Equilibrium Displacement Models: Theory, Applications, and Policy Analysis by Gary W. Brester, Joseph A. Atwood, and Michael A. Boland provides a resource that serves practitioners and students alike. The discussion of EDMs is scholarly, rigorous, and clear throughout the book and it will be a useful resource for all scholars who are interested in analyzing policy impacts. The book is engaging and effective from a pedagogical point of view and provides clarity of explanation and breadth of policy examples. The review is conducted by a group of applied economists with specialization in EDMs, reflecting many different uses and perspectives.
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.
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.
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.
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.
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.
This manuscript provides an overview of an online decision support system (DSS) developed to help growers implement integrated pest management (IPM) practices by delivering short-term risk forecasts for crop management, pest control, and disease prevention. Launched in 1995 by Cornell University’s New York State Integrated Pest Management (NYSIPM) Program, the Network for Environment and Weather Applications (NEWA) leverages local weather data from over a thousand ground-based sensors across the United States to deliver pest risk assessments for 32 models covering fruit, vegetable, ornamental, and agronomic crops. Through real-time weather data summaries, insect and plant disease models, and tailored crop tools, NEWA offers essential resources for agricultural professionals. The platform includes automated alerts for data interruptions and quality-controlled data processing to ensure reliable and timely weather inputs crucial for accurate crop and pest models. NEWA’s open-source framework allows users to customize and expand the system, making it adaptable to diverse agricultural settings. Moreover, historical climate data aids in trend analysis and long-term planning, supporting precision agriculture. The platform empowers Extension educators by providing a foundation for demonstrating sustainable and effective IPM strategies, making NEWA a vital tool for enhancing agricultural resilience and data-driven decision-making.
Teaching faculty across institutions find themselves entrenched in the same challenges as the pre-COVID-19 world. However, research and anecdotal evidence point to enhanced traditional challenges along with new ones altogether. Finding ways to encourage academic curiosity and the true value of genuine student learning have never been more difficult. To address this challenge, five mid-career faculty evaluated Blum’s (2020) book, Ungrading: Why Rating Students Undermines Learning (and What to Do Instead), over a series of four seminars. The book revealed that applications of ungraded teaching methodologies must fit within a formally graded framework. The book also offered positive results along with the challenges of implementation and other outcomes. This teaching commentary is a report of the seminars and provides different suggestions to incorporate the positive aspects of the ungraded classroom into a traditional graded environment.
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.
College teaching can be enhanced by a deeper understanding of student motivation. A highly motivated student can often outperform students with less enthusiasm and ambition. Reflection and consideration of student motivation allows teachers to develop and implement learning environments to maximize student learning outcomes. The objective of this research is to identify the major determinants of student motivation for learning in an academic environment, using an economic model of household production theory. The determinants of student motivation are identified by the construction of a mathematical model of human capital acquisition. The model provides useful implications concerning how college-level instructors could implement strategies that use student motivation to enhance student effort level and learning outcomes. Timely and useful strategies for teachers are derived from the economic model.
Recognized by Western Agricultural Economics Association (WAEA) and Agricultural and Applied Economics Association (AAEA) as an innovative adult education (Extension/outreach) program. Testing Agriculture Performance Solutions (TAPS) was developed at the University of Nebraska-Lincoln’s (UNL) West Central Research, Extension, Education Center (WCREEC) in North Platte, NE. This program was created to enhance Extension education by increasing stakeholder engagement and commitment. This engagement comes in the form of a series of season-long contests, the application of andragogical principles, and the support of Extension programming and materials. Four key groups make this program viable: facilitators, competitors, integrators, and followers. This program is hosted and maintained by the university facilitators, with help from integrators and agribusinesses. Competitors make production and management choices recorded and acted upon by the facilitators, with reports and publications made available to all, including followers. This paper describes the reasoning and application of the program with accompanying feedback by competitors. The current program focuses on farm profitability in conjunction with nitrogen and irrigation efficacy and efficiency. While the program is effective, it is costly and requires special resources that are limited. To address these issues, a virtual version is being developed. This new virtual TAPS will increase flexibility and reduce costs, making it more accessible and useful.
