Abstract: Textbooks designed for business statistics customarily present inferential statistics whose premises contradict the definitions developed in descriptive statistics. In particular, because the standard deviation of a population cannot be calculated if the population mean is unknown, hypothesis tests and confidence intervals for the mean that rely on the population standard deviation pose an inconsistency between lessons. To reduce potential confusion and utilize both class time and students’ homework time efficiently, the present note proposes de-emphasizing these tests and intervals in favor of those that depend on the sample standard deviation.

Abstract: In agricultural fields, automation is rapidly increasing, and the needs of employers are increasingly shifting toward integrating skills in data analysis and effectively collaborating and communicating with colleagues and stakeholders. Preparation for an increasingly integrated world must challenge graduates of agricultural programs beyond their traditional silos to gain an integrated understanding of skills and techniques for the twenty-first-century workforce. Higher education is slowly shifting toward an integrative model where students gain experiences and professors facilitate their education more than talking at them for three hours per week. Here, we call for a transdisciplinary approach to education in agricultural economics where students are presented with opportunities to develop technical skills in data science and analytics and experiences to develop soft skills to ask questions and effectively communicate results. These skills will make graduates more competitive in the workforce as more data become available and more production will be needed while increasingly minimizing the ecological impact.

Abstract: This study investigates empirical data on how students and educators perceive the use of generative artificial intelligence (AI) in agriculture and natural resources (ANR) courses. By surveying participants at a land-grant university, the research explores how different educational backgrounds and sociodemographic factors influence attitudes toward AI adoption. The findings reveal that less than half of the respondents currently use generative AI, with significantly lower usage among first-year and rural students. Key drivers encouraging AI adoption include perceived academic benefits, ease of use, and familiarity with the technology. In contrast, barriers such as concerns about reliability, potential misuse, and information overload deter usage. Seniors and graduate students are more likely to embrace generative AI tools, whereas older and rural students show lower adoption rates. The Analytical Hierarchical Process underscores the necessity for tailored strategies to address specific concerns like inaccurate information and how to leverage AI's advantages, such as streamlining tasks for instructors and providing grammar assistance for students. Future course curricula and institutional policies should incorporate targeted training and additional support to meet specific educational needs, thereby enhancing learning outcomes and ensuring equitable access to the benefits of generative AI tools.

Abstract: This article presents a structured approach for instructors in agricultural economics to explore the evolution of U.S. cotton policy, focusing on a podcast to build background knowledge and the use of real-world letters between agricultural leaders to link political decisions to policy outcomes. By examining key legislative changes, international trade disputes, and correspondence between the Chairman of the House Committee on Agriculture and the Secretary of Agriculture, students gain insights into the intersection between politics and agricultural policy. Classroom activities, discussions on the World Trade Organization (WTO) case of Brazil vs. United States, and assignments involving real-world letters and composing a follow-up letter in an ongoing correspondence enhance students’ understanding and critical thinking skills. The discussion and activities accommodate various levels of student preparedness. Optional homework and class discussions further reinforce the practical applications and real-world implications of cotton policy for both domestic and international stakeholders. These discussions and learning activities help students critically analyze policy decisions, examine the global implications of U.S. agricultural policies, and develop persuasive arguments for policy advocacy.

Abstract: This paper offers an overview of production economics and its usefulness in economic analysis. It presents all key arguments of production economics and efficiency under general conditions and in an integrated manner. An empirical example illustrates how the methods can be applied. The paper also investigates four somewhat unexplored topics in production economics: (1) the effects of a nonconvex technology, (2) the role of profit maximization, (3) economies of diversification, and (4) pricing efficiency and the role of nonlinear pricing. While it is well-known in economics that competitive markets support efficient allocations under a convex technology, this result does not apply under nonconvexity. In this context, we argue that restoring efficiency can require nonlinear pricing. This seems important in evaluating economies of diversification; under nonconvexity, competitive markets can lead to inefficient specialization (which may be particularly concerning applied to environmental management). Implications for management and policy are discussed.

Abstract: The Utah Urban and Small Farms Conference (USFC) provides outreach to new and existing small and urban agricultural producers facing urbanization and environmental challenges. The annual event attracts agricultural producers, home gardeners, stakeholders, and representatives and organizations in Utah and across the United States. Themed sessions given by producers, government personnel, and Extension faculty result in information adoption and implementation, community partnerships, and Extension educational outreach, influencing professional careers and urban agriculture governance. The USFC model may assist organizations and communities facing similar challenges, helping urban and small farmers navigate obstacles and opportunities through education and information sharing.

Abstract: The Extension program discussed in this commentary article was developed using a logic model to provide an economic analysis of Western-X disease (WXD) management at the farm and landscape levels. This program entered the Graduate Student Extension Competition organized by the Agricultural and Applied Economics Association (AAEA). It consisted of a simulated presentation to sweet cherry growers on the economics of tree removal as a disease management practice. The program’s delivery and communication strategies include an online platform, fact sheets, research articles, conference presentations, and workshops. This commentary shows how young professionals can create a successful program using a logic model.

Abstract: The motivations for this case study are recent developments in the U.S. broiler chicken industry involving allegations of an illegal exercise of buyer market power by the five largest broiler processors in the country in the market for broiler grow-out services. This case study introduces economic, business, and legal issues related to the alleged input price-fixing cartel of the five largest broiler processors. The case study describes the processors’ conduct and presents a theoretical framework that may explain market and price effects of the alleged input price-fixing cartel. The teaching note provides suggested answers to discussion and analytical questions, and it also includes multiple-choice questions that can be used as in-class assignments, quizzes, and exam questions. This case study is suitable for a variety of undergraduate and graduate courses taught in agricultural economics and agribusiness programs and for Extension and outreach audiences.

Abstract: This case study examines the Schmidt family’s decision at Pioneer Farm in the U.S. Midwest: whether to adopt Automated Milking Systems (AMS) on their dairy farm. AMS are robots that autonomously milk cows, potentially increasing operational efficiency, reducing labor reliance, and improving milk quality. However, installing AMS requires high upfront costs, maintenance expenses, and adjustments to farm management practices, making it a challenging decision for small and mid-sized dairy operations. Using detailed financial data from Pioneer Farm—a fictional farm based on a real farm in the Midwest—the case enables students to analyze the economic feasibility of AMS adoption and explore its impacts on labor dynamics, animal welfare, and long-term sustainability. The case draws on general industry insights; however, it specifically examines Pioneer Farm’s unique circumstances, providing a realistic and practical framework for classroom discussion. The case illustrates that while AMS can offer substantial long-term economic benefits, initial investment, and maintenance can be major constraints, leading to lackluster adoption rates nationwide. Engaging students in this decision-making process gives them valuable insights into the opportunities and trade-offs associated with technological innovation in the dairy industry. This research also offers valuable lessons for policymakers and educators, contributing to the ongoing discourse on technological innovation in agriculture.