Development of Methodology for Calculating 

Estimated Net Price Information for Negotiated 

Barrows and Gilts 

Agreement No. 12-25-A-5729

May, 2014 

Prepared by Joe Parcell and Ted Schroeder 
Forward 

We acknowledge valuable contributions of external reviewers, Dr. Glynn Tonsor of Kansas State 

University and Dr. Lee Schulz of Iowa State University. We also extend our appreciation to 

Agricultural Marketing Service staff in the Des Moines office for providing background 

information and historical data. 

This project report represents the sole professional opinions of the researchers. Agricultural 

Marketing Service staff provided access to data and information upon request. Opinions 

presented in this report are solely those of the authors and do not reflect or represent views or 

opinions of any Agricultural Marketing Service, U.S. Department of Agriculture or pork industry 

representatives. 

 
About the Principal Investigators 

Joe Parcell, PhD, is a Professor in the Department of Agricultural Economics at the University 

of Missouri. He has been on faculty at the University of Missouri since 1998. He received his 

MS and PhD in agricultural economics and BA in mathematics. His research involves value 

chain demand drivers, price analysis, and marketing. He has extensive knowledge of supply and 

value chain issues through his research and practical experience with producer agricultural 

ventures. His many scholarly publications, proceedings, book chapters, and extension 

publications relate to marketing, pricing, strategy, and value added. He is co-author of the 

textbook titled The Agricultural Marketing System. He is founder of Value Ag., LLC. Value Ag, 

LLC, headquartered in Columbia, MO, is an economic consultancy group committed to 

“Analyzing Innovative Ideas for Tomorrow’s Agriculture.” 

 

Ted C. Schroeder, PhD, is a University Distinguished Professor of Agricultural Economics at 

Kansas State University. He has a B.S. from the University of Nebraska and Ph.D. from Iowa 

State University. He has been on the Agricultural Economics faculty at Kansas State University 

since 1986. He teaches and conducts research. He is director of the North American Institute for 

Beef Economic Research and the Center for Risk Management Education and Research. Ted has 

done extensive research in livestock market risk management, meat demand, meat and livestock 

marketing, and price discovery and has more than 100 published journal articles and numerous 

other publications. Schroeder has worked as a consultant on numerous meat and livestock valueadded projects, and he has been the principal investigator on a large number of external grants. 

 
Table of Contents 

Executive Summary ................................................................................................. 1 

Chapter 1: Introduction ........................................................................................... 3 

Chapter 2: Hog Production and Processing Background ........................................ 5 

 2.1 Processing Industry ....................................................................................... 10 

 2.2 Hog Procurement Trends ............................................................................. 14 

 2.3 Chapter 2 Summary ..................................................................................... 17 

Chapter 3: Swine Mandatory Price Reporting Data Trends .................................. 18 

 3.1 Negotiated Price Trends and Relative Price ................................................ 19 

 3.2 Negotiated Hogs Purchase Shares ............................................................... 24 

 3.3 Relative Price Variation Trends by Purchase Method ................................. 27 

 3.4 Comparison of Hog Quality by Purchase Method ....................................... 29 

 3.5 Chapter 3 Summary ..................................................................................... 34 

Chapter 4: Analysis of Mandatory Price Reporting Transactions Data ............... 35 

 4.1 Data and Data Procedures ............................................................................ 36 

 4.2 Predicting Net Price from Base Price .......................................................... 39 

 4.3 Predicting Net Price from Information Available when the Purchase Base 

Price is Established ....................................................................................... 46 

 4.4 Base Price Sensitivity to Market Buyer Participation ................................. 52 

 4.5 Regional Trends in Prices and Volumes ...................................................... 62 

 4.6 Chapter 4 Summary ..................................................................................... 66 

Chapter 5: Conclusions and Recommendations ................................................... 68 

 5.1 Recommendations ........................................................................................ 68 

Appendices ............................................................................................................. 71 

 
1 | Page

 

Executive Summary 

This study’s main objective was to assess the ability of the AMS to accurately compute (predict) 

net prices received for hogs at the time the negotiated base prices are reported. Several 

approaches were used to assess the ability of the USDA AMS to predict the base prices at the 

time the negotiated base prices are established. 

Overall, this study concludes that no sufficiently accurate method to predict net prices at the time 

base prices are negotiated can be created. This conclusion is based on thorough analysis of daily 

reported base prices and net prices from the past 10 years and detailed analysis of all individual 

transactions data on negotiated base and net prices from the past 30 months. The errors in 

translating base prices into expected net prices would be too large to make this computation and 

reporting of it have value for the hog industry. Going forward the AMS and hog industry should 

consider several actions: 

 This study does not recommend that the AMS report computed net prices, derived from 

negotiated base prices, at the time negotiated base prices are established. The errors in 

this projection would be too large to make this information have any added value to the 

hog industry. 

 

o The inability to predict net prices at the time base prices are established is not a 

problem associated with packer submission of information, AMS data collection, 

mandatory price reporting, or AMS reporting. Instead, it’s related to the nature of 

the hog market. Too much unpredictable variation in hog quality is present across 

transactions, and over time, to enable reliably computing net prices at the time the 

base prices are established. 

o Currently, MPR legislation does not require a unique transaction identifier to 

match purchase transactions with slaughter transactions. While adding a unique 

identifier to the MPR requirement is appealing, we are unsure if the industry value 

will outweigh the cost to the processors. 

 We suggest that AMS examine segmenting negotiated purchase data weighted average 

base price into thirds based on the number of animals represented by a particular 

report. The concept involves ordering transactions (or lots) from low price to high 

price. Divide the number of hogs into three equal portions. Each hog in each third has a 

price assigned to it. The weighted average price is then computed for each third. We 

recommend assessing how this new reported set of three weighted average prices would 

perform and what information it would add to current base price reporting. 
2 | Page

 

 We suggest that AMS consider tracking individual plant price effect for all (barrows and 

gilts, carcass and live, and sow) negotiated prices reported, i.e., AMS could follow a 

similar methodology used here to measures the change in price due to dropping a 

plant. AMS could develop a rule for switching plants from negotiated to other market 

arrangements, for when a plant is considered to have a non-market related impact on the 

weighted average price. Impacts of alternative rules should be explored if this approach 

were taken to assess impacts on reported prices.

 Thinning negotiated base prices are apparent and we believe it to be true that day-to-day 

price variability appears to at times not be fully reflective of changing market 

fundamentals, and those using these reported prices as bases in marketing agreements 

might want to explore other alternatives if recent trends continue. 

o We recommend that the industry participants using the national weighted 

average consider using a historical combined multi-day (say 20 day) share 

volume weighting to calculate the national average from the regional prices 

rather than using the most recent single day’s volumes in the two regions.. 

This will mitigate day-to-day price fluctuations in relative regional volumes 

that are due to non-market factors. 

o Individual producers may be more able to predict their net prices more effectively 

than the AMS can predict a net price for the entire market or than the AMS can 

predict even for individual transactions. Transactions are not distinguished by a 

unique seller identifier, so the AMS cannot correlate purchase transactions with 

slaughter transactions. Individual hog producers, however, do know this 

information for their own transactions. 

 Tremendous variation exists among net purchase prices in the hog industry. This suggests 

strong price incentives are present for producing hogs that meet packer preferences for 

carcass weight and quality. Producers could benefit from continued information that 

shows them how much value they forfeit when they market hogs that do not take 

advantage of, or that do not fit well into, a particular packer’s value matrix. 

 
3 | Page

 

Chapter 1: Introduction 

Producers arrange marketing contracts to ensure that they can access a marketing outlet, align 

market formulas to match the quality of animals that they produce, or provide financial stability 

by tying their operations to marketing contracts. Such marketing contracts typically entail 

establishing a base price to which quality performance premiums would be added or to which 

quality underperformance discounts would be subtracted. In the hog market, the most popular 

price used as a base in contracts is the prior day negotiated producer sold price. The contract base 

price may be a regional or national price. The USDA Agricultural Marketing Service (AMS) 

reports local and national negotiated hog prices under Mandatory Price Reporting (MPR) 

legislation.1 Producers marketing with contracts want assurance that the prior day producer sold 

negotiated base price is the best representative price for AMS to report. Hog producers are 

concerned that the prior day producer sold negotiated purchase price does not include hog 

quality-related premiums and discounts that are reflected in an AMS-reported net price, which is 

reported when the hogs are slaughtered. Prior to slaughter, i.e., when the base price is set, these 

quality attributes are unknown. Following the definition of negotiated in the mandatory price 

reporting legislation, hogs purchased through negotiated means represent hogs to be scheduled 

for slaughter anytime during the immediate 14 calendar days following the purchase transaction.2 

Each processor, and sometimes individual plants owned by a processor, may have an 

independent quality standard (buying program) when purchasing hogs. The day-to-day swings in 

the reported prior day negotiated purchase price could be evidence that different processors make 

purchases in the cash market at different times. Therefore, the perception is that adjusting the 

negotiated base price to a net price yields a more accurate reflection of changing market 

conditions over time. An adjusted base price, i.e., known base price adjusted for expected quality 

attributes of a lot, could be more meaningful than the currently reported base price because the 

adjusted base would encompass different processor base quality standards and premium and 

discount schedules. An adjusted base would reflect what producers are actually being paid for 

hogs net of quality premiums or discounts. 

For example, suppose one processor is known to tie its net price to an expected back fat level. 

However, most processors tie the net price to an expected percentage lean level. Because the 

premiums and discounts are significantly different between back fat level and percentage lean 

 

1 Livestock Mandatory Reporting 

Act: http://www.ams.usda.gov/AMSv1.0/ams.fetchTemplateData.do?template=TemplateN&navID=LS

MNMainRN2L2&rightNav1=LSMNMainRN2L2&topNav=&leftNav=MarketNewsAndTransportationD

ata&page=MPRinfo&resultType=&acct=lsmn

2 Scheduled for delivery is different from delivered by as many as 4 days. Thus, some hogs purchased in 

the negotiated trade may not be slaughtered until 18 days later. 
4 | Page

 

level, the base price offered between packers could differ significantly. These different pricing 

structures could significantly impact the AMS base price reported if the packer using back fat 

level represents a large proportion of negotiated purchases on an irregular basis. This would 

introduce base price variation that is not associated with changing market conditions but instead 

due to who is participating in the negotiated market. These concerns are particularly important 

because the hog negotiated cash market has dwindled to less than 5 percent of overall hogs being 

marketed. 

During the past decade, the number of barrows and gilts sold through the negotiated cash hog 

market has steadily declined. According to mandatory price reporting data, prior day negotiated 

national purchases may represent as little as 1.5 percent of overall barrow and gilt purchases 

during some days. Small numbers of transactions allow for the possibility of small differences in 

procurement programs, between hog processors, to influence the weighted average negotiated 

price reported on any particular day. This is potentially problematic as it suggests that the 

particular plant buying hogs on a particular day could change the market reported negotiated 

price in a way not otherwise supported by general market supply and demand fundamentals. 

Because of these concerns, the National Pork Producers Council established a resolution in 

March 2013: 

"The resolution requested NPPC to work with appropriate parties to assist USDA Market 

News in development of a process to calculate, then publish, an estimated net price for 

daily negotiated bids and consider a potential methodology for including hogs bought on 

a live basis in the negotiated net price for prior day and daily purchased swine reports. 

Pork producers watch current-day purchase reports for guidance about the level of hog 

prices on a particular day. Purchase data include only base prices for hogs, since the 

animals have yet to be harvested. Carcass measurements, however, determine premiums 

and discounts, and ultimately, the net prices received by packers. USDA has over 10 

years of data on mandatory price reporting, and could easily determine the relationship 

between net and base prices reported by packers." 

