United States

Department of

Agriculture

Economic

Research

Service

Economic

Research 

Report

Number 105

October 2010 

Ephraim Leibtag

Catherine Barker

Paula Dutko

How Much Lower Are 

Prices at Discount Stores?

An Examination of Retail Food Prices
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Recommended citation format for this publication:

Leibtag, Ephraim, Catherine Barker, and Paula Dutko. How Much Lower Are 

Prices at Discount Stores? An Examination of Retail Food Prices, ERR-105, 

U.S. Dept. of Agri., Econ. Res. Serv. September 2010.

Use of commercial and trade names does not imply approval or constitute 

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United States 

Department 

of Agriculture 

www.ers.usda.gov 

A Report from the Economic Research Service

Economic

Research 

Report

Number 105

October 2010

How Much Lower Are Prices 

at Discount Stores?

An Examination of Retail Food Prices

Abstract

Nontraditional stores, including mass merchandisers, supercenters, club warehouse 

stores, and dollar stores, have increased their food offerings over the past 15 years 

and often promote themselves as lower priced alternatives to traditional supermarkets. 

How much lower are food prices at these stores? In order to better understand nontraditional stores’ impact on the cost of food, ERS analysts evaluate food price differences between nontraditional and traditional stores at the national and market level 

using 2004-06 Nielsen Homescan data. Findings show that nontraditional retailers 

offer lower prices than traditional stores even after controlling for brand and package 

size. Comparisons of identical items, at the Universal Product Code (UPC) level, 

show an expenditure-weighted average price discount of 7.5 percent, with differences 

ranging from 3 to 28 percent lower in nontraditional stores than in traditional stores. 

Nontraditional stores in metro areas where such stores have a higher-than-average 

market share have smaller and less frequent price discounts than those in areas where 

such stores have a lower market share. 

Keywords: retail food prices, price variation, Nielsen Homescan, supercenter, club 

warehouse store, dollar store, traditional food retailers, nontraditional food retailers

Coauthors Catherine Barker and Paula Dutko were ERS interns when this report was 

prepared.

Acknowledgments

The authors thank Christopher Davis, ERS/USDA; Geoffrey Pofahl, Arizona State 

University; and Charles Courtemanche, University of North Carolina-Greensboro, for 

their helpful suggestions and comments. Thanks also to Priscilla Smith (editor) and 

Susan DeGeorge (designer) for their excellent assistance.

Ephraim Leibtag, eleibtag@ers.usda.gov

Catherine Barker

Paula Dutko
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Contents

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Organization of Data and Product Comparison Groupings . . . . . . . . . . 3

National Price Differences Between Nontraditional 

and Traditional Stores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Broad Aggregation-Level Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Brand and Product Module-Specific Comparisons . . . . . . . . . . . . . . . . . . . 6

Same Individual Package Size Comparisons . . . . . . . . . . . . . . . . . . . . . . . 7

UPC-Level Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Some Unexpected Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Market-Level Analysis Between Nontraditional 

and Traditional Stores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Price Differences in Markets With High 

Nontraditional Retailer Market Share . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Price Differences in Markets With Medium 

Nontraditional Retailer Market Share . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Price Differences in Markets With Low 

Nontraditional Retailer Market Share . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Cross-Market Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Conclusions and Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
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Summary

What Is the Issue?

Food prices vary across different parts of the United States. One factor that 

may lead to differences in food prices is the types of stores in a given market 

or neighborhood. Nontraditional discount food retailers, including supercenters, mass merchandisers, wholesale club stores, and dollar stores, have 

gained a substantial portion of the retail food market over the past 15 years. 

Previous studies have shown that prices for some items are lower in nontraditional than in traditional stores. But those earlier studies were generally 

limited in the number of items compared, the detail level of comparison, and 

the geographic areas studied. This study compares prices for a wide range 

of foods at a finer level of detail than earlier studies, at both the national and 

geographic market levels, in order to quantify the difference in food prices 

across store formats.

What Are the Major Findings?

•	Nationally, 86 percent of broad food groups had lower prices in nontraditional stores than in traditional stores. Even after controlling for differences 

in brand and package size by comparing identical Universal Product Code 

(UPC) items, prices were lower for 82 percent of UPC products.

•	Expenditure-weighted average prices were 7.5 percent lower in nontraditional stores at the UPC level, with prices for individual food items ranging 

from 3 to 28 percent lower in nontraditional stores. This indicates that 

factors other than brand and package size, such as differences in store costs 

and pricing strategies, play a role in explaining price differences between 

store types. 

•	At the market level, price differences between traditional and nontraditional stores were smaller and less frequent in areas with a high market 

share of nontraditional retailers. Atlanta and San Antonio—which are 

cities with a high share of nontraditional retailers—had the fewest products 

with significantly lower prices in nontraditional stores and an average price 

discount of just 5.3 percent, while cities with a low share of nontraditional 

retailers (Philadelphia and the New York City metro area) had an average 

price discount of 11.5 percent.

•	Smaller price differences between store types may be due to some higher 

priced traditional retailers’ exiting markets in which nontraditional retailers 

gain a large market share, with the remaining traditional retailers’ lowering 

their prices in response to increased competition. Such an outcome would 

result in a decrease in average prices in traditional stores. Alternatively, the 

smaller differences could be due to nontraditional retailers’ raising prices 

once they have a large enough market share to do so. 

Results for specific food groups and items include:

•	Meat items had the largest average price discounts in nontraditional stores, 

while grain-based products had the greatest variation in price differences 

between nontraditional and traditional stores. 
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•	All canned products were priced significantly lower in nontraditional 

stores, even at the UPC level. 

•	Private-label (store-brand) items had larger price differences between store 

types than did national-brand goods. 

How Was the Study Conducted?

The study analyzed 2004-06 Nielsen Homescan data, which includes all foodat-home purchases for about 40,000 households in 52 markets and selected 

nonmetropolitan areas. (Nielsen defines “nonmetropolitan areas” as areas 

outside the 52 largest metropolitan areas in the United States). The study 

compared price differences at the national and market level for four broad 

food groups—dairy, meat, fruits and vegetables, and grains. These food 

groups were divided into four levels of aggregation for each year with the 

most commonly purchased products compared at each aggregation level:

•	broad food categories, such as low-fat milk

•	products of the same brand or a narrower subgroup of the broad categories 

(for items that do not have national brands, such as most fresh fruit)

•	products with the same individual package sizes, such as 6-ounce 

containers of yogurt

•	products with the same UPC

A linear regression model was used to control for other factors that may 

influence the average price for a given food item or group of foods, such 

as region and calendar quarter when purchased. When estimating food 

price differences between store types at the market level, we focused on 

six markets: Philadelphia and New York (with low shares of nontraditional 

retailers); Chicago and Baltimore/Washington (with medium shares of 

nontraditional retailers); and Atlanta and San Antonio (with high shares of 

nontraditional retailers). 
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Introduction

With retailers such as Wal-Mart, Costco, Target, and Family Dollar 

increasing their food offerings and share of consumer food expenditures 

over the past 15 years, the retail market for food has changed. In 2003, 

Wal-Mart passed Kroger as the largest supermarket chain in the United 

States and has come to dominate many major U.S. markets, particularly in 

the South and Midwest. By the end of 2005, Wal-Mart was within 5 miles 

of 46 percent of American homes and within 15 miles of 88 percent (Basker, 

2007). However, Wal-Mart supercenter growth is not the only catalyst for 

change in the retail environment. In 2008, 50 percent of the U.S. population shopped at warehouse club stores, including Costco, Sam’s Club, and 

BJ’s (NielsenWire, 2009). In addition, dollar stores have increased food 

offerings and have grown in popularity at a faster rate than other retail store 

types over the past decade (Maestri and Baertlein, 2009). From 2001 to 2008 

the number of dollar stores grew by 52 percent, and by 2008, 64 percent of 

U.S. households shopped at dollar stores in that year (NielsenWire, 2009). 

Why have consumers chosen to shift a large share of their food-purchase 

dollars to nontraditional retailers? It is often claimed that consumers shift 

food purchases to these stores due to lower prices. However, research that 

compares a wide range of food products both nationally and in a number of 

U.S. markets has not been conducted previously due to data constraints. With 

better data now available, we can quantify exactly how much lower prices 

are in these stores and determine whether the differences in prices between 

store formats vary across markets.

In this study, we improve on the previous literature by comparing prices not 

only for a wider range of food categories, but also by comparing specific 

individual food items within each category. We quantify the extent to which 

food prices are lower in nontraditional stores at both the national and market 

level by addressing two questions related to price variation between nontraditional and traditional food stores:

1. Are national food prices statistically significantly lower in nontraditional 

stores compared with traditional stores even after controlling for specific 

product characteristics at the universal product code (UPC) level?

2. Do market-level price differences vary with the relative market share of 

nontraditional retailers in a given market?

Addressing these two questions provides insight into how much consumers 

could save depending on where they choose to shop and what retail markets 

that currently have low nontraditional market share may experience in the 

future if nontraditional market share were to increase. 

Nontraditional retailers usually sell a wider range of nonfood items than do 

traditional supermarkets, so their growth in market share means traditional 

supermarkets face a new type of competition. What effect does this have 

on prices and sales? Basker and Noel (2009) found that Wal-Mart’s price 

advantage over competitors for 24 grocery products was approximately 10 

percent, while Capps and Griffin (1998) found that Wal-Mart was responsible for about a 21-percent reduction in sales at a conventional grocery store 
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1Quality differences exist due to differences in the underlying ingredients and 

materials used by different companies 

when producing food products. In our 

analysis, we control for quality differences by comparing items produced by 

the same manufacturer as well as by 

comparing identical UPCs.

chain in rural areas surrounding Dallas, suggesting that traditional stores face 

considerable competition from nontraditional stores. Carpenter and Moore 

(2006) found that people shop at a particular retail format due to a combination of factors such as price, inventory cost, and travel cost. Nontraditional 

stores may appeal particularly to large, low-income households—income, 

education, and household composition and size were all found to be significant variables affecting what format of retail store consumers chose. Finally, 

Kinsey and Senauer (1996) found that the average grocery retailer had operating costs equal to 21.8 percent of sales, while Wal-Mart’s operating costs 

were only 17.5 percent of sales. However, even if nontraditional stores have 

lower aggregate prices because they have lower operating costs, they may 

provide fewer services and varieties of products, so a more comprehensive 

comparison is warranted.

For some items in some markets, previous studies have shown that prices in 

nontraditional stores are lower than prices in traditional stores. For example, 

when comparing dairy products of similar package sizes, Leibtag (2006) 

found that prices were 5 to 25 percent lower in nontraditional retailers than 

traditional retailers from 1998 through 2003. When looking at Wal-Mart 

in particular and taking into account demographics and market conditions, 

Volpe and Lavoie (2007) found that prices were 6 to 7 percent lower for 

national-brand goods and 3 to 8 percent lower for store-brand goods in 2004 

based on data for the New England region. 

One concern with many previous studies on food price differences is that 

the lower prices observed in aggregated comparisons of broad food groups 

across stores were due to differences in the quality1 or package size of 

specific products sold in nontraditional outlets. Very large differences in 

price found in aggregate data are often confounded by this fact. In addition, 

for consumers shopping on a tight budget, the mere existence of lower perunit prices does not necessarily imply affordability since the potential savings 

comes at the cost of having to buy larger package sizes or products of lower 

quality. In order to address this concern, we compare product price differences across four levels of aggregation (broad food group, more specific 

food group, same package size, and same UPC) to differentiate between the 

effects on price of quality and package size characteristics as opposed to 

other store-based factors including operating costs and purchasing power. 

Our comparisons quantify how much of a difference remains in prices after 

controlling for the fact that not all stores sell the same items in every 

food category. 

