Aylin Kumcu and Abigail M. Okrent 

Economic

Research

Service

Technical 

Bulletin

Number 1938

May 2014

United States Department of Agriculture

Methodology for the 

Quarterly Food-Away-fromHome Prices Data
Economic Research Service 

www.ers.usda.gov

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on 

the basis of race, color, national origin, age, disability, and, where applicable, sex, marital status, familial 

status, parental status, religion, sexual orientation, genetic information, political beliefs, reprisal, or because 

all or a part of an individual’s income is derived from any public assistance program. (Not all prohibited 

bases apply to all programs.) Persons with disabilities who require alternative means for communication of 

program information (Braille, large print, audiotape, etc.) should contact USDA’s TARGET Center at (202) 

720-2600 (voice and TDD). 

To file a complaint of discrimination write to USDA, Director, Office of Civil Rights, 1400 Independence 

Avenue, S.W., Washington, D.C. 20250-9410 or call (800) 795-3272 (voice) or (202) 720-6382 (TDD). USDA 

is an equal opportunity provider and employer.

United States Department of Agriculture

Access this report online:

www.ers.usda.gov/publications/tb-technical-bulletin/tb-1938.aspx

Download the charts contained in this report:

• Go to the report’s index page www.ers.usda.gov/publications/

 tb-technical-bulletin/tb-1938.aspx

• Click on the bulleted item “Download TB1938.zip”

• Open the chart you want, then save it to your computer

Recommended citation format for this publication:

Kumcu, Aylin and Abigail Okrent. Methodology for the Quarterly Food-Away-from-Home 

Prices Data, TB-1938, U.S. Department of Agriculture, Economic Research Service, May 

2014.

Cover image: Shutterstock.

Use of commercial and trade names does not imply approval or constitute endorsement by USDA. 

The average prices presented in this report were produced by USDA’s Economic Research Service 

using Bureau of Labor Statistics (BLS) Consumer Price Index microdata. These estimates do not 

reflect official U.S. Bureau of Labor Statistics estimates.
Contents

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

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

Sources of FAFH Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

BLS Sample Design and Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Methodology for Calculating Average Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Product Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Sample and Price Adjustments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Average Price Calculation and Standard Errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

FAFH Price Variation across Area and Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Full-Service Restaurants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Limited-Service Restaurants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Vending Machines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Schools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Nonalcoholic Beverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Alcohol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
United States Department of Agriculture

Economic 

Research 

Service

Technical 

Bulletin

Number 1938

May 2014

Abstract

Accurate and detailed prices are a key component to analyze a variety of important 

questions related to consumer behavior. Given the importance of food-away-from-home 

(FAFH) consumption in a typical American’s diet, the variation in nutritional value across 

different types of FAFH meals, and evidence that prices may vary substantially across 

areas, Economic Research Service researchers created a novel dataset that can be used 

to study how prices may affect food choices, intake, and health outcomes. The Quarterly 

Food-Away-from-Home Prices (QFAFHP) data contain quarterly average prices 

without tax for meals and specific FAFH (e.g., all entrees and combination meals, soda, 

hamburgers, school lunches) from four types of FAFH establishments (full- and limitedservice restaurants, vending machines, and schools) and for alcoholic beverages (at home 

and away from home). The prices are further disaggregated for the entire Nation, four 

census regions, and nine census divisions. ERS developed QFAFHP as a complementary 

data product to the Quarterly Food-at-Home Price Database, which provides market-level 

food prices for food-at-home products based on the Nielsen Homescan data. This report 

describes in detail the methodology behind QFAFHP and the underlying data, composed 

of individual product prices collected by the Bureau of Labor Statistics for the Consumer 

Price Index.

Keywords: regional prices, food away from home, food policy

JEL: R10, C80, Q18

Acknowledgments

The authors would like to thank Thesia Garner, Joshua Klick, Rob Cage, Mark Bowman, 

Bill Cook, William Johnson, and John Schlip, Bureau of Labor Statistics, for their input 

and contributions, as well as three anonymous reviewers and seminar participants at 

BLS, and participants in the Western Agricultural Economics annual meeting for their 

comments. 

Aylin Kumcu and Abigail M. Okrent

Methodology for the Quarterly 

Food-Away-from-Home Prices Data
United States Department of Agriculture

A report summary from the Economic Research Service

ERS is a primary source 

of economic research and 

analysis from the U.S. 

Department of Agriculture, 

providing timely information on economic and policy 

issues related to agriculture, 

food, the environment,and 

rural America. www.ers.usda.gov

Find the full report 

at www.ers.usda.

gov/publications/tbtechnical-bulletin/tb1938.aspx

Aylin Kumcu and Abigail M. Okrent

Methodology for the Quarterly 

Food-Away-from-Home Prices Data

What Is the Issue?

Food away from home (FAFH) is integral to a typical American’s food budget and 

diet, constituting approximately 43 percent of the food budget for an average U.S.

household in 2012 and about a third of daily calories consumed by the average adult. 

Consequently, FAFH plays a key role in the nutrition and health of Americans as 

well. Researchers use the variation in food prices over time and across regions to estimate how price changes affect the demand for different products (changes in quantity 

purchased or expenditures), and in turn, how changes in demand affect nutritional and 

health outcomes. Several studies have investigated the role of food-at-home prices on 

food purchasing behavior and dietary outcomes, but conducting similar analyses for 

FAFH has been difficult because of limited price information. ERS researchers have 

constructed quarterly FAFH price data to help examine the economic determinants of 

diet quality and health outcomes. The new data allow researchers to analyze a variety 

of questions, such as how demand varies across establishment types (e.g., full- versus 

limited-service restaurants), across specific foods (e.g., hamburgers versus sandwiches), and across regions (e.g., West versus South).

What Did The Study Find?

• Full-service restaurant prices from 1998 to 2012 were, on average, highest in the 

Northeast at $8.94 and lowest in the South at $7.17.

• The price of meals at full-service restaurants in all four census regions rose between 

1998 and 2004, but began to decline in 2005. Prices were flat during the 2007-09 

recession but rose again slightly after the recession.

• Overall, limited-service meals were almost one-third the price of meals at fullservice restaurants. At limited-service restaurants, sandwiches were generally the 

most expensive category and Mexican-style meals the least expensive.

May 2014
www.ers.usda.gov

• School lunch prices varied less across regions and divisions than did full-service and limitedservice prices, but school lunch prices increased more than either of these other categories 

between 1998 and 2012, with school lunch prices in the Northeast rising more than 5 percent over 

this period.

• Beer and wine away from home were 3 to 4 times more expensive than their at-home versions, 

while spirits away from home were 6 to 10 times more expensive than spirits at home.

How Was the Study Conducted?

ERS researchers used prices without tax collected by the U.S. Bureau of Labor Statistics (BLS) 

for the Consumer Price Index from 1998 to 2012 to construct average, weighted prices for 20 

FAFH and alcohol products for the United States, the 4 census regions, and 9 census divisions for 

4 establishment types, full-service restaurants, limited-service restaurants, vending machines, and 

school lunches. Full-service restaurants are defined by BLS as establishments where a server takes 

customers’ orders and payment is made after eating, while limited-service restaurants include establishments where customers pay at a register before eating. Only prices for entrees and combination 

meals were included in the average, weighted price calculations for the disaggregated products of 

full- and limited-service restaurants and schools. For vending machines and alcoholic beverages and 

related disaggregated products, average, weighted price calculations were per ounce. The weights 

are based on the sample of outlets from which BLS collects prices and are designed to ensure prices 

represent the census regions and divisions. The researchers estimated standard errors using a jackknife approach to facilitate hypothesis testing.
1

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Methodology for the Quarterly FoodAway-from-Home Prices Data

Aylin Kumcu and Abigail M. Okrent 

Introduction

Food away from home (FAFH) and alcohol have become integral to a typical American’s food 

budget and diet. In 1977, FAFH constituted 30 percent of households’ food budgets, and this figure 

grew steadily to 43 percent in 2012 (figure 1) (ERS, 2013). Daily calories consumed from FAFH 

increased from 18 percent in 1977-78 to 32 percent in 2005-08 (figure 2) (Lin and Guthrie, 2012).

Alcohol sales in the United States grew from $33 billion to $171 billion over the same period, representing 11 percent of total food and alcohol sales in 2012 (ERS, 2013). Alcoholic beverages contributed almost 100 daily calories to the diet of the average adult in 2007-10 (Nielsen et al., 2012), and 

they are the fifth largest source of calories for adults over the age of 19 after grain-based desserts, 

yeast breads, chicken and chicken mixed dishes, and soda/energy/sports drinks (USDA and HHS, 

2010).

Note: FAFH = food away from home FAH = food at home

Source: U.S. Department of Agriculture, Economic Research Service, Food Expenditure Tables, table 7.

Figure 1

Portions of household food budgets spent on FAFH and FAH, 1929-2012

0

10

20

30

40

50

60

70

80

90

100

1929 1939 1949 1959 1969 1979 1989 1999 2009

FAH

Percent

FAFH
2

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

The growing importance of FAFH may contribute to Americans’ nutritionally poor diet (Lin et al., 

1999; Jeffrey et al., 2006; Todd et al., 2010) and may play a role in the rising rate of obesity (Chou et 

al., 2004; Davis and Carpenter, 2009; Currie et al., 2010; Chen et al., 2013). Although the relationship of alcohol consumption to diet quality and obesity is not as clear, some evidence suggests that 

alcohol consumption is associated with weight gain for heavier individuals and nondaily drinkers 

(Suter, 2005). 

For all these reasons, researchers, policymakers, and the public have an interest in determining 

what factors drive this increase in demand for FAFH and alcohol over time and across geographic 

areas. An extensive body of research has shown that food prices influence demand for healthy 

and unhealthy foods and, therefore, that prices significantly affect diet and health outcomes.

