Duration: 10/01/2026 to 09/30/2031

Administrative Advisor(s):

NIFA Reps:

Non-Technical Summary

To support the increasing global population, agriculture needs to produce more with fewer resources while facing harsher weather, new pests and diseases, shifting markets, and higher expectations for sustainability and safety. Meanwhile, growth in farm productivity appears to be slowing, and the way research is funded and performed is shifting toward more private actors. These trends affect food prices, farm incomes, environmental quality, and the resilience of rural communities. Innovation is widely viewed as a critical means to meet these challenges. The project’s goal is to provide clear, reliable evidence that guides efficient agricultural research, innovation, and technology adoption. We will: improve productivity measurement and identify determinants of productivity; document changes in public and private R&D funding and their consequences; explain how universities, startups, and established firms innovate and transfer technology; study how consumer demand, public perceptions, and regulations shape adoption; analyze digitization and AI; and assess the benefits and risks of emerging technologies such as precision agriculture, smart irrigation, and new biotechnologies. Policymakers, research administrators, extension leaders, farmers and ranchers, agribusinesses, and consumer and environmental groups will gain accessible datasets, practical metrics, and timely analyses that clarify what works, for whom, and at what cost. We will produce public datasets; publish peer-reviewed and outreach articles; brief agencies and legislatures; and host workshops and conferences. By linking causes (funding, regulation, technology) to effects (productivity, prices, and adoption), our evidence will help direct research funding, design programs, promote promising innovations, and turne research into results for producers, consumers, and the environment.

Statement of Issues and Justification

The need as indicated by stakeholders

This project serves a diverse range of agricultural sector stakeholders, including producers, trade associations, natural resource managers, environmental groups, consumer groups input suppliers, processors and policymakers engaged in the design and implementation of public policy related to agricultural research and development (R&D) and the adoption and utilization of new agricultural technologies, as well as others who are affected by new agricultural technologies. This ranges from farmers, ranchers, and others engaged in the total supply chains of U.S. agriculture spanning from input suppliers through to American consumers and those who advocate for environmental quality and conservation. Ultimately, every American is a stakeholder in this project.

Agricultural R&D and innovation are essential features of the economy. They are central to maintaining access to food at reasonable costs in the face of increasing demand, by increasing yields, preserving the environment and thus the productivity and sustainability of our limited land and water resources. R&D and innovation also increase product quality and the value-added of agriculture. Innovation reduces the risks and increases the resilience of agriculture in the face of plant and animal diseases, wildfires, weather events, pandemics, and trade disruptions plus increase the environmental friendliness of agriculture.

This project serves its stakeholders by conducting studies of agricultural innovation systems and by developing models and measures of the economic consequences of past and prospective changes in the technologies used on farms, and the role of public and private R&D policy in facilitating those changes. These studies enable the stakeholders in U.S. agriculture to better understand how agricultural R&D contributes to the development and diffusion of new technologies that will help American farmers adapt to changes in their decision-making environments plus maintain the sustainability of agriculture into the future. Understanding and adapting to new technologies is a cross-cutting issue because of the difference of factors that farmers and other stakeholders in U.S. agriculture face plus the need to manage our scarce land and water resources in a sustainable fashion.

Various initiatives at the state, regional, and national level have emphasized the importance of research, extension, and technology transfer in helping farmers adapt to diverse changes they are facing. In this context, stakeholder groups have called for social science research to address various issues related to the economics of agricultural R&D and innovation. These issues can be divided into four broad, yet closely interrelated, areas related to agricultural R&D, innovation, and technology, each with a number of pressing questions:

1. Understanding how R&D, innovation, and new technologies facilitate adaptive responses to change in markets, policies, and the physical environment:

○   How does agricultural R&D and innovation respond to the ever-changing environment, pest, disease, food safety, weather, population/demand growth and biosecurity challenges?

○   How does agricultural R&D and innovation respond to global challenges, such as natural disasters, weather extremes, or pandemics? When and how do private incentives arise for innovation to meet these public and productivity impacting challenges? What is and what should be the role of domestic, and international private and public institutions (e.g., CGIAR, seed manufacturing, state experiment stations, USDA, NSF and others) in addressing these challenges?

○   How does agricultural R&D and innovation respond to evolving market conditions, production shifts and public perceptions of different farming technologies and production systems? What is the role of the government in regulating those technologies and production systems relative to evolving public perceptions?

○    How does agricultural R&D and innovation respond to the emergence of new technological opportunities—such as those created by genome editing, precision data collection, artificial intelligence and machine learning?

○    How does U.S. agricultural R&D respond to increasing competition from China, India, and Brazil and the increasing size and sophistication of their agricultural R&D and production capacities?

○    How does agricultural R&D respond to the introduction of new products that substitute for traditional product categories (such as margarine and vegetable shortening in the early 20^th century, or dairy and meat substitutes today)?

 

2. Understanding the research and development (R&D) institutions and processes that contribute to innovations in food and agriculture:

○  Who is doing R&D and innovation for agriculture and why? What are the regional and national returns to R&D? Who is financing R&D? How is the structure of R&D changing, and why?  What are public and private roles?  Do any commodities or regions portend high returns from increased investment? What are the roles of intellectual property and regulations in incentivizing, constraining, and otherwise shaping both public and privately funded R&D?

○  How does technology transfer and the presence of incentives affect the performance of the innovation supply chain, connecting research labs with development (whether in agricultural research stations, start-ups, or corporations), commercialization, marketing, extension, and the demand side of farmers and beyond?

 

3. Understanding the technology adoption and diffusion processes that bring innovations into commercial practice:

○   What determines the adoption and lack thereof for different technologies? What are potential patterns of spatial and social diffusion?

○   What are the mechanisms by which technologies are introduced or incentivized to farmers and ranchers, whether through extension and private channels? And how effective are they?

○   How are consumer preferences, public perceptions, and private food industry standards and practices influencing technology adoption upstream by producers?

○   To what extent is technological diffusion affected by the growing prevalence of contractual relationships in agriculture such as vertical integration?

○   What are the drivers and barriers of international agricultural technology diffusion?

○   How does adoption of technologies in foreign markets affect U.S. technology providers as well as U.S. farmers and US commodity market and consumer prices?

 

4. Evaluating the impacts of research and innovation along multiple dimensions:

○  How do we characterize and measure productivity changes? How do we account for non-market or public goods & bads in productivity measures? How important are these aspects and other omissions from the widely used productivity measures?

○  How are new information technologies and data systems likely to change agricultural value chains? What is the value and ownership structure of emerging data? What is their effect on integration of agricultural value chains?

○  How much does research contribute to rural development and increase the wellbeing of rural America?

○  Who are the winners and losers when an innovation is introduced? How are those losses absorbed? How might the incidence of losses generate opposition, economically or politically?

○  How do we understand, measure, and value the impact of new technologies on sustainability and resilience of resources on which agriculture depends?

○   What are potential changes in energy production and energy use by agriculture?

In many cases the locus of production and the comparative advantage of different regions is evolving.  Where is this happening and how can R&D contribute to maintain regions of current productivity?

These four broad areas of stakeholder demands are intimately interconnected. The variety of questions across all four areas share many important themes involving production, cost, markets, regional advantage, the environment, health, and security. Crucially, many stakeholders understand the importance of taking a long-term, integrative, dynamic view of these interrelationships.