Another area of improvement found in our research is the focus on multiple 

markets with varying degrees of nontraditional market share. Researchers 

have previously compared prices in only one or two market areas, without 

accounting for different market conditions across the United States. We 

extend our national-level analysis to look at six specific markets to estimate 

the extent to which prices are lower in nontraditional stores in a given market 

and whether this difference depends on nontraditional retailer market share.
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2A subset of Homescan households also 

record non-UPC-coded food purchases 

using a codebook.

5For more information on the QFAHPD, 

see Todd et al. (2010).

4We calculate separate prices for 

purchases from drug and convenience 

stores since those stores offer a different combination of products and services as compared with both traditional 

and nontraditional stores. Drug and 

convenience store prices are available 

from the authors upon request (contact 

the authors at eleibtag@ers.usda.gov).

3Einav et al., (2008) conduct a validation study of the Homescan data by 

comparing estimates from Homescan 

to store-based data. They found that 

quantities purchased are reported 

more accurately in Homescan than are 

prices. However, many of the price 

differences are a function of the way 

Nielsen imputes prices: when available, 

Nielsen uses store-level prices instead 

of the actual price paid by the household. Overall, the fraction of variance 

explained by the documented recording errors is in line with other research 

datasets in which cross-validation 

studies have been conducted. See Einav 

et al., (2008) for additional information 

on the description, accuracy, and usage 

of Homescan data.

Organization of Data and Product 

Comparison Groupings

We use 2004-06 Nielsen Homescan data in our analysis. Homescan data is 

household-based scanner data in which households scan the UPC of each 

item after every food shopping trip.2 For each of the years, the data sample 

includes about 40,000 households in 52 markets and selected nonmetro areas. 

In addition to describing each purchase’s product details, such as brand name 

and flavor, the dataset includes household demographic information, such as 

income level and marital status. One advantage of using Homescan data rather 

than store-based scanner data is that store-based scanner data are not available 

for certain retail store outlets, meaning that we would not be able to include 

all nontraditional store formats in our analysis using only store-based scanner 

data. Also, store-based scanner data include purchases for all intended uses, 

whereas household-based data are more representative of actual household 

purchases, which is useful for making consumer-based estimates.3

The first aim of our analysis is to test whether nontraditional stores offer 

significantly lower prices than do traditional stores for a variety of foods. 

Nontraditional stores are defined as mass merchandisers, such as Target; 

supercenters, such as Wal-Mart Supercenter; wholesale club stores, such as 

Costco; and dollar stores, such as Dollar Tree and Family Dollar. Traditional 

stores include all traditional grocery stores, such as supermarkets, combination food/drug stores, and military commissaries, that have a majority of their 

sales in food products.4

We compare product prices at four levels of aggregation in order to determine how price differences between store types vary as the comparison group 

narrows (see table 1 for a list of all of the food categories). The most frequently 

purchased items within each aggregation level are presented in this study in 

order to have a sufficient sample size for each step in the analysis.

First aggregation level 

Our first, and broadest aggregation level includes prices for foods in 22 of 

the 52 Quarterly Food-at-Home Price Database (QFAHPD) groups, groups 

that were constructed based on the 2005 Dietary Guidelines.5 The 22 categories all fall under dairy, meat, fruit and vegetable, or grain food groups, and 

represent just under half of all food-at-home purchases nationally. We chose 

these 22 food groups for our analysis in order to have well-defined products 

for our disaggregated comparisons detailed below. 

Second aggregation level 

The second level of aggregation compares more narrowly defined food 

categories within each of the broader food groups. We use two criteria 

when comparing prices for this aggregation—brand name and product 

module. Product modules are the 600+ food categories that Nielsen uses 

to organize the various foods reported purchased in the Homescan data. 

For example, frozen pizza, lunchmeat, and shredded cheese are all product 

modules. We compared prices by store type for the same branded item and/

or product module, choosing the most frequently purchased brand in each 
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6If a given food group was too large and 

varied to identify one UPC that was the 

most frequently purchased, the sample 

was narrowed by product module or 

brand first. If a UPC product did not 

exist for 1 year, then the second or third 

most popular UPC product was chosen. For example, frozen whole-grain 

purchases increased by 72 percent from 

2004 to 2005 and by 56 percent from 

2005 to 2006. Due to this large growth, 

the most commonly bought UPC product 

in 2006 did not exist in 2004. In order to 

have all 3 years of comparison, the third 

most commonly purchased UPC in 2006 

was chosen, which also happens to be 

the most commonly purchased UPC in 

2004 and 2005.

of the 22 broad categories for 2006. Then, we narrowed the sample by the 

most frequently purchased product module, provided that the sample was 

still large enough for comparison across store types. Since some items do 

not have brands, the broad food group categories for these products were 

narrowed only by product module. For example, most fresh fruits, like many 

other non-UPC (random-weight) products, do not have national brands, so 

price comparisons were made for apples and bananas, the most frequently 

purchased product modules in the fresh fruits category, instead. These prices 

provide a more narrow comparison of price differences between nontraditional and traditional stores by controlling for product-specific characteristics 

not accounted for in the more broad food group comparisons. We compare 

both private-label (store-brand) products and nationally branded products 

across store types since the pricing behavior of these products may differ 

given the difference in pricing power that retailers have for store-brand 

vs. nationally branded products. This helps to determine whether privately 

labeled items have bigger, smaller, or similar price differences between store 

types than do nationally branded products. 

Third aggregation level 

The third aggregation level controls for the individual package size of the 

product purchased by comparing prices for items with the same unit weight. 

Controlling for weight is important because some nontraditional stores, such 

as warehouse club stores, have lower unit prices since they often sell larger 

sized items. For example, traditional stores may carry both half-gallon and 

gallon containers of milk, but nontraditional stores may only sell gallon 

containers. Some products, however, cannot be compared by weight since 

they are not sold in fixed-weight packages (random-weight products). Fresh 

produce, delicatessen meat, and seafood items are assigned a final price at 

the store based on the total purchased package weight. Nontraditional stores 

may have bigger packages, but weight price comparisons for these products 

do not tell much about price differences between store types since customers, 

not stores, decide how much of the random-weighted variable to purchase. 

We therefore only compare random-weight products by brand and/or product 

module as described above.

Fourth aggregation level 

The final and most specific aggregation level for comparison is at the UPC 

level. UPCs are used to identify all nonrandom-weight items purchased. The 

UPC products chosen are based on the frequency of purchases in the 2006 

sample.6 For some products, the UPC product was of the same brand, product 

module, and/or size as in the second and third aggregation levels of comparison. However, there were also cases in which a certain brand was the most 

commonly purchased brand in the broadest sample, but the most commonly 

purchased UPC was of a different brand. The UPC level of comparison is 

unique since exact products are not expected to have as large a price difference between store types given the fact that these are identical items sold at 

all stores. If there are still significantly lower prices in nontraditional stores 

at the UPC level, then other factors, in addition to brand and package size 

differences, must account for nontraditional stores’ lower prices.
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7The total-dollars-paid amount is a final 

transaction price taking into account 

loyalty-card member discounts, sales 

specials, and coupons.

8Additional regression results available 

from the authors upon request (contact 

the authors at eleibtag@ers.usda.gov).

It should be noted that the UPC comparison alone is not necessarily a sufficient measure of price differences between store types since each UPC 

product accounts for such a small share of overall food-at-home expenditures, but in conjunction with the information at the other aggregation levels, 

the UPC-level analysis can shed light on price differences between store 

types. In general, there is a tradeoff between the specificity of food products 

compared and the ability to find the exact food product for comparison in 

multiple markets across stores, so by including results for four aggregation 

levels, our aim is to provide a robust presentation of price differences. 

We use a linear regression model to control for factors other than the store 

from which the item was purchased that may influence the average price for a 

given food item or food group. For all four aggregation comparison levels for 

each product, we control for region, time, household income, size and race. 

Using the Homescan data, we calculate the average food price by unit weight 

by dividing the total dollars paid7 by the total quantity (in ounces) purchased 

during a given shopping trip. To control for other differences across space, 

time, and demographics, we use dummy variables for the four U.S. regions, 

households’ race, and for the quarter the product was purchased. Since 

Homescan does not collect exact household income, but instead has 19 

income levels ranging from below $5,000 to above $200,000 per year, we 

use the midpoint of each income range as our household-income variable (in 

thousands of dollars). The household-size variable in the Homescan data is 

continuous, ranging from one-person households to nine-person households. 

The model is then as follows, 

Pijt = F(Sjt, Rit, Iit, Hit, Ait, Tt

) i = household, j= store, t = date

with unit prices (P), store type (S), region (R), household income (I), household size (H), race (A), and quarter purchased (T) for each item for a given 

household from a specific store on a specific day. 

For the dummy variables used in these regressions, the defaults are traditional store type, East for region, White for race, and 1st quarter for quarter 

purchased. Almost all of the independent variables are significant for a 

majority of the regressions, with higher prices being associated with the 

East, higher incomes, and smaller households. An example of a regression 

at the UPC aggregation level for yogurt is presented in table 2.8 As in all of 

the national-level regressions in this study, we control for region, time, and 

demographics in order to estimate how much of a difference in prices can be 

explained by the store format chosen. In this yogurt UPC example, we find 

that prices are 12 percent lower in nontraditional stores as compared with 

traditional stores and over 30 percent higher in drug and convenience stores. 

Other statistically significant determinants of price are income (+), household 

size (-), Asian (+), and 4th quarter (+).
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9All of the UPC-level comparisons are 

the same package size across all stores, 

except if they are random-weight 

products. If package sizes are not the 

same for the other comparison levels, it 

means that in some stores, the products 

are sold in multipacks.

10Select-nutrient vegetables are vegetables other than dark green, orange, 

and starchy varieties that are a source 

of eight selected nutrients as listed in 

USDA/Health and Human Services’ 

Dietary Guidelines. Examples of 

vegetables included in this category 

are avocados and tomatoes; the eight 

nutrients are: potassium; vitamin E; 

iron; vitamin A; magnesium; vitamin 

C; dietary fiber; and calcium.

National Price Differences Between 

Nontraditional and Traditional Stores 

We calculate price differences between nontraditional stores and traditional 

stores and the share of each product’s expenditures in nontraditional stores 

for every product aggregation level and present the results in four tables, one 

for each major food group— dairy, meat, fruit and vegetable, and grains (see 

tables 3, 4, 5, and 6). For all levels of aggregation, the price differences were 

highly significant with many significant at the 1-percent level and almost all 

at the 5-percent level. Ninety-eight percent of products across all levels of 

aggregation show equal or higher average package sizes in nontraditional 

stores as compared with traditional stores, highlighting the importance of 

making comparisons at more specific aggregation levels.9

Broad Aggregation-Level Comparisons

The broad food category comparisons in dairy, meat, fruit, vegetable, and 

grain food groups are comprehensive in that many products are included in 

each group, but may overstate actual price differences because the composition of items sold at each store within each broad category may vary quite a 

bit. Therefore the comparisons at this level provide a benchmark with which 

to compare to the other aggregation levels. Not surprisingly, almost all products broadly aggregated have lower prices in nontraditional stores. For all 3 

years, 21 out of 22 products have significantly lower prices in nontraditional 

stores. Prices range from 69 percent lower in nontraditional stores (whole 

grain flour in 2006) to 6 percent more expensive in nontraditional stores 

(fresh/frozen select-nutrient vegetables10 in 2006). 

On average, meat products at the broad aggregation level tend to have larger 

overall discounts in nontraditional stores than do dairy, fruit and vegetable, 

and grain products. An expenditure-weighted average price difference 

between store types shows that meat products’ prices are about 12 percent 

lower in nontraditional stores, while for dairy as well as produce products the 

average expenditure-weighted price difference is 11 percent. For grain products, consumers save about 6 percent in nontraditional stores. 