Some of these studies link data on food-at-home (FAH) prices from the Quarterly Food-at-HomePrice Database (QFAHPD) with health surveys, such as the Early Childhood Longitudinal Study, 

Kindergarten Class of 1998-99 (ECLS-K) and the National Health and Nutrition Examination 

Survey (NHANES). 

Using QFAHPD and ECLS-K, Wendt and Todd (2011) show that price decreases of healthy foods 

purchased at grocery stores lower children’s body mass indices (BMI), and they find the inverse 

relationship between price decreases of unhealthy FAH and children’s BMI. Rahkovsky and Gregory 

(2012) use QFAHPD and NHANES to show that prices for a variety of foods purchased at grocery 

stores—such as vegetables, processed foods, whole milk, and whole grains—affect blood cholesterol. They conclude that a subsidy on vegetables and whole grains effectively lowers the cost of 

treating cardiovascular diseases. Lin et al. (2011) find that a 20-percent increase in the price of soda 

(about 0.5 cents per ounce) reduces caloric consumption by 34-47 calories per day for adults, leading 

Note: FAH = food at home FAFH = food away from home NHANES = National Health and Nutrition Examination Survey

Source: From table 2, “Average shares of U.S. caloric and nutrient intakes, by source of food, for individuals 2 years of 

age and older, 1977-78 and 2005-08,” in Lin, B.-H., and J. Guthrie. 2012. Nutritional Quality of Food Prepared at Home 

and Away From Home 1977-2008, EIB-105, U.S. Department of Agriculture, Economic Research Service.

Figure 2

Percentage of total daily calorie consumption by type of establishment as reported 

in NHANES

1977-78 2005-08

FAH, 82%

Full service, 3%

Limited service, 3%

Schools, 3%

Other FAFH, 8%

FAH, 68%

Full service, 7%

Limited service, 13%

Schools, 4%

Other FAFH, 8%
3

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

to 1 kilogram of weight loss in 1 year. While these studies illustrate that FAH prices are important, 

similar research on the role of FAFH prices on diet and health is limited because detailed FAFH 

price data have not existed.

Prices and income changes affect demand for FAFH quite differently than they affect FAH. The 

studies that support this finding have used four sources of FAFH prices: the Consumer Price Index 

(CPI) from the U.S. Bureau of Labor Statistics (BLS); price indexes for components of the Personal 

Consumption Expenditures (PCE) estimates from the National Income and Product Accounts 

(NIPA) produced by the Bureau of Economic Analysis (BEA); the Cost of Living Index (COLI) 

from the Council of Community and Economic Research (C2ER); and the Consumer Reports on 

Eating Share Trends (CREST) data published by the NPD group.

Some studies used the monthly CPI to estimate the responsiveness of FAFH product demand to 

price changes. Reed et al. (2005) found that demand for FAFH as a whole responds less to price 

changes than does demand for many disaggregated FAH products, while Okrent and Alston (2012) 

found that demand for certain disaggregated FAFH products, such as meals at full-service restaurants, responded more to price changes than did other disaggregated FAFH products, such as meals 

at limited-service restaurants, mobile vendors, and schools. Huffman (2011) used annual data from 

the NIPA and found FAH to be more price responsive than FAFH. However, both data sets used in 

these studies, the Consumer Expenditure Survey and NIPA, are only available at a national level, 

and thus these studies are not able to capture regional variation in FAFH prices.

Several studies have found significant regional price variation for FAH, which may be the case 

for FAFH as well (Sturm and Datar, 2011; Todd et al., 2011; Kumcu and Leibtag, 2011). In addition, Huffman (2011) estimated that prices, income, and changes in the structure of the population 

boosted demand for FAFH 350.7 percent and FAH 148.1 percent between 1948 and 1996, motivating his call for better information to understand trends in demand for FAFH across regions of the 

country and within types of FAFH products.

Other studies have linked quarterly average prices in metropolitan areas for specific limited-service 

items published by C2ER to nationally representative surveys of diet and health (e.g., Chou et al., 

2004; Powell et al., 2007; Khan et al., 2012). However, the coverage of FAFH products in these data 

is limited to only three items: a hamburger from McDonalds, pizza from Pizza Hut or Pizza Inn, and 

fried chicken from KFC or Church’s Chicken. Furthermore, the prices are not nationally representative because the C2ER data are collected with the specific purpose of comparing the cost of living in 

urban areas for “moderately affluent professional and managerial households,” or households in the 

top 20 percent of the income distribution for that area (C2ER, 2010). 

Lastly, the NPD group collects data on the total bill spent at an FAFH establishment for a nationally representative sample in CREST. Hence, one can calculate the price for certain characteristics 

of a meal per visit (Richards and Mancino, 2013) but not the price of individual items. In addition, 

because these data are only available as a cross section, they cannot be used to compare differences 

across time.

To fill in these gaps, the Quarterly Food-Away-from-Home Prices (QFAFHP) data provide prices on 

FAFH, alcohol at home, and alcohol away from home. QFAFHP contains quarterly average prices at 

national, census region, and census division levels for products from four types of FAFH establishments: full-service restaurants, limited-service restaurants, vending machines, and schools. BLS 

defines full-service restaurants as establishments where a server provides service, orders are gener-
4

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

ally taken while customers are seated, and customers pay after eating (BLS, 2008a). Limited-service 

restaurants are establishments where customers pay before eating, and if waiters or waitresses are 

present, they do not take customers’ orders (BLS, 2008b). Food types tracked by QFAFHP differ 

among the establishment types, such as inexpensive entrees and meals at full-service restaurants or 

hamburgers at limited-service restaurants. Prices for both alcohol at home and away from home are 

included because the Quarterly Food-at-Home-Price Database contains neither. Alcohol prices are 

disaggregated by product type but not by establishment type, beyond at home and away from home.

QFAFHP data can be used to estimate price elasticities for disaggregated FAFH products by region 

and to predict and compare growth in aggregate demand for FAH and FAFH. In this report, ERS 

researchers discuss the data and methods used to construct QFAFHP. They also present summary 

statistics on the average and dispersion of the prices across regions, products, establishment types, 

and time. 
5

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Sources of FAFH Prices

As discussed in the prior section, few sources of FAFH prices exist (table 1). Publicly available Government sources of FAFH price variation include the CPI, PCE, and average meal costs 

published in the Economic Census by the U.S. Census Bureau. Two additional sources of FAFH data 

are the COLI and CREST data.

BLS publishes price indexes for a variety of goods and services at different geographic levels (BLS, 

2013). Price indexes by establishment type are available for FAFH at the national level (e.g., fullservice restaurants in the entire United States), and composite price indexes are also available for 

all FAFH establishments by census region, large metropolitan areas, or aggregations of smaller 

metropolitan areas (e.g., all FAFH in the Northeast, New York City, or medium and small cities in 

the Northeast). Aggregations of the entire United States mask price variations between geographic 

areas, for example, between the Northeast and the Midwest. Also, aggregations of all establishTable 1

Comparison of different datasets with information on food away from home and alcohol

Data Units

Regional 

Disaggregation Frequency Coverage

Consumer Price 

Index

Geometric 

means price 

index 

National; 

limited product 

coverage for 

census regions

Time series, 

Monthly, 

1998-present

Full service, limited service, vending 

machines and mobile vendors, meals 

from employee sites and schools, 

other FAFH, alcohol at home, alcohol 

away from home; FAFH and alcohol for 

census regions

COLI Dollar per item Metropolitan 

area

Cross section, 

Quarterly

Hamburgers, pizza, fried chicken, beer 

at home, liquor at home, wine at home

CREST Dollar per visit Census division Cross section 44 restaurant categories (e.g., 

quick-service deli, fine dining), 300 

disaggregated prepared food and 

alcoholic beverages (e.g., pancakes, 

ham sandwich)

Economic Census Dollar per meal National, State Cross section, 

every 5 years

Full service, limited service, and 

cafeterias, grill buffets and buffets

QFAFHP Dollar per meal/

entrée; dollar 

per ounce

National, census 

region, census 

division

Time series, 

Quarterly, 

1998-2011

High level of detail across 

establishment types and foods. 

National Income 

and Product 

Accounts

Fisher ideal 

price index 

National Time series, 

Annual, 

1929-2012 

Food and nonalcoholic beverages for 

off-premise consumption; alcoholic 

beverages for off-premise consumption

Note: FAFH = food away from home 

Source: Bureau of Economic Analysis (BEA), National Income and Product Accounts; Bureau of Labor Statistics (BLS), 

Consumer Price Index; Council of Community and Economic Research (C2ER), Cost of Living Index (COLI); NPD Group, 

Consumer Reports on Eating Share Trends (CREST); U.S. Bureau of the Census, Economic Census; U.S. Department of 

Agriculture, Economic Research Service, Quarterly Food-Away-from-Home Prices (QFAHFP).
6

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

ment types mask price variations between types of outlets—for example, between full- and limitedservice restaurants. As shown in figures 3 and 4, the CPI for FAFH differs by census region and by 

establishment type. This pattern illustrates that price indexes, as well as average prices, are likely to 

vary by establishment type within geographic regions.

Note: FAFH = food away from home

Source: Bureau of Labor Statistics, Consumer Price Index (CPI).

Figure 3

Monthly CPIs for FAFH by census region, 1978-2012

Price index (1978=100)

 100

 150

 200

 250

 300

 350

 400

1978 80 82 84 86 88 90 92 94 96 98 2000 02 04 06 08 10 12

Northeast Midwest South West

Note: FAFH = food away from home

Source: Bureau of Labor Statistics, Consumer Price Index (CPI).

Figure 4

Monthly CPIs for FAFH by establishment type, 1997-2012

Index (December 1997=100)

100

110

120

130

140

150

160

170

1997 98 99 2000 01 02 03 04 05 06 07 08 09 10 11 12

Full service Limited service Schools and employee sites

Vending machines Other FAFH
7

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

BEA publishes national price indexes for components of its PCE estimates in NIPA (BEA, 2012).

