Background The livelihood of cattle producers, such as cow-calf operators and  feeders, depends fundamentally on the price they receive for their cattle  and the cost to produce these cattle. Numerous supply and demand  factors can affect this. For example, the long production cycle for cattle  means that producers must make decisions about herd size long before  they can price and sell their cattle. Producers’ profits also hinge on how  weather affects the supply and cost of forage and feed grains.  Additionally, the outcome for producers depends on the effect of  consumer preferences on demand for and price of beef. International  trade in cattle and beef and competition from other protein sources—such  as poultry and pork—are also among the many supply and demand  factors that influence cattle prices and producers’ incomes. Cattle Production Cycle  and Recent Price Trends  for Fed Cattle The cattle production cycle, which runs from birth to slaughter, for most  cattle generally ranges from 15 months to 24 months. Calves are usually  weaned from cows when they weigh about 500 pounds. They may then  move to stocker or growing operations until they weigh 600 to 800  pounds. At this point, they move to feedlots, which produce fed cattle.  Specifically, feedlots specialize in feeding cattle a concentrated diet of  corn and other grains to enable them to reach between 950 and 1,300  pounds. They are then transported to and slaughtered at a packing plant.  Feedlots and packing plants are located throughout the United States but  are concentrated in states such as Texas, Oklahoma, Kansas, Nebraska,  Colorado, South Dakota, and Iowa. Figure 1 traces the movement of  cattle from breeding to processing and consumption. Figure 2 shows the  locations of cattle in feedlots. According to price data from AMS’s price reporting group, inflation- adjusted fed cattle prices have generally been increasing since about  2010. Fed cattle prices rose from about $125 per hundred pounds (live  weight) in July 2013 and began to increase rapidly in fall 2013. Prices  reached a historical high of about $173 per hundred pounds in November  2014, began to drop at the beginning of 2015, and then decreased  dramatically in August and September of 2015, decreasing to about $123  per hundred pounds by the end of that year—an overall drop of about 30  percent from November 2014. In 2016, after briefly increasing, prices  dropped further throughout much of the year to about $100 per hundred  pounds—an overall drop of about 40 percent from November 2014.  Prices then rose in the first half of 2017 before dropping again midyear.  See figure 3 for more detailed information on fed cattle price changes  over the past 10 years, including a trend line. Function of the Futures  Market for Fed Cattle Market participants use the futures market for fed cattle to manage the  risk associated with price changes, determine prices, or speculate on  price changes. Futures contract terms that reflect the underlying fed cattle  market help ensure that prices in both the fed cattle and futures markets  are closely linked because they are influenced over the long run by the  same market forces. The two markets also show similar patterns because  participants in both markets tend to rely on the same types of information  when entering into transactions. The Chicago Mercantile Exchange  establishes the terms of futures contracts, including the quantity, quality,  and locations to which fed cattle bought and sold on the futures market  may be delivered. The only aspect left unspecified is the price at which  each individual contract will be bought or sold. The futures market provides cattle market participants with a means to  hedge—shift unwanted price risk to others more willing to assume the  risk. Some buyers and sellers in the fed cattle market, such as packers  and feeders, trade in futures contracts to hedge the risks of price changes  in the fed cattle or wholesale and retail beef markets. For example, a  feeder concerned that fed cattle prices may decline in the future may  decide to lock in his or her sell price by selling futures contracts: if fed  cattle prices decline, profits from the futures contracts will generally offset  losses from the lower fed cattle prices. The same is true for a meat  packer concerned about prices going up. The packer might buy a futures  contract to lock in a purchase price, with futures profits offsetting higher  fed cattle prices. Other futures market participants—generally,  speculators—may take a view about whether the price of fed cattle may  go up or down and, based on that view, enter into the market as a buyer  or seller. For example, speculators could purchase futures contracts from  cattle market participants if they think that futures prices may increase in  the future or, conversely, sell a futures contract if they believe prices may  decline. These speculators provide the market with additional liquidity so  that cattle market participants have willing buyers and sellers with whom  to conduct transactions. Cattle Market Oversight  Roles and Responsibilities  of USDA and CFTC Within USDA, AMS’s P&SP and price reporting group play specific roles  in the cattle market. For example, P&SP performs various functions to  help USDA execute its oversight responsibilities for cattle markets, which  include halting unfair and anticompetitive marketing practices. To help  USDA execute these oversight responsibilities, P&SP collects the  following types of information to conduct both routine monitoring and  targeted investigations: Packers’ annual reports. Under the Packers & Stockyards Act, each  packer must submit an annual summary of operations to P&SP that  includes information on the dollar volume of cattle purchased, number  of head purchased, and some proprietary financial information. P&SP  officials use this information to, among other things, review the  financial status of packers and their ability to stay solvent to pay for  their purchases. Transaction data from the four largest packers. P&SP officials told  us that they send letters annually to the industry’s four largest packers  requesting data on their transactions with feeders. According to P&SP  officials, the packers provide P&SP with information on every  transaction made during that year. P&SP officials told us that they  also ask for new marketing agreements the packers have entered into  throughout the year, to allow officials to track marketing agreements  over time. Investigation information. During investigations, P&SP officials  collect evidence such as business records and witness testimony from  packers and others. P&SP can conduct investigations based on its  own initiative or based on complaints from market participants. If, in the course of its oversight work, P&SP determines that a competition  violation may have occurred, P&SP officials refer the case to USDA’s  Office of the General Counsel, which may pursue the case or further refer  the case to the U.S. Department of Justice. The price reporting group’s role in the cattle market is to implement the  Livestock Mandatory Reporting program as required by the Livestock  Mandatory Reporting Act of 1999. According to AMS, the purpose of the  group is, among other things, to provide information regarding the  marketing of livestock and encourage competition in the marketplace for  livestock and livestock products. To fulfill this role, the price reporting  group collects information on packers’ daily livestock purchases on both  mandatory and voluntary bases. Mandatory. Under the Livestock Mandatory Reporting Act of 1999, all  qualifying packers must report information on all their purchases and  sales on a daily basis. The price reporting group receives daily price  data on all fed cattle that a packing plant purchases, and all the beef it  sells. According to price reporting group officials, they aggregate and  summarize the information by sector and publish it within an hour of  receipt. For example, the price reporting group publishes information  on the number of cattle transacted, proportion of each of the four  transaction types used, and the average weight and price of cattle  transacted. The price reporting group does not report information on  individual transactions or summarized information if there is a risk that  the packer may lose confidentiality due to low reporting numbers. Voluntary. The price reporting group collects additional voluntary  information from packers, such as data on feeder cattle transactions  and on new or unique markets (e.g., the market for grass-fed cattle). CFTC, an independent agency of the federal government, has exclusive  jurisdiction over futures and other derivatives markets, except otherwise  provided in law. Consistent with the Commodity Exchange Act,  CFTC’s mission is to protect market users and the public from fraud,  manipulation, abusive practices, and systemic risk related to derivatives,  and to foster open, competitive, and financially sound futures markets.  This mission is achieved through a regulatory scheme that is based on  federal oversight of industry self-regulation through organizations such as  the Chicago Mercantile Exchange. As a self-regulatory organization, the  Chicago Mercantile Exchange is responsible for, among other things,  establishing and enforcing rules governing the conduct and trading of its  members and preventing market manipulation. A Variety of Supply  and Demand Factors  Affected Fed Cattle  Price Changes from  2013 through 2016 Our review identified several supply and demand factors—such as a  prolonged drought that affected the price of cattle feed and the availability  of relatively less expensive protein substitutes such as pork—that  affected changes in fed cattle prices from 2013 through 2016.  Furthermore, we found that varying competition levels among packers did  not appear to explain the large national price changes but may have  contributed to variations in fed cattle prices in different areas of the  country. Several Supply and  Demand Factors Including  Drought and the Retail  Price of Substitute  Proteins Affected Fed  Cattle Price Changes Based on interviews with some experts, stakeholders, officials from  USDA and CFTC, and our analysis of cattle market data, several  interrelated supply and demand factors affected the large national  changes in fed cattle prices from 2013 through 2016. These factors  included drought, costs for feed, and the price of substitute proteins, such  as pork. As it relates to supply factors, from 2010 through early 2013 a  prolonged drought—beginning in the southern United States in late 2010  and expanding to the High Plains in 2012—affected major cattle areas.  