Consumer Expenditure Survey 

Anthology, 2011

U.S. Department of Labor

U.S. Bureau of Labor Statistics

July 2011

Report 1030
ii

This is the fourth in a series of reports presenting 

articles discussing the U.S. Bureau of Labor 

Statistics (BLS) Consumer Expenditure Survey 

(CE). The most recent report, Consumer Expenditure 

Survey Anthology, 2008, was published in December 2008. 

As in the previous anthologies, articles discussing ongoing 

research and methodological issues pertaining to the CE, 

and analytical articles using the survey’s data, are included 

in this report.

The report was prepared in the Office of Prices and 

Living Conditions, Division of Consumer Expenditure 

Survey (DCES), under the general direction of Steve 

Henderson, Chief of the Branch of Information and 

Analysis, and was produced and edited by John M. Rogers, 

Section Chief. Articles on research and methodology were 

contributed by Lucilla Tan and Adam Safir of the Branch 

of Research and Program Development, Jennifer Edgar of 

the Office of Survey Methods Research, Barry Steinberg of 

the Division of Price Statistical Methods, and Brett Creech 

of the CE Branch of Information and Analysis. Analytical 

articles were contributed by Ann C. Foster, William Hawk, 

Craig J. Kreisler, and Geoffrey Paulin of the Branch of 

Information and Analysis.

Preface

BLS makes CE data available in news releases, reports, 

quarterly Focus on Prices and Spending articles, and articles 

in the Monthly Labor Review, as well as on CD-ROMs and the 

Internet. Current and historical CE tables classified by standard 

demographic variables are available at the BLS Internet site 

http://www.bls.gov/cex. This site also provides other survey 

information, including answers to frequently asked questions, 

a glossary of terms, order forms for survey products, and 

Monthly Labor Review and other research articles. To order 

on CD-Rom the Consumer Expenditure Survey microdata 

at the consumer unit level, go to http://www.bls.gov/cex/

csxmicro.htm.

The material that follows is divided into two sections: 

Section 1 includes articles on survey research and methodology, 

and section 2 presents analyses of topics of interest based on 

CE data. An appendix includes a general description of the 

survey and its methods and a glossary of terms.

Sensory-impaired individuals may obtain information on 

this publication upon request. Voice phone: (202) 691-5200, 

Federal Relay Service: 1 (800) 877-8339. The material 

presented is in the public domain and, with appropriate 

credit, may be reproduced without permission. For further 

information, call (202) 691-6900.
iii

Page

Part I. Survey Research and Methodology 1

Gemini Project overview 2

A major multiyear redesign of the Consumer Expenditure Survey has commenced.

The mission of the Gemini project is to promote improved expenditure estimates by

reducing measurement error.

Jennifer Edgar and Adam Safir

An introduction to the Contact History Instrument (CHI) for the

Consumer Expenditure Survey 8

The Contact History Instrument is designed to capture information about the data 

collection effort and the interviewer’s interactions with the respondent. An overview 

of the CHI is given, with examples of information that the CHI data provide about 

data collection efforts.

Lucilla Tan

CE source selection for publication tables 17

The methods used to select the appropriate survey—the Interview or Diary Survey—

for items published in CE data tables are described, and results are shown from the latest 

analysis.

Brett Creech and Barry Steinberg

Part II. Analyses Using Survey Data 21

Health care spending patterns of U.S. consumers, by age, 1998, 2003, and 2008 22

The share of total spending allocated to health care varies substantially by age group 

and has changed over the last decade.

Ann C. Foster and Craig J. Kreisler

How consumers used the 2008 tax rebates: spending, saving, or paying off debt 29

In 2008, the Internal Revenue Service mailed economic stimulus payments to more

than 130 million income tax filers. Data obtained from responses to supplemental 

questions to the Interview Survey component of the Consumer Expenditure Survey

were analyzed to see who received the payments and how they were used.

Geoffrey Paulin

Household spending by single persons and married couples in their 40

twenties: a comparison 

The twenties are a period of transition for consumers. Differences in spending patterns 

between the early and late twenties within the single and married-couple categories are 

examined, followed by a comparison between single persons and married couples in their 

early and late twenties.

William Hawk

Appendix A: Description of the survey 47

Glossary 48

Contents
Part I. 

Survey Research and Methodology

1
Jennifer Edgar is a research psychologist in the 

Office of Survey Methods Research, Bureau of 

Labor Statistics. 

Adam Safir is Branch Chief, Research and 

Program Development, Division of Consumer 

Expenditure Survey, Bureau of Labor Statistics.

Consumer Expenditure Survey Anthology, 2011 2

The Consumer Expenditure 

Survey (CE) program initiated 

the Gemini Project, a multiyear 

survey redesign effort, in early 2009. 

The mission of the project is to promote improved expenditure estimates 

in the CE by reducing measurement 

error. During the course of the project, 

CE program staff will develop, test, 

evaluate, and (as appropriate) implement survey design changes with the 

goals of improving overall data quality, 

increasing the analytic value of the data 

to users, and supporting greater operational flexibility to respond to changes 

in the data-collection environment. 

The changes being pursued through 

the Gemini Project will ensure that the 

CE satisfies its primary purpose: maintaining the integrity of the expenditure 

weights used in the Consumer Price 

Index (CPI). Consumer expenditure 

data supplied by the survey are a critical component in the calculation of the 

CPI because they are used to estimate 

weights for the CPI’s consumer goods 

and services classification structure. In 

the construction of the CPI, CE data 

serve four distinct functional uses: (1) 

to estimate annualized expenditures, 

(2) to estimate monthly expenditure 

weights, (3) to probabilistically select 

item categories for pricing, and (4) to 

allocate expenditure estimates between 

more broadly defined expenditure 

categories from other survey sources.1

Improved data quality also enhances the usefulness of CE data in 

meeting the needs of other data users, 

both public and private. Increasing the 

flexibility of survey operations allows 

the program to meet new data-quality 

challenges in a timely fashion. 

This article reviews the background, 

motivation, and challenges that affect 

the survey and the survey redesign 

effort specifically. The article also 

provides an overview of the project’s 

approach, major activities to date, and 

an overall timetable, paying particular 

attention to research topics affecting 

the redesign, as well as plans to investigate those topics. The article concludes 

with a summary of project accomplishments and plans for the future.

Gemini Project background

The overall goal of the Gemini Project 

is to improve data quality by reducing measurement error, which is the 

difference between the reality of a 

respondent’s situation—and what the 

respondent reports to the CE. A major focus will be on underreporting, 

including error at the individual-item 

level and at the larger-scale householdbudget level. The latter may not matter 

if the relative shares remain unbiased, 

but it ultimately is an important feature 

of underreporting that needs to be addressed. At the same time, a secondary 

goal will be to maintain or increase 

response rates; therefore, any expected 

benefits of survey design changes will 

be weighed against potential negative 

effects on response rates. 

Motivation for redesign

All household surveys today face 

challenges that affect response rates, 

including busy respondents, confidentiality/privacy concerns, competing 

surveys, controlled-access residences, 

and non-English-speaking households. 

In addition, the CE is faced with particular issues that directly affect the 

quality of the data collected. These issues, presented in order of importance, 

include a) evidence of measurement erJENNIFER EDGAR and

ADAM SAFIR

Gemini Project Overview

1 Casey, William. "CPI Requiments of CE," Internal 

Bureau of Labor Statistics Paper, 2010. Available online 

at http://www.bls.gov/cex/geminimaterials.htm.
 Consumer Expenditure Survey Anthology, 2011 3

ror in the survey data, b) environmental 

changes related to spending behaviors, 

c) a need for greater flexibility in the 

mode of data collection, and d) the 

ability to modernize data collection. 

The new design of the CE must address 

these issues. 

Reducing measurement error is the 

primary mission of the Gemini Project, 

yet as certain social behaviors and technological changes become more common, there is an increased likelihood of 

introducing measurement error to the 

survey. For example, purchases made 

online or recurring bill payments made 

by automatic debit may be less salient 

to respondents. Flexibility in CE datacollection strategies better positions 

the program to respond to such changes 

over the long term. Furthermore, while 

the spending behaviors that the CE 

seeks to measure have changed considerably over the past 30 years, the 

fundamental design of the survey has 

not. Although a number of improvements have recently been incorporated 

into the survey design, including the 

transition to a computer-assisted personal interviewing (CAPI) instrument 

in the Interview Survey, there has been 

no large-scale, comprehensive change 

to the survey design since 1980. 

Gemini Project objectives

The primary short-term objective of the 

Gemini Project is to develop a detailed 

redesign planning document. This 

document will describe the priorities, 

individual steps, timeframe, resource 

needs, and costs required to develop, 

pilot test, evaluate, and implement a 

redesigned CE. The redesign planning document will also guide the 

development and implementation of 

CE research studies throughout the 

Gemini Project lifecycle.

As previously noted, the long-term 

objectives of the redesign initiative 

are to introduce design changes in the 

CE that reduce measurement error, 

improve overall data quality, enhance 

the analytic value of CE data to users, and support a greater operational 

flexibility to respond to changes in 

the interviewing environment. These 

changes must occur within specified 

budget levels. Therefore, all proposed 

changes will be subject to budgetary 

constraints, and implementation decisions will be considered in terms of 

priorities and trade-offs. To allow for 

an unpredictable budgetary environment, the redesign planning document 

will address both a complete redesign 

of the CE as well as more limited. 

Gemini Project timeline

A high-level project timeline includes 

information gathering in 2009 and 

2010, to be followed by information 

synthesis and research planning in 

2011. By the end of 2012, the project 

aims to have a proposed redesign 

planning document in place for the 

development and implementation of 

a redesigned CE. The development, 

testing, and implementation of a redesigned survey will occur in 2013 and 

beyond. 

Redesign challenges

Even at the outset of the survey redesign process, a number of challenges 

are evident. Defining survey requirements is challenging, particularly given 

the CE’s diverse user community. 

Despite identifying the needs of varied users and reconciling competing 

interests, there are certain to be some 

users with unmet needs. Additionally, 

it is a challenge to gather, respond, 

and act on stakeholder concerns and 

suggestions while maintaining forward 

project progress. Finally, because of 

time constraints and uncertainty over 

the direction and nature of the forthcoming recommendations, the team is 

currently investigating several redesign 

topics, and this research will be used 

to support or reject some proposals. 

Ultimately, however, the redesign process is constrained by two overriding 

factors: the final survey design must 

produce the estimates required by the 

CPI, and, as mentioned above, longterm operational survey costs must 

keep to specified budget levels.

Project structure

The Gemini Project is composed of five 

teams, all of which report to the Gemini 

Steering Team. (See exhibit 1.) Each 

team addresses a specific objective 

that serves the overall Gemini mission. 

The Research Project Tracking System 

Team’s primary objective was to create 

a research database for all completed, 

in-progress, and proposed CE research 

projects that could potentially inform 

the survey redesign. This team has 

finished its work, and the Research 

Project Tracking System is currently 

in use. The Data Quality Definition 

Team’s objective is to produce a framework for assessing CE data quality, addressing both disparate user groups as 

well as key elements for an operational 

definition of data quality. The Data 

Quality Definition Team focused on 

six dimensions: relevance, accuracy, 

coherence, timeliness, accessibility, 

and interpretability.2

Three other teams were formed to 

plan, conduct, and summarize events 

that provide input and recommendations on issues related to the redesign. 

One of these teams—called the Data 

User Needs Forum Team— hosted an 

event in June 2010 where customers 

described their uses of the data, data 

requirements, priorities, and recommendations for changes. The team will 

summarize the findings from the forum 

and a subsequent user survey in a CE 

program office statement on CE data 

priorities.

The Conference Team held a Methods Workshop in December 2010. In 

addition, this team has organized a 

Survey Redesign Workshop where five 

Federal survey teams gave an overview 

of their redesign activities, and a Data 

Capture Technology Forum where 

Nielsen, National Opinion Research 

Center, RTI International, and Westat 

presented various technologies used 

to collect survey data. The Conference Team also organized a panel at 

the 2010 American Association for 

Public Opinion Research (AAPOR) 

on respondent record use. 

Finally, the User Impact Team 

(which is not yet formed) is charged 

with assessing the impact of possible redesigns on data user products. 

2

Brackstone, Gordan. "Managing Data Quality in a 

Statistical Agency." Survey Methodology. vol. 25 no. 

2, 1999, pp. 139-149.
Consumer Expenditure Survey Anthology, 2011 4

Major activities

Several major products have been, or 

will be, created as part of the Gemini Project. The first is the Research 

Project Tracking System (RPTS) and 

accompanying report. The RPTS is 

a database that enables status tracking for all proposed, approved, inprogress, completed, and deferred CE 

methods research projects that have 

the potential to influence the CE redesign. The system stores project information in an organized structure, 

providing a mechanism for Gemini 

Project teams to better align current 

and proposed projects with specific 

redesign needs.

The second major product is the 

Data Quality Definition Team’s report, which provides an operational 

definition of data quality for the CE 

program. The definition includes a 

statement of the procedures or ways 

in which the program should measure 

data quality, provides a framework 

for assessing the overall quality of 

CE survey data, and addresses the 

data usability concerns of individual 

program stakeholders. 

A third major product is a set of 

summary documents created after 

each Gemini Project event. These 

reports identify the presenters, key 

points, and implications of the event. 

For example, a document summarizing the Data Capture Technology Forum will serve as a starting point for 

future exploration into data collection 

technologies by identifying strengths 

and weaknesses of the technologies 

presented, and identifying possible 

avenues of additional research. 

The User Needs Team will create 

a report summarizing the input provided by data users. This input, along 

with similar input from the CPI, will 

be used to create a list of CE priorities 

that identify the minimally required 

elements of CE data, as well as secondary data requirements. This is an 

important document for the Gemini 

Project because it will serve as a key 

reference for all subsequent events 

and discussions regarding potential 

design alternatives.

Redesign topics

Topics for current discussion. Many 

different elements of survey methodology influence the plans of a survey redesign. Listed below are topics deemed 

most important for current discussion 

in planning a redesigned CE. These 

topics are addressed first because they 

are fundamental to making later, more 

tailored decisions about issues such 

as mode, technology, recall aids, and 

overall respondent burden. Key issues 

associated with each topic, including 

benefits and risks of related design 

alternatives that need to be explored 

early in the redesign process, are also 

described. 

Global questions. The Interview Survey averages 65 minutes.3

 The length 

is a result of both the breadth of expenditure categories included in the survey 

and depth of detailed information 

required for each category. The aim 

of the current Interview Survey is to 

collect information about every expenditure category from every household. 

One proposed approach to accomplish 

this objective (while also making the 

interview shorter) is to replace some 

of the detailed questions with global 

questions. Global questions ask about 

an expenditure category from an aggregate standpoint (for example, “How 

Exhibit 1. Gemini project structure

Group Objective Outputs

 Gemini Steering Team Oversee the Gemini Project Team charters, Gemini Project plan, redesign 

planning document

Teams

 Research Project Tracking System Team Create a research database for all completed, inprogress, and proposed CE research projects that 

potentially inform the survey redesign

Research Project Tracking System

 Data Quality Definition Team Produce an operational definition of data quality 

for CE and a framework for assessing CE data 

quality by its disparate user groups

Report summarizing a data quality definition 

and framework for CE

Conference Team Coordinate methodology events to solicit 

external input and recommendations on issues 

related to the redesign

•Survey Redesign Panel

•Data Capture Technology Forum

•Respondent Records Use AAPOR Panel

•CE Methods Workshop

Data User Needs Team Coordinate an event and survey to solicit input 

from data users on current use, requirements, and 

potential use of the data

 Report summarizing data user needs, priorities,

 and recommendations

 User Impact Team Identify the impact of possible redesign alternatives 

on data user

Report summarizing impact of proposed redesign 

alternatives on data users

After alternative designs have been 

proposed, this team will explore the 

impact of the redesign proposals on 

users and their uses of the data.

3

U.S. Department of Labor. Bureau of Labor Statistics. 

BLS Handbook of Methods. Washington: U.S. Government Printing Office: 2007
 Consumer Expenditure Survey Anthology, 2011 5

much did you spend on clothing?”), 

as compared with a detailed series of 

questions about individual expenditure 

types within the larger category (for 

example, “How much did you spend 

on shirts, pants, sweaters, vests, etc.?”). 

Replacing some of the detailed question sections with global questions 

would reduce the length of the survey 

while still providing high-level expenditure information about the given 

categories. However, the quality of 

data collected with global questions is 

debatable, and global questions have 

the potential to increase the cognitive 

burden of the respondent because of 

question difficulty. Both of these issues 

need to be further explored.

Interview structure. Currently the Interview Survey is a highly structured 

and standardized CAPI interview. The 

instrument is programmed to administer the questions in a set order, and 

the questions are designed to be read 

by the interviewer exactly as worded. 

The questions are organized into sections by topic (for example, housing, 

utilities, vehicle expenses, insurance, 

educational expenses, and so forth), 

a structure which forces respondents 

to report expenditures in a prescribed 

format, rather than allowing them to 

draw on information in a sequence 

that might be easier for them to recall. 

Nonstructured interviewing may hold 

promise for collecting higher quality 

data, but will require a very different 

approach to data collection. In addition, it is more difficult to administer 

and may require more skilled interviewers to ensure the collection of all 

required data. 

Proxy reporting. Currently only one 

respondent reports expenditures in 

both the Interview Survey and Diary 

Survey, answering questions for the 

entire household. The accuracy of the 

data provided by the proxy depends 

on the extent to which the respondent has detailed knowledge about 

the expenditures of other household 

members. Given the complexity of 

many household situations, a proxy 

respondent may often be unaware of, 

or unfamiliar with, purchases made 

by others in the household. One approach to eliminating proxy reporting 

is to collect information from each 

person, either through an individual 

diary or an interview. The impact on 

data quality and response rates, and the 

risk that the same expenditure will be 

reported by more than one household 

member, are all issues requiring further 

investigation.