The first broad area, on adaptive response, emphasizes those interconnections. A unifying factor is the recognition that agricultural research and innovation play a central role in addressing emerging issues by developing and delivering new technologies that better adapt the current system of agriculture to cope with change while meeting  food, sustainability and other stakeholder needs. Much applied agricultural R&D is maintenance or adaptive research, for which it is crucial to understand the need for a (crop or livestock) species to be perpetually improving, adapting and evolving, because competing organisms (such as pests and pathogens) do not cease evolving. This effect is accentuated and accelerated by environmental changes, including land use, weather conditions, incidence of extremes, and water availability. Thus, some R&D is needed for the industry just to stay in place in the face of todays challenges. Similarly, R&D initiatives arise in response to temporary or permanent loss of access to input supplies or to important markets—whether due to trade, travel, or resource depletion disruptions. The development of new technologies that increase flexibility in logistics and trading relationships, re-deploy disrupted commercial links, or substitute inputs, enable the rapid response of value chain structure to mitigate or accommodate the effects of such disruptions on stakeholders. 

NC1034 research pays particular attention to the needs, conditions, or factors that induce innovation, and in turn how the resulting innovations cause or enable agriculture to adapt to meet those stakeholder needs. Such feedback or interdependencies are understood to be facilitated by markets, private investments and public policies. Yet, it is not necessarily a rapid process. It is recognized by stakeholders that there can be long time lags of many years from when research needs are recognized and research funding begins, to when new technologies become viable and are made available to farmers. The process of adoption itself can take considerable time and adopted technologies may continue to be used, having impacts on productivity and the environment, for decades. For this reason, changes in R&D are understood to have very long-cycle effects on productivity and economic wellbeing.

Some stakeholders might not realize they cannot take the future availability of a stream of new technologies as a given. Thus, the second broad set of issues is to understand how socio-economic factors affect the R&D institutions and processes that largely account for the supply of innovations and how evolving factors in society change public support for creating and making those technologies available to producers. It is also key to understand timing characteristics of the innovation creations and diffusion process to understand how reductions in R&D investment influence the future stream of productivity improvements.  NC1034 research serves this stakeholder interest by examining how public and private-sector research systems identify demands for, engage in technology development and ultimately increase productivity, reduce cost and improve environmental friendliness of agricultural systems.

The contributions of agricultural research depend not only on the amount of funding, but also on the sources and mechanisms of funding, the commodity focus and the organization of the research process. Dramatic changes have been made to the organization and funding of agricultural research that pose challenges and present opportunities. Over the last three decades, the total amount of public funding for agricultural R&D has been shrinking in real terms. The share of state agricultural experiment station (SAES) research funded by state governments has declined, relative to the shares funded by the USDA, other federal agencies and the private sector. This situation has led to the recent development of research partnerships between universities, federal labs, and private industries, particularly in the areas of biotechnology and biofuels R&D. The structure and performance of such collaborations plus their allocation of effort across components of the agricultural sector merit serious research investigation to inform public policy debates about public-private research partnerships.

In addition to domestic R&D systems in the United States, NC1034 is also concerned with the organization and efficacy of international research and technology transfer in agriculture. This setting includes the role of traditional public sector sources of research funding and technology transfer such as the World Bank and the CGIAR, as well as private foundations such as the Rockefeller Foundation and the Bill and Melinda Gates Foundation. The NC1034 project also increasingly considers the role of private sector R&D around the world, and how competing private interests may shape incentives to innovate or may directly invest new resources in R&D for agriculture. It also widely considers the ways domestic and international investments benefit domestic interests as well as world conditions.

The third broad issue that stakeholders need to consider is how economic incentives and public policies facilitate or hinder technology adoption,  the diffusion of technologies across the economy and the ultimate value of technology developments to producers, consumers and other industry stakeholders. The returns to farmers and ranchers who adopt a new agricultural innovation can be exceedingly different across a range of farm characteristics, and understanding how environmental, cost, market demand, price, and social characteristics influence uptake is key to interpreting and predicting the diffusion of new innovations and their ultimate impact. Another critical issue influencing adoption is market acceptance of new technologies, such as seen with the emergence of biotechnologies. Increasingly, farmers are expected and required to take into account societal attitudes toward their production practices, food industry production guidelines and product standards, and effects of voluntary and mandatory labeling requirements. The NC1034 project examines the direct effects of public perceptions and food industry standards toward farm and food technologies on agricultural producers and consumers, as well as the incentives and disincentives such factors create for technology development and dissemination.

The fourth broad issue important to stakeholders is impact. Foremost, this depends upon reliable measurement of the contribution of agricultural innovations to agricultural productivity. Growth of agricultural productivity is necessary to continue to feed the world’s growing population and at the same time conserve increasingly scarce natural resources and adapt to ever more challenging production environments plus benefit regions in a manner that does not greatly shift regional economic wellbeing. Productivity is a measure of the amount of agricultural production obtained from a given amount of land, water, and other inputs in a region or the nation. It thus directly relates to the amount of resources required to achieve a given amount of production. Productivity growth is thus a fundamental requirement to meet demands for food, fiber, and biofuels without placing undue pressure on land, water, and environmental resources. Key policy questions are: (a) Is productivity growth slowing down and contributing to rising global food prices; (b) what environmental factors are altering rates of productivity growth; (c) is productivity growth on pace to provide for future global food security? And d) are there high returning commodity or regionally aimed investments that might be pursued? This set of questions relates directly to both the economic and environmental impacts of agricultural production. Increasingly producer groups are being asked to document their resource “footprints” to meet consumer and processor demands for more economic and sustainable production practices.

Finally, stakeholders need information that requires the availability of data sources that describe regional production, cost, and investments as to allow these complex processes. Data on research, adoption, cost and productivity changes were more readily available when the public sector played a larger role. Increasingly agricultural R&D is carried out by the private sector, and data on private R&D activity and outcomes is often proprietary. Thus, considerable research, data collection, and partnership development is needed to measure the intensity of private sector innovation and its impacts. This requires finding, creating, and collecting data and tracking changes in R&D spending, patenting, licensing, complementary input requirements, product testing and costs to producers. Tracking public and private innovation activity (combined with an empirical understanding of the links between them) is critical to assessing whether future productivity will be sufficient to meet future demands while helping keep food production high and costs low along with adapting to increasing sustainability challenges, whether in the form of new pests, new weather patterns, natural disasters, extremes, or new market demands.

 

The importance of the work, and what the consequences are if it is not done.

Virtually all of the analyses of agricultural R&D conducted worldwide are based on methods developed by current or past participants of the NC1034 community (or its predecessor committees). NC1034 participants have conducted pioneering work in

• agricultural productivity measurement;
• estimation of the returns to agricultural research;
• assessment of the incidence of the payoff to agricultural research (the insight being that how and when an innovator captures a benefit from what they created can matter just as much if not more than the size of the benefit they capture);
• the determinants and effects of adoption of new agricultural technologies, particularly of biotechnologies and precision agricultural technologies;
• the implications of changes in intellectual property rights for U.S. agriculture;
• improved design of biotechnology regulations;
• design of processes for research evaluation, priority-setting, and management;
• design and evaluation of research funding mechanisms and processes; and
• evaluation of the impacts of environmental factors on agricultural productivity.

