The study estimates the contribution of changes in world prices, exchange rates, and trade policies in explaining the variability of domestic prices under the scenario of incomplete transmission of changes and a counterfactual scenario of complete pass-through. We utilize data from the Indian wheat market for the period 2006–09 and 2017–20. The findings reveal an improvement in the pass-through of changes from the landed price to domestic markets. The price transmission elasticity increased from 50% in 2006/07–2008/09 to 67% during 2017/18–2019/20. The policy response to rising (declining) global prices of decreasing (increasing) import tariffs had a significant effect on prices. The variation in exchange rate offsets the impact of declining or rising global prices on domestic prices.

We consider the effect of labor market volatility on employment and wages in the meat processing sector. The period of study includes the COVID-19 pandemic, which resulted in significant labor market shocks in the sector. We examine the relationship between historical volatility of employment and wages and current employment and wages, focusing on the animal slaughtering and processing sector (NAICS 3116). We utilize county-level data to estimate dynamic panel data models of employment and wages. We find that historical volatility in both employment and wages had a significant negative impact on employment in the sector. In the case of wage volatility, we find that wages are higher following periods of significant wage volatility, suggesting that workers demand higher wages under conditions of market volatility. During COVID, smaller meat processors had lower levels of employment, but a small number of large processors had significantly higher levels of employment. In contrast, wages were higher after COVID-19 for almost all counties included in the analysis. In an aggregate sense, COVID tended to largely reduce employment but increase wages in the meat processing sector.

We analyze the equilibrium conditions in which contracts are desirable for firms (buyers) with various levels of management efficiencies procuring a factor input under two levels of quality from supplies. The quality of the factor input, which affects production efficiency, may be known to the buyer; the efficiency of the firm is not known to the supplier. We estimate, using principal-agent models, that firms with high-management efficiency do not have the incentive to pay a quality premium to suppliers, but firms operating with low management efficiency are willing to offer a price premium for quality. The model is applied to the question of preconditioning cattle for the feedlot.

Dairy cows who excel at milk production also grow horns, which are dangerous to other animals and their human handlers. Recent developments in gene editing make it possible to edit a cow’s genome so that it does not grow horns. We assess from the consumer’s perspective whether the improvements in animal welfare resulting from gene-edited cows outweigh the perceived risks individuals associate with milk from these animals. We find that milk from gene-edited cows and milk from dehorned cows have lower willingness to pay relative to milk that comes from cows without mention of dehorning or gene editing.

Climate change can lead to increased pest migration and more frequent outbreaks by altering pest life cycles and habitats. Farmers facing increased temperatures or rainfall resort to more pesticides, emphasizing the need for adaptive pest management. This article evaluates the economic benefits of farmer networks for pest management by applying an economic model of social learning to a pilot network in Iowa. Our results show significant variation in the network’s effectiveness. We find that networks are particularly valuable for farmers facing high pest infestation risks, offering over $300 per acre in value against the impacts of extreme heat.1

Social media has the potential to reshape rural agriculture in developing nations in ways that differ from other Information and Communication Technologies (ICTs) because the communication method is mediated through social capital that expands and strengthens relationships. This paper uses two quasi-experimental approaches to estimate the impact of four different communication treatments (including three ICTs) on production practices of small-scale farmers in Rondônia, Brazil. Our difference-in-differences estimation controls for time-invariant unobservable differences in the characteristics of households that do and do not engage with ICTs and draws on a panel from 2009 and 2019. Our propensity score matching is estimated with over 1,200 farmer households surveyed in 2019. We find that the use of social media increases the uptake of both old and new pasture management and cattle practices that are promoted by state and federal agencies via their social media feeds. We also test the impact of the interaction between social media and extension agent visits and find evidence appear to operate independently, potentially as substitutes. Our results suggest that social media is an effective and low-cost way for extension agencies to reach farmers, although we are uncertain as to whether these effects would be stronger with targeted extension visits that use social media to reinforce messaging.

Microplastic pollution from plastic fragments accumulating in agricultural fields threatens the world’s most productive soils and environmental sustainability. This is the first paper to address the challenge of developing a dynamic economic model to analyze the adoption of soil-biodegradable plastic mulches (BDMs) as a sustainable alternative to conventional polyethylene mulches. The model considers the trade-off between BDM degradation rates and agricultural production, seeking to balance the cost of BDMs and the cost of waste disposal. We consider both private and social perspectives under deterministic and stochastic environments. Our findings suggest that BDMs can significantly decrease long-term plastic pollution from single-use plastics in agriculture. For example, increasing landfill tipping fees incentivizes Washington State tomato growers to optimally adopt BDMs with a 61% degradation rate and to till used BDMs into the soil, reducing plastic waste accumulation in landfills. The study highlights the role of economic incentives, such as landfill fees, corrective taxes and the role of risk aversion, in promoting BDM adoption and curbing plastic pollution. The framework presented here offers valuable insights for policymakers and stakeholders seeking to foster sustainable agricultural practices and mitigate global plastic pollution.

This study quantified the relative vulnerability of 3,141 counties in the United States. We built a comprehensive community vulnerability index (CCVI) that considers household, business, and public levels. Eighteen variables related to household socioeconomic characteristics, business size and diversity, local government economic size, social capital, and net immigration were used. In the existing vulnerability indices (CRE, SVI, and SoVI), the indices were constructed by using socioeconomic characteristics of the household. In addition to socioeconomic variables, this study sought to expand the concept of “place-based” by considering the business structure within the community and the potential ability to maintain the existing order of the community to construct a comprehensive index. Additionally, by providing the relative vulnerability of the community at each level (private, business, public), each dimension can provide evidence on which areas are more vulnerable and need remediation than others. We expect that the CCVI can be broadly extended to be used in various forms. In this study, we extend the vulnerability index by including exogenous variables such as climate change. In particular, the extended climate-enhanced CCVI in this study shows that the existing vulnerability index can be strengthened by incorporating extreme climate events.

This study uniquely explores the impact of militarization on carbon emissions in North Atlantic Treaty Organization (NATO) countries from 1985 to 2019 using panel econometric techniques. NATO countries, characterized by substantial defense budgets, advanced technologies, high industrialization, and significant energy consumption, offer a unique context for examining these factors. Employing the Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) and FMOLS models, the research analyzes the long-term and short-term dynamics across three groups: traditional NATO members (Group 1), new NATO members (Group 2), and a combined group (Group 3). Relevant variables used in the estimation are industrialization, technological innovation, energy consumption, and economic growth. Findings reveal that in Group 1, military expenditure and energy consumption significantly increase carbon emissions, while industrialization and technological innovation reduce them. In Group 2, increased military spending and industrialization reduce emissions, but energy consumption and technological innovation increase them. For Group 3, economic growth significantly drives emissions, whereas industrial advancements and selective technological innovations mitigate them. The study underscores the need for tailored environmental policies and technological advancements to reduce carbon emissions, contributing to sustainable development within military alliances. These insights are crucial for policymakers aiming to balance defense needs with environmental sustainability in NATO countries.