This article highlights the critical role of data visualization in applied economics education and outreach. We first outline some general principles for teaching graph literacy and data visualization principles in and out of the classroom. We then discuss the mechanics of visualizing data—collection, preparation, and visualization—with an emphasis on how instructors can teach each step using the R and/or Python statistical environments. We ultimately contend that the requisite skills for successful data visualization are indispensable for students trained in today’s agricultural and applied economics programs to communicate their research effectively.
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.
Despite the economic importance of the food retailing industry, the literature suggests that food retailers face a major talent recruitment challenge mostly stemming from the negative perceptions of the industry. Therefore, it is crucial that higher education food and agribusiness programs help students better understand and appreciate potential career opportunities and professional career paths. This research develops a teaching innovation that enhances student engagement in asynchronous online learning and explores how such an innovative pedagogy relates to students’ attitudes toward careers in food retailing, with relevance extending across educational formats and disciplines. Through an exploratory quasi-experiment, it is illustrated that innovative pedagogy in online learning may make a difference with respect to attracting students to food retailing careers. The outcomes included more positive attitudes toward a career in food retailing and higher interest levels among the students who were exposed to the teaching innovation compared to students in the control group.
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.
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.
An undergraduate honors program in agricultural economics confers a multitude of advantages, fosters an enriching academic experience, and propels students toward professional excellence within the agricultural sector. A major difficulty that many programs must manage is how to get more students interested and engaged in these programs, particularly as new pathways to our programs are developed. There is a lack of standardization concerning honors content and processes, particularly for transfer students. In programs that are commonly considered “found” majors, students may have the potential for honors research, yet are not sure how to engage in the short two years in the major. This article details existing honor program structures and offers a pathway toward a rigorous and comprehensive curriculum tailored to students who have two years to complete their program. The first year focuses on building a strong foundation in their field. In the second year, students embark on a specialized research project under the guidance of experienced faculty mentors. At the program’s conclusion, participants will have engaged with the complexities of agricultural economics and honed their critical thinking, research, and communication skills.
The use of generative artificial intelligence (AI), which includes tools such as ChatGPT, Bing, and Bard, allows users to find information for specific questions with just a few keystrokes. While this technology is not a replacement for traditional research methods, it can help undergraduate agriculture students be efficient in their time management skills as they move through the various stages associated with writing papers. The question remains whether students increase their retention of knowledge from use of generative AI in conjunction with traditional course lectures. Participants in this research were provided with a video describing generative AI and then completed a course assignment using this technology. Using a pre- and post-evaluation, agriculture students self-assessed how use of generative AI aided retention of knowledge. Questions on the evaluation addressed whether students view generative AI as ethical to use for course assignments and in a professional business environment, if it will aid their future career plans, and if they are more likely to use generative AI due to the assignment. Use of generative AI in conjunction with a course assignment can aid in improved understanding of the benefits and drawbacks associated with this technology. Our analysis provides information on students’ prior use of this technology and how it can benefit their retention of knowledge. Results indicate the extent to which students believe use of AI is ethical in business or professional settings, and previously earned dual enrollment credit indicates their retention of knowledge and change in beliefs toward its usefulness in future careers. Students were largely neutral on AI, aiding retention of knowledge more than a traditional lecture or their normal study methods.
Little attention has been given to the synergistic relationship that can exist between experimental economics research and undergraduate research experiences. In this article, we highlight the successes and challenges from working with more than 70 undergraduate research assistants at the University of Delaware’s Center for Experimental and Applied Economics (CEAE) since 2007. We describe our approaches for funding and engaging undergraduate students and efforts, including our layered mentorship network, to support CEAE’s mission to cultivate a diverse and inclusive research community. We present the results of a survey of CEAE’s alumni to understand how their research experiences influenced their undergraduate education and their post-graduate educational and career endeavors. Synthesizing the reflections of students and the experiences of lead researchers, we outline ten key recommendations regarding how faculty and administrators in agricultural and applied economics programs can design and implement successful undergraduate research experiences, strengthening the pipeline of researchers in our field."