Through such work, members of NC1034 have developed multidisciplinary knowledge about the performance of the research system that has been communicated to policymakers, scientists, farmers, and the public through multiple channels. Publications of group members have been widely cited in policy documents and reports, and NC1034 members regularly serve as committee members for policy advisory groups—such as National Academy of Sciences panels. We regularly respond to requests from federal and state agencies, provide testimony to Congress, and serve as expert witnesses in precedent-setting court cases. Our work is regularly cited in regulatory decisions governing approval and deployment of new agricultural technologies. If the group’s work were not done, some consequences would include:

1. A lack of an objective, data-driven knowledge base to inform public policy debates and private decisions concerning new agricultural technologies;
2. A lack of understanding and appreciation of the contributions to society from agricultural research that benefit both consumers and producers;
3. A lack of understanding of barriers to the development and adoption of innovations that drive productivity growth and their consequences;
4. A lack of understanding the role of agricultural research in maintaining global food security, low food prices, food security and U.S. agricultural competitiveness while helping preserve natural resources, landscapes, and environmental quality at home and abroad;
5. A lack of understanding of the full nature of threats to agriculture posed by pest, natural disaster, weather extremes and other evolving factors, along with a lack of knowledge on R&D and technology diffusion strategies to limit those threats.

 

The technical feasibility of the research.

NC1034 members have developed robust methods for evaluating agricultural innovation systems and technologies. The group’s record of accomplishment of significant publications speaks to the feasibility of such methods. Methods developed by this group for agricultural research evaluation and priority setting have been adopted by practitioners worldwide and have received awards from the Agricultural and Applied Economics Association and other professional bodies.

The demands being placed on agricultural innovation systems have expanded over time and so have the NC1034 group’s methods. Members have drawn upon and shared a variety of novel methods, as problems require. These include applications of agricultural economics, industrial organization, intellectual property analysis, environmental valuation, quantitative modeling, rural sociology, human health and nutrition, machine learning, natural language processing models, and energy economics.

Given unprecedented recent disruptions in agriculture, altered weather extremes, shifting public private investment shares and the plethora of new actors engaged in the agricultural innovation system, NC1034 intends to seek ongoing feedback from various stakeholders on information needsand usefulness of our research findings. In turn we intend to improve the quality and relevance of our information on research impacts and investment returns. This will be initiated by inviting policymakers, industry leaders, venture capital investors, and others to participate in our research workshops and provide feedback plus dialogue on emerging needs. We will then seek out new opportunities to partner with appropriate stakeholders on specific studies and in the provision of key information.

 

The advantages of doing the work as a multistate effort.

NC1034 participants encompass agricultural economists, resource economists, and rural sociologists from a widely dispersed group of land-grant universities, public universities, research institutes, and governmental organizations. Additionally, the score of the research effort and realization of its productivity impacts plus research needs are geographically and commodity-wise dispersed across the nation and globe. In such an environment the work of NC1034 is made more effective as a multi-state effort because it allows knowledge sharing across fields, institutions, geographies and commodities, facilitating a comprehensive analysis of the innovations benefits across segments of the total supply chain along with spillovers from innovation. It also facilitates pooling of resources to increase collaboration, and creates a network for mentoring the next generation of researchers studying agricultural innovation and productivity.

NC1034 provides a vehicle for participants to share and develop the latest social science and quantitative analytical methods in evaluating returns to the many dimensions of agricultural research and the producer, rural and consumer, socio-economic impacts of innovations. Most NC1034 members are also part of multi-disciplinary and multi-state research teams addressing important issues in agricultural technology development, adoption, and impact assessment. As part of those multi-state or multi-disciplinary teams, NC1034 participants take the lead in research problems associated with socio-economic causes and consequences of technological change. NC1034 as a multi-state effort allows participants to take these new evaluation methods back to their state and regional teams and apply them to local problems of interest. NC1034 allows members to benefit indirectly from knowledge gained directly by other members from multi-disciplinary projects. For example, one NC1034 member may gain valuable knowledge and develop valuable information from working on a project and then convey the insights gained to others. Knowledge and information is thus shared so that social scientists and agricultural scientists may work more effectively together, and a diverse group of stakeholders will be informed on findings.

Agricultural research grants often require comprehensive, multi-dimensional evaluations of the regional, commodity-wise, socio-economic and environmental effects of new technologies and production practices. By continuing to develop cutting-edge evaluation methods, NC1034 members are better able to leverage grant funding and, most significantly, to make major contributions to regional and multi-state deliberations on research priorities in a multi-disciplinary setting. Furthermore, through publications and outreach, challenges, adaptation means and opportunities can be conveyed to private and public decision makers altering R&D choices and improving future productivity plus reducing vulnerability.

Multistate collaboration facilitates comparative analyses that can also be more comprehensive. Adoption of technologies and their impacts spill over across commodity, state and international boundaries. While there is a certain value of studying impacts of new technologies in their local and commodity specific context, there is also value in the ability to compare and contrast how new technologies affect agricultural producers in different areas or for different crop and livestock endeavors and in the identification of areas that may benefit from potential new technologies. Federal agencies, private industry, environmental groups and commodity groups are interested in evaluations of technology and environmental implications for technology that can be scaled-up to commodity-wide or national scale impacts. 

Members pool expertise across different production systems and environmental situations. For example, comprehensive evaluation of herbicide-resistant crop varieties requires knowledge of corn, soybean, and cotton production systems or impacts of breeding on milk production not only inform decision making in a local situation but also in different production regions. Pooling research expertise can help identify commonalities in new technology development and dissemination, as well as regional or crop/livestock-specific differences. Another advantage of multistate collaboration is that it can raise awareness of contributions in other fields of research and facilitate acquaintance with other potential research collaborators. It can also suggest research directions for related commodities or enterprises.

NC1034 has a long and successful history of working with the USDA Economic Research Service. University based participants in NC1034 have worked closely with ERS economists, and indeed ERS economists are active participants of NC1034. ERS has been instrumental in collecting and developing data to measure public and private agricultural R&D, productivity and costs. NC1034 has been an important forum to discuss research methods related to data development, productivity/cost estimation, and technology assessment. Through these forums, state-of-the-art methods for productivity measurement have undergone peer discussions and review.

NC1034 offers a unique and enduring community for mentoring the next generation of experts in economics of agricultural productivity and innovation as well as in quantitative analysis of productivity enhancement. Graduate students and junior faculty from across the United States benefit greatly from opportunities to present their research and receive constructive and detailed feedback from more experienced colleagues in a supportive and collegial environment, and learn analytical approaches and have an opportunity to showcase emerging methods. Senior members of the community are enriched by engaging  with younger colleagues who often bring fresh perspectives, deeper technical and newly emerging method expertise in rapidly evolving areas such as digital agriculture, AI, automation, biotechnology, and sustainability analytics. This dynamic exchange makes NC1034 more than just a research group—it serves as an intellectual home where scholars at all stages of their careers can develop ideas, learn new approaches, test methods, and refine/develop policy-relevant information. The community fosters collaboration that spans states, institutions, levels of experience, different training foci, and disciplines, enabling members to build long-term professional networks, to pursue joint projects and exploit relative advantage in a way that advances theory, practice, and R&D information quality and impact. Such collaboration is greatly strengthened by relationships among scientists across states and institutions. Through the newly founded AAEA section “Agricultural Innovation and Productivity," NC1034 will broaden its outreach to graduate students and early-career scholars, actively supporting their engagement in multi-institutional and multi-state research initiatives. By cultivating these connections, the section will not only expand professional opportunities for young scholars but also accelerate the generation of innovative research and policy/industry supporting information that enhance agricultural productivity and sustainability nationwide.

Finally, the multi-state community of scholars also provides opportunities for members to economize and achieve synergies through

• the ability to pool resources and share data;
• avoiding redundancy in research activities;
• increasing specialization and complementarity in research (e.g., one member may work on one aspect of a general problem, while another researcher works on another);
• transfer of both newly evolving and well established but complex analytical methods across research applications;
• cross-pollinate ideas on factors that influence the demand for and impact of technology, generating stakeholder decision making supporting information; and
• transfer of analysis results revealing challenges and opportunities to other applicable areas.

