27

Consumer Expenditure Survey

Anthology, 2005

.

U.S. Department of Labor

U.S. Bureau of Labor Statistics

April 2005

Report 981
iii

Preface

This is the second in a series of reports presenting both

articles that discuss ongoing research and methodological issues pertaining to the U.S. Bureau of Labor

Statistics (BLS) Consumer Expenditure Survey (CE) and analytical articles using this survey’s data. The first report, Consumer Expenditure Survey Anthology, 2003, was published

in September 2003. Future CE anthology reports will be published biennially, with the next report scheduled for publication in 2006. The methodological articles included in this

report are intended to provide data users with greater insight

into improvements in the survey, as well as issues that are

faced in collecting, processing, and publishing information

from such a complex survey. The analytical articles provide

information on topics of interest using CE data.

This report was prepared in the Office of Prices and Living

Conditions, Division of Consumer Expenditure Surveys

(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

Jeanette Davis, Eric Figueroa, Lucilla Tan, and Nhien To of

the Branch of Research and Program Development, and

Sylvia Johnson-Herring, Sharon Krieger, Sally Reyes-Morales,

and David Swanson of the Division of Price Statistical Methods. Analytical articles were contributed by Meaghan Duetsch,

Abby Duly, George Janini, Laura Paszkiewicz, and Mark

Vendemia of the Branch of Information and Analysis.

BLS makes CE data available in news releases, reports,

and articles in the Monthly Labor Review, as well as on CDROMs and on the Internet. A biennial report includes standard tables of recent survey data, a discussion of expenditure

changes, and a description of the survey and its methods.

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.

The material that follows is divided into two sections: Part

1 includes articles on survey research and methodology, and

Part 2 presents analysis 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. Cover photo from

the Library of Congress. For further information, call (202)

691-6900.
v

Part I. Survey Research and Methodology ................................................................................................. 1

Is a user-friendly diary more effective? Findings from a field test ............................................................................ 2

A new Diary Survey questionnaire, designed to be more user-friendly, was tested to see how well it

performed compared to the questionnaire being used.

Eric Figueroa, Jeanette Davis, Sally Reyes-Morales, Nhien To, and Lucilla Tan

The efficacy of cues in an expenditure diary ................................................................................................................ 9

A cognitive study tested whether adding cues to the recording pages of the new Diary Survey questionnaire

would result in more detailed reporting by respondents.

Nhien To, Eric Figueroa, and Lucilla Tan

Characteristics of nonresponders in the Consumer Expenditure Quarterly Interview Survey ................................ 18

The characteristics of nonresponder consumer units were examined. The most common reason given for

not participating in the survey was “refusal.”

Sally Reyes-Morales

Determining area sample sizes for the Consumer Expenditure Survey ..................................................................... 24

A new, automated method of allocating the nationwide Consumer Expenditure Survey sample to individual

geographic areas was developed.

Sylvia Johnson-Herring, Sharon Krieger, and David Swanson

Part II. Analyses Using Survey Data ............................................................................................................. 30

From AFDC to TANF: Have the new public assistance laws affected consumer spending of recipients? ................. 31

There have been significant changes in the spending patterns of welfare recipients since the enactment of

welfare reform legislation in 1996. Some changes follow trends in the non-welfare population, whereas

others are unique to welfare recipients.

Laura Paszkiewicz

Spending patterns of older consumers raising a child ................................................................................................. 45

The demographic characteristics and spending patterns of older consumer units raising children are

different both from those of their generation who have no children at home and from younger consumer

units raising children.

Abby Duly

Tobacco expenditures by education, occupation, and age ............................................................................................. 51

Average annual expenditures on tobacco continue to rise despite the heightened awareness of the health

issues involved, but expenditure increases are less than the increases in the prices of tobacco products.

Spending patterns among various education, occupation, and age groups show marked differences.

Mark Vendemia

Spending by singles ...................................................................................................................................................... 56

Many differences in spending patterns between single women and single men can be explained by

differences in characteristics between the two groups, particularly age. However, differences remain

even when controlling for age.

Meaghan Duetsch

Trends in airfare expenditures..................................................................................................................................... 61

Spending on airline fares was at a peak prior to the September 11, 2001, terrorist attacks, fell sharply after

that, and rebounded some by late 2002. Spending dropped off more for some age groups than for others,

and the four regions of the country experienced different effects.

George Janini

Appendix A: Description of the Consumer Expenditure Survey ................................................................................... 70

Contents

Page
Consumer Expenditure Survey Anthology, 2005 1

Part I.

Survey Research and Methodology
2 Consumer Expenditure Survey Anthology, 2005

Is a User-Friendly Diary

More Effective? Findings

from a Field Test

Eric Figueroa, Nhien To, and Lucilla Tan are

economists in the Branch of Research and

Program Development, Division of Consumer Expenditure Surveys, Bureau of Labor

Statistics.

Jeanette Davis is a senior economist in the

Branch of Research and Program Development, Division of Consumer Expenditure

Surveys, Bureau of Labor Statistics.

Sally Reyes-Morales is a mathematical statistician in the Division of Price Statistical

Methods, Branch of Consumer Expenditure

Surveys, Bureau of Labor Statistics.

Diary surveys are often used to

collect information on daily

activities such as consumer

spending. They are particularly useful

for collecting daily records of small frequently purchased items, which are

normally difficult to recall.1 The Consumer Expenditure (CE) survey, sponsored by the U.S. Bureau of Labor

Statistics (BLS), with data collected by

the U.S. Census Bureau, uses a diary

survey to collect data on weekly household expenditures. 

Recent efforts to improve the performance of the CE diary survey have

focused on designing a more userfriendly form. Such a form would have

a simpler recording scheme and be more

attractive in appearance than the form

currently used in production. Several

prototype diaries were developed and

refined with the use of feedback from

survey respondents, field interviewers,

and program staff.2 On the basis of this

feedback, CE management selected one

of the designs (the Redesigned Diary)

for field testing. This diary was intended to stem declining response rates

and improve data quality by reducing

respondent’s burden associated with

the diary now used: the Production

Diary. The Redesigned Diary is smaller

and shorter than the Production Diary,

has a simpler organization, and highlights important instructions and examples.

The Redesigned Diary was tested

in the field from October through December of 2002.3 The primary objective

of this field test was to compare the

response rates and data quality obtained from the Redesigned Diary with

those obtained from the Production

Diary. The results showed no statistically significant difference between diary forms in completion response rates

and only a few significant differences

in expenditure means and allocation

rates. (The latter measure the proportion of expenditures requiring further

processing because they are reported

with insufficient detail.4 )

However, the Redesigned Diary performed statistically significantly better

than the Production Diary in a majority

of tests pertaining to the collection of

item attribute information needed for

3

 A field test is designed to reproduce data

collection conditions as closely as possible

to those in the production environment. 4

 Allocation is an adjustment performed

on expenditure entries that do not identify

individual items at the required level of detail

(for example, a report that says “groceries

$150,” rather than listing the specific items

purchased and the price of each). This type

of entry requires additional processing to assign the aggregate expenditure to target items.

ERIC FIGUEROA

NHIEN TO

LUCILLA TAN

JEANETTE DAVIS

SALLY REYES-MORALES

1

 S. Sudman and N. Bradburn, Asking Questions, (San Francisco, Jossey Bass Publishers,

1982). 2

 J. Davis, L. Stinson, and N. To, “Creating a ‘User-Friendly’ Expenditure Diary,”

Consumer Expenditure Survey Anthology

(Bureau of Labor Statistics, 2003), Report

967, p. 3.
Consumer Expenditure Survey Anthology, 2005 3

classification.5 In addition, the Census

Bureau field representatives who worked on the field test expressed a strong

preference for the Redesigned Diary

because of its more attractive layout

and simpler recording scheme.

On the basis of the field test results,

it was decided to continue research on

the Redesigned Diary before implementing it in production. The focus of

the research was to test modifications

to the Redesigned Diary that would increase reporting of expenditure levels

for food away from home and reporting detail for food for home consumption.

Background

Diary Survey Instruments. Two paperand-pencil questionnaires are currently

used to collect diary data. The first is

the Record of Daily Expenses, the actual diary form. This is a self-reporting

form on which respondents record a

detailed description of all expenses for

their consumer units (CUs) for two consecutive 1-week periods. (Data collected each week are considered independently.) The diary is divided by day

of purchase and by broad classifications of goods and services—a breakdown designed to aid the respondent

in recording daily purchases. Currently,

the major classifications are as follows:

• Food away from home

• Food for home consumption6

• Clothing, shoes, and jewelry

• All other purchases and expenses

Each classification is further divided

into numerous subcategories within

which the items reported are subsequently coded by the Census Bureau.

Thus, BLS can aggregate individual purchases for representation in

the Consumer Price Index and for presentation in statistical tables.

The second questionnaire used to

collect diary data is the Household

Characteristics Questionnaire, used to

record information pertaining to age,

sex, race, marital status, and family composition, as well as information on the

work experience and earnings of each

member of the consumer unit. This socioeconomic information is used by

BLS to classify the CU for the publication of statistical tables and for economic analysis. Since 2003, the Household Characteristics Questionnaire has

been administered with the use of computer-assisted personal interviews

(CAPIs).

Redesigning the Diary Form. The objective of redesigning the diary was to

produce a more user-friendly form to

encourage higher response rates and

more accurate reporting. BLS and the

Census Bureau began developing the

Redesigned Diary in 2000. Findings

from focus groups were used to define

the features of a user-friendly form: a

form that is easier to understand, less

complicated to navigate, simpler to

complete, and looks more attractive

than the Production Diary. Through a

series of cognitive tests of several prototype diaries designed with these

user-friendly features, one–the Redesigned Diary–was selected for testing

in the field.

Following is a summary of the differences in the features of the Production Diary and the Redesigned Diary:

• Smaller physical size. The Redesigned Diary is smaller (8 1⁄2” ×

11”), has fewer pages (44), and is

in portrait format. In contrast, the

Production Diary is 14”× 8” with

66 pages and is in landscape format. 

• Simplified layout. The Redesigned

Diary has a simpler organization

than the Production Diary. In

the Production Diary, each day’s

reporting space consists of seven

pages, broken down into broad

classifications and numerous

subcategories. In the Redesigned

Diary, each day’s reporting space

is reduced to four pages, also broken down into broad classifications, but without subcategories,

simplifying the respondent’s task

and the form’s appearance.

• Clearer instructions and examples. The Redesigned Diary’s instructions are formatted so topics are easier to find:

1. The Production Diary’s instructions

are evenly spread over two pages,

divided into eight topics, distinguished by their titles, which compete with numerous subtitles. The

Redesigned Diary’s instructions are

also contained on two pages, but

the different topics are more easily

distinguished from one another. The

information is grouped into three

topics, graphically set apart from

one another through the use of

frames and by means of title blocks

in large fonts.

2. A section titled “Frequently Asked

Questions” was added to the Redesigned Diary. This section answers

common questions asked about the

diary-keeping task and is found on

an easily accessible flap on the

diary’s back cover. Examples of expenditures are contained on a flap

on the front cover. Both flaps can

be used as bookmarks to help the

respondents keep their place.

3. Compared with the Production Diary, the Redesigned Diary has a

greater variety of examples, focuses

on difficult cases, and highlights important data entry instructions and

examples by using color, white space,

boldface text, and superimposed

balloons.

• More check boxes to facilitate

the recording task. In contrast

to the Production Diary, the Redesigned Diary has more check

boxes, allowing respondents to

classify expenditures more easily.

5 Attribute information is needed to classify items; the percentage of entries missing

such information measures the portion of

entries for which respondents did not provide the needed attribute information (for

example, a respondent who reports “peas,”

but does not provide attribute information

on the type of package—fresh, frozen, or

canned). 6 Includes food and beverages purchased

as gifts.
4 Consumer Expenditure Survey Anthology, 2005

• A more current and appealing

look that still maintains a professional and official quality.

The Redesigned Diary uses color

and photos to cue respondents

and to make the diary more appealing. The Production Diary is

printed in black and green on

white paper and has no photos.

The 2002 Field Test

Sample Design. To assess the performance of the Redesigned Diary, a field

test was conducted from September

through December 2002. In addition to

the redesigned form, a CAPI version of

the Household Characteristics Questionnaire was tested. This alternative

replaced the paper-and-pencil version

of the questionnaire formerly used in

production.7

The field test design included both

test (Redesigned Diary) and control

(Production Diary) samples. Both

samples used the CAPI Household

Characteristics Questionnaire. To create the samples, the Census Bureau

selected 1,800 households from a previously unused supplemental sample.

These sample units were drawn from 9

of the 12 Census regions.8 The test

sample of 1,200 households received

the Redesigned Diary, and the control

sample of 600 households received the

Production Diary.

As the field test proceeded, significant demographic differences were

found between the test and control

samples. The largest such differences

identified were in the proportions of

owners and renters. In the test sample,

these proportions were close to those

found in the general population. In the

control sample, the proportion of renters was higher than that found in the

general population. In addition, renters in the control sample had significantly lower incomes than renters in

the test sample. Because these characteristics affect expenditure levels, the

disparities weakened the control

sample’s usefulness for comparisons

with the test sample output.

In anticipation that the control

sample would not be large enough to

provide meaningful estimates, a production sample was selected for comparison with the test sample. The production sample was drawn from concurrent production data restricted to

the regions, Metropolitan Statistical

Areas, and sample frames used to draw

the field test sample. The resulting

sample consisted of 2,703 households.

Given the aforementioned differences in the demographics between the

test and control samples, the authors

chose to focus on comparisons between the test and production samples.

Although the production data had

been collected without the CAPI component, the demographic consistency

of its data with the test sample was

thought to make it a better subject for

comparison. 

Measures of Effectiveness. Our research goal was to compare the effectiveness of the Redesigned Diary with

that of the Production Diary. Our null

hypothesis states that they are equally

effective. Our alternative hypothesis

asserts that one diary is more effective

than the other.

The more effective diary must have

the following two attributes:

1. Higher completion response rates.

Completion response rates measure

the percentage of all eligible diaries

successfully placed and completed 9

2. Higher mean dollar expenditures per

CU in the two food expenditure categories: food away from home and

food for home consumption.

10

7

 After further refinement, the CAPI version was introduced into production in 2003.

8

 The nine Census regional offices that participated in the field test were Atlanta, Boston, Charlotte, Chicago, Dallas, Denver,

Detroit, Philadelphia, and Seattle; excluded

were New York, Los Angeles, and Kansas City.

These two criteria were selected, respectively, because of concern over the

declining response rates in the CE survey and the importance of the diary as

the major source for data on food expenditures. It would also be desirable

if a diary produced higher mean expenditures in the two nonfood expenditure

categories, produced relative expenditure shares11 consistent with the pattern in current production data, and had

lower percentages of entries missing

attribute information. However, it is

sufficient for one diary to be judged

more effective than the other if it meets

the foregoing two criteria.

In addition to the quantitative analyses on the field test data, two other

analyses were undertaken to evaluate

the diary:

1. A content analysis of the Redesigned and Production Diaries.

The objective of a content analysis is to compare the overall quality of entries in the diaries: Whether

entries were recorded properly and

clearly and whether relevant check

boxes were marked. Ten percent of

diaries were randomly selected for

content analysis, ensuring coverage in the three areas: Single and

multiperson CUs, diaries from

Weeks 1 and 2, and diaries from all

geographic regions.12A total of 47

Control Diaries and 81 Redesigned

Diaries from the months of September and October were reiewed.

2. A debriefing of field representatives. Field representatives who

participated in the field test were

given an opportunity to share

their impressions and reactions. In

December 2002, a debriefing questionnaire was sent to those who

participated in the field test. The

response rate for this question10 The latter category includes food and beverages purchased as gifts.

11 The relative share of each of the four

expenditure classifications is the percentage

of total expenditures that each constitutes.

12 The geographic regions are the Northeast, Midwest, South, and West.

9

Eligible housing units are those in the designated sample, less housing vacancies, housing units under construction, housing units

with temporary residents, destroyed or abandoned housing, and units converted to nonresidential use.
Consumer Expenditure Survey Anthology, 2005 5

naire was 86 percent. A total of 17

field representatives representing

the 9 Census regional offices participated in a 1-day debriefing in

January 2003.

Determining Significant Differences.

Statistical tests were performed to measure significant differences in the output of the Redesigned and the Production Diary. For the Redesigned Diary

field test, variances were calculated

using the method of “random groups.”

To obtain the random groups required for statistical analyses of the

test and production samples, the CU

universe was randomly divided into 10

groups called replicates, with each

replicate containing approximately 10

percent of the universe. Each statistic

of interest (such as mean expenditure,

response rate, and relative importance)

was computed separately for each

replicate, as well as for the full sample.

Then the variance for the statistic is

estimated by

The standard error is estimated by

If |Z| > 2, then the difference between

the statistics of interest is statistically

significant.

Findings

On the basis of comparisons between

the test and production samples, the

data yielded the following results:

Response rates. No significant difference in the response rates for completed

diaries was found. (See table 1.) Compared with the refusal rate in the

Redesigned Diary, the refusal rate in the

Production Diary was significantly

higher. However, the Redesigned Diary also had a significantly higher rate

of incomplete interviews for “other”

reasons, perhaps due to the more stringent placement dates enforced by

CAPI.

Expenditure means. In the Redesigned

Diary, expenditures were significantly

lower for Food Away from Home, but

significantly higher for Clothing,

Shoes, and Jewelry. In terms of expenditure shares—the percentage of total

expenditures spent on each component—only food away from home was

significantly lower in the Redesigned

Diary. These results may be due to new

titles13 in the Redesigned Diary for food

away from home and food for home

consumption. Because of the difference in titles, respondents using the

Redesigned Diary may have thought

they should omit from the food away

from home section some expenditures

that respondents using the Production

Diary thought should be included.

Allocation rates. In the Redesigned

Diary, the percentage of expenditures

for Food Away from Home coming from

allocation was significantly lower than

that in the Production Diary. The difTo determine whether the statistic of

interest was significantly different between the test and production

 samples, z-scores (Z) that

allow a statement of statistical significance were calculated with the formula

are the variance of the test and production statistics, respectively.

13 In the Redesigned Diary, the food away

from home and food for home consumption

sections were retitled, respectively, “Food &

Drinks from Food Service Places” and “Food

& Drinks from Grocery and Other Stores.”

ference may be largely a reflection of

the effectiveness of the additional

check boxes in the Redesigned Diary.

No other significant differences were

found.

Percentage of missing attributes. Three

of the five tests (meal type, alcohol

type, and gender) showed significantly

lower rates of missing attributes in the

Redesigned Diary compared with the

Production Diary. As with food away

from home, this phenomenon may be

due largely to the effectiveness of additional check boxes. One test (package type) showed significantly lower

results in the Production Diary, and one

(age) showed no difference between

the diaries.

Content analyses. On the basis of the

diaries that were manually reviewed, it

was not apparent that one type of diary had consistently higher error rates

than the other. (See table 2.)

Debriefings of field representatives.

• Survey of Census Bureau field representatives who administered the

field test. The field representatives

expressed overwhelming support

for the Redesigned Diary. When

asked to compare the two diaries on

several criteria (overall impression,

ease of administration, ease of respondent use, layout design, complete interviews obtained, accurate

data obtained), a majority of the field

representatives consistently gave

the Redesigned Diary favorable ratings and gave the Production Diary

neutral or negative ratings.

• In-person debriefing of 17 representatives. The majority of the field representatives thought that the format

of the Redesigned Diary, with fewer

categories, effectively reduced respondent burden. They believed

that respondents were more likely

both to record in the diary and to

persevere with recording entries

through the second week.

