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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 *.xls
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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