The purpose of this project was to respond to pork industry concerns, to assess whether the 

necessary data are available, and to determine whether a methodology can be applied to enable 

AMS to publish a meaningful computed net price at the time the negotiated price is reported (up 

to 14+ days prior to slaughter).3

 

3 Because for definition of negotiated trade hogs only need to be scheduled during the prior 14 calendar 

days, slaughter can take place beyond the 14 day window. 
5 | Page

 

Chapter 2: Hog Production and Processing Background 

The U.S. pork supply chain continues to evolve. Supply chain evolution presents challenges and 

opportunities. New paradigms are formed, and traditions are set aside. Integration and 

coordination of the pork supply chain continues as suppliers and processors strive to meet 

consumer demand consistent high quality pork products. Hog producers respond to market 

signals by adopting pork genetics, production systems, and marketing arrangements that 

maximize profits.4

 Likewise, hog processors adopt processing technologies, innovate into valueadded products, and develop buying programs that facilitate profitable operations. This chapter 

provides a broad overview of the evolving pork supply chain during the past 20 years. This 

information is important for addressing the objectives of this study because it provides 

information on the market environment in which the pork industry operates. 

Total hog production increased by 20 percent from the mid-1990s to 2013 (Exhibit 2.1). In 2013, 

federally inspected industry hog slaughter was 111 million head, of which 97 percent was 

barrows and gilts and the rest were cull sows, stags, and boars. While the number of federally 

inspected hogs slaughtered has been flat in recent years, federally inspected pounds of pork 

production continues to increase (Exhibit 2.2). The increase in pounds of pork production has 

been influenced by an increase in carcass weight over time (Exhibit 2.2). During the past 20 

years, the yield of carcass weight to live weight has increased from 73 percent to 75 percent of 

the live hog. 

 

 

4

 While profit maximization is a financial goal of a business, economists find other reasons why 

farmers use or choose not to use marketing arrangements and production contracts, for examples 

see the various works of Nigel Key. 
6 | Page

 

Exhibit 2.1. Barrow and Gilt, Sow, and Stag/Board Annual Slaughter, 1994 to 20135

Exhibit 2.2. Federally Inspected Pork Production and Carcass Weights, 1994 to 20136

 

5

USDA, ERS (Red Meat Yearbook Various Years) 

6

USDA, ERS (Red Meat Yearbook Various Years) 
7 | Page

 

Slaughter capacity has expanded along with hog production. Firm plant capacity information is 

confidential, which makes an actual historical account difficult. The trend in annual domestic 

slaughter capacity is approximated here as the annual maximum daily observed head slaughter 

between 1990 and 2013 (Exhibit 2.3). Similarly, the trend in daily domestic slaughter production 

capacity by year is approximated here as the annual maximum daily observed pork production 

between 1990 and 2013 (Exhibit 2.4). Approximated domestic daily hog slaughter capacity and 

domestic monthly pork production increased by more than 20 percent and more than 40 percent, 

respectively, from the mid-1990s to 2013. These trends mirror the increase in hog and pork 

production (see Exhibits 2.1 and 2.2). 

Pork processing plant managers maximize plant utilizationto reduce processing fixed costs per 

animal.7 Thus, firms have an incentive to schedule slaughter to minimize excess plant capacity. 

One advantage of firms entering into forward pricing agreements is that firms can better schedule 

slaughter. 

 

 

7

 For a discussion of how variances in slaughter utilization-to-capacity impact hog prices see: 

Parcell, J.L., J. Mintert, and R. Plain. “An Empirical Examination of Live Hog Demand.” Journal of 

Agricultural and Applied Economics, 36(2004)773-778. 
8 | Page

 

Exhibit 2.3. Approximated Daily U.S. Hog Slaughter Capacity (000 head), 1990 to 20138

 

 

8

USDA, ERS (Red Meat Yearbook Various Years)
9 | Page

 

Exhibit 2.4. Approximated Daily U.S. Pork Production Capacity (million lbs), 1990 to 

20139

Lastly, we note the growing importance of pork exports. Between 1984 and 2013 the percentage 

of US pork production exported has increased from 1% of production to 22% of production, 

while pork production has increased by around 60%. 

 

9

USDA, ERS (Red Meat Yearbook Various Years)
10 | Page

 

2.1 Processing Industry 

The daily slaughter capacity of barrow and gilt processors in 2013 is presented in Exhibit 2.1.1. 

Currently, all barrow and gilt processing plants that slaughter at least 100,000 head of swine per 

year on average for the immediate preceding five years are required to report hog purchase prices 

to the AMS under rules of the Livestock Mandatory Reporting Act of 1999. This would equate to 

hog processing plants slaughtering roughly 400 head per day.10 

The geographic dispersion of barrow and gilt slaughter plants is illustrated in Exhibit 2.1.2. 

Most of the plants subject to current hog price reporting, and certainly the largest volume of hogs 

represented, are located in the southeastern (e.g., NC, VA, and SC) and Midwestern (e.g., IA, IL, 

NE, MN, MO) regions of the United States. A few are also located in the West (e.g., CA). 

Geographic plant dispersion is important within hog price reporting. Spatial hog pricing 

differences are common due to regional pork pricing differences. For example, relative to 

Midwest prices, southeastern plants might pay a premium for hogs because of pork’s higher 

value in the region and the higher opportunity costs incurred when producing hogs in this region. 

 

 

10 These are only rough estimates of firms and plants because the researchers only have access to 

estimated slaughter capacity, not actual slaughter by year by plant. Actual slaughter by plant is 

confidential data not made available to the research team. 
11 | Page

 

Exhibit 2.1.1. U.S. Barrow and Gilt Processors and Daily Plant Slaughter Capacities, 

201311

Company Plant 

Capacity 

(head) Co. Total 

Smithfield (Smithfield, VA) Tar Heel , NC 34,000 

 Gwaltney, VA 10,400 

Morrell Sioux Falls, SD 20,500 

Farmland Crete, NE 10,400 

 Denison, IA 9,400 

 Monmouth, IL 11,400 

Prem. Std. Milan, MO 10,300 

 Clinton, NC 10,600 117,000

Tyson Foods (IBP) (Dakota Dunes, SD) Waterloo, IA 19,500 

 Logansport, IN 15,300 

 Storm Lake, IA 16,500 

 Col. Junction, IA 9,950 

 Madison, NE 7,925 

 Perry, IA 7,750 76,925

Swift (Greeley, CO) Worthington, MN 20,000 

Marshalltown, IA 20,000 

Louisville, KY 10,000 50,000

Cargill Pork (Wichita, KS) Beardstown, IL 19,400 

Wichita, KS Ottumwa, IA 18,400 37,800

Hormel (Austin, MN) Austin, MN 19,000 

 Fremont, NE 10,500 

Clougherty Los Angeles, CA 7,800 37,800

Seaboard Farms Guymon, OK 19,800 

Triumph Foods St. Joseph, MO 20,000 

Indiana Packing Co. Delphi, IN 17,000 

Hatfield Quality Meats Hatfield, PA 10,400 

J.H Routh Sandusky, OH 4,200 

Rantoul Foods Rantoul, IL 4,800 

Sioux-Preme Packing Sioux Center, IA 4,500 

Greenwood Packing Greenwood, SC 3,000 

Pork King Packing Marengo, IL 2,800 

Premium Iowa Pork Hospers, IA 2,000 

 

 

11 Meyer, S. 20014. Paragon Economics and National Pork Producers Council. Personal correspondence 

Winter 2014. 
12 | Page

 

Exhibit 2.1.1. (cont.) U.S. Barrow and Gilt Processors and Daily Plant Slaughter 

Capacities, 201312

 

12Meyer, S. 20014. Paragon Economics and National Pork Producers Council. Personal correspondence 

Winter 2014. 

Company Plant 

Capacity 

(head) Co. Total 

USA Pork Products Hazellton, PA 2,000 

Spectrum Meats Mount Morris, IL 1,600 

Yosemite Meats Modesto, CA 1,500 

Dakota Pork, Inc Estherville, IA 1,500 

Leidy's Souderton, PA 1,300 

Vin-Lee-Rom Mentone, IN 1,150 

Martin's Pork Products Falcon, NC 1,300 

Verschoor Meats Sioux City, IA 1,200 

Olson Meat Company Orland, CA 1,200 

The Pork Company Warsaw, NC 900 

Jim's Farm Meats Atwater, CA 850 

Independent Meats Twin Falls, ID 750 

Peoria Packing Chicago, IL 600 

Masami Meat Company Klammath Falls, OR 600 

Dekalb Packing Company De Kalb, IL 500 

Parks Family Meats Warsaw, NC 450 

Carleton Packing Company Carleton, OR 375 

Morris Meat Packing Morris, IL 300 

Dealaman Enterprises, Inc. Warren, NJ 200 

Weltin Meat Packing Minden City, MI 175 

Southern Quality Meats Pontotoc, MS 160 

Dayton Meat Co. Dayton, OR 100 

Kapowsin Meats, Inc. Graham, WA 100 
Exhibit 2.1.2. Geographic Locations of U.S. Barrow and Gilt Processing Plants, 20131313 Created through data obtained through Meyer, 2014. See footnote 10 or 11. 
14 | Page

2.2 Hog Procurement Trends 

As hog and pork production was expanding, a major shift occurred in how live hogs were 

sold by producers to hog processors (Exhibit 2.2.1). In 1994, it was estimated that 62 percent 

of hogs were sold through negotiated (live or carcass) cash markets. However, by 2013, 

negotiated (live or carcass) cash sales had declined to less than 4 percent of trade nationally. 

In 2013, live negotiated cash sales represented less than 1 percent of total hog marketings 

nationally.14 A further breakdown of hog sales methods are provided in Exhibit 2.2.2. Much 

of the reduced cash-negotiated hog sales has been a result of increased packer-owned hogs, 

which represented 28 percent of all hogs sold (or transferred inter-firm) in 2013. Formula 

pricing of hogs has been common for several years and has represented about 45 percent to 

50 percent of annual hog marketings. During the past 10 years, the percentage of packer-sold 

hogs has remained flat at around 5 percent. 

 

 

14In reaching contract production settlements with hog contract production farms in Iowa, the consent 

decree between the firm and Iowa Attorney General requires that should the firm sell hogs under 

production contract in Iowa to a processor which it is an owned affiliate, at least twenty-five percent 

of the hogs processed at that processor will be purchased from a firm other than the firm with the 

owned affiliation. The agreement is a for two year period. Such an agreement has been reached 

between the Iowa Attorney General and several hog contract production firms over the past decade. 

What impact this has on increasing the negotiated trade nationally, or regionally, is unknown. 

. 
15 | Page

Exhibit 2.2.1. Percentage of Hogs Purchased on Negotiated Cash Market, 1994 to 201315

 

15 Grimes, Glenn, and Ron Plain. "U.S. Hog Marketing Contract Study." Farm Marketing, University 

of Missouri-Columbia Dept. of Agricultural Economics. January 2009. 

http://agebb.missouri.edu/mkt/vertstud09.htm (22 October 2009). 

12 Plain, Ron. “U.S. Market Hog Sales, 2002-2012.” Farm Marketing, University of MissouriColumbia Dept. of Agricultural and Applied Economics. May 2013. 

http://agebb.missouri.edu/mkt/vertstud09.htm (5 January 2014).
Exhibit 2.2.2. Percentage of U.S. Hogs Sold using Various Pricing Arrangements, January 2004 to 201316

Pricing Arrangement 2004 2005 2006 2007 2008 2009 2010 2011 Mandatory Price Reporting Negotiated (carcass) 10.4 10.4 9.0 8.2 8.1 6.5 4.9 4.1  Market formula (carcass) 38.2 38.6 35.4 35.7 35.6 41.4 36.5 36.8  Other market formula (carcass) 8.6 8.4 8.4 8.1 9.4 6.5 10.1 9.4  Other purchase agreement (carcass) 17.0 15.5 14.8 13.8 12.6 11.2 12.4 14.6  Packer sold (carcass) 2.0 2.3 5.9 6.1 5.9 5.5 5.3 4.5  Packer owned (carcass) 18.1 19.4 20.7 22.3 23.1 24. 25.2 26.5  Negotiated (live) 1.6 1.5 1.7 1.9 1.5 0.9 1.3 1.3 Non-Mandatory Price Reporting 4.2 3.9 4.4 3.9 3.9 3.9 4.3 3.0 

Note: Percentages are based on denominator of total federal-inspected slaughter for the year listed. 16Plain, Ron. “U.S. Market Hog Sales, 2002-2012.” Farm Marketing, University of Missouri-Columbia Dept. of A

Economics. May 2013. http://agebb.missouri.edu/mkt/vertstud09.htm (5 January 2014). And, adapted from: USDA/AMS 

summary of LM_HG201 and LM_HG200 

17 The 2013 values are author calculations. It was necessary to extrapolate annual total mandatory price reporting slau

information during the government shutdown. The data extrapolation involved consistency between 2012 and 2013 for m

reported slaughter and federal inspected slaughter. 
17 | Page

 

2.3 Chapter 2 Summary 

 Hog production increased some 20 percent during the past 20 years.