( ) ( ) 10 2

1 Var 5 , 10(10 1)

r r

x x

x =

−

= −

∑

where

SE Var . ( ) x x = ( )

the full sample statistic of interest

and

the statistic for the thplicate.

x

x r

=

=

Test x

Production ( ) x

( )

Test Production

Test Production

, Var ( ) Var

x x Z x x− = +

where Var( ) and Var x x Test Production ( )

r
6 Consumer Expenditure Survey Anthology, 2005

Conclusion

The findings of the diary field test did

not allow us to reject the null hypothesis. Thus, both the Redesigned Diary

and the Production Diary are equally

effective. No significant difference was

found in the test of completion response rates. Results were mixed for

tests of mean expenditures in the two

food categories: the Redesigned Diary

had significantly lower expenditures

than the Production Diary had for food

away from home, and there was no significant difference between the diaries

in food for home consumption. Higher

results on both tests were necessary

for either diary to be judged more effective than the other.

The Redesigned Diary performed

significantly better in a majority of tests

having to do with missing attribute

information. Taking into account all test

differences—whether significant or

not—we find that the Redesigned Diary produced higher expenditure means

and lower allocation rates in three of

the four expenditure categories. In addition, the field representatives who

worked on the field test expressed a

strong preference for the Redesigned

Diary.

Further Reasearch

The Redesigned Diary’s weak areas

merit additional research. The expenditure means in the food away from home

section were lower in the Redesigned

Diary than in the Production Diary.

Cognitive work is needed to determine

whether the titles used in each diary

are confusing to respondents, possibly leading to incorrect items being entered.

Additional research also is needed

to develop effective cues to encourage more detailed reporting in the food

for home consumption, the clothing,

shoes, and jewelry, and the all other

purchases and expenses sections. The

cues should not be overwhelming or

add significant amounts of respondent

burden.

The authors would like to acknowledge the following BLS employees who

contributed to this analysis: Jeff Blaha,

Richard Dietz, Tammy Hagemeier,

William Mockovak, Troy Olson, Mary

Lynn Schmidt, Linda Stinson, David

Swanson, Clyde Tucker, and Wolf

Weber.
Consumer Expenditure Survey Anthology, 2005 7

Table 1. Comparison of data from the Redesigned and Production Diaries

Response rates (percent):

Completed ...................................................................................................... 74.5 75.2 —

Eligible CUs who did not complete interview because—

refused .................................................................................................... 11.9 17.9 ****

not home .................................................................................................. 5.0 4.3 —

other ......................................................................................................... 8.6 2.6  

Mean expenditures (dollars):

All expenditure categories ........................................................................... 371 359 —

Food for home consumption ........................................................................ 64 64 —

Food away from home ................................................................................. 37 41 ** 

Clothing, shoes, and jewelry ....................................................................... 39 33 **

All other purchases and expenses ............................................................. 231 221 **

Allocation rates(percent of expenditures from allocated items):

All expenditure categories ........................................................................... 17.6 20.8 —

Food for home consumption ........................................................................ 24.3 26.3 —

Food away from home ................................................................................. 18.3 49.5  

Clothing, shoes, and jewelry ....................................................................... 22.2 17.5 —

All other purchases and expenses ............................................................. 15.6 16.2 —

Missing attributes (percent of entries missing attribute

information):

Package type................................................................................................. 7.2 4.7 ** 

Meal type ....................................................................................................... 2.8 30.3 ****

Alcohol type .................................................................................................. 9.8 16.6 **

Age ................................................................................................................ 17.7 21.4 —

Gender .......................................................................................................... 16.4 21.4 **

SOURCE: The Consumer Expenditure Survey Redesigned Diary field test, September–December 2002.

Test

(CAPI and

Redesigned Diary)

Production

(Production

Diary)

Significant

difference Characteristic

 NOTES: Statistical significance based on Z-score: ** 2 abs ( ) < 3, *** 3 abs ( ) < 4,  abs ( ) 4. Dash indicates no ≤≤ ≥ Z ZZ

 significant statistical difference.
8 Consumer Expenditure Survey Anthology, 2005

Table 2. Content analysis of the Redesigned and Production Diaries

Error rate of illegible entries (cannot read, due to handwriting):

Food away from home ............................................................................. 0.0 0.0

Food for home consumption .................................................................... .4 .2

Clothing, shoes, and jewelry ................................................................... .0 .0

All other purchases and expenses ......................................................... .2 .0

Error rate of unintelligible entries (can read, but cannot tell what

the entry means):

Food away from home ............................................................................. .6 .0

Food for home consumption .................................................................... .9 5.5

Clothing, shoes, and jewelry ................................................................... .0 .0

All other purchases and expenses ......................................................... .9 1.8

Error rate of missing description fields:

Food away from home ............................................................................. .7 .0

Food for home consumption .................................................................... .0 .0

Clothing, shoes, and jewelry ................................................................... .0 .0

All other purchases and expenses ......................................................... .0 .0

Error rate of missing total-cost fields:

Food away from home ............................................................................. .0 .0

Food for home consumption .................................................................... .0 .2

Clothing, shoes, and jewelry ................................................................... .0 .0

All other purchases and expenses ......................................................... .0 .6

Error rate of missing alcohol check marks (when alcohol is

described or cost is given):

Food away from home ............................................................................. .0 3.4

Production Diary

(in percent)

Redesigned Diary

(in percent)

Characteristic
Consumer Expenditure Survey Anthology, 2005 9

The Efficacy of Cues in an

Expenditure Diary

Nhien To, Eric Figueroa, and Lucilla Tan are

research economists in the Branch of Research and Program Development, Division

of Consumer Expenditure Surveys, Bureau of

Labor Statistics.

NHIEN TO

ERIC FIGUEROA

LUCILLA TAN I

n designing any survey, it is important to provide respondents with

clear instructions and examples.

Self-administered expenditure diaries

often use cues as examples, not only

to aid recall, but also to prompt the respondent as to what types of expenses

to record and how those expenses

should be recorded. This cognitive

study investigates how cues should be

used in an expenditure diary to instruct

respondents to record their expenses

completely and accurately.

Background

The Consumer Expenditure Diary (CED)

Survey is a nationwide survey of

households used by the U.S. Bureau

of Labor Statistics (BLS) to collect expenditures on small, frequently purchased items. The respondent is asked

to record the household’s expenses for

2 consecutive weeks. Depending on

how promptly the respondent records

the expenditures in the diary after incurring them, various degrees of recall

are involved in the task. To aid in recall, diary forms are often organized into

broad categories (e.g., “Food and

Drinks for Home Consumption” or

“Clothing, Shoes, Jewelry, and Accessories”) and include cues that are examples of expenditure items.

Over the years, the use of cues in

the CED has undergone a variety of

changes. The first annual CED, implemented in 1980, was organized into five

broad expenditure categories that were

repeated for each day of the week, resulting in a diary that was 23 pages

long. There were 76 specific cues1

 on

the recording pages for each day.

In 1991, a new version of the diary

(the Current Diary) was introduced. In

this version, the five broad expenditure

categories were further divided into 42

subcategories (e.g., an “Eggs and

Dairy Products” subcategory within

the “Food for Home Consumption”

category). As a result, there were 305

specific cues on the recording pages

for each day. A field test conducted in

1991 showed that, for items mentioned

in the cues, the Current Diary yielded

higher reporting rates with relatively

higher reporting detailthan did the 1980

diary.2

Despite the Current Diary’s strong

performance in the field test, declining

response rates and diminishing data

quality during the 1990s led CED researchers to reexamine the diary and

the diary-keeping task. A previous test

in 1985 had revealed some disadvan1

 Specific cues are precise examples of

items described with sufficient detail for coding. For example, “powdered milk” and “whole

milk” are specific cues because they contain

enough information to be accurately coded.

By contrast, “milk” is not a specific cue,

because it does not specify the type of milk. 2

 Silberstein, A.R., “Part-Set Cuing in Diary Surveys,” paper presented at the annual

meeting of the American Statistical Association, 1993.
10 Consumer Expenditure Survey Anthology, 2005

tages associated with the subcategories,3

 namely, that the amount of successful recall decreases as the number

of cues increases.4 Furthermore, the

instrument looked intimidating: it was

66 pages long (compared with the 23

pages in the 1980 CED); and although

the physical size of the Current Diary was smaller than the 1980 version

(14" × 8", compared with 17" × 11"), it

was still large and bulky and had a

landscape layout.

In response to these factors, a joint

BLS and U.S. Census Bureau5 team was

chartered in 2000 to design a more userfriendly diary that would encourage

greater participation by simplifying the

diary-keeping task, yet still solicit the

reporting detail required.6 The team

identified nine main themes from participants’ recommendations. One

prominent theme was a reaction to the

subcategory cues. Participants recommended that the recording task be reduced to the minimum number of major

categories and not include a secondary classification task required by subcategories. The team used these

themes as a basis for designing a more

user-friendly diary.

The Redesigned Diary

The Redesigned Diary has four broad

categories with no subcategories. To

simplify the appearance of the recording pages, specific cues were removed

and placed on a flap attached to the

front cover. The Redesigned Diary has

an 8 1⁄2” × 11" portrait layout with 44

pages.

The Redesigned Diary was fieldtested from September to December of

2002. Results from the test were mixed.

The new user-friendly design was overwhelmingly preferred and supported by

Census field staff. Moreover, the fieldtest data indicated that the Redesigned

Diary was comparable to the Current

Diary in response rates and overall levels of reported expenditures.

However, the data also indicated that

respondents failed to record expenditures at a sufficient level of detail, causing an increase in allocation rates.7

 This

loss of detail was attributed to the elimination of the specific cues on the recording pages. Consequently, further

research into the addition of cues on

those pages in the Redesigned Diary

was recommended.

Scope and methodology

The purpose of the cognitive study

that was recommended was to test

whether adding specific cues on the

recording pages would alleviate the

problem of respondents failing to record

at a sufficient level of detail, while maintaining the user-friendly layout of the

Redesigned Diary. To accomplish this

task, alternative means of adding cues

to the recording pages of the Redesigned Diary were evaluated.

A. Test diaries

Three formats of the Redesigned Diary

were tested in the cognitive study:

1. The No-Cues Diary. This diary

was similar to the one used in

the 2002 field test and had no cues

on the recording pages. (See exhibit 1.)

2. The Margin-Cues Diary. This

diary listed cues along the left

side of the recording pages. (See

exhibit 2.)

3. The Header-Cues Diary. This

diary listed cues along the top

of the recording pages. (See exhibit 3.)

Selection of cues: Because space on

the recording pages was limited, the

number of cues had to be minimal, making the selection of cues an important

task. The cues were selected on the

basis of four criteria:

1. Analysis of the 2002 field-test data.

A comparison was made between

the mean expenditures of the Redesigned Diary and the Current Diary.

Because research has shown that

cues improve the reporting of an

item, items for which reported expenditures were significantly lower

in the Redesigned Diary compared

with the Current Diary were identified, and a subset of those items was

selected as cues. Examples include

white bread, oranges, and whole

chicken.

2. Items commonly reported without

adequate detail. Certain items are

commonly entered into the CED

with insufficient detail, requiring

data adjustment. For example, entries of “gas” must be allocated to

either gasoline or utility gas. Similarly, entries of “books” must be allocated to either schoolbooks or

other books. To encourage more

specific reporting of items, cues

such as “gasoline,” “utility gas bill,”

“textbooks,” and “cookbook” were

selected.

3. Problems identified in the two food

categories “Food and Drinks Away

from Home” and “Food and Drinks

for Home Consumption.”

• Drinks without a meal. Team

members were concerned that

linking “Food and Drinks” together in the titles would discourage the reporting of drinks

without a meal. To encourage

such entries, cues such as “beer

at happy hour” and “soda from

vending machine” were selected.

3

 Vitrano, F.A., et al., “Cognitive Issues

and Reporting Level Patterns from the CE

Diary Operational Test,” in Proceedings of

the Section on Survey Research Methods.

Washington DC: American Statistical Association, pp. 262–267, 1988. 4

 Roediger, H. L., “Inhibiting Effects of

Recall,” Memory and Cognition, pp. 261–

269, 1974. 5

 BLS contracts with the U.S. Census Bureau to implement the Consumer Expenditure Diary Survey in the field. 6

 Davis, J., et al., “What Does It Really

Mean to Be User-Friendly when Designing

an Expenditure Diary?” paper presented at

the annual meeting of the American Association of Public Opinion Research (2002). See

also Davis, J., et al. “Creating a User-Friendly

Expenditure Diary,” Consumer Expenditure

Survey Anthology, Report 967, pp. 3–17,

Sept. 2003.

7

 Figueroa, E., et al., “Is a User-Friendly

Diary More Effective? Findings from a Field

Test,” paper presented at the annual meeting

of the American Statistical Association, 2003.

Although allocations are often used to account for item nonresponse, in the diary the

term refers to an expenditure that does not

identify individual items at the required level

of detail (e.g., a respondent reports “groceries, $150,” rather than the specific items

purchased). This type of entry requires additional processing to assign the aggregate expenditure to target items.
Consumer Expenditure Survey Anthology, 2005 11

• Delivery and takeout meals. Due

to the wording of these two food

entries, the reporting of items

such as pizza delivery and Chinese takeout is confusing to respondents. Both entries should

be reported as “Food Away from

Home,” but are often entered as

“Food for Home Consumption,”

because respondents usually

consume these foods in the

home. To encourage entering

these items in the correct section,

cues of “pizza delivery,” “Chinese takeout,” and “carryout

lunch” were placed on the “Food

Away from Home” recording

pages.

4. A balanced representation of items.

One specific cue from each subcategory in the Current Diary was selected:

• “cigarettes” from “Tobacco and

Smoking Supplies”

• “prescription drugs” from

“Medicines, Medical Supplies,

and Services”

An effort was made to emphasize

items that are currently known to be

underreported.

Specificity of the cues: Cues were restricted to specific items (e.g., skim milk)

that do not require allocation because

they contain sufficient detail. Cues for

items requiring allocation (e.g., milk)

were excluded from consideration. It

was thought that cuing for sufficient

detail would instruct respondents to

record expenditures with similar specificity. A BLS study of the CED in the

early 1990s noted that cued items have

higher reporting rates when the cues

are specific (e.g., chuck roast vs. beef).8

Order of the cues: Most cues are

grouped with similar items (e.g., wine,

beer, and liquor) to emphasize the variety and specificity desired. Pairs of

cues selected to encourage more specific reporting of items were placed next

to one another to illustrate the importance of distinguishing similar items

(e.g., “gasoline” and “utility gas bill”

were placed next to each other to avoid

an entry such as “gas”).

B. Participants

Participants for this study were recruited from a database maintained by

the BLS Office of Survey Methods Research and through an advertisement

placed in a local newspaper. Sixty-one

individuals were recruited through

these methods, together with an additional 5 BLS employees, for a total of

66 participants, all from the Washington, DC, area. Thirty-four participants

were women, and while no information

on race or ethnicity was collected,

observationally, there appeared to be a

balance among African-Americans,

Caucasians, and Hispanics. The average age of the participants was 42, with

subjects ranging from 17 to 77 years.

The completed education level of the

participants ranged from 11th grade to

doctorate. The average education level

of the participants was 16 years,

equivalent to a college degree. About

one-third of the participants (n = 24)

were employed part time, one-third

(n=19) full time, and the remaining participants were unemployed (n = 9), selfemployed (n = 6), and retired (n = 3).

The average self-reported income was

$37,000. The median income was

$31,000, with reports ranging from $800

to $100,000.

Twenty-four participants were

single, 19 were married, 13 were divorced, and 3 were widowed. Of those

from whom data were collected, half had

children (n = 28) and half did not. The

median number of children per participant was one, and the ages of the children ranged from 1 to 42 years, with

the average being 22 years.

C. Study design

1. The recall task. Each participant

was provided a diary and asked to

enter all of his or her household’s

expenses for the previous week.

Since respondents in the field would

be able to use receipts, checkbooks,

and other records to help them complete the diary, any participant who

had such records available was allowed to use them. Diaries were distributed among three groups of partiticipants, with 21 participants receiving the No-Cues Diary, 23 receiving

the Margin-Cues Diary, and 20 receiving the Header-Cues Diary.9

2. The recognition task. After completing the diary-recall task, participants were given a comprehensive

list of commonly purchased and frequently forgotten items and were

asked to check off all items, including those they had recorded in the

diary, that they or anyone in their

household had purchased during

the past week.

Recall versus recognition.. Research

on memory has revealed that, when

given a recall task and a recognition

task, participants are able to remember

more items with the recognition task10

(Standing et al., 1970, and Sternberg,

1999). Therefore, it was thought that

participants in this study would identify more of the purchases made by

their households when using the recognition list than had been reported by

completing the diary (a pure recall task).

The items that were checked on the recognition list, but not recorded in the

diary during the recall task, would provide some measure of underreporting

(how many items respondents forgot

when completing the pure recall task

of recording in the diary).

Results from the study showed that

the average number of unique recognition items reported by participants was

greater than the average number of

unique diary (or recall) items reported.

There was no significant difference

8

 Dippo, C.S., and Norwood, J.L., “A Review of Research at the Bureau of Labor Statistics,” in Questions about Questions, ed.

J.M. Tanur: Russell Sage Foundation, NY, pp.

271–290, 1992.

9

 The original sample contained 66 diaries. Due to data problems, 2 diaries from the

group receiving the Header-Cues Diary were

eliminated from the analysis. 10 Standing, L., et al., “Perception and

memory for pictures: Single-trial learning of

2500 visual stimuli,” Psychonomic Science,

19, pp. 73–74, 1970. Also Sternberg, R.J.,

Cognitive Psychology, 2nd edition. Harcourt

Brace College Publishers, New York, 1999.
12 Consumer Expenditure Survey Anthology, 2005

(ANOVA) was performed to test differences between the three diary forms

on the following factors:11

• Overall level of expenditures

• Total number of items reported

• Number of unique diary items

(items recorded only with the recall task)

• Number of unique recognition

items (items checked only with

the recognition task)

• Percent of reported items requiring allocation

• Percent of items that matched the

cues verbatim

Comparing diary items

The only significant difference found

among the three types of diaries was

the average proportion of items matching the cues printed on the recording

pages verbatim. (See table 1.) Compared

with the No-Cues diary, the MarginCues Diary and the Header-Cues Diary

both had more than twice the proportion of items matching the cues (7 percent, as opposed to 19 and 20 percent,

respectively). This difference suggests

that the participants were looking at the

cues on the pages. However, there was

no significant difference between the

Margin-Cues Diary and the HeaderCues Diary (19.1 percent and 19.7 percent, respectively).

No significant differences were

found on any of the other variables

measured, including number of unique

diary items recalled, number of unique

recognition items reported, and percentage of items requiring allocation

due to inadequate detail in reporting.

Comparing diary expenditures

No significant differences in expenditures were found among the three diaries.

across the diaries in the percentage of

respondents underreporting. (See table

1.)

3. Followup questionnaire and debriefing. After completing both the recall

and recognition tasks, participants

were given a questionnaire about their

experience with the diary. There was a

separate questionnaire for each diary

format. The questions were designed

to identify the various features of the

cues, including the location, format,

and the actual cues that were selected.

Finally, before concluding the session, each participant received a 5-

minute debriefing in which he or she

had the opportunity to provide further

comments.

Findings

A. Qualitative findings

Observational findings

Because the goal of the study was to

examine the impact of adding cues to

the recording pages of the Redesigned

Diary, it was important to identify any

problems participants had that appeared to be a direct result of the cues.