Recall period. The Interview Survey 

currently asks respondents to report 

expenditures for the past 3 months. The 

length of this recall period, combined 

with the wide range of questions, may 

contribute to incomplete or less accurate reporting, and may also present 

a substantial cognitive burden for respondents. A shorter recall period may 

result in improved recall and therefore 

higher quality reporting; however, the 

potential increase in the number of 

interviews per household required to 

support annual estimates may negate 

the benefits of increased reporting accuracy or decreased respondent burden 

resulting from the change. An increase 

in the size of the sample could counter 

some of these drawbacks, but would 

incur a significant increase in survey 

costs and thus would not fit within the 

constraints presented for the redesign.

Split questionnaire design. Currently, 

all Interview Survey respondents are 

asked about the same set of expenditure categories during each interview. 

The resulting collected data are used 

to estimate average annual expenditures in the various categories at the 

household level. Covering the same set 

of expenditure categories with every 

respondent means that the interview is 

long and burdensome. It may be possible, however, to administer subsets of 

expenditure categories to separate subsets of respondents and still generate 

average annual household-level expenditure estimates. Calculation of these 

estimates may depend on the statistical 

capability to model the noncollected 

data (for imputation) or the willingness 

of the survey stakeholders to permit 

other types of data manipulation, such 

as matching similar households. 

Future topics 

In addition to the topics reviewed 

above, several other areas will be 

explored during the redesign process. 

Before a final redesigned CE can be 

developed, some topics should be 

addressed, including the use of administrative records or external data, 

mixed-mode designs, new technology, 

and recall aids. 

Administrative records/external data. 

Some of the information that the CE 

collects is also compiled by other 

sources. Use of external data could reduce respondent burden and potentially 

improve data quality. Whether these 

data can be used to reduce the amount 

of data that the CE collects depends on 

the availability of procedures to link or 

match CE sample units to external data, 

the quality of those data, and respondent willingness to allow the linkage. 

Mixed-mode designs. Offering more 

than one data collection mode has the 

potential to increase response rates 

and reduce nonresponse bias, although 

research evidence in this area is mixed. 

Because the Interview Survey was designed to be administered by personal 

visit, and a substantial percentage of 

cases are administered by telephone, 

redesigning the survey questions to 

be either mode-neutral or tailored 

more specifically to the mode of actual administration has the potential 

to improve data quality and reduce 

measurement error. 

New technology. New data collection 

technologies, such as personal digital 

assistants (PDAs), smartphones, or 

various types of scanning technologies, 

may have the potential to improve data 

quality, reduce respondent burden, and 

increase completion or response rates. 

Such electronic data capture devices 

eliminate information transfer from 

paper diaries to database, instead keeping the data in electronic form through-
Consumer Expenditure Survey Anthology, 2011 6

on data quality. The Interview Survey 

currently uses a 3-month reference 

period, which may be too long for 

respondents to reliably recall all types 

of expenditures; the test allows a 

comparison with data collected using 

a 1-month reference period. However, 

a shorter reference period may require 

more frequent data collection to allow 

for annual expenditure estimates, so 

understanding the impact of monthly 

data collection on response rates is the 

fourth goal of the study. 

The Order Effects Test study also 

examines questionnaire length. This 

test will provide data on whether the 

order of the interview section (that 

is, earlier or later placement) has an 

effect on the quality of data .This test 

randomly assigns first wave cases to 

one of two conditions. The first condition will have respondents proceed 

through the standard Interview Survey 

interview. The second condition moves 

a section from the middle of the Interview Survey to an earlier stage of the 

interview. If moving a section earlier 

in the interview significantly improves 

data quality, the results would support 

efforts to shorten the interview.

Over the past several years, the CE 

has explored the use of split questionnaire methods as an alternative to the 

current data collection procedures. 

These methods involve dividing a 

questionnaire into subsets of questions 

and then administering each subset to 

a subsample of respondents. Currently, 

the feasibility of this type of split questionnaire design is being investigated 

as one of the test conditions in the 

Measurement Issues Study, described 

above. Serving as a counterpart to the 

Measurement Issues Study, ongoing 

analyses use historical CE data to run 

statistical simulations investigating the 

value of an allocation method to assign 

survey items to groups of households 

based on previous waves of data. Since 

split questionnaire methods do not 

ask all survey items of all households, 

additional research has focused on 

methods to “fill-in” this missing data. 

Specifically, the CE has explored the 

use of imputation-based procedures to 

estimate from all households instead 

out the process. Additionally, the 

portability and potentially increased 

convenience of electronic data capture 

devices may lend an immediacy and 

ease of use to the recording process that 

may substantially reduce recall burden. 

Records and recall aids. Increased 

reliance and improved guidance on 

records, receipts, and recall aids, including electronic records, also has 

the potential to improve data quality. If 

the CE is able to identify a process to 

extract data from existing respondent 

records, respondent burden would also 

be reduced. 

Redesign-related research

To help make informed decisions in the 

redesign process, a number of research 

projects have either been initiated 

or are in the planning stages. These 

redesign-related research activities are 

presented below.

Current studies. Several research 

projects directly address the effect of 

questionnaire length on data quality 

and response rates. It is often assumed 

that the longer the questionnaire, the 

lower the quality of the data, and 

the less likely respondents will be to 

complete the entire interview, either 

in the current wave or in subsequent 

waves. The literature provides mixed 

results on the relationship between 

questionnaire length and data quality or 

response rates, with no clear implications for the CE. Therefore, the CE is 

exploring this issue directly.

The Measurement Issues study has 

four goals, two of which are to assess 

the impact of a shorter interview with 

a split questionnaire design and the use 

of global questions. By dividing the 

Interview Survey into portions and administering each portion individually, 

the study will be able to draw some 

conclusions about the impact of questionnaire length, as well as the quality 

of data obtained via global questions 

instead of detailed questions. In addition to studying questionnaire length 

and the use of global questions, the 

Measurement Issues study will also 

investigate the effect of recall period 

of only those households that were directly asked about a given expenditure 

category. Future research will look at 

refining the allocation and imputation 

procedures so that more efficient estimates can be obtained. 

Planned studies. There are two other 

key issues that need to be addressed 

through research before major redesign 

decisions can be made. The first issue 

is the effect of proxy reporting. As 

noted above, the CE program relies on 

one respondent to provide expenditure 

information for the entire household, a 

procedure suspected of being a major 

source of measurement error from 

underreporting. The Individual Diary 

Study will investigate the feasibility 

and impact of collecting data from all 

household members. This study will 

provide an individual diary to each eligible household member. The collected 

data will be analyzed for improvements 

in data quantity and quality over current production data, as well as the 

impact of the procedural change on 

collection costs and response rates. An 

online diary component is planned as 

part of this test. 

The second issue that the CE plans 

to address through research is measurement error. Comparison studies with 

external data, such as the Personal 

Consumption Expenditures, suggest 

that CE data may have significant measurement error, especially in certain 

categories. Currently, there is a limited 

understanding as to the sources of this 

error, and no estimates of the magnitude of the errors. The Records Study is 

planned to address both of these issues. 

In this study, participants will complete 

a partial CE interview. They will then 

be asked to locate all available records 

that are relevant to the expenditures 

covered in the interview. In a subsequent visit, interviewers will attempt 

to match the records with reported expenditures and to identify differences 

between the reported expenditures 

and those on the records. The comparison between reported expenditures 

and records-based information will 

provide estimates of the accuracy of 

the expenditure reports. A follow-up 
 Consumer Expenditure Survey Anthology, 2011 7

in-depth discussion with participants 

will also provide insight into the causes 

of the errors (for example, forgetting, 

comprehension difficulty, proxy issues, 

and so forth). 

Summary

Project accomplishments. The Gemini 

Project is designed to gather information on alternative survey designs and 

methodologies, to investigate the impact and feasibility of various options 

and propose relevant research, and to 

develop a planning document for redesigning the CE over approximately 

3 years. Much has been accomplished 

to date: project teams completed data 

quality and research tracking reports, 

and drafted issue papers on preliminary 

redesign topics (available online on the 

Gemini Project website at http://www.

bls.gov/cex/geminimaterials.htm). 

Additionally, in early 2010, several 

successful events were held to discuss 

issues related to the redesign, including 

a Survey Redesign Panel Discussion, a 

Data Capture Technology Forum, and 

a Data Users’ Needs Forum. 

Future plans. Looking ahead, the 

CE Steering Team is planning several 

major events and additional research 

studies. A methodological workshop 

focused on current research findings 

regarding interview structure, global 

questions, proxy reporting, recall period, and split questionnaire designs, and 

their implications for the CE redesign, 

was held in the fall of 2010. As an input 

to the methodological workshop, a 

review of current survey methods used 

in international consumer expenditure 

surveys will be prepared. In 2011, BLS 

plans to work with a consensus expert 

panel formed by the Committee on 

National Statistics (CNSTAT) to coordinate two events and produce a report 

with redesign recommendations based 

on the event discussions and other outside independent proposals. The 2011 

events will include a household survey 

data producer workshop designed to 

determine common challenges and 

best practices for large-scale household 

survey data producers, as well as a 

follow-up workshop to discuss options 

for the CE redesign, based on internal 

CE research, outside proposals, and 

input from the CNSTAT consensus 

expert panel. 
Lucilla Tan is an economist in the Branch of 

Research and Program Development, Division 

of Consumer Expenditure Survey, U.S. Bureau 

of Labor Statistics. 

Consumer Expenditure Survey Anthology, 2011 8

An Introduction

to the Contact History 

Instrument (CHI)

for the Consumer

Expenditure Survey

LUCILLA TAN

2

 Bates, N. (2003). Contact histories in personal visit surveys: the Survey of Income and 

Program Participation (SIPP) Methods Panel. 

AAPOR. http://www.fcsm.gov/committees/

ihsng/aapor2003proceedingforpdf.pdf 3

 Dyer, W. (2004). Contact History Instrument (CHI). http://www.blaiseusers.org/2004/

papers/03.pdf

The Consumer Expenditure Survey (CE) Program introduced the use of the Contact History 

Instrument (CHI) with the CE Interview 

Survey in April 2005 and for use with 

the CE Diary Survey in March 2006. 

The CHI is designed to capture information about the data collection efforts 

and the interviewer’s perceptions of 

interactions with the respondent when 

contact is made, regardless of whether 

an interview was conducted. Data 

from the CHI will be available for the 

first time with the 2009 CE Interview 

Survey public use microdata files. This 

article provides a brief overview of 

the CHI and a few illustrations of the 

insights that CHI data can provide about 

data collection efforts.

Background of the CHI 

In 2002, the Census Bureau and the 

Interagency Household Survey Nonresponse Group sponsored a Response 

Rate Summit conference. The purpose 

of the summit was to provide a forum 

for discussion among experts in the 

field about how to address concerns 

related to the decreasing response 

rate trend in household surveys.1 One 

of the recommendations that came 

out of the summit was that surveys 

should collect contact history information. This would provide data for 

two primary purposes: 1) to provide 

feedback to field staff about patterns 

that indicate what leads to successful or 

unsuccessful contact attempts, and 2) 

to provide data for a close examination 

of reasons for refusals, successful contact strategies, and differences between 

types of nonrespondents (refusals v. 

noncontact).2

The CHI was developed by the 

U.S. Census Bureau. It was designed 

to be a single instrument for use in all 

surveys that contract with the Bureau 

for data collection.3 The first version 

of the CHI was fielded for the National 

Health Interview Survey (NHIS) in 

January 2004, and the NHIS CHI data 

were made available for public use 

with the release of the 2006 NHIS 

public use files. In addition to the 

NHIS and the CE, the Current Population Survey adopted the CHI in August 

2009. 

Description of the CHI

The CHI is a software application separate from the survey data collection 

instrument. The interviewer can access 

CHI via the survey’s case management 

1

 Salvucci, S., Wenck, S., Hamsher, S., 

and Bates, N. (2002). Response Rate Summit: 

National Health Interview & Consumer Expenditure Quarterly Surveys. Summary Report. 

Synectics for Management Decisions, Inc., and 

U.S. Census Bureau. http://www.fcsm.gov/

working-papers/summitreportfinal.pdf
Consumer Expenditure Survey Anthology, 2011 9

system, or can launch CHI whenever 

the survey instrument is closed. The 

interviewer is instructed to record in 

the CHI every attempt made to contact 

the sample unit, and to do so as close as 

possible to the time the contact attempt 

was made.

The CHI prompts the interviewer 

for the following information about 

each contact attempt: the date and time 

of the attempt, the mode of the attempt 

(by personal visit or by phone), strategies the interviewer may have used to 

attempt to reach the respondent, and 

whether contact was made with the 

sample unit at that attempt. If the interviewer is unable to speak to someone 

at the sample unit, he or she can record 

reasons for noncontact. Alternatively, 

if the interviewer makes contact with 

the sample unit, the interviewer records whether or not an interview was 

conducted, and if so, whether it was 

partial or complete. If an interview 

could not be conducted, the interviewer 

records one or more reasons. In addition, regardless of whether there was 

an interview, the interviewer can record observations about the contacted 

sample unit member’s behavior and/or 

concerns regarding survey participation. Exhibit 1 shows an overview of 

the flow of questions through the CHI.

The reporting of contact attempt 

strategies (exhibit 2), reasons for noncontact by mode of attempt (exhibit 3 

for personal visit, exhibit 4 for phone), 

reasons for why an interview could 

not be conducted at a specific contact 

(exhibit 5), and the interviewer’s observations about respondent behavior 

and concerns (exhibit 6) are made from 

“check all that apply” lists of options 

that accompany each of these questions. Exhibits 2 through 6 are screen 

shots from the CHI that show the response options for these characteristics 

of contact attempts.

Illustrations of information describing data collection effort 

from CHI

In addition to interviewers’ notes 

recorded about a case, the CHI data 

constitute another source of information about interviewer-respondent 

interactions. The CHI data also provide 

insights to the overall data collection 

effort, and allow for the possibility of 

uncovering factors or behavior that 

promote or inhibit successful data collection. We offer a few illustrations of 

these insights, using CHI data from the 

CE Interview Survey for Interview 1 

cases fielded in 2009. CHI information 

at Interview 1 is of methodological 

interest, because it provides a systematic description of interviewer effort, 

likelihood of contact, and the nature of 

interactions with sample unit members 

who are approached for the first time 

in the survey. 

Effort expended to resolve a case.The 

number of contact attempts made to 

resolve a case with a final disposition 

is an indicator of the amount of effort 

interviewers exert to close out a case. 

A "final disposition" means that the 

interviewer closed out the case by 

classifying it as a completed interview, 

a noninterview, or ineligible (because 

the sample unit did not belong to the 

target population for the survey). The 

level of effort varies, but tends to be 

associated with the final disposition 

of the case. Completed interview cases 

are usually associated with relatively 

more cooperative respondents, and, 

thus, generally require fewer contact 

attempts to resolve the case. This fact 

is reflected in the CHI data. About 

70 percent of the 12,106 sample units 

in the 2009 sample (for which there 

were CHI data) had been resolved as 

completed interviews by the fourth 

contact attempt, as illustrated in chart 

1. Ineligible cases were also resolved 

fairly quickly—about 90 percent of 

these cases were classified as such by 

the fourth contact attempt. In contrast, 

relatively more effort was expended to 

resolve cases as noninterview—less 

than half of these cases were resolved 

by the fourth contact attempt, an 

indication that interviewers have to 

try harder to reach residents of these 

sample units, or that more attempts are 

needed before giving up on securing an 

interview. The CHI data also show that 

a lot of effort is expended to resolve 

the last 1 or 2 percent of cases still in 

the field. (It takes 15 or more contact 

attempts to resolve these cases.)

“Good” day-and-time combinations 

for first attempt to contact sample unit. 

Since costs are associated with each 

contact attempt, especially attempts 

made by personal visit, it would be 

cost effective if interviewers attempted 

to contact sample units at times when 

successful contacts and interviews are 

most likely to occur. The CHI data indicate that of the 12,106 first attempts 

made to contact sample units, 38.4 

percent were made between 8 a.m. and 

4 p.m. on Mondays through Thursdays, 

and 30.9 percent of those attempts 

resulted in contact with a sample unit 

member. (See chart 2.) However, it 

appears that evenings (4 p.m. to 9 p.m.) 

and weekends have slightly higher successful contact rates at first attempt. 

Therefore, interviewers may want to 

consider making a larger proportion of 

first attempts to contact sample units in 

the evenings and on weekends. 

Contact strategies attempted prior to 

first contact with sample unit. Among 

the 9,465 first contacts made with 

sample unit members, 86.3 percent 

were made by personal visit. An average of 2.2 attempts was made to obtain 

a first contact by personal visit and 3.5 

attempts to obtain a first contact by 

phone. An average of 1 strategy was 

used when a first contact with a sample 

unit member was made by personal visit (1.1 strategies), as well as by phone 

(1.2 strategies). The most frequently 

reported contact strategies used prior 

to first contact by both personal visit 

and phone were similar: “left appointment card or note with the sample 

unit,” “checked with neighbor,” and 

“advance letter given.” (See chart 3.) 

Reasons for incomplete interview 

or noninterview at first contact with 

sample unit. The primary reasons cited 

for an incomplete interview or noninterview at first contact with a sample 

unit are similar, regardless of whether 

first contacts were made by personal 

visit or by phone. The most frequently 

reported reason—more than a third of 
Consumer Expenditure Survey Anthology, 2011 10

9

 Bates, N., Dahlhamer, J., Phipps, P., Safir, 

A., and Tan, L. (2010). Assessing Contact 

History Data Quality and Consistency Across 

Several Federal Surveys. Paper to be presented 

at the Joint Statistical Meetings of the American 

Statistical Association. 

the sample unit refused the interview, 

and 3.1 percent as noninterview due 

to noncontact with the sample unit 

(no one home). There is also no verification that the correct reason for a 

noncontact is reported. Despite these 

limitations with the CHI data, survey 

methodologists have found information such as sample unit behavior and 

concerns reported by interviewers in 

the CHI to be very useful, especially 

in the absence of other information 

about nonrespondents. 

A study on the quality of the CHI 

data for the CE Interview Survey is 

currently underway. This study is a 

collaborative effort undertaken with 

the National Health Interview Survey 

and the Current Population Survey, the 

other two surveys that also utilize the 

CHI.9

 The study will examine how the 

CHI is being used by the three surveys, 

and compare findings from the CHI 

across the three surveys. Without a 

“gold standard” to evaluate the CHI 

data, this comparative approach will 

shed some light on the extent of consistency of the CHI data within and 

across the three surveys.