This drought caused the supply of young cattle to decrease and then  increase and, correspondingly, the national price of fed cattle to increase  and then decrease when those cattle came to market as fed cattle. Some  experts and stakeholders we interviewed told us that cow-calf operators  may have liquidated their herds in 2012 and 2013 because the droughts  reduced the supply of forage available to raise younger cattle, and cow- calf operators could not feed as many cattle on available pasture and  rangeland. The domestic cattle inventory decreased from about 96.5  million in 2007 to about 88.5 million in 2014. This decrease in inventory  reduced the supply of fed cattle available for sale in 2013 and 2014,  which could have driven up prices for fed cattle. As the drought eased in  late 2013, it became more feasible to feed herds on forage, creating  incentives for cow-calf operators to expand their herds throughout 2014  and 2015. This increased the number of fed cattle sold for slaughter by  late 2015, and prices began to drop at that time. See figure 4 for  information on the relationship between fed cattle price changes and the  U.S. cattle inventory over the past 10 years. See appendix II for more  information on the number of U.S. cattle at various points in the supply  chain. Costs for feed also affected the fed cattle supply, contributing to the large  changes in fed cattle prices from 2013 through 2016. An easing of the  widespread drought in late 2013 reduced the price of corn and other  grains used to feed cattle, which, according to some experts and P&SP  officials, may have created an incentive for feeders to grow their cattle to  heavier weights before marketing them to packers. For example, the price  of corn decreased from about $6.87 per bushel in late 2012 to about  $3.50 per bushel in late 2014. According to data from USDA’s price  reporting group, fed cattle weight increases from 2003 through 2013  averaged about 14 pounds per year; however, our analysis of cattle  market data from USDA showed average fed cattle weights increased by  about 40 pounds in 2015. For additional longer-term information on  increases in cattle weights, see appendix II. However, particularly heavy  cattle can receive lower prices per pound, in part because packers told us  that unusually large cuts of beef can be more difficult to sell. In 2014  when the fed cattle supply was low, P&SP officials reported that packers  were not necessarily paying lower prices for over-heavy cattle, so feeders  would not have received this price indicator to keep the cattle they sold  below certain weights. According to some experts, these heavier weights,  combined with the larger overall number of cattle offered for sale in 2015,  resulted in increased supply, exacerbating the price decline. Reduced demand for wholesale beef and for fed cattle also affected the  large national changes in fed cattle prices. Our analysis of cattle market  and other economic data showed that several factors reduced demand for  beef; this in turn reduced demand for fed cattle. These factors included  (1) higher wholesale beef prices and concurrently lower relative prices of  pork and chicken, which are substitutes for beef for consumers and which  would reduce demand for retail beef; (2) increases in the amount of beef  in cold storage, also limiting packer demand for fed cattle; and (3)  fluctuations in the strength of the U.S. dollar, which would shift consumer  purchases toward or away from relatively less expensive imported beef,  as well as contribute to shifts in net exports—that is, total exports minus  total imports. In addition, according to some experts and stakeholders, an  overall reduction in packing capacity when packers closed several plants,  including one large plant in Texas, may have also limited packer demand  for fed cattle. P&SP officials conducted an investigation into the price drop beginning in  August 2015. P&SP officials told us that as they saw fed cattle prices  rapidly decreasing in August and September 2015, they included this  investigation in the agency’s annual work plan for 2016. They also told us  that P&SP conducted the work based on its own initiative and not as the  result of a request from a market participant or because it received  specific information on possible wrongdoing. The P&SP investigation  reviewed changes in price spreads between fed cattle and wholesale—or  boxed—beef because such price spreads can serve as a rough indicator  of packer profit. P&SP found that packers may have benefitted for a short  period as the prices they paid for fed cattle decreased more quickly than  the prices they received for boxed beef, but it also found that those price  differences quickly diminished to smaller levels than before the price  drop. The report concluded that the sharp price decrease in 2015 was  likely due to a number of market factors that affected both supply and  demand, such as an increased number of fed cattle sold for slaughter and  lower relative prices for pork and chicken. Competition Levels among  Packers Did Not Appear to  Affect National Price  Changes in the Fed Cattle  Market but May Have  Contributed to Price  Variations in Different  Areas of the Country Competition levels among packers varied in different areas of the country.  These variations did not appear to explain the large national changes in  fed cattle prices from 2013 through 2015 but may have contributed to  variations in fed cattle prices in different areas of the country. Specifically,  at the national level, packer competition levels were stable from 2013  through 2015. Using P&SP’s annual data on transactions between  packers and feeders during this time frame, we estimated the degree of  competition in any given area by calculating market concentration levels  among packers using a measure called the Herfindahl-Hirschman Index  (HHI). From a practical perspective, a lower HHI indicates generally that  there is more competition in a market. In particular, an HHI is lowest when  a market is occupied by a large number of firms of relatively equal size  and is highest when a market is controlled by a single firm (i.e., there is  no competition in that market). Some large packing plants closed from  2013 through 2015, but the average HHI level varied by only one  percentage point (from about 51 to about 52 percent), whereas the total  price decrease from November 2014 through December 2015 was about  30 percent. Because of this, it was unlikely that variations in competition  affected the large price decrease. However, variations in competition levels in different areas of the country  may have contributed to price differences we observed in those areas.  The data show that the average competition level was about 51 percent,  suggesting that, on average, a given feedlot had two packing plants to  which it could sell its fed cattle. Competition levels tended to be higher in  states such as Texas, Oklahoma, Kansas, Nebraska, Colorado, South  Dakota, and Iowa, where there are more cattle on feed as we showed in  figure 2, suggesting that feeders in those areas had more packing plants  to choose from. Competition levels tended to be lower in areas that had  fewer cattle on feed, such as in the northeast and the Pacific Northwest, suggesting that feeders in those areas had fewer packing plants to which  they could sell their cattle. Using an econometric model, after controlling for other factors that could  affect price—such as the supply and demand factors we discuss above,  or attributes of the beef produced by fed cattle such as yield and quality  grade—we found that less packer competition in any given area was  associated with lower fed cattle prices in that area. Specifically, our  model estimated that fed cattle prices in less concentrated areas (those  with an HHI in the 25th percentile of our analysis) may have been about 9  percent higher than in more concentrated areas (those with an HHI in the  75th percentile of our analysis). Such competition effects can exist in  legitimately functioning markets. The results of our analysis suggest that  some packers may have been able to exercise market power in areas  with less competition. Evidence of this effect alone does not imply that  packers engaged in anticompetitive or improper behavior. For more  detailed information on our analysis, see appendix III. CFTC Did Not Find  Evidence of Trading  Irregularities in the  Futures Market for  Fed Cattle in 2015,  and Is Overseeing  Changes to Address  Contract Concerns CFTC’s regular monitoring efforts and its analysis of trading patterns,  including of particularly volatile trading days, did not find evidence of  irregularities in the futures market for fed cattle in 2015. However, CFTC  and others have expressed concern that certain terms in futures contracts  for fed cattle—such as the quality of beef represented in the contract—did  not sufficiently mirror the specifics of the fed cattle market, which could  make them less useful to cattle market participants for hedging risk. In  response, the Chicago Mercantile Exchange submitted changes to  contract terms to CFTC. CFTC reviewed those changes, and where the  agency found the changes consistent with the Commodity Exchange Act  and regulations, allowed or expressly approved those changes. CFTC’s Monitoring and  Analysis of Volatile  Trading Days Did Not Find  Evidence of Trading  Irregularities CFTC’s daily monitoring of the futures market for fed cattle did not find  evidence of trading irregularities. In addition, CFTC conducted a more in- depth review of volatile trading days in 2015 and did not identify evidence  of trading anomalies or that certain groups of traders, such as  speculators, unduly influenced the market. Our analysis of trading data  confirmed that the futures market for fed cattle experienced episodes of  higher volatility beginning in late 2015 and going through 2017 than it had  experienced in years immediately prior, and some market participants  expressed concern that this volatility could be due to possible trading  irregularities. Specifically, variations in futures market prices were  generally higher in late 2015 than in 2013 or 2014 and more frequently  reached the maximum allowed change in price for any given day, based  on rules set by the Chicago Mercantile Exchange. See figure 5 for  information on average futures prices for fed cattle and historical volatility  from 2008 through 2017. Some experts told us that high volatility in the futures market generally  can be the result of uncertainty or