This goal was achieved by observing

the participants and noting the questions they asked as they completed the

tasks and then reviewing each diary for

errors.

One of the main problems found was

with the Margin-Cues Diary. A few participants circled the margin cues instead of entering the description in the

space provided. This problem may

have stemmed from the visual layout

of the vertically formatted cues in the

Margin-Cues Diary, compared with the

horizontally formatted cues in the

Header-Cues Diary. Apparently, when

cues are listed vertically, some participants are more likely to view them as a

comprehensive list of expenses to circle

than when they are listed horizontally.

When recalling their purchases,

some participants asked what they

should do if they didn’t buy something

that was listed. Others asked what they

should do if they purchased something

that was not listed. These questions

suggested that some participants did

not fully understand the purpose of the

cues and thought of them as comprehensive lists from which they had to

choose. This type of confusion could

lead to overreporting of cued items and

underreporting of noncued items.

Findings from the followup questionnaire

Because the cues were designed to help

participants recall items they may have

purchased, one question asked

whether the participants used the

sample items (on the flap of the NoCues Diary, listed along the side of the

recording pages in the Margin-Cues

Diary, and listed along the top of the

recording page in the Header-Cues Diary) to help them remember their purchases. Among participants using the

No-Cues Diary, 50 percent reported that

they found the sample items helpful in

remembering purchases. Almost 70 percent of participants using the MarginCues Diary said the cues along the side

of the recording pages were helpful,

and 86 percent of respondents using

the Header-Cues Diary reported that

the sample cues along the top of the

recording pages were helpful.

In addition, the majority of the participants indicated that cues were helpful for determining which purchases to

record, how to record purchases, and

in which section to record purchases.

Findings from the debriefing

The debriefing questions provided additional feedback about the participants’ experience with the diary, so any

comments they made regarding the

cues were seen as particularly useful.

Many participants stated that the examples were very helpful. Although the

term “examples” may have been used

to denote examples anywhere in the

diary, some participants specifically

referred to the cues listed along the top

of the page or cues along the side of

the recording page.

B. Quantitative findings

A one-way analysis of variance

11 Where the data met the assumptions

required for ANOVA. When the data violated

these assumptions, the nonparametric

Wilcoxon Rank Sum test was performed.
Consumer Expenditure Survey Anthology, 2005 13

more extensive list.

The Modified Header-Cues Diary

(exhibit 4) will be implemented in January 2005.

In 1980, the CED had five broad categories, which were then divided into

42 detailed subcategories in 1991. In

2005, the subcategories will be removed, leaving four broad categories.

In terms of the specific cues it contains, the CED went from 76 in 1980 to

305 in 1991. The 2005 diary has 89 specific cues.

Will the combination of a userfriendly layout and a decreased number of specific cues on the recording

pages have a positive impact on response rates and quality of the data?

Did BLS strike the right balance between too many cues and too few?

These questions will be answered after data are collected with the Redesigned Diary in 2005.

Conclusion

The purpose of the cognitive study

was to test whether adding specific

cues on the recording pages would alleviate the problem of respondents failing to record at a sufficient level of detail. Although there was no significant

finding that the recording page cues

resulted in more detailed reporting, the

qualitative results provided evidence

that respondents used the cues and

found them helpful both in recalling

purchases and in remembering how to

record purchases. Quantitative analysis showed no significant differences

in the number of entries among the diaries, but there were significantly more

entries in the Header-Cues and Margin-Cues Diaries that matched the recording page cues than did entries in

the No-Cues Diary, suggesting that respondents noticed and used the recording page cues.

Given both the qualitative and quantitative evidence that respondents

found the recording page cues helpful

and that the vertical format of the cues

in the Margin-Cues Diary might be problematic, the team recommended that the

Header-Cues Diary be implemented

with two modifications, to emphasize

that the cues are only examples and not

a comprehensive list. This change

would help to decrease the potential

for overreporting of cued items and

underreporting of noncued items. The

modifications are as follows:

1. The word “Examples” is to be added

in a larger and different-color font

next to the lists of cues.

2. The arrow that was used to instruct

respondents to look in a different

section for “Additional Examples”

is to be moved to a more prominent

location closer to the list of cues, to

encourage respondents to utilize a

Table 1. Comparing the sample means of the three diaries

Sample size (number of diaries)............................................. 21 23 20

Number of entries in diary ...................................................... 42 43 42

Part 1. Food away from home ........................................... 7 10 9

Part 2. Food for home consumption ................................. 21 17 16

Part 3. Clothing, shoes, jewelry, and accessories ........... 3 3 4

Part 4. All other products, services, and expenses ........ 11 12 13

Number of unique diary items ................................................. 27 26 27

Number of unique recognition items ...................................... 35 47 44

Percent of items reported need allocation1 ............................ 5.6 6.2 5.3

Percent underreporting2 .......................................................... 28.2 37.7 37.4

Percent of cued items reported .............................................. 51.0 62.0 56.2

Percent of items that matched the cues(verbatim)3 .............. 7.3 19.1 19.7

Total expenditure ..................................................................... 1,317 893 1,100

Part 1. Food away from home ........................................... 39 61 96

Part 2. Food for home consumption ................................. 67 82 58

Part 3. Clothing, shoes, jewelry, and accessories ........... 83 79 71

Part 4. All other products, services, and expenses ........ 1,128 672 875

Header-Cues

Diary

Margin-Cues

 Diary

No-Cues

 Diary

1 Although “allocation” is often used to account for item

nonresponse, in the diary, the term refers to an expenditure that

does not identify individual items at the required level of detail. (For

example, a respondent reports “groceries $150,” rather than the

specific items purchased.) This type of entry requires additional

processing to assign the aggregate expenditure to target items. 2 “Underreporting” refers to the items that were checked

on the recognition list, but not recorded in the diary during

the recall task. 3 Significant difference at p = 0.05.

Characteristic
14 Consumer Expenditure Survey Anthology, 2005

Exhibit 1. The No-Cues Diary
Consumer Expenditure Survey Anthology, 2005 15

Exhibit 2. The Margin-Cues Diary
16 Consumer Expenditure Survey Anthology, 2005

Exhibit 3.The Header-Cues Diary
Consumer Expenditure Survey Anthology, 2005 17

Exhibit 4. The Modified Header-Cues Diary
18 Consumer Expenditure Survey Anthology, 2005

The Consumer Expenditure Quarterly Interview Survey collectsdata from selected consumer

units (CUs) across the United States.

Participating CUs are interviewed five

times, and their responses from the second through fifth interviews provide

data that are used in publications. Some

CUs complete interviews 2 through 5;

other CUs complete some, but not all,

of these interviews; and some CUs do

not complete any interviews. These

CUs are called complete responders,

intermittent responders, and nonresponders, respectively.

A study describing differences in

demographic characteristics between

complete and intermittent responders,

and estimating the effect of nonresponses from intermittent responders on

published consumer expenditure estimates, appeared in a previous U.S. Bureau of Labor Statistics (BLS) publication. (See “Characteristics of Complete

and Intermittent Responders in the

Consumer Expenditure Quarterly Interview Survey” by Sally E. Reyes-Morales, Consumer Expenditure Survey

Anthology, 2003, Report 967, Sept.

2003.) This article presents results of a

study of the characteristics of

nonresponder CUs, who were excluded

from the aforementioned study.

Background and definitions

The U.S. Census Bureau conducts the

Consumer Expenditure Survey for BLS

Characteristics of

Nonresponders in the

Consumer Expenditure

Quarterly Interview

Survey

Sally E. Reyes-Morales is a mathematical statistician in the Division of Price Statistical

Methods, Branch of Consumer Expenditure

Surveys, Bureau of Labor Statistics.

to find out how Americans spend their

money. Census Bureau field representatives collect data from a random

sample of CUs chosen through systematic sampling of residential addresses across the United States. This

sample is representative of the total

U.S. civilian population not living in

institutions.

The Consumer Expenditure Quarterly Interview Survey is a rotating

panel survey. CUs are interviewed once

per quarter for five consecutive quarters. After the fifth quarter, CUs leave

the sample and are replaced by new CUs

selected as before through systematic

sampling of residential addresses.

In the initial interview, field representatives ask respondents to report

all expenditures they made during the

previous month. This interview is used

only for “bounding” purposes—that

is, to make sure the expenditures reported in the second through fifth interviews reflect the correct periods. In

the second through fifth interviews,

field representatives collect data for the

3 months prior to the interview. Only

the expenditure data collected in the

second through fifth interviews are

used to compute official consumer expenditure estimates. Because data collected in each quarter are treated independently, annual estimates do not

depend on CUs participating for all five

quarters.

Terms used in this document are deSALLY E. REYES-MORALES
Consumer Expenditure Survey Anthology, 2005 19

fined below:

Household. The people who occupy a

housing unit. A housing unit is a

house, an apartment, a mobile home, a

room, or a group of rooms occupied (or

intended to be occupied) as separate

living quarters.

Consumer unit (CU). 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 of

the three major types of expenses:

Food, housing, and other expenses.

Students living in university housing

are also included in the sample as separate consumer units.

Respondent. Ideally an adult household member who is familiar with all of

the expenditures that his/her CU

makes. An eligible respondent is any

household member who is age 16 or

older and who can answer questions

on household and consumer unit composition accurately.

INSTAT. Interview status (ranges from

01 to 19):

01 = Interview

Type A noninterview:

02 = No one home

03 = Temporarily absent

04 = Refused

05 = Other Type A noninterview

Type B noninterview:

06 = Vacant (for rent)

07 = Vacant (for sale)

08 = Vacant (other)

09 = Occupied by person whose usual

residence is elsewhere

10 = Under construction (not ready)

11 = Other Type B noninterview

Type C noninterview:

12 = Demolished

13 = House or mobile home moved

14 = Converted to nonresidential use

15 = Merged

16 = Condemned

17 = Located on military base

18 = CU moved

19 = Other Type C noninterview

Interview. Completed by an eligible CU

(INSTAT = 01).

Type A noninterview. Occurs when an

address is within the scope of the survey and eligible for interview, but an

interview is not obtained (INSTAT =

02 through 05).

Type B noninterview. Occurs when an

address is within the scope of the survey but is not eligible for interview

(INSTAT = 06 through 11).

Type C noninterview. Occurs when an

address is out of the scope of the survey or is permanently ineligible for the

survey sample (INSTAT = 12 through

19).

Record. Contains all the information

relevant to each interview or

noninterview. Each CU could have as

many as five records.

Nonresponder CUs. CUs who did not

complete interviews 2 through 5.

Eligible CUs. Nonresponder CUs assigned a Type A noninterview code in

at least one of the last four records.

Ineligible CUs. Nonresponder CUs

who had no Type A noninterview code

in the last four records.

In-range CUs. CUs who were scheduled to participate in all five interviews

between January 1997 and December

2000.

Out-of-range CUs. All CUs who were

not in range.

Consumer units studied

Characteristics of nonresponder CUs

are the focus of this study. Data were

drawn from the universe of Consumer

Expenditure Quarterly Interview Survey

responder and nonresponder CUs

(1997 through 2000) using the following criteria:

• Only in-range CUs were used,

in order to track their history

throughout the survey.

• Only nonresponder CUs were

used in the study.

A summary of the 4 years of data

appears in table 1. Because CUs could

participate in the survey for five quarters, they could have as many as five

records. Of the total number of CU

records in the sample during the period of analysis, 71.5 percent (147,513

records) were in range; 28.5 percent

were out of range. Of the in-range

records, however, 76.1 percent were

provided by complete and intermittent

responders, who were excluded from

the study.

Nonresponder CUs’ records made

up 17.1 percent of all records and 23.9

percent of in-range records (corresponding to 27.5 percent of in-range

CUs). Nonresponder CUs were separated into those who were eligible and

those who were ineligible for interview

(table 2). Eligible nonresponder CUs

were those assigned a Type A

noninterview code for at least one of

the last four interviews (interviews 2

through 5)—that is, those nonresponders who were eligible for interview during a particular survey quarter

but did not participate in the survey

for that period. Conversely, the nonresponder CUs categorized as ineligible

were those CUs coded as Type B noninterviews (ineligible for interview because the residence was vacant, occupied by temporary residents, or under

construction) or Type C noninterviews (out of the scope of the survey because the residence was demolished, abandoned, or converted to

nonresidential use) for each of the last

four interviews.

Most nonresponder CUs (62.2 percent) were categorized as ineligible for

interview. The remaining 37.8 percent

were eligible for interview at some point

during the last four quarters of the survey but did not complete interviews.

Accordingly, ineligible nonresponder

CUs made up a larger percentage (53.1

percent) of records than did eligible

nonresponder CUs (46.9 percent).

Although nonresponder CUs did

not complete any of the last four interviews, some of them completed the first

(bounding) interview. Nonresponder
20 Consumer Expenditure Survey Anthology, 2005

CUs who completed the first interview

accounted for 21.7 percent of all CUs

in the study (9.1 percent of eligible CUs

and 12.6 percent of ineligible CUs).

Of the ineligible nonresponder CUs,

74.8 percent were coded as Type B or

Type C noninterview at the initial interview. This shows that most ineligible

nonresponder CUs were true nonresponders, as defined for the survey:

they were ineligible for interview and

did not contribute to the survey’s response rate. The remaining 25.1 percent can be divided into those that completed the first interview (20.3 percent)

and those for whom the first interview

resulted in a Type A noninterview (4.8

percent).

Reasons for dropping out of the

survey

Reasons for which CUs dropped out

of the survey can be identified by the

interview code of the first noninterview.

Table 3 shows that, among eligible

nonresponder CUs, refusal was the

most common reason for nonparticipation, accounting for 81.2 percent

of nonresponder CUs who completed

the first interview and 79.0 percent of

those who did not complete the first

interview. (Four out of five instances

of nonparticipation in the survey were

due to the refusal of the CU respondent.) The second most common reason was an “Other Type A noninterview,” accounting for 15.4 percent of

those who did and 13.0 percent of those

who did not complete the first interview. Because the rankings of the reasons for nonparticipation and their respective percentages were similar for

both categories, completion or noncompletion of the first interview seems

to have factored little in a CU dropping

out of the survey.

Ineligible nonresponders can be

partitioned into three distinct groups.

(See table 4.) The first group comprises

CUs who participated in the first interview but became ineligible for subsequent interviews. In this group there

are more CUs coded Type B

noninterview (57.8 percent) than Type

C noninterview (42.1 percent).

CUs who were coded as a Type A

noninterview for the first interview and

became ineligible for subsequent interviews constitute the second group. For

these CUs, the leading reason for not

participating in the survey (61.7 percent of the responses) was refusal; the

other reasons were combined into

“Other Type A noninterview” (38.3

percent).

The last group of ineligible CUs included those who did not complete any

of the five interviews and for which

none of the noninterviews were coded

as Type A. For these CUs, the bounding interview was coded as a Type B

noninterview (ineligible; 63.0 percent)

or as a Type C noninterview (out of

scope; 37.0 percent).

There were no conversions to Type

A noninterview in any of the four subsequent interviews for any of the three

groups of ineligible CUs.

Household and respondent characteristics

The demographic characteristics of the

nonresponders at the household and

CU levels are summarized in tables 5, 6,

and 7. Household tenure, race, and

mean family size cannot be obtained

for ineligible CUs, but degree of urbanization (urban or rural) and CUs per

household (one or multiple) are presented in table 5 from all five interviews

for eligible and ineligible CUs. Percentages of rural CUs and multiple-CU

households are larger for ineligible CUs

than for eligible CUs (37.7 percent and

3.4 percent compared with 18.4 percent

and 2.0 percent, respectively). The relatively high percentage of rural households in the ineligible column may suggest a problem with the rural sampling

frame (the list of all addresses in the

target population from which the

sample is selected.) The sampling frame

may be more accurate in urban areas;

the rural sampling frame may contain

addresses that are out of the scope of

this survey.

Comparative statistics about the

demographic characteristics of the

nonresponder CUs at the household

and consumer-unit levels are given in

tables 6 and 7.

Table 6 presents the race, sex, marital status, age range, and education of

respondents from eligible and ineligible

CUs who completed the first interview.

Respondents from eligible nonresponder CUs who completed the first

interview tended to be White (78.9 percent) women (59.1 percent) who were

married (43.1 percent), were 65 or older

(16.8 percent), and had at most a high

school diploma (28.8 percent). Respondents from ineligible nonresponder CUs

who completed the first interview were

mostly White (80.6 percent) women (53.9

percent) who had never married (41.9

percent), were under 25 years old (24.1

percent), and had at most some college

or an associate degree (36.6 percent).

Both eligible and ineligible nonresponder CUs had high percentages of

white female respondents. Eligible CUs

had a higher percentage of married respondents than of any other category,

while ineligible CUs had a higher percentage of those who never married

than of any other category. Eligible

CUs had a higher percentage of respondents aged 65 and older, and ineligible

CUs a higher percentage of respondents under age 25. Eligible CUs had a

larger percentage of respondents

whose highest educational level was

high school, whereas ineligible CUs had

a larger percentage of respondents with

some college or associate degree.

Table 7 gives summary statistics

about characteristics of eligible

nonresponder CUs who had Type A

noninterviews. Eligible CUs are separated into two groups, those who completed the first interview and those who

did not. Mean family size was slightly

greater (2.4) for CUs who completed the

first interview than for those who did

not (2.2). Percentages of urban CUs

and one-CU households differed little

between CUs who completed the first

interview and those who did not—78.2

percent and 97.5 percent compared with

81.9 percent and 98.6 percent, respectively.

There appears to be a relationship

between household tenure and race

and whether an eligible nonresponder

CU completed the first interview. The

percentage of homeowners was higher among those who completed the
Consumer Expenditure Survey Anthology, 2005 21

first interview than among those who

did not complete the first interview.

Similarly, the percentages of Blacks or

African Americans; American Indians,

Aleuts, or Eskimos; and Asians or Pacific Islanders were higher among those

who completed the first interview than

among those who did not.

Conclusion

The study presented in this article,

based on Consumer Expenditure Quarterly Interview Survey data collected

from 1997 to 2000, led to the following

conclusions:

• Most nonresponder CUs were ineligible CUs, or true nonresponder CUs, as defined for the survey.

• Most nonresponder CUs were urban, one-CU households (although a high percentage of ineligible CUs in rural areas may

suggest a problem with the rural

sampling frame).

• The most common reason for the

nonparticipation of eligible nonresponder CUs was refusal.

• Most respondents from nonresponder CUs who completed the

first interview were White women

with high school diplomas or with

some college or an associate degree. (From this group, eligible

CU respondents were mostly

married and older, whereas ineligible CU respondents were mostly

younger and had never married.)

• Eligible nonresponder CUs who

completed the first interview

were more likely to be homeowners and to include a smaller

percentage of Whites than were

those who did not complete the

first interview.

Table 1. Summary data from the Consumer Expenditure Quarterly Interview Survey, 1997-2000

Total............................................................................ 206,339 100.0 – ––

In range1 ............................................................... 147,513 71.5 100.0 34,286 100.0

Complete and intermittent responders .......... 112,318 54.4 76.1 24,860 72.5

Nonresponders .............................................. 35,195 17.1 23.9 9,426 27.5

Out of range ........................................................ 58,826 28.5 – ––

1

 In-range CUs were those scheduled to participate in all five interviews between January 1997 and December 2000.

NOTE: Dash indicates inapplicability.