Summary

This article gave an overview of the 

Contact History Instrument (CHI) and 

provided illustrations of how the CHI 

data can provide information about 

the data collection effort. CHI data for 

the 2009 CE Interview Survey will be 

released with the 2009 CE Interview 

Survey public use microdata files. 

The CHI data included in the public 

use files are for Interview 1 through 

Interview 5, for all eligible cases (that 

is, completed interviews and noninterviews) that have CHI records. 

the time—was “inconvenient time” for 

the sample unit. (See chart 4.) The next 

most frequently cited reason was reluctance on the part of the respondent.

Respondent concerns, attitude, and/or 

behavior at first contact with sample 

unit and final disposition. Interviewer 

observations about the contacted sample unit member, regardless of whether 

an interview was conducted, appear to 

be associated with final disposition of 

a case. For example, nearly two-thirds 

of cases where interviewers reported 

that respondents were concerned about 

time (“too busy”, “interview too time 

consuming”) or privacy had a final 

disposition of “completed interviews.” 

(See chart 5.) In contrast, fewer than 

a third of cases where interviewers 

reported the contacted sample unit 

member exhibited hostility (“hang up/

slam door”, “hostile behavior”) had a 

final disposition of “completed interviews.” This is consistent with research 

studies supporting the usefulness of 

these interviewer-respondent interactions recorded in the CHI for predicting 

survey nonresponse.4 

Recent survey methodological 

studies on the Consumer Expenditure 

Interview Survey have drawn on CHI 

data in their analyses. For example, in 

a study that attempted to quantify the 

magnitude of relative nonresponse 

bias for key survey measures in the 

CE Interview Survey, respondents 

were classified as harder-to-contact 

when more than 45 percent of their 

contact attempts resulted in noncontact 

and were treated as proxies for nonrespondents.5

 In a study of the effect of 

incentives, indicators of respondent 

cooperation and estimates of field collection costs in the study were based 

on contact attempt information from 

the CHI.6

 In an exploratory study that 

examined trade-offs between fundamental survey performance measures 

for establishing the “optimal number” 

of contact attempts, CHI information 

were utilized to form comparison 

groups for analysis, and were inputs 

to the construction of a summary 

index for reporting quality.7 In another exploratory study, interviewer 

reported observations about respondent 

behavior and concerns about survey 

participation in the CHI were found 

to strongly differentiate between the 

risk of first occurrence of nonresponse 

between groups of respondents with 

different types of concerns.8 

Limitations of the CHI

A weakness of the CHI data is that 

it is based on each interviewer’s self 

reports. There is no mechanism to 

ensure that the interviewer enters 

every contact attempt for a case in the 

CHI, or that any contact attempt will 

be recorded for a case. For example, 

out of the 12,304 Interview 1 sample 

addresses fielded in 2009 for the CE 

Interview Survey, 1.6 percent (198 

cases) did not have any CHI records. 

Of these cases without CHI, 58.1 

percent were resolved as ineligible, 

28.3 percent as completed interviews, 

5.6 percent as noninterview because 

6

 Goldenberg, K.L., McGrath D.E., and Tan, 

L. (2009). "The effects of incentives on the 

Consumer Expenditure Interview Survey." Paper 

presented at the Annual Meeting of the American 

Association for Public Opinion Research. 7

 Safir, A., and Tan, L. (2009). Using Contact 

Attempt History Data to Determine the Optimal 

Number of Contact Attempts. Paper presented at 

the Annual Meeting of the American Association 

for Public Opinion Research. 8

 Tsai, S. and Tan, L. (2010). An exploratory 

study on the effect of pre-paid incentives on the 

first occurrence of nonresponse in the Consumer 

Expenditure Interview Survey. Internal BLSDCES Internal Report.

4

 Groves, R. and Couper, M. (1996). Contactlevel influences on cooperation in fact-to-face 

surveys. Journal of Official Statistics, 12, pp. 

63–68. 5

 King, S.L., Chopova, B., Edgar, J., Gonzalez, J.M., McGrath D.E., and Tan, L. (2009). 

Assessing nonresponse bias in the Consumer 

Expenditure Survey. Proceedings of the Section 

on Survey Methods Research, American Statistical Association, pp. 1808–1816.

 
Consumer Expenditure Survey Anthology, 2011 11

Are you making a contact attempt or just looking at a 

case?

1. Contact attempt 

2. Looking at a case. Exit

Are you entering the CHI at the 

time of a contact attempt?

1. Yes 

2. No

Exit CHI

Enter date (mm/dd/yy) and tme (hh:mm a.m./p.m.) of contact 

attempt

Was this a personal visit or telephone 

contact attempt?

1. Visit 

2. Phone

Outcome of contact attempt

1. Contact with sample unit member 

2. Contact with nonsample unit member

3. Noncontact

Outcome of contact

1. Case final disposition assigned, ready to 

transmit

2. Partial interview

3. Unable to conduct interview

Reasons for partial interview , 

or unable to conduct interview.

Enter all that apply: 

 1-8 for CE Diary Survey

 1-7 for CE Interview Survey

Noncontact (personal 

visit attempt). 

Select reasons. 

Enter all that apply 1-14.

Noncontact (phone 

attempt). Select reasons.

Enter all that apply 1-7.

Respondent concern/ behavior / reluctance

Select categories that describe respondent 

concerns, behavior, or reluctance during this 

contact attempt.

Enter all that apply 1-23.

Contact strategies attempted. 

Select the categories that describe the 

strategies used on this contact attempt.

Enter all that apply 1-23.

Exit CHI

Exhibit 1. Question Flow in Contact History Instrument 

2

1

2

 1 or 2

1

2 or 3

2 or 3

Attempt made 

by personal 

visit

1

1

Attempt made 

by phone

Enter date (mm/dd/yy) and time (hh;mm a.m./p.m.) of contact 

attempt
Consumer Expenditure Survey Anthology, 2011 12

Exhibit 2. CHI: response options for contact attempt strategies attempted

Exhibit 3. CHI: response options for contact attempt by personal visit resulting in noncontact

Exhibit 4. CHI: response options for contact attempt by phone resulting in noncontact

Exhibit 5. CHI: response options for unable to conduct or complete interview when contact is made with sample

unit.
Consumer Expenditure Survey Anthology, 2011 13

Exhibit 5. CHI: response options for unable to conduct or complete interview when contact is made with sample

unit.

Note: Both CE Interview Survey and CE Diary use the same Contact History Instrument. Option 7 is valid only for

the CE Diary.

Exhibit 6. CHI: response options for respondent behavior or concerns perceived by the interviewer when contact

is made with the sample unit.  
Consumer Expenditure Survey Anthology, 2011 14

2.3

38.4

27.3

7.5

4.1

9.0

4.0 4.1 3.2

24.8

30.9

40.8

31.8

34.1

38.0

32.3 32.9

37.7

Overnight Mon-Thu Day Mon-Thu Evening Fri Day Fri Evening Sat Day Sat Evening Sun Day Sun Evening

Percent

Day of week and time

Chart 2. Day and Time of 1st Contact Attempts and 1st Contact with Sample Unit 

2009 Consumer Expenditure Interview Survey, Interview 1

Percent distribution of 1st attempts (N=12,106) Percent of 1st attempts that resulted in contact (N=4,195)

NOTE: Day: 8:00 a.m. to 4:00 p.m. Evening: 4:00 p.m. to 9:00 p.m. Overnight: 9:00 p.m. to 8:00 a.m.

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20+

Cumulative percent

Number of contact attempts

Chart 1. Number of contact attempts to final case disposition

2009 Consumer Expenditure Interview Survey, Interview 1

Completed interview (n=7,364) Noninterview- refused(n=1,361) Noninterview-noncontact (n=421)

Noninterview - other(n=424) Ineligible sample units(n=2,536) Overall (n=12,106)

Chart 1. Number of contact attempts to final case disposition

2009 Consumer Expenditure Interview Survey, Interview 1

NOTE: Day: 8:00 a.m. to 4:00 p.m. Evening: 4:00 p.m. to 9:00 p.m. Overnight: 9:00 p.m. to 8:00 a.m.

Chart 2. Day and Time of 1st Attempts and 1st Contact with Sample Unit

2009 Consumer Expenditure Interview Survey, Interview 1

Percent distribution of 1st attempts (N=12,106) Percent distribution of 1st attempts that resulted in contact (N=4,195)

2.3

24.8

38.4

27.3

40.8

38.1

7.5

34.1

4.1

9.0

4.0 4.1

38.0

32.3

3.2

37.7

32.9

Overnight Mon-ThuDay Mon-Thu Evening Fri Day Fri Evening Sat Day Sat Evening SunDay Sun Evening

30.9

Days of week and time

Percent

Cumulative percent

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20+

Number of contact attempts

0

10

20

30

60

50

40

90

80

70

100
Consumer Expenditure Survey Anthology, 2011 15

28.6

8.4 7.3 7.3

2.1

5.7

59.1

16.6

12.6

17.6

12.6 10.6

Left 

note/appointment 

card

Checked with 

neighbor

Advance letter given Left promotional 

information

Left message on 

answering machine

Requested "No One 

Home" letter

Percent reporting

Strategy

Chart 3. Most frequently reported contact attempt strategies used 

prior to first contact with sample unit member

2009 Consumer Expenditure Interview Survey, Interview 1 

First contact by personal visit (N=8,167) First contact by phone (N=1,298)

68.4

19.4

12.4

4.7 3.0 2.6

65.2

19.4

4.3 6.9

0.6 1.5

Inconvenient time Reluctant 

respondent

Eligible person 

unavailable

Spoke with someone Language problem Health problem

Percent reporting

Reason

Chart 4. Reasons for incomplete interview or noninterview at first contact

2009 Consumer Expenditure Interview Survey, Interview 1

First contact by personal visit (N=4,574) First contact by phone (N=794)

Chart 3. Most frequently reported contact attempt stategies used prior to first contact with sample unit member

2009 Consumer Expenditure Interview Survey, Interview 1

Chart 4. Reasons for incomplete interview of noninterview at first contact

2009 Consumer Expenditure Interview Survey, Interview 1

Checked with Advance letter given

neighbor

Left

note/appointment

card

Left promotional

information

Left message on

answering machine

Requested "No One

Home" letter

Inconvenient 

time

Reluctant

respondent

Eligible person

unavailable

Spoke with someone Language problem Health problem

First contact by personal visit (N=4,574) First contact by phone (N=794)

Reason

Percent reporting

Strategy

68.4 65.2

19.4 19.4

12.4

4.3 4.7 6.9 3.0 0.6 2.6 1.5

Percent reporting

28.6

59.1

8.4

16.6

7.3

12.6

7.3

17.6

2.1

12.6

5.7

10.6

First contact by personal visit (N=8,167) First contact by phone (N=1,298)
Consumer Expenditure Survey Anthology, 2011 16

67.8

62.6 62.7

49.4

41.2

32.6

16.4

Too busy Too time consuming Privacy Anti-government Not interested Hang up/slam door Hostile behavior

Percent reporting

Concern

Chart 5. Selected respondent concerns reported at first contact and 

completed interviews

2009 Consumer Expenditure Interview Survey, Interview 1 

Percent of cases reporting concern that were completed interviews

Chart 5. Selected respondent concerns reported at first contact and completed interviews

2009 Consumer Expenditure Interview Survey, Interview 1

Too busy Too time 

consuming

Privacy Anti-government Not interested Hang up/

slam door

Hostile behavior

Concern

Percent of cases reporting concern that were completed interviews

Percent reporting

67.8

62.6 62.7

49.4

41.2

32.6

16.4
Brett J. Creech is an economist in the Branch 

of Information and Analysis, Division of Consumer Expenditure Survey, Bureau of Labor 

Statistics.

Barry P. Steinberg is a Mathematical Statistician in the Statistical Methods Division, 

Consumer Expenditures Survey, Bureau of 

Labor Statistics.

Consumer Expenditure Survey Anthology, 2011 17

CE Source Selection for 

Publication Tables

The Consumer Expenditure 

Survey (CE) is a nationwide 

household survey conducted 

by the U.S. Bureau of Labor Statistics 

(BLS) to find out how Americans 

spend their money. The CE consists 

of two components, each with its own 

questionnaire and sample: the Interview Survey and the Diary Survey. 

The data are collected for the BLS 

by the U.S. Census Bureau. There is 

some overlap in the information collected by the two surveys, and data 

from only one of the surveys are used 

for each item in the publication tables. 

Therefore, when expenditure information is collected about a particular item 

category in both surveys, a decision 

needs to be made about which source 

of information is the more reliable for 

publication purposes. 

In the Interview Survey, consumer 

units1

 (CUs) are visited once every 3 

months over a period of 13 months. 

The survey collects expenditures on 

items that respondents can reasonably recall for a period of 3 months 

or longer, such as furniture or vehicle 

purchases, and expenses that occur on 

a regular basis, such as rent, utility payments, and insurance premiums. In the 

Diary Survey, CUs report expenditures 

in two consecutive 1-week diaries. 

Although CUs are asked to report all 

of their expenditures in the diaries, the 

focus of the diaries is on the expenditures of frequently purchased items.

Background

Prior to 1980, the CE was conducted 

at about 10-year intervals. However, 

since 1980 it has been conducted as an 

ongoing survey. From 1980 to 1983, 

CE data were published separately for 

the Diary and Interview surveys, but 

beginning in 1984, selected data were 

chosen from each survey and combined to produce publication tables. 

Such integrated data from the BLS 

Diary and Interview Surveys provide 

a complete accounting of consumer 

expenditures and income that neither survey alone is designed to do. 

For example, the Diary Survey does 

not collect data on expenditures for 

overnight travel or information on reimbursements, whereas the Interview 

Survey does. Examples of expenditures for which reimbursements are 

not collected in the Diary Survey are 

medical care; automobile repair; and 

construction, repairs, alterations, and 

maintenance of property. The Interview Survey does not collect detailed 

food expenditures, or expenditures for 

housekeeping supplies, personal care 

products, and nonprescription drugs. 

These are items collected uniquely in 

the Diary Survey.

For items that are unique to one 

survey or the other, the choice of which 

survey to use as the source of data is 

obvious. This article briefly describes 

the methods employed to select the appropriate survey source for published 

survey estimates where there is overlap 

in coverage between the surveys.

1

 A consumer unit is defined as members of a 

household related by blood, marriage, adoption, 

or other legal arrangement; a single person living alone or sharing a household with others but 

who is financially independent; or two or more 

persons living together who share responsibility 

for at least 2 out of 3 major types of expenses—

food, housing, and other expenses. The terms 

consumer unit and household are often used 

interchangeably.

BRETT J. CREECH AND

BARRY P. STEINBERG
Consumer Expenditure Survey Anthology, 2011 18

Past methods of source 

selection 

Expenditure items in the current CE are 

identified using the Universal Classification Codes (UCC) system. A UCC is 

a six-digit code that classifies reported 

expenditures at the most detailed level. 

An example of a six-digit UCC is “Tolls 

or Electronic Toll Passes,” which is 

classified as UCC 520541. Selection 

of survey source for UCCs common to 

both the Diary and Interview Surveys 

was first conducted for tabulations of 

1984–86 data through an Estimated 

Mean Square Error (MSE) method 

that used 1982–84 data. This method 

added the variance of the CE data to the 

squared difference between the mean of 

the CE data and the Personal Consumption Expenditure (PCE) produced by 

the Bureau of Economic Analysis to 

produce an estimate of the MSE for each 

CE source. The source with the smaller 

MSE was chosen. The method of source 

selection was changed in 1997 and used 

CE data from 1993–95. A Coefficient of 

Variation (CV) was computed for each 

source, and the source with the smaller 

CV was selected. 

CE data are used extensively by the 

Consumer Price Index (CPI). In 2001, 

meetings were conducted at the request 

of the CPI group to look at differences 

in source selection between the CE 

and the CPI using 1999 data. At that 

time fewer than 15 UCCs had different 

sources between the two programs. It 

was recommended that the CPI adopt 

the CE source decision in all cases with 

greater than 50 reports of expenditures 

at the UCC level. Subsequently when 

new expenditure items and UCCs were 

introduced in 2005, source selection 

was coordinated so that the CE and the 

CPI were in agreement on the newly 

introduced UCCs.

In 2007, a team was formed with the 

task of reviewing the previous methods 

of source selection and developing 

a new quantitative methodology for 

selecting expenditure data from the 

two surveys.

CE coverage versus CPI 

coverage

The CPI is a measure of the average 

change over time in the prices paid by 

urban consumers for a market basket 

of consumer goods and services. The 

CE provides BLS with expenditure 

data that are used to calculate the relative importance of items in the market 

basket. One reason the CE and CPI 

used different sources in the past is 

that the population coverage of the CE 

differs from that of the CPI. The CPI is 

calculated for urban CUs, whereas the 

CE uses all CUs (urban and rural) in 

their calculations. Definitions of components also differ between the CE and 

the CPI. For example, homeownership 

is treated differently in the two surveys: 

actual expenditures of homeownership 

are reported in the CE, whereas the CPI 

uses a rental-equivalence approach 

that estimates the change in the cost 

of obtaining, in the rental marketplace, 

services equivalent to those provided 

by owner-occupied homes.

The CE publishes expenditures 

for items such as medical care and 

auto repair net of reimbursements by 

health insurance and vehicle insurance, respectively. Reimbursements for 

these expenditures are captured in the 

Interview Survey and are used in calculating out-of-pocket expenditures. 

The Diary Survey does not collect 

reimbursement data so expenditures 

for these items are necessarily taken 

from the Interview Survey. There are 

also transportation UCCs that are 

derived from information exclusively 

in the Interview Survey. For example, 

for a new car purchase, the value of 

any trade-in vehicles is deducted from 

the purchase price to calculate the net 

out-of-pocket expense for the new car. 

Other issues affecting source 

selection

A small number of UCCs are excluded 

from the source selection process. 

In some cases, the number of Diary 

Survey observations reported directly 

by respondents was so small that it disqualified the Diary Survey as a source. 