BEA uses the CPI for meals and snacks at limited-service and full-service restaurants, alcoholic 

beverages away from home, and food at employee sites and schools to calculate a price index for 

purchased meals and beverages (BEA, 2012). Hence, the movements in the national CPI for FAFH 

and BEA’s price index closely follow each other, with only minor differences in which products 

are included in each index (e.g., alcoholic beverages are excluded from the CPI for FAFH) and in 

the index formulas (figure 5). Again, these data are only available at the national level and do not 

provide geographic price variation.

The U.S. Census Bureau publishes data on the average cost per meal at restaurants at the national 

and State levels in the Economic Census. Costs are available for three types of establishments: (1) 

full-service restaurants (North American Industry Classification System (NAICS) industry code 

722110); (2) limited-service restaurants (NAICS industry code 722211); and (3) cafeterias, grill 

buffets, and buffets (NAICS industry code 722212). Establishments are grouped into eight categories 

based on the average cost per meal at the outlet. Figure 6 shows the average cost of a meal at most 

limited-service restaurants, in 2007, ranging between the $5.00-$6.99 and $7.00-$9.99 cost categories, whereas the average cost of a meal at full-service restaurants varies much more. Additional data 

are available to calculate average costs for broader categories, such as the number of establishments 

in each category, and the total number of establishments that responded for each category. However, 

the Economic Census is available only every 5 years, and the average cost data is released with a 

3-year lag.

Note: PCE = Personal Consumption Expenditures CPI = Consumer Price Index FAFH = food away from home

Source: Bureau of Economic Analysis, Personal Consumption Expenditures Price Index and Bureau of Labor Statistics, 

Consumer Price Index (CPI).

Figure 5

Comparison of annual PCE price index for purchased meals and beverages and CPI for 

FAFH, 1929-2012

Price index (1953=100)

0

200

400

600

800

1,000

1,200

1929 39 49 59 69 79 89 99 2009

PCE index CPI
8

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

In COLI, C2ER publishes an aggregate quarterly index and underlying average prices for nearly 

300 metropolitan and nonmetropolitan areas across the United States (with a few in Canada) and 57 

specific products. Products include select FAH, FAFH, alcohol, and nonfood items—for example, 

the average price per pound of a T-bone steak or per 75-ounce box of Cascade brand dishwashing 

powder. COLI includes average prices for three FAFH products: a Quarter-Pounder with cheese 

from McDonald’s, an 11-12-inch regular thin crust pizza with cheese from Pizza Hut or Pizza Inn, 

and a fried chicken thigh or drumstick from Kentucky Fried Chicken or Church’s (C2ER, 2010). 

The COLI data has advantages over other sources, but it also carries some caveats. First, COLI’s 

goal is to represent prices paid by moderately affluent professional and managerial households in 

the top income quintile in different markets. Therefore, the data fail to represent large portions of 

the population, including lower and medium-income households and households that hold bluecollar occupations. Second, C2ER emphasizes that COLI is not intended to measure price change 

over time, making quarter-to-quarter comparisons invalid. Third, standard errors are not computed 

because the sample is not randomly selected and because a limited number of products are priced in 

a given area and quarter. This means significance cannot be determined, and thus, it is not possible 

to conduct hypothesis tests on differences between geographic regions (C2ER, 2012).

CREST provides daily data on consumer purchases of meals and snacks at restaurants, including 

information on both the food ordered and the establishment. The main advantage of CREST is 

that these data come from a large sample (52,500 individuals in a given month) that demographically and geographically represents the U.S. population. The data are also rich in characteristics of 

the food, restaurants, and respondents. Information includes specific types of food ordered, such 

Note: FAFH = food away from home

Source: U.S. Census Bureau, Economic Census 2007.

Figure 6

Number of establishments by average cost of meal for FAFH, 2007

Number of establishments

Average meal cost

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

< $2.00 $2.00-

$4.99

$5.00-

$6.99

$7.00-

$9.99

$10.00-

$14.99

$15.00-

$19.99

$20.00-

29.99

≥ $30.00

Full service Limited service Cafeterias and buffets
9

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

as penne pasta or BBQ chicken; specific categories of restaurants, such as Asian, Mexican, family 

style, steak restaurant, and upscale hotel; data on when and where the food was consumed; and 

whether discounts were used. Demographics include the ages, household income, and education of 

individuals visiting the restaurants. However, these data are only available at the total bill level; that 

is, the price, serving size, and all other information recorded are for the entire bill. Thus, prices and 

quantities for individual food items cannot be directly determined, though indirect measures have 

been estimated (Richards and Mancino, 2013).

The above review of the existing data sources of FAFH prices demonstrates that currently available data provide only a limited understanding of price variation across geographic regions and 

over time for FAFH. To overcome these gaps in the data, ERS researchers constructed quarterly 

average prices without tax for a complete set of FAFH items using the prices underlying the BLS 

CPI. These data, which quantify the price variation across regions, establishment types, and meals, 

will help researchers, Government agencies, and the public more completely understand the nature 

of FAFH prices in the United States. For example, researchers could link the QFAFHP to several 

publicly available datasets by census region or division to investigate the influence of FAFH prices 

on purchases and consumption of FAFH and FAH—and hence, indirectly, on body weight, nutrition, 

and health outcomes. Researchers could also use the database to examine interactions between time 

use and price on demand for FAFH.
10

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

BLS Sample Design and Data Collection

QFAFHP is constructed from individual prices of products collected by BLS for the CPI.

1 BLS 

constructs the CPI each month by collecting prices across U.S. urban areas for the majority of 

products consumers purchase, including FAH and FAFH. First, BLS generates a sample of establishments in each primary sampling unit (PSU)2 based on the Telephone Point-of-Purchase Survey 

(TPOPS). Within each PSU, TPOPS asks a randomly selected sample of representative households 

with a landline what their expenditures were on TPOPS categories at every retail location they 

visited. For example, a sample respondent in New York City might be asked whether he or she 

purchased any food at a limited-service restaurant. If the answer is yes, then he or she is asked at 

what location(s) the food was purchased and the total amount of money spent on food from that 

location. TPOPS categories for FAFH include the following:

1. Full-service meals and snacks

2. Limited-service meals and snacks

3. Food at employee sites and schools 

4. Food from vending machines and mobile vendors

5. Beer, ale, and other malt beverages at home

6. Distilled spirits at home

7. Wine at home

8. Alcoholic beverages away from home

Based on the responses from TPOPS, BLS chooses a sample of outlets within each PSU using probability proportional to size sampling, where the “size” is aggregate expenditures at each outlet.

Smaller PSUs are aggregated into areas based on each PSU’s population and census region (e.g., 

small- and medium-sized PSUs in the Northeast are grouped together), whereas a larger PSU can, by 

itself, represent an entire area (e.g., New York City). About 25 percent of the outlet sample in each 

PSU rotates throughout a year, so that at the end of 4 years, the entire outlet sample in the United 

States has been updated (BLS, 2007).

To determine which products to price at each outlet, a BLS field agent uses a multistage probability 

selection method, with the help of a manager or owner of the sample outlet. The manager provides 

the BLS field agent with the proportion of revenue attributable to different characteristics of the 

product being priced within an Entry-Level Item (ELI).

3 The field agent then uses a probability 

proportional to size sampling methodology to select a specific product. For example, a field agent 

assigned to a limited-service restaurant will first determine the proportion of revenue from the 

1Products purchased at FAFH establishments range from (1) specific entrees, a la carte items, and beverages offered 

on a menu at a certain time of day for full- and limited-service restaurants, (2) total meal cost of a lunch (including 

beverage) at primary and secondary schools, and (3) individual packaged beverage and food items purchased through a 

vending machine.

2PSUs are classified by population size into metropolitan and nonmetropolitan urban areas, and they are generally 

made up of multiple counties. They include Metropolitan Statistical Areas (MSAs), Primary Metropolitan Statistical 

Areas (PMSAs), and Consolidated Metropolitan Statistical Areas (CMSAs). For additional details on BLS PSU construction, see the Handbook of Methods, Chapter 17 (BLS, 2007).

3An ELI is the smallest category of item BLS uses in its index calculation. Prices for individual products are aggregated to the ELI level before aggregating to higher levels. In the case of FAFH, the TPOPS categories match the ELI 

categories one for one. Alcoholic beverages at home are aggregated into one category.
11

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

first stage of characteristics, such as different types of menus offered—breakfast, lunch, or dinner 

menus (figure 7). The field agent chooses one type of menu, where the probability of selecting 

each is proportional to the share of revenue the restaurant receives from each menu type. For the 

chosen menu, the field agent then determines the proportion of revenue at the outlet attributable to 

the second stage of characteristics—for example, type of food, which might be combination meal, 

entree, salad, side dish, or beverage, depending on the menu chosen. Once the product characteristics have been sufficiently narrowed down, the field agent records any additional information needed 

to identify the product on later visits and collects the product’s price every other month for 4 years.

4 

Once the price is collected and sent to BLS headquarters in Washington, D.C., a commodity analyst 

checks the price for errors and adjusts for sales tax and unit size (BLS, 2007).

4If, within the 4 years, a price for an item with a particular set of characteristics becomes unavailable, then the field 

agent chooses another price that has characteristics similar to the unavailable item. For example, if the price for a fried 

chicken sandwich on the regular lunch menu is no longer available, the field agent may price a grilled chicken sandwich 

on the same menu instead. The field agent notes the substitution, and a BLS commodity analyst determines if the two 

products are comparable. If the commodity analyst deems the two products not comparable, then the would-be replacement product may be added to the sample as a completely new item with different characteristics. For more details, see 

the BLS Handbook of Methods, Chapter 17 (BLS, 2007).

Source: Authors’ rendering, loosely based on Bureau of Labor Statistics checklist for limited-service meals and snacks.