Number

of

records

Percent

of

records

Percent of

in-range

records

Number of

in-range

CUs

Percent of

in-range

CUs

Type of consumer unit (CU)

Table 2. In-range1 nonresponder consumer units (CUs) in the Consumer Expenditure Quarterly Interview Survey,

1997-2000

Total ...................................................... 9,426 100.0 – 35,195 100.0 11,868 100.0

Eligible CUs ........................................ 3,567 37.8 100.0 16,516 46.9 11,868 100.0

Completed first interview ............ 858 9.1 24.1 4,119 11.7 2,827 23.8

Did not complete first interview .. 2,709 28.7 75.9 12,397 35.2 9,041 76.2

Ineligible CUs ...................................... 5,859 62.2 100.0 18,679 53.1 0 .0

Completed first interview ............ 1,192 12.6 20.3 3,593 10.2 0 .0

First interview was Type A ......... 282 3.0 4.8 794 2.3 0 .0

First interview was Type B/C ..... 4,385 46.5 74.8 14,292 40.6 0 .0

All CUs

Percent

of all

CUs

Percent of

CUs by

category

All

records

Percent

of all

records

Type A

records

Percent of

Type A

records Type

1

 In-range CUs were those scheduled to participate in all five interviews between January 1997 and December 2000.

2

 Eligible CUs were assigned a Type A noninterview code in at least one of the last four records; ineligible CUs had no Type A

noninterview code in the last four records.

NOTE: Dash indicates inapplicability.

2
22 Consumer Expenditure Survey Anthology, 2005

Table 4. Reasons for which ineligible1 nonresponder consumer units (CUs) dropped out of the

Consumer Expenditure Quarterly Interview Survey, 1997-2000

(Percent of CUs)

Refusal ............................................................................................................ 0.0 61.7 0.0

Other Type A noninterview ............................................................................ .0 38.3 .0

(temporary absences, noncontacts, and other)

Type B noninterview ....................................................................................... 57.8 .0 63.0

(residence was vacant, occupied by a person whose usual

residence was elsewhere, or under construction)

Type C noninterview ....................................................................................... 42.1 .0 37.0

(residence was demolished, moved, converted to nonresidential

use, merged, condemned, or on a military base, or CU moved)

No records ...................................................................................................... .1 .0 .0

Total ............................................................................................................ 100.0 100.0 100.0

Type B/C

first

interview

Completed

first

interview

Type A

first

interview

Reason

1

 Ineligible CUs had no Type A noninterview code in the last four records.

Table 5. Household characteristics of nonresponder consumer units (CUs) in the Consumer

Expenditure Quarterly Interview Survey, 1997-2000

(Percent of records in each category)

Degree of urbanization:

Urban .............................................................................................................. 81.6 62.3

Rural ............................................................................................................... 18.4 37.7

Total ........................................................................................................... 100.0 100.0

CUs per household:

One ................................................................................................................. 98.0 96.6

Multiple ........................................................................................................... 2.0 3.4

Total ........................................................................................................... 100.0 100.0

Characteristic Eligible1

CUs

Ineligible

CUs

1

 Eligible CUs were assigned a Type A noninterview code in at least one of the last four records; ineligible CUs

had no Type A noninterview code in the last four records.

Table 3. Reasons for which eligible1 nonresponder consumer units (CUs) dropped out of the

Consumer Expenditure Quarterly Interview Survey, 1997-2000

(Percent of CUs)

Refusal ................................................................................................................. 81.2 79.0

Other Type A noninterview ................................................................................. 15.4 13.0

(temporary absences, noncontacts, and other)

Type B noninterview ............................................................................................ 3.3 8.0

(residence was vacant, occupied by a person whose usual residence

was elsewhere, or under construction)

Type C noninterview ............................................................................................ .1 .0

(residence was demolished, moved, converted to nonresidential use,

merged, condemned, or on a military base, or CU moved)

Total ................................................................................................................. 100.0 100.0

Reason Completed

first interview

Did not complete

first interview

1 Eligible CUs were assigned a Type A noninterview code in at least one of the last four records.
Consumer Expenditure Survey Anthology, 2005 23

1 Eligible CUs were assigned a Type A noninterview code in at least one of the last four records.

2 Data are from all Type A noninterview records.

NOTE: Percentages do not all add to 100 due to rounding.

Table 7. Household characteristics of eligible1 nonresponder CUs in the Consumer Expenditure

Quarterly Interview Survey, 1997-2000

Mean family size ................................................................................................. 2.4 2.2

Degree of urbanization:

Urban .............................................................................................................. 78.2 81.9

Rural ............................................................................................................... 21.8 18.1

CUs per household:

One ................................................................................................................. 97.5 98.6

Multiple ........................................................................................................... 2.5 1.4

Household tenure:

Homeowner ................................................................................................... 81.0 69.0

Renter or other .............................................................................................. 19.0 31.0

Household race:

White .............................................................................................................. 81.8 87.1

Black ............................................................................................................... 11.7 8.7

American Indian, Aleut, Eskimo ..................................................................... 1.1 .7

Asian or Pacific Islander............................................................................... 5.4 3.6

Characteristic2 Completed

first interview

Did not complete

first interview

Other characteristic (Percent of households)

Table 6. Characteristics of respondents1 from nonresponder consumer units (CUs) who completed

the first interview for the Consumer Expenditure Quarterly Interview Survey, 1997-2000

(Percent)

Race:

White ............................................................................................................... 78.9 80.6

Black ................................................................................................................ 12.3 10.9

American Indian, Aleut, Eskimo ...................................................................... 1.5 1.8

Asian or Pacific Islander................................................................................ 5.5 3.8

Other ............................................................................................................... .4 1.3

No information ................................................................................................. 1.5 1.6

Sex:

Male ................................................................................................................. 40.9 45.9

Female ............................................................................................................. 59.1 53.9

No information ................................................................................................. .0 .2

Marital status:

Married ............................................................................................................ 43.1 27.3

Widowed......................................................................................................... 12.3 9.9

Divorced .......................................................................................................... 15.1 17.1

Separated ....................................................................................................... 3.0 3.7

Never married ................................................................................................. 25.6 41.9

No information ................................................................................................. .8 .2

Age range:

24 or younger ................................................................................................. 9.4 24.1

25 to 34 ........................................................................................................... 16.6 17.3

35 to 44 ........................................................................................................... 13.9 13.9

45 to 54 ........................................................................................................... 14.5 11.2

55 to 64 ........................................................................................................... 11.5 6.5

65 and older .................................................................................................... 16.8 9.8

No information ................................................................................................. 17.3 17.3

Highest level of education:

Never attended or no high school diploma ................................................... 14.3 14.3

High school diploma........................................................................................ 28.8 24.0

Some college or associate degree ................................................................ 27.7 36.6

Bachelor’s degree .......................................................................................... 17.7 12.8

Master’s, professional school, or doctoral degree ...................................... 6.7 6.4

No information ................................................................................................. 4.8 5.9

Characteristic Eligible2

CUs

Ineligible

CUs

1 For 125 eligible and 127 ineligible CUs, the respondent was not identified; as a result, those CUs were excluded

from the calculations. 2 Eligible CUs were assigned a Type A noninterview code in at least one of the last four records; ineligible CUs had

no Type A noninterview code in the last four records.

NOTE: Percentages do not all add to 100 due to rounding.
24 Consumer Expenditure Survey Anthology, 2005

Determining Area Sample

Sizes for the Consumer

Expenditure Survey

SYLVIA A. JOHNSON-HERRING

SHARON KRIEGER

DAVID SWANSON

Sylvia A. Johnson-Herring is a mathematical

statistician in the Division of Price Statistical Methods, Consumer Expenditure Surveys,

Bureau of Labor Statistics.

Sharon Krieger is a mathematical statistician

in the Division of Price Statistical Methods,

Consumer Expenditure Surveys, Bureau of

Labor Statistics.

David Swanson is Branch Chief, Division of

Price Statistical Methods, Consumer Expenditure Surveys, Bureau of Labor Statistics.

The Consumer Expenditure Survey (CE) is a national household survey conducted by the

U.S. Bureau of Labor Statistics (BLS)

to find out how Americans spend their

money. The survey’s sample design,

based on the decennial census, is updated approximately every 10 years. At

that time, many decisions need to be

made, such as the number of geographic

areas in which to collect data and the

number of households from which to

collect data in each area. This article

describes a new method for making

these decisions, one that has been incorporated in the sample design to be

introduced in 2005.

Background

The CE is used to produce the most

accurate estimate of consumer expenditures possible at the national level.

The U.S. Consumer Price Index (CPI)

program relies on CE data to produce

inflation estimates. The most comprehensive CPI is based on the expenditure patterns of consumers in urban

and metropolitan areas and is denoted

CPI-U. The CPI-U population represents about 87 percent of the total U.S.

population. The CE is designed to balance the goals of the CE and CPI programs. These goals compete with each

other when BLS allocates the CE’s nationwide sample of households to geographic areas covered by the two programs.

The number of households in the

CE’s national sample is determined by

the survey’s data collection budget.

Allocating this fixed number of households to individual geographic areas

must be done in a way that satisfies

the competing goals of the CE and CPI

programs as much as possible. The CE

program’s goal is to allocate the sample

households to the selected geographic

areas in proportion to their share of the

U.S. population, whereas the CPI

program’s goal is to allocate sample

households to the selected urban areas in proportion to their share of the

Nation’s urban population. The CPI

program further strives to include a

minimum number of households in each

selected urban area to ensure the statistical quality of its published price

indexes for those areas.

This article describes a new automated method of allocating the CE’s

nationwide sample of households in a

way that balances competing goals and

constraints. The CE actually consists

of two surveys, the Diary and Interview surveys, but this article focuses

on the Interview survey.

Geographic areas in the CE

sample

The selection of households for the

survey begins with the definition and

selection of primary sampling units

(PSUs), which consist of counties (or

parts thereof), groups of counties, or
Consumer Expenditure Survey Anthology, 2005 25

independent cities. The sample design

currently used in the survey, based on

the 1990 census, consists of 105 PSUs,

classified into 4 size categories:

• 31 “A” PSUs, which are metropolitan statistical areas (MSAs)

with a population of 1.5 million

or greater

• 46 “B” PSUs, which are MSAs

with a population less than 1.5

million

• 10 “C” PSUs, which are nonmetropolitan urban areas

• 18 “D” PSUs, which are nonmetropolitan rural areas. The “D” PSUs

are used in the CE program but

not in the CPI program.

These 105 PSUs are grouped according to the geographic areas they

represent. A populous PSU constitutes

its own geographic area, which is called

a “self-representing” geographic area.

The 31 A PSUs are self-representing

geographic areas, and they are in the

sample with certainty. The 74 B, C, and

D PSUs are “non-self-representing”

PSUs. They were randomly selected

to represent all of the less populous

PSUs in the Nation. The 74 non-selfrepresenting PSUs are grouped into 11

geographic areas called region-size

classes, which are formed by crossclassifying the 4 regions of the country (Northeast, Midwest, South, and

West) with the 3 size classes (B,C, and

D) as shown in the shaded area of the

table below. There are only 11 regionsize classes for the areas that are not

self-representing because no C PSUs

were selected in the Northeast.

These 11 region-size classes are treated just like the 31 A PSUs and are also

referred to as self-representing geographic areas. Hence, the CE can be thought

of as having 42 self-representing geographic areas: 31 A PSUs plus 11 regionsize classes for the smaller PSUs. Because the 4 D region-size classes are

used by the CE only, there are only 38

self-representing geographic areas used

by the CPI.

The sample allocation problem

In the CE’s current sample design, usable interviews are collected from 7,760

households1

 in each calendar quarter

of the year: 4,260 households in the A

PSUs, and 3,500 households in the B,

C, and D PSUs. To guarantee that

enough data are collected to satisfy

CPI’s publication requirements, the

sample of 7,760 households is allocated

so that at least 120 usable interviews

are obtained in each of the 38 geographic areas used by the CPI, with no

minimum number of usable interviews

required in the 4 D geographic areas.

Thus, the problem is to allocate the

7,760 households in the CE’s national

sample to the 42 geographic areas in a

way that satisfies the following constraints:

• The 31 A PSUs are allotted 4,260

households.

• The 11 B, C, and D region-size

classes are allotted 3,500 households.

• Each of the 38 geographic areas

used in the CPI is allotted 120 or

more households.

BLS staff recently reevaluated the

minimum sample size requirement of 120

usable interviews to determine whether

it is still an appropriate number. One of

the results of the reevaluation was the

development of a new automated

method of allocating the nationwide

sample of households to geographic

areas. The new method allowed repeated analyses to be conducted

quickly and easily using different minimum sample size requirements. The

method involved setting up the sample

allocation problem as a mathematical

optimization problem and using SAS

statistical software to solve it.

Target versus required sample size

In the past, there were various interpretations of the word “required” in the

phrase “minimum required sample size.”

At times, the requirement that at least

120 usable interviews be obtained was

interpreted as a target sample size,

meaning that the expected number of

usable interviews should be at least 120:

E( i x ) ≥ 120.

At other times, it was interpreted as a

required sample size, meaning that

there should be a very high probability

that at least 120 interviews be obtained,

P { i x ≥ 120} ≥ 0.95

where i x is the number of usable interviews collected in geographic area = i.

For example, under the first interpretation (target sample size), data collectors would have to visit 185 households

in each quarter of the year to collect

120 usable interviews in the Boston

metropolitan area, assuming that usable

interviews are obtained at 65 percent

of the residential addresses in the CE’s

sample.2

E( i x ) = 185 × 0.65 = 120

A B C D Total

Northeast ........................................... 6 8 – 4 18

Midwest ............................................. 8 10 4 4 26

South ................................................. 7 22 4 8 41

West................................................... 10 6 2 2 20

Total.................................................... 31 46 10 18 105

Size

Region 1

 In 2000 the average number of usable

interviews collected per quarter in the CE

Interview Survey was 7,760. 2

 Approximately 15 percent of the residential addresses selected for the CE Interview Survey are ineligible for the survey, and

20 percent do not participate in the survey

due to refusal or to no one being home. This

leaves 65 percent of the sample to participate in the survey.

Table 1. PSU region-size classes
26 Consumer Expenditure Survey Anthology, 2005

However, under the second interpretation (required sample size), data collectors would have to visit 202 households to be 95-percent certain of getting

at least 120 usable interviews, again

assuming a 65-percent survey participation rate.

P { i x ≥ 120} =

k k

k k

−

=

− ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ ∑ 202 202

120

0.65 (1 0.65)

202

= 0.95

Table 2 shows the difference in the

sample size that would be needed for a

target versus a required minimum number of usable interviews. The number

of selected addresses needed to

achieve a target minimum sample size

is approximately 10 percent less than

that needed for a required sample size.

The estimates in table 2 were produced using formulas from the binomial distribution for the mean and variance of the number of usable

interviews,

μ = ( )i E x = 0.65 n

( ) 2

i σ = V x = 0.65(1 − 0.65) n

and the normal distribution was used

to approximate the binomial distribution to estimate a 95-percent confidence interval on the number of usable interviews:

One-sided confidence interval:

[ μ - 1.64σ , +∞ )

Two-sided confidence interval:

[ μ − 1.96σ , μ + 1.96σ ]

After some discussion, staff decided

that target sample sizes would be satisfactory. Because the widths of the

two-sided confidence intervals are relatively small, it is unlikely that any

sample sizes achieved will be greatly

below the target level.

Setting up the optimization

problem

The CE’s current sample design calls

for allocating 7,760 households to the

42 geographic areas in a way that satisfies the three constraints mentioned

previously.

These constraints can be written in

mathematical terms as follows:

• 1 2 31 x + x +L+ x = 4,260

• 32 33 42 x + x +L+ x = 3,500

• i x ≥ 120 for i = 1,2,...,38

where i x is the number of usable interviews collected in geographic area=i.

Again, the objective of the CE’s

sample design is to allocate the nationwide sample of households to geographic areas in a way that minimizes

the standard error of the expenditures

estimate at the national level. Allocating the sample in proportion to the

population that each geographic area

represents comes very close to achieving that goal. Although this allocation

does not minimize the nationwide standard error, it is a very simple sample

design that is known to achieve near

minimization. Staff chose to implement

this method because of its simplicity

and its near optimal properties.

Based on research and evaluation,

staff modified the sample allocation

problem described above. More of the

CE’s sample households were allocated

to the urban portion of the Nation (of

interest to the CPI), and fewer households were allocated to rural areas. This

change results in a slight oversampling

of the urban areas: The CPI-U population represents about 87 percent of the

total U.S. population, but it is given 95

percent of the CE’s sample. An analysis showed that limiting the rural sample

to 400 households would have a minimal effect on the nationwide standard

error of the CE’s expenditure estimates.

Thus, the revised optimization problem

allocates exactly 400 households to the

4 rural geographic areas, leaving 7,360

households to be allocated to the 38

urban geographic areas.

For some of the geographic areas

with small populations—for example,

Anchorage and Honolulu—the requirement that at least 120 usable interviews be collected during each calendar quarter conflicts with the

objective of allocating the sample in

proportion to the population. For example, the Anchorage metropolitan area

has approximately 0.09 percent of the

U.S. population, and allocating the

7,760 usable interviews proportionally

would give Anchorage only enough addresses to obtain 7 usable interviews—

not 120.

Because an exact proportional allocation cannot be achieved within the

given constraints, BLS staff decided to

allocate the sample as proportionally

as possible. This involved setting up a

least-squares problem to square the

Table 2. Sample size needed to obtain a target versus a required minimum

number of usable interviews for the Consumer Expenditure Survey

Target sample size (two-sided 95-percent confidence interval)

62 40 [33, 47]

92 60 [51, 69]

123 80 [70, 90]

154 100 [88, 112]

185 120 [107, 133]

215 140 [126, 154]

Required sample size (one-sided 95-percent confidence interval)

72 47 [40, +∞)

105 68 [60, +∞)

137 89 [80, +∞)

170 110 [100, +∞)

202 131 [120, +∞)

234 152 [140, +∞)

Number of sample

households (n)

Expected number of usable

interviews assuming a 65-

percent survey participation

rate (=0.65n)

95-percent confidence

interval
Consumer Expenditure Survey Anthology, 2005 27

difference between each geographic

area’s proportion of the population and

its proportion of the sample and then

minimize the sum of those 42 squared

differences.

Thus, the optimization task is to

solve the following constrained leastsquares problem:

Given values of n, i p ,and p,

find values of i n that

Minimize

Subject to

7,360 n1 + n2 +L+ n38 =

≥120 i n for i = 1,2,...,38

≥ 0 i n for i = 39,...,42

where

i n = number of housing units assigned

to geographic area = i

 n = number of housing units nationwide (n = 7,760)

i p = population of geographic area = i

p = population in all geographic

areas (p = 1 2 42 p + p +L+ p )

Solving the optimization

problem

The optimization problem described

above can be seen to have both equality and inequality constraints. This

creates a practical problem because

optimization problems with equality

constraints are usually solved with different techniques than those with inequality constraints. Least-squares

problems with equality constraints are

usually solved with linear algebra and

linear regression theory, while problems with inequality constraints are

usually solved with iterative search techniques. Fortunately, the SAS procedure for nonlinear programming (PROC

NLP) can handle both kinds of constraints simultaneously. An example

using this SAS procedure to solve

the problem above is given at the end

of this paper.

Estimating the standard error

The variance of the estimate of consumer expenditures resulting from the

sample allocation process described

above was estimated using the following formula:

where

i x = sample mean of geographic

area = i

x = sample mean of the Nation

= expenditure variance of a randomly selected household

The variance of the estimate of

consumer expenditures under the

proposed sample allocation method

is estimated by substituting the values of ni obtained from the optimization problem (the output of PROC

NLP) into the formula

∑= ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =

42

1

2 2

( ) i i

i

p n

p V x σ

.