While the source selection methodology generally evaluates sources based 

on the number of expenditure reports 

over a given year, there are some items 

included in the chained C-CPI-U price 

index for which a sufficient number 

of monthly expenditure reports are 

required. In order to compare the 

monthly expenditure counts from both 

surveys, the Diary Survey’s monthly 

counts have to be adjusted upward 

to account for the Interview Survey’s 

longer recall period and larger sample 

size. During the 2007 source selection 

process, the source for four UCCs 

was based on a monthly comparison 

of adjusted Diary Survey counts to 

Interview Survey counts.

Source selection methodology

Implementing the source selection 

methodology involves a number of 

steps. Counts, sample means, and 

sample variances are calculated for 

each UCC. Before calculating means 

and variances, expenditure data are top 

coded and bottom coded to minimize 

the impact of outliers. Bottom coding 

is a form of censoring the data and is 

performed by applying the value of the 

1st percentile to replace all smaller values. Conversely, top coding applies the 

value at the 99th percentile to replace 

all larger values for each UCC. 

Next, the counts (each represents a 

reported expenditure for that UCC) and 

Z-Scores (defined below) are weighted 

for the three most recent collection 

years using the following scheme, 

which places greater emphasis on the 

more recent collection years:

• 1st collection year (oldest) by 1/6. 

(For 2007, 2004 data are used.)

• 2nd collection year (middle) by 

2/6. (For 2007, 2005 data are 

used.)

• 3rd collection year (most recent) by 3/6. (For 2007, 2006 

data are used.)

If a new UCC was created within 

the most recent 2 years or if there was 

a change in the collection instrument 

that caused a significant difference 

between the means in the years before 

and after the instrument change, then 

the 2 most recent years of data are 

analyzed. Counts and Z-Scores are 
Consumer Expenditure Survey Anthology, 2011 19

weighted with more emphasis given to 

the most recent collection year:

• 1st collection year (oldest) by 

2/5. (For 2007, 2005 data are 

used.)

• 2nd collection year (most recent) 

by 3/5. (For 2007, 2006 data are 

used.)

Source selection decision 

criteria

Definitions of the statistical terms used 

in the analysis are as follows:

1) UCC Mean—the weighted annual 

average expenditure for the CPI-U 

population using the adjusted full 

sample weight.

2) UCC Z-Score = 

XI = Annual UCC mean2 from the 

Interview Survey

X D = Annual UCC mean from the 

Diary Survey

I = Annual UCC population mean 

from the Interview Survey

D = Annual UCC population mean 

from the Diary Survey

2

XI

σ = Annual UCC variance from the 

Interview Survey

2

X D

σ = Annual UCC variance from the 

Diary Survey

With the null hypothesis that 

the team tested, Ho: = ∝∝ DI or

μμ DI =− 0 , the Z-Score represents the test of equality between 

the two weighted source means. The 

numerator is the difference between 

the sample means −− .0)( XX DI

The denominator is the standard deviation of that difference; it is assumed 

that the two surveys are statistically 

independent of each other. Variances 

are estimated using the method of Balanced Repeated Replications (BRR)3 

with 44 replicates. 

In order to determine which source 

to select for each UCC, the following 

decision criteria are used: 

Criterion 1: Counts Sufficiency. 

For each UCC and each survey, the 

number of CUs with at least one expenditure is counted for each of the 

3 most recent data collection years. 

This yields six counts for each UCC: 

three yearly counts for the Interview 

Survey and three yearly counts for 

the Diary Survey. These counts 

are used to ensure that a sufficient 

amount of data is available to make 

source selection decisions. A sufficient amount of data exists when 

the count for each of the 3 years is 

greater than or equal to 60.4

• If both surveys have sufficient 

data, then proceed to Criterion 2.

• If both surveys lack sufficient 

data, then keep the original 

source.

• If one survey has sufficient data, 

but the other has insufficient 

data, then a weighted average of 

the three yearly counts for the 

survey having an insufficient 

amount of data is computed: n* 

= (3/6)nt-1 + (2/6)nt-2 + (1/6)nt-3.

5 

• If the weighted average n* from 

the insufficient survey is greater 

than or equal to 60, then proceed to Criterion 2.

• If the weighted average n* from 

the insufficient survey is still 

less than 60, then use the survey with sufficient data as the 

source. 

Criterion 2: Statistical Significance. 

a) If the absolute value of the weighted 

Z-Score, z* = (3/6)zt-1 + (2/6)zt-2 + 

(1/6)zt-3, is greater than or equal to 

1.645 then select the source based 

on the following6:

• If the weighted Z-Score is 

greater than or equal to 1.645, 

then the Interview Survey is selected as the source.

• If the weighted Z-Score is less 

than or equal to –1.645, then the 

Diary Survey is selected as the 

source.

b) If the weighted Z-Score is between 

–1.000 and 1.000, then the current 

source will continue to be used.

c) If the weighted Z-Score is greater 

than 1.000 and less than 1.645 or 

less than –1.000 and greater than 

22

)()(

I XX D

XX DI DI

σσ

μμ

+

−−−

2

XI and X D represent the weighted 

means of collected data from the Interview and 

Diary Surveys, respectively. I and D

represent the population means for the Interview and Diary surveys, respectively, which are 

unknown. For the Z-score calculation, the null 

hypothesis tests that the difference between I

and D is zero.

3

 Balanced Repeated Replication (BRR) is a 

method of variance estimation used for sample 

survey statistics when the complexity of a survey’s sample design prevents standard classical 

variance estimation techniques from being used. 

BRR belongs to a class of variance estimation 

techniques that use replications. The basic idea 

behind replication is to select subsamples of the 

collected data repeatedly from the full sample, 

and then calculate the statistic of interest from 

both the full sample and from each sub-sample. 

These sub-samples are called replicates. The 

difference between the replicate estimates and 

the full sample estimate are then used to estimate 

the variance of the full sample statistic. 4

 The number 60 represents an average of 

five expenditures per month, which was found to 

be the minimum number of expenditures needed 

to produce stable results.

5

 For the equation n* = (3/6)nt–1 + (2/6)nt–2

+ (1/6)nt–3, t represents the evaluation year with 

the collection years being t–1, t–2, and t–3. 

For example, a 2007 evaluation will have t–1 

representing collection year 2006, t–2 representing collection year 2005, and t–3 representing 

collection year 2004. The same concept applies 

to z* = (3/6)zt–1 + (2/6)zt–2 + (1/6)zt–3 that will be 

mentioned later in the article. 6

 The value of 1.645 represents the 95th 

percentile of the standard normal distribution. 

It is often used in research as the critical value 

in determining statistical significance. On the 

left side of the standard normal distribution, the 

value of –1.645 represents the 5th percentile and 

is used in a similar manner. 
Consumer Expenditure Survey Anthology, 2011 20

–1.645, the following method is 

used to select the source:

• If all three Z-Scores are greater 

than 1.000, then the Interview 

Survey is selected as the source.

• If all three Z-Scores are less 

than –1.000, then the Diary Survey is selected as the source.

• In all other scenarios, the source 

remains the same.

2007 data results from the 

source selection process 

Table 1 lists the number of overlapping UCCs researched for source 

selection and the number of UCCs 

that changed sources. Out of approximately 900 UCCs, there were 222 

overlap UCCs that were researched, 

resulting in 22 changing sources. 

Eighteen changed because they had 

high Z-Scores (absolute values) and 

4 changed due to the Diary Survey 

failing the counts criterion, thereby 

switching to the Interview Survey. 

There were a total of 9 UCCs that had 

fewer than 60 observations in both 

surveys; therefore the source stayed 

the same. A total of 75 UCCs had 

observations in the Diary Survey that 

failed the counts criterion, thereby using the Interview Survey as the source. 

Only one UCC had an observation in 

the Interview Survey that failed the 

counts criterion. There were a total of 

94 UCCs that had high Z-Scores (their 

absolute values were greater than or 

equal to 1.645), 27 UCCs with low 

Z-Scores (their absolute values were 

less than 1.000) and 16 UCCs with 

Z-Scores between 1.000 and 1.645 or 

between -1.000 and –1.645. 

2009 results 

The source selection process implemented in 2007 was used to evaluate 

2006–08 data for the development of 

2009 estimates. Upon receiving a list 

of new UCCs, the source selection 

program was run on all UCCs having 

data in both the Interview and Diary surveys. The 3-year period from 

2006–08 was used for most UCCs, and 

2007–08 data for the newer UCCs. After calculating the expenditure counts 

and Z-Scores, the procedures identified 

six UCCs for which the applicable 

source selection criterion had changed. 

After further evaluation the source was 

changed for only two of them.

The source for two of these six 

UCCs had been changed in 2007 and 

it was decided not to change again in 

2009, to avoid an undue switching 

between sources every 2 years. Of the 

remaining four UCCs, it was decided to 

keep the Interview Survey as the source 

for two UCCs because of concerns 

about the consistency of the Diary 

Survey estimates. When the analysis 

was completed, two UCCs changed 

sources from the Diary Survey to the 

Interview Survey.

Summary 

Source selection is the process of 

choosing the better survey to use in 

CE’s official published expenditure 

estimates. It is a multistep process 

performed every 2 years for every 

overlapping UCC by comparing expenditure data from both the Interview 

and Diary Surveys using a counts criterion and weighted Z-Score approach 

to determine the better source for use 

in CE production. The method uses 

the previous 3 years of data when 

available, giving more weight to the 

most recent years. For new UCCs 

only 2 years of data are used. The 

data are adjusted for outliers in both 

the Interview and Diary Surveys. A 

number of criteria are then tested to 

determine which source to select. The 

first criterion assesses the number of 

unweighted consumer units making 

an expenditure for each UCC in each 

survey and may eliminate a source 

where an insufficient number of CUs 

report. The next criterion chooses the 

source that provides the larger overall 

expenditure per UCC. The means of 

reported expenditures, weighted by 

year, are compared from each survey using a standard Z-test, and in 

essence, the statistically significant 

larger mean is chosen.

The source selection process will 

continue to be run every 2 years. 

In addition to running the process, 

the CE will be looking for ways to 

accelerate the process by methods 

such as automation. Future research 

will also be performed to adapt the 

process for changes in survey instruments, collection methodology, and 

data processing.

Table 1. Number of overlap Universal Classification Codes (UCC)

 researched for source selection

UCCs

researched

UCCs changing

source

Total 222 22

UCCs for any year with observations less than 60 in both surveys 9 0

UCCs in which the observations in the Diary survey fail the counts criterion 75 4

UCCs in which the observations in the Interview survey fail the counts criterion 1 0

UCCs with Z-scores between –1.00 and 1.00 27 0

UCCs with Z- scores of +–1.00 and +–1.645 16 0

UCCs with Z- scores of –1.645 or less 68 17

UCCs with Z- scores of 1.645 or greater 26 1
Part II. 

Analyses Using Survey Data

Consumer Expenditure Survey Anthology 2011 21
Ann C. Foster is an economist in the Division 

of Consumer Expenditure Survey, Office of 

Prices and Living Conditions, Bureau of Labor 

Statistics.

Craig J. Kreisler is an economist in the Division of Consumer Expenditure Survey, Office 

of Prices and Living Conditions, Bureau of 

Labor Statistics.

Consumer Expenditure Survey Anthology, 2011 22

Health care spending 

patterns of U.S. 

consumers, by age,

1998, 2003, and 2008

ANN C. FOSTER and

CRAIG J. KREISLER T he National Health Care Expenditure Accounts (NHEA), the 

official estimates of total health 

care spending in the United States, 

show that in 2008, U.S. health care 

spending by business, governments, 

and households was $2.3 trillion, or 

$7,681 per person. The NHEA also 

shows that in 2008 health care spending was 16.2 percent of the gross domestic product (GDP), up from 13.5 

percent in 1998.1

NHEA estimates indicate that 

households accounted for 34 percent 

of spending on health services and 

supplies in 1998, 32 percent in 2003, 

and 31 percent in 2008. In 1998, household health care spending averaged 5.3 

percent of adjusted personal income, 

increasing to 5.8 percent in 2003, and 

5.9 percent in 2008.2

Although NHEA data supply a 

great deal of information to the Government and play an important role 

in health care policy decisions, they 

fail to provide a complete picture of 

how increases in health care spending 

influence household budget decisions. 

For this reason, Consumer Expenditure 

Survey (CE) data from the U.S. Bureau 

of Labor Statistics (BLS) are used to 

provide a snapshot of out-of-pocket 

health care spending changes among 

consumer units3 by age of the reference 

person4 in 1998, 2003, and 2008. This 

study examines changes in total health 

1

When the Centers for Medicare and Medicaid 

Services publish NHEA data for subsequent 

years, data from previous years often are revised. 

The NHEA data cited were those released with 

the 2008 estimates and accessed January 12, 

2010. NHEA data for 2009 were released on 

January 6, 2011, and the earlier data were replaced with newer data titled “National Health 

Expenditures by Type of Service and Source of 

Funds: Calendar Years 1960–2009” (U.S. Department of Health and Human Services, Centers 

for Medicare and Medicaid Services, Jan. 6, 

2011), on the Internet at http://www.cms.hhs.

gov/NationalHealthExpendData/downloads/

highlights.pdf (visited Jan. 6, 2011)

2

 Healthcare Services and Supplies (HSS), a 

subset of the NHEA, excludes Investment, the 

sum of medical sector purchases of structures and 

equipment and expenditures for noncommercial 

medical research. In 2008, HSS was $2.2 trillion 

compared with $2.3 trillion for the NHEA. A 

continued drop in the share of health care outlays 

represented by consumer out-of-pocket spending 

contributed to the decline between in household 

share between 1998 and 2005 when it reached 

31 percent where it has remained. Adjustments 

to personal income included adding contributions 

to social insurance for Medicare and excluding 

health benefit payments. This information is from 

“Sponsors of Health Care Costs: Business, Households and Governments, 1987-2008,” Centers 

for Medicare and Medicaid Services, Baltimore, 

MD, and was accessed on August 10, 2010. The 

data in this report were revised and updated and 

the report replaced with “Sponsors of Health Care 

Costs: Business, Households and Governments, 

1987–2009,” available online at www.cms.gov/

NationalHealthExpendData/downloads/bhg09.

pdf (visited Jan. 6, 2011). 

3

A consumer unit is defined as (1) all members of 

a particular household who are related by blood, marriage, adoption, or other legal arrangement, such as 

foster children; (2) a financially independent person 

living alone, sharing a housing unit with others, or 

living as a roomer in a private home, lodging house, 

or permanently in a hotel or motel; or (3) two or more 

persons living together who pool their incomes to 

make joint expenditures. For more information, see 

BLS Handbook of Methods, chapter 16, “Consumer 

Expenditures and Income” (updated 4/2007), available online at http://www.bls.gov/opub/hom/pdf/

homch16.pdf (visited October 25, 2010). 4

In the CE, the reference person is the first consumer unit member mentioned by the respondent 

when asked to "start with the name of the person 

or one of the people who owns or rents the home." 

It is with respect to the reference person that the 

relationship of the other consumer unit members is 

determined. For more information, see “Consumer 

Expenditure Survey Glossary,” available online 

at http://www.bls.gov/cex/csxgloss.htm#chars. 

(visited August 4, 2010).
Consumer Expenditure Survey Anthology, 2011 23

care spending in dollars as well as in 

the share of total annual expenditures. 

Changes in the distribution of health 

care spending by health care commodities and services are also examined. 

Data and methodology

This research uses CE data from 

the 1998, 2003, and 2008 Interview 

Survey collection years.5

 However, 

BLS provides integrated data from the 

CE Diary and the Interview Surveys 

online.6 For each year examined, this 

study sample consists of consumer 

units interviewed in that year who 

reported positive health care spending 

(net of any reimbursements) during 

an interview. Expenditure estimates 

presented for the collection year are 

annual estimates, whereas percent-reporting numbers are average quarterly 

estimates. Quarterly percent-reporting 

estimates are computed by adding up 

the number of consumer units reporting a positive health care expenditure 

during a given quarter and dividing 

this figure by the total number of 

consumer units interviewed during the 

quarter to obtain an average. Once the 

percent-reporting figures are obtained 

for all 4 quarters, an arithmetic mean 

of the 4 quarters is used to represent 

the average quarterly estimate. Annual expenditure means are computed 

by first summing up the total for an 

expenditure, such as health insurance 

premiums, for a given quarter, then 

annualizing the sum, and dividing by 

the number of consumer units reporting 

the expense. For each collection year, 

an arithmetic mean of the 4 quarters is 

used to represent an annual average.7

The expenses examined are total 

health care outlays and its associated 

components: health insurance, medical 

services, prescription drugs, and medical supplies. Nonprescription drugs, 

nonprescription vitamins, topicals 

and dressings, and medical equipment repair are not included in this

study because these expenses are collected from Diary Survey respondents 

only.

Health insurance includes premiums paid by consumers for private 

health insurance and Medicare. Private 

insurance includes coverage obtained 

individually or through a group plan 

sponsored by an employer or other 

organization. Medicare outlays are 

premiums paid for Medicare Part B and 

Medicare Part D coverage. Medicare 

Part B (Medical Insurance) helps cover 

physicians’ services and outpatient care 

and Medicare Part D covers prescription drugs.8

Medical services include physicians’, dental, eye care, and other professional services;9

 inpatient hospital 

care; lab tests and x-rays; other medical 

care services, such as hospital outpatient and emergency room care; and 

nursing home care. The prescription 

drug spending category is for outlays 

that are not connected to inpatient 

hospitalization. Medical supplies 

include the purchase of hearing aids, 

eyeglasses and contact lenses, and the 

purchase or rental of medical equipment for general use. For each year 

examined, findings will be reported for 

the total sample and by the age of the 

reference person. 

Findings

In 2008, nearly 78 percent of Interview 

Survey respondents reported making 

health care expenditures during a 

quarter, compared with 78.6 percent 

in 2003 and 80.4 percent in 1998. The 

proportion reporting expenses ranged 

from 42.3 percent among consumer 

units with a reference person under 

25 years old to 95.3 percent among 

consumer units with a reference person 

65 years and older in 2008; similar 

patterns were found for 1998 and 

2003, as chart 1 indicates. As table 1 

shows, among those with health care 

expenditures, in all years, average total 

expenditures increased with the age of 

the reference person up to 45–54 years 

and then declined. However, in all 

years, average total health care expenditures, in dollars and as a proportion 

(or share) of total annual expenditures, 

generally increased with age.

