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This documentation contains information on the legislative
mandate for the reporting of retail scanner prices for
random-weight fresh meat products, a description of
retail scanner data, the meat categories included in the
ERS database, the data collection and processing procedures,
and the resulting data. See more
information for details on: 1) how the retail scanner
prices differ from retail prices reported by the Bureau
of Labor Statistics (BLS) and 2) the calculation of meat
price spreads.
Legislative Mandate
The
Livestock Mandatory Reporting Act of 1999 (P.L. 106-78,
Title IX, Section 257, Publication of Information on Retail
Purchase Prices for Representative Meat Products) requires
the compilation and publication of retail purchase prices
for "representative food products made from beef,
pork, chicken, turkey, veal, or lamb." ERS has been
given the responsibility for the publication of the retail
meat purchase prices and quantity measures for these representative
meat products.
Scanner Data
The Act states that the Secretary of Agriculture is allowed
to "obtain the information from retailers or commercial
information sources and use valid statistical sampling
procedures if necessary." ERS is using retail supermarket
scanner data obtained from commercial sources to fulfill
the requirements of the Act.
Scanner data are collected at the point of sale by supermarkets
using electronic scanners in the check-out lines. Stores
may use bar codes attached to the product package or store
codes typed into the register to record the product type
and price.
Supermarkets are defined as retail grocery stores with
dairy, produce, fresh meat, packaged food, and nonfood
departments and annual sales of $2 million or more. Not
included in retail scanner data are sales from butcher
shops, warehouse clubs, convenience stores, fast-food
establishments, and restaurants; at institutions (e.g.,
hospitals and schools); through mail order; or by food
distributors that choose not to provide their data for
third-party use.
Supermarkets that use electronic scanners may provide
the information to commercial data firms (i.e., syndicated
data suppliers). These firms combine point-of-sale transaction
data from supermarkets. They process and categorize the
data, and sell information to both supermarket chains
and manufacturers for inventory, revenue control, and
general marketing purposes.
To ensure confidentiality of the meat retail scanner
data, a third-party cooperator (to ERS) obtains and processes
the retail scanner data and provides ERS with summary
statistics. Store- and chain-level data are not provided
to ERS in raw form nor can it be constructed from the
data published on the ERS website. No data related to
individual store- and/or chain-level sales are obtained
or maintained by ERS.
While not based on a random sample, the raw data underlying
the database are from supermarkets across the United States
that account for approximately 20 percent of U.S. supermarket
sales (i.e., all commodity volume or ACV). In the future,
price reporting by region may be added to the database.
Included Meat Categories
After consultation with industry groups, ERS chose to
base the product groupings in the meat retail scanner
database on those defined by the URMIS
industry standard and BLS. In addition to the BLS
categories for beef, pork, and chicken, ERS reports a
composite price for all beef, all pork, all chicken, all
turkey, all lamb, and all veal.
Currently, BLS reports about 30 meat-cut categories,
excluding lamb and veal, for the entire fresh meat department
(one of the five standard departments within a supermarket).
Many meat cuts are aggregated in the BLS data into a combined
category. For example, items listed as chuck roast, arm
pot roast, shoulder pot roast, and 7-bone pot roast are
combined into the chuck roast category.
ERS is using URMIS codes to categorize descriptions of
different cuts of meat so the ERS and BLS data are comparable.
First, items in retailers' point-of-sale systems—that
are represented in the meat retail scanner database—are
matched (by ERS' third-party cooperator) to an URMIS code.
Second, URMIS codes are assigned to the appropriate scanner
data category. (See item
groupings by scanner data category for a list of categories
in the retail scanner database and examples of individual
meat cuts that are in those categories. See scanner
and BLS categories for the scanner data categories
that correspond to the BLS meat categories. Both files
are in Excel 
format).
Because the ERS data are based on URMIS codes, the system
can accommodate more exacting item descriptions than the
BLS data. Initially, ERS is publishing weighted-average
prices from the retail scanner data side-by-side with
matching BLS price data. After further observation and
evaluation of the retail scanner data, ERS plans to report
more detailed meat-cut categories.
BLS reports a composite fixed-weight price index for
each commodity, requiring ERS to construct a composite
price for beef, pork, or poultry. ERS uses BLS prices
for meat cuts and fixed cut-out proportions—based
on the typical way a carcass is cut up—to calculate
the composite retail price for beef, pork, and chicken.
These are the composite retail prices that ERS publishes
monthly as part of the meat
price spreads. In comparison, the composite prices
from the meat retail scanner data for all beef, all pork,
all chicken, all turkey, all lamb, and all veal are based
on actual transactions and will change as consumers vary
their purchasing patterns.