 Pork production increased more than 40 percent during the past 20

years through both increased hog production and increased carcass

weights.

 Processors use forward marketing arrangements to improve hog

slaughter scheduling, which maximizes plant use and reduces fixed

costs per animal processed.

 Regionalization of hog slaughter can create spatial pricing differences

due to the regionalization of hog production costs and the value of

pork, which may influence reported market prices for hogs based on

the quantity of day‐to‐day purchases by a particular firm.

 Substantial declines in negotiated live and carcass pricing has

resulted in less than 5 percent of hogs currently being priced using

these methods.

 
18 | Page

 

Chapter 3: Swine Mandatory Price Reporting Data 

Trends 

Currently, AMS reports several daily and weekly prices and hog quality data. Chapter 4 details 

the transaction-level analysis of mandatory price reporting (MPR) data. The information reported 

in this chapter reflects available aggregated information reported as a result of MPR legislation 

to collect transaction data and generate publically available reports. Understanding what 

information is publically available is important for describing industry interest in pursuing price 

alternatives to the current prior day purchase negotiated weighted average prices. All data used 

to create exhibits in this chapter represent publically reported AMS data sourced through the 

Livestock Marketing Information Center (LMIC) data bank, http://www.lmic.info/. 

These data are used to portray long-term price and quality trends and aid in understanding 

industry concerns, challenges, and opportunities for assessing alternative price discovery 

methods. The USDA AMS reports several daily market reports. This study is especially focused 

on information reported in two particular reports, the LM_HG200, National Daily Direct Prior 

Day Hog Report Plant Delivered Purchase Data (referred to as the “prior day purchase report”) 

and the LM_HG201, National Daily Direct Hog Prior Day Report – Slaughtered Swine (referred 

to as the “prior day slaughter report”). 

The prior day purchase report (LM_HG200) summarizes packer hog purchase information from 

the previous business day. In addition to volumes of hogs purchased by type of purchase (i.e., 

negotiated, other market formula, swine or pork market formula, and other purchase agreement), 

weighted average carcass prices are also summarized for each of these purchase types as well as 

weighted average carcass and live basis prices for negotiated purchases (including packer sold). 

A hog purchase pricing matrix, representing individual plant carcass merit buying programs, is 

also provided in the report. For this study, the research team analyzed the weighted average 

negotiated purchase prices for live hogs purchased on a live basis and live hogs purchased on a 

carcass basis. These two series represent the negotiated purchases of hogs each day by packers, 

and these are the prices commonly used as base prices for formula hog purchases. As such, these 

two price series are arguably the most important and widely used prices reflecting cash hog 

market supply and demand fundamentals. The daily negotiated purchased hog data specifically 

refers to hogs for which a base price is established and delivery of the hogs scheduled to the 

packer is expected to occur sometime during the next 14 calendar days. As discussed in the 

previous chapter, the relative volume of hogs being purchased through daily negotiated 

transactions has declined markedly and raised questions regarding the representativeness or 

reliability of these negotiated prices. 
19 | Page

 

The prior day slaughter report (LM_HG201) provides information summarizing volumes and 

prices of hogs slaughtered the previous business day. This report contains the base price for 

carcass-based purchases as well as the net price received for these purchase types. In addition, 

selected average carcass quality traits (weight, sort loss, backfat, loin depth, loineye area, and 

lean yield) are also summarized in this report. Base prices for live weight negotiated hogs 

slaughtered during the previous day are not reported within this report.18 This study’s main 

objective is to determine whether the net price received for negotiated purchases (reported in this 

report) can be estimated from information known at the time negotiated prices were reported in 

the prior day purchase report. As such, the main information of interest contained in this report 

includes the net price received and the base price. The latter price is only collected for carcassbased purchases in compiling this report. 

 

3.1 Negotiated Pricing Trends and Relative Price 

The daily negotiated prior day purchase live and carcass weighted average prices are shown in 

Exhibit 3.1.1 for January 2004 to December 2013. The price series trend together and have a 

0.99 correlation coefficient. The price series are expected to trend together as a live price is 

derived from a carcass value by adjusting the carcass value for an average dressing percentage. 

The daily negotiated prior day slaughter carcass base and net weighted average prices are shown 

in Exhibit 3.1.2 for January 2004 to December 2013. The price series trend together and have a 

1.00 correlation coefficient. The high correlation coefficient does not imply that one series can 

precisely predict the other series, as the spread between the base price and net price varies day to 

day. It only indicates statistically that the two price series have a strong positive linear 

relationship. 

For January 2004 to December 2013, the daily negotiated prior day slaughter weighted average 

net price minus the prior day slaughter weighted average base price is shown in Exhibit 3.1.3. 

The correlation coefficient between the price difference and carcass weighted average base price 

is 0.69 and between the carcass weighted average net price and price difference is 0.72. This 

indicates that the spread between the base and net prices varies positively, but not perfectly, with 

price levels. As such, other factors beyond price levels influence the spread between base and 

weighted average net prices. Day-to-day variability in the price spread has increased over time 

(see section 3.3 for the rolling 15-day coefficient of variation for these series). 

The AMS also reports negotiated low and high prices for alternative purchase methods. The prior 

day purchase carcass base price high minus low spread and live base price high minus low are 

shown graphically in Exhibits 3.1.4 and 3.1.5, respectively. A smaller high-low price difference 

 

18 The live negotiated price, which is the net price for purchases on a live weight basis, was established 

upon purchase of the animals and reported in LM_HG201. 
20 | Page

 

indicates a more integrated market where different buyers are purchasing based on similar 

pricing signals and similar quality hogs. The carcass high-low price difference has varied from 

$5 per hundredweight to $20 per hundredweight during the past decade. Considerable day-to-day 

variation is present in the high-low price difference. The live high-low price difference is more 

variable than the carcass high-low price difference (see section 3.3 for the rolling 15-day 

coefficient of variation for these series). The observed range, for both live and carcass 

transactions, indicates challenges with computing an alternative weighted average price that 

captures all relative information. 

In comparison to Exhibits 3.1.4 and 3.1.5, the carcass net price high minus low is illustrated in 

Exhibit 3.1.6. The high-low carcass net price differential varies consistently by more than $30 

per hundredweight. Rarely is the differential less than $15 per hundredweight. That is, the singleday variability between transactions (or lots) of carcass negotiated hogs is often as much as $60 

per head. One interpretation is that computing a weighted average net price from base prices may 

add variability over what is now observed with reported weighted average base prices. 

Finally, the difference between the prior day negotiated slaughter carcass weighted average base 

price and the prior day purchase carcass weighted average base price and prior day purchase live 

weighted average base price was analyzed. Note that these prices have differences in market 

timing in that the prior day negotiated is yesterday’s negotiated price, but the prior day slaughter 

base represents some combination of base prices negotiated during the past 14+ calendar days.19

As such, if a market that has prices that trend for a while, these price series would be expected to 

vary relative to one another. This would mean that one could not predict one series accurately 

from just the other series without incorporating additional market factors. This type of 

“forecasting” would undermine the intent of the MPR legislation to report prices with 

information provided by processors. 

 

19 Because for definition of negotiated trade hogs only need to be scheduled during the prior 14 

calendar days, slaughter can take place beyond the 14 day window. 
21 | Page

 

Exhibit 3.1.1. Daily Negotiated Prior Day Purchase Carcass and Live Base Prices, January 

2004 to December 2013 

Exhibit 3.1.2. Daily Negotiated Prior Day Slaughter Carcass Base and Net Prices, 

January 2004 to December 2013 
22 | Page

 

Exhibit 3.1.3. Daily Negotiated Carcass Prior Day Slaughter, Net Price Minus Base Price, 

January 2004 to December 2013 

Exhibit 3.1.4. Daily Negotiated Carcass Prior Day Purchase Spread Between Low and 

High Base Prices, ($/cwt), January 2004 to December 2013 
23 | Page

 

Exhibit 3.1.5. Daily Negotiated Live Prior Day Purchase Spread Between Low and High 

Base Prices ($/cwt), January 2004 to December 2013 

Exhibit 3.1.6. Daily Negotiated Carcass Prior Day Slaughter Spread Between Low and 

High Net Prices ($/cwt), January 2004 to December 2013 
24 | Page

 

3.2 Negotiated Hogs Purchase Shares

One pork industry concern with negotiated hog trade is that hogs marketed through negotiated 

trade may not accurately reflect market supply and demand fundamentals, particularly if 

negotiated hog trade is thinning. Lawrence and Grimes (2006) reported that as many as 57 

percent of swine forward pricing agreements have a base price tied to a negotiated trade price.20

Although this particular concern is beyond the current study’s scope, understanding the trend in 

negotiated trade is important for the degree of confidence when inferring a computed weighted 

average net price from purchase prices. An increasing share of negotiated transactions increases 

confidence in the reported weighted average price, and a decreasing share of negotiated 

transaction reduces confidence in the reported weighted average price. 

Exhibit 3.2.1 shows the historical percentage of both carcass and live hogs sold through 

negotiated means relative to total hogs procured. The trend has been consistently downward . 

Negotiated trade declined from around 20 percent in 2005 to commonly less than 5 percent in 

2013. That is, of the nearly 107 million hogs marketed in 2013, approximately 5.1 million head 

were marketed through a combination of carcass or live negotiated trade. 

Exhibits 3.2.2 and 3.2.3 show the daily percentage of negotiated purchase carcass and live 

transactions, respectively, from January 2004 to December 2013. While the trade volume for 

both has trended down over time, the carcass negotiated trade volume has lost the greatest 

market share by declining from around 23 percent in 2004 to around 6 percent in 2013. Live 

negotiated trade volume has commonly represented less than 4 percent of total hog marketings 

during the past decade. The daily live negotiated hog trade, as a percentage of daily total hog 

trade, has on certain days spiked up to 10 percent or more. The negotiated live trade continues to 

play a minor role in hog procurement for certain situations. 

 

20 Lawrence, J., and G. Grimes. “Production and Marketing Characteristics of the U.S. Pork Producers, 

2006.” University of Missouri-Columbia Dept. of Agricultural and Applied Economics working paper 

No. AEWP 2007-5. Accessed at: http://agebb.missouri.edu/mkt/ (13 January 2014). 
25 | Page

 

Exhibit 3.2.1. Prior Day Purchases Live and Carcass Negotiated Number of Head 

Reported Over Total Head Reported for All Purchase Types that Day (%), January 2004 

to December 2013 

Exhibit 3.2.2. Prior Day Purchases Carcass Negotiated Number of Head Reported Over 

Total Head Reported for All Purchase Types that Day (%), January 2004 to December 

2013 
26 | Page

 

Exhibit 3.2.3. Ratio of Negotiated Prior Day Live Purchased Head over Total Head 

purchased that Day (%), January 2004 to December 2013 
27 | Page

 

3.3 Relative Price Variation Trends by Purchase Method 

Section 3.1 outlined the trend in daily prices for various prices reported as a result of hog 

mandatory price reporting. Hog producers and hog processors often use price data for strategic 

and operational decision making. These decisions depend on the ability to confidentially predict 

prices and ensure that the predicted prices will closely represent actual prices. Prices that are 

more stable, or follow some pattern, are more easily predicted than prices that have higher 

variance. One challenge when analyzing the relative variance between price series is that price 

levels differ between items. For example, looking at 10 years of data for two different hog price 

series, such as negotiated purchase live weighted average base price and negotiated carcass 

weighted average net price, may show the exact same measures of dispersion. This may lead to 

the erroneous conclusion that both series have a price risk profile similar to each other. However, 

the risk is dependent of the overall price level. Economists and statisticians use the coefficient of 

variation to compare relative risk, which is: 

Coefficient of variation (%) = (standard deviation/average) × 100. 