The proportion of total annual 

expenditures represented by health 

care went from 6.2 percent in 1998 

to 6.8 percent in 2003 and was virtually the same at 6.7 percent in 2008. 

Chart 2 shows that these averages 

varied among age groups. For example, 

among consumer units with a reference 

person age 25–34, the proportion of 

total annual expenditures represented 

by health care was 4.8 percent in 2008, 

compared with 4.6 percent in 2003 and 

4.4 percent in 1998. Among consumer 

units with a reference person 65 years 

and older, the proportion of annual 

expenditures represented by health 

care went from 12.6 percent in 1998 to 

13 percent in 2003, but was about the 

same (12.9 percent) in 2008. 

Health care component shares 

changed between 1998 and 2008. 

Health insurance premiums increased 

from about 52 percent of health care 

outlays in 1998 to nearly 58 percent 

in 2008. The most pronounced change 

was among consumer units with a 

reference person under 25 years old; 

5

Because of the rotating panel design of the 

Interview Survey, a collection year is different 

from a calendar year. For example, data for the 

first quarter of calendar year 2008 were collected 

in January, February, and March. Respondents 

interviewed in January were asked to recall 

expenditures made since the first of the month 

3 months prior to the interview, resulting in a 

reference period between Oct.1, 2007, and Dec. 

31, 2007. Similarly, respondents interviewed in 

February would have a reference period from 

Nov, 1, 2007, to Jan. 31, 2008. This means that 

respondents interviewed in January who were also 

interviewed in April, July, and October would 

have provided 4 quarters worth of data in collection year 2008. However, the data would cover a 

combined period from Oct. 1, 2007, to Sept. 30, 

2008, the last 3 months of calendar year 2007, and 

the first 9 months of calendar year 2008. For more 

information see “2008 Consumer Expenditure 

Interview Survey Public Use Microdata: User’s 

Documentation,” October 15, 2009, available 

online at http://www.bls.gov/cex/2008/csxintvw.

pdf. (visited August 4, 2010.)

6

For more information, see "2008 Consumer Expenditure Interview Survey Public Use Microdata: 

User's Documentation," October 15, 2009, available 

online at http://www.bls.gov/cex/2008/csxintvw.

pdf. (visited August 4, 2010). 

7

Annual pretax income and total consumption 

figures were derived in the same manner as the 

health expenditure means figures. 8

For more information, see “Medicare and 

You: 2010,” Centers for Medicare and Medicaid Services, Baltimore, MD, available online 

at http://www.medicare.gov/navigation/

medicare-basics/medicare-benefits/part-b.

aspx. (visited August 4, 2010.) 9

Spending on other professional services 

includes those provided by health professionals 

other than physicians, dentists, and optometrists. 

Among those professionals are chiropractors, 

acupuncturists, marriage counselors, nurse 

practitioners, podiatrists, physical therapists, 

psychologists, substance abuse professionals, 

and (certified) medical massage therapists. 
Consumer Expenditure Survey Anthology, 2011 24

health insurance was 47.9 percent 

of health care spending in 1998, 

compared with 59.1 percent in 2008. 

Despite this percentage increase, these 

consumer units still spent substantially 

less on health insurance than other 

groups. For consumer units with a 

reference person 65 years and older, 

the proportion of the health care budget 

represented by health insurance was 

similar in 1998 and 2003, 56 and 55.8 

percent, respectively, but was higher 

(63.5 percent) in 2008. (See chart 3 

and table 1.)

Spending on medical services 

dropped from 31.1 percent of total 

health care spending in 1998 to 25.9 

percent in 2008. The largest declines 

were for groups with a reference person under age 55. One reason may be 

increased enrollment in managed care 

plans, particularly preferred provider 

organizations (PPOs), which tend to 

have lower out-of-pocket costs than 

traditional fee-for-service (FFS) plans. 

Additional analysis of the insurance 

coverage of sample consumer units 

provides some support for this conclusion.

Table 2 presents information about 

sample consumer units with private 

coverage under a health maintenance 

organization (HMO), a PPO, or an 

FFS plan, and with Medicare Part B 

coverage. The proportions add up to 

more than 100 percent because some 

consumer units have members covered 

under different plans. For example, a 

married respondent may have private 

coverage under an HMO plan, but the 

respondent’s spouse may have coverage under Medicare Part B. In 1998, 

26.4 percent of the sample reported 

having an FFS plan, compared with 

14.8 percent in 2003 and 13.4 percent 

in 2008. Although FFS coverage declined among all groups, consumer 

units with a reference person age 55–64 

reported the greatest proportion of FFS 

coverage in all years surveyed.

For consumer units with a reference person 65 years and older, PPO 

coverage was higher in 2008 than in 

1998—15.0 percent compared with 

9.3 percent—but it still represented 

the lowest participation rate of all 

groups. Similarly, FFS coverage for the 

65-and-older group dropped from 27.2 

percent in 1998 to 14.2 percent in 2003 

and 2008, but it was still the second 

highest among all groups. 

Prescription drug spending increased from 13.1 percent of health 

care outlays in 1998 to 15.9 percent in 

2003, with all age groups experiencing 

increases. Between 2003 and 2008, 

overall prescription drug spending 

decreased to 13 percent of health care 

outlays, with all age groups showing 

declines, except those with a reference person age 35–44. The greatest 

decline during the period was for 

the 65-and-older group, attributable

to the introduction of Medicare Part

D.10 Medical supplies, a small proportion of health care spending, declined 

for the sample as a whole, from

4.3 percent in 1998 to 3.2 percent in 

2008.

Conclusions and implications

Among respondents with expenses, the 

proportion of annual expenditures for 

health care increased between 1998 

and 2003, but was unchanged in 2008. 

Whether this pattern will continue 

is uncertain because of the recession 

that began in December 2007. If poor 

economic conditions suppressed health 

care spending in 2008, then increased 

health care outlays relative to total 

consumption expenses are possible in 

the future.11

The share of total health care spending accounted for by various components changed during the period. In 

2008, the share of health care spending 

accounted for by health insurance premiums had increased while the share 

accounted for by medical services had 

decreased relative to 1998, possibly 

due to increased enrollment in managed care plans. 

The age of the reference person 

had an effect on health care spending. 

For example, the greatest decline in 

prescription drug spending was found 

for the 65-and-older group. However, 

increased spending on health insurance premiums resulted in virtually 

no change in the proportion of annual 

expenditures allocated to health care 

among this group.12

11 On September 20, 2010, the National Bureau of Economic Research determined that a 

trough in business activity occurred in the U.S. 

economy in June 2009. The trough marked the 

end of the recession that began in December 

2007 and the beginning of an expansion. For 

more informa¬tion, see “U.S. Business Cycle 

Expansions and Contractions,” Cambridge, 

MA, National Bureau of Economic Research, 

available online at http://www.nber.org/cycles/

cyclesmain.html (visited October 12, 2010).

An NHEA report indicates that household outof-pocket health care spending (which excludes 

insurance premiums and contributions to Medicare) decelerated from 6 percent in 2007 to 2.8 

percent in 2008. It was concluded that the slower 

growth may be because poor economic conditions have forced households to reduce health 

care spending by forgoing treatment. For more 

information, see “Sponsors of Health Care Costs: 

Private Business, Households and Governments, 

1987–2008,” available online at www.cms.

gov/NationalHealthExpendData/downloads/

bhg09.pdf (visited August 10, 2010).

12 In 2008, the average Medicare Part

D base beneficiary monthly premium was 

$27.93. The Part B standard monthly premium 

was $96.40, but there is a higher “incomerelated” premium for those individuals whose 

modified adjusted gross income exceeds a 

specified threshold. For more information, see 

“2009 Annual Report of the Boards of Trustees 

of the Federal Hospital Insurance and the Federal 

Supplementary Medical Insurance Trust Fund,” 

May 12, 2009, Centers for Medicare and Medicaid Services, Baltimore, MD, available online at 

http://www.cms.hhs.gov/ReportsTrustFunds/ 

(visited August 10, 2010).

10 Additional analysis of 2008 data found that 

37.6 percent of consumer units with a reference 

person 65 years and over had one or more members with Medicare Part D coverage. Existing research has found that Medicare Part D coverage 

reduced user cost among the elderly in 2006. For 

more information, see Schneeweis, Sebastian, 

Amanda R. Patrick, Alex Pedan, Laleh Varasteh, 

Raisa Levin, and William H. Shrank, “The Effect of Medicare Part D Coverage on Drug Use 

and Cost Sharing Among Seniors without Prior 

Drug Benefits,” Health Affairs, February 2009, 

pp. w305–w316, and Lichtenberg, Frank R. and 

Shawn X. Sun, “The Impact of Medicare Part 

D on Prescription Drug Use by the Elderly,” 

Health Affairs, volume 26, number 6, November/

December 2007, pp. 1735–44.
Consumer Expenditure Survey Anthology, 2011 25

Table 1. Average income before taxes, annual expenditures, total health care; total health care spending shares of annual

expenditures; health insurance, medical services, prescription drugs, and medical supplies share of total health care

spending, by age of reference person, 1998, 2003, and 2008

Item

All consumer units Under 25 25–34

1998 2003 2008 1998 2003 2008 1998 2003 2008

Income before taxes $44,576 $54,949 $69,465 $22,118 $28,026 $39,415 $46,559 $56,182 $68,333

Average annual

expenditures

$35,592 $42,435 $53,785 $22,210 $27,966 $36,467 $36,942 $42,664 $53,167

Total health care $2,204 $2,882 $3,591 $922 $1,283 $1,449 $1,613 $1,953 $2,533

Share of average annual

expenditures

6.2 6.8 6.7 4.2 4.6 4.0 4.4 4.6 4.8

Health insurance $1,134 $1,563 $2,080 $442 $666 $856 $840 $1,151 $1,498

Medical services 685 766 931 330 426 392 585 571 745

 Prescription drugs 289 458 468 102 143 158 127 176 217

 Medical supplies 96 95 113 48 48 43 62 54 73

Shares of total health

care

 Health insurance 51.5 54.2 57.9 47.9 51.9 59.1 52.0 59.0 59.1

 Medical services 31.1 26.6 25.9 35.8 33.2 27.0 36.3 29.2 29.4

 Prescription drugs 13.1 15.9 13.0 11.0 11.1 10.9 7.8 9.0 8.6

 Medical supplies 4.3 3.3 3.1 5.2 3.7 2.9 3.8 2.8 2.9

SOURCE: U.S. Bureau of Labor Statistics, Consumer Expenditure Interview Survey
Consumer Expenditure Survey Anthology, 2011 26

Table 1. Average income before taxes, annual expenditures, total health care; total health care spending shares of annual

expenditures; health insurance, medical services, prescription drugs, and medical supplies share of total health care

spending, by age of reference person, 1998, 2003, and 2008—Continued

Item

35–44 45–54

1998 2003 2008 1998 2003 2008

Income before taxes $55,180 $66,621 $86,709 $62,178 $72,653 $88,961

Average annual

expenditures

$42,689 $50,160 $64,195 $45,492 $52,952 $64,746

Total health care $1,975 $2,589 $3,022 $2,323 $2,900 $3,442

Share of average annual

 expenditures

4.6 5.2 4.7 5.1 5.5 5.3

Health insurance $1,012 $1,436 $1,730 $1,088 $1,443 $1,837

Medical services 705 801 881 879 912 1,056

 Prescription drugs 166 270 324 241 426 419

 Medical supplies 91 82 87 114 120 130

Shares of total health care

 Health insurance 51.3 55.5 57.2 46.8 49.7 53.4

 Medical services 35.7 30.9 29.2 37.8 31.4 30.7

 Prescription drugs 8.4 10.4 10.7 10.4 14.7 12.2

 Medical supplies 4.6 3.2 2.9 4.9 4.1 3.8

55–64 65 and older

1998 2003 2008 1998 2003 2008

Income before taxes $45,288 $60,415 $75,422 $24,095 $30,420 $39,683

Average annual

expenditures

$36,578 $44,844 $57,654 $22,363 $27,848 $36,178

Total health care $2,411 $3,382 $4,204 $2,812 $3,624 $4,658

Share of average annual

 expenditures

6.6 7.5 7.3 12.6 13.0 12.9

Health insurance $1,164 $1,798 $2,268 $1,574 $2,020 $2,956

Medical services 787 898 1,175 587 707 866

 Prescription drugs 361 577 632 537 788 697

 Medical supplies 98 109 129 114 108 140

Shares of total health care

 Health insurance 48.3 53.2 54.0 56.0 55.8 63.5

 Medical services 32.6 26.6 27.9 20.9 19.5 18.6

 Prescription drugs 15.0 17.1 15.0 19.1 21.7 15.0

 Medical supplies 4.1 3.2 3.1 4.1 3.0 3.0

SOURCE: U.S. Bureau of Labor Statistics, Consumer Expenditure Interview Survey
Consumer Expenditure Survey Anthology, 2011 27

Table 2. Percentage enrollment in HMO, PPO, FFS plans, and Medicare Part B, by age of reference person,

1998, 2003, and 2008

Item

All consumer units Under 25 25–34 35–44

1998 2003 2008 1998 2003 2008 1998 2003 2008 1998 2003 2008

HMO 52.2 45.5 36.0 47.6 39.4 38.4 67.8 56.2 40.5 61.3 50.8 40.6

PPO 23.0 30.2 32.5 24.1 30.3 27.7 26.2 36.6 38.8 27.6 36.2 37.8

FFS 26.4 14.8 13.4 21.2 14.1 10.5 22.1 10.9 10.9 21.0 13.4 11.3

Medicare 

Part B

28.7 27.3 31.1 1.9 2.1 4.8 2.4 2.9 3.9 5.2 5.4 6.5

Item

45–54 55–64 65 and older

1998 2003 2008 1998 2003 2008 1998 2003 2008

HMO 59.1 54.9 37.6 54.1 47.7 39.5 28.1 26.2 25.4

PPO 30.7 37.5 40.4 25.8 34.2 37.2 9.3 12.4 15.0

FFS 31.4 15.9 14.7 34.1 20.2 15.6 27.2 14.2 14.2

Medicare 

Part B

6.7 7.8 10.6 19.9 19.2 24.4 93.2 86.1 93.4

Chart 1. Average percent reporting health care expenditures by age of reference person,

1998, 2003, and 2008

In percent

100

90

80

70

60

50

40

30

20

10

0

All households

reporting

expense

Under 25 years 25–34 years 35–44 years 45–44 years 55–64 years 65 years

and older

SOURCE: U.S. Bureau of Labor Statistics, Consumer Expenditure Interview Survey

1998 2003 2008

SOURCE: U.S. Bureau of Labor Statistics, Consumer Expenditure Interview Survey
Consumer Expenditure Survey Anthology, 2011 28

Chart 2. Average health care spending shares of total annual expenditures by age of reference person, 1998, 

2003, and 2008

In percent

14

12

10

8

6

4

2

0

All households

reporting

expense

Under 25 years 25–34 years 35–44 years 45–44 years 55–64 years 65 years

and older

SOURCE: U.S. Bureau of Labor Statistics, Consumer Expenditure Interview Survey

1998 2003 2008

Chart 3. Distribution of total health care spending, by type of expense, 1998, 2003, and 2008

Medical supplies

Prescription drugs

Medical services

Health insurance

100

90

80

70

60

50

40

30

20

10

0

In percent

1998 2003 2008

SOURCE: U.S. Bureau of Labor Statistics, Consumer Expenditure Interview Survey
Consumer Expenditure Survey Anthology, 2011 29

GEOFFREY PAULIN

How Consumers Used 

the 2008 Tax Rebates: 

Spending, Saving, or 

Paying Off Debt 

I

n May 2008, the Internal Revenue 

Service (IRS) started mailing 

Economic Stimulus Payments 

(also called tax rebates) to more than 

130 million income tax filers.1 In 

June 2008, the Interview component 

of the Consumer Expenditure Survey 

(CE) started collecting information on 

receipt and use of these payments, a 

process that continued through March 

2009. Information, such as amount of 

payment received, form in which it was 

received (electronic funds transfer or 

check), and how payment was used 

(mostly for spending, saving, or paying 

off debt) was collected. (The appendix at the end of this article shows the 

questions as asked in the survey.) This 

report examines the data collected to 

find out what types of consumers received payments, the form(s) in which 

they were received, and how payments 

generally were used by consumers.

The payments

For those who owed taxes, most were 

eligible to receive a maximum of $600 

per filer, or $1,200 for married couples 

filing jointly. Filers with no net tax liability but at least $3,000 in qualifying 

income were eligible for payments of 

half these amounts (that is, $300 per 

Geoffrey Paulin is a senior economist in the 

Branch of Information and Analysis, Division 

of Consumer Expenditure Survey, Bureau of 

Labor Statistics.

filer, or $600 for married couples filing 

jointly). In each case, recipients were 

eligible to receive an additional $300 

for each child who was younger than 

17 years old on December 31, 2007.2 

However, payments were phased out 

for higher income filers, starting at 

$75,000 in adjusted gross income for 

singles, and $150,000 for married 

couples filing jointly. For every dollar 

over the limit, stimulus payments were 

reduced by 5 cents. For example, a 

married couple with two qualifying 

children and $160,000 in adjusted 

gross income would be eligible to 

receive $1,300 in payments.3 

The data

Nearly 7,000 consumer units (see glossary) were interviewed each quarter 

during the collection period, which ran 

from June 2008 through March 2009. 

Although the total sample in each of 

these four quarters was over 27,500, 

only half were unique consumer units, 

because some units were visited more 

than once. Of these, more than 5,600 

provided information on receipt of 

the payment, and over 5,300 provided 

information on use of the payment. 

(See tables.)

1

Facts about the Economic Stimulus Payments,” http://www.irs.gov/newsroom/

article/0,,id=179095,00.html, FS-2008–15, 

February 2008, last reviewed or updated: 12 Dec 

2008 (December 12, 2008), visited 8/24/2009.

