh have made her coastal areas one of the highly productive areas for livestock production in the world. The study was conducted through qualitative and quantitative analysis, and after finding the authors recommended for sustainable value chain approach for livestock production to a marketing channel for improving the financial condition and self-employment for the communities.

Climate change and variability present different challenges to the livelihoods of forest-dependent communities. This paper aims to determine climate variability/change and its effects on the livelihoods of the Buyangu community, which depends on Kakamega tropical rain forest in Kenya.

Rainfall and temperature trends were analysed using Mann–Kendall tests and Sen’s slope estimator. The effects of climate variability on the community were determined using household survey questionnaires, focus group discussions and in-depth interviews with key stakeholders.

Temperature trend analyses represent statistically significant trends for the period of 1980-2015. Results reveal a warming trend for both mean annual maximum temperatures and mean annual minimum temperatures by 0.04°C/year and 0.02°C/year, respectively. Moreover, analysis of annual precipitation (1923-2015) indicated an increase of 0.068 mm/year; however, the mean monthly rainfall showed a decreasing trend. As a result, crop production and livestock rearing are negatively affected. Although there is a high level of awareness of climate variability and its related effects on livelihoods, a majority of the Buyangu community still do not understand the influence of climate change on forests and the provision of forest products. Lack of knowledge on this subject will consequently limit adaptation responses.

This research fulfills the need to study climate variability and its effects on the livelihoods of forest-dependent communities. The study calls for all-round stakeholder participation of local and national players in formulating coherent adaptation strategies that will enhance the resilience of forest-dependent communities to a changing climate.

The purpose of this paper is to examine how first-tier suppliers in multi-tier supply chains adapt their vertical and horizontal relationships to reduce the risk of slavery-like practices.

Using Archer’s morphogenetic theory as an analytical lens, this paper presents case analyses adduced from primary and secondary data related to the development of relational anti-slavery supply capabilities in Brazilian–UK beef and timber supply chains.

Four distinct types of adaptation were found among first-tier suppliers: horizontal systemisation, vertical systemisation, horizontal transformation and vertical differentiation.

This study draws attention to the socially situated nature of corporate action, moving beyond the rationalistic discourse that underpins existing research studies of multi-tier, socially sustainable, supply chain management. Cross-sector comparison highlights sub-country and intra-sectoral differences in both institutional setting and the approaches and outcomes of individual corporate actors’ initiatives. Sustainable supply chain management theorists would do well to seek out those institutional entrepreneurs who actively reshape the institutional conditions within which they find themselves situated.

Practitioners may benefit from adopting a structured approach to the analysis of the necessary or contingent complementarities between their, primarily economic, objectives and the social sustainability goals of other, potential, organizational partners.

A range of interventions that may serve to reduce the risk of slavery-like practices in global commodity chains are presented.

This paper presents a novel analysis of qualitative empirical data and extends understanding of the agential role played by first-tier suppliers in global, multi-tier, commodity, supply chains.

This paper aims to understand the perception of smallholder farmers on climate change, identify major livestock related climate change adaptation (CCA) strategies and their determinants in selected neighboring districts of Tigray and Amhara regions of Ethiopia.

A total of 416 household heads were involved in a questionnaire survey using a multistage sampling approach. To understand the socio-economic factors that influence farmers’ perception on climate change (CC) and/or variability, a binary logit model was used. Multinomial logit model was used to identify the determinants of smallholder farmers’ choices of adaptation strategies.

Milk reduction, weight loss, feed shortage and frequent animal disease outbreak were indicated as major impacts of CC on livestock production. About 86.2% of the farmers’ exercise CCA measures where livestock health care and management (25%), followed by livelihood diversification (21.5%) and shifting and diversification of livestock species (20.9%) were the top three adaptation measures implemented. Education, knowledge on CCA strategies, access to veterinary service and extension, market access, annual income, non-farm income, total livestock unit, sex of household head and household size were the major determinant factors to farmers’ choice of CCA.

Concerned authorities working in CC related sectors should give due attention to improve smallholder farmers’ access to extension and veterinary services, market access and climate information to enhance their adaptive capacity to CC impacts. In addition, incorporating climate change awareness trainings into the existing extension packages is crucial to enhance the awareness of farmers on climate change and implement appropriate adaptation strategies. Moreover, it is very essential to provide appropriate herd management and marketing strategy based on the production system to avoid the significant price reduction during drought periods.

Concerned authorities working in CC related sectors should give due attention to improve smallholder farmers’ access to extension and veterinary services, market access and climate information to enhance their adaptive capacity to CC impacts. In addition, incorporating climate change awareness trainings into the existing extension packages is crucial to implement appropriate adaptation strategies. Moreover, it is very essential to provide appropriate herd management and marketing strategy based on the production system to avoid the significant price reduction during drought periods.

This research is focused on smallholder crop-livestock farmers, livestock-based CCASs and presents the determinant factors to their choice of adaptation.

The study proposes Material Flow Analysis (MFA) methodology as a tool to measure and qualify food waste in the Italian beef supply chain in each stage of the food supply chain, from farm to fork. In particular, the authors attempt to: (1) measure resources consumption and waste generation toward companies' and policymakers' sustainable evaluations; (2) enhance consumers' education in the field of agri-food resilience and sustainability.

MFA is applied to the entire Italian sector of beef consumed as packaged fresh product in 2020, during the Covid-19 pandemic. The analysis regards bovine, which represent roughly one-third of the national meat flow. To collect data, bottom-up and top-down mixed approach is applied. Subsequently, MFA results are used to calculate the wastage-related losses in terms of embedded natural resources (e.g. water, energy).

In 2020, it results that the Italian meat industry slaughtered more than 1.15 Mt of bovine to produce approximately 0.29 Mt of fresh meat, 0.69 Mt of by-products and over 0.015 Mt of food waste at households, while 0.15 Mt of beef meat is destined to catering services and food industry (out-of-boundaries). In terms of hidden natural resources, it emerged that, on average, more than 94bn m3 of water, approximately 101,000 TJ of energy and over 11,500 t of PET and PE trays are required to sustain the entire beef system.

This research is one of the few studies proposing MFA methodology as a tool to measure food waste and hidden associated flows in the agri-food sector. This analysis shows its utility in terms of natural resources (water, energy, materials) and waste quality/quantity evaluation, hidden flows accounting and development of new educational strategies toward food waste minimization and sustainability at household consumption.