shocks in the futures or fed cattle  markets. For example, the futures market experienced high levels of  volatility in late 2003 through 2005 after bovine spongiform  encephalopathy (BSE) was first detected in a cow in the United States in  December 2003 (see appendix II for more information on BSE events  since 2003 and their impact on U.S. beef exports). More recently, the  market also experienced high levels of volatility during the financial crisis  that began in 2008 as well as in the latter part of 2015 as the price of fed  cattle rapidly decreased. However, some cow-calf operators and feeders,  including members of the National Cattleman’s Beef Association and the  Ranchers-Cattlemen Action Legal Fund United Stockgrowers of America  raised questions about whether the futures market volatility in 2015 might  be due to manipulation or to high-frequency trading, a specific type of  activity in which a speculator makes numerous trades at very high speeds  in an effort to profit from small changes in the market. Both CFTC and the Chicago Mercantile Exchange conduct daily  monitoring of the futures market for fed cattle, and CFTC officials told us  that they did not identify evidence of trading irregularities in 2015. In  addition, in response to concerns and a request from some cattle market  participants, CFTC analyzed trading patterns in the market, including  reviewing particularly volatile days in 2015. CFTC did not find evidence of  trading anomalies or that certain groups of traders, such as speculators,  unduly influenced the market. The Chicago Mercantile Exchange  conducted a similar review and came to similar conclusions. Both CFTC  and the Chicago Mercantile Exchange also concluded that high-frequency  trading did not contribute substantially to volatility on the days they  reviewed. Specifically, the Chicago Mercantile Exchange concluded that  the futures market volatility was predominantly the result of non-high  frequency traders placing and executing large, aggressive futures orders. Furthermore, as a way of comparing the use of automated and high- frequency trading in the futures market for fed cattle to related markets,  CFTC officials told us that their review found that futures contract markets  for other agricultural commodities from 2014 through 2016—including for  corn, wheat, soybeans, and pork—were characterized by a greater  percentage of automated trading, including high-frequency trading, than  the futures market for fed cattle. Finally, according to documentation from  the Chicago Mercantile Exchange, the high levels of volatility in the  futures market could be related to both the swift declines in fed cattle  prices and the fact that an increasing number of fed cattle are sold during  the last few business days of the week, rather than throughout the week.  Concentrating purchases to one or two days of the business week  decreases the number of price signals that the fed cattle market can  provide futures market participants. According to Chicago Mercantile  Exchange documentation, a decrease in the frequency of price signals  creates information gaps for market participants and likely contributes to  price volatility. CFTC and Some  Stakeholders Expressed  Concern about Cattle  Futures Contract Terms,  and CFTC Is Overseeing  Related Changes CFTC and some stakeholders expressed concern that the terms of cattle  futures contracts did not adequately reflect structural changes in the fed  cattle market and that differences between the terms of futures contracts  and the fed cattle market could cause futures contracts to become less  useful to cattle market participants to hedge risks. According to Chicago  Mercantile Exchange documents, futures contract terms are designed to  match relevant commodities markets and industry standards to help  ensure that there is a two-way relationship between the futures market  and the relevant commodity market. When contract terms reflect the  market and futures markets operate properly, prices in the fed cattle and  futures markets may initially diverge, but over time should generally  converge by the time a contract expires. If the prices do not converge,  contracts become less useful to market participants as a way to hedge  risks. For example, prior to October 2017, cattle futures contracts  specified that at least 55 percent of the fed cattle in those contracts were  to produce a beef quality grade of Choice or better. From fiscal years  2013 through 2017, the percentage of beef graded nationally as Choice  or better has been higher than this—at times as high as about 80 percent,  although proportions have varied by region. Stakeholders have expressed  concern that because the beef quality specifications in futures contracts  for fed cattle are lower than the beef quality produced by animals traded  in the fed cattle market, this difference may decrease the value of those  futures contracts. Additionally, stakeholders expressed concern that this  difference can negatively impact whether prices in the futures and fed  cattle markets effectively converge as expected. In response to these concerns, the Chicago Mercantile Exchange made  changes to the terms of futures contracts for fed cattle in 2016 and 2017,  which were reviewed and approved by CFTC. To better align futures  contracts with the fed cattle market, the Chicago Mercantile Exchange  has increased the quality percentage of Choice or better quality beef to  60 percent, starting with October 2017 futures contracts, and to 65  percent Choice or better quality beef, starting with October 2018 futures  contracts. In 2016, also in response to concerns raised by stakeholders, CFTC  asked the Chicago Mercantile Exchange to provide information on  additional measures under consideration by the exchange, such as  changing the terms in futures contracts for fed cattle and making them  more consistent with the fed cattle market. As a result of dialogue  between the two entities, the Chicago Mercantile Exchange revised its  delivery process and expanded the timeframe for making deliveries,  which has allowed it to add locations where cattle can be delivered to  satisfy a futures contract. According to CFTC, this change made  delivery more accessible and improved the connection between the fed  cattle and futures markets. The Chicago Mercantile Exchange submitted  these and similar changes to CFTC. CFTC reviewed those changes, and  where the agency found the changes consistent with the Commodity  Exchange Act and regulations, allowed or expressly approved those  changes. Chicago Mercantile Exchange representatives told us that these  changes will help futures contracts better reflect the fed cattle market.  CFTC officials said that they believe the changes have the potential to  strengthen the performance of the futures market for fed cattle as a risk  management and price discovery tool, but will continue to monitor the  effectiveness of the changes. P&SP Does Not  Analyze Some Key  Transaction Data Two factors affect P&SP’s routine monitoring to ensure against  discriminatory or anticompetitive practices in the fed cattle market. First,  USDA’s view of its legal authority does not allow P&SP routine access to  the data from AMS’s price reporting group on daily transactions between  packers and cattle feeders. Second, P&SP does not periodically analyze  the transaction data that it collects from packers to learn more about the  operation of the fed cattle market. P&SP Does Not Have  Routine Access to Daily  Transaction Data That the  Price Reporting Group  Collects P&SP carries out its oversight responsibilities through monitoring and  investigations. The price reporting group, housed within AMS with P&SP  (which moved to AMS in November 2017), collects extensive data on  transactions between packers and feeders via livestock mandatory price  reporting as required by law. The price reporting group does not  regularly share these data with P&SP, so the data are not available for  P&SP to use for regular monitoring activities to flag potential issues for  investigation. Currently, according to USDA officials, P&SP officials may  request and receive only specific portions of price reporting data based  on individual investigations it has already decided to conduct. For  example, P&SP was able to analyze price reporting data in the course of  its investigation into the price drop in 2015. Based on USDA’s reading of the Livestock Mandatory Reporting Act of  1999 provisions that prohibit the disclosure of facts or information  acquired through the mandatory reporting program, the price reporting  group has not routinely shared the data with P&SP. The act provides  some exceptions to the disclosure prohibition. For example, the act allows  the price reporting group to share data, as directed by the Secretary of  Agriculture, for enforcement purposes. USDA officials told us that they  do not believe this exception allows the price reporting group to provide  routine access to the data for monitoring activities. The officials told us  that while the statute does allow for sharing of price reporting data for  enforcement purposes, they interpret the term “enforcement purposes” to  be a specific ongoing investigation, not market oversight. USDA officials  note that the act does not discuss market oversight; rather, it was  established to help market participants make business decisions through  USDA’s collection and dissemination of price data. P&SP officials told us that regular access to price reporting data would  allow them to more routinely conduct analyses as part of their routine  market monitoring activities similar to those carried out in their  investigations as part of their routine market monitoring activities.  