2 Economic Stimulus Payment Q&As: Eligibility,” http://www.irs.gov/newsroom/

article/0,,id=179181,00.html, initially updated 

July 16, 2008; last reviewed or updated: 12 Dec 

2008 (December 12, 2008), visited 8/24/2009. 3

 Ibid., visited 8/24/2009.
of rebate received, although number 

of earners peaks for those aged 45 to 

54 years, instead of for those aged 

35 to 44 years. However, the amount 

received follows the age and income 

patterns for qualifying children; that 

is, number of persons less than 18 also 

peaks for 35- to 44-year olds, and for 

those with incomes in the highest range. 

The average size of each rebate is larger 

for consumer units receiving a single 

rebate than for those receiving multiple 

rebates. On average, consumer units receiving one rebate received $910, while 

consumer units receiving two or more 

rebates received $1,352. (See table 1.) 

Therefore, the average rebate for those 

receiving two or more is less than $676 

(that is, less than $1,352 divided by 2).

In general, there was little difference 

in the average amount of the rebate 

received for those who mostly spent 

($926) or saved ($936) it. (See table 

5.) However, those who used the payment mostly to pay off debt had larger 

rebates, on average ($995), than the 

others.

The aggregate amount of all tax rebate receipts reported in the CE, $94.6 

billion, closely matched the $95.7 billion total of all tax rebates reported by 

the Internal Revenue Service.

Use of the rebate. Nearly half (49 

percent) of recipients reported using 

the rebate mostly to pay off debt. 

(See chart 1.) Recipients of multiple 

rebates were a little more likely (53 

percent) to use the payment in this 

way than recipients of one rebate (49 

Findings

Amounts received. For those receiving at least one stimulus payment, the 

amount reported ranges from $6 to 

$4,800, with an average of $958. (See 

table 1.) Amounts varied as expected 

with demographic characteristics. 

For example, consumer units with 

qualifying children received more, 

on average, than their counterparts 

without children. (See table 2.) The 

average received rises with age of reference person (see glossary) through 

the 35-to-44-year-old group, and then 

declines. (See table 3.) Generally, the 

amount also rises with income, peaking 

for the $70,000-and-over range. (See 

table 4.) For both age and income, the 

number of earners in the consumer unit 

follows a pattern similar to the amount 

Table 1. Number of tax rebates reported, Consumer Expenditure Interview Survey, June 2008–March 2009

Item All consumer 

units

No rebate 

reported

At least 

one rebate 

reported

One rebate 

reported

Two or more 

rebates 

reported

Sample size 13,803 8,151 5,652 5,032 620

Income before taxes $63,197 $63,937 $62,128 $60,857 $72,446

Age of reference person 48.5 47.3 50.3 50.4 49.5

Average number in consumer unit:

Persons 2.5 2.4 2.6 2.6 3.1

Children under 18 .6 .6 .7 .7 .7

Earners 1.3 1.2 1.4 1.3 1.8

Rebate information:

Average amount received $392 $0 $958 $910 $1,352

Percent distribution:

Receiving no rebate 59.1 100.0 0.0 0.0 0.0

Receiving one rebate 36.5 0 89.0 100.0 0

Receiving two or more rebates 4.5 0 11.0 0 100.0

Rebate reporters only

Receiving at least one rebate by:

Check 60.5 0 60.5 59.3 69.8

Electronic funds transfer (EFT) 40.0 0 40.0 39.0 48.1

No information (invalid blank) 1.9 0 1.9 1.7 3.1

Asked how rebate was used: 94.7 0 94.7 94.5 96.8

If asked how rebate was used:

Rebate was used mostly for:

Spending 30.2 0 30.2 30.5 28.2

Saving 17.6 0 17.6 18.0 14.5

Paying off debt 49.1 0 49.1 48.6 52.8

No information (invalid blank) 3.0 0 3.0 2.9 4.5

Consumer Expenditure Survey Anthology, 2011 30
percent). (See table 1.) Less than 

one-third (30 percent) of recipients 

reported mostly spending the rebate, 

and less than one-fifth (18 percent) 

reported mostly saving the rebate. The 

remainder (3 percent) did not know or 

refused to report how the rebate was 

mostly used.

In one way, the youngest consumers (those under 25) were more like 

older consumers (those aged 55 and 

older) than those closer to their own 

age. (See table 3.) About one third (34 

percent) of the youngest consumer 

units spent the rebate, while fewer 

(25 to 30 percent) of those aged 25 

to 54 did. However, well over half 

of those aged 25 to 54 used the rebate 

to pay off debt, compared with well 

under half for those aged under 25 

or 55 and older; for the latter group, 

this use appears to decrease with age, 

because for those 75 and older, only 

one-third (33 percent) used the rebate 

to pay off debt. The oldest group was 

also the most likely to save the rebate 

(31 percent). They were followed by 

the second oldest group (23 percent). 

Those under 65 were less likely to 

save the rebate (13 to 17 percent).

Consumer units with at least one 

parent and at least one qualifying 

child were about two to two-andone-half times more likely to use the 

rebate to pay off debt than they were 

to spend it. (See table 2.) However, 

single parents (6 percent) were less 

likely to save the rebate than husband 

and wife families with children (15 

percent). Similar consumer units 

without children (husband and wife 

only or single person 18 or older) 

were similar to each other in their 

propensities to allocate these funds: 

Less than one third spent the rebate; 

Table 2. Tax rebate data, classified by presence of qualifying child, Consumer Expenditure Interview Survey, June 2008–March 2009

Item

All 

consumer 

units

Husband and 

wife, at least 

one qualifying 

child

Single parent, 

at least one 

qualifying child

Husband 

and 

wife only

Single person, 

18 years or 

older 1

All other

 consumer 

units

Sample size 13,803 2,817 845 2,943 4,094 3,104

Income before taxes $63,197 $94,280 $35,575 $75,895 $32,450 $71,020

Age of reference person 48.5 39.4 38.1 57.8 51.1 47.4

Average number in consumer unit:

Persons 2.5 4.1 3.0 2.0 1.0 3.3

Children under 18 .6 2.0 1.8 0 0 .6

Earners 1.3 1.8 1.0 1.2 .6 1.9

Rebate information:

Average amount received $392 $646 $318 $453 $170 $417

Percent distribution:

Receiving no rebate 59.1 54.9 63.6 53.7 66.5 56.8

Receiving one rebate 36.5 41.1 34.6 41.7 32.7 32.7

Receiving two or more 

rebates 4.5 4.0 1.9 4.6 .8 10.5

Rebate reporters only

Receiving at least one rebate by:

Check 60.5 48.5 64.9 63.5 61.9 66.2

Electronic funds transfer 

(EFT) 40.0 51.0 35.1 35.8 36.8 38.0

No information (invalid 

blank) 1.9 1.6 1.9 1.7 2.2 2.1

Asked how rebate was used 94.7 94.2 90.6 96.8 93.4 95.4

If asked how rebate was used:

Rebate was used mostly for:

Spending 30.2 28.7 26.9 31.9 31.9 29.0

Saving 17.6 15.0 6.1 23.3 21.4 13.0

Paying off debt 49.1 53.8 65.2 41.7 43.6 54.4

No information (invalid blank) 3.0 2.5 1.8 3.1 3.2 3.6

1

 For this table, single persons 18 years and older are assumed to qualify for the rebate. However, information on tax status is not available 

in the data examined. Therefore, some of these persons may be claimed as dependents on another tax return, and, as such, are ineligible.

Consumer Expenditure Survey Anthology, 2011 31
more than one fifth saved it; and most 

of the rest used it to pay off debt. A 

small portion, 3 percent in each case, 

did not report usage.

For income, there is no discernable 

relationship between the propensity to 

allocate and the level of income. (See 

table 4.) In each income group where 

use questions were asked, about one 

half (46 to 54 percent) used it to pay 

off debt, with more than one fourth to 

more than one third (28 to 35 percent) 

mostly spending, and most of the rest 

(15 to 20 percent) mostly saving the 

rebate. Between 2 and 4 percent did 

not know or refused to report use of 

the rebate.

Percent reporting. Most of those 

reporting receipt of a rebate reported 

receipt of only one rebate. However, a 

substantial portion—nearly 1 in 9 (11 

percent)—reported receipt of two or 

more rebates. (See table 1.) This is possible when a consumer unit includes 

more than one tax filer (for example, 

a husband and wife filing separately; 

or a retired parent who resides with 

working children).

Only 23 percent of the youngest consumers—those under age 25—received 

any rebate, compared with nearly 

half (46 to 47 percent) of consumers 

who were age 65 or older. (See table 

3.) There is little variation in percent 

reporting at least one rebate for those 

aged 25 to 64, although the values 

reported (40 to 43 percent) are closer 

to those for older consumers than to 

that for the youngest consumers. These 

results may have been influenced by 

the composition of the sample. More 

than half (55 percent) of those whose 

reference person is under 25 completed 

only one in the series of four quarterly 

interviews, compared with about one 

third (34 to 35 percent) of those at least 

55 years old. (See chart 2.) Similarly, 

the percent completing all four interviews is more than double (9 to 11 

percent) the rate for those at least 55 

and older than it is for those under 25 

Table 3. Tax rebate data, classified by age of reference person, Consumer Expenditure Interview Survey, June 2008–March 2009

Item

All consumer 

units

Under 25 

years

25–34 

years

35–44 

years

45–54 

years

55–64 

years

65–74 

years

75 years 

and 

older

Sample size 13,803 1,094 2,304 2,671 2,832 2,217 1,397 1,288

Income before taxes $63,197 $26,617 $58,841 $77,506 $82,804 $71,700 46,300 $32,964

Age of reference person 48.5 21.4 29.5 39.6 49.4 59.2 69.0 81.6

Average number in consumer unit:

Persons 2.5 1.9 2.8 3.3 2.8 2.1 1.8 1.5

Children under 18 .6 .3 1.1 1.4 .6 .2 .1 (1

)

Earners 1.3 1.3 1.5 1.6 1.7 1.3 .6 .2

Rebate information:

Average amount received $392 $186 $425 $500 $421 $385 $349 $282

Percent distribution:

Receiving no rebate 59.1 77.2 60.5 57.9 58.4 57.3 53.2 54.4

Receiving one rebate 36.5 19.3 35.5 38.1 36.7 36.9 41.7 42.2

Receiving two or more rebates 4.5 3.5 4.0 4.0 4.9 5.8 5.1 3.3

Rebate reporters only

Receiving at least one rebate by:

Check 60.5 65.1 50.7 54.9 57.1 62.6 71.3 75.5

Electronic funds transfer

 (EFT) 

40.0 37.8 50.3 45.1 43.2 37.4 29.1 24.9

No information (invalid blank) 1.9 1.6 1.2 2.0 2.5 2.2 1.5 1.4

Asked how rebate was used: 94.7 87.6 90.6 94.6 95.8 96.5 97.4 96.3

If asked how rebate was used:

Rebate was used mostly for:

Spending 30.2 33.9 25.0 29.7 26.5 33.3 36.6 32.7

Saving 17.6 12.8 15.0 13.3 15.4 17.2 22.8 30.8

Paying off debt 49.1 47.7 57.5 54.2 55.3 46.2 37.5 33.1

No information (invalid blank) 3.0 5.5 2.5 2.7 2.7 3.4 3.1 3.4

1 Less than 0.05.

Consumer Expenditure Survey Anthology, 2011 32
Table 4. Tax rebate data, classified by income before taxes, Consumer Expenditure Interview Survey, June 2008–March 2009

Item

All 

consumer

 units

Less 

than 

$5,000

$5,000 

to 

9,999

$10,000 

to

 14,999

$15,000 

to 

19,999

$20,000 

to

 29,999

$30,000 

to 

39,999

$40,000

 to

49,999

$50,000 

to 

69,999

$70,000

 and 

more

Sample size 13,803 564 668 911 877 1,678 1,400 1,258 2,033 4,414

Income before taxes $63,197 –$758 $7,689 $12,461 $17,331 $24,752 $34,522 $44,644 $59,118 $130,229

Age of reference person 48.5 40.3 47.5 55.2 54.1 52.3 48.6 47.1 46.7 47.0

Average number in 

 consumer unit:

Persons 2.5 1.7 1.6 1.7 1.9 2.1 2.3 2.5 2.7 3.1

Children under 18 .6 .4 .3 .4 .5 .5 .6 .7 .7 .9

Earners 1.3 .5 .4 .5 .6 .8 1.1 1.3 1.6 1.9

Rebate information:

Average amount received $392 $133 $116 $160 $236 $300 $354 $441 $507 $527

Percent distribution:

Receiving no rebate 59.1 81.0 77.8 68.7 62.1 57.6 56.9 52.7 52.0 57.0

Receiving one rebate 36.5 17.0 21.1 29.6 35.6 38.8 40.1 42.3 41.1 37.0

Receiving two or more

 rebates 4.5 2.0 1.0 1.6 2.3 3.6 3.0 5.0 6.8 6.0

Rebate reporters only

Receiving at least

 one rebate by:

Check 60.5 67.3 71.6 77.9 72.0 67.5 65.5 60.5 56.1 52.5

Electronic funds 

 transfer (EFT) 40.0 32.7 27.7 21.4 28.3 31.5 33.7 39.8 44.3 16.5

No information 

 (invalid blank) 1.9 3.7 2.0 1.4 1.5 2.4 2.0 1.2 2.5 1.6

Asked how rebate

 was used 94.7 95.3 93.9 93.7 94.0 92.5 94.9 94.1 95.1 95.8

If asked how 

 rebate was used:

Rebate was

 used mostly for:

Spending 30.2 33.3 30.2 34.8 29.8 31.0 28.7 28.6 28.5 31.1

Saving 17.6 16.7 15.1 17.6 15.7 19.6 16.1 15.9 15.6 19.5

Paying off debt 49.1 48.0 50.4 45.7 52.2 45.9 51.0 53.6 52.2 46.6

No information 

(invalid blank) 3.0 2.0 4.3 1.9 2.2 3.5 4.2 2.0 3.7 2.8

(4 percent). This is worth noting because participation in more interviews 

over time means more opportunity to 

report receipt of at least one rebate. At 

any rate, regardless of age, only 3 to 6 

percent reported receipt of more than 

one rebate. (See table 3.)

The presence of a qualifying child 

did little to change the probability of 

reporting at least one rebate: For single 

persons, the presence of a qualifying 

child raises the probability of reporting 

a rebate by only 3 percentage points; 

for husband and wife consumer units, 

the probability actually fell by about 

1 percentage point. (See table 2.) 

Presumably, this is because the presence of a qualifying child affected the 

amount of the payment, but not the 

eligibility to receive one, when two 

otherwise identical consumer units 

were compared. As expected, amount 

received is larger for consumer units 

with at least one qualifying child, as 

noted previously.

Surprisingly, the percent reporting at 

least one rebate increased with income 

Consumer Expenditure Survey Anthology, 2011 33
Table 5. Use of tax rebate (for those asked only), Consumer Expenditure Interview Survey, June 2008–March 2009

Item Rebate use 

asked

Rebate used 

mostly 

for spending

Rebate used 

mostly

 for saving

Rebate used 

mostly 

for paying 

off debt

Rebate use 

asked, 

but not 

reported

Sample size 5,353 1,618 944 2,628 163

Income before taxes $62,699 $64,013 $65,871 $60,299 $69,972

Age of reference person 50.7 52.0 55.4 48.2 51.3

Average number in consumer unit:

Persons 2.6 2.5 2.3 2.8 2.5

Children under 18 .7 .6 .4 .8 .5

Earners 1.4 1.3 1.2 1.5 1.4

Rebate information:

Average amount received $962 $926 $936 $995 $925

Percent distribution:

Receiving no rebate 0.0 0.0 0.0 0.0 0.0

Receiving one rebate 88.8 89.6 90.8 87.9 83.4

Receiving two or more rebates 11.2 10.4 9.2 12.1 16.6

Receiving at least one rebate by:

Check 60.8 62.2 62.1 59.7 55.8

Electronic funds transfer (EFT) 39.8 38.5 37.9 41.9 28.8

No information (invalid blank) 1.9 1.2 1.3 1.4 18.4

Asked how rebate was used: 100.0 100.0 100.0 100.0 100.0

Rebate was used mostly for:

Spending 30.2 100.0 0 0 0

Saving 17.6 0 100.0 0 0

Paying off debt 49.1 0 0 100.0 0

No information (invalid blank) 3.0 0 0 0 100.0

4

According to the rules, all eligible tax 

payers who “file[d] a federal tax return by 

October 15, 2008” were scheduled to receive 

the payment (“Basic Information on the 

Stimulus Payments,” updated July 18, 2008, 

on the Internet at http://www.irs.gov/newsroom/article/0,,id=179211,00.html, visited 

8/27/2009).

5 According to table 2, the group of rebate 

reporters with the highest percent reporting 

multiple rebates is “all other consumer units” (24 

percent). This is expected, since the composition 

of this group presumably includes consumer unit 

structures in which multiple tax units plausibly 

reside, such as a single parent with a working 

child who is at least 19 years old, and no younger 

(that is, qualifying) children.

for respondents with less than $70,000. 

(See chart 3.) Because all tax payers 

within the income ranges described 

previously are equally eligible, the expected outcome is that the relationship 

would be stable within this range.4 The 

explanation for the observed outcome 

may lie in the fact that low-income 

families are less likely to participate 

in all four interviews over time, and, 

therefore, to have four opportunities 

to provide information on receipt of 

the rebate, than are higher-income 

families. For example, only 4 percent 

of consumer units with incomes less 

than $5,000 participated in all four 

interviews, compared with 10 percent 

of those with incomes of $70,000 

and more. (See chart 4.) Similarly, 50 

percent of those in the lowest income 

group participated for only one interview during the collection period, 

compared with 37 percent of the highest income consumer units.

When considering only those who 

reported at least one rebate, multiple 

rebate reporting was most frequently 

observed for the youngest consumers (15 percent), and least frequently 

observed for the oldest consumers 

(7 percent). (See table 3.) For those 

between the ages of 25 and 74, the 

percent reporting multiple rebates 

among those who reported at least one 

rebate ranged from 10 to 14 percent. 

