Performing Department
Agricultural And Applied Economics
Non Technical Summary
The beef industry adds value to its product through health programs, nutrition programs, genetic choices, and addressing temperament of the cattle. Genetic testing of cattle is becoming increasingly important to maximize the economic performance of these value-adding production strategies (Beef Cattle, October 15, 2013: Available from: http://beefmagazine.com/cattle-genetics/genomics-coming-age-commercial-beef-herds?page=3). In turn, the effectiveness and value of commercial tests rests on advances in underlying beef cattle genetics and genomics research.Despite the recognition that genetic traits have economic value, and the priority on federal funding for functional genomics, there is little information currently available on the economic benefits and distribution of benefits among beef industry participants from these scientific investments. Benefits result when the scientific advances lead to new commercially available technologies and practices that are adopted by producers. The adopted technologies, if successful, result in higher productivity, and therefore lower costs per unit of output for producers, or possibly in higher product demand (if the advances are directed to product quality). These advances may be passed on to consumers in the form of lower meat prices, higher consumption levels, or, possibly, better meat quality. At the global level, the benefit may be enhanced food security for a world experiencing increasing demand for meat.The beef cattle industry is organized along multiple vertical segments, including: seed stock; cow-calf operations; feedlots; processors; retailers; and final consumers (Field, 2007). Each of these segments might assign different initial values or rankings to the various improvements that may result from beef genetics/genomics research. For example, cow-calf operators may put a high priority on research that results in tests to detect lower rates of fetal or calving losses and better reproductive performance, while feedlot operators may put a higher priority on tests for feedlot growth rates or feedlot disease reduction1. And, yet, the benefits of all types of improvements may ultimately make their way through the marketing chain and into product values at each stage.Beef cattle and calves are Wyoming's most important source of agricultural receipts, and cow-calf and some summer stocker operations are the dominant industry segments in the state (Wyoming Agricultural Statistics 2012). Wyoming therefore has a strong interest in understanding the benefits to cow-calf operations (vis-a-vis other industry segments) of alternative investments in beef cattle genetics/genomics research. It's also important for Wyoming to know how technologies adopted outside the state (e.g. at the feedlot level or in other cow-calf environments) affect Wyoming producers through the marketing channels, and how the benefits of technologies adopted on Wyoming ranches are transmitted through the livestock marketing chain to other market segments and other states. The competitiveness of Wyoming beef producers may depend in part on how successful they are in responding to demand for genetic traits sought by feedlot operators and processors.In summary, this research will provide insights into the linkages between genetics and genomics research and the development of commercially available genetic technologies that support beef production strategies. It will also advance knowledge about the potential benefits and distribution of benefits of the use of new genetic technologies within the beef cattle industry.1A growing concern among feedlot operators is brisket disease, which is being seen in feedlots at lower elevations than previously (Beef Magazine, available from: http://beefmagazine.com/health/0801-brisket-disease-cattle).
Animal Health Component
0%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Goals / Objectives
The overarching goal is to explore and better understand the benefits and distribution of benefits from public investments in beef genetics/genomics research. This effort involves the integration of information about scientific advances in genetics and genomics research, emerging genetic technologies, and the adoption and economic impacts of genetic technologies within the vertically segmented beef marketing system.The main objectives of this project are to:Garner an authoritative understanding of the investments in and diffusion of knowledge from beef genetics/genomics research.Match research investments and discoveries with categories of value-adding production strategies in the beef cattle industry, with a particular focus on strategies of most interest in Wyoming. [Aggregate value-adding strategies, which may be further refined as the research proceeds, include: Reproductive enhancements, fetal mortality, feeding efficiency and carcass weight, disease resistance, meat characteristics and quality improvements.]Develop a conceptual framework forexploring the benefits and distribution of benefits of genetic technologies within the vertically segmented beef cattle industry. Using Wyoming (and its closest beef market linkages, such as feedlots in Colorado and Nebraska) to explore producers' perceptions at different stages of the marketing chainand in different production environments(e.g. High Plains or Great Basin) of the value of different types of genetic information, and their use and anticipated use of genetic technologies to make economic decisions. Construct a Wyoming-centric illustrative model of the channels by which the benefits of genetic technologies adopted in the state or outside of the state potentially are shared between Wyoming and other beef industry participants. The Wyoming-based model can later be used to inform the specification of a full-blown beef sector model.Investigate and advance options for empirical modeling of returns to genetic technologies within the full U.S. beef cattle sector.Norwood and Lusk (2008) make the case that investments in beef genetics are less profitable than in poultry and pork, because beef markets are under much less vertical control than poultry and pork markets. They are under less vertical control because the biological cycle is longer, there are more stages of production, and larger geographic areas involved in the production stages.