Specifically, the officials said that going forward, price reporting data  could be used to detect price outliers more quickly and help P&SP identify  potential anticompetitive behavior; for example, where buyers might  agree to take turns buying cattle at different times so as to avoid  competing with one another. Under federal internal control standards, an  agency’s management should internally communicate the necessary  quality information to achieve the entity’s objectives. Such information  is, for example, communicated down, across, up, and around reporting  lines to all levels of the entity. Because USDA eliminated the Grain Inspection, Packers & Stockyards  Administration and reorganized P&SP under AMS in November 2017, the  reorganization provides an opportunity for USDA to review the extent to  which price reporting data could be shared with P&SP under the act— now that both P&SP and the price reporting group are within the same  agency. However, USDA officials told us in November 2017 that it was  too early in the reorganization process to determine whether AMS  leadership would view routine sharing of these data any differently. By  reviewing the extent to which AMS’s price reporting group can share daily  transaction data with P&SP to strengthen the effectiveness of its  oversight, USDA has an opportunity to allow P&SP to more effectively  carry out its responsibilities to ensure against discriminatory or  anticompetitive practices in the fed cattle market. In reviewing its authority  to share these data, determining whether it is necessary or advisable to  request additional exceptions from the current information disclosure  restrictions from Congress would position USDA to strengthen its  oversight of that market. P&SP Does Not Conduct  Detailed Periodic Analyses  of Transaction Data  Collected from Packers P&SP does not periodically analyze the transaction data that it collects  from packers to learn more about the operation of the fed cattle market.  As part of its monitoring program, P&SP reviews publicly available,  summarized price data on a weekly basis but it does not routinely review  the data it collects on transactions between packers and feeders, a  potentially useful source of data from packers that would enable P&SP to  conduct more detailed monitoring. We conducted several in-depth analyses of P&SP’s transaction data, and  found that some of these analyses could provide useful information to  agency management when it makes oversight decisions. For example, as  discussed earlier in this report, one of our analyses found that different  areas of the country experienced differing levels of competition and that,  controlling for other possible sources of price variation, areas with less  packer competition were associated with lower fed cattle prices. Such  analyses may allow P&SP to better monitor changes in competition and  prices over time, which may help inform its decisions on where to direct  its investigative resources and better fulfill its mission to ensure against  discriminatory or anticompetitive practices in the fed cattle market. Other federal agencies conduct routine, in-depth analyses to efficiently  direct their investigative resources. For example, as we reported in March  2012, as required by statute, USDA routinely conducts in-depth analyses  of crop insurance data to detect potential program fraud, waste, and  abuse by farmers, insurance agents, and loss adjusters. The agency  then uses these analyses to direct its investigative resources. Federal  internal control standards specify that management should use quality  information to achieve the entity’s objectives including processing the  obtained data into quality information and then evaluating the processed  information. P&SP officials told us that they typically do not receive all of the previous  year’s transaction data from packers until the following May. As a result,  P&SP has previously considered the use of packer transaction data for  routine monitoring to be somewhat limited by the lack of timeliness.  However, these officials also told us that the analyses we suggested  could still provide useful information. By routinely conducting in-depth  analysis of the transaction data it collects, USDA could enhance its  monitoring of the fed cattle market. Such analysis could include but not be  limited to examining competition levels in different areas of the country. Conclusions The cattle industry is an important part of the nation’s agricultural sector  and contributes tens of billions of dollars to the U.S. economy. Amid  concerns about the drop in fed cattle prices beginning in late 2015 and  ongoing questions about anticompetitive behavior in the fed cattle market,  P&SP’s role in overseeing this market is paramount. While P&SP routinely conducts monitoring and investigations, the  program does not have routine access to daily price reporting data or  periodically analyze the transaction data that it currently collects from  packers. The Livestock Mandatory Reporting Act of 1999 allows AMS’s  price reporting group to share data with P&SP for enforcement purposes,  as directed by the Secretary of Agriculture, but USDA does not believe it  has the authority to do so, based on its interpretation of “enforcement  purposes” in the statute. Although both P&SP and the price reporting  group are within AMS because of a November 2017 departmental  reorganization, USDA officials told us that it was too early in the  reorganization process to determine whether AMS leadership would view  routine sharing of these data any differently. By reviewing the extent to  which AMS’s price reporting group can share daily transaction data with  P&SP to strengthen the effectiveness of its oversight, USDA has an  opportunity to allow P&SP to more effectively carry out its responsibilities  to ensure against discriminatory or anticompetitive practices in the fed  cattle market. In reviewing its authority to share these data, determining  whether it is necessary or advisable to request additional exceptions from  the current information disclosure restrictions from Congress would  position USDA to strengthen its oversight of that market. Furthermore, as  part of its monitoring, P&SP does not periodically analyze the transaction  data that it collects from packers to learn more about the operation of the  fed cattle market. In analyzing P&SP’s transaction data, we found that  while less competition among packers did not appear to result in lower  national cattle prices from 2013 through 2015 on a national level, it did  account for variations in prices in different parts of the country. By  routinely conducting in-depth analysis of the transaction data it collects,  USDA could enhance its monitoring of the fed cattle market. Such  analysis could include but not be limited to examining competition levels  in different areas of the country. Recommendations for  Executive Action We are making the following two recommendations to USDA:  The Secretary of Agriculture should review the extent to which, under the  Livestock Mandatory Reporting Act of 1999, the price reporting group can  share daily transaction data with P&SP to allow P&SP to strengthen the  effectiveness of its oversight. After reviewing that authority, if the  Secretary determines that the statute does not permit the price reporting  group to share data with P&SP for routine monitoring purposes, and that  routine sharing is advisable in light of the purposes behind the statutory  disclosure restrictions, the Secretary should submit to Congress a  proposal to allow such sharing. (Recommendation 1) The Secretary of Agriculture should direct the AMS administrator to  ensure that P&SP routinely conducts in-depth analysis of the transaction  data that it collects. Such analysis could include but not be limited to  examining competition levels in different areas of the country.  (Recommendation 2) Agency Comments  and Our Evaluation We provided a draft of this product to USDA and CFTC for comment. In  written comments, reproduced in appendix V, USDA agreed with our two  recommendations and described actions it has taken and will take to  implement them. CFTC only provided technical comments, which we  incorporated as appropriate. With respect to our first recommendation, USDA stated that it took action  and reviewed the authority provided by the Livestock Mandatory  Reporting Act of 1999 and determined that the act does not allow for data  sharing for routine monitoring purposes. Further, USDA stated that the  agency believes considering a statutory amendment to allow for routine  data sharing is not advisable, due to the agency’s concerns about  maintaining the public’s trust in USDA’s administration of the Livestock  Mandatory Reporting program. We believe the steps USDA has taken  address our recommendation. Concerning our second recommendation, USDA agreed that routine in- depth analysis of packer transaction data would enhance USDA’s  monitoring of the fed cattle market to ensure against discriminatory or  anticompetitive practices. USDA stated that it plans to create a new  competition branch in P&SP—now known as the Packers and Stockyards  Division—that will be staffed by employees with economic expertise.  USDA stated that this new branch will be responsible for reviewing the  transactions data P&SP receives from packers and conducting in-depth  analyses that would help the agency to monitor changes in competition  and prices over time to inform USDA decisions on where to direct its  resources. Routinely conducting such analyses would address our  recommendation. USDA also provided technical comments. We incorporated these  comments as appropriate. We are sending copies of this report to the appropriate congressional  committees, the Secretary of Agriculture, the Chairman of the Commodity  Futures Trading Commission, and other interested parties. In addition, the  report is available at no charge on the GAO website at  http://www.gao.gov. If you or your staff members have any questions regarding this report,  please contact Steve Morris at (202) 512-3841 or moriss@gao.gov or  Oliver Richard at (202) 512-2700 or richardo@gao.gov. Contact points for  our Offices of Congressional Relations and Public Affairs may be found  on the last page of this report. Key contributors to this report are listed in  appendix VI. Appendix I: Objectives, Scope, and  Methodology This report (1) describes key factors that affected fed cattle price changes  from 2013 through 2016; (2) describes what CFTC found about possible  trading irregularities in the futures market for fed cattle in 2015 and any  changes to the futures contract for fed cattle since 2015; and (3)  examines factors that may affect the U.S. Department of Agriculture’s  (USDA) routine monitoring to ensure against discriminatory or  anticompetitive practices in the fed cattle market. To describe the key factors that affected fed cattle price changes from  2013 through 2016 and to understand changes and trends in the U.S.  cattle market since 2000, we analyzed economic and other market data  collected by federal agencies. These data included information about  cattle and beef prices, quality, and inventories; cattle and beef  transactions; feed prices and feedlot sizes; transaction methods; national  drought patterns; and consumption trends for beef, pork, and chicken. We  gathered these data from USDA’s Agricultural Marketing Service (AMS),  Economic Research Service, National Agricultural Statistics Service, and  World Agricultural Outlook Board, among others. For example, we  reviewed AMS data on fed cattle prices from November 2002 through  August 2017, and we used it to, among other things, develop a long term  price trend line. We did not quantify or rank the impact of various factors.  