Brand and Product Module-Specific Comparisons

The second level of aggregation for our price comparisons, by brand name 

and product module, controls for differences in the characteristics of products 

within a broad category. We compared some items only by brand since the 

sample would be too small otherwise or the sample already was comprised of 

just one product module (for example, yogurt), while items that are usually 

not branded, such as fruits and vegetables, were compared at just the productmodule level. Comparing prices of products with the same product module 

may provide a more accurate depiction of price differences by store type 

since some nontraditional retailers offer a different mix of products than do 

traditional stores. On average for all 3 years, about 82 percent of products 

show significantly lower prices in nontraditional stores as compared with 

traditional stores when comparing more specific products. Within each of 

the four major food groups, we find that 80 percent of dairy products show 

significantly lower prices with as much as 15 percent lower prices found 
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11 There are only four meat products 

compared at this aggregation level, 

as one of the five most commonly 

purchased meat product categories is a 

random-weight product.

in nontraditional stores. For grain products, about 78 percent of products 

have significantly lower prices in nontraditional stores and price discounts 

range from 4 percent to 67 percent. Just as we saw with the broad group 

comparisons, grain products at the brand and product module level have the 

biggest range in price differences as compared with the other food groups. 

About five-sixths of fruit and vegetable products of the same brand and/or 

product module show significantly lower prices in nontraditional stores, 

and discounts range from 3 percent lower prices for Tropicana juices to 25 

percent lower prices for store-brand canned pineapple. 

The comparisons for meat products show that about 80 percent of meat categories have significantly lower prices in nontraditional stores for all 3 years. 

Of the products that showed significantly lower prices, the range in price 

differences was from 13 to 47 percent. The main exception to the general 

findings for meat products was that the national-brand (Oscar Mayer) bacon 

had statistically significant higher prices in nontraditional stores for 2 of the 

3 years. This result highlights the differences that can exist between different 

levels of aggregation since the broad comparison level for this category, as 

well as some of the more specific comparisons made within this category, 

showed significantly lower prices in nontraditional stores. 

Same Individual-Package-Size Comparisons

When we compare prices of fixed-weight products with the same volume 

weight, we find that about 92 percent of products with the same weight show 

significantly lower prices in nontraditional stores compared with traditional 

stores. When controlling for unit weight, 93 percent of dairy products have 

significantly lower prices in nontraditional stores with prices ranging from no 

price difference to 13 percent lower in nontraditional stores. All 4 meat products11 show significantly lower prices in nontraditional stores, with a range 

from 5 percent to 32 percent lower prices in nontraditional stores. Similar to 

the meat category, fruits and vegetables had four products compared at the 

weight aggregation level, and prices were significantly lower in nontraditional stores for all of the products in 2005 and 2006. For 2004, only the halfgallon size of the national-brand (Tropicana) fruit juice showed higher prices 

in nontraditional stores, yet insignificantly so. The range in price discounts 

varies from 2 to 23 percent lower prices in nontraditional stores. Finally, all 

grain products have significantly lower prices in nontraditional stores at this 

comparison level, and prices range from 1 percent to 58 percent lower in 

nontraditional stores.

UPC-Level Comparisons

The final set of national level comparisons is for identical UPC-level items. 

Comparing products with identical UPCs controls for all possible productspecific differences between store types and shows how big of a role size 

and brand differences play in explaining price variation across stores, when 

compared to the results presented above. About 82 percent of UPC-specific 

products have lower prices in nontraditional stores as compared with traditional stores. The expenditure-weighted average price discount for all 3 years 

was about 7.5 percent, with average discounts of 5 percent in 2006, 8 percent 

in 2005, and 9 percent in 2004.
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12However, it appears that controlling for the individual package size of 

products does not fully explain price 

differences between store types since 

nearly 93 percent of these items have 

significantly lower prices in nontraditional stores.

Looking at items within each of the four major food groups, we find that all 

but one UPC grain product have significantly lower prices in nontraditional 

stores, with discounts ranging from 3 to 28 percent, while 80 percent of UPC 

meat and dairy products show significantly lower prices in nontraditional 

stores and 78 percent of fruit and vegetables have significantly lower prices 

in nontraditional stores.

Looking across all four levels of price comparisons, the following general 

findings should be noted: 

1. Comparing results across the four major food groups, we find that meat 

products tend to have the largest price discounts in nontraditional stores 

overall, while grains have the largest range of price differences. 

2. Canned items show significantly lower prices in nontraditional stores, 

which could be due to nontraditional stores supplying more of these 

items relative to other foods, procuring them at lower costs, or because 

nontraditional store customers have more elastic demand for canned food 

products, or some combination thereof. 

3. When the level of comparison narrows in specificity, fewer products 

show significantly lower prices in nontraditional stores. Since the number 

of items with significantly lower prices in nontraditional stores falls as 

the level of specificity increases, it is evident that characteristic differences between specific food items within a broad category are partially 

responsible for the price differences observed across store types.12

4. At the UPC level, more than half of the products are still significantly 

lower priced in nontraditional stores for all 3 years with a range from 3 to 

28 percent lower prices. This means that differences in quality and size 

of products are not the only factors that drive price differences between 

nontraditional and traditional stores.

Some Unexpected Results

There are a few unexpected results and interesting observations from these 

national-level price comparisons. As the products narrow in specificity, we 

expect to see smaller price differentials between store types and a consistent 

pattern of lower prices, higher prices, or no price differences between store 

types. However, only about half of the 22 categories show declining price 

differences in all three of the more specific aggregation-level comparisons. 

In the case of yogurt, price difference between store types increases when 

controlling for brand and volume. These unexpected results could be due to a 

variety of factors. First, a large number of products at the brand comparison 

level show bigger price differences than at the broad level, which may mean 

that the brand type has a significant role in price differences between store 

types. Second, many other products that do not follow the expected trend are 

UPC-level products. Since a specific UPC is such a small share of an overall 

category and price differences can vary quite a bit between UPC products, 

having contrary results at the UPC level is not too surprising. By presenting 

price differences at four aggregation levels in this study, we mitigate the 

effects from comparing prices with too broad or too narrow of a sample. 
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Another unexpected result is that for some products, one aggregation level 

shows significantly lower prices in nontraditional stores, yet another aggregation level shows significantly higher prices in nontraditional stores. The UPC 

comparison for low-fat cheese has significantly higher average prices in nontraditional stores even though the broader categories show significantly lower 

prices in nontraditional stores, implying some very large differences for storebrand, low-fat cheese products in contrast to the national-brand differences.
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13Distinguishing between these two 

possibilities requires additional analysis 

beyond this study’s scope.

14The only variables excluded from the 

market-level regression models were 

the region dummy variables, since it is 

unnecessary to control for region at the 

market level.

Market-Level Analysis Between 

Nontraditional and Traditional Stores

Nationally, nontraditional stores have lower prices than traditional stores 

for a clear majority of products in dairy, meat, fruit and vegetable, and grain 

categories, even when controlling for the brand, size, and exact UPC of the 

products. However, analysis of price differences on a national level does 

not show the actual price differences between store types that consumers 

face within a specific market. Therefore, we now examine price differences 

between nontraditional and traditional stores at the market level in order to 

determine if market-level results differ from the national results and to see if 

there is a discernable pattern based on nontraditional retailer market share in 

a given market. 

We focus on six U.S. markets with varying levels of nontraditional market 

share (see table 7), ranging from under 10 percent in New York to 30 percent 

in Atlanta, to determine whether the price differences between nontraditional and traditional stores are smaller in areas with high nontraditional 

retail market share as compared with markets with low nontraditional retail 

market share. Smaller differences might be observed because traditional 

stores that survive the original entry and expansion of nontraditional stores 

in a given market remain competitive by lowering relative prices in response 

to the increased competition, thereby lowering overall average prices. 

Alternatively, the smaller differences may be due to nontraditional retailers 

raising prices once they have large enough market share to do so, thereby 

raising overall average prices.13

We calculated average prices for each of the six markets using the same 

method described above, but included more broad categories for price comparisons at the market level than at the national level. The additional broad categories at the market comparison level are eggs, nuts, fresh fish, canned fish, fresh/

frozen orange vegetables, canned orange vegetables, canned dark greens, fresh/

frozen starchy vegetables, canned starchy vegetables, and regular-fat yogurt. 

We included more broad categories for comparison at the market level because 

narrowing the aggregation levels for comparison sometimes leaves the sample 

size too small to test in a given category at the market level. One broad category, frozen whole grains, was removed from the market-level analysis due to 

insufficient sample size. In total, we have 31 broad categories in all four food 

groups for the market-level comparisons.

Broad categories’ unit price differences between nontraditional and traditional 

stores were estimated using the same linear model described above.14 We 

also calculated price differences for products grouped at the brand aggregation level for each market. Unfortunately, the brand aggregation level was the 

narrowest level of comparison possible. The sample sizes were too thin and 

varied across markets to do a UPC-level comparison. The brands selected 

were the most commonly purchased brands within each broad category 

for all six markets in 2006. For 19 categories, the store brand was the most 

commonly purchased brand and for 10 categories, a national brand was the 

most commonly purchased brand. Two categories, fresh fruit and fresh selectnutrient vegetables (see footnote 10 for definition), did not have a brand 

constituting more than 5 percent of the categories’ expenditure share since 
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these products are usually random-weight products that are not branded. 

Therefore, the broad sample was narrowed by product module rather than 

brand. Bananas were the most commonly purchased type of fruit in 2006, 

and tomatoes were the most commonly purchased type of fresh select 

nutrient vegetable. Table 8 lists the broad categories and the brands used in 

the market-level price analysis, tables 9 and 10 summarize the expenditureweighted average price differences for each market at the broad and brand 

levels of aggregation, respectively, and tables 11-16 show the price difference results at the broad and brand aggregation levels for each market.

Price Differences in Markets With High Nontraditional 

Retailer Market Share

In Atlanta, about 67 percent of products showed significantly lower prices 

in nontraditional stores, with price discounts ranging from 1 to 74 percent at 

the broad level (table 11). Dark green vegetables (2005) are the only product 

that showed significantly higher prices in nontraditional stores, and about 

one-third of products had no price difference between store types. Fruits 

and vegetables had lower prices in nontraditional stores most frequently. 

For example, in 2006, about 73 percent of fruit and vegetables, 66 percent 

of meat/protein products, 60 percent of grains, and 33 percent of dairy 

products showed significantly lower prices in nontraditional stores. A clear 

majority of canned products, 83 percent, showed significantly lower prices 

in nontraditional stores. Even though two-thirds of national-brand items had 

significantly lower prices as compared with 53 percent for store-brand items, 

store-brand goods’ price discounts were 2 percent larger on average for all 3 

years. These results suggest that even though national-brand products are less 

expensive in nontraditional stores more often than store-brand goods, storebrand goods have slightly larger price discounts in nontraditional stores.

In San Antonio, only about 54 percent of food categories showed significantly lower prices in nontraditional stores, the lowest percentage of items 

with lower prices in nontraditional stores in any of our six markets. Price 

discounts ranged from 4 to 73 percent, with about 4 percent of products 

showing significantly higher prices in nontraditional stores and 42 percent 

with no price difference between store types. Just as in Atlanta, a wholegrain product had the biggest price discount in nontraditional stores and dark 

green vegetables had the biggest price markup in nontraditional stores. Meat 

products had price discounts most often (table 12). For example, in 2006, 78 

percent of meat/protein products, 56 percent of dairy products, 45 percent of 

fruit and vegetable products, and 20 percent of grain products showed significantly lower prices in nontraditional stores. Sixty-three percent of canned 

products in 2006 and 2005 and 50 percent in 2004 showed significantly lower 

prices in nontraditional stores. 

Fifty-three percent of store-brand goods and 78 percent of national-brand 

goods had significantly lower prices for at least 2 of the 3 years. Store brand 

goods’ average price discount, however, was 19.2 percent while for nationalbrand products, it was 17.7 percent. National-brand goods had significantly 

lower prices in nontraditional stores more often than store-brand goods, but 

store-brand goods had a greater average price discount in nontraditional 

stores than did national-brand goods. 
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Taking the average of Atlanta and San Antonio, 62 percent of products at 

the broad aggregation level have lower prices in nontraditional stores for 

all 3 years, which is the lowest percentage of all three market categories. 