The coefficient of variation allows for comparing or measuring price dispersion while accounting 

for the absolute level of prices. Higher coefficient of variation values indicate greater relative 

price risk, and lower coefficient of variation values indicate less relative price risk. A 15-day 

rolling average coefficient of variation for various negotiated hog price series is presented in 

Exhibit 3.3.1. The prior day purchases swine/pork formula price is reported here because of its 

tendency to have a base price tied to the negotiated base price. Data from June 2011 to 

December 2013 were used to visually observe relative dispersion differences between the price 

series. No price series indicates a strong tendency for lower relative price dispersion. 

Next, the coefficient of variation was computed for various high to low price spreads. The highlow coefficients of variation are shown in Exhibit 3.3.2. Data from June 2011 to December 2013 

were used to visually observe relative dispersion differences and trends between the high-low 

price series. The negotiated live high-low spread relative dispersion value has tended to trend 

above the other prices. Recently, the negotiated live high-low price spread has been observed to 

exceed the other price series by between 50 percent and 70 percent. The high-low slaughter 

carcass net price spread does not stand out as having lower relative price uncertainty to the highlow purchase carcass base price.
28 | Page

 

Exhibit 3.3.1. Daily Rolling 15-Day Coefficient of Variation for Weighted average Base 

Price for the Five Comparison Price Series’, June 2011 to December 2013 

Exhibit 3.3.2. Daily Rolling 15-Day Coefficient of Variation for High Price Minus Low 

Base Price for Prior Day Carcass Purchases, Live Purchases, and Carcass Slaughter (%), 

June 2011 to December 2013 
29 | Page

 

3.4 Comparison of Hog Quality by Purchase Method 

The transaction level net price is derived by starting with the base price and adjusting the base 

price by adding premiums and subtracting discounts for the quality attributes associated with the 

hogs comprising the transaction (or lot). Processors establish buying programs that list baseline 

quality attributes for every transaction. A premium is applied to the transaction when the average 

hog quality is above the baseline. A discount is applied to the transaction when the average hog 

quality is below the baseline. Or, for the case of carcass weight, a discount may be applied when 

the carcass weight falls either below a lower level threshold or above an upper level threshold. 

The premiums and discounts are usually not applied symmetrically. That is, the premium level 

and discount level are not the same for a similar deviation above or below the baseline. When 

hog purchases are made, little animal attribute information known about the transaction is 

available. See Appendix Exhibit A5 for a list of information collected for prior day purchase 

transactions. 

For computed weighted average net prices to add value to the pork industry, the AMS would 

need to compute a price that would be more informative than the existing reported weighted 

average base prices. Thus, any adjustment from a base price to a net price must assume that 

animal quality data is either predictable or consistent day-to-day. Understanding historical 

quality information trends by purchase method helps to make inferences regarding the reliability 

of AMS-computed net prices, derived from the base prices and available quality information, for 

industry use. 

Exhibits 3.4.1 through 3.4.5 show trends in quality attribute levels for carcass weight, percent 

lean, loin area, backfat, and sort loss, respectively, by purchase method. Carcass weight indicates 

a presence of seasonality, and the seasonal low-to-high weight range has been increasing over 

time (Exhibit 3.4.1). The day-to-day carcass weight variability has increased for negotiated 

carcass trade, which decreases the likelihood of confidently computing a relevant purchase net 

price using slaughter data. Furthermore, the negotiated trade carcass weight data vary notably 

from carcass weights observed for alternative purchase methods. Thus, there is no value in 

aggregating data between purchase methods to reduce the issue of small sample size with the 

prior day negotiated slaughter data. 

Percent lean has trended upward over time for alternative purchase methods other than 

negotiated carcass transactions (Exhibit 3.4.2). This finding again indicates that transactions 

other than negotiated carcass transactions are useless in providing information for deriving a 

computed net price from the purchase price. Negotiated carcass loin area has followed a slowly 

increasing trend in the mean with little variation around the mean (Exhibit 3.4.3). Mean backfat 

has followed a downward trend with all purchase types following a similar pattern (Exhibit 

3.4.4.). Negotiated trade carcass sort loss has become increasingly variable during the past three 
30 | Page

 

years (Exhibit 3.4.5). The sort loss range is as much as $0.50 under to more than $3 under. Sort 

loss is determined based on whether barrows and gilts fall within the individual’s packer’s 

established carcass weight, or lot, variation range. Recall, at the time a purchase transaction 

occurs, a lot’s carcass weight is unreported because it is unknown. Thus, making the adjustment 

from a base price to a computed net price would be difficult given the day-to-day variability in 

sort loss and not knowing an actual carcass weight for the lot. 

An important caveat to the discussion in the last paragraph relates to what data is required to be 

reported under the Mandatory Price Reporting Act. Only data that a packer collects must be 

reported. Over the past five years one firm, and possibly one additional firm, discontinued 

collecting quality data on all hogs purchased. Thus, the firm no longer provides quality data as 

part of the MPR Act.21 If a particular firm, or firms, routinely purchases hogs of quality 

sufficiently different from the market’s average quality, for a particular purchase type, then the 

firm’s decision to discontinue collecting quality data could move the industry average quality for 

that purchase method. Firms have discontinued collecting quality data because the cost savings 

from collecting the data and assigning discounts and premiums outweighs the cost associated 

with the probability of accepting hogs of inferior quality. That is, the firm is able to project 

quality based on the quality history of animals being delivered. Because quality data is 

aggregated for MPR reporting it is unknown how (or when) this change in procurement method 

impacted the quality averages for a particular purchase method. 

 

 

21 A side note is that the volume reported, by purchase method, refers only to the number of transactions 

used in computing the weighted average reported price. 
31 | Page

 

Exhibit 3.4.1. Prior Day Slaughter: Daily Carcass Weight by Purchase Method (lbs) 

January 2004 to December 2013 

Exhibit 3.4.2. Prior Day Slaughter: Percent Lean by Purchase Method (%), January 2004 

to December 2013 
32 | Page

 

Exhibit 3.4.3. Prior Day Slaughter: Loin Area by Purchase Method (inches), January 2004 

to December 2013 

Exhibit 3.4.4. Prior Day Slaughter: Backfat by Purchase Method (inches), January 2004 

to December 2013 
33 | Page

 

Exhibit 3.4.5. Prior Day Slaughter: Sort Loss by Purchase Method ($/cwt), January 2004 

to December 2013 
34 | Page

 

3.5 Chapter Summary 

 To derive a computed weighted average net price from base prices, it is

important that the quality of hogs aggregated between purchase and

slaughter is consistent or predictable day to day.  

 Carcass weight has strong seasonality, and day‐to‐day carcass weight,

by purchase method, varies considerably

 Purchase method negotiated trade percent lean indicates a

differentiated hog relative to alternative purchase methods.

 Level of loin area tends to be the least variable quality attribute, but

carcass negotiated trade level of loin area has been increasing in

variability.

 The sort loss level for negotiated carcass trade is unpredictable.

 Using quality information from alternative purchase agreement

methods other than negotiated trade is not feasible due to differences

in quality attribute levels between purchase agreement methods.

 
35 | Page

 

Chapter 4. Analysis of Mandatory Price Reporting 

Transactions Data 

This analysis assesses the ability to accurately predict the negotiated weighted average net price 

given the base prices for individual transactions at the time the base price is reported by the AMS 

(i.e., the day the prior day purchase report is released). For prior day purchases, negotiated base 

prices are collected and reported as a weighted average base price, but the net price received 

cannot be determined until the hogs are slaughtered and price adjustments for carcass merits are 

made. Once hogs are slaughtered, the net price is reported by the AMS in the prior day slaughter 

report. 

To evaluate the validity of computing and reporting a projected negotiated weighted average net 

price from prior day purchase negotiated base price, a four-phase process was used. The goal 

was to evaluate whether a computed weighted average net price can be predicted accurately the 

day the purchased base price is reported. The four phases involve 1) replicating the transaction 

data consistent with data reported in AMS reports; 2) evaluating correlations between the base 

price and the net price; 3) using those correlations between base and net prices to project a net 

price; and 4) evaluating whether the projected net price is useful information. 

In addition, the research team evaluated whether an alternative prior day negotiated weighted 

average base price computation could yield a price that provides more information on the day-today impact of market conditions. In particular, the team analyzed how nonmarket factors impact 

the day-to-day variation in the currently reported negotiated weighted average base price. If 

nonmarket factors affect the weighted average base price, then accounting for nonmarket factors 

may allow for an alternative weighted average base price to be more reflective of day-to-day 

market changes. 

Three guiding principles were used here in analysis and reporting of results. First, to ensure data 

confidentiality plant and company identification information was all randomized to prevent 

anyone from matching results with a particular company. Second, to ensure credibility and 

validity, the team replicated the process that the AMS uses to create both live and carcass base 

prices for prior day purchase reports and both the base and net prices for prior day slaughter 

reports. Third, the analysis must yield alternative price information that is easily replicated, 

which requires a transparent methodology, and that is useful to the pork industry. 
36 | Page

 

4.1. Data and Data Procedures 

Individual transaction data that are reported by packers daily to USDA were analyzed in this 

section to replicate data reported by the AMS in daily prior day purchase reports. Data available 

for this analysis were all data required to be reported by hog processors under mandatory price 

reporting. A detailed breakdown of data is described in Exhibits A3 through A5 in this report’s 

Appendix section.22

Thirty months of recent prior day purchase barrows and gilts data for live and carcass 

transactions and prior day slaughter barrows and gilts data for carcass transactions, representing 

daily data between June 6, 2011, and December 17, 2013, were used for analysis.23 This time 

period was chosen to reflect current industry practices and provide sufficient data for this 

analysis. A total of 32 pork packing plants owned by 17 pork packing firms are represented in 

the mandatory price reporting hog purchase and slaughter transaction databases during the 30-

month window. Data were scrubbed for errors, AMS-established thresholds, and MPR 

confidentiality guidelines. Data requested for this analysis are listed in Exhibits 4.1.1 and 4.1.2 

for prior day purchase negotiated trade and prior day slaughter negotiated trade, respectively. 

Exhibit 4.1.1. Transactions Data for Prior Day Purchase Negotiated Live and Carcass 

Trade 

Variable 

Plant identifier 

Firm identifier 

Lot purchase identifier 

Base prices for the lot ($/cwt): live prices and carcass prices 

Number of head in the lot 

Average live weight for the lot 

a.For animals purchased on a live weight basis, this is a projected weight because weights 

are unknown until the animals are slaughtered. 

b.No weight is submitted to AMS for animals sold on a carcass basis. 

State of origin of lot 

Transaction date 

 

 

22 The USDA AMS Compliance and Enforcement Division routinely visits hog processing plants for 

compliance visits on mandatory price reporting. This ensures that hog processors are following the 

regulations set forth in the MPR Act. See Appendix A2 for a historical list of compliance visit data. 23 The total number of transactions included in the prior day purchase data was 82,656 (20,232 for 2011, 

32,636 for 2012, and 29,788 for 2013). The total transactions included in the prior day slaughter data was 

121,813 (32,784 for 2011, 48,789 for 2012, and 40,250 for 2013). 
37 | Page

 

To replicate the AMS-reported weighted average prices and head counts for the prior day 

purchase negotiated live report data, the research team used the same data filters that the AMS 

uses: 1) eliminating any transaction with fewer than 10 head; 2) eliminating any transaction with 

a projected live weight less than 240 pounds or greater than 300 pounds; and 3) including both 

packer and producer sold transactions. The team was able to exactly replicate AMS-reported 

price information using these filters. 

To replicate AMS-reported weighted average prices and head counts for the prior day purchase 

negotiated carcass report data, the same data filters were used that the AMS uses: 1) eliminating 

any transaction with fewer than 10 head and 2) including both packer and producer sold 

transactions. The team was able to exactly replicate AMS-reported price information by 

following this protocol. 