Then the standard error is computed

by taking the square root of the variance.

SE = ∑= ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ 42

1

2 2

i i

i

p n

p σ

This formula allows comparisons to

be made with the current method of

sample allocation. The value of σ does

not have to be known because the

change in standard error is the number

of interest; when the ratio of two estimates of the standard error is taken (to

compare the standard error of using,

say, 80 as the minimum sample size instead of 120), the σ in the numerator

and the σ in the denominator cancel

each other.

Standard error with different

minimum sample size

requirements

After allocating the CE’s nationwide

sample to individual geographic areas

using PROC NLP, staff computed the

percentage change in standard error for

various minimum target sample sizes.

The baseline used in the comparison

was the current sample allocation. The

current minimum target sample size is

around 120, but for technical reasons it

is not exactly equal to 120. The results

i

i

i i

i i

i

i

i

i i

x p

p

p

p x

p

p x

∑

∑

∑

∑

=

=

=

=

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = = =

42

1

42

1

42

1

42

1

2 σ

∑= ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ −

42

1

2

i

i i

p

p

n

n

n39 + n40 + n41 + n42 = 400

i

i

i x p

p V x V

42

1

( ) ∑= ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =

Table 3. The effect of changes in minimum target sample size on the

standard error for the Consumer Expenditure Survey

0 -4.16

10 -4.16

 20 -4.15

30 -4.10

40 -4.04

50 -3.96

60 -3.88

 70 -3.74

 80 -3.54

 90 -3.21

100 -2.72

110 -2.04

120 -1.14

130 +.06

140 +1.45

150 +3.28

160 +5.63

170 +10.07

180 +14.41

Minimum target sample for each

primary sampling unit

Percent change in standard error

(from SE for a minimum target sample

size of 120)

( )

42

1

2

i

i

i V x p

p ∑=

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =

i i

i

p n

p 42 2

1

2

σ ∑=

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =

R

R
28 Consumer Expenditure Survey Anthology, 2005

sample size of 80 would be satisfactory

for both surveys because the overall

standard error would be reduced and

publication criteria met for both the CE

and CPI programs.

Table 4 shows current and proposed

sample sizes for A PSUs in the West

after applying the proposed sample allocation method. The PSUs with populations larger than 4 million will have

their sample sizes increased, while the

PSUs with populations less than 4 million will have their sample sizes decreased. This change will decrease the

standard error in the larger A PSUs and

increase the standard error in the smaller

A PSUs, but the standard error for the

Nation as a whole will be reduced.

BLS staff tested other methods to

find one that satisfied the goals of both

the CE and CPI programs. Some of the

other methods tested had a positive

effect on reducing the standard error

for CE, but not for CPI, and vice versa.

The chosen method reduced CE and

CPI standard errors by about the same

amount, 3.54 percent and 3.86 percent,

respectively.

Conclusion

A new sample design for the CE will be

introduced in 2005. Based on analysis

of the current design, the new method

of sample allocation could reduce the

standard error of the estimate of consumer expenditures at the national level

by from 3 percent to 4 percent.

The CE and CPI programs’ competing goals and constraints complicated

the process of allocating households

to geographic areas in constructing the

CE’s national sample. CE program staff

wanted to allocate the sample in a way

that minimized the national variance,

while CPI program staff wanted to minimize the variance of the urban portion of

the Nation and also limit the variance of

individual sampled areas. Setting up a

mathematical optimization problem and

then solving a constrained least-squares

problem led to a solution that satisfied

the requirements of both the CE and the

CPI programs.

Writing the problem as a formal mathematical optimization problem had several advantages:

of the comparisons are shown above

in table 3.

Standard error is minimized when the

sample is allocated directly in proportion to population—that is, when 0 is

the minimum number of usable interviews required in each geographic area

(table 3). Reducing the target number of

usable interviews from 120 to 0 would

reduce the standard error by 4.16 percent. Standard error is maximized when

the sample is divided equally among all

geographic areas—180 usable interviews

per geographic area. Increasing the target number of usable interviews from

120 to 180 would increase the standard

error by 14.41 percent.

Reducing the minimum target number of usable interviews from 120 to 80

per geographic area would reduce the

standard error by 3.54 percent. Nearly

all the reduction in standard error is

achieved by reducing the minimum target sample size to 80, and little further

reduction is achieved by reducing the

minimum target sample size below 80

(chart 1). Therefore, staff decided to

reduce the minimum target sample size

from 120 to 80 usable interviews per

geographic area.

Other effects of the proposed

allocation

A minimum target sample size of 80 usable interviews per geographic area reduces the national standard error by

3.54 percent and reduces the standard

error in the urban portion of the Nation

by 3.86 percent. After some discussion,

staff decided that a minimum target

Chart1. Changes in the Consumer Expenditure Survey's standard error with minimum sample size

Percent change in standard error

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180

Minimum sample size

-10

-5

0

5

10

15

20

Proposed sample size of 80

Table 4. The effect of changing sample allocations on the standard error for

the Consumer Expenditure Survey: Primary sampling units in the West

A419 Los Angeles ...................... 8,863,164 231 290 -10.81

A420 Greater Los Angeles ........ 5,668,365 152 187 -9.88

A422 San Francisco ................... 6,253,311 158 206 -12.44

A423 Seattle................................ 2,970,328 119 100 +9.08

A424 San Diego .......................... 2,498,016 104 85 +10.78

A425 Portland.............................. 1,793,476 130 80 +27.48

A426 Honolulu ............................. 836,231 112 80 +18.32

A427 Anchorage ......................... 226,338 125 80 +25.00

A429 Phoenix .............................. 2,238,480 132 80 +28.45

A433 Denver ............................... 1,980,140 121 80 +22.98

 Total U.S. ................................ 240,218,238 7,760 7,760 -3.54

NOTE: Minimum target sample size is 80.

Primary sampling unit Population Current

sample size

Proposed

sample size

Percent

change in

standard

error
Consumer Expenditure Survey Anthology, 2005 29

• It required the objectives and constraints to be stated clearly and

explicitly.

• It helped document the allocation

process.

• It allowed several different allocation methods to be tested quickly

and easily.

• It led to an optimal solution to

the problem.

This approach offers clear benefits for allocating the CE’s nationwide sample of households to individual geographic areas while

satisfying the CE and CPI programs’

competing goals.

APPENDIX:

Automating the Sample

Allocation Process

Below is the optimization problem for

the sample allocation, along with a

SAS program (PROC NLP) that

solves it.

 Given values of n, i p , and p,

 find values of i n that

 Minimize

Subject to

 7,360 n1 + n2 +L+ n38 =

≥ 80 i n for i = 1,2,...,38

≥ 0 i n for i = 39,...,42

Where

i n = number of housing units assigned

to geographic area = i

 n = number of housing units nationwide (n = 7,760)

i p = population of geographic area = i

p = population in all geographic areas

(p = ) ∑=

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ −

42

1

2

i

i i

p

p

n

n

400 n39 + n40 + n41 + n42 =

1 2 42 p + p +L+ p

** ***********************************************

* COMPUTE THE SQUARED DIFFERENCE BETWEEN EACH *

* AREA’S PROPORTION OF THE POPULATION & ITS *

* PROPORTION OF THE SAMPLE. *

*************************************************;

%MACRO MAC1;

SUM_POP = SUM(OF POP1-POP42);

%DO I=1 %TO 42;

 SQR&I = ((N&I/7760) - (POP&I/SUM_POP))**2;

%END;

%MEND MAC1;

*************************************************

* SOLVE A CONSTRAINED LEAST-SQUARES PROBLEM TO *

* FIND THE NUMBER OF HOUSEHOLDS IN EACH PSU *

* THAT MINIMIZES THE SUM OF SQUARED DIFFERENCES *

*************************************************;

PROC NLP DATA=POP_DATA(KEEP=POP1-POP42) NOPRINT

 OUT=RESULTS(KEEP=N1-N42)

 /* CONVERGENCE CRITERIA */

 GCONV=1E-15 FCONV2=1E-15 MAXITER=100000;

 /* DECISION VARIABLES */

 DECVAR N1-N42;

 /* COMPUTE THE SQUARED DIFFERENCES */

 %MAC1;

 /* SUM THE SQUARED DIFFERENCES */

 F1=SUM(OF SQR1-SQR42);

 /* FUNCTION TO BE MINIMIZED */

 MIN F1;

 /* PROBLEM CONSTRAINTS */

 BOUNDS N1-N38>=80, N39-N42>=0;

 NLINCON F2=7360, F3=400;

 F2=SUM(OF N1-N38);

 F3=SUM(OF N39-N42);

RUN;

R
30 Consumer Expenditure Survey Anthology, 2005

Part II.

Analyses Using Survey Data
Consumer Expenditure Survey Anthology, 2005 31

From AFDC to TANF:

Have the New Public

Assistance Laws Affected

Consumer Spending of

Recipients?

Laura Paszkiewicz is an economist in the

Branch of Information Analysis, Division of

Consumer Expenditure Surveys, Bureau of

Labor Statistics.

LAURA PASZKIEWICZ Introduction

The Personal Responsibility and Work

Opportunity Reconciliation Act of 1996

(the Welfare Reform Act) replaced the

previous welfare program, Aid to Families with Dependent Children (AFDC),

with a new program, Temporary Assistance for Needy Families (TANF). The

new program gives block grants to

States to design their own welfare programs—provided that they meet certain Federal guidelines. One of the main

requirements is to limit the amount of

time that a person can receive welfare

(hence, temporary assistance).

Since the implementation of the new

laws, numerous research projects have

investigated just how well TANF has

been doing. Some studies have looked

at how the welfare reform affects different groups of people, employment

and earnings, and family structure.

This study looks at how the welfare

reform has affected the spending patterns of welfare recipients. Looking at

spending can give insights into welfare recipients’ quality of life.

Using the Consumer Expenditure

Survey (CE), a comparison of data on

welfare recipients prior to TANF (1988-

89), during the transition to TANF

(1997-98), and post-TANF (2001-02) was

made. An analysis of the sample characteristics of welfare recipients over the

three time periods was done, as well as

an analysis of expenditure patterns.

A brief overview of TANF

The welfare reform established block

grants for States to develop their own

welfare programs as long as certain requirements were met. States were mandated to limit the amount of time that

recipients could receive funds, to require that recipients work when ready

or after 24 months of receiving assistance, and to establish goals to reduce

out-of-wedlock pregnancies.

Prior to the Welfare Reform Act, as

far back as 1987, some States had already established welfare programs

similar to TANF.1

 The Welfare Reform

Act was passed in 1996 and fully implemented in all states by 1998. Data from

1997-98 were used to look at TANF’s

transition period, and data from 2001-

02 were used to look at the post-TANF

time period.

In 2003, TANF was due for reauthorization in Congress. A bill reauthorizing TANF was passed in the House of

Representatives, but not in the Senate.

Funding was extended by Congress

through March of 2005.

1

 This article assumes that these States

would not have a large effect on the welfare

population in the 2 years following the development of their programs. Due to the

design of the CE, data from 1988-89 were

more accessible than earlier data (from 1986-

87), so these data were used to reflect the

welfare population prior to TANF.
32 Consumer Expenditure Survey Anthology, 2005

The sample

Data on welfare receipts are collected

in the income section (section 22) of

the Interview Survey in the CE. Established survey participants are asked to

answer the income section of the questionnaire during the second and fifth

interviews. Respondents who replace

original CUs are also asked to report

their income for section 22 at the time

that they enter the survey. Income information from the second interview is

carried over to the third and fourth interviews.

The screener question about welfare has changed over the three time

periods of interest. For 1988 and 1989

(prior to TANF), each respondent was

asked the following question about

welfare receipts and other forms of income:

“During the past 12 months, did you

(or any member of your CU) receive

income from...worker’s or unemployment compensation; veteran’s payments; public assistance or welfare

from Federal, State, or local welfare

offices?”

If the respondent replied that he or

she had received some form of assistance, he or she was then asked for

each amount individually:

“How much was received from public

assistance or welfare, including money

received from job training grants, such

as Job Corps?”

If a respondent answered affirmatively to the screener question but did

not know or refused to say the amount,

then there was no way to know which

type of assistance was collected.

The question used during 1997 and

1998 (transition to TANF) asked the

respondent about welfare assistance

separately from other forms of assistance and grouped the screener question and the amount question together:

“During the past 12 months, did you

(or any member of your CU) receive

income from...public assistance or

welfare, including money received

from job training grants, such as Job

Corps?”

If the respondent answered affirmatively, the interviewer asked:

“What was the total amount received

by all CU members?”

For 2001 and 2002 (post TANF), the

questions about welfare were similar to

those used during 1997 and 1998, but

the wording specified the AFDC and

Job Corps programs2:

“During the last 12 months, did you

(or any member of your CU) receive

any income from...public assistance

or welfare, such as AFDC and grants

from Job Corps? Do not include nonmonetary assistance, such as food

stamps.”

If the respondent answered affirmatively, the interviewer asked:

“What was the total amount received

by all CU members?”

An additional difference in the 2001

and 2002 questionnaires was the introduction of income ranges or brackets

in section 22. If the respondent did not

know or refused to say the amount of

the welfare payments received, he or

she would be shown a number of brackets and asked to indicate which bracket

the amount fell in. The introduction of

brackets decreased the percentage of

overall refusals to the amount question.

The differences in the questions

between 1988 and 2002 led to the definition of the welfare sample used in this

study. Because the screener question

that was used in 1988 and 1989 did not

separate welfare payments from other

forms of income, it was not possible to

identify welfare recipients based on

that screener question. Instead, a welfare recipient was defined as a person

who reported a positive amount for

welfare assistance (or indicated an income bracket for 2001 or 2002) when

asked about specific amounts. Respondents in CUs who refused to provide

an amount or did not know the amount

of welfare assistance and would not

provide a bracket (in 2001-02) were excluded from the sample. No other

sample restrictions were made.

The sample was weighted to match

the U.S. population; and, using the

above definition of a welfare recipient,

the weighted welfare sample made up

3.2 percent of the population in the

1988-89 period, 2.3 percent in the 1997-

98 period, and 1.4 percent in the 2001-

02 period.3

 The decreasing percentage

of welfare recipients was expected because TANF was designed to give temporary assistance. This is consistent

with data on welfare receipts published

in the 2003 Statistical Abstract, which

shows that the percent of families receiving welfare decreased from 4.1 percent in 1988-89 to 3.34 percent in 1997-

98, and, then, to 1.91 percent in 2001-02.4

Sample characteristics

In the 1988-89 period, 83.1 percent of

consumer units (CUs) who received

welfare payments also received some

other form of assistance (food stamps,

housing assistance, unemployment

compensation, or worker’s compensation). (See table 1.) This percentage

didn’t change significantly in 1997-98

or 2001-02. 5 The largest form of additional assistance among welfare recipients was food stamps. Seventy-eight

percent of welfare recipients also received food stamps in 1988-89, but this

percentage decreased from 73.1 in 1997-

98 to 66.8 percent in 2001-02.6 The Welfare Reform Act also imposed some

stricter eligibility requirements for receiving food stamps, which may explain

some of the decline in food stamp recipients among welfare recipients.

Other studies have shown overall declines in the numbers of both welfare

and non-welfare recipients receiving

food stamps. Percentages of welfare

recipients receiving other forms of assistance either increased or trended

upwards over the same three time periods.

2

 Although AFDC was discontinued in

1996, the CE did not reflect this change until

2003.

3

 Including the CUs who claimed welfare

receipts but did not know the amount or refused to share the amount, welfare recipients

made up 3.1 percent of the population in

1997-98 and 1.6 percent in 2001-02. This

statistic is not available for 1988-89. 4

 These statistics from the Statistical Abstract differ slightly from the CE numbers

due to definitional differences and sample

error. 5

 All significance tests are at the .05 significance level. 6

 Whenever the words “increase or decrease” are used, the modifier “statistically

significant” should be understood.
Consumer Expenditure Survey Anthology, 2005 33

The distribution of welfare recipients by race in the sample changed significantly between 1988-89 and 2001-

02. The percentage of welfare recipients

who were White increased from 53.7

percent in 1988-89 to 58.1 percent in

1997-98 and, then, to 61.4 percent in

2001-02. The percentage of welfare recipients who were Black decreased from

41.6 percent in 1988-89 to 36.4 percent

in 1997-98 and, then, to 31.3 percent in

2001-02. For the non-welfare population, the percentage of Whites in the

sample decreased from 87.7 percent to

84.7 percent and, then, to 83.6 percent,

while the percentage of Blacks increased from 9.6 percent to 11.3 percent and, then, to 11.9 percent. The

percentage of welfare recipients who

were Hispanic rose from 16.0 percent

to 20.3 percent and, then, to 21.5 percent over the three time periods, but

these changes weren’t statistically significant.

Among welfare recipients, single

mothers were the largest portion of the

population for all three time periods with

no significant changes. Single mothers composed 41.5 percent of the welfare population in the 1988-89 period,

38.3 percent in the 1997-98 period, and

38.1 percent in the 2001-02 period.

There were not many fluctuations in

the distribution of family type among

welfare recipients over these time periods. The only significant change was

a 3 percent decrease in the population

of husband and wife families with at

least one school-aged child.

The average size of CUs receiving

welfare did not change significantly

with the implementation of TANF. In

1988-89, the average CU size was 3.7

persons; in 1997-98 and 2001-02, it was

3.6 persons. The percentage of welfare recipients that were two-person

CUs significantly increased from 16.9

percent in 1988-89 to 21.9 percent in

2001-02. The only other significant

change for welfare recipients was a

decrease in five-person CUs from 16.7

percent in 1997-98 to 11.6 percent in

2001-02. For non-welfare CUs, the

percent distribution of CU sizes did

not vary much over the three time

periods.

Expenditures

To compare expenditure patterns over

time, data on relative shares (the percent of total expenditures accounted

for by an expenditure item or component), percent reporting (the percent of

the sample that reported an expenditure greater than zero for the item or

component), and selected means were

tracked. Looking at all three types of

statistics gives a better idea of spending patterns over time than looking at

only one type.

Typically, relative shares do not fluctuate much from year to year, so large

changes in shares indicate changes in

spending patterns. Shares also remain

pretty consistent if prices rise for everything at an equal rate and all else

remains constant.

When comparing the percent reporting, keep in mind that expenditures can

be affected by various factors, including policy changes. For example, with

a policy change requiring welfare recipients to work, an increase in people

with work-related expenditures would

be expected. Thus, spending on child

care services would be likely to increase

as well as expenditures on commuting

costs, and, possibly, work apparel.

In order to compare means over the

three time periods, it was necessary to

remove the effects of price changes

over those periods. For selected items,

which are described in the following

paragraphs, means were compared after they were adjusted to 2002 dollars

by the Consumer Price Index.7

 Means

can be affected by the price of a good

or service and the number of people

reporting it. When more CUs report an

expenditure, the mean will increase. If

there is a low percent reporting for a

particular item, then the mean can be

highly variable and can show large

jumps from year to year. The means

here were adjusted for change in price

and have a relatively large percent reporting, so they should not have as

much variability.

For welfare recipients, there were

significant changes in spending patterns in a number of categories, based

on fluctuations in the expenditure

shares, percent reportings, and inflation-adjusted means. For specifics, see

the text and tables that follow.

Food

There were a number of significant

changes in the food category. The percent of welfare recipients who reported

an expense for eating away from home

increased from 56.5 in 1988-89 to 64.4

in 1997-98 and, then, to 69.6 in 2001-02.