Not surprisingly, rebate reporters consisting of a husband and wife with (9 

percent) or without (10 percent) at least 

one qualifying child are more likely 

to report multiple rebates than either 

single parents (5 percent) or single persons aged 18 or older (2 percent). (See 

table 2.)5

 Also, except for the lowest income group (10 percent), the incidence 

of multiple rebates ranges from 5 to 

8 percent of rebate recipients in each 

income group in the less-than-$40,000 

categories, compared with 11 to 14 perConsumer Expenditure Survey Anthology, 2011 34
cent of rebate recipients in each income 

group in the $40,000-or-over categories. 

(See table 4.)

Method of receipt. The most popular 

method of receiving the stimulus 

payment was by check. Well over 

half (more than 60 percent) of respondents reporting receipt of at least one 

rebate reported receiving at least one 

payment by check. (See table 1.) In 

comparison, 40 percent of recipients 

reported receiving at least one rebate 

by electronic funds transfer (EFT); 

and for 2 percent of the recipients, no 

information is available on the method 

for the remaining cases, because the 

respondent did not know, or refused 

to report, the information.6

 However, 

there are marked differences by demographic characteristic. For example, 

the percent reporting receipt by check 

increases with age of reference person from about half (51 percent) for 

those in the 25-to-34-year-old group 

to three fourths (75 percent) for those 

in the 75-and-older group. Those 

under 25 were comparable with older 

consumers, with nearly two-thirds (65 

percent) reporting receipt by check. 

The relationship to income is that of 

an inverted “check mark,” rising from 

about two thirds (67 percent) for the 

lowest income group to more than 

three fourths (78 percent) of those 

in the $10,000 to $14,999 range, and 

falling to just over half (52 percent) 

of the highest income range.

Summary

Between June 2008 and March 2009, 

respondents to the Interview component of the Consumer Expenditure 

Survey were asked about receipt and 

use of the 2008 Economic Stimulus 

Payments (also called tax rebates). 

Averaging more than $900 for consumer units reporting receipt, nearly 

half (49 percent) of these consumer 

units reported using the payments 

mostly for paying off debt. Less than 

one third (30 percent) reported using 

the payments mostly for spending, 

and less than one fifth (18 percent) 

reported using the payments mostly 

for saving. Those who used the payments mostly to pay off debt also 

received larger rebates, on average, 

than those who used them mostly for 

spending or saving.

The use of the rebates varied by 

demographic characteristics. For example, the majority of consumer units 

with reference person aged 25 to 54 

used the rebates mostly for paying off 

debt; those with older or younger reference persons were much less likely 

to do so.

Most respondents (more than 60 

percent) reported receiving these 

payments by check, rather than by 

electronic funds transfer. Although 

the percentage changed with age, 

more than half of each age group 

examined reported receipt by check 

(51 percent of those in the 25-to-34-

year-old group; 75 percent for those in 

the 75-and-older group). Presumably, 

the method of receipt has implications 

for administrative costs associated 

with distributing the payments, and is, 

therefore, of interest to policymakers.

 6 Values add to more than 100 percent because 

some recipients received multiple rebates. If 

at least one was by check and at least one was 

by EFT, the same recipient is included in both 

groups.

Consumer Expenditure Survey Anthology, 2011 35
0

10

20

30

40

50

60

0

60

10

20

30

40

50

1 2 3 4

Chart 2. Number of interviews completed by age of reference person for 2008 tax rebates

Number of interviews completed

Percent reporting

Under 25

25 - 34

35 - 44

45 - 54

55 - 64

65 - 74

75 and older

2,628

(49)

163

(3)

1,618

(30)

944

(18)

Chart 1. Number (and percent) of consumer units and primary use of the 2008 tax rebates

Spending

Saving

Paying off debt

Rebate use asked, but not reported

Consumer Expenditure Survey Anthology, 2011 36

Age
No rebateA t least one rebateO ne rebate onlyT wo or more

Chart 3. Number of rebates received by income before taxes for 2008 tax rebates Percent reporting

0

20

40

60

80

100

0

20

40

60

80

100

No rebate At least one rebate One rebate only Two or more

Number of rebates received

0

10

20

30

40

50

60

0

10

20

30

40

50

60

Chart 4. Number of interviews completed by income before taxes for 2008 tax rebates

1 2 3 4

Number of interviews completed

Percent reporting

0

60

10

20

30

40

50

0

10

20

30

40

50

60

Consumer Expenditure Survey Anthology, 2011 37

Less than $5,000

5,000 to 9,999

10,000 to 14,999

15,000 to 19,999

20,000 to 29,999

30,000 to 39,999

40,000 to 49,999

50,000 to 69,999

70,000 and more

Less than $5,000

5,000 to 9,999

10000 to 14,999

15,000 to 19,999

20,000 to 29,999

30,000 to 39,999

40,000 to 49,999

50,000 to 69,999

70,000 and more

Income

Income
Technical Note

Data collection. In the usual course of the Interview Survey, 

an address is visited once per quarter for five consecutive 

quarters. For the Economic Stimulus Payments, data regarding amount received and method of payment were collected 

the first time that the consumer unit was interviewed during 

the collection period (June 2008 through March 2009). In 

the next completed interview, respondents were asked how 

they mostly used the funds. When the first interview during 

the collection period was also the fifth interview for the 

consumer unit, both sets of questions were asked during 

the same interview. Nonetheless, there was not always 

information available regarding both receipt and use. For 

example, a respondent may have provided receipt information in one interview, but then may not have been available 

for any subsequent interview, or may not have known or 

may have refused to provide information about the use of 

the rebate. In such cases, no information on use of the payment was obtained. In cases where receipt, but no value, of 

the payment was reported in the first eligible interview, a 

value based on other available information, such as family 

composition, was imputed during data processing.

Weighting. Data in this report have not been weighted to 

reflect the population. Weights used in standard publications are derived through a process in which each interview 

is treated independently, even though the same consumer 

unit may be interviewed several times during the course of 

the survey. However, in this report, information for each 

consumer unit is linked across interviews when more than 

one occurred during the period in the collection period. As 

noted, the number of interviews in which a consumer unit 

participated ranges from one to four, depending on numerous factors. (For example, consumer units completing their 

fifth interview in June 2008 or their second interview in 

March 2009 had no opportunity to answer rebate questions 

in a later interview, and, therefore, have only one interview 

on record.) Because the interviews each quarter are not 

treated independently, and because the number of possible 

interviews differs across consumer units, weighting was not 

used in this report.

Consumer Expenditure Survey Anthology, 2011 38
The 2008 economic stimulus payment information was collected in sections 19B and 20B of the Consumer Expenditure 

Interview Survey questionnaire as shown below. Outside 

experts were consulted prior to finalizing the questions. The 

questions on the amount and month of the payment were 

similar to those from 2001 when tax rebate information was 

also collected. The questions on how the rebate was used 

are similar to those in the University of Michigan Survey of 

Consumers and also in the U.S. Census Bureau Survey of 

Income and Program Participation 2008 wave 1 supplement.1

Section 19B. Earlier this year/Last year the Federal government approved an economic stimulus package. Many 

households will receive a one-time economic stimulus payment, either by check or direct deposit. Previously you or 

your CU reported receiving one or more economic stimulus 

payments. This is also called a tax rebate and is different 

from a refund on your annual income taxes. 

Since the first of the reference month, have you or any 

members of your CU received a/an additional

10. Tax rebate? [Economic Stimulus Payment] 

99. None/No more entries 

What was the payment/contribution for? [enter text] 

_____________ 

In what month did you make the payment/contribution? 

[enter text] _____________ 

* Enter 13 for same payment/contribution each month of 

the reference period.

What was the total amount of the payment/contribution?/

What is the monthly payment/contribution? [enter value] 

_____________

Did you make any other payments/contributions for this 

"payment/contribution item"? 

1. Yes

2. No 

Who was the rebate for? [enter text] _____________ 

* Collect each rebate separately and include the name(s) of 

the recipient(s).

In what month did you receive the rebate? [enter text] 

_____________ 

What was the total amount of the rebate? [enter value] 

_____________

* Probe if the amount is not an expected increment such as 

$300, $600, $900, $1,200, etc.

Was the rebate received by - ? 

1. check?

2. direct deposit? 

Did you or any members of your CU receive any other tax 

rebate [economic stimulus payment]? 

1. Yes

2. No 

Section 20B. Earlier in this interview/Last interview/Previously you or your CU reported receiving a one-time tax 

rebate that was part of the Federal government's economic 

stimulus package. Did the rebate lead you or your CU mostly 

to increase spending, mostly to increase savings, or mostly 

to pay off debt?

* Select the category that best describes how the rebate was 

mostly used.

1. mostly to increase spending 

2. mostly to increase saving

3. mostly to pay off debt 

Appendix 

Consumer Expenditure Survey Anthology, 2011 39

1

 Section 19B http://www.bls.gov/cex/capi/2008/csxsection19b.htm 

(visited 4/28/2011). Section 20B http://www.bls.gov/cex/capi/2008/csxsection20b.htm (visited 4/28/2011). 
William Hawk is an economist in the Branch 

of Information and Analysis, Division of Consumer Expenditure Survey, Bureau of Labor 

Statistics.

Consumer Expenditure Survey Anthology, 2011 40

Household spending 

by single persons and 

married couples in their 

twenties: a comparison

WILLIAM HAWK

1

 Geoffrey Paulin, “Examining Expenditure 

Patterns of Young Single Adults in a Historical 

Context: Two Recent Generations Compared,” 

Consumer Expenditure Survey Anthology, 2008

(U.S. Bureau of Labor Statistics, December 

2008). 2 See “Table 3. Age of reference person,” on 

the Internet at http://www.bls.gov/cex/2008/

Standard/age.pdf. 

I

n the United States, persons reaching age 21 enter adulthood facing 

the challenges and opportunities 

that come with personal and economic 

autonomy. Young adults in their twenties traditionally are completing their 

educational goals, entering the workforce, and making decisions regarding 

marriage and living arrangements. An 

earlier Consumer Expenditure Survey 

Anthology article by Geoffrey Paulin 

noted the relevance of studying persons in their twenties.1

 In the article, 

Paulin investigated the spending habits 

of never-married singles ages 21 to 29 

years and noted that “For many Americans, the age of 21 is a major point of 

demarcation in one’s life cycle.” 

Published Consumer Expenditure 

Survey (CE) data indicate that, compared with average U.S. consumer 

units (CUs), those headed by persons 

25 years or younger earn lower incomes, are less likely to own a home 

or a car, and spend less on food, gifts, 

health care, and retirement plans. 

They are also more likely to rent 

a home and spend more on education 

and alcohol.2 

The analysis that follows examines 

demographic characteristics, percapita incomes, and spending patterns 

of single and married persons in their 

twenties. The first section explores how 

these characteristics, within the single 

and married categories, differ from the 

early twenties to the late twenties. The 

second section explores income and 

spending differences between singles 

and married couples. The analysis uses 

2007–08 CE data on single persons 

ages 21 to 29 years who were never 

married and on married couples whose 

reference person3

 is 21 to 29 years and 

has no children.

The chief findings of the study are 

as follows:

• Singles in their late twenties 

spend more and have a higher 

income than singles in their early 

twenties.

• The average per-capita income of 

singles 21 to 23 years is significantly lower than that of married 

couples in the same age range. 

The reverse is true of singles and 

married couples 27 to 29 years. 

• Married couples are more likely 

than singles to be homeowners. 

• Singles spend significantly more 

per capita than married couples 

do on food, housing, apparel, 

and education, and less on health 

care.

3

 See glossary on page 48 for the BLS definition of “reference person.”
 Consumer Expenditure Survey Anthology, 2011 41

Data and methods

Interview survey. The data for this article are from the 2007–08 Interview 

Survey component of the CE. The Interview Survey contains information 

on incomes, expenditures, and demographic characteristics of American 

consumers, collected quarterly from 

a nationally representative sample of 

CUs in the U.S. population. 

The CE includes two components: 

the quarterly Interview Survey and 

the weekly Diary Survey. Published 

CE tables are created by integrating 

information from the two surveys. 

The Interview Survey, which is designed to collect data on major types 

of expenditures, household characteristics, and income, is used in this study 

because it provides the most complete 

picture of spending. Respondents are 

usually asked to report values for 

expenditures or outlays that occurred 

during the three months prior to the 

interview. The data in this analysis 

are by collection year, not calendar 

year, from CUs interviewed in 2007 

and 2008. This study employs many 

of the methods set forth in Paulin’s 

article. 

Outlays. The analysis that follows 

uses outlays, as opposed to expenditures, for comparisons. Outlays are 

similar to expenditures in that both 

measures (1) define spending as the 

transaction cost, including taxes, to 

obtain goods and services, (2) include 

spending on gifts for people outside 

of the CU, and (3) exclude business 

expenses. The key difference is in 

the treatment of purchases of real 

property and vehicles. In the CE, expenditures on purchases of property 

include only mortgage interest and 

expenditures on vehicles include the 

full value of the purchased vehicle, 

regardless of whether it was or was 

not financed. By contrast, outlays 

include both the principal and interest portions of property on mortgages 

and vehicle loans. The purchase price 

of vehicles bought outright and not 

financed also is included in outlays.

Weights. The CE uses a representative 

sample to estimate the spending habits of the U.S. civilian noninstitutional 

population. Estimates shown in this 

article are calculated with the use of 

weights. For the 2007–08 Interview 

Survey, approximately 600 married 

CUs and 2,200 single CUs provided 

data for this analysis. These sampled 

CUs represent nearly 7 million CUs 

in the population.

Reference groups. Recognizing that 

21- to 29-year-olds are not a homogeneous group and that the twenties 

are a period of lifestyle transition, 

the analysis examines three distinct 

groups: those CUs (with reference 

person) ages 21 to 23 years, those in 

their midtwenties (24 to 26 years), 

and those in their late twenties (27 to 

29 years). Further restrictions on the 

age difference between spouses in a 

married-couple CU follow.

Consumers must be single or married with no children in order to be 

included in the analysis. To be categorized as a “single” CU, a person must 

identify him- or herself as single and 

never married and must be in a CU 

of size 1. This categorization implies 

that the person is not living with 

other blood relatives, is not widowed 

or divorced, and, if there are other 

people living in the housing unit, is 

financially independent (that is, is 

not making joint financial decisions 

with his or her housemates). Financial independence is determined by 

the three major expense categories: 

housing, food, and other living expenses. To be considered financially 

independent, the respondent must 

pay all or part of the consumer unit’s 

expenses in at least two of the three 

major expense categories. 

Examples of singles eligible for 

this study include a 25-year-old living with three of her friends who 

makes her own financial decisions 

and a 21-year-old residing in a college dormitory even if he receives 

money from his parents each month. 

In contrast, a 27-year-old living at 

home with his parents is not counted 

as single even if he is financially 

independent. 

For the married group, each CU 

must, of course, be married and must 

be living in a two-member CU. In 

order to allow for closer comparisons 

between singles and couples in the 

same age group, couples with age differences greater than 4 years between 

their members are omitted from their 

respective groups.

An example of a married couple 

eligible for the study is a married 

couple, one member of whom is age 

27, and the other age 31, with no 

children. The same couple would be 

eligible even if the pair rented out 

their basement to another family. By 

contrast, any couple whose members 

Single

Ages: 21–23; 24–26; 27–29

CU type: single persons

CU size: 1

Marital status: single, never married

Married

Age of reference person: 21–23; 24–26; 27–29 

Age of spouse: within 4 years of age of reference person

CU type: husband and wife only

CU size: 2

Marital status: married, no children

Groups eligible to participate in the study
Consumer Expenditure Survey Anthology, 2011 42

are, respectively, 22 and 27 years 

would not be eligible, because their 

ages differ by more than 4 years. 

Also ineligible is a couple living in 

the home of the reference person’s 

parents, regardless of the members’ 

ages and financial independence.

Results are from the eligibility classification used and were computed on 

a per-capita basis, unless explicitly 

stated otherwise. This approach allows 

for closer comparisons between singles 

and couples. 

Early twenties compared with 

late twenties

Singles. Sixty-seven percent of singles 

in their early twenties (21 to 23 years) 

are enrolled in college either full or 

part time, 18 percent have earned a 

bachelor’s degree, and 6 percent report 

owning a home. (See chart 1.) 

Singles in their early twenties 

tend to spend more money, on average, than they earn per year. Table 1 

shows that average reported outlays 

of 21- to 23-year-olds exceed average 

income by about $5,000 ($21,083 and 

$16,067).

Lending credence to the view that 

singles in their twenties are in a transitional period, more of those in their 

late twenties have bought a home or 

earned a bachelor’s degree. Thirty-five 

percent of singles ages 27 to 29 years 

report owning a home, 55 percent have 

earned a bachelor’s degree, and 18 

percent are enrolled in college either 

part time or full time. 

The average income of a late-twenties single, $39,757, is almost 21⁄2 times 

that of an early-twenties single, and the 

average total outlay of a late-twenties 

single, $34,889, is well above that of 

an early-twenties single. Late-twenties 

singles outspend early-twenties singles 

in every expenditure category except 

education.

There are also differences in how 

singles allocate their outlays. Earlytwenties singles spend a larger share 

of their budgets on food and education 

and a smaller share on housing and 

transportation than do late-twenties 

singles. Food accounts for 18.0 percent, and education 11.0 percent, of 

outlays for an early-twenties single, 

whereas food accounts for only 14.6 

percent, and education 1.6 percent, 

for a late-twenties single. Housing 

accounts for 34.5 percent, and transportation 14.2 percent, of outlays for an 

early-twenties single; housing makes 

up 39.0 percent, and transportation 

16.6 percent, of outlays for a latetwenties single.

Married couples. For married CUs 

with reference person ages 21 to 23 

years, 17 percent report owning a 

home, 21 percent have at least one 

person with a bachelor’s degree, and 

46 percent have at least one person 

enrolled in college either part or full 

time. (See chart 2.) Average per-capita 

income is $22,986 and average percapita total outlays are $20,120. (See 

table 1.)

The twenties are also a transitional 

age for couples. Of married couples 

with reference person ages 27 to 29 

years, 69 percent report owning their 

home, 73 percent live in a CU with 

at least one person with a bachelor’s 

degree, and 29 percent are CUs with at 

least one member enrolled in college 

either part or full time. The average 

per-capita income of the late-twenties 

married group, $38,182, is 66 percent 

higher than the average per-capita 

income of the early-twenties married 

group, whereas average per-capita 

total outlays of late-twenties married 

couples, $26,649, are 32 percent higher 

than those of early-twenties married 

couples.