What the likely impacts will be from successfully completing the work.

Future contributions will build on previous ones by exploring emerging issues. These will include:

• continued formal and informal communication with stakeholders on these issues through multiple channels;
• policy engagement as evidenced by contributions to National Academy of Sciences panels, USDA and state funding allocation processes, and responses to requests from other federal and state agencies;
• continued contributions to the support of decision-making regarding the regulation of new technologies in agriculture;
• continued development of multidisciplinary knowledge about the performance of the research system and the returns to investment; and
• a continued stream of high-impact publications and other public communications to disseminate and advance that knowledge base.

Over the next five years, we envision future research to include studies that:

• continue the tradition of modeling and measuring the consequences of innovation with application not only to conventional agricultural technologies but also to deal with novel aspects of the new generations of genome editing, shifting agricultural locations, new market development  and information technologies;
• develop new models and measures of the implications of the evolving funding structure and and management of public agricultural R&D;
• explore the role of innovation in the historical and ongoing structural changes in American agriculture and associated productivity growth;
• develop detailed institutional and quantitative understandings of the causes and consequences of the recent trends in regulation of existing and prospective agricultural technologies;
• explore the role of consumer perceptions and demand for genome-edited foods on R&D investment and regulations;
• investigate the mechanisms by which technologies are introduced to farmers, both through extension and private channels;
• investigate the implications of the growing prevalence of contractual structures in the supply chain for technological diffusion;
• explore the impact of venture capital and private equity investment on agricultural R&D, and the commodity and regional implications of the growing private role;
• explore the roles of startups and established firms in innovating new forms of agricultural enterprises, including “vertical farming,” meat substitutes, and cannabis production and marketing;
• evaluate private-sector agricultural input, producing technology, and processing research using new market-based measures and intellectual property information;
• explore and analyze models of stewardship and ownership of on-farm data in order to understand their implications for the growth and distribution of productivity gains from precision agriculture data collection;
• analyze the impact of adoption of conservation agriculture practices on soil health and resilience and explore the potential of market-based programs to incentivize adoption of conservation practices by agricultural producers;
• assess R&D needs to address opportunities and potential challenges brought by natural disasters, weather extremes, pests, shifts in regional locations of production, and increasing demand.

Related, Current and Previous Work

Scholars participating in NC1034 and its long history of predecessor projects have made unique and resounding contributions to our understanding of the profound economic and social impacts created by agricultural science, commercial innovation, and technological change in agriculture. Virtually every research proposal funded by the USDA or corporate R&D expenditure must be justified in terms of the contributions that it will make, such as improvements in farm productivity, consumer benefits, or resource savings along with rates of return to society. The work of NC1034 contributes, both directly and indirectly, to the intellectual and methodological foundations for such considerations. Many of the landmark contributions in this field have been made by current or past members of NC1034, including but not limited to the following (citation count is based on Google Scholar):

Alekseev, Oleg, Karel Janda, Mathieu Petit, and David Zilberman. "Return and volatility spillovers between the raw material and electric vehicles markets." Energy Economics 137 (2024): 107808. (cited by 5)

Alston, Julian M., George W. Norton, and Philip G. Pardey. Science Under Scarcity: Principles and practice for agricultural research evaluation and priority setting. Cornell University Press, 1995. (cited by 2,381)

Alston, Julian M., Matthew A. Andersen, Jennifer S. James, and Philip G. Pardey. Persistence Pays: US agricultural productivity growth and the benefits from public R&D spending. Springer Science & Business Media, 2009. (cited by 543)

Ball, V. Eldon. "Output, input, and productivity measurement in US agriculture 1948–79." American Journal of Agricultural Economics 67, no. 3 (1985): 475-486. (cited by 391)

Bansal, Sangeeta, and Madhu Khanna. "Corporate Social Responsibility: Motivations and Effectiveness in Developing Countries." International Review of Environmental and Resource Economics 18, no. 1-2 (2024): 123-164. (cited by 3)

Barrett, Christopher B., and Holly Wang. "Introducing Policy Comments." Food Policy 125 (2024): 102627. 

Barrett, Christopher B., Thomas Reardon, Johan Swinnen, and David Zilberman. "Agri-food value chain revolutions in low-and middle-income countries." Journal of Economic Literature 60, no. 4 (2022): 1316-1377. (cited by 387)

Chen, Xiaoguang, Jing Gao, Luoye Chen, Madhu Khanna, Binlei Gong, and Maximilian Auffhammer. "The spatiotemporal pattern of surface ozone and its impact on agricultural productivity in China." PNAS Nexus 3, no. 1 (2024): 1-15. (cited by 7)

Christian, Paul, and Christopher B. Barrett. “Spurious Regressions and Panel IV Estimation: Revisiting the Causes of Conflict.” The Economic Journal 134, no. 659 (2024): 1069-1099. (cited by 42)

Dorfman, Jeffrey H., Scott H. Irwin, Munisamy Gopinath, and David Zilberman. "The future of agricultural and applied economics departments." Applied Economic Perspectives and Policy (2024). (cited by 7)

Evenson, Robert E., and Yoav Kislev. Agricultural Research and Productivity. Yale Univ. Press, 1975. (cited by 573)

Feder, Gershon, Richard E. Just, and David Zilberman. "Adoption of agricultural innovations in developing countries: A survey." Economic Development and Cultural Change (1985): 255-298. (cited by 5,723)

Fuglie, Keith O., Sun Ling Wang, and V. Eldon Ball, eds. Productivity Growth in Agriculture: An international perspective. CABI, 2012. (cited by 179)

Huffman, Wallace E., and Robert E. Evenson. Science for Agriculture: A long-term perspective. John Wiley & Sons, 2008. (cited by 772)

Hutchins, Jared P., Scott H. Irwin “Productivity Growth from Genetic Improvement: Evidence from Illinois Soybean Trial Data.” American Journal of Agricultural Economics (2025) (cited by 2)

Hutchins, Jared. "The US farm credit system and agricultural development: Evidence from an early expansion, 1920–1940." American Journal of Agricultural Economics 105.1 (2023): 3-26. (cited by 23, won AJAE Outstanding Article Award)

Khanna, M., Basso, B., O’Hara, J., Zilberman, D., & Hochman, G. (2025). Climate-smart biofuel policy as a pathway to decarbonize agriculture. Science, 389(6761), 687–689. https://doi.org/10.1126/science.adw6739 

Moschini, G., and H. Lapan, 1997. “Intellectual property rights and the welfare effects of agricultural R&D.” American Journal of Agricultural Economics, 79(4): 1229-1242. (cited by 338)

Rohr, Jason R., Alexandra Sack, Sidy Bakhoum, Christopher B Barrett, David Lopez-Carr, Andrew J Chamberlin, David J Civitello, Cledor Diatta, Molly J Doruska, Giulio A De Leo, Christopher J E Haggerty, Isabel J Jones, Nicolas Jouanard, Andrea J Lund, Amadou T. Ly, Raphael A Ndione, Justin V Remais, Gilles Riveau, Anne-Marie Schacht, Momy Seck, Simon Senghor, Susanne H Sokolow, Caitlin Wolfe, “A planetary health innovation for disease, food, and water challenges in Africa,” Nature, vol. 619, no. 7971 (July 27, 2023), pp. 782–787. (cited by 58)

Sunding, David, and David Zilberman. "The agricultural innovation process: research and technology adoption in a changing agricultural sector." Handbook of Agricultural Economics (2001): 207-262. (cited by 1,434)

 

Review of NIMSS data suggests there is very little duplication of NC1034 research activities. NC1034 research primarily applies two fields of social science—economics and sociology—to questions regarding the management of research and its impacts on the agricultural economy, on society, and on the environment. According to our search of the NIMSS database, we find only one recent multi-state project with (weakly) related activities:

• S1090: AI in Agroecosystems: Big Data and Smart Technology-Driven Sustainable Production. S1090’s duration is 2021-2026 and its focus is the technological applications of AI and big data in agricultural production. Although it has a social-economic component in the project, its analysis is confined to analyzing the impact of individual AI technology on expected net returns and economic risk upon adoption. In contrast, NC1034 covers almost every aspect of agricultural innovation, ranging from innovation funding sources to the social, economic, and environmental impact of the whole spectrum of technological innovation. Some members of NC1034 are founding members of S1090.