We assessed the reliability of the data we analyzed by interviewing  officials who maintain the data, reviewing related documentation, and  testing the data for missing or erroneous values, and determined that the  data were sufficiently reliable for our purposes. When we found  discrepancies such as data entry errors, we brought them to the  agencies’ attention and worked with the agencies to correct the  discrepancies before conducting our analyses. We also collected USDA transaction data on beef packer (packer)  purchases of fed cattle from 2013 through 2015 and we analyzed these  data using a variety of methods, including econometric analysis. For  more on the methods and results of this analysis, see appendix III. We  assessed the reliability of the transactions data we analyzed by  interviewing officials who maintain the data, reviewing related  documentation, and testing the data for missing or erroneous values. We  determined that the data were sufficiently reliable for our purposes. In  addition to analyzing these data, we reviewed an investigation by AMS’s  Packers & Stockyards Program (P&SP) on the 2015 drop in fed cattle  prices. We did not obtain and review internal packer documents, so the  scope of our analysis did not include a review of whether packers  engaged in anticompetitive behavior. Such specific investigations would  typically be carried out by entities with subpoena authority such as the  Federal Trade Commission of the Antitrust Division in the Department of  Justice. To describe what CFTC found about possible trading irregularities in the  futures market for fed cattle in 2015 and any changes to the futures  contract for fed cattle since 2015, we reviewed and summarized relevant  statutes and regulations, such as the Commodity Exchange Act and  Commodity Futures Trading Commission (CFTC) regulations for futures  exchanges. We compared that information with CFTC documentation on  its oversight activities related to the futures market for fed cattle, such as  its 2013 review of the Chicago Mercantile Exchange and the Chicago  Board of Trade to verify the exchange’s ongoing compliance with  standards intended to, among other things, prevent market manipulation.  Such rule enforcement reviews include oversight into whether designated  contract markets comply with core principles as outlined by CFTC. We  also reviewed CFTC analyses of trading patterns on specific dates in  2015 after conducting a review of the analyses data and methods and  determining the work to be sufficiently reliable for our purposes. In  addition, we reviewed and summarized documentary evidence from the  Chicago Mercantile Exchange on its analysis of the market and on its  changes to terms in futures contracts for fed cattle. To better understand  the volatility in the market in 2015, we gathered and analyzed price data  from Bloomberg on the futures market for fed cattle. To examine factors that may affect USDA’s routine monitoring to ensure  against discriminatory or anticompetitive practices in the fed cattle  market, we gathered and reviewed relevant oversight documentation,  including P&SP annual reports and investigative policies and procedures.  In addition, we met with officials from AMS’s P&SP and Livestock  Mandatory Reporting program (price reporting group) to discuss their  roles and responsibilities. We also used the results of our analysis of  USDA transaction data on packer purchases of fed cattle. We compared  USDA actions with standards for internal control in the federal  government, specifically those related to the communication and use of  quality information. To address all our objectives, we conducted interviews with (1) cattle  market experts; (2) stakeholders selected to represent a variety of views  including small and large feedlot operators (feeders), packers, futures  market speculators, the Chicago Mercantile Exchange, and an  organization specializing in competition and antitrust issues; and (3)  agency officials from AMS’s P&SP and price reporting group, and USDA’s  Office of the General Counsel, as well as CFTC. We used the following  criteria to identify cattle market experts:  the expert’s recognition in the professional or academic community,  and  the relevance to cattle markets of his or her published work or  research to cattle markets. We identified these experts through our prior work, the recommendations  of USDA or CFTC officials, stakeholders, or other recognized experts. We  conducted semi-structured interviews with 34 individuals or groups of  experts, stakeholders, and officials, and performed a content analysis of  relevant responses to our questions. To characterize responses and  quantify interviewees’ views throughout this report, we defined modifiers  (e.g., “some”) as follows:  “some” users represents 2 to 5 users,  “several” users represents 6 to 9 users,  “many” users represents 10 to 15 users,  “most” users represents 16 to 24 users, and  “nearly all” users represents 25 to 29 users. The views of the experts and stakeholders we interviewed cannot be  generalized to all others with expertise in the cattle markets or all cattle  market stakeholders, but they provided valuable insights to our work.  Appendix IV presents a list of recognized experts that we interviewed. We conducted this performance audit from August 2016 to March 2018 in  accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain  sufficient, appropriate evidence to provide a reasonable basis for our  findings and conclusions based on our audit objectives. We believe that  the evidence obtained provides a reasonable basis for our findings and  conclusions based on our audit objectives. Appendix II: Supplemental Information on  Trends in the Fed Cattle Market This appendix provides supplemental information on trends in the fed  cattle market. The sections below provide information from analyses and  interviews we conducted as part of our review of the fed cattle market,  including on fed cattle transaction methods, drought, number of U.S.  cattle, feedlot consolidation and size, cattle weights, consumption trends,  product differentiation and branded beef, beef price spread, and factors  affecting beef exports. Fed Cattle Transaction  Methods Beef packers (packers) and cattle feedlot operators (feeders) generally  use one of four transaction methods to buy and sell fed cattle, and their  use of these methods has changed over time for various reasons. The  four transaction methods are: Cash (also referred to as spot or negotiated). A purchase price is  determined through buyer-seller interaction. The price is known at the  time of agreement, and delivery to the packing plant may take place  up to 30 days later. Negotiated grid. A base price is negotiated between buyer and seller  and is known at the time of agreement. Delivery to the packing plant is  usually expected within 14 days. Unlike a cash transaction, the final  net price is determined by applying a series of premiums and  discounts after slaughter based on carcass performance (usually  related to weight, beef yield grade, and beef quality). Forward contract. An agreement for the purchase of cattle, executed  in advance of slaughter, under which the base price is established by  reference to prices quoted on the Chicago Mercantile Exchange and  can be set any time prior to the transaction. Formula contract. An advance commitment of cattle—by any method  other than cash, negotiated grid, or forward contract—in advance of  slaughter. Formula contracts use a method of calculating price in  which the price often is not known until a later date. For example, a  feeder and a packer may enter into a formula contract several months  in advance of slaughter. According to U.S. Department of Agriculture’s  (USDA) Agricultural Marketing Service (AMS) officials and others we  interviewed, formula contracts often use the cash price from AMS’  Livestock Mandatory Reporting price summaries around the time of  slaughter as a base upon which the contract then applies additional  premiums and discounts. Since 2002, the share of fed cattle sold via cash transactions has  decreased and the share of cattle sold through formula and forward  contracts has increased proportionally. According to our analysis of AMS  data, approximately 50 percent of cattle were traded using cash  transactions in 2002, but the share fell as low as 22 percent of cattle  transactions in 2015. Conversely, the use of other types of transactions— formula and forward contracts and negotiated grid arrangements— increased from about 50 percent of cattle in 2002 to approximately 78  percent in 2015. However, the use of the cash transactions slightly  increased again from 2016 through 2017. Figure 6 shows the share of  fed cattle transactions by method from November 2002 through  September 2017. Several experts and stakeholders we interviewed told us that feeders and  packers have generally increased their use of formula contracts for a  variety of reasons, including improving the quality and consistency of beef  products while decreasing transaction costs. For example, one industry  stakeholder told us that formula contracts ensure a steady supply of  specific cattle breeds and eliminate the costs of sending personnel to bid  for these cattle using cash transactions. In addition, a report from AMS’s  Packers and Stockyards Program (P&SP) noted that formula contracts  help feeders to, among other things, reduce the price risks of raising and  selling fed cattle; these contracts also help packers ensure a steady  supply of cattle to help them satisfy delivery requirements they may have  in contracts with their wholesale or retail customers. However, some  experts and stakeholders told us that the movement away from cash  transactions has reduced the depth and liquidity of several regional  markets, which may make it more difficult for market participants to  accurately determine the market price of cattle (e.g., for a cash sale)  because there are fewer observed price points. Moreover, the effect of  this difficulty in determining market prices is not limited to cash  transactions because cash prices are often used to establish a base price  in formula contracts. This reduction of depth and liquidity may also make  the fed cattle market more susceptible to wider price fluctuations,  according to some experts we interviewed. Several experts and stakeholders told us that options such as an online  fed cattle exchange, established in May 2016, may help address this  issue by providing a transparent forum for feeders and packers to sell and  purchase fed cattle. However, the exchange is still in its early stages and,  as of September 2017, comprised a small fraction of total fed cattle  transactions. Drought Prolonged drought may cause cow-calf operators to liquidate their herds.  