Figure 7

Choosing prices at each sample outlet: limited-service restaurants

Breakfast-lunch-dinner Lunch-dinner Breakfast Lunch Dinner

Type of menu

Type of food

Ingredients

Combination meal Entrée Salad Side dish Beverage

Name of combo meal

and components Name of entrée Name of salad Name of side dish Name of beverage

"Hamburger with french 

fries and soda" "Fried chicken" "Garden salad" "Bag of chips" "Coffee"

"Price for regular size 

combo meal" "White meat only" "Includes dressing" "Any flavor" "Large"

Additional descriptions
12

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

BLS records three prices for each product within each ELI: collected price, effective price, and 

effective price with tax. The collected price comes directly from the BLS field agent and is not 

modified in any way. A BLS commodity analyst then adjusts this price in two ways. First, adjusting 

the collected price for units of measurement creates the effective price. Second, adjusting the effective price to include sales tax creates the effective price with tax. The effective price with tax of a 

6-pack of 12-ounce cans of beer would be the price of the beer with taxes per ounce (BLS, 2007). 

For products from full-service and limited-service restaurants and schools, the collected price is 

the same as the effective price.

5 For products from vending machines and for alcoholic beverages 

(at home and away from home), the effective price is generally the collected price adjusted for unit 

size.

6 ERS used the effective price without tax in its weighted average price calculations but made 

some adjustments to the sample of products and the prices, as described in the next section.

5Even though BLS collects prices for employee sites in the ELI school lunches and employee sites, these prices were 

excluded because of small sample size and the hetereogeneity of the establishment and meal types offered at employee 

sites. For example, it includes both office cafeterias and buffets as well as catered meals at hotel conference sites. 

6Prices from mobile vendors were excluded from the QFAFHP because products offered by mobile vendors were quite 

different from those offered by vending machines, but there were not enough observations to calculate a separate price 

for mobile vendors.
13

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Methodology for Calculating Average Prices

Product Selection

Artificial variation in average prices can arise if prices are not adjusted for changes in quality or 

differences across areas, time, establishment types, and products (Okrent and Alston, 2012; Todd 

et al., 2010). Therefore, ERS researchers calculated FAFH product prices at the most disaggregated 

level possible: by census region and division and by establishment and product type (table 2). Using 

a number of product characteristics recorded by the field agent at the time of price collection, ERS 

chose products within BLS’s six FAFH establishment types in such a way as to maintain a minimum 

Table 2

Aggregation of BLS PSUs to census region and division

BLS PSU Census division* Census region*

Hartford, CT

Springfield, MA

Boston, MA

Burlington, VT

New England

Northeast

New York City, NY

Pittsburgh, PA

Syracuse, NY

Buffalo, NY

Sharon, PA

Johnstown, PA

Philadelphia, PA

Reading, PA

New York Suburbs, NY**

New Jersey Suburbs, NJ

Middle Atlantic

Detroit, MI

Milwaukee, WI

Saginaw, MI

Chicago, IL

Cleveland, OH

Cincinnati, OH

Dayton, OH

Columbus, OH

Youngstown, OH

Wausau, WI

Evansville, IN

Elkhart, IN

Madison, WI

Decatur, IL

Mount Vernon, IL

East North Central

Midwest

St. Louis, MO**

Minneapolis, MN**

Kansas City, MO

Lincoln, NE

Faribault, MN

Chanute, KS

West North Central

—continued
14

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Table 2

Aggregation of BLS PSUs to census region and division—continued

BLS PSU Census division* Census region*

Melbourne, FL

Ocala, FL

Gainesville, FL

Norfolk, VA

Raleigh, NC

Richmond, VA

Baltimore, MD

Miami, FL

Tampa, FL

Ft. Myers, FL

Arcadia, FL

Atlanta, GA

Washington, DC

Florence, SC

Albany, GA

Greenville, SC

Statesboro, GA 

South Atlantic

South

Florence, AL

Birmingham, AL

Chattanooga, TN**

Morristown, TN

East South Central

Pine Bluff, AR

Oklahoma City, OK

San Antonio, TX

Dallas, TX

Houston, TX

Lafayette, LA

Baton Rouge, LA

Beaumont, TX

Brownsville, TX

Amarillo, TX

Odessa, TX

West South Central

Phoenix, AZ

Denver, CO

Yuma, AZ

Provo, UT

Boise, ID

Las Vegas, NV

Brookings, SD

Mountain

West

San Diego, CA

Modesto, CA

Los Angeles, CA

Los Angeles Suburbs

Seattle, WA

Portland, OR

Bend, OR

San Francisco, CA

Chico, CA

Pullman, WA

Pacific

Note: BLS = Bureau of Labor Statistics PSU = Primary Sampling Unit 

*Quarterly Food-Away-from-Home-Prices data include prices for census divisions and census regions; 

**PSUs that cross census division borders. Authors adjusted weights to account for the percentage of population residing 

in each division to ensure prices are geographically representative. BLS already adjusts weights to account for PSUs that 

cross census region borders to ensure representativeness.

Source: BLS, Consumer Price Index.
15

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

sample size of three individual prices within each quarter and area.

7 The establishment types 

closely follow the TPOPS categories for FAFH: full-service FAFH, limited-service FAFH, schools, 

vending machines, alcohol at home, and alcohol away from home (table 3).

The quality of full-service restaurants (reflected in ambiance, reputation, and so on) varies widely, 

and this quality variation could drive much of the price variation in this category (Mehta and 

Maniam, 2002). In particular, the BLS sample included full-service meal prices that could cost 

less than $5 per entree or more than $100 per entree for any given region and quarter. The average 

meal price at a full-service restaurant generally reflects whether it is an inexpensive or fine-dining 

establishment. 

To eliminate some of these obvious quality differences, ERS defined two types of full-service 

products: entrees and combination meals at inexpensive restaurants and entrees and combination 

meals at moderately priced restaurants. Combination meals are meals with one price for two or 

more items, usually a main course and one or more additional items, such as a side dish or beverage.

“Inexpensive” is defined as full-service restaurants that had a less-than-$10 average price per entree 

or meal over the entire time the restaurant was in the BLS sample, and “moderately priced” is 

defined as restaurants that had an average price between $10 and $20.

8

Products at limited-service restaurants were divided into seven categories: all entrees and combination meals, nonalcoholic beverages, hamburgers, pizza, fried chicken, sandwiches, and Mexicanstyle dishes. ERS researchers grouped the limited-service categories by products offered rather than 

by the establishments’ price points, because limited-service restaurants display less price variation 

(figure 6) than do full-service restaurants. Furthermore, while industry analysts tend to categorize 

full-service establishments by price points, such as “casual” or “fine dining,” limited-service restaurants are often categorized by their food offerings because they tend to specialize in a certain type of 

cuisine, such as hamburgers, sandwiches, or Mexican food (Basham and Menza, 2007). The seven 

limited-service categories ERS researchers chose to study were the only ones for which a sufficient 

sample size existed, and they represent the largest share of the limited-service industry (Friddle et 

al., 2001).

The beverages category consists mainly of carbonated beverages that were often sold for the same 

price, regardless of type (cola, non-cola, and so on) and sugar content (regular or diet). It also 

includes lemonade, iced tea, coffee, and juice, but not milkshakes or smoothies. The hamburgers 

category includes all types (e.g., with or without cheese, double burgers, junior-sized burgers), as 

well as combination meals with french fries, beverages, and so on. The average price for pizza is the 

price per person, determined by information recorded by the field agent (e.g., serving size of each 

pizza). Fried chicken includes chicken nuggets, fingers, tenders, and other variations, as well as 

fried chicken legs, thighs, drumsticks, and white meat.

9 The sandwich category includes any kind of 

sandwich or wrap. Mexican-style dishes include items such as tacos, nachos, burritos, quesadillas, 

7The minimum sample size of three was required by BLS to ensure confidentiality of participating establishments.

BLS considers a single price or single establishment to be representative given their sampling methodology.

8ERS did not include fine-dining restaurants because of the small sample size. The break between inexpensive and 

moderately priced restaurants was chosen based on price ranges used by Government, industry, and other publicly accessible sources such as the Economic Census Subject Series for the Average Cost Per Meal, the National Restaurant 

Association, Yelp.com, and Zagat. Sample size and natural breaks in the data seen visually were also considered.

9Chicken breasts, quarters, and other cuts from establishments that primarily serve fried chicken are also included.

Fried chicken sandwiches, however, are not included; they are in the sandwich category. 
16

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Table 3

QFAFHP sample size and product characteristics

Average quarterly sample size 

Per region Per division Price determining characteristics

Full service

All meals 259 158 Combination meals and entrees

Inexpensive 99 64 Combination meals and entrees sold at establishments 

with average price less than $10

Moderately priced 65 37 Combination meals and entrees sold at establishments 

with average price between $10 and $20

Limited service

All meals 305 190 Combination meals and entrees

Hamburgers 55 34

Hamburger combination meals and entrees, all types 

(e.g., with or without cheese, double burgers, juniorsized burgers)

Fried chicken 29 21

All entrees and combination meals of chicken nuggets, 

fingers, tenders, and other variations; fried chicken legs, 

thighs, drumsticks, and white meat (no sandwiches)

Pizza 21 14 All pizza, not including combo meals, per serving

Sandwiches 21 14 All sandwich and wrap entrees and combination meals

Mexican-style dishes 27 18

Tacos, nachos, burritos, quesadillas, fajitas, enchiladas, taquitos, chimichangas, tamales, taco salads, and 

so on

Nonalcoholic beverages 31 20

Lemonade, iced tea, coffee, hot tea, milk and juice, 

carbonated beverages but excluding milk shakes and 

smoothies

School lunches 81 54 Lunches at public and private (excluding vocational) 

primary and secondary schools

Vending machines

Snacks 38 23 Candy bars, chips, and sweets, but not ice cream, 

candy or gum, ounces per unit sold

Nonalcoholic beverages 79 50 Coffee, tea, juice, and soda, ounces per unit 

Soda 59 39 Soda, ounces per unit sold

Alcohol

Beer at home 101 59 All beer, ale, and other malt beverages at home, price 

per ounce

Wine at home 103 61 All wine at home including sparkling wine, price per 

ounce

Spirits at home 81 49 All spirits away from home, price per ounce

Beer away from home 61 36 All beer, ale, and other malt beverages away from 

home, price per ounce

Spirits away from home 33 19 All spirits and cocktails away from home, price per 

ounce

Wine away from home 44 25 All wine away from home including sparkling wine, 

price per ounce

Source: U.S. Department of Agriculture, Economic Research Service, Quarterly Food-Away-from-Home Prices (QFAFHP).
17

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

fajitas, enchiladas, taquitos, chimichangas, tamales, and taco salads sold at any type of limitedservice outlet.