NC1034 members are highly productive scholars, publishing altogether over 1,000 peer-reviewed journal articles since the inception of the current project in 2016. In addition, they have made numerous contributions to edited volumes and government reports. They have also been active in several collaborative research and publishing efforts. For example, NC-1034 members have contributed: (a) several chapters to a volume by the prestigious National Bureau of Economic Research (NBER) on Economics of Research and Innovation in Agriculture, edited by Petra Moser and published by University of Chicago Press, (b) co-editorship and chapters for a volume on California Agriculture Dimensions and Issues, (c) co-editorship and submissions to a special issue of the journal Sustainability on “Accelerating Bioeconomy Growth through Applied Research and Policy Change,” co-edited by Wesseler and Zilberman, and (d) co-editorship for the Choices Magazine, an outreach publication of the Agricultural and Applied Economics Association.

NC1034 members at the USDA Economic Research Service and at land-grant universities have benefitted from their mutual engagement in the project. ERS economists responsible for construction and integration of national and state-level productivity accounts are NC-1034 participants, while academic NC1034 participants have made important contributions (see Ball & Norton, 2012) and have advised USDA regarding advances and improvements in the official productivity data (Shumway et al, 2015). In 2023, the NC1034 annual meeting was held consecutively with the Agricultural Productivity Growth Conference co-organized by ERS, creating synergies between participants of the two events. Since 2016, NC1034 members at the USDA ERS and universities have established several cooperative research agreements, including one with Iowa State University on R&D and agricultural productivity growth in the United States, one with the University of Arizona on the economics of plant disease control research, and one with Colorado State University on venture capital funded agricultural innovation. Five of the NC1034 members are research fellows (and the director) of the International Science & Technology Practice & Policy (InSTePP) program that brings together scholars at the University of Minnesota and elsewhere to engage in economic research on science and technology practice and policy, emphasizing the international implications.

Objectives

1. Improve measures of agricultural productivity growth; examine drivers and barriers to agricultural productivity growth; study the consumer and producer impacts of agricultural productivity growth; characterize and quantify the impacts of natural disasters, societal crises, regional conditions, and policy shocks on agricultural productivity; and analyze how technological innovations help agriculture to adapt to such challenges.
   
2. Document and explain changes in agricultural research funding by public and private sectors in both high-income and emerging economies as well as the causes and potential consequences of these changes.
   
3. Explain the benefits and risks of different types of public-private R&D linkages and technology transfer mechanisms for different technological and market contexts; examine and compare agricultural innovations by startups, incumbent private companies, and the public sector; investigate how different funding mechanisms (e.g., public, private, partnership) may affect research and agricultural innovation, and the potential improvements on and implications for university research and public-private partnership.
   
4. Explain the role of consumer demand, public perceptions, costs, prices, and regulation on the adoption of new technologies in agriculture and food, as well as their impact on decisions to invest in R&D of those technologies; estimate the heterogeneous effects of technology adoption on agribusinesses and producers of different characteristics.
   
5. Investigate the causes, nature, and impacts of digitization of agricultural production and artificial intelligence (AI) on supply chains as well as the influence of data and information technologies on management, productivity, and the structure of the industry; explore the different options for data ownership and management and the associated impact on farmer autonomy, technology adoption, and policy interventions.
   
6. Assess the implications of emerging novel agricultural and food technologies (such as vertical agriculture, smart irrigation systems, precision crop and livestock monitoring technologies, genetically modified crops/livestock, cultured meat products, robotics and machine learning) and how their development is influenced by changes in population, lifestyles, resources, and new technological opportunities; study how AI-driven technologies may shift the perceived risk of liabilities between producers, service or product providers, and AI developers, and the associated implications on adoption decisions and possible insurance and risk transfer mechanisms.
   
7. For each of the preceding objectives, raise awareness among key decision makers, stakeholders, and the public about the issues, provide evidence about causes and consequences, and inform choices for action and intervention.
   

Methods

Methods

Methods to Achieve Objective 1 (Improve measures of agricultural productivity growth; examine drivers and barriers to agricultural productivity growth; study the consumer and producer impacts of agricultural productivity growth; characterize and quantify the impacts of natural disasters, societal crises, regional conditions, and policy shocks on agricultural productivity; and analyze how technological innovations help agriculture to adapt to such challenges.)

Research will continue to refine measurement of agricultural productivity, which assesses how much output one can obtain from a given quantity of inputs, or conversely, the resource requirements to generate a given quantity of output both nationally and regionally. Measuring productivity accurately is a non-trivial issue, as one must determine how to handle changes in the quality of inputs and highly influential regional resource and weather conditions, which typically arises when new technologies (e.g., genetic varieties) are introduced and adopted.

Scholars participating in NC1034 (and its predecessor projects) from both the ERS and academia play a central role in developing, improving, and implementing methods for productivity measurements. The USDA Economic Research Service (ERS) is responsible for constructing the agricultural productivity accounts for U.S. agriculture. These accounts generate the official estimates of productivity in the U.S. farm sector. They include estimates of outputs, inputs, and total factor productivity (TFP), the conventional measure of agriculture’s contribution to innovation in the U.S. economy overall (Schramm et al. 2008). ERS updates the U.S. agricultural productivity data every two years and posts the data online with detailed documentation. To communicate with a general, non-technical audience, major findings are published on the ERS website data page as well as in an article in Amber Waves (the magazine published by ERS).

NC1034 participants will be engaged in developing updated measures of international and U.S. state-level productivity. There are several challenges to be overcome.

First, in the absence of reliable farm labor and other resource usage data at a fine enough scale to infer their influence on county or fine level  agricultural production, USDA-ERS researchers have developed new approaches and data sources to measure quality-adjusted state-level labor indices so that important state-level U.S. agricultural productivity accounts could continue to enable high quality research on the economics of U.S. agriculture for public and private decision making. Ongoing advances in labor and other resource saving technologies, including precision agriculture, irrigation efficiency, pest control and fertilizer use with advanced sensors, artificial intelligence, and autonomous machinery, continue to influence measures of the labor and other factor input to agriculture.

An increasingly important area of methodological development concerns the need to consider environmental impacts and natural resource input use in productivity accounts, as well as evaluation of methods for estimating "water footprints", fertilizer use, feed consumption and other environmental indicators for agricultural production. The longer run relationship between the outputs and the mix of natural resource, intermediate product and chemical inputs of agriculture are central to concepts of “conservation,” “sustainable,” and “regenerative” agriculture. As private initiatives to meet market demand for sustainably-grown agricultural products continue, and even more so as policies are developed to incentivize farmers to improve environmental quality, provide ecosystem services, and produce under increasing weather extremes, will require high-quality productivity measures that accurately account for these environmental ond other factors of production across time and space.