Exhibit 4.1.2. Transactions Data for Prior Day Slaughter Negotiated Carcass Trade24

Variable 

Plant identifier 

Firm identifier 

Lot slaughter identifier 

Base price for the lot ($/cwt): carcass prices only 

Average net price for the lot ($/cwt): carcass prices only 

Number of head in the lot25

Average live weight for the lot 

Average carcass weight for the lot 

Average sort loss for the lot 

Average backfat measure for the lot 

Average loin area for the lot 

Average lean percentage for the lot 

Transaction date 

 

 

24 Only carcass transactions are reported for prior day slaughter trade. 

25 Note, that the average head in a lot between slaughter and purchase may not match due to death loss 

between when the purchase price was set and when the lot was slaughtered (up to 18 days later) due to 

sort loss, pens being split up at delivery, or additional factors unknown at the time the purchase price was 

set. 
38 | Page

 

To replicate AMS-reported weighted average prices and head counts for the prior day slaughter 

negotiated carcass report data, the data were filtered based on the AMS protocol by 1) 

eliminating any transaction with fewer than seven head; 2) including only producer sold 

transactions; 3) eliminating transactions reflecting sort loss transactions26; 4) eliminating 

transactions occurring on a live basis27; and 5) eliminating any transaction with a reported 

average lot carcass weight of less than 100 pounds. The team was able to exactly replicate AMSreported price information to within a few cents per hundredweight by following this protocol. 

Since base prices for prior day live negotiated purchases are not reported in the prior day 

slaughter report (only base prices for slaughter purchases are reported in the prior day slaughter 

report), live negotiated base prices could not be compared with net prices using the prior day 

slaughter data. One possible way to attempt to predict the net price from the prior day slaughter 

report with the base price, from the prior day negotiated live hog purchases, would require 

matching the slaughter report transactions with the purchase transactions. If hog deliveries 

reported in the prior day slaughter report could be accurately matched with those reported in the 

prior day purchases for live negotiated sales, then analysis could be conducted by comparing 

prices for individual negotiated live purchases with their respective net prices. 

 

The research team attempted to match the prior day purchase and prior day slaughter transactions 

for live hog negotiated sales. The analysis suggests that it is virtually impossible to match the 

purchase and slaughter transactions for live sales. Only 87 of the nearly 24,000 live negotiated 

transactions during the 30-month time period (June 2011 to December 2013) were able to be 

matched by using the lot and plant identification values reported by packers in each of the two 

AMS reports. If the team relaxed plant identification and used only lot identifier, this increased 

to 167 matches, which is still less than 1 percent of the live negotiated transactions. Furthermore, 

many of these transactions were not perfect matches, and the number of head often deviated by 

more than 100 head. As such, the team sees no reliable way to consistently match a 

representative set of live negotiated prior day purchase transactions to prior day slaughter 

transaction data. Therefore, limited opportunity is available for using existing AMS data to 

predict net prices from base prices for negotiated live hog purchases. Instead, other alternatives 

for predicting net prices were necessary as described in the next section. 

 

26 AMS personnel daily sort and view data for the exact cut between sort loss transactions and normal 

transactions. Replicating this manual step would be immensely time consuming and was judged 

unnecessary for the precision needed for this project. In lieu of visual choice of the daily break point, the 

researchers chose the most common breakpoint price during the 30 months of data. This price was 

$45/cwt, which eliminated a few transactions. 

27 AMS personnel visually separate live and carcass transactions. Replicating this step was judged 

unnecessary for accomplishing the goals of this project. In lieu of visual choice of the daily break point, 

the researchers eliminated all of those transactions where the ratio of net price to base price was greater 

than 1.25. 
39 | Page

 

4.2. Predicting Net Price from Base Price

Net price varies considerably relative to the base price. Understanding how base prices relate to 

net prices is important for measuring the reliability of computing net price from a base price. 

Fortunately, prior day slaughter data contain both base and net prices for comparison. Recall, 

there is not a unique identifier between a purchase transaction and a slaughter transaction. 

Exhibits 4.2.1 through 4.2.3 illustrate the scatter plot of the net price versus the base price for 

carcass-based transactions collected from the prior day slaughter report data for the last half of 

2011 and all of 2012 and 2013, respectively. Each dot in a chart represents a net price on the 

vertical axis matched with its respective negotiated base price on the horizontal axis. The chart 

only includes carcass-based purchases because the base price for negotiated live hogs is not 

collected in the AMS prior day slaughter report. Readily apparent from the chart is the variability 

in the negotiated net price around the base. The net prices frequently differ from the base prices 

by $2 per hundredweight or more in either direction. 

 
40 | Page

 

Exhibit 4.2.1. Scatter Plot of Prior Day Slaughter Negotiated Carcass Net Price Versus 

Base Price ($/cwt), by Lot, June 2011 to December 2011 

Exhibit 4.2.2. Scatter Plot of Prior Day Slaughter Negotiated Carcass Net Price Versus 

Base Price ($/cwt), by Lot, January 2012 to December 2012
41 | Page

 

Exhibit 4.2.3. Scatter Plot of Prior Day Slaughter Negotiated Carcass Net Price Versus 

Base Price, by Lot, January 2013 to December 2013

To further illustrate how the net price differs from the base price, the prior day carcass net price 

and base price differences were plotted in Exhibits 4.2.4 through 4.2.6 for the last half of 2011 

and all of 2012 and 2013, respectively. These charts further illustrate the magnitude of variation 

in net prices around negotiated base prices. Individual net prices differ from base prices by 

economically important amounts every day. 

Because so many transactions were presented in the previous charts, it is difficult to discern the 

precise distribution of the prior day slaughter net prices around the base from the charts alone. 

Thus, Exhibits 4.2.7 through 4.2.9 provide the distribution of the prior day slaughter net price 

minus the base price for each year, respectively. 

For the last half of 2011 (Exhibit 4.2.7), on average, the net price was $2.47 per hundredweight 

greater than the base price with a standard deviation of $3.38 per hundredweight. Although 45 

percent of transaction net prices were between zero and $3 per hundredweight greater than base 

prices, 37 percent were more than $3 per hundredweight greater, and 9 percent were greater by 

$7 per hundredweight or more. On the other extreme, 6.5 percent of net prices were more than $2 

per hundredweight below the base price. 

For 2012 (Exhibit 4.2.8), on average, the net price was $2.14 per hundredweight greater than the 

base price with a standard deviation of $3.13 per hundredweight. Although 52 percent of 
42 | Page

 

transaction net prices were between zero and $3 per hundredweight greater than base prices, 30 

percent were more than $3 per hundredweight greater, and 7.5 percent were greater by $7 per 

hundredweight or more. On the other extreme, 6.5 percent of net prices were more than $2 per 

hundredweight below the base price. 

For 2013 (Exhibit 4.2.9), on average, the net price was $2.55 per hundredweight greater than the 

base price with a standard deviation of $3.22 per hundredweight. Although 47 percent of 

transaction net prices were between zero and $3 per hundredweight greater than base prices, 38 

percent were more than $3 per hundredweight greater, and 9 percent were greater by $7 per 

hundredweight or more. On the other extreme, 5.5 percent of net prices were more than $2 per 

hundredweight below the base price. 

The main conclusion is that there is a substantial range of net prices around the base prices, and 

this circumstance reflects the myriad of carcass quality differences present in the pork industry. 

No simple method exists to adjust the base price to predict the net price. Next, the capability of 

predicting net prices using information that may be available when the base price is established 

was explored. 

Exhibit 4.2.4. Negotiated Prior Day Slaughter Carcass Net Price Minus Base Price, by Lot 

($/cwt), June 2011 to December 2011 

 
43 | Page

 

Exhibit 4.2.5. Negotiated Prior Day Slaughter Carcass Net Price Minus Base Price, by Lot 

($/cwt), January 2012 to December 2012 

Exhibit 4.2.6. Negotiated Prior Day Slaughter Carcass Net Price Minus Base Price, by Lot 

($/cwt), January 2013 to December 2013
44 | Page

 

Exhibit 4.2.7. Negotiated Prior Day Slaughter Net Carcass Price Minus Base Price, Last 

Half of 2011 

Summary Statistic Net Price minus Base Price ($/cwt) Percentage of Transactions (%) 

 Less than -$3.00 4.2% 

 -$3.00 to -$2.01 2.3% 

 -$2.00 to -$1.01 3.7% 

 -$1.00 to -$0.01 7.2% 

 $0.00 to $.99 11.7% 

 $1.00 to $1.99 16.6% 

 $2.00 to $2.99 17.1% 

 $3.00 to $3.99 8.4% 

 $4.00 to $4.99 7.2% 

 $5.00 to $5.99 7.2% 

 $6.00 to $6.99 5.3% 

 $7.00 to $7.99 3.9% 

 $8.00 or more 5.3% 

 Total 100.0% 

Average $2.47 

Std Dev $3.38 

Minimum -$22.38 

Maximum $20.39 

Exhibit 4.2.8. Negotiated Prior Day Slaughter Net Carcass Price Minus Base Price, 2012 

Summary Statistic Net Price minus Base Price ($/cwt) Percentage of Transactions (%) 

 Less than -$3.00 4.1% 

 -$3.00 to -$2.01 2.5% 

 -$2.00 to -$1.01 4.3% 

 -$1.00 to -$0.01 7.6% 

 $0.00 to $.99 13.4% 

 $1.00 to $1.99 20.1% 

 $2.00 to $2.99 18.5% 

 $3.00 to $3.99 5.9% 

 $4.00 to $4.99 5.6% 

 $5.00 to $5.99 5.8% 

 $6.00 to $6.99 4.9% 

 $7.00 to $7.99 3.5% 

 $8.00 or more 3.9% 

 Total 100.0% 

Average $2.14 

Std Dev $3.13 

Minimum -$36.41 

Maximum $18.24 
45 | Page

 

Exhibit 4.2.9. Negotiated Prior Day Slaughter Net Carcass Price Minus Base Price, 2013 

Summary Statistic Net Price minus Base Price ($/cwt) Percentage of Transactions (%) 

 Less than -$3.00 3.7% 

 -$3.00 to -$2.01 1.8% 

 -$2.00 to -$1.01 3.6% 

 -$1.00 to -$0.01 6.8% 

 $0.00 to $.99 12.6% 

 $1.00 to $1.99 18.2% 

 $2.00 to $2.99 15.8% 

 $3.00 to $3.99 7.5% 

 $4.00 to $4.99 7.0% 

 $5.00 to $5.99 8.1% 

 $6.00 to $6.99 5.9% 

 $7.00 to $7.99 4.1% 

 $8.00 or more 4.9% 

 Total 100.0% 

Average $2.55 

Std Dev $3.22 

Minimum -$18.63 

Maximum $18.89 
46 | Page

 

4.3. Predicting Net Price from Information Available when the 

Purchase Base Price is Established 

Of interest is whether the net price can be predicted at the time the prior day purchase report is 

released based upon the information available at the time the base purchase price is negotiated. 

The negotiated purchase base price represents prices for hogs to be delivered to plants during the 

next 14 calendar days. The goal was to determine whether the differences between the slaughter 

net price and the purchase base price discussed above can be predicted based upon information 

available at the time the AMS prior day purchase negotiated price report is released. This is one 

of this study’s central objectives. 

At the time negotiated hogs are purchased, very little is known about the hogs. Prior day 

purchase data reported to AMS are the date of the negotiation, the number of head in the lot, the 

estimated weight for live weight purchases (but not for carcass purchases), the plant and 

company that bought the hogs, the state of origin of the hogs, and the negotiated base price. This 

is all the information that is known at the time of negotiated purchase transaction that could be 

used to predict the net price at the time the hogs are delivered to the packer during the next two 

weeks. Because AMS does not collect net prices for live weight purchases and also does not 

collect an estimated weight for negotiated carcass purchases,28 this eliminates use of estimated 

average hog weight as a potential predictor of net carcass price. The origin of the hogs is strongly 

related to the plant that purchased the hogs, so adjusting prices by purchasing plant essentially 

adjusts for origin. 

To develop a model to predict net price based upon base price using information that is available 

on the day that the purchase is negotiated, a regression model was developed to explain the 

difference between net price and base price. The model regressed the difference in net price 

minus base price as a function of head (Head); head squared (Head2), which allows for a 

nonlinear relationship; binary variables for plants that purchased the hogs (Plant); and monthly 

dummy variables to account for seasonality (Month). This model was used to predict net prices 

given base prices. In essence, this predicts net prices for each transaction based upon information 

available at the time the purchase was negotiated and that was potentially relevant for predicting 

how the net price might differ from the negotiated base price. Lot size, plant purchasing the 

hogs, and seasonality were accounted for in the model to forecast net price given the base price. 