Also, the average price discount in nontraditional stores is much smaller in 

these two markets than the other markets. At the brand and product module 

level, the average of price discounts in Atlanta and San Antonio reveal that 

price discounts are smaller by about half as compared to other markets and 

discussed below.

Price Differences in Markets With Medium 

Nontraditional Retailer Market Share

In the Baltimore/Washington market, about 90 percent of products showed 

significantly lower prices in nontraditional stores, the highest percentage of 

products with lower prices in nontraditional stores, with the remaining 10 

percent having no price difference between store types. Price discounts ranged 

from 5 to 76 percent (table 13). In 2006, all meat/protein and grain products, 

67 percent of dairy, and 91 percent of fruit and vegetables showed significantly 

lower prices in nontraditional stores. Seventy-five percent of canned products 

had significantly lower prices in nontraditional stores in 2006, while 88 percent 

had significantly lower prices in 2004 and 2005. From 2004 to 2005, nationalbrand goods had bigger price discounts in nontraditional stores than storebrand goods, and there were more national-brand goods than store-brand goods 

with price discounts in nontraditional stores. In 2006, however, there were 

more store-brand goods with price discounts and these price discounts were 

larger on average than national-brand goods’ price discounts. 

In Chicago, about 71 percent of products showed significantly lower prices 

in nontraditional stores, with price discounts ranging from 4 to 64 percent, 

while 3 percent of products showed significantly higher prices and the 

rest had no difference in prices between store types (table 14). Just as in 

Baltimore/Washington, canned poultry and whole-grain flour products had 

the largest price discount in nontraditional stores. For 2006, 78 percent 

of meat products, 83 percent of dairy products, 73 percent of fruit and 

vegetables, and 60 percent of grains showed significantly lower prices in 

nontraditional stores. Seventy-five percent of canned products on average 

from 2004 to 2006 showed significantly lower prices in nontraditional stores. 

National-brand products had significantly lower prices in nontraditional 

stores 76 percent of the time, while store-brand goods had significantly lower 

prices in nontraditional stores only 46 percent of the time. The average price 

discount for store-brand goods was 22 percent, while for national-brand 

goods, the average price discount was 29 percent. These results suggest that 

national-brand goods not only have price discounts in nontraditional stores 

more often, but also by bigger amounts than do store-brand goods. At the 

broad aggregation level, Baltimore/Washington and Chicago had the highest 

average price discounts in 2004 and 2006. However, at the product module 

level in 2004 and 2005, the average price discounts and average percent of 

products with lower prices in nontraditional stores in Baltimore/Washington, 

and Chicago are in between the averages for markets with low and high 

nontraditional retailer market share.
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15Product categories that showed insignificant price differences between store 

types counted as a 0-percent difference 

in price.

Price Differences in Markets With Low Nontraditional 

Retailer Market Share

In Philadelphia, about 71 percent of products had lower prices in nontraditional stores, with price discounts ranging from 6 to 57 percent, while 

the remaining products had no price difference between store types at the 

broad aggregation level (table 15). In 2006, 89 percent of meats/proteins, 83 

percent of dairy, 60 percent of grains, and 73 percent of fruit and vegetables 

had significantly lower prices in nontraditional stores. In 2004 and 2006, 75 

percent of canned products showed significantly lower prices in nontraditional stores, while 88 percent showed significantly lower prices in 2005. On 

average, national-brand goods had price discounts in nontraditional stores 

more often than store-brand goods, while store-brand goods had bigger price 

discounts on average than national-brand goods, except in 2005.

Finally, in New York, about 81 percent of products showed significantly 

lower prices in nontraditional stores, ranging from 7 to 55 percent at the 

broad aggregation level. Only 2 percent of products had higher prices in 

nontraditional stores, and 17 percent had no price difference between store 

types (table 16). In 2006, 100 percent of dairy products, 91 percent of fruit 

and vegetable products, 67 percent of meat/protein products, and 60 percent 

of grain products showed significantly lower prices in nontraditional stores. 

Canned products had significantly lower prices in nontraditional stores 88 

percent of the time in 2006, 75 percent in 2005, and 100 percent in 2004. 

Store-brand goods had bigger price discounts in nontraditional stores than 

national-brand goods, but only by about 1 percent. Also, 83 percent of 

national-brand goods had price discounts in nontraditional stores, while only 

55 percent of store-brand goods showed price discounts in nontraditional 

stores. At the brand and product module level, the average price discounts in 

New York are larger than any other market. Philadelphia and New York, on 

average, had the largest price discounts in 2005 and 77 percent of products 

with lower prices in nontraditional stores for all 3 years.

Cross-Market Comparison

As predicted, there are significantly lower prices in nontraditional stores as 

compared with traditional stores in all six major markets for a majority of 

products. The price differences between store types for each product category 

were adjusted by expenditure weights per market in order to estimate the 

aggregate average price differences for each market. Table 9 summarizes the 

expenditure-weighted price differences15 and the percent of products with 

significantly lower prices in nontraditional stores for each market from 2004 

to 2006 for the broad aggregation level. Table 10 shows the same percentages at the brand and product module level. In support of our hypothesis, 

markets with high nontraditional retailer market share, Atlanta and San 

Antonio, showed the smallest and least frequent price discounts in nontraditional stores, even when controlling for brand and package size. The average 

price discount at the broad aggregation level for these markets ranged from 

5.7 percent to 6.4 percent, and at the brand and product module level, the 

price discount range was from 4.7 percent to 5.7 percent.

The markets with the highest nontraditional retailer market share, Atlanta and 

San Antonio, had the fewest products at the broad aggregation level, with 
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significantly lower prices in nontraditional stores and smaller price differences between store types than other markets. Even when controlling for the 

brand and type of product, these markets had the smallest price discounts in 

comparison to the other two market categories for all 3 years. We expected 

the markets with low nontraditional market share, Philadelphia and New 

York, to have the biggest price discounts in nontraditional stores, but this 

was only true in 2005 for the broad aggregation level and for 2004 and 2005 

at the brand and product module level. The results for medium nontraditional 

retailer market share are very similar to those for low nontraditional retailer 

market share. By looking at the averages for each of the three categories 

(high, medium, and low nontraditional retailer market share), a general 

pattern supporting our hypothesis is discernable.

Markets with high nontraditional retail market share had the smallest price 

differences between store types by a significant amount at the broad aggregation level. At the brand and product module level, the price discounts are half 

of the price discounts shown in the other markets. Medium nontraditional 

retailer markets had larger average price differences than did low nontraditional retailer markets at the broad aggregation level in 2004 and 2006, while 

in 2005, both market types had the same average price difference between store 

types (11.1 percent). Also, from 2004 to 2006, markets with high nontraditional retail market share had the fewest number of products with significantly 

lower prices in nontraditional stores. The difference in the amount of products 

having lower prices in nontraditional stores between low and medium nontraditional retail market share areas is about 20 percentage points. 

These results show that areas with high nontraditional retailer market share 

have fewer products with lower prices in nontraditional stores and smaller 

price differences between store types than areas with medium and low 

nontraditional retailer market share. This cross-sectional price convergence 

could be due to nontraditional stores raising prices or traditional stores 

lowering prices, or some combination of the two. Nontraditional stores 

could be placing greater pressure on other stores to lower prices as they gain 

market share or smaller stores could be closing down or just not opening in 

areas with many nontraditional retailers due to the high level of competition. 

It is important to note, however, that price differences between store types for 

markets with medium nontraditional retailer market share are similar to the 

price differences shown in markets with low nontraditional retailer market 

share. This may indicate that there is only strong price competition between 

nontraditional stores and traditional stores once nontraditional stores have 

gained a substantial share of the retail food market. The smaller price gap 

shows that there are higher levels of price competition between store types as 

there is greater nontraditional retailer presence. 

Overall, the market results generally support the national results in that for a 

majority of products, prices are lower in nontraditional stores than traditional 

stores, even when controlling for brand and package size. The results at the 

market level that do not follow this pattern may be due to unobservable or 

unmeasured factors that affect price differences between store types at the 

market level, such as the cost of living in each market. For all of the markets 

other than New York, meat/protein products had the most items with significantly lower prices in nontraditional stores. Meat products at the national 
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comparison level showed the biggest price discounts in nontraditional stores. 

In congruence with the results at the national level, canned products had 

significantly lower prices in nontraditional stores more often than any other 

type of product for each market. 
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Conclusions and Implications

Our analysis shows that even after controlling for brand, weight, region, 

quarter purchased, household size, income, and race, food prices are still 

significantly lower in nontraditional stores, and those differences persist even 

at the UPC level. Although the price gap between store types narrows for 

almost all products as the aggregation level narrows in specificity, the gap is 

still substantial. National average prices are significantly lower in nontraditional stores for 86 percent of the products at the broadest level of comparison on average, while at the UPC comparison level, 82 percent of products 

show significantly lower prices in nontraditional stores with an average 

price discount of 7.5 percent. One factor that may explain price differences 

between store types is the lower procurement costs faced by nontraditional 

stores as they often buy large quantities of items in bulk and provide a 

smaller assortment of goods, as compared to traditional stores. Also, the 

marginal operating costs of a nontraditional store may be less than that of a 

traditional store due to fewer services offered within a given store. 

On a national level, our results show that meat products had the biggest 

expenditure-weighted price discounts in nontraditional stores and grains 

had the biggest range in price differences between store types. Interestingly, 

our analysis also suggests that there is not that great of a difference in price 

discounts between store types for low-fat versus regular-fat items, but a 

majority of whole-grain items have bigger price differences between store 

types than do refined-grain products. Store-brand goods have significantly 

lower prices in nontraditional stores as often as national-brand goods, but 

store-brand goods have bigger price differences between store types than do 

national-brand goods. 

At the market level, areas with high nontraditional retailer market share, 

Atlanta and San Antonio, showed the smallest expenditure-weighted price 

differences between store types and the smallest percentage of products 

with lower prices in nontraditional stores. The average price difference 

within these markets was about 6 percentage points lower and the percent of 

products with lower prices in nontraditional stores was about 7 percentage 

points lower than that for markets with low nontraditional retailer market 

share. However, there is only about a 2-percentage-point difference between 

medium nontraditional retail markets and low nontraditional retail markets in 

terms of the percent of products with lower prices in nontraditional stores. 

Future analysis could explore five issues as extensions to this analysis. 

First, why are prices significantly lower in nontraditional stores? We find 

that brand, product characteristics, and package size partially explain price 

variation between nontraditional and traditional stores, but there are other 

factors as well, since the majority of UPC products are also significantly 

lower priced in nontraditional stores. Focusing on startup and operating costs 

between store types and calculating a variable for the distance from point 

of production to stores may help explain some price variation. Secondly, 

since some items are discounted more than others in nontraditional stores, 

analyzing consumers’ food-purchasing behavior and the nutritional quality of 

purchased items as consumers’ knowledge of and choices based on perceived 

“good nutrition” relates to food prices would be a worthwhile extension of 
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this analysis. Third, high-quality and premium items were not included in the 

study as they are not the most frequently purchased items nor are they largely 

represented in nontraditional stores. However, further studies may want to 

examine price differences between high-quality products of various comparison levels of specificity. 

Extensions to this analysis also could focus on price differences between 

nontraditional retailers and specific types of traditional retailers, such as 

large chains. Since the biggest supermarket-chain retailers share some of 

the competitive advantages that nontraditional retailers have, price differences might be smaller between those store types. Along those same lines, 

researching drugstore and convenience-store prices could shed light on how 

much people who shop mostly at drugstores and convenience stores pay for 

the same goods bought by their counterparts who shop at nontraditional or 

traditional food retailers. Lastly, food-price trends over time between store 

types could be examined. Many products showed price convergence from 

2004 to 2006, and the market-level analysis showed that areas with higher 

levels of nontraditional retailer market share also have smaller price differences between store types. Understanding which retailer type, nontraditional 

or traditional, is responsible for this price convergence will be important 

when analysts weigh the costs and benefits of nontraditional retail growth in 

the long run. 