There is concern over the rate at which U.S. and global agricultural productivity is growing, with increasing evidence suggesting that agricultural productivity growth is slowing. This consideration leads to policy questions of what has accounted for this slowdown. Productivity growth has implications for U.S. agricultural exports and imports, world commodity prices, and food security. Productivity accounts for a rising share of the increase in agricultural production, easing pressure on natural resources to supply the rising demand for food.

In addition, efforts are devoted to measuring and assessing the economic valuation of biophysical and ecological resources, implementing economic valuation for non-market amenities, and using those measurements to model policy options (University of Illinois).

The analysis of natural disaster and extreme weather impacts on agricultural productivity (Cornell, Texas A&M) involves multi output-multi input econometric analysis of agricultural productivity growth. The econometric analysis will typically link productivity growth with natural disasters and extremes to capture the underlying responsiveness of the agricultural sector. This empirical relationship is validated by considering a range of model specifications plus doing work across regions with different natural endowments.

Research (Texas A&M) is evaluating the effect of extreme weather events on yields of 18 crops and milk production, feedlot finishing weight, calving rates, and calf survival.  Possible adaptations including irrigation, land use change, crop mix alteration, livestock mix and livestock stocking rate are being evaluated. Simulations are used for acreage allocation, animal numbers and market price effects.

Research (University of Illinois) will assess the impact of alternative technologies, including localized load-shifting technologies, such as electrochemical fertilizer production, on agricultural communities. The work aims to quantify the effect of the alternative scenarios on profit and agricultural production. This analysis aims to highlight pathways for improving the economic viability and environmental sustainability of agricultural output.

Finally, the technique of welfare analysis together with dynamic models of adoption (University of California Berkeley, Rutgers University, and Texas A&M ), as well as spread of disease and the incidence of extreme weather events, are used to assess how new technologies (such as new varieties, genetic modifications, precision farming, new practices) reduce the negative effects of expected changes, and how economic impacts are divided among technology manufacturers, producers, and consumers. Research can also assess the impact of alternative regulations on the adoption of technologies and the implication of regulatory-induced delays in adoption. This will expand the framework developed by Wesseler and Zilberman (2014) and Alston et al. (2010) along with the sector modeling framework employed in many studies out of Texas A&M.

 

Methods to Achieve Objective 2 (Document and explain changes in agricultural research funding by public and private sectors in both high-income and emerging economies as well as the causes and potential consequences of these changes.)

Differences in public and private-sector agricultural research funding across geographic locations and over time are associated with different explanatory factors using econometric estimation techniques. For public spending, this includes differences across states within the United States as well as across countries. Determinants of private-sector R&D expenditures, patenting, and varietal field trials are estimated using similar methods. Further, data on public and private R&D efforts are compared with productivity data to estimate how changes in R&D activity over space and time affects trends in agricultural productivity growth. Implications for food prices and food security can then be assessed.  Differences are also examined in efforts by commodity with an eye toward identifying what returns might be to shifts in investments and changes in public private efforts and roles.

Thus, research examines the linkages from underlying factors, to agricultural R&D investment, to productivity growth, and ultimately to food costs and security. Returns to research are evaluated using a broader set of metrics than just agricultural production. The influence on other outcomes such as nutrition, health, and the environment are likewise measured and assessed (University of California Berkeley and University of Illinois). One line of work (incl. Colorado State, University of California Berkeley, Clemson, USDA-ERS) will examine the increasing role of venture capital investments in private agricultural R&D and factors that explain these growing private investments. Further, project members from Texas A&M will examine the commodity specific relationships and the contributions of public and private efforts.

 

Methods to Achieve Objective 3 (Explain the benefits and risks of different types of public-private R&D linkages and technology transfer mechanisms for different technological and market contexts; examine and compare agricultural innovations by startups, incumbent private companies, and the public sector; investigate how different funding mechanisms (e.g., public, private, partnership) may affect research and agricultural innovation, and the potential improvements on and implications for university research and public-private partnership.)

Changes in public research have impacts on private R&D just as changes in private R&D have impacts on public research. Ongoing research seeks to quantify the impacts of public research on aggregate private R&D and examine the potential complementary or substitute relationships between these major sources of R&D overall and from a commodity specific lens.

While intellectual property protection is vital for generating private incentives for innovation, there are also benefits from allowing researchers access to information and technologies. Ongoing research assesses such trade-offs. Specific projects (Colorado State, University of Illinois) include analysis of patenting by universities in gene-editing along with licensing mechanisms to allow access to gene editing for specific applications in agriculture.

Projects (Colorado State, Auburn, and Montana State) will apply natural language processing techniques to examine the similarity between patents granted to agricultural startups, large agribusinesses, and public agricultural research institutions in the United States. Measures of novelty, impact, and importance of patents will be constructed. Analysis will draw on detailed data on technologies being developed by private companies and agricultural startups with venture capital funding (developed by Colorado State and the U.S. PTO) to quantify the emergence of novel agricultural and food technologies and factors associated with their funding and development.

 

Methods to achieve Objective 4 (Explain the role of consumer demand, public perceptions, costs, prices, and regulation on the adoption of new technologies in agriculture and food, as well as their impact on decisions to invest in R&D of those technologies; estimate the heterogeneous effects of technology adoption on agribusinesses and producers of different characteristics.)

Various experimental and non-experimental methods, including discrete choice experiments (SDSU, University of California Davis, Purdue) and webscraping, are used to estimate consumer preferences and willingness to pay for new and emerging technologies (such as gene editing) in the food sector and assess their implications on producers’ adoption of technologies and practices.

Several projects (University of California Davis, Minnesota, Virginia Tech) involve measuring the returns to genetic improvements of crops and livestock using conventional breeding methods as well as modern biotechnology, considering both the technological and scientific possibilities, farming realities, and market acceptance constraints. This involves combining various methods including farm production budgets, commodity market price and cost models, and consumer and producer attitude surveys and experiments.

Econometric modeling is used to understand the various determinants of agricultural producers’ adoption of technologies such as genetically modified crops, gene-edited crops, precision agriculture technologies, and conservation agriculture practices. Interdisciplinary approaches and statistical learning techniques are used to assess the link between producers' adoption of conservation agriculture practices, productivity, soil health, and yield stability. This is a precursor to developing policies and programs that internalize the public good aspects of conservation agriculture practices and provide market-based solutions and incentives to scale up the adoption of agricultural practices and technologies that mitigate the adverse environmental impacts of intensive agriculture production (University of California Berkeley and University of Illinois).

Methods to achieve Objective 5 (Investigate the causes, nature, and impacts of digitization of agricultural production and artificial intelligence (AI) on supply chains as well as the influence of data and information technologies on management, productivity, and the structure of the industry; explore the different options for data ownership and management and the associated impact on farmer autonomy, technology adoption, and policy interventions.)

Welfare analysis is used to assess the distributional impacts of new precision farming  and genetic modification technologies on agriculture and the environment, that is how the economic impact of the technology’s adoption is divided among technology manufacturers, seed suppliers, producers, consumers, and the environment, using frameworks developed by Moschini et al. (2000), Alston et al. (2010), Wesseler and Zilberman (2014), and Ciliberto et al. (2019), among others.

One line of research (University of Illinois) analyzes the role of cooperative data ownership in the Dairy Herd Improvement program for the development of the dairy sector as well as how such information affects technology adoption and farm management decisions. Emphasis is given to both the private and public benefits that cooperative data systems provide. This research is complemented by analyzing current trends in adoption of genetics on dairies, and what role disseminating information through cooperative data ownership plays in farmer decisions.