Vending machine products were divided into three groups: snacks, all beverages, and carbonated 

beverages. The snacks category includes candy bars, chips, and sweets (e.g., cookies, donuts, sweet 

rolls), but not hard candy, gum, fresh fruit, meals (e.g., sandwiches, pizza) or ice cream, which are 

all included in the BLS ELI.10 The beverages category includes all beverages, while the carbonated 

beverages category does not include coffee, tea, or juice. Products sold by mobile vendors are not 

included in any category.

ERS researchers removed lunches at employee sites from the schools category because school lunch 

prices are an important area of interest, particularly because USDA operates the National School 

Lunch Program (e.g., Ollinger et al., 2011). School lunches were defined as the student price for 

one lunch at any school serving grades Kindergarten through 12th grade, including both public and 

private institutions, but not vocational schools. The price includes meals that are offered for free or 

at a reduced price, although the field agent records the full price. 

The alcoholic beverages category includes beer, wine, and spirits, which are divided into at home 

and away, yielding six alcohol categories: beer at home, wine at home, spirits at home, beer away 

from home, wine away from home, and spirits away from home. Beer includes all types of malt 

beverages; wine includes sparkling wine; and spirits away from home includes drinks mixed with 

other ingredients, such as juice, soda, or mixers. Prices are reported per ounce.

Sample and Price Adjustments

ERS researchers adjusted the sample of products and individual prices in several ways. The sample 

was adjusted for outliers by removing individual prices that were three standard deviations below or 

above the average per year, quarter, and area. Meal and snack prices were adjusted to be per person 

by dividing the effective price by the average number of people the product was meant to serve (as 

recorded by the field agent). For example, the price of a pizza noted to serve six to eight people was 

adjusted by dividing the collected price by 7. Likewise, effective prices for nonalcoholic beverages 

were adjusted to be per ounce by dividing the effective price by the number of ounces in the drink 

recorded by the field agent.

11 Also, non-restaurants, such as grocery stores, convenience stores, 

and gas stations, were excluded from the sample. Even though these establishments sell meals and 

snacks intended to be consumed away from home, these foods and their pricing strategies may be 

different than those of FAFH establishments. School lunch prices that were recorded as monthly 

were adjusted to daily by dividing by 22.

Average Price Calculation and Standard Errors

Average prices were constructed in two steps. In the first step, ERS researchers calculated an average 

price per individual product within a quarter, where an individual product refers to a specific item 

10Hard candy, gum, fresh fruit and meals were removed because they differ from the majority of other products (namely candy bars, chips, and sweets) in systematic ways. They represent a small portion of this category and their prices are 

driven by different factors.

11If the field agent did not record the number of servings or ounces for pizza or beverages, ERS researchers used other 

information to calculate the price per person or per ounce. For example, the collected price of 12- and 14-inch pizzas 

without a serving size was divided by 4, because most 12- and 14-inch pizzas in the data were reported to serve four 

people.
18

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

at a specific store location (e.g., a cheeseburger at the fast-food restaurant at 100 Main St.). Because 

most prices are collected bimonthly, individual product prices collected in odd months would enter 

the average quarterly price twice in quarters 1 and 3, while those collected in even months would 

enter only once. To reduce artificial quarter-to-quarter variation based on this bimonthly collection methodology, ERS first calculated an average quarterly price per individual product. (In other 

words, individual products that entered the quarter twice were given a weight of 0.5.) In the second 

step, ERS calculated a weighted average of these quarterly prices per individual product to obtain an 

average price per quarter and area for each item (figure 8). 

The average price

1

 ̅

 ∑ ̅

 ̅ 

 

∑ ̅ 

 

, (1)

 ̅ 

 ̅ 

 

 . (2)

 

 . (3)

 

 

 

 . (4)

 

 

 

 (5)

 √ 

 ∑ ( ̂

 ) , (4)

, for a given establishment type e, area a, year y, and quarter q, is given by equation (1):

 ̅

 

∑ ̅

 ̅ 

 

 

∑ ̅ 

 

 

, (1)

 ̅ 

 ̅ 

  

 

 . (2)

  

 

 . (3)

  

 

 

 

 . (4)

  

 

 

 

 (5)

 √ 

 ∑ ( ̂

 ) 

 , (4)

 , (1)

Figure 8

Aggregation of individual product prices to average quarterly price per census region 

Product i January Product i March

Individual product's price

Product i quarter 1 = 

average of product i January and 

product i March

Quarterly price per individual product

Quarter 1 price for 

hamburger combination meal 

at the fast-food restaurant at 100 Main St.

Sum all products q1 region 1, 

weighted by quarter product weights 

= product i q1 * weight i q1 + ... 

+ product N q1 * weight N q1

Quarterly average price per region

Individual product's price

January price for 

hamburger 

combination meal at 

the fast-food 

restaurant at 100 

Main St.

March price for 

hamburger 

combination meal at 

the fast-food 

restaurant at 100 

Main St.

Quarter 1 price for all entrees 

and combination at meal limited-service 

restaurants in the Northeast

Source: U.S. Department of Agriculture, Economic Research Service, Quarterly Food-Away-from-Home Prices. Authors’ 

rendering of QFAFHP methodology.
19

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

where 

1

 ̅

 ∑ 

  

 

∑ ̅ 

 

, (1)

 ̅ 

 ̅ 

 

 . (2)

 

 . (3)

 

 

 

 . (4)

 

 

 (5)

 √ 

 ∑ ( ̂

 ) , (4)

 is the average quarterly price per individual product calculated in the first step, 

and 

1

 

 

∑ ̅ 

 

, (1)

 ̅ 

 ̅ 

 

 . (2)

 

 . (3)

 

 

 

 . (4)

 

 

 (5)

 √ 

 ∑ ( ̂

 ) , (4)

 is the weight for a given product i, establishment type e, area a, year y, and quarter q, 

described below.

The weights, 

1

 ̅

 ∑ ̅

 ̅ 

 

∑ ̅ 

 

, (1)

 ̅ 

 ̅ 

 

 . (2)

 

 . (3)

 

 

 

 . (4)

 

 

 

 (5)

 √ 

 ∑ ( ̂

 ) , (4)

, were calculated in the same manner as the weights used by the BLS average prices 

for FAH products. The BLS weights roughly approximate the average quantity purchased per item 

and are representative at the census region level by accounting for the outlet sample and the share 

of the population in each PSU. The BLS weights are designed to be used monthly. Because ERS 

researchers aggregated the data quarterly, they averaged the weights for individual products that 

appeared twice in a quarter.

The census region weights for all the TPOPS categories, except alcoholic beverages, are based on 

four pieces of information given by equation (2):

1

 ̅

 ∑ ̅

 ̅ 

 

 

∑ ̅ 

 

 

, (1)

 ̅ 

 ̅ 

 

 . (2)

 

 . (3)

 

 

 

 . (4)

 

 

 

 (5)

 √ 

 ∑ ( ̂

 ) 

 , (4)

(2)

The TPOPS weight, TPOPSwt, is based on the aggregate expenditure by all households for all items 

in the TPOPS category in a given PSU in a given month. For example, every price collected from 

limited-service restaurants in New York City in January 2000 will have the same TPOPS weight.

The remaining variables adjust the TPOPS weight so that it approximates the quantity of the item 

purchased, in a given outlet, making the weights unique to each item for which a price is collected. 

The Count variable gives the number of individual products intended to be collected according to 

the sample design. Dividing the TPOPS weight (total expenditure for the entire TPOPS category in 

a PSU) by the number of items priced in the PSU results in the average monthly expenditure on each 

item in that TPOPS category in the PSU. Dividing this expenditure by the price in the base period, 

BasePrice, gives an approximate average quantity for the item.

Less than 1 percent of the observations in any given TPOPS category also use the duplication factor, 

DupFactor, which adjusts for the fact that, in some cases, BLS field agents are not able to collect all 

of the prices needed for the sample (e.g., because of time constraints). For example, if four prices 

should have been collected from limited-service restaurants in New York City in January 2000 but 

the field agent could collect only three, then the duplication factor will be equal to 1.25 so the three 

prices actually represent four.

The weights for the alcoholic beverage TPOPS categories are given by equation (3): 

 ̅

 ∑ ̅

 ̅ 

 

 

∑ ̅ 

 

 

, (1)

 ̅ 

 ̅ 

 

 . (2)

 

 . (3)

 

 

 

 . (4)

 

 

 

 (5)

. (3)

Three additional variables are used for these categories: GeoAdjFactor, PercentTPOPS, and 

ELIfactor. The geographic adjustment factor, GeoAdjFactor, corrects for the population and sample 

in the PSU. The percentage of TPOPS, PercentTPOPS, and the ELI adjustment factor, ELIfactor, 

convert the TPOPS weight to represent the ELI rather than the TPOPS category.

Census region and division (i.e., area a) were defined based on the PSU of the individual product 

(table 2). Table 2 displays each BLS PSU and the corresponding census division and census region.