Our work highlights the importance of what and how price comparisons are 

made. The fact that differences in food prices are robust to both productspecific detail and market-level analysis implies that the additional affordability of food bought at nontraditional retailers should be considered when 

analyzing issues related to food access and food choices. 
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Table 1

Food groups included in national-level price analysis

Type of 

product Broad food group

Specific food group

 (product module/brand) Same weight Same UPC

Dairy Low-fat milk Store brand Gallon Lactaid-100 Non-Fat Milk Vitamin A&D 

(half-gallon)

Regular-fat milk Store brand Gallon Carnation Vitamin D Milk 

Low-fat cheese Breakstone’s Store brand 24 oz Kraft Free Shredded Cheddar (8oz)

Regular-fat cheese Borden brand Borden 12 oz Kraft Singles American Single-Sliced

Low-fat yogurt Yoplait brand Yoplait 6 oz Yoplait Low-Fat Original Fruit Yogurt 

Strawberry (6 oz)

Meat Fresh/frozen low-fat meat Oscar Mayer brand Oscar Mayer 9 oz Oscar Mayer Turkey Breast (9 oz)

All fresh/frozen regular-fat 

meat

Oscar Mayer Bacon (1)

Oscar Mayer Sliced 

Lunchmeat (2)

n/a Oscar Mayer Salami (16 oz)

Canned regular-fat meat Armour brand 12 oz Hormel Spam C (12 oz)

Fresh/frozen poultry Perdue 

Random-weight chicken

n/a Random-weight chicken breast

Canned poultry Store brand 12.5 oz Valley Fresh Chicken Chunk White (5 

oz)

Fruit and 

vegetable 

Fresh/frozen fruit Bananas (1)

Apples (2)

n/a Random-weight conventionally grown 

bananas

Canned fruit Store brand canned 

pineapple

Canned pineapple 

20 oz

Dole Pineapple Chunk in Juice (20 oz)

Fruit juice Tropicana brand Tropicana halfgallonTropicana Orange Juice (half-gallon)

Fresh/frozen dark green 

vegetables

Frozen broccoli (1)

Dole lettuce (2)

n/a Random-weight broccoli

Fresh/frozen other 

vegetables

Nonrandom-weighted 

tomatoes (1)

cauliflower (2)

n/a Fresh grape tomatoes

Canned other vegetables Store brand canned tomatoes Canned tomatoes 

14.5 oz

Rotel Diced Tomatoes (10 oz)

Grain Packaged whole grains General Mills Cheerios Whole-grain cereal 

15 oz

General Mills Whole-Grain Cheerios 

Cereal (15 oz)

Whole-grain flour/mixes Bob’s Red Mill All-Purpose 

Flour

5 oz King Arthur All-Purpose Flour

Frozen whole grains Rhodes Frozen Biscuits/Rolls/

Muffins (1)

Frozen biscuits/rolls/

muffins (2)

n/a Weight Watchers Choco-Choco Chip 

Muffin

Packaged refined grains Pepperidge Farm Bread (1)

Barilla Pasta (2)

n/a Kellogg Special-K Strawberry Cereal

Refined grain flour/mixes Store brand all-purpose white 

wheat flour

All-purpose white 

wheat flour 5oz

Gold Medal White Wheat All-Purpose 

Flour (5 oz)

Frozen refined grains Pillsbury Grands Biscuits (1)

Frozen New York Bread (2)

n/a Pillsbury Regular Pie Crust

n/a = not available.

oz = ounce(s).

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service selections from the ERS Quarterly Food-at-Home Price Database (QFAHPD) and Nielsen Homescan.
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Table 2

Regression results for Yoplait Original Low-Fat Strawberry 

Yogurt 6 oz1, 2006 

Dependent variable:

Price per UPC product Parameter estimate Standard error t-statistic

Independent variables:

Store format

 Traditional stores Default store type

 Nontraditional stores -0.011 0.001 -15.92 

 Drug/convenience stores 0.029 0.008 3.56

Region

 East Default region

 Central -0.002 0.002 -1.07 

 South -0.002 0.002 -1.32 

 West 0.003 0.002 1.82

Income 0.000 0.000 5.93

Household size -0.001 0.000 -3.39

Race

 White Default race

 Black 0.000 0.001 0.06

 Asian 0.005 0.002 2.28

 Other 0.001 0.002 0.38

 Hispanic 0.002 0.002 -0.67 

Quarter purchased

 First Default quarter

 Second 0.000 0.001 0.08

 Third 0.001 0.001 1.14 

 Fourth 0.002 0.001 2.33

Constant 0.096 0.005 18.61

Note: Observations: 5910; R-squared: 0.1168; mean of the dependent variable: 0.092 (9.2 cents/ounce).

1As measured by Universal Product Code (UPC); oz = ounce(s). 

Source: USDA, Economic Research Service estimates using Nielsen Homescan.
20

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 3

Dairy price differences between nontraditional and traditional stores, 2004-06

Expenditure share

Product and level Price difference in nontraditional stores of nontraditional

of aggregation (I-IV) 2004 2005 2006 stores, 2006 

 

-------------------------------------------Percent-------------------------------------------

Low-fat milk

I. All -12.2 -6.1 -6.8 22.3

II. Store brand -12.5 -7.1 -6.7 27

III. Gallon -8.7 -4.9 -2 36

IV. Lactaid-100 Non-Fat Milk 

 Vit A&D (half-gallon) -11.3 -9.2 -12.7 15.4

 

Regular-fat milk

I. All -4.9 -2.4 -2.4 22.7

II. Store Brand -2.2 -2.1 Negative, 27.5

 insignificant

III. Gallon -3.4 -1.3 Negative, 25.6

 insignificant

IV. CarnationVitamin D Milk -6.6 -7.3 -6.3 22

 

Low-fat cheese

I. All -5.7 -3.8 -6.3 18.1

II. Breakstone’s -7.3 -8.3 -15.3 31.2

III. Store brand 24 oz -4.7 -3.9 -4 22.7

IV. Kraft Free Shredded Cheddar (16 oz) 3.2 11.7 9.8 27

 

Regular-fat cheese

I. All -17.7 -16.3 -17.4 25

II. Borden -4.9 Positive, Positive, 35.1

 insignificant insignificant

III. Borden 12 oz -8.1 -5.4 -6.4 16.4

IV. Kraft Singles American Cheese -11.6 -11.8 -6.9 17.6

 

Low-fat yogurt

I. All -9.0 -7.1 -8.2 21.3

II. Yoplait -13 -13.6 -12.2 27.2

III. Yoplait 6 oz -12.6 -13.4 -12.2 26.6

IV. Yoplait Low-Fat Original 

 Fruit Yogurt Strawberry (6 oz) -14.3 -13.9 -12 21.2

oz = ounce(s).

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homescan.
21

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 4

Meat price differences between nontraditional and traditional stores, 2004-06

Expenditure share

Product and level Price difference in nontraditional stores of nontraditional

of aggregation (I-IV) 2004 2005 2006 stores, 2006 

 

-------------------------------------------Percent-------------------------------------------

Fresh/frozen low-fat meat

I. All -17.4 -16.9 -14.8 28.6

II. Oscar Mayer -16.7 -13.1 -15.6 36.2

III. Oscar Mayer 9 oz -5.1 -5.7 -7.9 32.3

IV. Oscar Mayer Turkey Breast (9 oz) -7 -6.1 -5.9 27.6

 

Fresh/frozen regular-fat meat 

I. All -13.0 -10.5 -9.4 -13.0

II. Oscar Mayer Bacon Negative, 

 insignificant 16 13.7 25.1

III. Oscar Mayer Sliced Lunchmeat -16.5 -8.9 -6.8 26.6

IV. Oscar Mayer Salami Regular -9.5 -3.6 Negative, 31.5

 insignificant 

 

Canned regular-fat meat

I. All -20.8 -21.6 -20.8 37.6

II. Armour -19.6 -31.7 -28.1 42.6

III. 12 oz canned meat -15.6 -14.1 -10.7 38.4

IV. Hormel Spam (12 oz) -10.9 -10.7 -9.6 29.6

 

Fresh/frozen poultry

I. All -12.0 -11.1 -7.6 22.1

II. Perdue -26.4 -22.8 -10.1 13.5

III. Random-weight chicken -13.5 -13 -3.4 11.2

IV. Random-weight chicken breast -6.5 Negative, Positive, 9.8

 insignificant insignificant

 

Canned poultry

II. All -34.2 -34.3 -31.6 62.7

II. Store brand -45.2 -47.1 -37.2 84.5

III. 12.5 oz canned poultry -32.1 -29.3 -27.9 89.4

IV. Valley Fresh Chicken 

 Chunk White (5 oz) -17.3 -15.7 -16.7 23.3

oz = ounce(s).

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homescan.
22

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 5

Fruit and vegetable price differences between nontraditional and traditional stores, 2004-06

Expenditure share

Product and level Price difference in nontraditional stores of nontraditional

of aggregation (I-IV) 2004 2005 2006 stores, 2006 

 

-------------------------------------------Percent-------------------------------------------

Fresh/frozen fruit

I. All -9.7 -10.5 -15.5 38.1

II. Bananas -6.8 -7.9 -8.8 11.8

III. Apples 4.9 4.2 7.5 33.6

IV. Random-weight bananas -11.2 -12.6 -13.3 11.8

 

Canned fruit

I. All -18.2 -13.6 -12.7 25.1

II. Store brand canned pineapple -25 -19.6 -17 20.8

III. Canned pineapple 20 oz -16.9 -14.4 -11.5 22.4

IV. Dole Pineapple Chunk in Juice (20 oz) -14.3 -17.1 -11.5 12.8

 

Fruit juice

I. All -12.6 -14.3 -13.2 24.7

II. Tropicana 1.7 -3.3 -8.4 25.3

III. Tropicana (half-gallon) Positive, -2.1 -4.6 19.1

 insignificant

IV. Tropicana Orange Juice (half-gallon) -5.4 -2.6 -4.4 10.1

 

Fresh/frozen dark greens

I. All -10.6 -11.4 -13.9 24.6

II. Frozen broccoli -14.6 -14.9 -15.6 23.2

III. Dole lettuce -22.8 -19.2 -18.1 41.8

IV. Random-weight broccoli Negative, Negative, Negative, 3.6

insignificant insignificant insignificant

 

Fresh/frozen select nutrients

I. All Positive, Positive, 6.0 22.7

 insignificant insignificant

II. Nonrandom- weight tomatoes Positive, Negative, -6.4 29

 insignificant insignificant

III. Cauliflower Negative, 4.2 3.9 11.2

 insignificant

IV. Fresh grape tomatoes -12.4 -16.7 Positive, 17.5

 insignificant

 

Canned select nutrients

I. All -17.2 -15.7 -16.6 22.7

II. Store brand canned tomatoes -8.3 -9.8 -9.6 23.7

III. Canned tomatoes (14.5 oz) -18.1 -19.4 -17.9 22.5

IV. Rotel Diced Tomatoes (10 oz) -14.3 -11.5 -10.7 32.4

oz = ounce(s).