Methods to achieve Objective 6 (Assess the implications of emerging novel agricultural and food technologies (such as vertical agriculture, smart irrigation systems, precision crop and livestock monitoring technologies, genetically modified crops/livestock,  cultured meat products, robotics and machine learning) and how their development is influenced by changes in population, lifestyles, resources, and new technological opportunities; study how AI-driven technologies may shift the perceived risk of liabilities between producers, service or product providers, and AI developers, and the associated implications on adoption decisions and possible insurance and risk transfer mechanisms.)

Econometric, theoretical, simulation, sector modeling, and survey methods will be employed to estimate the impact of emerging technologies in the agriculture and food sector. For instance, to ensure credible inference, we will combine causal identification strategies (e.g., staggered adoption or event-study designs, matched difference-in-differences, and instrumental variables) with structural models, sector scoped models and numerical simulation to translate reduced-form estimates into welfare, risk, market price/quantity and adoption metrics. Analyses will draw on various datasets such as Agricultural Resource Management Survey (ARMS) data, remote sensing data, targeted survey data, and patent data. In addition, economic appraisal of a continuation of current production and geographic locus trends plus the influence of alternative adaptation and mitigation actions will be undertaken. This will involve methods development, application, and dissemination. Work will also be done on program design to facilitate private-sector adoption (University of California Berkeley and University of Illinois). 

Measurement of Progress and Results

Outputs

• New datasets reporting national and regional quantities of agricultural inputs, outputs, and costs
• New datasets measuring public and private research investments, patenting, and other inventive activity overall and by commodity
• Results from analysis of data to estimate factors determining inventive activities
• Results from analysis of data to estimate the effect of agricultural R&D on productivity on a national and regional basis
• Results from analysis of data to estimate the effect of natural disasters and extreme weather events on productivity
• Results from analysis of data to estimate economic returns to investments in agricultural R&D and extension overall and by production system
• Results from analysis of patent text data to examine novelty, impact, and importance of innovations
• Publications that will assess the economic and social impacts of new technologies, including biotechnology, bioenergy, information technologies, and natural resource conserving technologies
• Publications that will assess the productivity, economic, environmental, and social impacts of drought, weather extremes, and other disruptive events in addition to prospects and program design for adaptation and mitigation

Outcomes or Projected Impacts

• The project will provide analysts and research program planners throughout the United States and worldwide with improved methods to evaluate impacts of technological change and to conduct economic evaluations of alternative research policy options. Research administrators will be provided with improved methods to analyze data and information and to make recommendations to decision-makers.
• Outputs of the project will be used to enhance knowledge and awareness among state agricultural experiment station directors, NIFA, and groups that influence the allocation of public research and extension dollars, of the impacts of national and regional changes in research and extension funding levels and funding mechanisms.
• Project participants will continue to contribute to projects and publications of The Board on Agriculture and Natural Resources (BANR). BANR is the major program unit of the National Research Council (NRC) responsible for organizing and overseeing studies on issues of agricultural production and related matters of natural resource development, including forestry, fisheries, wildlife, and land, chemical, and water use. The goal of the NRC, organized by the National Academy of Sciences, is to further knowledge and advise the federal government on critical issues in science and technology. Project participants will continue to be directly involved in publications and to be sources of information inputs to BANR assessments.
• Organizations furthering international agricultural research and technology transfer such as the CGIAR Consortium and the World Bank will be supported in their deliberations by information from and technical approaches for understanding the impacts of research funding developed by project participants.

Milestones

(2026):1. Organization of the NC1034 annual research symposium, 2. Organize track sessions under the section Agricultural Innovation and Productivity at the annual meeting of the Agricultural & Applied Economics Association (https://www.aaea.org/meetings), 3. Organization of and participation in sessions of the International Consortium on Applied Bioeconomy Research annual conference (https://icabr.net/), 4. Organization of a workshop and participation in sessions on circular bioeconomy.

(2027):1. Organization of the NC1034 annual research symposium, 2. Organize track sessions under the section Agricultural Innovation and Productivity at the annual meeting of the Agricultural & Applied Economics Association (https://www.aaea.org/meetings), 3. Organization of and participation in sessions of the International Consortium on Applied Bioeconomy Research annual conference (https://icabr.net/).

(2028):1. Organization of the NC1034 annual research symposium, 2. Organize track sessions under the section Agricultural Innovation and Productivity at the annual meeting of the Agricultural & Applied Economics Association (https://www.aaea.org/meetings), 3. Organization of and participation in sessions of the International Consortium on Applied Bioeconomy Research annual conference (https://icabr.net/).

(2029):1. Organization of the NC1034 annual research symposium, 2. Organize track sessions under the section Agricultural Innovation and Productivity at the annual meeting of the Agricultural & Applied Economics Association (https://www.aaea.org/meetings), 3. Organization of and participation in sessions of the International Consortium on Applied Bioeconomy Research annual conference (https://icabr.net/).

(2030):1. Organization of the NC1034 annual research symposium, 2. Organize track sessions under the section Agricultural Innovation and Productivity at the annual meeting of the Agricultural & Applied Economics Association (https://www.aaea.org/meetings), 3. Organization of and participation in sessions of the International Consortium on Applied Bioeconomy Research annual conference (https://icabr.net/).

(2031):1. Organization of the NC1034 annual research symposium, 2. Organize track sessions under the section Agricultural Innovation and Productivity at the annual meeting of the Agricultural & Applied Economics Association (https://www.aaea.org/meetings), 3. Organization of and participation in sessions of the International Consortium on Applied Bioeconomy Research annual conference (https://icabr.net/).

Projected Participation

View Appendix E: Participation

Outreach Plan

This project places a premium on communicating and disseminating research results to Experiment Station Directors, Deans of Colleges of Agriculture, national research administrators, and national policymakers and research directors responsible for justifying and allocating resources to research in agriculture and natural resources.  We will also provide information to industry groups that can help support private industry decision making and identification of needed areas of R&D investment.

Participants provide background assessments, materials based on project experience, research findings, and expert input across all three branches of the federal government and to  agricultural sector stakeholders:

• The Department of Justice periodically engages participants in NC1034 for background information concerning the potential impact of mergers and acquisitions of agricultural companies on agricultural innovation. It is expected that participants will continue providing background materials and assessments as requested in support of such evaluation efforts.
• Participants work with the U.S. Patent and Trademark Office, in the Department of Commerce, on intellectual property policy and effects on innovation in agriculture.
• Project findings have been cited in Congressional Research Service reports to Congress and project members regularly provide direct testimony before state and federal legislative bodies.
• Participants regularly provide talking points based on project to Land Grant University deans and experiment station directors in support of their testimony before Congressional agricultural and natural resource committees
• Participants contribute to authoring/filing Amicus Briefs for cases before the United States Supreme Court
• Participants have served as expert witness in a range of federal cases involving agricultural industry, technology, and intellectual property disputes.

There is an active exchange of information, data, and expertise between ERS economists and other NC1034 members, beneficial to both. ERS forums, publications and briefings are a critical means of bringing NC1034 research findings to the attention of policymakers in timely and accessible formats. Close collaboration with ERS economists will continue throughout the next phase of the project.

Participants also work with agricultural policy and commodity groups such as the Farm Bureau, Cotton Incorporated, and the United Soybean Board to develop materials based on project research. Examples include providing supporting research and developing infographics about the economic benefits of herbicide resistance management, water conservation, and integrated pest management. Participants are also regular speakers at workshops organized by the Farm Foundation and contribute to the Foundation’s Issue Reports on topics such as returns to public investment in research and extension and university-industry relations in biotechnology research.

