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1. What
legislation mandates the collection of this data?
2. What is electronic scanner data,
and how is the confidentiality of individual stores protected in the
LMIC data set?
3. What
does "featuring" mean?
4. What
are the categories of meat included in the database?
5. How
were the categories of meat determined?
6. What
are URMIS codes and how is the LMIC using them?
7. Which
stores are included in the scanner data?
8. How
are data weighted to arrive at a national average price?
9.
What
types of difficulties arise in scanner data collection for meat and
how are they addressed?
10. How
does the BLS collect meat price data?
11. How do the LMIC scanner data compare with the BLS data?
12. How
are meat price data used in market and policy analysis?
13.
How
are meat price spreads calculated?
14. What
geographic coverage is provided by the scanner data?
What legislation mandates the
collection of this data?
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
was originally responsible for publishing retail meat purchase prices and
quantity measures for these representative meat products. In
addition, USDA's Agricultural Marketing Service has released background information
on the rule (which implements the program).
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What is electronic scanner
data, and how is the confidentiality of individual stores protected
in the LMIC data set?
Data are collected at the point of sale
by supermarkets using electronic scanners in 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 retail grocery stores with dairy, produce, fresh
meat, packaged food, and nonfood departments and annual sales of $2
million or more. 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.
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 the LMIC) obtains and processes the
retail scanner data and provides the LMIC with summary statistics. Store-
and chain-level data are not provided to the LMIC in raw form nor can it
be constructed from the data published on the LMIC website. No data
related to individual store- and/or chain-level sales are obtained
or maintained by the LMIC. The summary data are delivered to ERS every
month by our third-party cooperator, reviewed by the LMIC staff for
consistency and quality, and posted to the LMIC website.
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What does "featuring"
mean?
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
the LMIC's 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.
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What are the categories of meat included
in the database ?
Average monthly retail scanner prices are
reported for beef, pork, poultry, lamb, and veal. Only random-weight
items that are species-specific and sold in the fresh meat
department of traditional supermarkets are included in the LMIC's 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 data from individual point-of-sale transactions are
aggregated into the following categories:
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
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How were the categories of meat
determined?
In the development of the
meat retail scanner database, ERS consulted with industry groups and
chose to base the product groupings in the meat retail scanner
database on those defined by the URMIS
industry standard and BLS. 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.
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.
Because the LMIC data are based on URMIS codes, the system can
accommodate more exacting item descriptions and, thus, more specific
retail prices by group than the BLS data. Combined with industry
agreed-upon carcass yields, the scanner data could translate into a
more accurate "rebuild" of the carcass and give us better
information for calculating price spreads.
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What are URMIS codes and how is ERS
using them?
The Uniform Retail Meat Identity Standards
(URMIS) codes were established in 1973 by the National Cattlemen's
Beef Association. The system was developed to provide a
retail-meat-cut identification system and a standardized
nomenclature for every retail red meat item (beef, veal, lamb, and
pork).
The goal of URMIS is to eliminate consumer confusion caused by
the proliferation of names used to describe retail meat cuts. Before
URMIS, a specific retail cut had several different names depending
on the store or region of the country in which it was sold. For
example, a Kansas City strip, New York strip, and beef loin steak
are all the same cut. While the URMIS standards have been part of
the industry for several decades, the program is strictly voluntary
and has seen mixed levels of implementation.
The LMIC is using URMIS codes to categorize descriptions of different
cuts of meat so the
LMIC 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
LMIC's 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).
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Which stores are included in the scanner
data?
Retail scanner data are from supermarkets that: 1)
process their receipts by electronic scanners, 2) sell products
through the traditional supermarket retail meat case, and 3)
voluntarily provide their data to commercial data firms.
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.
The
LMIC's
third-party cooperator obtains the retail scanner data from a
commercial data firm. The
LMIC
does not have information about the stores whose data are included
in the database, but we know that the information covers
approximately 20 percent of U.S. supermarket sales.
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How are data weighted to arrive at a
national average price?
The
LMIC's third-party cooperator obtains
retail scanner data at the chain level by item from a commercial
data firm. 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. Because of the variation in item codes for random-weight
meats, the
LMIC's cooperator standardizes item codes across stores and
retailers. After adjusting for feature discounts, items are
classified into appropriate cut and aggregate categories based on
the item description and background information. The
weighted-average price for each category is computed by dividing
total dollar sales for the month by the volume sold (in pounds).
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What types of difficulties arise in
scanner data collection for meat and how are they
addressed?
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 the retail scanner database,
item codes are standardized (by the
LMIC's third-party cooperator) across
stores and retailers.
Once codes for items 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 the
LMIC's
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.
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How does the BLS collect meat price
data?
Meat prices are included in the information that the
Bureau of Labor Statistics collects for development of the Consumer
Price Index (CPI). The CPI represents all goods and services
purchased for consumption. BLS has classified expenditure items into
more than 200 categories, arranged into eight major groups. Food and
beverages—items such as breakfast cereal, milk, coffee, chicken,
wine, full-service meals, and snacks—are in one major group.
For each of the more than 200 categories, BLS has chosen samples
of items to represent the thousands of varieties available in the
marketplace. For example, in a given supermarket, the Bureau may
choose a plastic bag of golden delicious apples, U.S. extra fancy
grade, weighing 4.4 pounds to represent the "apples" category.
Each month, BLS data collectors visit or call thousands of retail
stores all over the United States to obtain price information on
thousands of items used to track and measure price changes in the
CPI. These prices represent a scientifically selected sample of the
prices paid by consumers for goods and services purchased.
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How do the
LMIC scanner data compare
with the BLS data?
The
LMIC retail scanner data supplements BLS data in three ways. First, the
LMIC database contains an index of
volume sold (with the average monthly volume for 2001 equaling 100). BLS does not collect information on the volume of meat sold. Second,
it provides additional specie coverage for lamb and veal. Third, BLS
collects a "snapshot" of prices from sample stores once a month.
This may not capture the full amount of featuring done by the store.
Since featuring influences the volume sold and the
LMIC scanner
database reflects featuring for the entire month, it is hypothesized
that the
LMIC data may report lower prices.
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How are meat price data used in market
and policy analysis? Meat prices from BLS are used to develop farm-to-retail
price spread information that measures the relative
contributions of farm production, food manufacturing, wholesaling,
and retailing firms. Changing consumer preferences are one of the
driving forces behind changing food selections. As preferences
change, so do the marketing services needed to transform live
animals to finished products. The recent strong economy raised
incomes and allowed more consumers to pay for convenience. Families
have lifestyles that include limited time for preparing food at
home, raising the demand for quick, easy-to-prepare food and the
accompanying marketing services. Price-spread information captures
both changes in the relative prices of inputs used by food marketing
firms and changes in consumer demand for marketing services and
convenience.
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How are meat price spreads
calculated?
ERS calculates the difference (spread) between
the value of live animals at the farm, carcasses at wholesale
levels, and meat products at retail levels. ERS analysts calculate
farm values for Choice steers and slaughter hogs, and wholesale and
retail values for the meat produced by Choice steers, slaughter
hogs, and broilers to determine price spreads. Farm-to-retail
price spreads for individual food items outlines the current
methodology ERS uses to determine farm, wholesale, and retail values
for meat. ERS is required by the Livestock Mandatory Reporting Act
of 1999 to continue using BLS retail prices in calculating price
spreads for 2 years after the first release of the retail scanner
prices for meat.
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What geographic coverage is provided by
the scanner data?
At first, the
LMIC's meat retail scanner
database will provide national coverage. 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. In the future, price reporting by region
(Northeast, Midwest, South, and West) may be added to the database.
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