The model is formally (e is a random error term and i refers to individual transaction)29: 

 

28 The live price is the net price because no adjustments are made to the price paid for quality in the lot. 

Thus, no quality information is known for animals procured through the live negotiated trade. 

29 Regression analysis was used to allow for simultaneous evaluation of multiple factors. The variation of 

regression would be to conduct data sorts and apply averages from the sorts to adjust the base price to a 

computed net price. 
47 | Page

 

ଶ݄݁ܽ݀ଶܾ௜ ൅ ݄݁ܽ݀ଵܾ଴	 ൅ ܾ ൌ௜ ݅ܿ݁ݎܲ	݁ݏܽܤ	 െ௜ ݅ܿ݁ݎܲ	ݐܰ݁

௜

௞௜ݐ݈ܲܽ݊ ෍ ௞ଶାܾ൅	

௄

௞ୀଶ

௠௜݄ݐ݊݋ܯ ෍ ௠ା௄ଶାܾ൅ 

ଵଶ

௠ୀଶ

൅ ݁௜

 

The errors (e) from this model illustrate our ability to predict net prices based on information 

available to the AMS at the time the negotiated base price is established and at the purchase 

transaction. If the errors are generally near zero, this indicates that a reliable estimate of net 

prices based upon purchase base prices could be devised at the time the base is determined. 

Errors deviating from zero suggest reduced ability to accurately predict net prices. 

The errors for each day during the last half of 2011 and all of 2012 and 2013 for every carcass 

negotiated transaction in predicting net price are illustrated in Exhibits 4.3.1, 4.3.2, and 4.3.3, 

respectively.30 The distribution of the errors, from these charts, is summarized in Exhibits 4.3.4, 

4.3.5, and 4.3.6 for 2011, 2012, and 2013, respectively. 

For the last half of 2011, for 41 percent of transactions, the net price could be predicted to within 

$1 per hundredweight (up or down) accuracy using information available at the time the base is 

negotiated. In contrast, 59 percent of predicted net prices would be wrong by more than $1 per 

hundredweight. Furthermore, 11 percent of predicted net prices would be wrong by at least $3 

per hundredweight (either too high or too low). 

For 2012, for 43 percent of transactions, the net price could be predicted to within $1 per 

hundredweight (up or down) accuracy using information available at the time the base is 

negotiated. In contrast, 57 percent of predicted net prices would be wrong by more than $1 per 

hundredweight. Furthermore, 9.6 percent of predicted net prices would be wrong by at least $3 

per hundredweight (either too high or too low). 

For 2013, for 44 percent of transactions, the net price could be predicted to within $1 per 

hundredweight (up or down) accuracy using information available at the time the base is 

negotiated. In contrast, 56 percent of predicted net prices would be wrong by more than $1 per 

hundredweight. Furthermore, 11.3 percent of predicted net prices would be wrong by at least $3 

per hundredweight (either too high or too low). 

This illustrates the difficulty with predicting the net price for negotiated purchases at the time the 

negotiated base is established at the time of the purchase transaction. The magnitude of error 

 

30 The model was also estimated excluding the number of head and head squared variables, but results 

were very similar and conclusions were identical to those reported here. 
48 | Page

 

estimating net prices at the time negotiated base prices are reported is excessively large to 

provide useful market information in reporting predicted net prices. 

Mandatory livestock reporting regulations do not require processors to report a common lot 

identifier between purchase transactions and slaughter transactions. So, prior day slaughter 

negotiated carcass base and net prices were used to analyze the ability to predict a net price from 

a base price. By using only the slaughter data, base prices were able to be matched with net 

prices and all associated market and nonmarket factors. By not being able to match purchase and 

slaughter transactions, only the time dimension between when a negotiated purchase price is 

established for a lot and when the lot is slaughtered (between one and 14 days after the purchase 

price is set) was left out. That is, the team was not able to confidently match slaughter 

transactions occurring today with purchases that occurred sometime during the previous 14 days. 

Ideally, the analysis would match purchase transactions with slaughter transactions; however, 

this not possible. 

Exhibit 4.3.1. Errors Predicting Negotiated Carcass Net Price at the Time the Negotiated 

Base is Established ($/cwt), June 2011 to December 2011

 
49 | Page

 

Exhibit 4.3.2. Errors Predicting Negotiated Carcass Net Price at the Time the Negotiated 

Base is Established ($/cwt), January 2012 to December 2012 

Exhibit 4.3.3. Errors Predicting Negotiated Carcass Net Price at the Time the Negotiated 

Base is Established ($/cwt), January 2013 to December 2013 
50 | Page

 

Exhibit 4.3.4. Error Predicting Net Price when Base Price is Negotiated, Last Half of 2011 

Summary Statistic Error Predicting Net Price Percentage of Transactions (%) 

 Less than -$6.00 1.9% 

 -$6.00 to -$5.01 1.0% 

 -$5.00 to -$4.01 1.9% 

 -$4.00 to -$3.01 3.1% 

 -$3.00 to -$2.01 5.6% 

 -$2.00 to -$1.01 9.8% 

 -$1.00 to -$0.01 18.3% 

 $0.00 to $0.99 25.7% 

 $1.00 to $1.99 20.5% 

 $2.00 to $2.99 8.7% 

 $3.00 to $3.99 2.6% 

 $4.00 or more 0.9% 

 Total 100.0% 

Average $0.00 

Std Dev $2.20 

Minimum -$25.00 

Maximum $14.56 

Exhibit 4.3.5. Error Predicting Net Price when Base Price is Negotiated, 2012 

Summary Statistic Error Predicting Net Price Percentage of Transactions (%) 

 Less than -$6.00 1.9% 

 -$6.00 to -$5.01 1.0% 

 -$5.00 to -$4.01 1.7% 

 -$4.00 to -$3.01 3.1% 

 -$3.00 to -$2.01 5.7% 

 -$2.00 to -$1.01 9.6% 

 -$1.00 to -$0.01 17.3% 

 $0.00 to $0.99 25.5% 

 $1.00 to $1.99 24.4% 

 $2.00 to $2.99 8.0% 

 $3.00 to $3.99 1.5% 

 $4.00 or more 0.5% 

 Total 100.0% 

Average $0.00 

Std Dev $2.16 

Minimum -$35.85 

Maximum $16.63 

 
51 | Page

 

Exhibit 4.3.6. Error Predicting Net Price when Base Price is Negotiated, 2013 

Summary Statistic Error Predicting Net Price Percentage of Transactions (%) 

 Less than -$6.00 2.4% 

 -$6.00 to -$5.01 1.0% 

 -$5.00 to -$4.01 1.8% 

 -$4.00 to -$3.01 3.1% 

 -$3.00 to -$2.01 5.6% 

 -$2.00 to -$1.01 9.9% 

 -$1.00 to -$0.01 17.2% 

 $0.00 to $0.99 23.6% 

 $1.00 to $1.99 22.0% 

 $2.00 to $2.99 10.7% 

 $3.00 to $3.99 2.2% 

 $4.00 or more 0.7% 

 Total 100.0% 

 

Average $0.00 

Std Dev $2.39 

Minimum -$24.25 

Maximum $18.84 
52 | Page

 

4.4. Base Price Sensitivity to Market Buyer Participation

Hog processors are regionally dispersed (see Exhibits 2.2.1 and 2.2.2) and use different 

procurement strategies between firms and/or plants. Thus, day-to-day firm participation may 

impact day-to-day variability in the weighted average negotiated base price. 

Exhibits 4.4.1 and 4.4.2 display the number of firms and plants, respectively, participating in the 

daily negotiated live and carcass trade between June 2011 and December 2013. If market 

participation becomes too small, then the mandatory price reporting confidentiality requirement 

(see Appendix Exhibit A1) would be cause for discontinuing negotiated price reporting. For 

neither carcass nor live negotiated trade is there current concern that the price series will be 

discontinued due to the mandatory price reporting confidentiality requirement. The mandatory 

price reporting confidentiality requirement not only protects processors from firm-specific data 

being reported, but the requirement also protects information users from accessing information 

that is based on a significantly small unrepresentative sample of market activity. 

The daily largest four-plant share was computed to examine the concentration of plants 

purchasing (see Exhibits 4.4.3 and 4.4.4). This share is for the four plants accounting for the 

highest percentage of trade on a particular day. Thus, from one day to the next, the four plants 

could be an entirely different plant buying group. The largest four-plant shares have been upward 

trending during the past 30 months. Only in the case of negotiated live purchases is there an 

indication of the share consistently approaching 1.0. 
53 | Page

 

Exhibit 4.4.1. Number of Different Firms that Bought Negotiated Hogs, Separately for 

Carcass and Live, by Day, June 6, 2011, to Dec. 17, 2013 

Exhibit 4.4.2. Number of Different Firms that Bought Negotiated Hogs, Separately for 

Carcass and Live, by Day, June 6, 2011, to Dec. 17, 2013
54 | Page

 

Figure 4.4.3. Shares of Purchases by the Plants with the Four Largest Shares by Day, 

Carcass and Live Negotiated Purchases Combined, June 2011 to December 2013 

Exhibit 4.4.4. Shares of Purchases by the Plants with the Four Largest Shares by Day, 

Separately for Carcass and Live Negotiated Purchases, June 2011 to December 2013 

 
55 | Page

 

To determine the daily prior day purchase weighted average reported price sensitivity to who is 

participating in the market each day, the changes in the reported daily weighted average base 

price were computed by removing each plant’s purchases each day one plant at a time, 

recalculating the weighted average, and comparing that to the reported weighted average. For 

example, if plant one bought 10 lots of hogs in the negotiated carcass market on a particular day, 

all of those purchases were removed from the carcass purchases, the weighted average base price 

for that day was recalculated, and the recalculated weighted average price was compared to the 

AMS-reported weighted average price. This was done for each plant that purchased hogs each 

day from June 6, 2011, to December 17, 2013. 

This study refers to each of these plant-by-day prices as plant-day prices. That is, if a plant buys 

hogs today, regardless of the number of head, that constitutes one plant-day. Four plants all 

buying each of 10 days would constitute 40 plant-days. Overall, 32 plants had purchased at least 

one lot of hogs (either carcass or live negotiated) during the 30-month time frame, though several 

of these plants did not purchase regularly in one or both negotiated markets. Overall, for 

negotiated carcass purchases, total plant-days equaled 9,888 plant-days (number of plants that 

purchased each day summed across all days), total plant-days equaled 5,116 plant-days for live 

negotiated purchases during the 30-month time period. 

If the new weighted average price calculated by eliminating a plant was lower than the AMSreported base price, this was considered a decline in the change in base price. That is, if 

removing a plant’s purchases results in a lower reported weighted average base price for a day, 

this is recognized as a decline in the weighted average base price as a result of removing that 

plant’s purchases on that day. If removing a plant’s purchases results in a higher weighted 

average base price than the AMS-reported weighted average base price that day, this is 

recognized as an increase in the weighted average base price. 

Exhibit 4.4.5 reports the distributions of changes in weighted average base prices that result from 

removing individual plants’ purchases. For about 4 percent of plant-days for the carcass prices 

and 3 percent of plant-days for the live price, individual plant purchases impact the weightedaverage AMS-reported base price by $1 per hundredweight or more in absolute value. During 84 

percent of plant-days for carcass purchases and 75 percent of plant-days for live purchases, 

weighted averages calculated by removing individual plants would be within $0.25 per 

hundredweight (higher or lower) of the AMS-reported weighted average price. If no plant’s 

purchases influenced the AMS-reported weighted average base price any day, then 100 percent 

of the plant-days would be near zero. The fact that 16 percent of carcass purchase plant-days and 

25 percent of live purchase plant-days have more than $0.25 per hundredweight base price 

influence on the AMS prices indicates that the plant being included in the market quote for a 

single day does influence reported weighted-base average prices frequently by at least $0.25 per 

hundredweight, especially for live purchases. 
56 | Page

 

Exhibit 4.4.5. Distribution of How Much Daily Prior Day Purchase Weighted Average 

Base Price Would Change As Plants Included in the Weighted Average are Dropped One 

at a Time, June 6, 2011, to Dec. 17, 2013 

 Percentage of Plant-Days 

Change in Weighted Average Price Negotiated Negotiated 

($/cwt) Carcass Price Live Price 

Decline by $1.00 or more 1.7% 2.4% 

Decline by $0.25 to $0.99 7.6% 11.7% 

Change between -$0.25 and $0.25 83.9% 74.6% 

Increase by $0.26 to $1.00 4.7% 10.7% 

Increase by more than $1.00 2.2% 0.6% 

Total 100.0% 100.0% 

Note: A plant-day refers to any plant that bought at least one lot of 

hogs during a day. 