Some PSUs cross census regions and divisions. BLS adjusts the aggregation weights to ensure their 
20

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

published price indexes are representative at the region level. To ensure prices calculated by ERS 

are representative at the census division level, BLS staff provided their population percentages and 

ERS adjusted their weights to account for the share of the division population located in each PSU 

following BLS methodology. The weights are adjusted by the share of the division population in 

each PSU, PSUpop/DIVpop, to ensure that the prices are representative at the division level as well 

(equations (4) and (5)):

1

 

 . (3)

 

 

 

 . (4)

 

 

 

 (5)

 √ 

 ∑ ( ̂

 ) 

 , (4)

 , (4)

1

 

 . (3)

 

 

 

 . (4)

 

 

 

 (5)

 √ 

 ∑ ( ̂

 ) 

 , (4)

. (5)

Standard errors were also calculated for each average price to facilitate hypothesis testing and create 

confidence intervals. ERS researchers calculated the standard errors for each region-quarter-year 

average price using a jackknife approach, in which an average price was recalculated multiple times, 

each time dropping one individual product’s price from the sample (equation (6)): 

1

 

 . (3)

 

 

 

 . (4)

 

 

 

 (5)

 √ 

 ∑ ( ̂

 ) 

 , (4) , (6)

where N is the number of average quarterly prices per individual product for a given establishment 

or category in a given area, quarter, and year; μ is the average quarterly price calculated using the 

entire sample; and 

1

 ̅

 ∑ ̅

 ̅ 

 

∑ ̅ 

 

, (1)

 ̅ 

 ̅ 

 

 . (2)

 

 . (3)

 

 

 

 . (4)

 

 

 (5)

 √ 

 ∑ ( ̂

 ) is the quarterly price calculated when individual product , (4) n is dropped.
21

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

FAFH Price Variation Across Area and Time

This section summarizes census region prices from QFAFHP across the country and over time. 

Table 4 presents the average quarterly price across the entire period (first quarter of 1998 to second 

quarter of 2012), coefficients of variation across this period, the price at the beginning of the period 

(usually the minimum price), the price at the end of the period (usually the maximum price), and the 

average annual growth rate. The coefficient of variation (CV), presented for each product-area price 

series, is a statistic that measures dispersion or variation, standardized for the variable in question.

In this case, it measures how much prices vary over time. It is calculated by dividing the standard 

deviation by the average price, which allows comparison of variation across FAFH and alcohol products and areas even if they have widely different average values. A higher CV means prices vary 

more.

Jackknife standard errors (equation 6) for the individual price estimates are very small for most of 

the FAFH and alcohol categories and areas. Thus, the average-weighted prices are generally statistically significant at the 5-percent level.

12 For brevity, the standard errors for the individual averageweighted prices are not reported here, but they are available in QFAFHP for closer inspection.

12In this case, statistical significance refers to comparisons across areas within the same establishment type or food 

category and over time. For example, full-service meals in the Northeast are statistically significantly different from 

those in the Midwest, South, and West. Prices that tend not to be statistically significantly different from other areas 

include those with smaller sample sizes, such as the division-level specific food prices. For example, prices for Mexicanstyle meals in division 1 are not statistically significantly different from Mexican-style meals in division 2. However, 

Mexican-style meal prices in divisions 1 and 2 are statistically significantly different from fried chicken prices in division 

2. Region-level prices for specific foods and division-level prices for establishment types are statistically significantly 

different from other price series.

Table 4

QFAFHP 1998-2012 price data disaggregated by product and census region

Northeast Midwest South West

Full service

All meals

Mean price ($) 8.94 7.78 7.17 8.60

CV (0.10) (0.14) (0.11) (0.09)

1998 ($) 7.25 5.81 5.69 7.39

2012 ($) 10.10 8.95 9.54 11.15

Growth (%) 2.45 3.13 3.62 2.80 

Inexpensive

Mean price ($) 6.36 6.32 5.81 6.77

CV (0.13) (0.15) (0.12) (0.09)

1998 ($) 5.07 4.81 4.61 6.48

2012 ($) 7.38 7.82 7.41 8.58

Growth (%) 2.73 3.51 3.58 1.91 

Moderately priced

Mean price ($) 11.43 11.82 11.12 10.96

CV (0.09) (0.04) (0.07) (0.07)

1998 ($) 10.04 11.36 10.83 10.24

2012 ($) 12.12 12.03 13.25 12.69

Growth (%) 1.42 0.50 1.61 1.67 

—continued
22

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Table 4

QFAFHP 1998-2012 price data disaggregated by product and census region—continued

Northeast Midwest South West

Limited service

All meals

Mean price ($) 3.37 2.95 3.18 2.80

CV (0.15) (0.13) (0.17) (0.17)

1998 price ($) 2.63 2.33 2.43 2.13

2012 price ($) 4.01 3.56 4.12 3.42

Growth (%) 3.18 3.00 3.73 3.25 

Hamburgers

Mean price ($) 4.22 3.75 3.67 3.70

CV (0.23) (0.15) (0.16) (0.17)

1998 price ($) 3.09 2.97 2.89 2.93

2012 price ($) 6.21 5.00 4.66 4.74

Growth (%) 4.96 3.52 3.28 3.65 

Fried chicken

Mean price ($) 3.97 3.81 3.86 4.09

CV (0.18) (0.15) (0.17) (0.16)

1998 price ($) 2.91 3.40 3.09 3.33

2012 price ($) 5.18 4.59 4.51 5.13

Growth (%) 4.14 2.39 2.79 4.07 

Pizza

Mean price ($) 2.73 3.74 3.61 3.34

CV (0.21) (0.14) (0.11) (0.15)

1998 price ($) 2.44 3.48 3.13 3.39

2012 price ($) 4.01 4.91 4.41 3.61

Growth (%) 4.17 3.55 3.58 1.45 

Sandwiches

Mean price ($) 5.19 4.75 4.74 4.94

CV (0.18) (0.15) (0.19) (0.14)

1998 price ($) 4.26 3.69 3.27 4.11

2012 price ($) 6.74 5.83 6.11 5.60

Growth (%) 3.63 3.29 4.30 2.44 

Mexican

Mean price ($) 2.60 2.47 2.47 2.23

CV (0.23) (0.37) (0.22) (0.17)

1998 price ($) 1.69 1.70 1.68 1.78

2012 price ($) 3.27 4.23 3.48 3.58

Growth (%) 5.31 7.16 5.66 4.81 

Nonalcoholic 

beverages*

Mean price ($) 0.07 0.07 0.07 0.08

CV (0.17) (0.20) (0.18) (0.20)

1998 price ($) 0.07 0.06 0.05 0.05

2012 price ($) 0.09 0.10 0.07 0.09

Growth (%) 2.53 3.84 2.84 4.01 

Schools

Lunches

Mean price ($) 1.72 1.78 1.67 1.78

CV (0.22) (0.16) (0.15) (0.14)

1998 price ($) 1.26 1.34 1.31 1.50

2012 price ($) 2.54 2.36 1.98 2.34

Growth (%) 5.34 3.94 3.09 3.93 

—continued
23

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Table 4

QFAFHP 1998-2012 price data disaggregated by product and census region—continued

Northeast Midwest South West

Vending machines

Food snacks*

Mean price ($) 0.42 0.38 0.34 0.32

CV (0.16) (0.17) (0.22) (0.19)

1998 price ($) 0.32 0.29 0.24 0.34

2012 price ($) 0.61 0.56 0.59 0.53

Growth (%) 5.13 4.76 7.48 4.58 

Nonalcoholic beverages*

Mean price ($) 0.06 0.05 0.05 0.05

CV (0.17) (0.14) (0.13) (0.21)

1998 price ($) 0.05 0.05 0.04 0.04

2012 price ($) 0.07 0.07 0.06 0.07

Growth (%) 3.22 2.87 2.09 4.69 

Soda*

Mean price ($) 0.06 0.05 0.05 0.05

CV (0.13) (0.14) (0.11) (0.14)

1998 price ($) 0.04 0.04 0.04 0.04

2012 price ($) 0.07 0.06 0.06 0.06

Growth (%) 3.12 2.79 2.01 3.61 

Alcoholic beverages

Beer at home*

Mean price ($) 0.07 0.06 0.06 0.07

CV (0.14) (0.09) (0.12) (0.14)

1998 price ($) 0.05 0.05 0.05 0.05

2012 price ($) 0.08 0.07 0.07 0.09

Growth (%) 2.75 2.00 2.29 3.17 

Wine at home*

Mean price ($) 0.24 0.24 0.19 0.20

CV (0.19) (0.34) (0.23) (0.22)

1998 price ($) 0.17 0.16 0.14 0.15

2012 price ($) 0.30 0.35 0.25 0.27

Growth (%) 5.17 6.08 4.27 4.40 

Spirits at home*

Mean price ($) 0.51 0.42 0.44 0.40

CV (0.15) (0.18) (0.11) (0.13)

1998 price ($) 0.37 0.32 0.35 0.29

2012 price ($) 0.59 0.50 0.48 0.44

Growth (%) 3.62 3.49 2.43 2.83 

Beer away 

from home*

Mean price ($) 0.23 0.20 0.21 0.20

CV (0.20) (0.14) (0.17) (0.09)

1998 price ($) 0.17 0.15 0.16 0.17

2012 price ($) 0.31 0.24 0.27 0.24

Growth 3.97 3.27 3.95 2.27

Wine away 

from home*

Mean price ($) 0.80 0.63 0.81 0.75

CV (0.27) (0.31) (0.20) (0.31)

1998 price ($) 0.39 0.33 0.51 0.39

2012 price ($) 0.97 0.93 0.94 0.98

Growth (%) 8.46 7.49 6.00 7.60 

Spirits away 

from home*

Mean price ($) 3.28 2.94 3.40 3.71

CV (0.17) (0.08) (0.19) (0.17)

1998 price ($) 2.69 2.40 2.58 2.68

2012 price ($) 3.66 3.03 4.17 3.82

Growth (%) 2.28 1.81 3.80 2.80 

Note: CV = coefficient of variation, 1998-2012; 1998 = 1998 quarter 1(first period) price; 2012 = 2012 quarter 2 (last 

period) price; Growth = average annual growth.

*Prices are per ounce.