This is because drought can reduce the supply of forage used to raise  younger cattle, so that cow-calf operators cannot feed as many cattle on  available pasture and rangeland. From 2000 to 2010 the United States  saw periods of both extensive drought and extensive wetness on a broad  scale, according to the National Oceanic and Atmospheric Administration.  Following that, in early 2010, little of the country was experiencing  drought, according to the U.S. Drought Monitor; however, drought  conditions worsened throughout the second half of that year and  improved through the first half of 2011 before worsening in the second  half of 2011. This drought impacted some areas of the United States  particularly hard with nearly 12 percent of the country in an exceptional  drought by the third quarter of 2011. Although the winter months of  January 2012 through March 2012 were dry, extreme drought levels  improved through early 2012 before a widespread drought began in the  summer of 2012. By July 2012, more than 80 percent of the country was  at least abnormally dry and more than 60 percent of the country was  experiencing drought. From 2013 through early 2015, drought conditions generally improved.  Overall drought conditions continued to improve in 2015, except in the  spring and fall, which were somewhat drier. The second half of 2016 was  drier but after this, drought conditions improved, with a smaller  percentage of the country experiencing dryness in 2017 than had been  seen since 2000. Figure 7 shows the percent of the United States land  mass experiencing drought conditions from January 2000 through May  2017. Number of U.S. Cattle at  Various Points in the  Supply Chain The number of cattle at different points in the supply chain can provide  various levels of insight into fed cattle market supply. Specifically, the  beef cow inventory provides insight into what may happen in the fed cattle  market in a few years,  and the number of cattle on feed can give an  indication of what may happen in the fed cattle market in the next few  months. The number of cattle sold for slaughter (also called marketings)  is an indication of current supply levels in the fed cattle market. Beef Cow Inventory The beef cow inventory drives the size of the overall cattle inventory and  therefore the number of fed cattle coming to market. As such, the size of  the beef cow inventory provides a sense of how the fed cattle industry  may change over the following 2 years. Our analysis of inventory data  from USDA’s National Agricultural Statistics Service indicated that the  beef cow inventory declined from 2006 through 2014, at which point it  started to increase. In the most recent period of contraction the year-over- year period with the highest rate of contraction in the beef cow inventory  was from July 2011 to July 2012, during which the beef cow inventory  decreased by 3.0 percent—a rate of contraction not seen in a single year- over-year period since July 1988 to July 1989. The inventory then began  to expand in 2014, increasing rapidly by mid-2014, and continued to  expand through 2016. From January 2016 to January 2017, the beef cow  inventory expanded 3.5 percent, the highest rate of expansion in a single  year-over-year period since January 1993 to January 1994. Prior to the  late 1980s, higher rates of expansion and contraction were common, but  during the next 20 years, annual changes in the beef cow inventory were  more gradual, with rates of expansion staying below 0.5 percent. Figure 8  shows the beef cow inventory from 1920—the first year for which we have  data—through 2016, with an overall downward trend since the mid-1970s. Cattle are sent to feedlots and are fed for 3 to 10 months before being  sold for slaughter. Thus, the number of cattle on feed at a given point in  time provides insight into the number of cattle that will be available for  slaughter in the coming months. Unlike the beef cow inventory, which saw  larger rates of increase in the mid-2010s than seen in the prior 2  decades, the number of cattle on feed increased at a more modest rate  during the same time frame. The total number of cattle on feed decreased  throughout 2012 and 2013, then began increasing in 2014, and continued  to increase through 2015, before decreasing in 2016. Although it might be  expected that cattle on feed would increase steeply about 18 months after  the steep increases in the beef cow inventory, these sharper increases  may be delayed as cow-calf operators continue to increase their beef cow  herds, thus preventing these heifers from going into the pool of fed cattle. Sales for Slaughter Total sales for slaughter declined overall from the early 2000s through  2015. On an annual basis, sales for slaughter declined sharply from 2014  through 2015 before increasing sharply in 2016. Sales for slaughter fell  5.68 percent in 2014, the largest decline in the data available (starting in  1996), followed by a further decline of 3.87 percent in 2015 and a rise of  6.29 percent in 2016, the largest increase in the data we analyzed. The  monthly sales for slaughter data show that after the long decline starting  in 2014, year-over-year increases in sales for slaughter began in  November 2015 and continued through August 2017, the most recent  month for which data were available at the time of our review. Feedlot Consolidation and  Size Some experts told us that significant consolidation has occurred among  feedlots. Our analysis of USDA National Agricultural Statistics Service  data from the mid-1990s through 2016 suggests that the number of  individual larger feedlots (those with a capacity of 50,000 or more head of  cattle) increased by a small amount—in terms of both number and  percentage of total feedlots. During this time frame, the number of cattle  fed at large lots increased, and the number of cattle fed at feedlots of  other sizes decreased. For example, while there were 45 feedlots with a  capacity of more than 50,000 head of cattle in 1996, there were 73  feedlots of this size in 2016. Similarly, in 1996, large feedlots made up 2  percent of all feedlots with a capacity of more than 1,000 head of cattle;  this number rose to 3 percent in 2016. Furthermore, since the late  2000s, larger feedlots generally have been contributing an increasing  portion of fed cattle to overall slaughter numbers, with medium-sized  feedlots (those with a capacity of 16,000 to 49,000 head of cattle)  generally contributing fewer. Cattle Weights Average cattle weights have increased gradually and steadily from 2002  through September 2017, according to our analysis of average weights  reported to AMS and several industry stakeholders we interviewed.  Figure 9 shows average monthly and annual cattle weights in live weight  contracts from November 2002 through September 2017. In the figure,  seasonal fluctuations are visible, with weights generally declining in late  fall. Consumption of Beef and  Other Proteins According to our analysis of consumption data from USDA’s Economic  Research Service, there has been a broad societal shift in consumption  from beef to chicken in the United States since the mid-1970s. Increasing  consumption of proteins such as chicken may shift consumption away  from beef, which would put downward pressure on beef and cattle prices.  Per capita chicken consumption has increased steadily for the past 40  years, though the growth in consumption has slowed since 2006. Per  capita pork consumption has remained steady over the same period,  while per capita beef consumption has largely decreased. Figure 10  provides information on the long-term trends in per capita consumption of  beef, pork, and chicken in the U.S. from 1970 through 2016. Product Differentiation and  Branded Beef As consumer tastes and demands have changed since 2000, producers  have increased differentiation of their products. For example, producers  have increased grass-fed options since 2000, and organic beef became  available in 2002. In addition, producers have increased their offerings of  branded beef varieties (e.g., Certified Angus and Wagyu beef). As beef  products become increasingly differentiated and more branded varieties  become available, average prices of beef and fed cattle may be expected  to rise. Packers are unlikely to differentiate or brand a product if it is less  valuable than an unbranded commodity product, so they would likely only  create differentiation or branding for higher-value beef products, which  are sold at higher prices than commodity beef. Because of this, packers  will likely pay more for the fed cattle that produce these higher value  products. We analyzed information on branded beef from AMS and found  that branded beef sales increased from about 7 percent of total beef sales  in 2002 to about 17 percent of total beef sales in 2017. Some experts we  spoke with pointed out that the increase in formula and forward contracts  has gone hand-in-hand with the increase in product differentiation and  branding. They told us that, as retailers demand specific types or brands  of beef, the industry has relied more heavily on formula and forward  contracts to ensure a steady supply of those types and brands. Beef Price Spread In the fed cattle market, the fed cattle-retail price spread is the difference  between the price feeders receive for their cattle and the price consumers  pay for beef at the retail level. The vast majority of the price spread  comes from price spread between the wholesale and retail levels. In  short, the retail price is much higher than the wholesale price that retailers  pay packers for beef, which, in contrast, is not much higher than the price  packers pay feeders for fed cattle. The fed cattle-wholesale price spread remained fairly steady from 2000  through May 2016, typically remaining below $0.50 per pound of retail  weight equivalent. The price spread, at both the fed cattle-wholesale and  wholesale-retail levels, spiked in June 2016. The spike was small but  persistent, continuing through the end of 2016. To be more specific, the  fed cattle-wholesale spread was between $0.51 and $0.67 from June  through December, compared with a range of $0.36 to $0.52 from  January through May of 2016. The