Early-twenties couples spend a 

larger share of their budgets on food, 

transportation, and entertainment, and 

a smaller share on housing, than do 

late-twenties couples. Food accounts 

for 15.4 percent, transportation 21.3 

percent, and entertainment 6.5 percent 

of total outlays for an early-twenties 

couple, whereas food accounts for 13.6 

percent, transportation 19.5 percent, 

and entertainment 5.4 percent for a 

late-twenties couple. Housing constitutes 30.0 percent of outlays for an 

early-twenties couple, compared with 

35.6 percent for a late-twenties couple.

Singles compared with married 

couples

Demographics. For the combined 

single and married-couple groups 

ages 21 to 29 years, married couples 

are far more likely than singles to be 

homeowners. The statistics show that 

55 percent of married couples report 

owning their homes and 84 percent of 

singles are renters. Sixty-one percent 

of married CUs and 39 percent of 

single CUs, have at least one member 

with a bachelor’s degree, and 39 percent of married CUs, compared with 43 

percent of single CUs have at least one 

member currently enrolled in college.

The difference in home ownership 

rates of singles and married couples is 

the smallest for 21- to 23-year-olds, 

compared with 27- to 29-year-olds. For 

the younger group, 6 percent of singles 

and 17 percent of couples report home 

ownership. 

The difference in home ownership 

rates is the largest among 27- to 29-yearolds, with 69 percent of married couples 

reporting home ownership, compared 

with 35 percent of singles. 

For the 21- to 23-year-olds, 67 

percent of singles report that they are 

enrolled in college and 46 percent 

of couples report having at least one 

member enrolled in college. Also, 18 

percent of singles have a bachelor’s 

degree, and 21 percent of married 

persons have at least one member 

with a bachelor’s degree. For the 27- 

to 29-year-olds, 18 percent of singles 

report that they are enrolled in college 

and 29 percent of married persons 

report having at least one member 

enrolled in college. Fifty-five percent 

of singles have a bachelor’s degree 

or higher, and 73 percent of married 

couples have at least one member with 

a bachelor’s degree or higher. 

Income. Married couples ages 21 to 

29 have incomes that are, on average, 

$6,779 more than singles’ incomes. 

Among singles, average income is 

$16,067 for 21- to 23-year-olds, compared with $39,757 for 27- to 29-yearolds. (See chart 3.) Among married 

couples, income averages $22,986 for 
Consumer Expenditure Survey Anthology, 2011 43

the younger age group, compared with 

$38,182 for older married couples. Differences in income between singles and 

married couples are largest in the early 

twenties ($6,919) and smallest in the 

late twenties ($1,575). 

Singles in their late twenties with at 

least a bachelor’s degree or higher earn 

$42,645, and those in their late twenties with a high school diploma or less 

earn $26,708. Married couples in their 

late twenties with at least one member 

with a bachelor’s degree or higher earn 

$40,240 per capita, and late-twenties 

married couples for which the highest level attained by either member 

is a high school diploma or less earn 

$33,169 per capita. 

Outlays. For all CUs, ages 21 to 29, 

average outlays are similar for singles 

and married couples, with the latter 

spending $1,532 less. Differences 

in outlays between singles and married couples are smallest in the early 

twenties ($963) and largest in the late 

twenties ($8,240). (See chart 4.)

Spending patterns. For the three age 

groups combined, singles spend 6 

percent more per capita than married 

couples spend, but married couples 

earn 25 percent more per capita in 

income than singles earn. Income and 

total outlays, however, tell only part of 

the story; a focus on how outlays are 

allocated demonstrates the differences 

in spending patterns of single and married consumers.

For all age groups combined, singles spend a larger share of their budget 

on food, housing, and education, and a 

smaller share on transportation and on 

personal insurance and pensions, than 

do married couples. Specifically, food 

accounts for 16.3 percent, housing 36.7 

percent, and education 5.7 percent of 

total outlays for singles, whereas food 

accounts for 13.1 percent, housing 

34.5 percent, and education 2.4 percent 

for married couples. Transportation 

makes up 15.6 percent, and personal 

insurance and pensions 8.9 percent, of 

total outlays for singles; transportation 

accounts for 20.0 percent, and personal 

insurance and pensions 12.7 percent, 

for married couples.

For each age group, some of the 

differences in spending shares between singles and married couples are 

more pronounced than for the three 

age groups combined. Among 21- to 

23-year-olds, singles and married 

couples allocate their spending quite 

differently: singles apportion a higher 

percentage of their outlays to food, alcohol, housing, and education, whereas 

married couples apportion a higher 

percentage of their outlays to transportation, health care, and entertainment.

The same result holds for the 27- to 

29-year age group; however, for most 

areas of spending, the difference is 

smaller. Singles’ and married couples’ 

budget shares for food, alcohol, housing, transportation, health care, entertainment, and education are closer to 

each other in the 27- to 29-year age 

group than in the 21- to 23-year age 

group. In this regard, late-twenties 

singles resemble late-twenties couples 

more than they resemble early-twenties 

singles. 

Summary of total outlays

Data from the Interview Survey component of the CE for 2007–08 show 

that ages 21 to 29 years are a time of 

transition for young adults. Regardless 

of their marital status, persons in their 

late twenties, ages 27 to 29 years, earn 

more, spend more, are more likely to 

have a bachelor’s degree, and are more 

likely to own a home than are their earlytwenties counterparts. Singles in their 

early twenties earn less in income than 

early-twenties married couples, but spend 

about the same amount per capita. However, late-twenties singles earn per-capita 

incomes similar to those of late-twenties 

married couples, but spend significantly 

more per capita. Finally, late-twenties 

singles report larger per-capita outlays 

than married couples do in each category 

examined, except for health care. 
Consumer Expenditure Survey Anthology, 2011 44

Table 1. Characteristics, per-capita outlays, and outlay shares of singles and married couples, by age group, 

2007–08

Category

21–29 years 21–23 years 24–26 years 27–29 years

Single Married 

couple Single Married 

couple Single Married 

couple Single Married 

couple

Number of CUs (in thousands) 5,236 1,515 2,083 243 1,737 578 1,417 694

Per-capita income $27,267 $34,046 $16,067 $22,986 $30,512 $33,723 $39,757 $38,182 

Percent distribution:

 Sex

 Men 58 50 56 50 59 50 60 50

 Women 42 50 44 50 41 50 40 50

 Housing tenure

 Homeowner 16 55 6 17 14 55 35 69

 Renter 84 45 94 83 86 45 65 31

 Educational status (highest level 

 attained by single or by any 

 member of married couple)

 High school diploma or less 61 39 82 79 50 36 45 27

 Bachelor’s degree or higher 39 61 18 21 50 64 55 73

 College enrollment (by single or by

 either member of married couple)

 Enrolled 43 39 67 46 34 47 18 29

 Not enrolled 57 61 33 54 66 53 82 71

Total per-capita outlays: $27,178 $25,646 $21,083 $20,120 $28,197 $26,761 $34,889 $26,649

 Food 4,417 3,363 3,798 3,101 4,592 3,173 5,111 3,613 

 Food at home 2,359 1,940 2,050 1,932 2,417 1,830 2,744 2,036 

 Food away from home 2,057 1,423 1,748 1,169 2,175 1,343 2,367 1,577 

 Alcoholic beverages 660 227 637 195 683 265 668 205 

 Housing 9,964 8,844 7,266 6,045 10,238 9,249 13,593 9,484 

 Apparel 896 650 760 596 827 774 1,180 567 

 Transportation 4,233 5,128 2,991 4,286 4,461 5,393 5,779 5,202 

 Health care 570 963 334 913 663 1,061 802 899 

 Entertainment 1,346 1,347 1,048 1,299 1,415 1,246 1,702 1,448 

 Education 1,544 611 2,329 731 1,405 737 560 464 

 Personal insurance and pensions 2,431 3,250 1,200 1,932 2,782 3,279 3,811 3,686 

 Other outlays1 1,117 1,264 720 1,021 1,131 1,585 1,683 1,081 

Total outlay shares (percent)

 Food 16.3 13.1 18.0 15.4 16.3 11.9 14.6 13.6

 Food at home 8.7 7.6 9.7 9.6 8.6 6.8 7.9 7.6

 Food away from home 7.6 5.5 8.3 5.8 7.7 5.0 6.8 5.9

 Alcoholic beverages 2.4 0.9 3.0 1.0 2.4 1.0 1.9 0.8

 Housing 36.7 34.5 34.5 30.0 36.3 34.6 39.0 35.6

 Apparel 3.3 2.5 3.6 3.0 2.9 2.9 3.4 2.1

 Transportation 15.6 20.0 14.2 21.3 15.8 20.2 16.6 19.5

 Health care 2.1 3.8 1.6 4.5 2.4 4.0 2.3 3.4

 Entertainment 5.0 5.3 5.0 6.5 5.0 4.7 4.9 5.4

 Education 5.7 2.4 11.0 3.6 5.0 2.8 1.6 1.7

 Personal insurance and pensions 8.9 12.7 5.7 9.6 9.9 12.3 10.9 13.8

 Other outlays1 4.1 4.9 3.4 5.1 4.0 5.9 4.8 4.1

1

 Other outlays include personal care, reading, tobacco, cash contributions, and miscellaneous. 

Source: U.S. Bureau of Labor Statistics, Consumer Expenditure Survey, 2007–08
 Consumer Expenditure Survey Anthology, 2011 45

80

70

60

50

40

30

20

10

0

Chart 2. Comparison of home ownership, attainment of bachelor’s degree, and 

college enrollment, by age of married reference person, 2007–08

Chart 1. Comparison of home ownership, attainment of bachelor’s degree, and 

college enrollment by singles in their early twenties and late twenties, 2007–08

Source: U.S. Bureau of Labor Statistics, Consumer Expenditure Survey, 2007–08

Homeowner Bachelor's degree Enrolled in college

80

70

60

50

40

30

20

10

0

Percent

80

70

60

50

40

30

20

10

0

Percent

80

70

60

50

40

30

20

10

0

Percent Percent

Homeowner Bachelor's degree Enrolled in college

Married, 21 to 23

Married, 27 to 29

Singles, 21 to 23

Singles, 27 to 29

Source: U.S. Bureau of Labor Statistics, Consumer Expenditure Survey, 2007–08
Consumer Expenditure Survey Anthology, 2011 46

Chart 4. Outlays of single persons and of married couples ages 21–29, 2007–08

Chart 3. Income of single persons and of married couples ages 21–29, 2007–08

Early twenties Midtwenties Late twenties

45,000

40,000

35,000

30,000

25,000

20,000

Income

(dollars)

15,000

Married couples

Single persons

45,000

40,000

35,000

30,000

25,000

20,000

Income

(dollars)

15,000

40,000

35,000

30,000

25,000

20,000

Outlays

15,000

Married couples

Single persons

40,000

35,000

30,000

25,000

20,000

Outlays

15,000

Source: U.S. Bureau of Labor Statistics, Consumer Expenditure Survey, 2007–08

Source: U.S. Bureau of Labor Statistics, Consumer Expenditure Survey, 2007–08

Early twenties Midtwenties Late twenties
Consumer Expenditure Anthology, 2011 47

T he current Consumer Expenditure Survey (CE) program began in 1980. Its principal 

objective is to collect information on 

the buying habits of American consumers. Consumer expenditure data 

are used in various types of research 

by government, business, labor, and 

academic analysts. Also, the data are 

required for periodic revision of the 

Consumer Price Index (CPI).

The survey, which is conducted by 

the U.S. Census Bureau for the Bureau 

of Labor Statistics, consists of two 

components: a diary or recordkeeping survey completed by participating 

consumer units for two consecutive 

1-week periods, and an interview survey in which expenditures of consumer 

units are obtained in five interviews 

conducted at 3-month intervals. 

Survey participants record dollar 

amounts for goods and services purchased during the reporting period, 

regardless of whether full payment is 

or is not made at the time of purchase. 

Expenditure amounts include all sales 

and excise taxes for all items purchased 

by the consumer unit for itself or for 

others. Excluded from both surveys are 

all business-related expenditures and 

expenditures for which the consumer 

unit is reimbursed.

Each component of the CE queries 

an independent sample of consumer 

units that is representative of the U.S. 

population. In the Diary Survey, about 

7,000 consumer units are sampled each 

year. Each consumer unit keeps a diary for two 1-week periods, yielding 

approximately 14,000 diaries a year. 

In the Interview Survey, the sample 

is selected on a rotating panel basis, 

surveying about 7,000 consumer units 

each quarter. Each consumer unit is 

interviewed once per quarter for five 

consecutive quarters. Data are collected on an ongoing basis in 91 areas 

of the United States.

The Interview Survey is designed 

to capture expenditure data that respondents can reasonably recall for a 

period of 3 months or longer. In general, data captured include relatively 

large expenditures, such as spending on 

real property, automobiles, and major 

appliances, and expenditures that occur 

on a regular basis, such as spending 

on rent, utilities, and insurance premiums. Also included are expenditures 

incurred on leisure trips. Expenditures 

on nonprescription drugs, household 

supplies, and personal care items are 

excluded. The Interview Survey collects detailed data on an estimated 60 

percent to 70 percent of total household 

expenditures. Global estimates—that 

is, expenditures made over a 3-month 

period—are obtained for food and 

other related items, accounting for an 

additional 20 percent to 25 percent of 

total expenditures.

The Diary Survey is designed to 

capture expenditures on small, freAppendix A: Description 

of the Consumer

Expenditure Survey
Consumer Expenditure Anthology, 2011 48

quently purchased items that normally 

are difficult for respondents to recall. 

Detailed records of expenses are 

kept for food and beverages—both at 

home and in eating places—tobacco, 

housekeeping supplies, nonprescription drugs, and personal care products 

and services. Expenditures incurred 

away from home overnight or longer 

are excluded from the Diary Survey. 

Although the diary was designed to 

collect expenditure information that 

could not be recalled easily over any 

reasonably lengthy period, respondents are asked to report all expenses 

(except overnight travel expenses) that 

the consumer unit incurs during the 

survey week.

Integrated data from the BLS Diary and Interview Surveys provide 

a complete accounting of consumer 

expenditures and income that neither 

survey alone is designed to do. Data on 

some expenditure items are collected in 

only one of the surveys. For example, 

the Diary Survey does not collect data 

on expenditures for overnight travel 

or information on third-party reimbursements of consumer expenditures, 

whereas the Interview Survey does. 

Examples of expenditures for which 

reimbursements are excluded are 

medical care; automobile repair; and 

construction, repairs, alterations, and 

maintenance of property.

For items unique to one or the other 

survey, the choice of which survey to 

use as the source of data is obvious. 

However, there is considerable overlap in coverage between the surveys. 

Because of this overlap, integrating the 

data presents the problem of determining the appropriate survey component 

from which to select expenditure items. 

When data are available from both 

survey sources, the more reliable of 

the two (as determined by statistical 

methods) is selected. As a result, some 

items are selected from the Interview 

Survey and others from the Diary 

Survey. (See Creech and Steinberg's 

article, pages17-20, for details on how 

the appropriate source is selected.)

The population coverage and the 

definition of home ownership differ 

between the CE and the CPI. As regards the former difference, consumer 

expenditure data cover the total population, whereas the CPI covers only the 

urban population. As regards the latter, 

actual expenditures of homeowners are 

reported in the CE, whereas the CPI 

uses a rental equivalence approach that 

attempts to measure the change in the 

cost of obtaining, in the rental marketplace, services equivalent to those 

provided by owner-occupied homes.

Interpreting the data

Expenditures are averages for consumer units with specified characteristics, regardless of whether a particular 

unit incurred an expense for a specific 

item during the recordkeeping period. 

The average expenditure for an item 

may be considerably lower than the 

expenditures by those consumer units 

which actually purchased the item. The 

less frequently an item is purchased, 

the greater is the difference between 

the average for all consumer units and 

the average for those purchasing the 

item. Also, an individual consumer 

unit may spend more or less than the 

average, depending on its particular 

characteristics. Factors such as income, 

the ages of family members, geographic location, taste, and personal 

preference influence expenditures. 

Furthermore, even within groups with 

similar characteristics, the distribution 

of expenditures varies substantially. 

These points should be considered in 

relating reported averages to individual 

circumstances.

In addition, sample surveys are 

subject to two types of errors: sampling 

error and nonsampling error. Sampling 

errors occur because the data are collected from a representative sample 

rather than from the entire population. 

Nonsampling errors result from the 

inability or unwillingness of respondents to provide correct information, 

differences in interviewers’ abilities, 

mistakes in recording or coding, and 

other processing errors.

Glossary

Consumer unit. Members of a household related by blood, marriage, adoption, or some other legal arrangement; 

a single person living alone or sharing 

a household with others, but who is 

financially independent; or two or more 

persons living together who share responsibility for at least two out of three 

major types of expenses: food, housing, 

and other expenses. Also, students living in university-sponsored housing 

are included in the sample as separate 

consumer units.

Reference person. The first member 

mentioned by the respondent when 

asked to "Start with the name of the 

person or one of the persons who owns 

or rents the home." It is with respect 

to this person that the relationship of 

other members of the consumer unit is 

determined.

Total expenditures. The transaction costs, 

including excise and sales taxes, of goods 

and services purchased during the 3-month 

interval over which interviews take place. 

Estimates include expenditures for gifts 

and contributions and payments for pensions and personal insurance.

Income. The combined income earned 

by all consumer unit members 14 years 

or older during the 12 months preceding the interview. The components of 

income are wages and salaries; selfemployment income; Social Security 

and private and government retirement 

income; interest, dividends, and rental 

and other property income; unemployment and workers’ compensation and 

veterans’ benefits; public assistance, 

Supplemental Security Income, and food 

stamps; rent or meals or both as pay; and 

regular contributions for support, such 

as alimony and child support. Missing 

income is imputed.

Quintiles of income before taxes. Consumer units are ranked in ascending order 

of income value and divided into five 

equal groups.