(See table 2.) This is a contrast to the

non-welfare population, in which the

percentage of the group eating away

from home declined over the same time

period from 85.2 percent in 1988-89 to

85.3 percent in 1997-98 and, then, to

81.8 in 2001-02.

Expenditure shares for food away

from home did not change significantly

for the welfare population during the

time period before and after TANF;

however, the share for food at home

decreased. About 5 percentage points

less of the household budget was spent

on groceries in 2001-02 than in 1988-

89. (See table 3.) The non-welfare population spent about 1.5 percentage

points less of their budget on groceries in 2001-02 than they did in 1988-89.

There were no significant changes

in the adjusted means for food expenditures among welfare recipients, but

there was an upward trend of average

expenditures for food away from home,

which rose from $441 in 1988-89 to $485

in 1997-98 and, then, to $581 in 2001-

02. (See table 4.) The adjusted means

decreased significantly for expenditures on food away from home in the

non-welfare population. The average

fell from $1,661 in 1988-89 to $1,526 in

1997-98 and, then, to $1,428 in 2001-

02.

Spending on food includes expenditures made using all available sources

of income, including food stamps. As

noted previously, the overall percent

of the welfare sample and non-welfare

sample receiving food stamps decreased with the welfare reform over

the three time periods in this study.

This could have affected the food expenditure results.

7

 Not all expenditure items had an associated price index.
34 Consumer Expenditure Survey Anthology, 2005

Housing

After the welfare reform, there were a

larger number of home owners among

welfare recipients; the percent reporting expenditures on owned dwellings

nearly doubled from 13.1 percent in

1988-89 to 25.0 percent in 2001-02. The

relative share of total expenditures on

owned dwellings also increased, from

2.7 percent of the total in 1988-89 to 5.2

percent in 2001-02. The non-welfare

sample showed similar increases in

both the percent reporting and the relative share spent on owned dwellings

over that time period. In the 1988-89

period, 55.3 percent of the non-welfare

population reported expenditures on

owned dwellings; in the 2001-02 period,

66.9 percent reported expenditures on

owned dwellings. The relative share

spent on owned dwellings by the nonwelfare population rose from 10.9 percent in 1988-89 to 13.6 percent in 2001-

02. Although the relative shares of

expenditures on rented dwellings did

not significantly change for either

group before and after the implementation of TANF, there was a significant

decrease in the percent of CUs reporting expenditures on rented dwellings

for both groups. For the welfare population, reporting dropped from 82.7 percent in 1988-89 to 82.0 percent in 1997-

98 and, then, to 72.2 percent in 2001-02;

and for non-welfare recipients, reporting dropped from 35.5 percent in 1988-

89 to 33.4 percent in 1997-98 and, then,

to 31.6 percent in 2001-02.

Transportation

There were some significant changes

in the transportation category of the

survey. Transportation includes purchases of vehicles; vehicle finance

charges; vehicle insurance; vehicle

rental, leases, and licenses; gas and

motor oil; maintenance and repairs; and

public transportation. For overall

transportation, there was an increase

in the share of total expenditures between 1988-89 and 2001-02; the share

rose from 13.3 percent of total expenditures in 1988-89 to 16.0 percent in 1997-

98 and, then, to 18.1 percent in 2001-02.

There was no significant change in

expenditure shares for non-welfare

recipients. Within the transportation

category, there was a significant decrease in percent reporting for used

cars and trucks for the welfare and nonwelfare populations; however, shares

of expenditures on used cars and trucks

trended upward for the welfare population and increased for the non-welfare population. The percent reporting

new cars and trucks trended upward

between 1988-89 and 2001-02 for welfare recipients. The percent reporting

new cars and trucks decreased for nonwelfare recipients over the same time

period. Shares of expenditures on new

cars and trucks increased between

1988-89 and 2001-02 for welfare recipients from 0.4 percent of total expenditures in 1988-89 to 2.1 percent in 2001-

02. Shares of expenditures on new cars

and trucks decreased for non-welfare

recipients over the same time period

from 5.3 percent to 4.5 percent.

Public transportation expenditures

remained constant between 1988-89

and 1997-98, but showed a significant

drop in expenditure shares and percent

reporting for both welfare and non-welfare recipients between 1997-98 and

2001-02. Public transportation spending includes airfares as well as expenditures on buses, trains, and other

forms of mass transit. The time period

after 9/11 caused a drop in overall expenditures on airfares, most likely driving the decrease in overall public

transportation expenditures. A subcategory for public transportation was

available only for 1997-98 and 2001-02,

which includes data on intracity mass

transit, taxis and limousines, and

school buses (excluding all public

transportation expenditures on trips).8

Data available between 1997-98 and

2001-02 indicate that the share of total

expenditures spent on intracity mass

transit, taxi fares and limousines, and

school buses by the welfare population decreased from 0.2 percent to 0.1

percent between 1997-98 and 2001-02.

The percent reporting expenditures for

these items also declined from 4.4 percent to 2.9 percent.

With the work requirement for welfare recipients that was instituted with

the 1996 legislation, welfare recipients

were expected to have more transportation expenditures due to the necessity of commuting. Data indicate that

vehicle purchases and operating expenditures increased for welfare recipients

from before to after the welfare reform,

even though public transportation expenditures decreased.

Child care

With the new work requirements for receiving TANF benefits and the large

percentage of single parents receiving

benefits, expenditures on child care

were expected to increase. While there

were no significant changes for the

welfare population, the percent reporting an expenditure for child care

trended upward from 8.8 percent in

1988-89 to 10.6 percent in 2001-02. Alternately, percent reporting for child

care by the non-welfare population decreased over the three time periods with

10.0 percent reporting in the 1988-89

period, 8.8 percent reporting in the

1997-98 period, and 8.1 percent reporting in the 2001-02 period. There were

no significant changes in expenditure

shares for child care in either group.

Entertainment

Before the welfare reform, 70.2 percent

of welfare recipients reported an expenditure on entertainment. The percentage rose to 82.1 in 1997-98 and to 83.5

percent in 2001-02. For non-welfare

recipients, the percent reporting also

increased overall, rising from 86.7 percent in 1988-89 to 90.0 percent in 1997-

98, but, then, remaining about the same

for 2001-02. A large part of the change

in the percent reporting appears to be

from the purchase of televisions, radios,

and sound equipment. The percent of

welfare recipients reporting an expenditure on that component rose from 49.8

percent to 72.3 percent between 1988-

89 and 2001-02. For non-welfare recipients, spending on that component rose

from 70 to 81.8 percent over the same

time period. There were no significant

changes in the expenditure shares of

overall entertainment expenditures for

8

 Trips are defined as any overnight trips

or day trips of 75 or more miles.
Consumer Expenditure Survey Anthology, 2005 35

either group during that time period;

however, the non-welfare recipients’ expenditure share on televisions, radios,

and sound equipment rose slightly.

Apparel

There were not many significant differences in percent reporting or in expenditure shares on apparel for the welfare

sample. Overall, the total share on apparel decreased between 1988-89 and

2001-02 from 6.9 percent to 5.2 percent

of total expenditures, respectively. The

two significant differences in shares

among the subcomponents were for

footwear expenditures and for men’s

and boys’ apparel expenditures: both

had a significant decrease. Footwear

expenditures also showed the only decrease in percent reporting for the welfare sample. Although there were not

many significant changes, the welfare

population showed similar trends to the

spending patterns of the non-welfare

population. For the non-welfare population, the percentage of CUs reporting and the shares of expenditures decreased for most of the apparel subcomponents.

Other

A number of other categories showed

significant changes between the preTANF and post-TANF welfare period.

The percent of CUs reporting spending on health insurance increased for

the welfare and non-welfare populations between 1988-89 and 2001-02. For

welfare recipients, the percent reporting health insurance rose from 14.9 percent in 1988-89 to 20.1 percent in 1997-

98 and, then, to 24.6 percent in 2001-02.

For the non-welfare group, these percentages were 57.0 percent, 63.8 percent, and 63.0 percent, respectively.

The share of expenditures on health insurance also increased over that time

period for both groups. The welfare

group allocated 0.7 percent of their total expenditures to health insurance in

1988-89. This share went from 1.1 percent in 1997-98 to 1.6 percent in 2001-

02. The non-welfare group allocated

2.0 percent of their total expenditures

to health insurance in 1988-89, 2.8 percent in 1997-98, and 3.0 percent in 2001-

02. For expenditures on life and other

personal insurance, the percent reporting decreased for both groups, and the

expenditure shares also decreased for

both groups.

Conclusion

Overall, there were some significant

changes in spending by welfare recipients from the pre-TANF to post-TANF

period. Many changes for the welfare

population, such as the change from

renting to owning, have followed the

trends of the non-welfare population.

Other changes in the spending patterns of welfare recipients, such as expenditures on food away from home,

have been different from the trends of

the non-welfare recipients. While it

may not be possible to definitely attribute the reason for changes in spending to the introduction of TANF, CE

data show that there were some significant changes from the pre-TANF to

the post-TANF period.
36 Consumer Expenditure Survey Anthology, 2005

Table 1. Characteristics of welfare and non-welfare sample, Consumer Expenditure Survey, 1988-89, 1997-98, and 2001-02,

in percent

Receiving public assistance:

Any type

Welfare .............................................................................................. 83.1 80.1 81.2

Non-welfare ...................................................................................... 11.3 10.3 * 12.0 +

Food stamps

Welfare............................................................................................ 78.0 73.1 66.8 *

Non-welfare .................................................................................... 3.3 4.0 * 2.4 * +

Housing

Welfare ........................................................................................... 28.2 34.2 38.3 *

Non-welfare .................................................................................... 2.3 3.2 * 7.0 * +

Unemployment compensation

Welfare .......................................................................................... 3.7 4.6 6.5 *

Non-welfare .................................................................................... 4.0 2.8 * 2.9 *

Workers’ compensation

Welfare ........................................................................................... 1.6 1.8 3.1

Non-welfare .................................................................................... 3.0 1.8 * 1.1 * +

Race1:

White

Welfare .............................................................................................. 53.7 58.1 61.4 *

Non-welfare ...................................................................................... 87.7 84.7 * 83.6 * +

Black

Welfare .............................................................................................. 41.6 36.4 31.3 *

Non-welfare ...................................................................................... 9.6 11.3 * 11.9 * +

Other

Welfare ............................................................................................. 4.7 5.5 7.4

Non-welfare ...................................................................................... 2.7 4.0 * 4.5 * +

Hispanic origin2:

Hispanic

Welfare ............................................................................................. 16.0 20.3 21.5

Non-welfare ...................................................................................... 5.7 8.1 * 8.8 * +

Non-Hispanic

Welfare ............................................................................................. 84.0 79.7 78.5

Non-welfare ...................................................................................... 94.3 91.9 * 91.2 * +

Age3:

Under 25

Welfare ............................................................................................. 13.8 16.4 18.5

Non-welfare ...................................................................................... 7.6 7.2 7.7

25 to 34

Welfare ............................................................................................. 32.8 26.2 20.8

Non-welfare ...................................................................................... 20.2 17.0 15.4

35 to 44

Welfare ............................................................................................. 20.2 24.5 23.6

Non-welfare ...................................................................................... 18.8 20.7 20.0

45 to 54

Welfare ............................................................................................. 11.4 11.8 16.4

Non-welfare ...................................................................................... 13.0 16.4 17.9

55 to 64

Welfare ............................................................................................. 6.0 6.5 5.9

Non-welfare ...................................................................................... 12.0 10.6 11.8

65 to 74

Welfare ............................................................................................. 3.8 1.8 3.2

Non-welfare ...................................................................................... 11.0 10.2 9.2

Over 75

Welfare ............................................................................................. 2.3 1.0 3.3

Non-welfare ...................................................................................... 7.8 8.5 8.7

Family type:

Single4

Welfare ............................................................................................. 11.3 9.0 11.0

Non-welfare ...................................................................................... 28.5 29.1 29.8 * +

Husband and wife, oldest child under 6 years

Welfare ............................................................................................. 3.9 3.2 4.3

Non-welfare ...................................................................................... 6.4 5.2 * 4.8 *

Husband and wife, oldest child 6 to 17 years

Welfare ............................................................................................. 7.3 7.3 4.2 *

Non-welfare ...................................................................................... 15.0 14.8 13.8 * +

Characteristic 1988-89 1997-98 2001-02
Consumer Expenditure Survey Anthology, 2005 37

Husband and wife, oldest child over 17

Welfare ............................................................................................. 2.5 2.8 2.6

Non-welfare ...................................................................................... 8.7 7.4 * 7.2 *

Husband and wife, no children

Welfare ............................................................................................. 1.3 1.9 3.2

Non-welfare ...................................................................................... 22.2 22.0 21.0 * +

Single mom

Welfare ............................................................................................. 41.5 38.3 38.5

Non-welfare ...................................................................................... 4.0 4.6 * 4.8 *

Single dad

Welfare ............................................................................................. 2.0 .8 2.45

Non-welfare ...................................................................................... .7 .8 .8

Other family type

Welfare ............................................................................................. 23.5 29.1 26.3

Non-welfare ...................................................................................... 10.8 12.3 * 13.8 * +

Family size:

Single

Welfare ............................................................................................. 11.3 9.0 11.0

Non-welfare ...................................................................................... 28.5 29.1 29.8 * +

2 persons

Welfare ............................................................................................. 16.6 17.1 21.9 * Non-welfare ...................................................................................... 30.8 31.2 31.0

3 persons

Welfare ............................................................................................. 24.1 24.8 23.0

Non-welfare ...................................................................................... 16.4 15.7 15.2 * 4 persons

Welfare ............................................................................................. 20.0 20.8 19.2

Non-welfare ...................................................................................... 14.3 14.2 14.0

5 persons

Welfare ............................................................................................. 14.1 16.7 11.6 +

Non-welfare ...................................................................................... 6.4 6.3 6.3

More than 6 persons

Welfare ............................................................................................. 13.9 11.6 13.3

Non-welfare ...................................................................................... 3.5 3.5 3.6

Table 1. Characteristics of welfare and non-welfare sample, Consumer Expenditure Survey, 1988-89, 1997-98, and 2001-02,

in percent—Continued

1988-89 1997-98 2001-02

* Indicates statistical difference from 1988-89 at the 0.05 significance level

+ Indicates statistical difference from 1997-98 at the 0.05 significance level 1

 Race refers to race of the reference person.

2

 Hispanic origin refers to Hispanic origin of the reference

person. 3

 Age refers to the age of the reference person.

4

 Even though AFDC and TANF are both intended for families

with children, the question asks for income from public assisCharacteristic

tance for the past 12 months. This question is also only asked

during the second and fifth interview. If the person is in the fourth

interview, then data from the second interview will be used. In this

case, the CU could have received income from welfare up to 19

months prior. The family type of the CU will be current to the quarter.

If the CU, now listed as single, previously was listed with children, then the CU could have received AFDC or TANF. Furthermore, the welfare question also asks whether respondents received any income from Job Corp grants in 1997-98 and 2001-02.

These are possible examples of singles with welfare.
38 Consumer Expenditure Survey Anthology, 2005

Food total:

Welfare ................................................................................................... 99.1 99.4 98.8

Non-welfare ............................................................................................ 99.2 99.4 99.5 * +

Food at home

Welfare ................................................................................................. 98.4 98.6 98.6

Non-welfare ......................................................................................... 99.2 99.4 * 98.9 * +

Food away

Welfare ................................................................................................. 56.5 64.4 * 69.6 *

Non-welfare ......................................................................................... 85.2 85.3 81.8 * +

Alcoholic beverages

Welfare ................................................................................................... 30.1 22.8 * 22.8

Non-welfare ............................................................................................ 50.9 45.8 * 42.1 *

Housing:

Welfare ................................................................................................... 47.0 52.2 * 48.8

Non-welfare ............................................................................................ 65.4 61.3 * 55.2 *

Shelter

Welfare ................................................................................................. 95.5 99.3 * 96.9 +

Non-welfare ......................................................................................... 91.7 98.2 * 97.6 * +

Owned dwellings:

Welfare .............................................................................................. 13.1 17.4 25.0 * +

Non-welfare ...................................................................................... 55.3 65.4 * 66.9 * +

Mortgage interest

Welfare ........................................................................................... 8.3 9.0 13.7 *

Non-welfare .................................................................................... 38.2 39.8 * 41.3 * +

Property tax

Welfare ........................................................................................... 4.2 16.7 * 23.9 *

Non-welfare .................................................................................... 18.8 64.8 * 65.6 * +

Maintenance, repairs, insurance, and other expenses

Welfare ........................................................................................... 8.9 9.6 14.2 *

Non-welfare .................................................................................... 36.8 39.3 * 39.0 *

Rented dwellings

Welfare .............................................................................................. 82.7 82.0 72.2 * +

Non-welfare ...................................................................................... 35.5 33.4 * 31.6 * +

Other lodging

Welfare .............................................................................................. 4.9 5.0 4.5

Non-welfare ...................................................................................... 26.8 23.0 * 21.4 * +

Utilities, fuels, and public services:

Welfare ................................................................................................. 94.9 96.9 96.8

Non-welfare ........................................................................................ 98.1 98.3 97.9 +

Natural gas

Welfare .............................................................................................. 50.1 48.2 47.2

Non-welfare ...................................................................................... 48.6 49.6 50.1

Electricity

Welfare .............................................................................................. 78.2 81.5 85.0

Non-welfare ...................................................................................... 90.5 91.7 * 91.9 *

All other fuels

Welfare .............................................................................................. 4.8 6.7 5.0

Non-welfare ...................................................................................... 14.0 11.6 * 9.9 * +

Telephone

Welfare .............................................................................................. 79.8 89.2 * 87.5 *

Non-welfare ...................................................................................... 95.3 96.3 * 95.7 +

Water and public services ..................................................................

Welfare .............................................................................................. 31.6 31.8 31.9

Non-welfare ...................................................................................... 57.9 59.2 * 62.7 * +

Household operations:

Welfare ................................................................................................. 29.3 29.2 37.4 *

Non-welfare ........................................................................................ 41.8 43.6 54.3 * +

Domestic services

Welfare .............................................................................................. 24.2 24.2 26.4

Non-welfare ...................................................................................... 35.0 33.5 31.1 *

Babysitting and daycare services

Welfare .............................................................................................. 8.8 10.0 10.6

Non-welfare ...................................................................................... 10.0 8.8 * 8.1 *

Other household expenditures

Welfare .............................................................................................. 6.7 7.0 17.3 * +

Non-welfare ...................................................................................... 12.1 18.7 * 39.3 * +

Table 2. Percent reporting expenditures for selected items, Consumer Expenditure Survey, 1988-89, 1997-98, and 2001-02,

in percent

Item 1988-89 1997-98 2001-02
Consumer Expenditure Survey Anthology, 2005 39

Household furnishings and equipment:

Welfare ................................................................................................. 100.0 99.9 99.8 +

Non-welfare ......................................................................................... 99.8 99.8 99.6 * +

Household textiles

Welfare .............................................................................................. 20.3 21.3 16.4 +

Non-welfare ...................................................................................... 26.6 22.2 * 19.4 * +

Furniture

Welfare .............................................................................................. 10.9 13.1 * 12.9

Non-welfare ...................................................................................... 15.5 13.9 * 12.2 * +

Floor coverings

Welfare .............................................................................................. 2.4 3.2 3.2

Non-welfare ...................................................................................... 4.0 3.8 3.3 * Major appliances

Welfare .............................................................................................. 6.6 8.0 8.7

Non-welfare ...................................................................................... 9.7 8.8 * 8.7 * Small appliances

Welfare .............................................................................................. 19.6 18.8 16.4

Non-welfare ...................................................................................... 22.8 19.7 * 17.4 * +

Miscellaneous household equipment

Welfare .............................................................................................. 26.6 31.7 30.2

Non-welfare ...................................................................................... 48.2 45.5 * 40.4 * +

Apparel and services:

Welfare ................................................................................................... 87.5 86.3 85.5

Non-welfare ............................................................................................ 89.4 86.1 * 80.1 * +

Men’s and boys’ apparel:

Welfare ................................................................................................. 39.0 42.4 36.2

Non-welfare ......................................................................................... 52.3 47.9 * 43.1 * +

Men, 16 and over

Welfare .............................................................................................. 16.4 19.5 16.8

Non-welfare ...................................................................................... 46.2 40.8 * 36.6 * +

Boys, 2 to 15 .......................................................................................