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homescan.
23

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 6

Grain price differences between nontraditional and traditional stores, 2004-06

Expenditure share

Product and level Price difference in nontraditional stores of nontraditional

of aggregation (I-IV) 2004 2005 2006 stores, 2006 

 

-------------------------------------------Percent-------------------------------------------

Packaged whole grains

I. All -10.1 -6.6 -5.2 26.7

II. General Mills Cheerios 

 (all package sizes) -19 -18.2 -20.3 31.6

III. Whole-grain cereal 15 oz -6.2 -2.5 -1.2 20.4

IV. General Mills Cheerios Cereal 15 oz -8.5 -6.1 -3.6 18.7

 

Whole-grain flour/mixes

I. All -46.7 -55.6 -68.8 9.2

II. Bob’s Red Mill All-Purpose Flour 10.1 19.6 -67.2 9.7

III. Whole-grain flour/mixes 5 oz -13.3 -16.4 -17.1 16.1

IV. King Arthur All-Purpose Flour -22.9 -19.1 -28 18.5

 

Frozen whole grains

I. All -67.6 -11.2 -25.4 13.3

II. Rhodes frozen biscuits/rolls/muffins -15.3 -26 -8.7 6

III. Frozen biscuits/rolls/muffins -57.9 -22.3 -48.9 13.7

IV. Weight Watchers Choco-Choco 

 Chip Muffins NA -19.1 -20.6 5.4

 

Packaged refined grains 

I. All -6.2 -4.3 -4.5 23.1

II. Peppridge Farm Bread -4 Negative, 2.6 19.3

 insignificant

III. Barilla Pasta -9.5 -8.5 -5.1 26.9

IV. Kellog Special-K Strawberry cereal -3.5 -3.1 -3.8 26

 

Refined-grain flour/mixes 

I. All -5.4 -11.7 -18.1 24.1

II. Store brand all-purpose 

 white wheat flour -21.2 -20.3 -19.2 20.3

III. All-purpose white wheat flour 5 oz -10.5 -10.3 -8.1 18.8

IV. Gold Medal White Wheat -7.9 -6.8 Positive, 15.2 

 All-Purpose Flour 5 oz insignificant

 

Frozen/ready-to-cook refined grains 

I. All -9.7 -8.7 -8.5 21.6

II. Pillsbury Grands Biscuits -11.3 -10.6 -10.7 16.7

III. Frozen New York Bread -9.4 -7.8 -6 22.3

IV. Pillsbury Regular Pie Crust -10.1 -12.7 -11.3 15.5

oz = ounce(s).

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homescan.
24

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 7

Nontraditional food expenditures as share of total food expenditures

Market type and location 2004 2005 2006 

Percent

High nontraditional retailer share

Atlanta 27.6 29.4 30.8

San Antonio 20.9 24.1 24.8

Medium nontraditional retailer share

Baltimore/Washington 18.7 20.5 20.0

Chicago 13.3 15.2 15.5

Low nontraditional retailer share

Philadelphia 11.7 13.0 14.3

New York 9.4 10.7 12.3

Source: USDA, Economic Research Service estimates using Nielsen Homescan.

Table 8

Food groups in market-level price analysis

Product type Broad food group Specific food group (brand)

Dairy Low-fat milk

Regular-fat milk

Low-fat cheese

Regular-fat cheese

Low-fat yogurt

Regular-fat yogurt

Store brand

Store brand

Store brand

Store brand

Yoplait brand

Dannon brand

Meat/protein Fresh/frozen low-fat meat

Fresh/frozen regular-fat meat

Canned regular-fat meat

Fresh/frozen poultry

Canned poultry

Fresh/frozen fish

Canned fish

Raw and processed nuts

Eggs

Oscar Mayer brand

Oscar Mayer brand

Libby’s brand

Perdue brand

Store brand

Store brand

Bumble Bee brand

Store brand

Store brand

Fruit and vegetable Fresh/frozen fruit

Canned fruit

Fruit juice

Fresh/frozen dark green vegetables

Canned dark green vegetables

Fresh/frozen orange vegetables

Canned orange vegetables

Fresh/frozen starchy vegetables

Fresh/frozen other vegetables

Canned other vegetables

Bananas

Store brand

Store brand

Store brand

Store brand

Store brand

Libby’s brand

Store brand

Tomatoes

Store brand

Grain Packaged whole grains

Whole-grain flour/mixes

Packaged refined grains 

Refined grain flour/mixes 

Frozen refined grains 

Store brand

King Arthur brand

Store brand

Store brand

Pillsbury brand

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service selections from QFAHPD (see definition, table 1) and Nielsen 

Homescan.
25

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 9

Expenditure-weighted average price differences of products with significantly lower prices in nontraditional stores at the broad aggregation level

Products with lower

Market type Average price difference prices in nontraditional

and location 2004 2005 2006 stores, 2006 

 

-------------------------------------------Percent-------------------------------------------

High nontraditional retailer share

Atlanta -5.9 -7.1 -5.9 68.8

San Antonio -6.3 -5.7 -5.5 54.8

 Average -6.1 -6.4 -5.7 61.8

 

Medium nontraditional retailer share 

Baltimore / Washington -17.3 -15.1 -15.7 89.2

Chicago -13.2 -7.1 -7.8 74.2

 Average -15.3 -11.1 -11.8 81.7

 

Low nontraditional retailer share

Philadelphia -11.9 -8.9 -9.6 70.9

New York -17.6 -13.2 -13.2 82.8

 Average -14.8 -11.1 -11.4 76.9

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homescan.

Table 10

Expenditure-weighted average price differences of products with significantly lower prices in nontraditional stores at the brand aggregation level

Products with lower

Market type Average price difference prices in nontraditional

and location 2004 2005 2006 stores, 2006 

 

-------------------------------------------Percent-------------------------------------------

High nontraditional retailer share

Atlanta -7.8 -6.5 -6.4 56.5

San Antonio -3.7 -2.9 -4.4 52.7

 Average -5.7 -4.7 -5.4 54.6

 

Medium nontraditional retailer share 

Baltimore / Washington -8.1 -7.8 -14.4 67.7

Chicago -10.8 -8.2 -12.7 52.1

 Average -9.5 -8.0 -13.5 59.9

 

Low nontraditional retailer share

Philadelphia -6.9 -8.1 -10.5 59.1

New York -15.0 -13.5 -15.0 64.5

 Average -11.0 -10.8 -12.8 61.8

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homescan.
26

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 11

Atlanta price differences between nontraditional and traditional stores

Expenditure share

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006 

 

-----------------------------------------------Percent-------------------------------------------------

Fresh/frozen fruit -10.3 -11.0 Positive, 27.8

insignificant

 Banana Positive, Positive, Positive, 23.7

insignificant insignificant insignificant

Canned fruit -1.1 -16.3 -17.9 27.3

 Store brand -12.2 -14.6 -19.4 22.4

Fruit juice -7.3 -11.2 -16.2 30.3

 Store brand Positive, Positive, Negative, 21.6

insignificant insignificant insignificant

Dark green vegetables -20.3 19.2 -21.3 24.1

 Store brand Positive, 32.8 -32.2 13.3

insignificant

Canned dark greens -6.6 -11.2 Negative, 24

insignificant

 Store brand -16 Negative, Negative, 36.2

insignificant insignificant

Fresh/frozen orange vegetables -7.2 -8.6 Positive, 19.6

insignificant

 Store brand -31 -36.3 -34.4 1.3

Canned orange vegetables Positive, -12.4 -6.1 19.1

insignificant

 Libby’s brand -20.2 -17.7 -13.5 21.2

Fresh/frozen starchy vegetables -8.5 -14.8 -12.1 23.9

 Store brand Positive, Positive, Positive, 11.6

insignificant insignificant insignificant

Canned starchy vegetables Positive, -6.7 -10.8 22.5

insignificant

 Store brand -10.1 -7.9 -11.1 15.7

Fresh/frozen select-nutrient vegetables -16.1 -14.7 -5.4 21

 Tomato -7.1 -13.1 -6.7 15.2

Canned select-nutrient vegetables -6.3 -12.6 -14.9 22.9

 Store brand -9.8 -14.5 -14.2 20.1

Packaged whole grains Negative, Positive, Positive, 29.9

insignificant insignificant insignificant

 Store brand Positive, Positive, Negative, 10.5

 insignificant insignificant insignificant

Whole-grain flour/mixes -49.9 -61.1 -73.7 11.7

 King Arthur brand NA -18.4 Negative, 25.8

insignificant

Packaged refined grains Negative, Negative, Negative, 27.5

insignificant insignificant insignificant

 Store brand -19.4 -14.7 -9.8 21.8

continued
27

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 11

Atlanta price differences between nontraditional and traditional stores, continued

Expenditure share

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent--------------------------------------------------

Refined grains flour/mixes Positive, -13.3 -23.0 25.3

insignificant

 Store brand -26.8 Negative, Negative, 24.7

insignificant insignificant

Frozen refined grains -11.4 -11.9 -11.8 25.7

 Pillsbury brand -18.9 -13.8 -5.8 21.7

Low-fat milk Negative, Negative, -9.4 25.8

insignificant insignificant

 Store brand Negative, Negative, -9 23.5

insignificant insignificant

Low-fat cheese -17.2 Negative, Positive, 28.7

insignificant insignificant

 Store brand Negative, Negative, Negative, 37.6

insignificant insignificant insignificant

Low-fat yogurt Negative, -7.4 Negative, 30.6

insignificant insignificant

 Yoplait brand -8.1 -15.9 -13.5 38

Regular-fat milk Negative, Positive, Positive, 29.5

insignificant insignificant insignificant

 Store brand Positive, Positive, Negative, 25.3

insignificant insignificant insignificant

Regular-fat cheese -13.0 -12.8 -15.3 27.5

 Store brand -14.7 -13.8 -11.4 17.9

Regular-fat yogurt -11.3 Negative, Positive, 22.5

insignificant insignificant

 Dannon brand Negative, Positive, 12.8 21.5

insignificant insignificant

Low-fat fresh/frozen meat -9.6 -9.7 -12.4 29

 Oscar Mayer brand -6.5 -6.4 -5.7 37.2

Regular-fat fresh/frozen meat Negative, -4.5 Negative, 24.8

insignificant insignificant

 Oscar Mayer brand Negative, Positive, 21.5 27.3

insignificant insignificant

Canned regular-fat meat Negative, -14.7 -21.5 31.2

insignificant

 Libby’s brand Negative, -20.3 -23.3 34.8

insignificant

Fresh/frozen poultry Negative, --6.5 Negative, 19.8

insignificant insignificant

 Perdue brand Negative, Positive, -19.2 20.7

insignificant insignificant

Canned poultry -27.5 -21.4 -18.1 63.9

 Store brand -26.2 -34.7 -28.4 87.5

continued
28

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Fresh/frozen fish -11.2 -9.2 -7.7 29.3

 Store brand -14.8 -19 -11.7 20.6

Canned fish -12.6 -9.7 -13.2 33.3

 Bumble Bee brand -22.3 Negative, -23.6 37.4

insignificant

Raw and processed nuts -14.3 -6.2 -9.6 40.8

 Store brand -11.6 Negative, -12.1 41

insignificant

Eggs -7.2 Positive, Positive, 29.4

insignificant insignificant

 Store brand -7.2 Positive, 8.3 1.4

insignificant

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homesca

Table 11

Atlanta price differences between nontraditional and traditional stores, continued

Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006 

 

-----------------------------------------------Percent-------------------------------------------------
29

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 12

San Antonio price differences between nontraditional and traditional stores

Expenditure share

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent-------------------------------------------------

Fresh/frozen fruit Negative, Negative, Negative, 22.2

insignificant insignificant insignificant

 Banana Positive, Negative, -4.1 17.5

insignificant insignificant

Canned Fruit -10.7 -11.5 -13.5 31.5

 Store brand -12.5 -10.5 -13.6 25.9

Fruit juice -15.4 -18.5 -14.1 27.2

 Store brand Negative, -16.5 -8.1 29

insignificant

Dark green vegetables 34.2 37.6 31.6 25.7

 Store brand Positive, 30.4 -17.5 7.4

insignificant

Canned dark greens Negative, Negative, Negative, 25.8

insignificant insignificant insignificant

 Store brand -9.9 Negative, Positive, 22.8

insignificant insignificant

Fresh/frozen Negative, Negative, Negative, 15.3

orange vegetables insignificant insignificant insignificant

 Store brand -35.5 -38.1 -38.5 0.9

Canned orange Positive, -6.5 -8.3 23

vegetables insignificant

 Libby’s brand -8.1 -9.8 Negative, 29.4

insignificant

Fresh/frozen Negative, -7.9 -7.5 19.2

starchy vegetables insignificant

 Store brand 17.6 Negative, 10.1 6.9

insignificant

Canned starchy vegetables Positive, Negative, Negative, 22.4

insignificant insignificant insignificant

 Store brand Negative, Negative, Negative, 15.2

insignificant insignificant insignificant

Fresh/frozen select- Negative, Negative, Positive, 19.7

nutrient vegetables insignificant insignificant insignificant

 Tomato -7.4 Negative, Negative, 12.1

insignificant insignificant

Canned select-nutrient vegetables -9.7 -6.6 -10.4 25.9

 Store brand Negative, -8.2 -19.3 22.6

 insignificant

Packaged whole grains -4.9 Positive, Positive, 27

insignificant insignificant

 Store brand 18.4 32 15.4 8.2

continued
30

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Whole-grain flour/mixes -38.3 -54.4 -72.4 12.7