price spread dropped to lower levels in  early 2017, then spiked again from May through August 2017, the latest  date for which data were available at the time of our review. Similar to the fed cattle-retail and fed cattle-wholesale spreads, the fed  cattle share of the beef dollar is a measure of the percentage of the retail  price of beef made up by the price of fed cattle. The fed cattle share of  the beef dollar dropped from about 65 percent in the early 1970s to about  50 percent by the mid-1990s. From 2000 to the present, the farmers’  share of the beef dollar has remained relatively flat, rising to close to 60  percent in 2014 but regularly being as low as 40 percent. Several factors  can drive changes in the fed cattle share of the beef dollar. For example,  a report from USDA’s Economic Research Service found that much of the  decline in the proportion of the beef dollar paid to producers can be driven  by technology changes that help increase productivity; and, as producers  have become more productive, they have been willing and able to supply  more animals to packers at lower prices. Figure 11 shows the historical  price spread for beef from January 1970 through December 2016. Bovine Spongiform  Encephalopathy and Beef  Exports Some industry stakeholders told us that the bovine spongiform  encephalopathy (BSE) event—in which the disease was detected in a  cow in the United States in 2003—has had a lasting effect on beef  exports from the United States. Specifically, these industry stakeholders  told us that the 2003 event—and additional BSE events in 2005 and  2006—has continued to depress demand for beef by closing certain  foreign markets to U.S. beef. Based on our review of ERS export data,  the total tonnage of beef exports plummeted in January 2004 due to the  BSE outbreak in the United States and did not consistently return to  levels seen before the BSE outbreak until May 2010. Appendix III: Econometric Model to Estimate  the Impact of Market Power on Fed Cattle  Transaction Prices This appendix provides information on the econometric model we used to  estimate the impact of market power on transaction prices for fed cattle. It  describes our econometric model in detail, provides the results of our  analysis, and discusses some limitations. Econometric Model We developed an econometric model to analyze the effect of market  concentration on the cash price of fed cattle. Specifically, we analyzed  how the level of market concentration of beef packers (packers) affected  the cash price of fed cattle. The U.S. fed cattle market is characterized by  a large number of feedlot operators (feeders) that sell to a small number  of packers for slaughter at packing plants; approximately 83 to 85 percent  of the total amount of packing market is conducted by four major packing  companies. To analyze the packing market, we obtained transaction data  from the Agricultural Marketing Service’s Packers and Stockyards  Program (P&SP) within the U.S. Department of Agriculture (USDA). The  data we used for our analysis comprised transactions collected from  these four largest packers for about 127,000 cash transactions from 2013  through 2015. The data identified the packing plant involved in each transaction;  however, we generally could not identify the specific feedlot involved,  especially when comparing transactions across different packers. The  data were administrative data from each packer, and in some instances, a  packing plant may have used a unique set of identifying codes for the  feedlots with which it did business. Therefore, we could only consistently  identify different feedlots associated with a given packing plant. The same  feedlot may have done business with a different plant but we were unable  to identify this information consistently across plants. The data contained  963 different dates on which transactions occurred, 970 counties where  feedlots were located, and 23 packing plants that purchased fed cattle. To reduce distortion from dissimilar transactions and outliers, we  eliminated transactions that were not cash transactions as well as cash  transactions that met certain parameters. Specifically, we excluded  transactions with (1) fewer than 10 animals; (2) a per-pound carcass price  of less than 1 dollar or of 10 dollars or more; (3) an average weight per  animal that was less than 500 pounds or more than 2,000 pounds; (4) a  slaughter date that preceded the number of days from the purchase date  by more than 14 days; (5) more than 10 percent cows in the lot; and (6)  more than 10 percent ungraded cattle in the lot. Dependent Variable Our dependent variable in the model was the logarithm of the transaction  price per carcass-based pound (not including freight) between a packing  plant and a feedlot on a given purchase date. Explanatory Variables Our model included a variety of explanatory variables, including the  Herfindahl-Hirschman Index (HHI), beef quality and yield grades,  feedlots, live weights, and fixed effects for time and geographic location of  the feeder and packing plants. HHI. The key variable in the model was the HHI, a measure of packer  market concentration faced by feedlots in a given geographic area— analyzed in the model by county—on a given purchase date. The HHI  takes the same value for any transaction in a given county on a given  purchase date (it varies only at the county level and over time). Our  calculation used a 90-day moving average window (current day and  the 89 days prior) to calculate the HHI for each county on each date. Although our model included only cash transactions, we calculated  the HHI using all transactions; that is, we included formula contracts,  forward contracts, negotiated grid transactions, and cash  transactions. However, we excluded transactions involving packer- owned feedlots and feedlots not in the United States from our HHI  calculation. Econometric analysis that uses HHIs to explain prices  generally considers the possibility that the HHI variable is endogenous  and is possibly correlated with the error term and to address this  issue, we instrumented our HHI variable. Beef quality and yield grades. For each lot of cattle transacted, we  used as controls the percent of fed cattle in each transaction whose  beef graded as Choice or better. We also used as a control the  percent of fed cattle in each transaction whose beef yield was rated  grades 1 or 2. In addition, we included a measure of the percentages  of Holstein cattle, ungraded cattle, and cows in the lot. Large feedlots. We used an indicator (dummy) variable for large  feedlots—specifically feedlots that were in the 95th percentile of  feedlots for the packing plant with which the transaction occurred. We  used this variable to control for possible extra bargaining leverage that  large feedlots may have with packers. Live weight. We controlled for the average live weight of the cattle lot  by including categorical variables (dummies) for: less than 1,050  pounds and more than 1,500 pounds (the 1,050 pounds to 1,500  pounds category is the omitted comparison category). We selected  these category cut-off values because generally prices are reduced  for cattle lots with an average weight of less than 1,050 pounds or  more than 1,500 pounds. Fixed effects. We used a set of indicator variables to account for  fixed effects associated with packing plants, time, and individual  counties. Specifically, we used a set of packing plant indicator  variables to account for effects pertaining to individual packing plants,  such as a plant’s location. We also used a set of time indicator  variables—one for each purchase date in the data—to account for  prevailing market conditions on that particular day, such as whether  prices were generally low or high on that day. Last, we used a set of  county indicator variables to account for local or regional effects that  are time invariant, such as a county’s transportation availability or  proximity to inexpensive sources of feed. The Model Our model was written as:  𝑦𝑦𝑖𝑖,𝑡𝑡=𝑋𝑋𝑖𝑖,𝑡𝑡𝛽𝛽+𝜀𝜀𝑖𝑖,𝑡𝑡 ,𝑖𝑖=1,…,𝑁𝑁𝑡𝑡; 𝑡𝑡=1,…,𝑇𝑇. 𝑦𝑦𝑖𝑖,𝑡𝑡 was the dependent variable in our model; namely, the logarithm of 𝑋𝑋𝑖𝑖,𝑡𝑡 was the list of control variables used in the model including the the transaction price per pound.  sets of fixed effects for plants, counties and purchase dates. β was the list of parameters associated with the control variables  Each observation in the model was a single transaction between a  packing plant and a feedlot. The subscript i represented a transaction  between a feedlot and a packing plant, and the subscript t represented  (𝑋𝑋𝑖𝑖,𝑡𝑡).  𝜀𝜀𝑖𝑖,𝑡𝑡. was an error term.  the purchase date of that transaction. The term 𝑁𝑁𝑡𝑡 expressed the fact that  the number of transactions may have varied across purchase dates. Results Our results suggest that when there is a more concentrated market of  buyers (packers), those packers will have more negotiating and market  power, and therefore, with other factors held constant, these packers will  be able to purchase fed cattle at lower prices from feeders. We found a  significant negative parameter estimate for our HHI explanatory variable.  This estimate suggests that for each 0.01 increase in the HHI—meaning,  a greater degree of packer concentration—there is about a 0.86 percent  reduction in the price of cattle. The interquartile range for the HHI is from  approximately 0.45 to 0.55, which implies an approximate price effect of 9  percent across that range. For a carcass price of about $2.22 per  pound—the average for 2013 through 2015, based on the data from P&SP—that translates to a difference of about 20 cents per pound  variation across this HHI range. The variables used in the model to control for effects other than HHI had  the expected directional effect on price or else were not significant.  Parameter estimates for the indicator variables for beef quality and yield  were both significant and positive, suggesting that fed cattle with higher  beef quality grade and yield levels have a higher price. The indicator  variables for the lots with weights of less than 1,050 pounds average  weight suggest that lots with very low weight received lower prices.  However, the variable for lots with more than 1,500 pounds was not  significant. The feedlot size variable was not statistically significant. Our  controls for the percent of Holsteins and ungraded cattle in the lot were  both negative and statistically significant, as expected. The percent of  cows in the lot was not statistically significant. Finally, our measure of  feedlot size was positive and statistically significant, suggesting that  larger feedlots may be able to obtain higher prices from packers. Our results suggest that instrumenting the HHI variable was appropriate.  