Doctor of Philosophy / Department of Agricultural Economics / Ted Schroeder / This dissertation empirically examines how demand-enhancing activities conducted by food industry participants affect retail beef steak pricing, consumer demand for ground beef, and industry concentration. It follows the journal article style and includes three self-contained chapters. Chapter 1 uses a two step hedonic model with retail scanner data of consumer beef steak purchases to determine if there are incentives to identify certain attributes and to determine what types of attributes entertain price premiums and at what levels these premiums exists. Results indicate that most branded beef steak products garnered premiums along with organic claim, religious processing claim, and premium steak cuts. Factors influencing brand equity are new brands targeting emerging consumer trends, brands with regional prominence, and those positioned as special-labels, program/breed specific, and store brands. Chapter 2 reports tests of aggregation over elementary ground beef products and estimates composite demand elasticities. Results suggest consumers differentiate ground beef according to lean percentage (70-77%, 78-84%, 85-89%, 90-95%, and 96-100%) and brand type (local/regional, national, store, and unbranded). The range in composite elasticity estimates shows the value of analyzing demand elasticity based on differentiation and not simply considering ground beef as being homogeneous. Composite elasticity estimates provide improved understanding of how consumers make decisions concerning ground beef purchases. Chapter 3 examines industry concentration for the U.S. food manufacturing sector. This study is the first to examine whether particular subsectors within the food manufacturing industry, which operate in the presence of industry-funded check-off programs such as marketing orders, are more or less concentrated than industries without such research and marketing programs. Results provide evidence to support the hypothesis that industries with demand-enhancing check-off programs have lower concentration relative to industries without these programs.

Doctor of Philosophy / Department of Agricultural Economics / Glynn T. Tonsor / The U.S. beef industry is comprised of multiple, vertically connected segments. Beginning at the cow-calf level, cattle move through the industry to backgrounding/stocker operations, feedlots, and then to beef packers. The beef produced then continues to move through the marketing channel from beef packers to wholesalers and on to multiple final consumer outlets. Each level of the beef industry has both distinct and related economic issues. This dissertation contains three essays on beef cattle economics. Essay 1 focuses on price and animal health risk management at the feedlot level. Essays 2 and 3 explore how upstream demand changes impact primary beef suppliers. The objective of Essay 1 is to determine if feedlot operators manage price risk and animal health risk as two separate and independent risks or if they manage them jointly. The animal health attribute of interest is purchasing feeder steers from a single known source versus an auction with unknown background. The output price risk mitigation tools are futures contracts, forward contracts, other, and accept cash price at time of sale. Primary data is collected using an online survey administered to feedlot operators. Participants are placed in forward looking, decision making scenarios utilizing a split-sample block design. Evidence of a relationship between animal health risk and output price risk management is mixed. Ricardian rent theory (RRT) is tested in Essay 2 to determine if complete pass-through occurs from fed cattle and corn prices to feeder cattle prices. Monthly price data from December 1995 to December 2016 is used. Based on RRT, surplus rents should pass through the market to the holder of the scarcest resource. In cattle markets, feeder calves are the scarcest, widely traded resource and thus gains and losses at the feedlot theoretically pass-through to feeder cattle prices. The hypothesized pass-through rates suggested by RRT is calculated using monthly production data from the Focus on Feedlots data series. The regression pass-through estimates are tested against the hypothesized RRT pass-through. In many models, the estimated pass-through rate is statistically greater than the RRT hypothesized pass-through rate. Thus, when fed cattle or corn prices change, these changes are more than fully passed to cow-calf producers through the feeder cattle price. Evidence is found of asymmetric pass-through during times of herd expansion versus contraction. Essay 3 provides a quantification of how changes in retail and export beef demand are transmitted to different members of the beef industry. Understanding how information is transmitted from primary consumer demand through the supply chain is key for long-term prosperity of the U.S. cattle industry. However, empirical applications quantifying how demand signals are transmitted through vertically connected industries are limited. Using both naïve and forward looking price expectations, a four equation system of inverse demand and supply equations for live and feeder cattle is estimated. Using retail and export beef demand indices, the impacts of 1% change in retail or export demand on live cattle and feeder cattle prices are quantified.

<p>  </p> <p>Cattle derived food, like beef and dairy, have long been a staple of our human diets and continue to be prominent in our days. This prominence and their relevance naturally extend to our economies. According to the U.S. Department of Agriculture, Economic Research Service (2022), cattle production is the most important agricultural industry in the US representing about 17% of the $391 billion total cash receipts for agricultural commodities in 2021.</p> <p><br></p> <p>Economists have looked into cattle derived products from a wide array of perspectives focusing on the product itself, for example beef, but also in the forces of supply and demand that at times are external to product attributes. The effect of supply and demand shocks on agricultural markets have been heavily considered in the literature (Thomsen and McKenzie, 2001; McKenzie and Thomsen, 2001; Lusk and Schroeder, 2002, Piggott and Marsh, 2004). Yet another important aspect of agricultural markets is price determination and the body of literature in this area is ample (Tomek & Robinson, 2003). Recent phenomena in the world, like the availability of information, good or bad, in the most current, voluminous and accessible way that we have ever seen, could be a new force in price determination of agricultural products. My research contributes to such strains of literature by investigating perceptions and willingness to pay for beef attributes, market shocks in beef markets, and the role of online media in dairy prices.</p> <p><br></p> <p>Beef attributes, and their relative valuation by consumers, have been studied to assist in understanding consumer demand for beef. Given the relevance of such attributes in consumer’s mind, researchers have sought to study how to profitably provide those beef attributes demanded by consumers. Addressing consumer demands for tenderness, an important attribute (Schroeder and Mark, 2000), aging beef has been proved to be a technology that improves flavor, tenderness and juiciness (Kim, Kemp & Samuelson, 2016). By using aging processes, the same cattle carcass can generate more highly valued beef products. I study the willingness to pay for aging and USDA grade in beef, to understand valuation of attributes by consumers with various demographics. </p> <p><br></p> <p>In beef markets, the heterogeneity of beef cuts in their usage, pricing and distribution channels is crucial. Supply and demand shocks can affect individual cuts in different ways (Ortez et al, 2022). With some beef cuts relying heavily on restaurant sales more than others, this offers a good opportunity to introduce a new concept in beef market analysis, namely the price relationship amongst beef cuts and its response to different market shocks. The traditional discussion around spreads in meat focus on differences in price at separate steps in the supply chain, namely farm, wholesale and retail. However, little attention has been given to the relative differences in prices of specific cuts of beef.</p> <p><br></p> <p>The potential influence of online media chatter in its sentiment and volume has largely been under appreciated in the Agricultural Economics literature. A predecessor in this area is Tonsor and Olynk (2011) who first established a connection between news activity and economic fundamentals in agriculture. The advent of the internet may have the ability to decrease information asymmetry and bridge the information gap between consumers, producers and market products. Online media listening allows for data collection efficiently and in real time (Widmar, 2019) and it may be a relevant aspect in the decision making of agricultural and food industries. Moved by this endeavor, I seek to understand if potential relationships between online media chatter sentiment and volume with futures prices in dairy products exist.</p> <p>  </p>