Similar to the plant purchases, the weighted average base price distributions were also calculated 

including or excluding entire companies each day in the reported weighted average base price. In 

this analysis, all purchases by each company each day were removed one at a time and the 

weighted average negotiated carcass and live base prices were recalculated. During the 30-month 

time period, there are a total of 5,005 company-days (sum of companies that bought each day 

across all days) for carcass negotiated purchases and 3,876 company-days for live negotiated 

purchases. 

As shown in Exhibit 4.4.6, for 64 percent of carcass and 67 percent of live negotiated purchase 

company-days, the weighted average base price would be within $0.25 per hundredweight of the 

reported AMS price regardless of whether any individual company (each removed one at a time) 

was included in the weighted average price reported by AMS. Thus, for 36 percent of carcass 

and 33 percent of live negotiated reported weighted averages, the company being included in the 

weighted average each day does influence prices by at least $0.25 per hundredweight (up or 

down). Of course, these numbers by firm are larger than the by plant numbers reported above of 

16 percent carcass and 25 percent live purchases because several companies own more than one 

plant, and as such, removing a company from the weighted average, involves frequently 

removing more individual transactions from the daily data than if just an individual plant is 

removed. 

 
57 | Page

 

Exhibit 4.4.6. Distribution of How Much Daily Prior Day Purchase Weighted Average 

Base Price Would Change As Companies Included in the Weighted Average are Dropped 

One at a Time. 

 

Percentage of CompanyDays 

Change in Weighted Average Price Negotiated Negotiated 

($/cwt) Carcass Price Live Price 

Decline by $1.00 or more 4.8% 5.1% 

Decline by $0.25 to $0.99 14.1% 13.1% 

Change between -$0.25 and $0.25 63.9% 67.2% 

Increase by $0.26 to $1.00 12.7% 13.8% 

Increase by more than $1.00 4.5% 0.8% 

Total 100.0% 100.0% 

Note: A company-day refers to any packing firm that bought at least 

one lot of hogs during a day. 

Because of the percentage of observations in the tails (above a $0.50/cwt move up or down) 

reported in Exhibits 4.4.5 and 4.4.6 we further investigated whether individual plants may be 

independently influencing the weighted average market price. During the June 6, 2011, to 

December 17, 2013 period a plant may have participated in the market a total of 643 plant 

reporting dates. We computed the percentage of trading days, of the 643 plant reporting dates 

that a specific plant influenced the weighted average price by at least $0.50/cwt. and at least 

$1/cwt. The results are reported in Exhibit 4.4.7 for negotiated carcass transactions and Exhibit 

4.4.8 for negotiated live transactions. Only plants purchasing greater than 5% of the trading days 

were analyzed. While we recognize the daily participation of individual plant purchases is an 

important factor to consider, to protect confidentiality we categorized percentage of days a 

purchase was made (of the 643 trading days) as less than fifty percent or greater than or equal to 

fifty percent. Plants were randomly assigned a row in each table, and the row order is not the 

same between tables, i.e., one cannot compare row one of Exhibit 4.4.7 and row one of Exhibit 

4.4.8. Interpretation of the exhibit values is important. 

For row one of Exhibit 4.4.7, the value of 0.6% represents that removing this particular plant 

from the weighted average price resulted in the national weighted average price declining by 

$0.50/cwt or more 0.6% of the 643 days. There is only one plant that raises concern over its 

purchasing presence influencing the national weighted average base price. The plant represented 

by row one in Exhibit 4.4.7 shows a strong tendency to be $0.50/cwt. or more below the national 

weighted average carcass base price. Put another way, whether this plant purchases hogs or not 

on a given day causes the weighted average reported market price to move by a $1/cwt. or more 
58 | Page

 

32.8% of the trading days analyzed here. The fact the reported market price can change by an 

economically important amount depending upon whether the plant is in or out of the market is a 

non-market factor affecting day-to-day reported price movement. What about the net price? 

For the plant of concern here, we next looked at the impact removing the plant has on the 

weighted average reported net slaughter price. Removing the plant from the weighted average 

net slaughter price causes a $0.50/cwt. or more increase 4.5% of the time. This value is still 

significant even though the frequency of impact is substantially less than for the reported 

purchase base price affect. Regardless of finding a lower impact for the plant’s net price, based 

on the information available when the base price is established there will still be poor 

predictability of a weighted average net price from the base price. What is the implication of this 

finding? 

The finding of one influential plant creates a quandary for AMS. First, mandatory price reporting 

requires AMS to report all data collected, so AMS cannot arbitrarily drop a plant. Second, due to 

confidentiality disclosing the plant identifier is not an option, so a plant exemption cannot be 

requested in the process of MPR reauthorization. Third, the presence of the plant in the report 

means that hog buyers and sellers will observe day-to-day price movements depending on 

whether this plant is in the market on a given day and how large of market share this plant 

represents from one day to the next. What is the solution? 

We suggest that AMS consider tracking individual plant price effect for all (barrows and gilts, 

carcass and live, and sow) negotiated prices reported, i.e., AMS could follow a similar 

methodology used here to measures the change in price due to dropping a plant.31 AMS could 

develop a rule for switching plants from negotiated to other market arrangements, for when a 

plant is considered to have a non-market related impact on the weighted average price. For 

example, AMS could confirm type of negotiated purchases with the plant. 32

We, also, suggest that AMS examine segmenting negotiated purchase data weighted average 

price into thirds based on the number of animals represented by a particular report. For example, 

if the negotiated barrows & gilts carcass purchase data includes 6,000 head of hogs, then the 

breakpoints would be at 2,000 and 4,000 head. The concept involves ordering transactions (or 

lots) from low price to high price. Divide the number of hogs into three equal portions.33 Each 

hog in each third has a price assigned to it. The weighted average price is then computed for 

 

31 While the plant we found causes the weighted average base price to decrease merely by the 

presence of the plant purchasing hogs, the other consideration is that plants purchasing value 

added hogs (for example, antibiotic free, natural) could similarly influence the weighted average 

price higher for the case of a thin market. 

32 We also believe this methodology minimizes the chance of reports being discontinued due to 

the 3/70/20 rule. 

33 For this scenario, a pen may be split between two categories. 
59 | Page

 

each third. This information would give the industry an idea of the variability of prices within the 

reported weighted average price.

Within thinly traded markets a set of outlier transaction is more likely to have a significant 

impact. We did not examine whether through the process of eliminating one plant’s transactions 

that the problem may become recursive, i.e., the removal of one plant triggers another plant to 

have a more sizeable price impact on the weighted average, etc.
60 | Page

 

Exhibit 4.4.7. Percentage of the 643 Trading Days over the June 2011 - December 2013 

Period that the Weighted Average Carcass Base Price would have Changed by Excluding 

Individual Plants from the Weighted Average.1

 Percent of Decline by Decline by Increase by Increase by 

 

Days 

Bought2

$0.50/cwt or 

more 

$1/cwt or 

more 

$0.50/cwt or 

more 

$1/cwt or 

more 

Each Row Represents a Unique Processing Plant (Only 

plants with a Participation Rate Greater than 5% Reported) 

≥50% 0.6% 0.6% 60.8% 32.8% 

≥50% 1.1% 1.1% 0.3% 

≥50% 0.3% 0.3% 

≥50% 2.3% 0.2% 

≥50% 1.2% 1.2% 0.3% 

≥50% 2.8% 2.8% 0.2% 

≥50% 0.8% 0.8% 

≥50% 4.7% 4.7% 

≥50% 0.2% 0.2% 

<50% 10.7% 10.7% 

≥50% 0.2% 0.2% 0.2% 

<50% 0.0% 0.3% 0.0% 

≥50% 0.0% 0.9% 0.0% 

≥50% 0.3% 0.3% 0.2% 

<50% 0.8% 0.2% 

≥50% 0.3% 0.3% 1.6% 

<50% 1.9% 1.9% 

≥50% 0.3% 0.3% 0.2% 

<50% 0.6% 0.0% 0.0% 

1. To restrict plant identifiers the row placement of plants differs between Exhibit 4.4.7 and 

Exhibit 4.4.8. 

2. To restrict plant identifiers we coded the percent of trading days a plant buys, of the 643 

trading days total, as greater than or equal to 50% or less than 50%. 

 
61 | Page

 

Exhibit 4.4.8. Percentage of the 643 Trading Days over the June 2011 - December 2013 

Period that the Weighted Average Live Base Price would have Changed by Excluding 

Individual Plants from the Weighted Average.1

 Percent of Decline by Decline by Increase by Increase by 

 

Days 

Bought2

$0.50/cwt or 

more 

$1/cwt or 

more 

$0.50/cwt or 

more 

$1/cwt or 

more 

Each Row Represents a Unique Processing 

Plant (Only plants with a Participation Rate 

Greater than 5% Reported) 

≥50% 1.2% 1.2% 1.4% 

<50% 0.5% 0.5% 

<50% 0.3% 0.3% 

<50% 0.5% 0.5% 

≥50% 7.6% 7.6% 0.9% 

<50% 0.2% 0.2% 0.2% 

≥50% 1.6% 1.6% 

≥50% 0.2% 0.2% 

≥50% 0.3% 0.3% 

≥50% 0.6% 0.6% 

≥50% 4.0% 4.0% 

<50% 0.2% 0.2% 

≥50% 12.1% 2.3% 

<50% 1.6% 1.6% 

<50% 0.2% 

1. To restrict plant identifiers the row placement of plants differs between Exhibit 4.4.7 and 

Exhibit 4.4.8.

2. To restrict plant identifiers we coded the percent of trading days a plant buys, of the 643 

trading days total, as greater than or equal to 50% or less than 50%. 
62 | Page

 

4.5. Regional Trends in Prices and Volumes

Using MPR publically available data we examined the regional trends in negotiated prior day 

purchase base price and volume. The western cornbelt trade and eastern cornbelt trade are 

subsets of the national trade. Iowa-Minnesota trade is not shown here because it is subset of the 

regional data. Generally, the national report is a weighted average of both the data reported in 

the eastern cornbelt report and the western cornbelt report. The price and volume trends are 

examined to determine changes in procurement patterns. 

Exhibit 4.5.1 shows the historical path of negotiated eastern cornbelt and western cornbelt prices. 

The price series tend to follow a similar path over the 14 year period. Regional volume is 

presented in Exhibit 4.5.2. Not surprising, volume in both regions has trended downward. The 

western cornbelt volume has dropped more than the eastern cornbelt volume. What are the 

implications of the substantial decline in western cornbelt volume relative to the drop in eastern 

cornbelt volume? 

Exhibit 4.5.3 represents the ratio of the western cornbelt price to national price and the ratio of 

the eastern cornbelt price to the national price. Two observations are noteworthy from the data 

in this exhibit. First, the western cornbelt price is generally above the national average price 

(above 1.00 in the exhibit) and the eastern cornbelt price is generally below the national average 

price (below 1.00 in the exhibit). Second, eastern cornbelt price relative to the national price is 

much more variable than is the western cornbelt price relative to the national price. Next, we 

combine the price information with relative share of the national trade. 

Exhibit 4.5.4 represents the relative shares of western cornbelt and eastern cornbelt hogs 

contributing to the national totals. This exhibit confirms the trend in data observed in Exhibit 

4.5.2. By combining the information in Exhibits 4.5.2, 4.5.3 and 4.5.4 the following conclusion 

can be made. Current period day-to-day national average trade is likely to reflect either a 

majority of western cornbelt hogs or a majority of eastern cornbelt hogs. This is a change from 

the past where the western cornbelt trade was a dominant contributor to computing the national 

price. Currently, there is no clear dominant regional market or is the market evenly represented 

day-to-day. Also, the national average price today is more reflective of eastern cornbelt prices 

than in the past, which indicates the national average price is more susceptible to the variability 

in the eastern cornbelt prices. Is there a solution? 