Only random-weight
items that are species-specific and sold in the fresh
meat department of traditional supermarkets are included
in ERS' meat retail scanner database. Multi-species items,
canned meats, products containing meat (such as frozen
dinners), and deli products are not included. Although
most bacon and sausage are sold in fixed-weight packages,
the database does contain information on random-weight
bacon and sausage.
The items reported from the retail scanner data for meat
are:
Beef
Ground chuck
Ground beef, 100-percent beef
Lean and extra lean ground beef
All uncooked ground beef
Chuck roast, USDA Choice, boneless
Chuck roast, graded and ungraded but not choice or prime
Round roast, USDA Choice, boneless
Round roast, graded and ungraded but not choice or prime
All uncooked beef roasts
Steak, T-bone USDA Choice, bone-in
Steak, rib eye USDA Choice
Steak, round, USDA Choice
Steak, round, graded and ungraded but not choice or prime
Steak, sirloin USDA Choice, boneless
Steak, sirloin, graded and ungraded but not choice or
prime
All uncooked beef steaks
Beef for stew, boneless
All uncooked other beef not veal (such as beef briskets
and ribs)
All beef
Pork
Bacon, sliced
Chops, center cut, bone in
Chops, boneless
All pork chops
Ham, boneless not canned
All ham (not canned or sliced)
Sausage, fresh, loose
All other pork excluding canned and sliced (such as pork
roast and ribs)
All pork
Poultry
Chicken, fresh whole
Chicken, breast, bone-in
Chicken, legs, bone-in
All chicken
Turkey, frozen whole
All turkey
Other Meat
All lamb
All veal
Data Collection and Processing
To maintain confidentiality of the meat retail scanner
data, ERS' third-party cooperator obtains retail scanner
data at the chain level by item from a commercial data
firm. Meat sold in random-weight
packages requires special data processing procedures that
differ from those used for other retail food items that
have manufacturers' universal product codes (UPC bar codes).
Random-weight foods may be labeled with UPC bar codes
(meat more often than produce), but—for the same
item—the code may vary among supermarket chains and
among stores within a chain. As a result, for this process,
item codes are standardized across stores and retailers.
Once item codes are standardized, item prices are checked
for feature activity. Featuring refers to the price discounts
offered to consumers through retailers' weekly feature
advertisements. These discounts likely have an effect
on the quantity of meat sold. In preparation of the data
(by ERS' third-party cooperator), information on featuring
activity is matched and compared to the price provided
in the retail scanner data. Where differences in the recorded
price and the feature price are observed, the feature
price is used to represent the price of the product to
the consumer. For example, the regular price of Choice
T-bone steak in supermarket X is $7.50 per pound. In the
second week of May, the advertised price is $6.50 per
pound. Depending upon the supermarket's data management
system, this feature price may or may not be recorded
as the purchase price. (Sometimes item discounts are recorded
at the bottom of a sales receipt and are subtracted from
the total sale.) In this example, the advertised feature
price for supermarket X's Choice T-bone steak would replace
the recorded price for that item in the database. Processes
have been created and iterations performed to ensure that
the feature price adjustment for individual items are
valid and performed in an appropriate and consistent manner.
After adjusting for feature discounts, the data include
dollar sales, price per pound, and volume sold for each
item. Items are classified into appropriate cut and aggregate
categories based on the item description and background
information. Items other than those in a BLS category
are assigned to a broader category. For example, ungraded
steak is assigned to the category "all uncooked beef
steaks" and a beef cut not in another category (such
as a beef brisket) is assigned to "all uncooked other
beef not veal." All items per specie are combined
for the species totals (all beef, all pork, etc).
Three variables are reported monthly for each cut and
aggregate category: a weighted-average price, an index
of volume sold, and the percent of volume sold under featuring
(or feature discounts). The weighted-average price for
each category is computed by dividing total dollar sales
for the month by the volume sold (in pounds). The volume
index is calculated by dividing the volume sold per month
by the monthly average of volume sold in 2001. The number
is converted to an index with the monthly average for
2001 equaling 100. The percent of volume sold under feature
is the volume sold under feature (in pounds) divided by
the total volume sold for the month (in pounds) multiplied
by 100.
These summary data are then delivered to ERS every month
by our third-party cooperator, reviewed by ERS staff for
consistency and quality, and posted to the ERS website
on, or near, the 20th of the month. The data have a 2-month
reporting lag; for example, prices for May are reported
in July.
Revisions are incorporated into the database monthly
and will be reflected in the latest monthly release. Revisions
are based on additional data or refined methodology.
Data Results
Weighted-average prices, the volume index, and the percent
sold under feature are reported monthly for the categories
listed above. Data are posted at Colorado State University's
Livestock
Marketing Information Center in two ways: summary
tables and a searchable
database.
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