 King Arthur Brand -15.7 -34.3 -30.9 22.6

Packaged refined grains 5.4 Positive, 4.3 24.5

insignificant

 Store brand Positive, Positive, 7.7 19.3

insignificant insignificant

Refined grains flour/mixes Positive, -20.3 Negative, 25.2

insignificant insignificant

 Store brand Negative, Negative, Negative, 16.3

insignificant insignificant insignificant

Frozen refined grains Positive, Negative, Positive, 20.7

insignificant insignificant insignificant

 Pillsbury brand -7.5 -11.8 -9.9 20.5

Low-fat milk Negative, Negative, Positive, 26.3

insignificant insignificant insignificant

 Store brand Negative, Negative, Negative, 21.9

insignificant insignificant insignificant

Low-fat cheese -23.3 -26.0 -15.0 19.3

 Store brand -24.6 -17.1 -15.9 27.5

Low-fat yogurt -8.0 Negative, -7.8 25.5

insignificant

 Yoplait brand -6.2 -5.7 -4.3 27.6

Regular-fat milk -11.3 Negative, Positive, 23

insignificant insignificant

 Store brand Positive, Positive, Positive, 17

insignificant insignificant insignificant

Regular-fat cheese -21 -17.4 -20.6 25.8

 Store brand -22.2 -23.2 -25.5 16.9

Regular-fat yogurt -11.3 Negative, -8.5 18.8

insignificant

 Dannon brand Negative, Positive, Positive, 25.9

insignificant insignificant insignificant

Low-fat fresh/frozen meat -14.5 -14.8 -17.9 22.6

 Oscar Mayer brand -13.7 -6.6 -12.7 28.7

Regular-fat fresh/frozen meat -7.1 Negative, Negative, 20.2

insignificant insignificant

 Oscar Mayer brand Positive, Positive, Positive, 30

insignificant insignificant insignificant

Canned regular-fat meat Negative, -10.2 Negative, 34.3

insignificant insignificant

 Libby’s brand -15.4 -20.5 -9.3 25.9

Table 12

San Antonio price differences between nontraditional and traditional stores, continued

Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006 

 

-----------------------------------------------Percent-----------------------------------------------

continued
31

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Fresh/frozen poultry -17.0 -17.7 -9.2 15.8

 Perdue brand NA NA NA NA

Canned poultry -25.7 -20.1 -21.3 59.7

 Store brand -38.7 -36.2 -40.6 81.7

Fresh/frozen fish -7.6 -18.0 -23.9 23.4

 Store brand Negative, -20.9 -31.9 41

insignificant

Canned fish -13.6 -17.0 -23.7 31.2

 Bumble Bee brand -62.6 -53.8 Positive, 0.7

insignificant

Raw and processed nuts -9.7 -9.8 -9.2 43.5

 Store brand -11.5 -15.1 Negative, 52.3

insignificant

Eggs -15.5 -21.7 -13.9 21.4

 Store brand -6.9 -20.8 -13.1 0.6

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homesca

Table 12

San Antonio price differences between nontraditional and traditional stores, continued

Expenditure share

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent-----------------------------------------------
32

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 13

Baltimore/Washington price differences between nontraditional and traditional stores

e Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

------------------------------------------------Percent------------------------------------------------

Fresh/frozen fruit -7.1 -7.6 -9.1 19.4

 Banana -9.2 -6.3 -9 11.2

Canned fruit -18.3 -9.4 -12.5 21.2

 Store brand -18 Negative, -17.4 16.3

insignificant

Fruit juice -21.7 -17.7 -25.7 18.8

 Store brand Negative, Negative, -19.3 22.1

insignificant insignificant

Dark green vegetables Negative, 21.5 69 15.6

insignificant

 Store brand 29.6 32.5 -34.3 4.5

Canned dark greens -12.9 -11.4 Negative, 18.5

insignificant

 Store brand -23.9 -29.2 -23 10.1

Fresh/frozen orange vegetables -17.2 -11.9 -11.4 11.5

 Store brand -48.8 -26.3 -18.6 2.8

Canned orange vegetables -13.9 -17.4 -16.2 17.2

 Libby’s brand -20.3 -20.6 Negative, 23.4

insignificant

Fresh/frozen starchy vegetables -24.2 -11.7 -16.6 13.3

 Store brand Negative, Negative, -7.9 5.7

insignificant insignificant

Canned starchy vegetables -21.7 -15.4 -20.7 19.7

 Store brand -20.6 -15.5 -9.4 13

Fresh/frozen selectnutrient vegetables -12.7 -10.4 -6.2 15

 Tomato -14 -16.3 -15.8 4.9

Canned selectnutrient vegetables -23.5 -26.2 -30.4 17.5

 Store brand -12.6 -14 -18.4 16.7

Packaged whole grains -13.2 -9.3 -5.1 18.6

 Store brand Negative, Positive, 8 8.3

insignificant insignificant

Whole-grain flour/mixes -40.9 -64.5 -76 4.5

 King Arthur brand Negative, -30.3 Negative, 8.3

insignificant insignificant

Packaged refined grains -5.9 -4.5 -7.2 18.8

 Store brand -15.4 -15.1 Negative, 20.8

insignificant

continued
33

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Refined grains flour/mixes -23.1 Negative, -15.4 18.3

insignificant

 Store brand Positive, Negative, Positive, 21.8

insignificant insignificant insignificant

Frozen refined grains -11.7 Negative, -13.6 12.6

insignificant

 Pillsbury Brand -14 Positive, -11 11.9

insignificant

Low-fat milk -24.7 -16.5 -23.8 19

 Store brand Negative, -17.1 -25.2 17.6

insignificant

Low-fat cheese Negative, Positive, Negative, 15

insignificant insignificant insignificant

 Store brand -27.6 -13 -11.4 9.6

Low-fat yogurt -7.8 -7.1 -7.0 15.4

 Yoplait brand -14.3 -7.2 Negative, 28.3

insignificant

Regular-fat milk -12.5 -12.0 -14.1 16.5

 Store brand -9.4 -12.5 -11.8 16.6

Regular-fat cheese -25.0 -21.8 -24.9 19.7

 Store brand -21.3 -19.6 -25.7 13.9

Regular-fat yogurt Negative, -10.1 Negative, 11

insignificant insignificant

 Dannon brand -10.8 -13.7 Negative, 8.5

insignificant

Low-fat fresh/frozen meat -20.5 -27.0 -19.3 21.6

 Oscar Mayer brand -23.6 -29.5 -25.6 25

Regular-fat fresh/frozen meat -22.8 -21.1 -18.0 18.2

 Oscar Mayer brand -36.9 Negative, Negative, 20.1

insignificant insignificant

Canned regular-fat meat -30.4 -30.6 -28.5 36.2

 Libby’s brand -32.3 -30.5 -28.5 40.1

Fresh/frozen poultry -30.4 -29.7 -24.4 12.6

 Perdue brand -40.4 -49.6 -34.4 10.9

Canned poultry -35.2 -41.1 -36.3 53.7

 Store brand -37 -57.6 -37.8 91.7

Fresh/frozen fish -13.0 -14.8 -12.6 18.7

 Store brand Negative, -11.6 -18.6 19.2

insignificant

Table 13

Baltimore/Washington price differences between nontraditional and traditional stores, continued

Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent-----------------------------------------------

continued
34

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Canned fish -17.5 -13.1 -16.6 23.5

 Bumble Bee brand -12.9 Negative, Negative, 24.8

insignificant insignificant

Raw and processed nuts -22.0 -17.0 -18.7 39.7

 Store brand Negative, 11.5 Positive, 55.5

insignificant insignificant

Eggs -20.6 -14.5 -14.0 20.8

 Store brand -24.8 -11 Negative, 4.1

insignificant

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homesca

Table 13

Baltimore/Washington price differences between nontraditional and traditional stores, continued

Expenditure share

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

-----------------------------------------------Percent-----------------------------------------------
35

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 14

Chicago price differences between nontraditional and traditional stores

Expenditure share

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006 

 

-----------------------------------------------Percent-----------------------------------------------

Fresh/frozen fruit Positive, 26.7 -5.2 13.6

insignificant

 Banana Negative, Positive, -10.8 2

insignificant insignificant

Canned fruit -20.3 Negative, Negative, 15.3

insignificant insignificant

 Store brand -11.4 Negative, Negative, 3.3

insignificant insignificant

Fruit juice Negative, -18.2 -14 14.6

insignificant

 Store brand Positive, Negative, Negative, 9.5

insignificant insignificant insignificant

Dark green vegetables -11.0 Negative, Negative, 11.5

insignificant insignificant

 Store brand Positive, 545 Positive, 4.4

insignificant insignificant

Canned dark greens -15.7 Negative, -17.7 10.4

insignificant

 Store brand -47.9 Negative, -28.4 13.5

insignificant

Fresh/frozen orange vegetables -17.9 -10.7 -7.2 7.1

 Store brand Negative, Negative, -20.2 0.2

insignificant insignificant

Canned orange vegetables -9.8 -11.5 -20.8 7.5

 Libby’s brand -25.3 -17.8 -22.3 9.2

Fresh/frozen starchy vegetables -11.6 Negative, Negative, 7.5

insignificant insignificant

 Store brand Positive, Positive, -14.9 2.5

insignificant insignificant

Canned starchy vegetables -18.3 -9.2 -13.3 13.2

 Store brand Negative, -8.9 -6.4 3.3

insignificant

Fresh/frozen selectnutrient vegetables 11.8 16.6 18.0 10.2

 Tomato Negative, Negative, Negative, 0.7

insignificant insignificant insignificant

Canned select-nutrient vegetables -19.6 -18.4 -21.4 8.7

 Store brand Positive, Positive, Positive, 5.4

insignificant insignificant insignificant

Packaged whole grains -13.4 Negative, Negative, 18.3

insignificant insignificant

 Store brand Positive, Positive, -15.5 3.6

insignificant insignificant

continued
36

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

 Whole-grain flour/mixes Negative, -53.0 -63.6 2.1

insignificant

 Store brand NA NA -75.5

Packaged refined grains -15.7 Positive, -4.4 12

insignificant

 Store brand -21.1 -19.6 Negative, 7.6

insignificant

Refined grains flour/mixes -15.7 Negative, -14.3 13.6

insignificant

 Store brand Negative, Negative, Negative, 13.1

insignificant insignificant insignificant

Frozen refined grains -15.2 Negative, Positive, 10.2

insignificant insignificant

 Pillsbury brand -12.2 -14.5 Negative, 5

insignificant

Low-fat milk -40.8 -30.8 -21.0 14.5

 Store brand -34.6 -18.6 -39.5 17.4

Low-fat cheese 21.4 Positive, -20.9 7.6

insignificant

 Store brand Positive, Positive, 21.4 8.8

insignificant insignificant

Low-fat yogurt -11.6 Positive, -7.8 10.8

insignificant

 Yoplait brand -15.1 -7.1 -11.3 9.4

Regular-fat milk -22.5 -35.1 -32.5 13.7

 Store brand -35.6 -28.7 -23.4 18.6

Regular-fat cheese -20.9 -14.4 -15.6 12.9

 Store brand Negative, -7.5 -20.8 3.5

insignificant

Regular-fat yogurt -10.8 Negative, Positive, 13.9

insignificant insignificant

 Dannon brand -19.3 Negative, -11 3.1

insignificant

Low-fat fresh/frozen meat -21.3 -20.4 -12.9 17.4

 Oscar Mayer brand -28.9 -33 -21.2 19.3

Regular-fat fresh/frozen meat -17.7 -12.5 Negative, 12.3

insignificant

 Oscar Mayer brand Negative, Positive, -17.2 9.3

insignificant insignificant

Table 14

Chicago price differences between nontraditional and traditional stores, continued