Source: U.S. Department of Agriculture, Economic Research Service, Quarterly Food-Away-from-Home Prices (QFAFHP).
24

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Full-service restaurants

Overall, full-service prices were highest in the Northeast ($8.94 on average between 1998 and 2012), 

while prices at inexpensive restaurants were generally higher in the West, and prices at moderately 

priced restaurants were higher in the Midwest (figure 9). During the time period studied, the South 

saw the greatest average annual growth in prices at all full-service restaurants (3.6 percent) as well 

as inexpensive restaurants (3.6 percent), and the West saw the greatest growth in moderately priced 

restaurants (1.7 percent). Prices in the Midwest displayed the greatest variation over time with a CV 

of 0.14, while prices in the West displayed the least variation with CV of 0.09 percent. The regions 

had different experiences during the 2007-09 recession. Prices paid for all full-service meals began 

to decline in 2005 and were generally stagnant during the recession (i.e., between fourth quarter 

of 2007 and third quarter of 2009). Average quarterly price growth of moderately priced meals, 

however, was negative in all regions except for the Midwest, and price growth of inexpensive meals 

was positive in all regions except for the West.

Limited-service restaurants 

Entrees and meals at limited-service restaurants displayed similar trends, though the price of a meal 

at a limited-service establishment was nearly one-third the price of a full-service meal. Between 

1998 and 2012, the highest average price was in the Northeast ($3.37) and the lowest in the West 

($2.80), representing a price difference of 20 percent. Prices varied the most in the South and West, 

with a CV of 0.17, and they varied the least in the Midwest, with a CV of 0.13. The price of meals 

at limited-service restaurants increased between 3 and 3.7 percent annually. During the recession, 

limited-service prices, unlike full-service prices, did not differ from non-recessionary periods, with 

the exception of the West. During the recession, limited-service prices in the West and Midwest 

declined, but prices in the South and Northeast steadily increased (figure 10).

Note: q1 (as in “1998q1”) = first quarter. 

Source: U.S. Department of Agriculture, Economic Research Service, Quarterly Food-Away-from-Home Prices. 

Figure 9

Average quarterly price of full-service meals by census region, 1998q1-2012q1

Price per meal/entree ($)

Northeast Midwest South West U.S.

6.00

7.00

8.00

9.00

10.00

11.00

1998q1 2000q1 2002q1 2004q1 2006q1 2008q1 2010q1 2012q1

95% Confidence Interval
25

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Limited-service meals disaggregated by food type varied more than the aggregate meals category. 

Average prices were generally highest for sandwiches, and they were generally lowest for Mexicanstyle meals over the entire period. Regionally, in the second quarter of 2012, sandwiches were most 

expensive in the Northeast ($6.74) and least expensive in the West ($5.60), a 27-percent difference (figure 11). Displaying CVs between 0.14 and 0.19, sandwich prices varied more than the 

limited-service meal category as a whole. Average annual growth was highest for Mexican-style 

meals, ranging between 4.8 percent and 7.2 percent per census region. Price patterns of disaggregated limited-service entrees and meals, except for hamburgers, did not seem to differ during the 

recession.

Comparing full-service and limited-service meals by region illustrates that prices were highest in 

the Northeast for both full-service and limited-service meals. The least expensive regions were the 

South for full-service meals and the West for limited-service meals. 

Vending machines

Prices for snacks at vending machines varied substantially over time as product availability changed. 

The average regional price per ounce of a vending-machine snack over the entire time period studied 

was between $0.32 (in the West) and $0.42 (in the Northeast). Prices varied the most in the South 

(CV of 0.22) and least in the Northeast (CV of 0.16). Prices increased 4.8 to 7.5 percent annually, 

with the highest growth in the South. 

Note: q1 (as in “1998q1”) = first quarter.

Source: U.S. Department of Agriculture, Economic Research Service, Quarterly Food-Away-from-Home Prices. 

Figure 10

Average quarterly price of limited-service meals by census region, 1998q1-2012q1

Price per meal/entree ($)

Northeast Midwest South West U.S.

95% Confidence Interval

2.00

2.50

3.00

3.50

4.00

1998q1 2000q1 2002q1 2004q1 2006q1 2008q1 2010q1 2012q1
26

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Schools 

School lunch prices displayed smaller geographic differences than did prices in full-service and 

limited-service restaurants (figure 12). For the entire sample period, on average, the Midwest and 

West had the highest prices for school lunches ($1.78), while the South had the lowest ($1.67), a 

difference of 9 percent. Regional prices varied the most in the Northeast and the least in the West 

(CVs of 0.22 and 0.14 respectively). At the end of the period, the Northeast had the highest price 

($2.54), while the South had the lowest ($1.98). On average, the price of school lunches grew about 

3 to 5 percent annually.

Note: q1 (as in “1998q1”) = first quarter.

Source: U.S. Department of Agriculture, Economic Research Service, Quarterly Food-Away-from-Home Prices. 

Figure 11

Average quarterly price of specific limited-service meals and entrees by census region, 

1998q1-2012q1

0.00

2.00

4.00

6.00

8.00

Price ($) Price ($)

Price ($) Price ($)

1998q1 2000q1 02q1 04q1 06q1 08q1 10q1 12q1 1998q1 2000q1 02q1 04q1 06q1 08q1 10q1 12q1

1998q1 2000q1 02q1 04q1 06q1 08q1 10q1 12q1 1998q1 2000q1 02q1 04q1 06q1 08q1 10q1 12q1

Northeast

0.00

2.00

4.00

6.00

8.00

Midwest

0.00

2.00

4.00

6.00

8.00

South

0.00

2.00

4.00

6.00

8.00

West

Hamburger Fried chicken Mexican Pizza

Sandwich 95% Confidence Interval
27

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Nonalcoholic Beverages

Nonalcoholic beverages from limited-service restaurants were slightly more expensive than beverages and soda alone from vending machines. Across the Nation, limited-service beverages were 

$0.04-$0.05 per ounce (or about $0.64-$0.80 per 16-ounce drink) in the first quarter of 1998 and 

$0.05-$0.07 per ounce (or $0.80-$1.12 per 16-ounce drink) in the second quarter of 2012. Limitedservice beverage prices grew 2.5 to 4.0 percent annually between 1998 and 2012, roughly the same 

rate as beverages from vending machines (2.1 to 4.7 percent annually) and soda from vending 

machines (2.0 to 3.6 percent annually). 

Alcohol

As for alcoholic beverages, the away-from-home versions were typically more expensive than their 

at-home versions, though at-home spirits were twice as expensive ($0.44 per ounce) than beer 

consumed away from home ($0.21 per ounce). In general, wine displayed the greatest variation, 

with CVs of 0.19 to 0.34 at home and 0.20 to 0.31 away from home, while beer displayed the least 

variation, with CVs of 0.09 to 0.14 at home and 0.09 to 0.20 away from home. Average annual price 

growth was also greatest for wine, with at-home use growing 5 percent annually and away from 

home growing 7 percent, compared to beer use which grew 3 percent (including at-home and awayfrom-home versions). 

Note: q1 (as in “1998q1”) = first quarter.

Source: U.S. Department of Agriculture, Economic Research Service, Quarterly Food-Away-from-Home Prices. 

Figure 12

Average quarterly price of school lunches by census region, 1998q1-2012q1

Price per meal/entree ($)

95% Confidence Interval

1.00

1.50

2.00

2.50

1998q1 2000q1 2002q1 2004q1 2006q1 2008q1 2010q1 2012q1

Northeast Midwest South West U.S.
28

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Limitations

While QFAFHP will be useful to many researchers, using the data poses some notable limitations.

First, the price variation across regions reflects changes in supply and demand, making welfare 

comparisons across regions based directly on QFAFHP inaccurate. For example, the fact that 

limited-service prices are consistently higher in the Northeast than in other census regions does 

not automatically imply that Northeastern consumers are worse off. It may be that limited-service 

restaurants in the Northeast offer better quality meals or service than in other regions.

A second, related limitation is that prices for meals at limited- and full-service restaurants are 

presented as a price per meal not a price per ounce or gram (i.e., they are not unitized). Using the 

Northeast as an example, the price of meals at limited-service restaurants could be higher because 

the portion size in the Northeast is larger. However, because of the many national chains of limitedservice restaurants where the portion sizes are standard within chains, portion size is less likely to 

differ among limited-service than among full-service restaurants and schools.

Lastly, expenditures are not readily available for the user to aggregate prices into price indexes. 

However, a user of QFAFHP can construct census region or national price indexes using sales from 

the Economic Census in a fixed-weight price index formula.

13 Expenditures for FAFH by establishment type and census region are available from the BLS Consumer Expenditure Survey, and can be 

used to calculate national level price indexes.

14

13These data are available through Census’ American FactFinder Portal at http://factfinder2.census.gov/faces/nav/jsf/

pages/index.xhtml.

14These data are available at http://www.bls.gov/cex/.
29

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Conclusion

While the Quarterly Food-at-Home Price Database (QFAHPD) provides reliable estimates of 

market-level food prices over time for food-at-home (FAH) products, complementary food-awayfrom-home (FAFH) and alcohol prices did not exist before. Other publicly available FAFH price 

data do not provide detail on how prices of disaggregated FAFH and alcohol products vary over 

time and geographic areas. Given the growing importance of FAFH to a typical American household’s food budget and diet, ERS researchers constructed Quarterly Food-Away-from-Home Prices 

(QFAFHP) and examined trends in FAFH and alcohol prices over time and across geographic areas.

ERS researchers used prices collected by the Bureau of Labor Statistics (BLS) for the Consumer 

Price Index (CPI) from 1998 to 2012 to construct average, weighted prices for 20 FAFH product 

categories for the Nation, the 4 census regions, and 9 census divisions. The prices are from four 

types of FAFH establishments: full-service restaurants, limited-service restaurants, schools, and 

vending machines. ERS calculated the prices using BLS’s complex survey design and sample 

weights so as to be representative at the census division, census region, and national level.