Project Methods
Bibliometric analysis beef genomics science and technologiesThe initial phase will include a bibliometric analysis of the scientific literature related to beef genetics and genomics. This will help to identify the emergence of new genetic technologies with potential economic benefits, and to describe the structure of beef genomics science at a given point in time. We will examine the collected literature in terms of the research performers (authors, institutions, and geographic locations), funding agencies, functional traits of focus, R&D phase (e.g. basic or applied), and the emergence of new technology related to functional traits. Co-citation analysis and bibliographic coupling will be used to examine spatial characteristics of citations and the transference of knowledge from the basic research literature up to applications leading to new technologies.We will then collect spatial and temporal data on public R&D expenditures for beef genetics and genomics for a set of research institutions that represent the majority of the scientific literature as identified by the bibliometric analysis.1 The R&D expenditure database will be constructed using data from the Current Research Information System (CRIS), as well as by contacting the institutional research offices directly. We will then link the expenditures to the emergence of new technology as evidenced in the scientific literature. Ideally, we will be able to track specific new technologies related to beef genetics from the funding, to the emergence in the scientific literature, and ultimately adoption into the marketing chain, producing several case studies.Welfare analysis to conceptually explore the size and sharing of research benefits Economic surplus is the monetary gain obtained by consumers because they are able to purchase a product for a price that is below the highest price they would be willing to pay, and by producers because they are able to sell a product for a price that is higher than the least they would be willing to sell for. Graphically, consumer surplus is represented as the area under the demand curve and above the equilibrium market price, and producer surplus is represented as the area above the supply curve and below the equilibrium market price. A competitive equilibrium clears markets-- such that no additional trades would be beneficial to either buyers or sellers--and maximizes the sum of producer and consumer surplus. Technological change (e.g. the use of genetic tests) is generally represented in this framework as an outward shift in the supply curve. The elasticities2 of supply and demand determine the distribution of benefits of technological change between consumers and producers. Alston et al. (2009) show producer shares of research benefits are higher if the shift in supply is parallel or proportional (rather than pivotal), and if supply is less elastic and demand more elastic. Holloway (1989) extended this framework to develop the theory of how investments in research that reduces distribution service costs would be shared with farmers. Alston et al. (1998) developed and explored extensions to the basic welfare model to include technology adopters and non-adopters. For this research, this basic welfare framework used to explore technological change will be extended to include the several vertical market segments in the beef-cattle sector and the linkages between them. Norwood and Lusk (2008) present the basic multi-sector model in a graphical framework. They use the notion of derived demand to explain how demand for a final product (such as meat) leads to derived demand for the inputs into meat production (such as beef fattened in feedlots). Likewise, demand from processors for fed beef results in derived demand by the feedlot for cattle from cow-calf (or summer stocker) operations. The multi-sector model can be used to show how changes in one part of the marketing channel affect the entire channel. For example, technological change that reduces the marketing bill (the cost of transforming the product as it moves from one level of the marketing chain to the next) will be a focus of this research. So, for example, lower veterinary or pharmaceutical costs associated with selecting for greater disease resistance (or lower feed costs associated with greater feeding efficiency) will lower the marketing bill for feedlot operators and raise the derived demand for cattle from the cow-calf sector, making these cattle more valuable. At the same time, if it becomes less expensive to produce fed cattle, then meat prices to consumers can fall. Norwood and Lusk (2008) also show that the distribution of costs or benefits associated with changes in the marketing bill depend on the elasticities of supply and demand. They show that whoever has the least elastic supply or demand pays most of an increase in the marketing bill; likewise, they will gain most from a decrease in the marketing bill.3to develop a realistic conceptual framework, we will interview a number of producers at different stages of the beef marketing chain to verify our understanding of how buyers at one level of the marketing chain (e.g. feedlots) communicate their preferences for genetic traits to sellers (e.g. cow-calf operators), and seek out the animal product that best meets their preferences; and to also ensure we have a realistic understanding of how suppliers respond to demand for genetic information.Empirical modeling Equilibrium Displacement Models (EDM) are used to quantify the results of "shocks" to market equilibria in terms of changes in market prices and quantities, and values of producer and consumer surplus (Wohlgenant, 2011). A shock is any external event that produces a shift in supply or demand, such as the adoption of genetic technology. EDMs can include vertical market segments of the sort required for this research and also horizontal segments (for example, to represent different production environments within the cow-calf sector). Muth (1964) was the first to apply the EDM framework to vertically related markets. Economic benefits generated with an EDM model can be compared to research investment costs.One advantage of EDMs is that they allow researchers to use elasticity estimates from previous research (without estimating them from scratch using econometric models), or to conduct sensitivity analysis to determine the implications of using different elasticity estimates. They therefore allow the researcher to focus on the importance of the relative magnitudes of the elasticities, and also of the supply and demand shifts, to the outcomes and the sharing of outcomes between buyers and sellers in the marketing chain. The flip side of this advantage is the difficulty of finding and selecting the model parameters. For this reason, a significant amount of time during year three will be required find, evaluate, and select model parameters. In addition, we believe that the producer interviews can be extremely helpful in targeting the most critical model parameters, as well as formulating estimates for supply, demand, and derived demand shifts. As is always recommended in economic modeling, we will perform sensitivity analysis to determine the importance to the results of various modeling assumptions.1We hypothesize that this research will be highly concentrated at a relatively small number of institutions.2Elasticities describe the percentage change in quantities supplied or consumed in response to a percentage change in the price of the product.3Imperfect competition within the chain would likely alter the distribution of these benefits, and will need to be considered in the conceptual analysis. Dr. Bastian has appropriate expertise in livestock market structure.