Expenditure share

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent------------------------------------------------

continued
37

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Canned regular-fat meat -24.5 -18.5 -20.8 22.1

 Libby’s brand -36.6 -91.7 -77.6 49.7

Fresh/frozen poultry -17.5 -27.6 -15.2 9.8

 Perdue brand Negative, Negative, Positive, 0.1

insignificant insignificant insignificant

Canned poultry -51.7 -47.2 -37.4 61.9

 Store brand -36.3 -38.8 -29.7 91.3

Fresh/frozen fish -10.4 Positive, Negative, 18.2

insignificant insignificant

 Store brand Positive, 20.2 -14 17.1

insignificant

Canned fish -25.6 Negative, -17 18.1

insignificant

 Bumble Bee brand -21.3 -25.5 -26 7.4

Raw and processed nuts -21.1 -10.2 -13.7 28.7

 Store brand 15.9 10.8 -21.2 24.5

Eggs -11.3 -11.7 -8.9 12.4

 Store brand -29.6 -19 -10.9 1.2

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homesca

Table 14

Chicago price differences between nontraditional and traditional stores, continued

Expenditure share

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent-----------------------------------------------
38

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 15

Philadelphia price differences between nontraditional and traditional stores

Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent-----------------------------------------------

Fresh/frozen fruit Negative, Negative, -8.7 12.4

insignificant insignificant

 Banana -25.4 -20.7 -24.6 3.8

Canned fruit -17.5 -13.9 -11.3 11.4

 Store brand -16.5 -14.8 Positive, 7

insignificant

Fruit juice -12.1 Positive, -8.5 12.5

insignificant

 Store brand Negative, Positive, -13.1 10

insignificant insignificant

Dark green vegetables -12.2 Positive, Negative, 11.3

insignificant insignificant

 Store brand 300 Positive, -28.4 4.1

insignificant

Canned dark greens -13.1 -11.1 -19.2 7.2

 Store brand -41.4 -27.2 -25.3 11.5

Fresh/frozen orange vegetables -9.6 Negative, Negative, 5.4

insignificant insignificant

 Store brand Negative, Negative, -16.2 0.8

insignificant insignificant

Canned orange vegetables Negative, -14.4 -12.1 9.5

insignificant

 Libby’s brand -21.9 -23 -11.9 10.2

Fresh/frozen starchy vegetables Negative, Positive, -10.9 7

insignificant insignificant

 Store brand Positive, Positive, Positive, 2.8

insignificant insignificant insignificant

Canned starchy vegetables -20.5 -17.4 -13.1 14.1

 Store brand -18.4 -12.3 -14 2.4

Fresh/frozen selectnutrient vegetables -8.2 -6.8 Negative, 7.5

insignificant

 Tomato Negative, -22.78 -18.6 1.3

insignificant

Canned select-nutrient vegetables -13.4 -16.6 -12.3 12.6

 Store brand Positive, Positive, Positive, 8.8

insignificant insignificant insignificant

continued
39

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Packaged whole grains -12.8 -7.8 -5.7 14

 Store brand -23.6 Negative, -15.6 4

insignificant

Whole-grain flour/mixes Positive, -56.8 -49.5 0.9

insignificant

 Store brand -20.9 -47 Negative, 2.4

insignificant

Packaged refined grains Negative, Negative, Negative, 11.7

insignificant insignificant insignificant

 Store brand -20.3 -7.4 -12.1 8.6

Refined grains flour/mixes Positive, Positive, Positive, 13.1

insignificant insignificant insignificant

 Store brand Negative, Positive, Positive, 5.8

insignificant insignificant insignificant

Frozen refined grains -14.6 -11.8 -9.0 8

 Pillsbury brand -26.5 Negative, -9.7 7.5

insignificant

Low-fat milk Negative, -12.4 -9.9 10.1

insignificant

 Store brand Negative, -10.8 -10 5.5

insignificant

Low-fat cheese -26.7 Positive, -24.0 5.9

insignificant

 Store brand -27.2 Negative, -14.4 3.7

insignificant

Low-fat yogurt -11.3 Negative, -5.7 11.2

insignificant

 Yoplait brand Positive, Negative, -8.5 13.8

insignificant insignificant

Regular-fat milk -11.1 -13.1 -23.7 14.4

 Store brand Negative, -14.2 -14.7 11.6

insignificant

Regular-fat cheese 21.6 -19.7 -20.6 11.7

 Store brand -15.2 -14.9 -17.3 8.6

Regular-fat yogurt Negative, Positive, Negative, 11

insignificant insignificant insignificant

 Dannon brand Negative, Positive, -7.74 9.9

insignificant insignificant

Low-fat fresh/frozen meat -17.9 -12.3 -13.0 15.4

 Oscar Mayer brand -19.2 -12.8 -9.2 18.9

Regular-fat fresh/frozen meat -22.6 -15.1 -11.1 11.5

 Oscar Mayer brand -37.1 Negative, Positive, 16.5

insignificant insignificant

Table 15

Philadelphia price differences between nontraditional and traditional stores, continued

Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent-------------------------------------------------

continued
40

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Canned regular-fat meat -15.9 -22.2 -12.5 19.6

 Libby’s brand Negative, -34.8 -32.7 14.7

insignificant

Fresh/frozen poultry -22.8 -20.9 -20.0 9.5

 Perdue brand -17.2 Positive, Positive, 15.3

insignificant insignificant

Canned poultry -30.2 -35.4 -31.5 50.3

 Store brand -48.2 -51.2 -31.8 87.8

Fresh/frozen fish Positive, Positive, Positive, 13.1

insignificant insignificant insignificant

 Store brand Positive, Positive, Positive, 15.4

insignificant insignificant insignificant

Canned fish -18.5 -15.4 -11.2 18.3

 Bumble Bee brand -18.2 -18.1 Negative, 15.2

insignificant

Raw and processed nuts -17.7 -11.8 -5.8 30.7

 Store brand Negative, Positive, -19.4 31.8

insignificant insignificant

Eggs -17.2 -18.7 -12.1 11.7

 Store brand -23.1 -12.9 -4.5 2.6

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service estimates using QFAHPD and Nielsen Homesca

Table 15

Philadelphia price differences between nontraditional and traditional stores, continued

Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent-----------------------------------------------
41

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Table 16

New York price differences between nontraditional and traditional stores

Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent-----------------------------------------------

Fresh/frozen fruit -23.8 -13.3 -12.8 14.5

 Banana -27.8 -19.3 -23.7 1.9

Canned fruit -16.0 -20.8 -15.0 10

 Store brand Negative, -15.1 -22.4 4

insignificant

Fruit juice -15.7 -13.1 -12.4 13.4

 Store brand Negative, Positive, Negative, 11.9

insignificant insignificant insignificant

Dark green vegetables Negative, Negative, -17.6 11.8

insignificant insignificant

 Store brand Positive, Positive, -23.6 3.3

insignificant insignificant

Canned dark greens -40.2 -44.3 -26.3 1.2

 Store brand NA -46 -44.8 1.7

Fresh/frozen orange vegetables -23.8 -13.3 -12.8 5.2

 Store brand Negative, Negative, Negative, 3.4

insignificant insignificant insignificant

Canned orange vegetables -14.0 -20.8 -16.3 5

 Libby’s brand -26.9 -15.2 -16 11.9

Fresh/frozen starchy vegetables -13.4 Positive, -17.0 6.7

insignificant

 Store brand 62 33.5 Positive, 3.8

insignificant

Canned starchy vegetables -12.3 -17.5 -15.5 12.9

 Store brand -15.7 -14.6 -9.1 1.9

Fresh/frozen selectnutrient vegetables 8.0 Negative, 11.1 10.3

insignificant

 Tomato Positive, -38.6 -36.5 0.5

insignificant

Canned select-nutrient vegetables -13.3 Negative, -21.5 8.2

insignificant

 Store brand Positive, 42.4 53 18

insignificant

Packaged whole grains -15.7 -11.9 -11.0 13.2

 Store brand -42.1 -16.7 -17.5 4.9

continued
42

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Whole-grain flour/mixes -54.6 Negative, Negative, 1.8

insignificant insignificant

 Store brand -34.7 -47.2 -34.8 1.4

Packaged refined grains -7.0 Positive, Negative, 9.9

insignificant insignificant

 Store brand -18.5 -14.7 -15.1 10.7

Refined grains flour/mixes Positive, -26.7 -30.3 8.5

insignificant

 Store brand Negative, Negative, Positive, 7.7

insignificant insignificant insignificant

Frozen refined grains -13.4 -19.0 -15.0 4.7

 Pillsbury brand -38.9 -15.4 -17.1 4.7

Low-fat milk -34.1 -30.6 -31.8 10.4

 Store brand -30.1 -28.9 -31.9 14.6

Low-fat cheese Negative, Negative, -22.5 3.5

insignificant insignificant

 Store brand -33.5 -36.7 Negative, 1.4

insignificant

Low-fat yogurt -10.4 -10.7 -11.4 6.2

 Yoplait brand -17.2 -13.8 -14.1 13.7

Regular-fat milk -24.5 -26.0 -20.0 10.3

 Store brand -25.3 -35.6 -38.9 14.6

Regular-fat cheese -24.6 -22.7 -22.1 11.1

 Store brand -16.7 -17 -23.1 6.7

Regular-fat yogurt -24.5 -26.0 -20.0 5.6

 Dannon brand -33.1 -31.2 -28.3 3.5

Low-fat fresh/frozen meat -20.4 -18.3 -13.4 15.9

 Oscar Mayer brand -33.3 -17.6 -17.3 13.2

Regular-fat fresh/frozen meat -18.0 -15.5 -15.4 9.4

 Oscar Mayer brand -31.8 Negative, Negative, 8

insignificant insignificant

Canned regular-fat meat -22.4 -22.1 -33.6 15

 Libby’s brand -25.4 -25.5 -26.8 22.5

Fresh/frozen poultry -23.0 -18.7 -15.5 8.8

 Perdue brand -21 -14.1 18.9 13.3

Table 16

New York price differences between nontraditional and traditional stores, continued

Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006

 

-----------------------------------------------Percent-----------------------------------------------

continued
43

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

Canned poultry -52.4 -60.9 -54.4 56.5

 Store brand 78 Negative, Negative, 84.7

insignificant insignificant

Fresh/frozen fish -14.5 -8.7 Negative, 16.7

insignificant

 Store brand -22.1 -23.3 Negative, 43.5

insignificant

Canned fish -9.0 Positive, Negative, 14.8

insignificant insignificant

 Bumble Bee brand Negative, Negative, Positive, 17.4

insignificant insignificant insignificant

Raw and processed nuts -20.3 -10.6 Negative, 29.9

insignificant

 Store brand Positive, 16.4 -10.8 52.8

insignificant

Eggs -45.6 -34.3 -33.2 13.3

 Store brand -41.2 -34.1 -29.1 7.1

Note: All low-fat products were classified based on the product description codes in Nielsen Homescan.

Source: USDA, Economic Research Service estimates using QFAHPD (see definition, table 1) and Nielsen Homesca

Table 16

New York price differences between nontraditional and traditional stores, continued

Expenditure share 

Price difference in nontraditional stores of nontraditional

Food group category 2004 2005 2006 stores, 2006 

 

-----------------------------------------------Percent-----------------------------------------------
44

How Much Lower Are Prices at Discount Stores? An Examination of Retail Food Prices / ERR-105

Economic Research Service / USDA

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