ERS finds that prices of products at full-service restaurants (including meals at inexpensive and 

moderately priced restaurants) and limited-service establishments vary significantly across census 

regions. In particular, ERS finds that regional prices are generally statistically significantly different 

from each other, whereas divisional prices differ less. Between 1998 and 2012, for all the products 

in the QFAFHP, the price of wine showed the highest average annual growth at about 5 percent 

across regions for wine at home and around 7 percent for wine away from home. Of the foods, 

prices of snacks from vending machines grew the most between 1998 and 2012, between 4 and 8 

percent, which is double the rate of meals at limited- and full-service restaurants (with the exception 

of Mexican-style meals).

ERS researchers also found differences in the way that prices trended over the sample period and 

during the 2007-09 recession. Prices paid for full-service meals began to decline in 2005 and were 

generally stagnant during the recession, but by 2010, they began to climb (except in the Northeast). 

Unlike full-service restaurants, limited-service restaurants showed no differences in price trends 

between the recession and non-recessionary periods.

Although FAFH is an important component in Americans’ diets, limitations in the recent publicly 

available data have precluded understanding how FAFH prices vary across the country, across 

establishment types, and across meal types. Likewise, researchers have lacked data on alcohol, 

despite its growing place in Americans’ food budgets and diets. QFAFHP aims to close these data 

gaps, facilitating more research on these important issues.
30

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

References

Basham, M. and J. Menza. 2007. “Industry Surveys: Restaurants.” Standard & Poor’s Industry 

Surveys, Vol. 175, No. 42, Section 1. Available online: http://homepage.smc.edu/thomas_phillip/

rpt/Restaurants.pdf.

Bureau of Economic Analysis (BEA). 2012. Concepts and Methods of the U.S. National Income and 

Product Accounts. Available online: http://www.bea.gov/national/pdf/methodology/chapters1-4.

pdf.

BEA. 2013. National Income and Product Accounts Table 2.5.4. Available online: http://www.bea.

gov/iTable/index_nipa.cfm.

Bureau of Labor Statistics (BLS). 2007. “The Consumer Price Index,” BLS Handbook of Methods, 

BLS. Washington, DC. Available online: http://www.bls.gov/opub/hom/pdf/homch17.pdf.

BLS. 2008a. “Checklist for ELI FV011 – Full Service Meals and Snacks.” Internal documentation.

BLS. 2008b. “Checklist for ELI FV012 – Limited Service Meals and Snacks.” Internal 

documentation.

BLS. 2013. Consumer Price Database: All Urban Consumers (Current Series). Available online: 

http://www.bls.gov/cpi/.

Chen, S.E., R.J. Florax, and S.D. Snyder. 2013. “Obesity and Fast-Food in Urban Markets: A New 

Approach Using Geo-referenced Micro Data,” Health Economics 22: 835-856.

Chou, S.-Y., M. Grossman, and H. Saffer. 2004. “An economic analysis of adult obesity: results 

from the Behavioral Risk Factor Surveillance System,” Journal of Health Economics 23(3): 

565-587.

Community and Economic Research (C2ER). 2010. Cost of Living Index: Manual. C2ER: 

Arlington, VA. Available online: www.coli.org/surveyforms/colimanual.pdf.

C2ER. 2012. ACCRA Cost of Living Index: Section 2 Average Prices. C2ER: Arlington, VA.

CSP Daily News. 2012. “Say (Grilled) Cheese,” CSP Business Media, LLC. Available online: http://

www.cspnet.com/news/foodservice/articles/say-grilled-cheese.

Currie, J., S. DellaVigna, E. Moretti, and V. Pathania. 2010. “The Effect of Fast Food Restaurants on 

Obesity and Weight Gain,” American Economic Journal: Economic Policy 2(3): 32-63.

Davis, B., and C. Carpenter. 2009. “Proximity of Fast-Food Restaurants to Schools and Adolescent 

Obesity,” American Journal of Public Health 99(3): 505-510.

Friddle, C. G., S. Mangaraj, and J. Kinsey. 2001. “Food Service Industry: Trends and Changing 

Structure in the New Millennium,” Working Paper 01-02. The Retail Food Industry Center, 

University of Minnesota.
31

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Huffman. W. E. 2011. “Household Production and the Demand for Food and Other Inputs: U.S. 

Evidence,” Journal of Agricultural and Resource Economics 36(3): 465-487.

Jeffrey, R.W., J. Baxter, M. McGuire, J. Linde. 2006. “Are Fast-Food Restaurants an Environmental 

Risk Factor for Obesity?” International Journal of Behavior Nutrition and Physical Activity

3(2):35.

Khan, T. L.M. Powell, and R. Wada. 2012. “Fast Food Consumption and Food Prices: evidence 

from panel data on 5th and 8th grade children,” Journal of Obesity. Vol. 2012, Article ID 857697. 

doi: 10.1155/2012/857697. http://dx.doi.org/10.1155/2012/857697

Kumcu, A. and E. Leibtag. 2011. The WIC Fruits and Vegetable Cash Voucher: Does Regional 

Price Variation Affect Regional Buying Power? EIB-75, U.S. Department of Agriculture, 

Economic Research Service.

Lin, B.-H., J. Guthrie, and E. Frazao. 1999. Away-From-Home Foods Increasingly Important 

to Quality of American Diet, AIB-749, U.S. Department of Agriculture, Economic Research 

Service.

Lin, B.-H., and J. Guthrie. 2012. Nutritional Quality of Food Prepared at Home and Away From 

Home 1977-2008, EIB-105, U.S. Department of Agriculture, Economic Research Service.

Lin, B.-H,, T.A. Smith, J.-Y. Lee, and K.D. Hall. 2011. “Measuring Weight Outcomes for Obesity 

Intervention Strategies: The Case of a Sugar-Sweetened Beverage Tax,” Economics and Human 

Biology 9(4): 329-341.

Mehta, S. and B. Maniam. 2002. “Marketing Determinants of Customers’ Attitudes Towards 

Selecting a Restaurant,” Academy of Marketing Studies Journal 6(1): 27-44.

Nielsen, S.J., M. Div, B.K. Kit, T. Fakhouri, C.L. Ogden. 2012. Calories Consumed From Alcoholic 

Beverages by U.S. Adults, 2007-2010. NCHS Brief No. 110. U.S. Department of Health and 

Human Services, Centers for Disease Control and Prevention, National Center for Health 

Statistics.

Okrent, A.M. and J.M. Alston. 2011. Demand for Food In the United States: A Review of the 

Literature, Evaluation of Previous Estimates and Presentation of New Estimates of Demand, 

Giannini Foundation Monograph 48. University of California: Berkeley, CA.

Okrent, A.M. and J.M. Alston. 2012. The Demand for Disaggregated Food-at-Home and FoodAway-from-Home Products in the United States, ERR-139, U.S. Department of Agriculture, 

Economic Research Service.

Ollinger, M., K. Ralston, and J. Guthrie. 2011. School Foodservice Costs: Location Matters, 

ERR-117, U.S. Department of Agriculture, Economic Research Service.

Powell, L.M., M.C. Auld, F.J. Chaloupka and L.D. Johnston. 2007. “Access to fast food and food 

prices: relationship with fruit and vegetable consumption and overweight among adolescents,” 

Advances in Health Economics and Health Services Research 17: 23-48.
32

Methodology for the Quarterly Food-Away-from-Home Prices Data, TB-1938

Economic Research Service/USDA

Rahkovsky, I. and C.A. Gregory. 2012. “Food Prices and Blood Cholesterol,” Economics and 

Human Biology 11(1): 95-107.

Reed, A.J., J.W. Levedahl, and C. Hallahan. 2005. “The Generalized Composite Commodity 

Theorem and Food Demand Estimation,” American Journal of Agricultural Economics 87(1): 

28-37.

Richards, T.J. and L. Mancino. 2013. “Demand for Food-Away-From Home: A Multiple DiscreteContinuous Extreme Value Model,” European Review of Agricultural Economics 41(1): 111-133.

Suter, P.M. 2005. “Is Alcohol Consumption A Risk Factor For Weight Gain and Obesity?” Critical 

Reviews in Clinical Laboratory Sciences 42(3): 197-227.

Sturm, R. and A. Datar. 2011. “Regional Price Differences and Food Consumption Frequency 

Among Elementary School Children,” Public Health 123(3): 136-41.

Todd, J.E., E. Leibtag and C. Penberthy. 2011. Geographic Differences in Relative Prices of Healthy 

Foods, EIB-78, U.S. Department of Agriculture, Economic Research Service.

Todd, J.E., L. Mancino, and B.-H.Lin. 2010. The Impact of Food Away From Home on Adult Diet 

Quality, ERR-90, U.S. Department of Agriculture, Economic Research Service.

Todd, J.E., L. Mancino, E. Leibtag, C. Tripodo. 2010. Methodology Behind the Quarterly Food-atHome Price Database, TB-1926, U.S. Department of Agriculture, Economic Research Service.

U.S. Census Bureau. 2007. 2007 Economic Census, Miscellaneous Subject Series. Available at 

http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml.

U.S. Department of Agriculture, Economic Research Service. 2013. Food Expenditure Tables. 

Available online: http://www.ers.usda.gov/data-products/food-expenditures.aspx

U.S. Department of Agriculture and U.S. Department of Health and Human Services. 2010. Dietary 

Guidelines for Americans, 2010. 7th edition, Washington, D.C. Available online: http://www.fns.

usda.gov/sites/default/files/PolicyDoc.pdf

Wendt, M. and J.E. Todd. 2011. The Effect of Food and Beverage Prices on Children’s Weights,

ERR-118, U.S. Department of Agriculture, Economic Research Service.

Whitehouse Task Force on Childhood Obesity Report to the President. 2010. Solving the Problem of 

Childhood Obesity Within a Generation. Executive Office of the President of the United States. 

Available online: http://www.letsmove.gov/sites/letsmove.gov/files/TaskForce_on_Childhood_

Obesity_May2010_FullReport.pdf.