We used a measure of the proportion of total fed cattle traded by the  packer using non-cash transaction methods as an instrument. Our  results satisfied the essential specification tests for appropriate use of  instruments: The endogeneity tests rejected the null hypothesis that the  endogenous variable (HHI) can be treated as exogenous. Thus it is  appropriate to instrument the HHI variable. Our results rejected the null hypothesis of weak instruments— Sanderson-Windmeijer, Stock-Wright and Anderson-Rubin. The F- Statistic from the first stage of the regression (20.36) is highly  significant and exceeded the critical Stock-Yogo value for the 10  percent maximal instrumental variable size (16.38). Thus the  instruments had sufficient explanatory power in the first-stage  regression equation. See Table 1 for a more detailed description of our results. Limitations Our analysis had a number of limitations as listed below. Only transactions for the market’s four major packers were  included in the data from P&SP. As a result, our HHI variable is a  “large firm HHI.” Whereas these four firms account for approximately  83 to 85 percent of total cattle sold, the remaining 15 to 17 percent of  fed cattle sold in the United States was not included in the data from  P&SP. In addition, we did not use some of the four large packers’  plant-level data because the data was missing key variables, such as  the purchase date. Therefore, our estimates of HHI in any location are  likely to be overestimates, and in general, our HHI estimates for any  location should be viewed only as relative to other locations in this  analysis and should not be compared with measures in other studies  or industries. The feedlot location may not be in the city listed for it. In some  cases, the feedlot city that is named in the data from P&SP as the  location of the feedlot is not the exact feedlot location. The feedlot  may be somewhat outside the city or at a headquarters location. Feedlot concentration differs across counties. The analysis  reflects the fact that, on average, in any given area, feedlots are far  more numerous and packing plants are relatively few in number.  However, this is not generalizable to all areas. Although there are a  relatively large number of feedlots in the United States in general, in  some cases, it is possible that a relatively small number of feedlots  account for a relatively large proportion of cattle sold to some packing  plants. Our data could only identify a feedlot that sold cattle to a  particular packing plant, so we could not identify which feedlots might  have sold fed cattle to multiple plants. We control for this in the  regression model in part by including an indicator variable for packing  plants’ transactions that were with a large feedlot (in the 95th  percentile for that particular packing plant). HHI calculations must use a geographic definition. In our analysis,  we include fixed effects for each packing plant as well as fixed effects  for each county, which controls for variations in market conditions in  different areas that are constant over time. The calculation of the HHI  takes into account transactions flowing from different counties to the  same packing plants and from a single county to different packing  plants, so the HHI calculations by necessity must use some  geographic definition. However, our HHI calculation does not depend  upon a county to define a market, but simply measures market  concentration conditions that the feedlots in that county face. The level of detail and scope in the data varied across the  different packing plants in our data set. For example, a detailed  breakdown of the type of cattle was not available on a consistent  basis across all packers and packing plants. Therefore, we were  unable to control for some variation in quality and type of cattle in our  model. However, this may be mitigated by our use of fixed effects if  certain transaction characteristics—for instance, the type or breed of  cattle sold—are fairly constant over time in a given county or plant. As in any model, there is the possibility of misspecification or  bias. We used various econometric tests for our instrumental  variables estimation (two-stage least-squares): endogeneity of the  HHI measure, J-statistic for identification, and weak instrument tests.  However, in any instrumental model there is a possibility that the  instruments are inappropriate or the estimators are biased, and that  bias may be exacerbated in the presence of outliers. Sargan  recommends a simple procedure for assessing the efficacy of two- stage least-squares versus ordinary least squares. Our results using  this criterion suggests our use of two-stage least squares is justified. Packing plants from the same company likely did not compete  with one another. Our HHI measure was calculated treating each  packing plant as a separate entity rather than at the packing company  level, despite the fact that multiple plants are owned by each of the  four major packing companies. Therefore, we assumed that packing  plants “compete” to some extent regardless of whether they are  owned by the same company. However, in the data we used for our  model, there were no plants owned by the same packing company in  the same city. There may be noise in the data. The data were administrative data  and may have random noise associated with issues such as different  administrative procedures of a plant, affecting when and how the data  are entered. We cleaned the data to remove observations that  appeared unreasonable or not easily explained, but some variation in  prices remains. Specifically, in the data that was used in our model,  the median intra-day price variation was about 18 percent for the 1st  to 99th percentile and about 11 percent for the 5th to the 95th  percentile. Appendix IV: Recognized Experts That We  Interviewed Appendix V: Comments from the U.S.  Department of Agriculture Appendix VI: GAO Contacts and Staff  Acknowledgments GAO Contacts Staff  Acknowledgments In addition to the contacts named above, Thomas Cook (Assistant  Director), Michael Kendix (Assistant Director), Kevin Bray, Candace  Carpenter, Tara Congdon, Jaci Evans, Dan Royer, Monica Savoy, Kiki  Theodoropoulos, Richard Tsuhara, and Jarrod West made key       contributions to this report. Related GAO Products U.S. Agriculture: Retail Food Prices Grew Faster Than the Prices  Farmers Received for Agricultural Commodities, but Economic Research  Has Not Established That Concentration Has Affected These Trends.  GAO-09-746R. Washington, D.C.: June 30, 2009. Livestock Market Reporting: USDA Has Taken Some Steps to Ensure  Quality, but Additional Efforts Are Needed. GAO-06-202. Washington,  D.C.: December 9, 2005. Economic Models of Cattle Prices: How USDA Can Act to Improve  Models to Explain Cattle Prices, GAO-02-246. Washington, D.C.: March  15, 2002. Packers and Stockyards Programs: Actions Needed to Improve  Investigations of Competitive Practices, GAO/RCED-00-242. Washington,  D.C.: September 21, 2000. Beef Industry: Packer Market Concentration and Cattle Prices,  GAO/RCED-91-28. Washington, D.C.: December 6, 1990.
The U.S. cattle industry accounted for about $64 billion in receipts in 2016, according to USDA. The price of fed cattle has fluctuated widely from 2013 through 2016 and experienced a sharp downturn beginning in late 2015, raising concerns about the market and questions about USDA's oversight. GAO was asked to review issues related to the U.S. cattle market. This report (1) describes key factors that affected changes in fed cattle prices from 2013 through 2016; (2) describes what CFTC found about possible trading irregularities in the futures market for fed cattle in 2015 and any changes to the futures contract for fed cattle since 2015; and (3) examines factors that may affect USDA's routine monitoring to ensure against discriminatory or anticompetitive practices in the fed cattle market. GAO reviewed economic data and USDA and CFTC documentation; analyzed transaction data on beef packer purchases from 2013 through 2015; and interviewed recognized experts, cattle industry stakeholders such as feedlot operators and packers, and agency officials. Supply and demand factors , such as a drought that affected the price of cattle feed, affected changes in prices of fed cattle—those ready for slaughter from 2013 through 2016. According to industry experts and GAO's analysis, a drought from late 2010 to early 2013 led the cattle inventory to fall and rise and, in turn, fed cattle prices to fluctuate (see figure). GAO's analysis of cattle market data from the U.S. Department of Agriculture (USDA) also indicated that competition levels among packers that slaughter and process fed cattle did not appear to affect the national price changes in the fed cattle market in 2015 but that areas of the country with less competition among packers had lower cattle prices. The Commodity Futures Trading Commission (CFTC)—an agency that regulates cattle futures markets where participants buy and sell standardized agreements for cattle at an agreed-upon price at a specified date in the future—did not find evidence of trading irregularities in the cattle futures market in 2015. However, to better align futures contracts with the actual fed cattle market, CFTC reviewed changes to contract terms and will continue to monitor those changes. The Packers & Stockyards Program (P&SP), which oversees the cattle industry within USDA's Agricultural Marketing Service (AMS), does not have routine access to daily data for transactions between feedlot operators, which produce fed cattle, and packers. Those data are collected by AMS's price reporting group, which does not routinely share them with P&SP because officials said it is prohibited by statute from doing so. The Livestock Mandatory Reporting Act of 1999 specifies that the Secretary of Agriculture may authorize the sharing of these data for enforcement purposes, which USDA interprets as an ongoing investigation, not market monitoring. In November 2017, USDA reorganized P&SP under AMS and officials said it was too early in the reorganization to determine whether AMS would view routine sharing of these data any differently. Reviewing the extent to which these data can be shared with P&SP provides an opportunity to enhance P&SP's oversight of the fed cattle market. Determining whether it is advisable to request additional exceptions from information disclosure restrictions from Congress would help USDA strengthen its oversight.