Welfare .............................................................................................. 23.4 29.3 24.3

Non-welfare ...................................................................................... 16.1 15.4 * 13.2 * +

Women’s and girls’ apparel:

Welfare ................................................................................................. 60.3 54.9 54.4

Non-welfare ......................................................................................... 64.6 59.2 * 52.8 * +

Women, 16 and over

Welfare .............................................................................................. 47.9 42.3 44.3

Non-welfare ...................................................................................... 61.1 54.5 * 48.1 * +

Girls, 2 to 15

Welfare .............................................................................................. 31.1 28.7 27.0

Non-welfare ...................................................................................... 16.9 16.4 14.0 * +

Children under 2

Welfare ................................................................................................. 28.2 30.6 31.2

Non-welfare ......................................................................................... 17.4 17.6 14.9 * +

Footwear

Welfare ................................................................................................. 44.6 40.6 38.4 * Non-welfare ........................................................................................ 47.0 40.3 * 32.9 * +

Other apparel products and services

Welfare ................................................................................................ 56.5 52.6 50.6

Non-welfare ......................................................................................... 63.4 55.8 * 46.2 * +

Transportation:

Welfare ................................................................................................... 77.9 83.4 * 78.7

Non-welfare ............................................................................................ 94.8 94.7 94.0 * +

Cars and trucks, new (net outlay)

Welfare ................................................................................................. .2 .3 .5

Non-welfare ......................................................................................... 2.6 1.7 * 4.8 *

Cars and trucks, used (net outlay)

Welfare ................................................................................................. 7.2 6.5 5.3 *

Non-welfare ......................................................................................... 5.9 5.1 * 4.8 *

Other vehicles

Welfare ................................................................................................. .3 n.a. n.a.

Non-welfare ......................................................................................... .3 .2 * .2 *

Vehicle finance charges

Welfare ................................................................................................. 11.6 14.2 14.4

Non-welfare ......................................................................................... 37.2 32.0 * 32.7 *

Table 2. Percent reporting expenditures for selected items, Consumer Expenditure Survey, 1988-89, 1997-98, and 2001-02,

in percent—Continued

Item 1988-89 1997-98 2001-02
40 Consumer Expenditure Survey Anthology, 2005

Table 2. Percent reporting expenditures for selected items, Consumer Expenditure Survey, 1988-89, 1997-98, and 2001-02,

in percent—Continued

Gas and motor oil

Welfare ................................................................................................ 53.8 58.4 62.1 *

Non-welfare ......................................................................................... 90.1 89.9 89.4

Maintenance and repairs

Welfare ................................................................................................. 28.6 35.1 29.9

Non-welfare ......................................................................................... 60.7 61.2 56.6 * +

Vehicle insurance

Welfare ................................................................................................ 19.8 30.0 * 33.2 *

Non-welfare ......................................................................................... 47.4 52.3 * 55.6 * +

Public transportation

Welfare ................................................................................................. 33.4 32.3 25.0 * +

Non-welfare ......................................................................................... 23.2 22.2 19.8 * +

Intracity mass transit, taxis and limousines, and school buses1

Welfare .............................................................................................. - 4.4 2.9

Non-welfare ...................................................................................... - 13.9 12.2 +

Health care:

Welfare ................................................................................................... 38.1 38.6 39.8

Non-welfare ............................................................................................ 80.9 81.3 79.7 +

Health insurance

Welfare ................................................................................................. 14.9 20.1 * 24.6 *

Non-welfare ........................................................................................ 57.0 63.8 * 63.0 *

Medical services

Welfare ................................................................................................. 19.5 17.8 15.4

Non-welfare ......................................................................................... 54.7 48.7 * 45.5 * +

Prescription drugs

Welfare ................................................................................................. 25.5 21.1 24.2

Non-welfare ......................................................................................... 52.9 46.4 * 49.3 * +

Entertainment:

Welfare ................................................................................................... 70.2 82.1 * 83.5 *

Non-welfare ............................................................................................ 86.7 90.0 * 89.6 *

Fees and admissions

Welfare ................................................................................................. 28.2 27.3 32.2

Non-welfare ........................................................................................ 57.9 56.9 51.0 * +

TVs, radios, and sound equipment

Welfare ................................................................................................. 49.8 67.8 * 72.3 *

Non-welfare ........................................................................................ 70.0 81.6 * 81.8 *

Personal care products and services

Welfare ................................................................................................... 47.2 49.4 48.4

Non-welfare ............................................................................................ 79.3 75.3 * 74.4 *

Reading

Welfare ................................................................................................... 48.8 41.6 * 33.1 * +

Non-welfare ............................................................................................ 76.5 65.1 * 54

Education

Welfare ................................................................................................... 12.6 17.7 * 14.8

Non-welfare ............................................................................................ 16.7 18.3 16.9 +

Tobacco

Welfare ................................................................................................... 55.5 44.9 * 37.3 * +

Non-welfare ............................................................................................ 37.9 28.8 * 24.3 * +

Miscellaneous

Welfare ................................................................................................... 20.7 25.3 31.3 *

Non-welfare ............................................................................................ 48.9 46.4 * 47.3

Personal insurance and pensions:

Welfare ................................................................................................... 54.1 53.0 64.6 * +

Non-welfare ............................................................................................ 80.7 76.5 * 77.1 *

Life and other personal insurance

Welfare ................................................................................................. 22.1 16.6 14.1 *

Non-welfare ......................................................................................... 45.5 41.6 39.5 * +

Retirement, pensions, and Social Security

Welfare ................................................................................................. 41.1 47.4 59.3 * +

Non-welfare ......................................................................................... 70.6 64.7 * 66.4 *

* Indicates statistical difference from 1988-89 at the 0.05

significance level

+ Indicates statistical difference from 1997-98 at the 0.05

significance level 1 Data on intracity mass transit, taxis and limousines, and

school buses are only available for 1997-98 and 2001-02.

Item 1988-89 1997-98 2001-02
Consumer Expenditure Survey Anthology, 2005 41

Food total:

Welfare ................................................................................................... 27.4 23.4 * 22.1 * Non-welfare ............................................................................................ 16.3 15.0 * 14.1 * +

Food at home

Welfare ................................................................................................. 24.7 20.9 * 19.3 *

Non-welfare ......................................................................................... 11.7 10.9 * 10.3 * +

Food away

Welfare ................................................................................................. 2.7 2.5 2.9

Non-welfare ........................................................................................ 4.6 4.2 3.8 * +

Alcoholic beverages

Welfare ................................................................................................... .9 .5 * .5 *

Non-welfare ............................................................................................ 1.0 .9 * .9 * Housing:

Welfare ................................................................................................... 36.7 38.5 48.8

Non-welfare ............................................................................................ 31.4 32.8 * 33.0 *

Shelter

Welfare ................................................................................................. 21.9 23.8 22.3

Non-welfare ........................................................................................ 18.6 19.9 * 20.7 * Owned dwellings:

Welfare .............................................................................................. 2.7 3.9 5.2 * Non-welfare ...................................................................................... 10.9 12.6 * 13.6 * +

Mortgage interest

Welfare ........................................................................................... 1.6 2.2 3.0 *

Non-welfare .................................................................................... 6.7 7.3 * 7.8 * +

Property tax

Welfare ........................................................................................... .6 .7 1.3 * +

Non-welfare .................................................................................... 2.2 3.1 * 3.3 * +

Maintenance, repairs, insurance, and other expenses

Welfare ........................................................................................... .6 .9 .9

Non-welfare .................................................................................... 2.1 2.3 * 2.5 *

Rented dwellings

Welfare .............................................................................................. 18.8 19.6 16.8

Non-welfare ...................................................................................... 5.8 5.9 5.7

Other lodging

Welfare .............................................................................................. .4 .3 .2

Non-welfare ...................................................................................... 1.9 1.4 * 1.4 *

Utilities, fuels, and public services:

Welfare ................................................................................................. 10.4 10.9 10.5

Non-welfare ......................................................................................... 7.1 7.4 * 7.3

Natural gas

Welfare .............................................................................................. 2.0 1.5 * 1.8

Non-welfare ...................................................................................... .9 .9 1.0 +

Electricity

Welfare .............................................................................................. 4.0 4.2 4.0

Non-welfare ...................................................................................... 2.9 2.8 2.7 * +

All other fuels

Welfare .............................................................................................. .3 .2 .2

Non-welfare ...................................................................................... .4 .3 * .3 * Telephone

Welfare .............................................................................................. 3.3 4.1 * 3.7

Non-welfare ...................................................................................... 2.2 2.5 * 2.5 *

Water and public services

Welfare .............................................................................................. .8 .9 .9

Non-welfare ...................................................................................... .7 .9 * .9 *

Household operations:

Welfare .............................................................................................. 1.2 1.2 1.5

Non-welfare ...................................................................................... 1.7 1.7 1.9 * +

Domestic services

Welfare .............................................................................................. .9 1.0 1.2

Non-welfare ...................................................................................... 1.4 1.4 1.4

Babysitting and daycare services

Welfare .............................................................................................. .2 .2 .3

Non-welfare ...................................................................................... .2 .2 .2

Other household expenditures

Welfare .............................................................................................. .3 .2 .4 +

Non-welfare ...................................................................................... .3 .3 .5 * +

Item 1988-89 1997-98 2001-02

Table 3. Shares of total expenditures spent on selected items, Consumer Expenditure Survey, 1988-89, 1997-98, and

2001-02, in percent
42 Consumer Expenditure Survey Anthology, 2005

Household furnishings and equipment:

Welfare ................................................................................................. 3.1 2.7 2.5

Non-welfare ......................................................................................... 4.0 3.8 * 3.2

Household textiles

Welfare .............................................................................................. .3 .2 .2

Non-welfare ...................................................................................... .4 .2 * .2 * +

Furniture

Welfare .............................................................................................. 1.1 1.0 .9

Non-welfare ...................................................................................... 1.3 1.2 * 1.0 * +

Floor coverings

Welfare .............................................................................................. n.a. .1 n.a.

Non-welfare ...................................................................................... .2 .2 * .1 * +

Major appliances

Welfare .............................................................................................. .7 .4 * .4 * Non-welfare ...................................................................................... .6 .5 * .5 * +

Small appliances

Welfare .............................................................................................. .2 .2 .1 * Non-welfare ...................................................................................... .2 .2 * .1 * +

Miscellaneous household equipment

Welfare .............................................................................................. .7 .8 .8

Non-welfare ...................................................................................... 1.3 1.5 * 1.2 +

Apparel and services:

Welfare ................................................................................................... 6.9 5.5 5.2 * Non-welfare ............................................................................................ 5.2 4.2 * 3.6 * +

Men’s and boys’ apparel:

Welfare ................................................................................................. 1.3 1.0 1.0 *

Non-welfare ......................................................................................... 1.3 1.1 * 1.0 * +

Men, 16 and over

Welfare .............................................................................................. .5 .3 .4

Non-welfare ...................................................................................... 1.1 .9 * .7 * +

Boys, 2 to 15

Welfare .............................................................................................. .9 .7 .6 *

Non-welfare ...................................................................................... .2 .2 .2 * +

Women’s and girls’ apparel:

Welfare .............................................................................................. 2.4 1.9 1.8

Non-welfare ...................................................................................... 2.1 1.6 * 1.4 * +

Women, 16 and over

Welfare ........................................................................................... 1.5 1.1 1.1

Non-welfare .................................................................................... 1.8 1.3 * 1.2 * +

Girls, 2 to 15

Welfare ........................................................................................... .9 .8 .7

Non-welfare .................................................................................... .3 .3 .3 * +

Children under 2

Welfare .............................................................................................. 1.1 .9 1.0

Non-welfare ...................................................................................... .2 .2 .2 * +

Footwear

Welfare ........................................................................................... .8 .7 .6 *

Non-welfare .................................................................................... .5 .5 * .3 * +

Other apparel products and services

Welfare ........................................................................................... 1.3 1.1 .8 * Non-welfare .................................................................................... 1.1 .8 * .7 * +

Transportation:

Welfare ................................................................................................... 13.3 16.0 18.1 * Non-welfare ............................................................................................ 20.5 20.0 20.4

Cars and trucks, new (net outlay)

Welfare ................................................................................................. .4 1.1 2.1 *

Non-welfare ......................................................................................... 5.3 4.1 * 4.5 * +

Cars and trucks, used (net outlay)

Welfare ................................................................................................. 4.5 5.9 6.8

Non-welfare ......................................................................................... 4.0 4.6 * 4.9 * +

Other vehicles

Welfare ................................................................................................. .3 n.a. n.a.

Non-welfare ......................................................................................... .1 .1 * .2 *

Vehicle finance charges

Welfare ................................................................................................. .4 .6 .7 *

Non-welfare ......................................................................................... 1.2 .9 * 1.0 * +

Table 3. Shares of total expenditures spent on selected items, Consumer Expenditure Survey, 1988-89, 1997-98, and

2001-02, in percent—Continued

Item 1988-89 1997-98 2001-02
Consumer Expenditure Survey Anthology, 2005 43

Gas and motor oil

Welfare ................................................................................................. 3.4 3.2 3.4

Non-welfare ......................................................................................... 3.9 3.3 * 3.4 * Maintenance and repairs

Welfare ................................................................................................. 1.5 1.5 1.8

Non-welfare ......................................................................................... 2.1 1.9 * 1.7 * +

Vehicle insurance

Welfare ................................................................................................. 1.3 1.7 1.8 * Non-welfare ......................................................................................... 2.2 2.3 * 2.3 * Public transportation:

Welfare ................................................................................................. 1.0 1.3 .7 * +

Non-welfare ......................................................................................... 1.1 1.3 * 1.1 +

Intracity mass transit, taxis and limousines, and school buses ........

Welfare ................................................................................................. - .2 .1 +

Non-welfare ......................................................................................... - .0 .0 +

Health care:

Welfare ................................................................................................... 2.3 2.7 2.7

Non-welfare ............................................................................................ 5.1 5.4 * 5.7 * +

Health insurance

Welfare ................................................................................................. .7 1.1 * 1.5 * Non-welfare ......................................................................................... 2.0 2.8 * 3.0 * +

Medical services

Welfare ................................................................................................. 1.0 1.0 .5

Non-welfare ......................................................................................... 2.2 1.7 * 1.6 * Prescription drugs

Welfare ................................................................................................. .7 .4 .5

Non-welfare ......................................................................................... .9 .7 * .9 +

Entertainment:

Welfare ................................................................................................... 3.9 4.1 4.4

Non-welfare ............................................................................................ 5.2 5.3 5.1

Fees and admission

Welfare ................................................................................................. .4 .4 .5

Non-welfare ......................................................................................... 1.5 1.5 1.5

TVs, radios, and sound equipment

Welfare ................................................................................................. 2.1 2.3 2.4

Non-welfare ......................................................................................... 1.7 1.8 * 1.8 * Personal care products and services

Welfare ................................................................................................... .9 .9 .6 * +

Non-welfare ............................................................................................ .9 .9 .7 * +

Reading

Welfare ................................................................................................... .4 .3 * .2 * Non-welfare ............................................................................................ .6 .5 * .4 * +

Education

Welfare ................................................................................................... .4 .6 .9

Non-welfare ............................................................................................ 1.3 1.7 * 1.7 *

Tobacco

Welfare ................................................................................................... 2.6 2.1 2.0

Non-welfare ............................................................................................ 1.0 .8 * .8 * Miscellaneous

Welfare ................................................................................................... .8 1.3 1.1

Non-welfare ............................................................................................ 1.2 1.5 * 1.5 *

Personal insurance and pensions:

Welfare ................................................................................................... 3.3 3.8 4.6 * +

Non-welfare ............................................................................................ 9.5 10.2 * 10.2 *

Life and other personal insurance

Welfare ................................................................................................. .8 .5 .6

Non-welfare ......................................................................................... 1.3 1.2 1.1 * +

Retirement, pensions, and Social Security

Welfare ................................................................................................. 2.5 3.2 4.0 *

Non-welfare ........................................................................................ 8.2 9.0 * 9.1 *

Table 3. Shares of total expenditures spent on selected items, Consumer Expenditure Survey, 1988-89, 1997-98, and

2001-02, in percent—Continued

Item 1988-89 1997-98 2001-02

* Indicates statistical difference from 1988-89 at the 0.05

significance level

n.a. Not applicable.

+ Indicates statistical difference from 1997-98 at the 0.05

significance level
44 Consumer Expenditure Survey Anthology, 2005

Table 4. Mean expenditures for selected items (adjusted to 2002 dollars), Consumer Expenditure Survey, 1988-89,

1997-98, and 2001-02

Food total:

Welfare ................................................................................................. $4,553 $ 4,443 $ 4,465

Non-welfare .......................................................................................... 5,995 5,440 * 5,284 * +

Food at home

Welfare ............................................................................................ 4,118 3,852 3,875

Non-welfare .................................................................................... 4,318 3,826 * 3,849 * Food away

Welfare ............................................................................................ 441 485 581

Non-welfare .................................................................................... 1,661 1,526 * 1,428 * +

Alcoholic beverages

Welfare ................................................................................................. 157 89 * 98 *

Non-welfare .......................................................................................... 394 316 * 331 *

Rented dwellings1

Welfare ................................................................................................. 3,297 3,965 * 3,434

Non-welfare .......................................................................................... 2,240 2,273 2,162 +

Reading

Welfare ................................................................................................. 239 178 * 143 * +

Non-welfare .......................................................................................... 76 52 * 47 *

Tobacco

Welfare ................................................................................................. 871 640 * 426 * +

Non-welfare .......................................................................................... 724 465 * 323 * +

Item 1988-89 1997-98 2001-02

1

 Mean expenditures for rent are based on all CUs (homeowners and renters).

* Indicates statistical difference from 1988-89 at the 0.05 significance level

+ Indicates statistical difference from 1997-98 at the 0.05

significance level
Consumer Expenditure Survey Anthology, 2005 45

The growing population of older

Americans has been an important focus of researchers and

policymakers for some time, with issues

such as Social Security benefits, longterm care, and prescription drug costs

at the forefront. Recent studies show

that an increasing number of these older

Americans are also facing issues involved in raising children, such as the

rising costs of child care and higher

education. For example, the U.S. Census Bureau reports that, in 2000, approximately 2.4 million grandparents

were “responsible for the basic needs”

of their co-resident grandchildren.1 At

the same time, the National Center for

Health Statistics reports that the number of births to women aged 45-49 years

has more than quadrupled since 1984,

and births to women aged 50 and older

have increased 13 percent annually

since 1997.2 This article seeks to examine the lifestyle and welfare of these

older caregivers, using demographic

characteristics and spending patterns

derived from the Consumer Expenditure

Survey (CE).