Information will be provided on consumer benefits of agricultural R&D linking effects of food availability, prices and security.

Participants will continue to engage with international organizations:

• the CGIAR system
• the OECD Network on Agricultural Total Factor Productivity and the Environment
• the OECD Co-operative Research Programme on Biological Resource Management for Sustainable Agricultural Systems
• the Food and Agriculture Organization of the United Nations 
• the World Intellectual Property Organization 
• ICABR

A primary channel for communication of the results of NC1034 research will continue to be peer-reviewed journal articles and book chapters. As indicated above, between 2020 and 2025 participants in NC1034 produced over 400 such publications, including select publications in prominent economic and agricultural and resource economics journals, as well as high circulation scientific journals such as Science, Nature, Nature Biotechnology, Nature Communications, PNAS, and the PLOS journals. We expect the output to continue at a similar rate and impact factors over the next phase of the project.

A key means of outreach to sectoral stakeholders and the policy community is publication of research results in more accessible outreach publications:

• Project participants frequently publish project findings in the magazine Choices, the principal outreach vehicle of the Agricultural and Applied Economics Association (AAEA).
• Participants have also coordinated publications in the online journal AgBioForum, which is “committed to providing a space where academics, private and public sector analysts, and decision makers can present timely scientific evidence to enrich the ongoing public debate regarding the economic and social impacts of agricultural biotechnology.” AgBioForum is financed by the Illinois Missouri Biotechnology Alliance (IMBA). IMBA is supported by a Congressional Special Grant to provide funding for university biotechnology research.
• Research findings have been and will continue to be published in a variety of outreach publications and online extension series of land grant universities. These include, for example, the University of California’s Agricultural Issues Center Briefs, ARE Update, and California Agriculture, Iowa State University’s Iowa Ag Review, University of Illinois’ FarmDoc project, South Dakota State University’s online extension platform, and Colorado State University’s online extension Fact Sheets. We will also use online outlets where information can be accessed through search engines employing careful choice of keywords to facilitate information retrieval and inclusion in emerging AI supported search result reports.

Results of the project will be integrated into Cooperative Extension in a number of ways. First, participants will be conducting research projects measuring the economic returns to specific Cooperative Extension programs. These include extension programs for water conservation, energy conservation, rangeland management, seed potato certification, genetically engineered crop adoption, and integrated pest management. The value of extension programs and technology adoptions will be communicated to state legislators and other decision makers through Cooperative Extension publications, testimony, briefings and press releases. Ongoing project research has also estimated the contribution of extension funding to state-level productivity growth.

To keep up with new developments in social media, participants are increasingly making project findings accessible via university press releases and websites, development of infographics (often in collaboration with industry groups), guest articles in farm organization newsletters, blogs, and Cooperative Extension webinars.

Organization/Governance

The project will be organized as a Multi-state Research Project consistent with the specifications for membership and organization given in the Guidelines for Multi-state Research Activities. The project technical committee shall consist of one vote from each cooperating university and agency as appointed or otherwise designated by each respective organization, an administrative advisor appointed by the Association of North Central Experiment Station Directors and a representative of the National Institute of Food and Agriculture (NIFA).

The executive committee for NC-1034 shall consist of a chairman and secretary, elected by the full membership as well as ad hoc members added to particular tasks like meeting organization and report/testimony preparation. Members of the executive committee will be elected annually and may succeed themselves. This committee will have the major responsibility for coordinating an annual research symposia contributing to the Multi-state Research Project.

The chairman of the project technical committee will prepare the annual report, summarized from material supplied to him by the technical committee. The chairman will send two copies of the final draft of the annual report with original signature of recommendation and an approval block for signature to the Administrative Advisor. The Administrative Advisor will make the appropriate distribution.

Meetings will be held at least once a year at a time and place mutually agreed upon by the technical committee with the approval of the administrative advisor. The secretary will have responsibility of creating a minutes document for each project wide meeting. The secretary will be responsible for distribution of approved minutes to the membership. The Administrative Advisor will send approved copies to NIFA and Directors of participating SAES and other agencies. A research symposium, communicating on the work of individuals inside and outside the project, will normally be held in conjunction with the annual meeting.

Literature Cited

Alston, Julian M., Andersen, Matthew A., James, Jennifer S., & Pardey, Philip G. 2010. Persistence Pays: US Agricultural Productivity Growth and the Benefits from Public R&D Spending. Springer Science & Business Media.

Alston, Julian M., George W. Norton, and Philip G. Pardey. 1985. Science Under Scarcity: Principles and practice for agricultural research evaluation and priority setting. Cornell University Press.

Alston, Julian M., Philip G. Pardey and Xudong Rao. 2020. The Payoff to Investing in CGIAR Research. Washington DC: SoAR Foundation.

Alston, J. M., Norton, G. W., & Pardey, P. G. 1995. Science Under Scarcity: Principles and Practice for Agricultural Research Evaluation and Priority Setting. Cornell University Press.

Ball, V. Eldon. 1985. "Output, input, and productivity measurement in US agriculture 1948–79." American Journal of Agricultural Economics 67, no. 3: 475-486.

Ball, V. Eldon and George Norton. 2012. Agricultural Productivity: Measurement and Sources of Growth. Springer Science & Business Media.

Ciliberto, F., G. Moschini, and E. Perry, 2019. “Valuing product innovation: genetically engineered varieties in US corn and soybeans.” The RAND Journal of Economics, 50(3): 615-644.

Evenson, Robert E., and Yoav Kislev. 1975. Agricultural Research and Productivity. Yale Univ. Press.

Feder, Gershon, Richard E. Just, and David Zilberman. 1985. "Adoption of agricultural innovations in developing countries: A survey." Economic Development and Cultural Change 33.2: 255-298.

Fuglie, K. O., Wang, S. L., & Ball, V. E. (eds.) 2012. Productivity growth in agriculture: an international perspective. Cambridge, MA: CABI.

Huffman, Wallace E., and Robert E. Evenson. 2008. Science for Agriculture: A long-term perspective. John Wiley & Sons.

Khanna, M., Basso, B., O’Hara, J., Zilberman, D., & Hochman, G. (2025). Climate-smart biofuel policy as a pathway to decarbonize agriculture. Science, 389(6761), 687–689. https://doi.org/10.1126/science.adw6739 

Moschini, G., H. Lapan, and A. Sobolevsky, 2000, “Roundup Ready soybeans and welfare effects in the soybean complex,” Agribusiness: An International Journal, 16(1): 33-55.  

Schramm, C., and 14 others. 2008. Innovation Measurement: Tracking the State of Innovation in the American Economy. A Report to the Secretary of Commerce by the Advisory Committee on Measuring Innovation in the 21st Century Economy.

Shumway, C. Richard, Barbara M. Fraumeni, Lilyan E. Fulginiti, Jon D. Samuels, and Spiro E. Stefanou. 2015. Measurement of U.S. Agricultural Productivity: A 2014 Review of Current Statistics and Proposals for Change. Report of the Review Committee for USDA Productivity Accounts, Working Paper Series WP 2015-12, School of Economic Sciences, Washington State University.

Sunding, David, and David Zilberman. 2001. "The agricultural innovation process: research and technology adoption in a changing agricultural sector." Handbooks in Economics 18.1A: 207-262.

Wesseler, Justus, and David Zilberman. 2014 "The economic power of the Golden Rice opposition." Environment and Development Economics 19, no. 6: 724-742.

 

 

Attachments

Land Grant Participating States/Institutions

AL, CO, IA, IL, IN, MT, NE, NY, TX, WA

Non Land Grant Participating States/Institutions