 
63 | Page

 

Our recommendation is that the pork industry participants interested in the national weighted 

average use a weighting matrix other than head reported for a specific date. For example of a 

particular trading date in January 2014, 

 Western Cornbelt Negotiated Carcass Trade: 2749 head $83.14/cwt. 

 Eastern Cornbelt Negotiated Carcass Trade: 2450 head $80.55/cwt. 

Now, the national weighted average price would be computed as equal to weights based on 

observed volume: 

 = [(2749 x $83.14) + (2450 x $80.55)]/(2749+2450) = $81.92/cwt., 

here the volume is 49% eastern cornbelt and 51% western cornbelt.34 An alternative weighting 

matrix, where the national average would be computed as equal to a twenty-day average is: 

 = [(0.62x $83.14) + (0.38 x $80.55)] = $82.10/cwt. 

The regional prices do not change, only the weighting function changes. While this example 

shows that the new computed price increased over the reported price, the price could have as 

easily decreased if another time period would have been chosen. Computing alternative volume 

weights over a longer time period removes day-to-day price swings due to which region 

represents a majority of the market share from one day to the next. Anyone in the industry can 

run this computation without AMS facilitating the computation, i.e., industry participants can 

choose their preferred number of days to compute a national weighted average price. 

 

 

34 Daily volume weights do not always equate to one when adding the eastern cornbelt trade and 

western cornbelt trade. Of the 3157 days reviewed these two regions account for 95% or more of 

hogs reported in the national weighted average price 95% of the time.
64 | Page

 

Exhibit 4.5.1. Daily Prior day Purchase Negotiated Base Price for the Western Corn and 

Eastern Corn Belt, September 2001 through January 2014.

Exhibit 4.5.2. Daily Prior day Purchase Negotiated Volume for the Western Corn Belt 

Price and Eastern Corn Belt, September 2001 through January 2014. 
65 | Page

 

Exhibit 4.5.3. Daily Prior day Purchase Negotiated Ratio of Western Corn Belt to the 

National and the Ratio of Eastern Corn Belt to the National, September 2001 through 

January 2014.

 Exhibit 4.5.4. Daily Prior day Purchase Negotiated Volume for the Western Corn Belt to 

the National and the Ratio of the Eastern Corn Belt to the National, September 2001 

through January 2014. 

 
66 | Page

 

4.6. Chapter Summary

 Analyzing 30 months of recent transactions on negotiated live and 

carcass purchases from the AMS demonstrates challenges in predicting 

net prices at the time negotiated prices are established. 

 For more than one-third (half) of the transactions, the difference between 

the net price and the negotiated base price is more than $3 per 

hundredweight ($2 per hundredweight) in absolute value. 

 Multiple regression analysis, a statistical tool for aggregating across 

data sorts, was used to predict net price based on information that would 

be known at the time the base price is established. For more than 10 

percent (20 percent) of transactions, the predicted net price would be off 

by more than $3 per hundredweight ($2 per hundredweight) using this 

method to predict net prices. 

 The particular plant participating in the market purchasing hogs can 

influence market-reported negotiated base price. During 84 percent of 

plant-days for carcass purchases and 75 percent of plant-days for live 

purchases, single plants impact the weighted average reported prices by 

$0.25 per hundredweight in absolute value. However, for 3 percent to 4 

percent of plant-days, the particular plant participating in the market 

impacts reported base price by $1 per hundredweight or more. And, we 

found that one plant can have a significant impact on the day-to-day 

weighted average market price change. That one plant moved the market 

by $0.50/cwt over 60% of the trading days. 

 We suggest that AMS consider tracking individual plant price effect for all 

(barrows and gilts, carcass and live, and sow) negotiated prices reported, 

i.e., AMS could follow a similar methodology used here to measures the 

change in price due to dropping a plant. AMS could develop a rule for 

switching plants from negotiated to other market arrangements, for when a 

plant is considered to have a non-market related impact on the weighted 
67 | Page

 

average price. Impacts of alternative rules should be explored if this 

approach were taken to assess impacts on reported prices.

 We suggest that AMS examine segmenting negotiated purchase data 

weighted average base price into thirds based on the number of animals 

represented by a particular report. For example, if the negotiated barrows 

& gilts carcass purchase data includes 6,000 head of hogs, then the 

breakpoints would be at 2,000 and 4,000 head. The concept involves 

ordering transactions (or lots) from low price to high price. Divide the 

number of hogs into three equal portions. Each hog in each third has a 

price assigned to it. The weighted average price is then computed for each 

third. We recommend assessing how this new reported set of three weighted 

average prices would perform and what information it would add to current 

base price reporting. 

 We recommend that the industry participants consider a multi-day (say 

20) volume weight average to compute the national average price from 

the regional prices. This will mitigate day-to-day price fluctuations that 

are due to non-market factors. 

 
68 | Page

 

Chapter 5. Conclusions and Recommendations 

The hog market has undergone dramatic structural change during the past decade. Among the 

major changes have been substantial reductions in daily negotiated hog purchases with 

associated increases in formula marketing agreements that rely upon thinning negotiated prices 

for bases. The thinning base price raises concerns regarding whether the market is subject to 

manipulation and whether the base price is a reliable representation of market supply and 

demand fundamentals each day. In essence, the efficiency of the negotiated cash hog market 

trade is being questioned. Indeed, this report’s data analysis indicates that the particular packer 

participating in the market does potentially influence the reported weighted average negotiated 

base prices, though most of the time (75 percent) by a modest ($0.25 per hundredweight or less) 

amount. Nonetheless, there are times when an individual packing plant’s purchases have much 

greater impact on reported weighted average negotiated prices. 

This study’s main objective was to assess the ability of the AMS to accurately compute (predict) 

net prices received for hogs at the time the negotiated base prices are reported. Several 

approaches were used to assess the ability of the USDA AMS to predict the base prices at the 

time the negotiated base prices are established. 

Overall, this study concludes that no sufficiently accurate method to predict net prices at the time 

base prices are negotiated can be created. This conclusion is based on thorough analysis of daily 

reported base prices and net prices from the past 10 years and detailed analysis of all individual 

transactions data on negotiated base and net prices from the past 30 months. The errors in 

translating base prices into expected net prices would be too large to make this computation and 

reporting of it have value for the hog industry. 

5.1 Recommendations 

Going forward the AMS and hog industry should consider several actions: 

 This study does not recommend that the AMS report computed net prices, derived from 

negotiated base prices, at the time negotiated base prices are established. The errors in 

this projection would be too large to make this information have any added value to the 

hog industry. 

 

 The inability to predict net prices at the time base prices are established is not a problem 

associated with packer submission of information, AMS data collection, mandatory price 

reporting, or AMS reporting. Instead, it’s related to the nature of the hog market. Too 
69 | Page

 

much unpredictable variation in hog quality is present across transactions, and over time, 

to enable reliably computing net prices at the time the base prices are established. 

 Tremendous variation exists among net purchase prices in the hog industry. This suggests 

strong price incentives are present for producing hogs that meet packer preferences for 

carcass weight and quality. Producers could benefit from continued information that 

shows them how much value they forfeit when they market hogs that do not take 

advantage of, or that do not fit well into, a particular packer’s value matrix. If 

transactions costs are low (search costs and transportation costs) and if the term of the 

hog marketing contract allows, then hog producers might consider shopping around the 

hogs sold through negotiated trade. 

 Thinning negotiated base prices are apparent, and those using these reported prices as 

bases in marketing agreements might want to explore other alternatives if recent trends 

continue. 

 Individual producers may be more able to predict their net prices more effectively than 

the AMS can predict a net price for the entire market or than the AMS can predict even 

for individual transactions. Transactions are not distinguished by a unique seller 

identifier, so the AMS cannot correlate purchase transactions with slaughter transactions. 

Individual hog producers, however, do know this information for their own transactions. 

Individual hog producers who can consistently produce a relatively predictable set of 

carcass quality attributes can likely predict the net prices that they will receive more 

accurately than can the AMS or than the researchers can using only AMS data. 

 We suggest that AMS examine segmenting negotiated purchase data weighted average 

base price into thirds based on the number of animals represented by a particular 

report. The concept involves ordering transactions (or lots) from low price to high 

price. Divide the number of hogs into three equal portions. Each hog in each third has a 

price assigned to it. The weighted average price is then computed for each third. We 

recommend assessing how this new reported set of three weighted average prices would 

perform and what information it would add to current base price reporting. 

 
70 | Page

 

 We suggest that AMS consider tracking individual plant price effect for all (barrows and 

gilts, carcass and live, and sow) negotiated prices reported, i.e., AMS could follow a 

similar methodology used here to measures the change in price due to dropping a 

plant. AMS could develop a rule for switching plants from negotiated to other market 

arrangements, for when a plant is considered to have a non-market related impact on the 

weighted average price. Impacts of alternative rules should be explored if this approach 

were taken to assess impacts on reported prices.

 We recommend that the industry participants consider a multi-day (say 20) volume 

weight average to compute the national average price from the regional prices. This 

will mitigate day-to-day price fluctuations that are due to non-market factors. 
71 | Page

 

Appendices 

Appendix Exhibit A1. Mandatory Price Reporting Confidentiality Guidelines 

The 3/70/20 confidentiality guideline requires the following three conditions: 

• At least three reporting entities need to provide data at least 50 percent of the time over the 

most recent 60‐day time period. 

• No single reporting entity may provide more than 70 percent of the data for a report over the 

most recent 60‐day time period. 

• No single reporting entity may be the sole reporting entity for an individual report more than 20 

percent of the time over the most recent 60‐day time period. 

Source: http://www.ams.usda.gov/AMSv1.0/getfile?dDocName=STELDEV3019136
Appendix Exhibit A2. Hog Processing Plants Quarterly Plant Compliance Visits Data Source: LMR Quarterly Plant Compliance Visits, Swine Reporting; http://www.ams.usda.gov/AMSv1.0/LMRQuarterlyPlantReviewArchive 

1234

First quarter 2009 19 272 0 0 14 3 17 20 37 12 Second quarter 2009 29 336 0 0 15 1 16 25 41 13 Third quarter 2009 19 346 0 0 9 6 15 28 43 2Fourth quarter 2009 29 418 0 0 7 8 15 22 37 10 First quarter 2010 18 230 0 0 6 2 8 27 35 2Second quarter 2010 28 431 0 0 11 0 11 14 25 13 Third quarter 2010 28 265 0 0 10 0 10 12 22 12 Fourth quarter 2010 19 362 0 0 2 0 2 10 12 3 First quarter 2011 19 343 0 2 7 1 10 9 19 2 Second quarter 2011 25 246 0 0 5 0 5 17 22 5 Third quarter 2011 21 331 0 0 2 0 2 17 19 1 Fourth quarter 2011 20 317 0 0 0 0 0 18 18 7 First quarter 2012 23 432 0 0 2 0 2 11 13 10 Second quarter 2012 23 416 0 0 1 0 1 3 4 4 Third quarter 2012 24 266 0063 9 0 9 9 Fourth quarter 2012 23 393 0 0 3 3 6 0 6 6 First quarter 2013 17 348 0030 3 0 3 3 Second quarter 2013 13 206 0 0 2 2 4 0 4 2 Third quarter 2013 19 342 0011 2 2 4 2 

Non-Com

Issues R

This Q

Plants Lots with Non-Compliances

Audited This 

Quarter

Lots Audited This Quarter

Total NonCompliance Issues 

This Quarter

Unresolved NonCompliance Issues Brought Forward

Total NonCompliance 

Issues
Appendix Exhibit A3. Swine Mandatory Price Reporting Form LS118 
Appendix Exhibit A3 (continued). Swine Mandatory Price Reporting Form LS118 
75 | Page

 

Appendix Exhibit A4. LS-118B: Swine Prior Day Report - Slaughtered Swine, see A3 also 

 
76 | Page

 

Appendix Exhibit A5. LS-118B: Swine Prior Day Report - Purchased Swine, see A3 also