Spending Patterns of

Older Consumers Raising

a Child

Abby Duly is an economist in the Branch of

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

Statistics.

Study methodology

Data presented here were collected by

the CE Interview Survey during the

years 2000, 2001, and 2002. (Three

years of data are necessary to provide

sufficient sample sizes for analysis.)

The Interview component of the CE is

used rather than the Diary because the

Interview Survey is estimated to cover

80 to 95 percent of total expenditures

by consumer units (CUs).3 Specifically,

the Interview Survey collects detailed

data on an estimated 60 to 70 percent

of total household expenditures. In

addition, global estimates, that is, expense patterns for a 3-month period,

are obtained for food and other selected items. These global estimates

account for an additional 20 to 25 percent of total expenditures.

The sample selected for this study

is divided into three groups, based primarily on the age of the reference person4

 and the presence and age of children in the household. First, an “older

with children” group is defined as having a reference person aged 60 or older

and at least one child under the age of

18 years in the household. Furthermore,

ABBY DULY

1 Grandparents Living With Grandchildren: 2000. U.S. Census Bureau, October

2003. 2

 Martin J.A., Hamilton B.E., Sutton P.D.,

Ventura S.J., Menacker F., Munson M.L.

“Births: Final Data for 2002”, National Vital Statistics Reports; Volume 52, Number 10.

National Center for Health Statistics, 2003.

3

 The Consumer Expenditure Survey collects data for consumer units. In this article,

consumer units and households are used interchangeably. See the glossary at the end of

this anthology for the definition of consumer

unit.

4

 See the glossary at the end of this anthology for the definition of reference person.
46 Consumer Expenditure Survey Anthology, 2005

in order to ensure the role of the older

person as caregiver, the sample is further restricted such that no other adults

reside in the home, except the spouse

of the reference person, if there is one.

Additionally, only the reference person

and spouse may earn income. (Presumably, some working teenagers may contribute significantly to the household

budget.5) Two other groups are selected for comparative purposes. First,

in order to determine if there are generational or age-related differences

among households raising children, a

“younger parents” group is selected,

whose reference person is aged 35 to

49 years and for whom there is at least

one child under the age of 18 years.

Second, an “older without children”

group, whose reference person is aged

60 or older with no children present,

provides a measure of how dependent

children in the household may change

the lifestyle of the older generation.

The additional criteria regarding other

adults and earners are also applied to

the younger parents and older without

children groups for consistency. Finally, all three sample groups contain

only persons related by blood, marriage, adoption, or other legal arrangements. The resulting sample sizes are:

9,869 younger parents; 18,056 CUs in

the older without children group; and

206 older households with children.

The first part of the study is a comparison of the three sample groups by

selected demographic characteristics.

Selected sample demographics are displayed in table 1. Then, spending patterns are analyzed using expenditure

shares, which are the proportions of

total household expenditures allocated

to specific categories of expense.

Shares analysis has two important advantages in this study. First, using proportions of total spending allows for

meaningful comparisons among groups

of CUs with very different incomes, as

is the case here. (See table 1.) Additionally, expenditure shares provide

insight into the relative importance of

one spending category over another,

indicating that some budgetary decisions are being made. In order to test

the significance of observed differences in spending, the standard t-test

formula is modified to account for the

use of proportional measures.6

 Before

presenting any findings, it is important

to note that the results of these analyses are not weighted to the general

population.

Demographic comparisons

As previously mentioned, the average

incomes of the three groups are quite

different. Most notable is the roughly

$30,000-per-year gap between those

older CUs with children and those without children. Not surprisingly, those

with children are younger on average

(67 years old compared with 73 years

old) and more likely to have an earner

in the household than their contemporaries without children. It seems that

having a child to raise may affect the

decision to retire or to obtain some

employment to supplement retirement

income. While almost two-thirds of

older households without children

have a retired reference person, only

about 35 percent of older households

with children are retirees. However, an

additional 11 percent of the latter have

reference persons who are not working for reasons other than retirement,

including unemployment, disability,

school attendance, or caring for the

home and/or family.

While the average income of older

caregivers may more closely resemble

that of the younger parents group, educational attainment appears to be more

generational. The distribution of households among educational levels are almost identical between the two older

groups, with the most prevalent category being high school graduate.

Younger parents, on the other hand,

are more likely to have reference persons who are college graduates (36

percent of the sample) than any other

educational designation.

As shown in table 1, the sample contains different types of families. For

older households without children,

there are only two possible family

types: 46 percent of these families are

married couples, and 54 percent are

single persons. Almost half of the older

caregivers fall into the “other husband

and wife” category, which includes

those raising grandchildren or some

other young relative, such as a niece

or nephew. When comparing twoparent households, those with

younger parents also are more likely to

have younger children. (Approximately

12 percent have only children under the

age of six, compared to just 1.5 percent

of older households with children.) For

both age groups, the majority of twoparent households have at least one

child, the oldest being between the ages

of 6 and 17 years. There are a greater

percentage of single parents in the

younger group (21 percent) than in the

older group (roughly 5 percent).

In terms of housing tenure, table 1

shows that more than 75 percent of

each of the groups studied are homeowners. However, while approximately

two-thirds of younger parents own a

home with a mortgage, 60 percent of

older households without children and

46 percent of older households with

children own homes with no mortgage.

Other demographic comparisons

also reveal differences among the three

groups of study. For example, the comparisons by race and origin of the reference person reveal that older caregivers are more likely to be Black and

are more likely to be of Hispanic origin

than either the younger parent group

or the older without children group.

Finally, while younger parent households and older households without

children are similarly distributed across

the United States by region, a greater

percentage of older caregivers live in

the South and West.

Analysis of expenditure shares

Not only is total annual spending different, and actually higher, for older

households with children than either

of the comparison groups, but the allocation of those dollars among selected

item categories is also different. (See

5

 See David S. Johnson and Mark Lino,

“Teenagers: employment and contributions

to family spending,” Monthly Labor Review,

September 2000, p. 15.

6

 See Geoffrey Paulin, “Consumer expenditures on travel, 1980-87,” Monthly Labor

Review, June 1990, p.60. See also Geoffrey

Paulin, “The changing food-at-home budget:

1980 and 1992 compared,” Monthly Labor

Review, December 1998, p.32.
Consumer Expenditure Survey Anthology, 2005 47

table 2.) For example, older caregivers

devote a smaller proportion of total expenditures to food (9 percent) than

younger parents and older households

without children, each of whom spends

roughly 13 percent. Examining the subcomponents of the food category reveals that the shares for both food at

home and food away from home compare similarly to the category as a whole,

although the differences are only significant7

 for the proportions allocated

to food away from home. (The difference in shares for food as a whole is

also significant between older households with children and younger parents.)

Conversely to the food comparison,

spending on housing accounts for a

greater portion of the budget in households with an older reference person

and children (approximately 40 percent,

compared with 33 percent for younger

parents and 29 percent for older households without children). In the CE Survey, the housing category is an aggregation of various subcategories. For

this study, selected housing components are included either because they

are predominant in the total housing

measure, such as shelter and utilities,

or because they are particularly relevant

to the analysis, such as child care and

other domestic services. Shelter, which

includes mortgage interest, property

taxes, rent, and various expenses related to the repair and maintenance of

a dwelling, is similar to the total housing category, with older caregivers having the largest share of the three groups

studied. Utility expenditures, on the

other hand, make up a greater proportion of total spending by older households without children than by those

with children (approximately 8 percent

compared to 6 percent). Allocations of

total spending to babysitting and

daycare are close between younger

parents and older households with children at 1.9 percent and 1.2 percent, respectively. The same is true for other

domestic services, for which older

households without children devote a

greater proportion of total spending

(roughly 6 percent) than younger parents and older caregivers, who each

devote only one-half of 1 percent to

these services. (The category of “domestic services excluding child care”

includes housekeeping services, gardening and lawn care, laundry and drycleaning, and care of the elderly or invalid, among other services.)

Another category of expense in

which the subcategories are particularly relevant to this study is apparel.

As one might expect, the older without children group spends a significantly lesser share for all three subcategories of children’s clothing than their

contemporaries who have children in

the home. Younger parents, however,

spend a significantly greater share for

young girls’ and infants’ clothing than

the older caregivers spend. The expenditure shares for the apparel category

as a whole are not significantly different among the groups, ranging from

about 2.5 percent for older households

without children to 3.7 percent for

younger parents.

Perhaps, the most important spending category analyzed here is health

care. Spending on medical insurance,

services, supplies, and prescription

drugs is a major budget concern for

both older Americans and families raising children. In this study, age appears

to have the stronger positive effect on

health care expenditures. Older households without children, the group with

the highest average age, devote significantly greater shares of their total

spending to each component of health

care than either of the other groups.

In fact, the categorical shares of

younger parents and older caregivers

are almost identical, with the exception

of prescription drugs, for which the

share allocated by younger parents is

significantly less.

Similar to health care, spending on

personal insurance and pensions is

also related to age and employment

status. For example, retirees may no

longer make contributions to Social

Security or other pensions, and life insurance premiums may cease beyond

a certain age. So, it follows that

younger parents, who are much more

likely to be working, allocate a significantly greater proportion of their total

spending to this category (roughly 11

percent, compared with 5 percent by

older households without children and

4 percent for older households with

children).

One major expenditure category for

which older caregivers spend significantly less, as a percentage of total

spending, than either of the comparison groups is cash contributions.

Older caregivers allocate just 3 percent

to this category, which includes contributions to religious organizations,

educational or other institutions, political organizations, and cash support

for college students, while older CUs

without children allocate more than 15

percent of total expenditures. Younger

parents devote just less than 7 percent

of their total budget to contributions.

There are no significant differences

in the allocations of total expenditures

to transportation among the three

types of households. The same is true

for entertainment shares, even when

specifically examining purchases related to children, such as pets, toys,

and playground equipment. Although

older households without children allocate less than one-half of 1 percent

of total expenditures to educational

expenses, compared with 1.8 percent

by older households with children and

1.6 percent by younger parents, the

differences are not statistically significant.

Conclusion

This article has presented sample demographic characteristics and spending patterns for older CUs raising children. The results show that, for the

sample studied, older caregivers are

different both from those in their generation who have no children at home

and from younger parents. The demographic comparison reveals that older

caregivers are younger on average and

earn roughly $30,000 more per year than

7

 The t-test for significance is conducted

in pairs–older with children compared to older

without children and older with children compared to younger parents–such that “significantly different” means “significantly different from the older with children group.”
48 Consumer Expenditure Survey Anthology, 2005

older households without children.

When compared with younger parents,

older caregivers are less likely to have

a college education and more likely to

own their homes without a mortgage.

Older households with children are

more likely to be Black and are more

likely to be of Hispanic origin than either of the comparison groups.

The expenditure share analysis

shows that older caregivers and

younger parents allocate significantly

different percentages of total spending to total food, food away from home,

apparel for girls aged 2 to 15, apparel

for children under 2 years old, prescription drugs, personal insurance and pensions, and cash contributions. Differences in expenditure shares among the

older households with and without

children are significant for food away

from home, babysitting and daycare,

apparel for boys and girls aged 2 to 15,

apparel for children under 2 years old,

total health care, as well as all health

care components, and cash contributions.
Consumer Expenditure Survey Anthology, 2005 49

Table 1. Selected demographic characteristics by type of consumer unit, Consumer Expenditure Survey,

2000-2002

Younger parents

Sample size ............................................................................... 9,869 206 18,056

Averages: ..................................................................................

 Income before taxes ............................................................. $55,790 $53,175 $23,164

 Number of vehicles ............................................................... 2.2 2.1 1.5

 Age of reference person ....................................................... 41.0 67.0 73.0

 Family size ............................................................................. 3.7 3.3 1.5

 Number of children ................................................................ 2.0 1.4 n.a.

 Number of earners ................................................................ 1.6 .8 .4

Percent of sample by: ...............................................................

Family composition: ..................................................................

 Husband and wife only ......................................................... n.a. n.a. 45.8

 Husband and wife with own children: ...................................

 Oldest child < 6 years ........................................................ 12.0 1.5 n.a.

 6 years <= oldest child <= 17 years .................................. 67.0 44.7 n.a.

 Other husband and wife1 ...................................................... n.a. 49.0 n.a.

 Single parent .......................................................................... 21.0 4.9 n.a.

 Single person ......................................................................... n.a. n.a. 54.2

Occupation of reference person:

Retired .................................................................................... .1 35.0 65.7

Salaried ................................................................................... 90.3 43.7 22.5

Self-employed ........................................................................ 6.0 10.2 5.4

Other2 ..................................................................................... 3.6 11.2 6.4

Education of reference person:

Less than high school ........................................................... 8.0 23.8 25.3

High school graduate............................................................. 25.5 33.5 32.5

Some college .......................................................................... 30.5 18.5 22.0

College graduate .................................................................... 36.1 24.3 20.3

Housing tenure:

Owner with mortgage ............................................................ 66.8 35.0 18.6

Owner, no mortgage .............................................................. 10.2 46.1 60.5

Renter ..................................................................................... 22.5 18.9 20.6

Region of residence:

Northeast ................................................................................ 19.4 13.1 18.5

Midwest .................................................................................. 22.6 18.5 25.8

South ....................................................................................... 31.8 38.4 33.6

West ........................................................................................ 26.2 30.1 22.0

Race of reference person:

White ....................................................................................... 83.2 75.2 88.8

Black ....................................................................................... 11.1 18.9 8.1

Other3 ..................................................................................... 5.7 5.8 3.1

Origin of reference person:

Hispanic .................................................................................. 9.8 20.4 3.5

Non-Hispanic ......................................................................... 90.2 79.6 96.5

1 In this sample, “other husband and wife” families are

those with children in the home who are not their own but are

related, such as grandchildren, nieces, or nephews. 2 “Other” occupation includes working without pay, unemployed, and not working due to disability, taking care of

Older without

children

Older with

children

the home/family, going to school, or doing something else.

n.a. Not applicable.

3

 “Other” race includes American Indian, Aleut, Eskimo,

Asian, Pacific Islander, and others.

Characteristic
50 Consumer Expenditure Survey Anthology, 2005

Table 2. Expenditure shares for selected categories by type of consumer unit, Consumer Expenditure Survey,

2000-2002

Total annual expenditures ........................................................ $53,523 $82,211 $29,498

Share (percent) of total expenditures: ....................................

Total food: .................................................................................. *13.3 9.4 13.0

Food at home ......................................................................... 9.8 7.4 9.7

Food away from home .......................................................... *3.4 1.9 *3.3

Housing: .................................................................................... 32.6 39.8 29.3

Shelter .................................................................................... 20.4 21.9 16.9

Utilities .................................................................................... 6.0 5.9 7.7

Domestic services, excluding child care ............................. .5 .5 5.8

Babysitting and daycare ........................................................ 1.9 1.2 *n.a.

Apparel: ..................................................................................... 3.7 3.2 2.5

Men, 16 and over................................................................... .6 .9 .5

Boys, 2 to 15 .......................................................................... .5 .5 *n.a.

Women, 16 and over ............................................................. .8 .8 1.0

Girls, 2 to 15 ........................................................................... *.6 .2 *.1

Children under 2 .................................................................... *.2 n.a. *.1

Transportation ........................................................................... 17.7 13.5 15.3

Health care: ............................................................................... 3.9 4.0 *10.7

Health insurance .................................................................... 2.1 2.0 *5.7

Medical services .................................................................... 1.3 1.2 *2.3

Medical supplies .................................................................... .2 .1 *.4

Prescription drugs ................................................................. *.4 .7 *2.4

Entertainment: ........................................................................... 5.6 4.8 4.0

Pets, toys, and playground equipment ................................. .9 .6 .6

Education .................................................................................. 1.6 1.8 .3

Personal insurance and pensions ........................................... *11.2 3.5 4.8

Cash contributions ................................................................... *6.7 3.2 *15.4

* Significantly different from “older with children” at the 95-percent confidence level

n.a. Not applicable.

Older without

children

Older with

children Characteristic Younger parents
Consumer Expenditure Survey Anthology, 2005 51

Tobacco Expenditures by

Education, Occupation,

and Age

Mark Vendemia is an economist in the

Branch of Information and Analysis, Division of Consumer Expenditure Surveys, Bureau of Labor Statistics.

MARK VENDEMIA Despite the heightened awareness of health problems associated with using tobacco

products, Americans continue to spend

large amounts of money on these items.

Data from the U.S. Bureau of Labor Statistics (BLS or the Bureau) Consumer

Expenditure Survey (CE) show that, in

2002, the average annual expenditure

per consumer unit (CU)1 for tobacco

products and smoking supplies was

$320. This is more than a 25 percent

increase over 1996, when the average

annual expenditure per CU on the same

items was $255. (While the increase in

expenditures was more than 25 percent,

it did not match the 106-percent rise in

the price of tobacco products and

smoking supplies, as measured by the

Bureau’s Consumer Price Index (CPI)

during the same time period.)

Methodology

This article looks at the amount spent

on tobacco products and smoking supplies by CUs, as classified according

to education, occupation, and age of

the reference person. Tobacco products and smoking supplies consist of

the following expenditure items: Cigarettes, other tobacco products, and

smoking accessories. In 2002, spending on cigarettes accounted for 91 percent of expenditures on tobacco and

smoking supplies. Published expenditure estimates for cigarettes and other

tobacco products are derived from data

collected in the CE’s Interview Survey,

while estimates for smoking accessories are derived from the Diary Survey.

Because the expenditures collected

from the Diary Survey represent less

than 1 percent of total tobacco spending, percent reporting (the percent of

CUs who report purchasing an item) is

based on the Interview Survey only.

In the Interview Survey, the mean expenditures are annualized figures,

whereas the percent reportings are average quarterly figures. Published CE

expenditure estimates for a particular

item are averages for all CUs in each

class, including both those who purchase the item and those who do not.

The mean for those who actually purchase the item is higher than the mean

averaged across purchasers and nonpurchasers. For example, in 2002, the

average expenditure for tobacco products per CU was $320, while the average for those who actually purchased

tobacco products was $1,321. This article looks at mean expenditures for all

CUs (purchasers and non-purchasers)

and for CUs who reported purchasing

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 two out

of three major types of expenses—food,

housing, and other expenses.
52 Consumer Expenditure Survey Anthology, 2005

tobacco. This paper focuses on the ratios of spending on tobacco, rather

than the aggregate dollar amounts, because of suspected underreporting for

this type of expenditure. For CUs who

report tobacco expenditures, this analysis assumes consistent reporting (and

underreporting) levels across three

demographic groups—education, occupation, and age.

Spending and share data

This section examines tobacco expenditures, share allocation, and percent

reporting, and compares tobacco expenditures with other selected expenditure items classified by education,

occupation, and age of the CU. Tobacco expenditures are compared with

expenditures for food and alcoholic

beverages to examine consumer spending on necessary items, such as food,

and on elective items, such as alcoholic

beverages. These ratios are based on

average annual tobacco expenditures,

as compared with average annual food

expenditures and with average annual

alcoholic beverage expenditures for all

CUs within each group.

Education. In the CE Survey, education levels are divided into two major

categories—less than college graduate

and college graduate. Less than college graduate is further subdivided into

four groups: Less than high school

graduate, high school graduate, high

school graduate with some college, and

associate degree. College graduate is

subdivided into two groups: bachelor’s

degrees and master’s, professional, or

doctoral degrees. For those CUs whose

reference persons had less than a college degree, the average annual expenditure for tobacco was $375 in 2002.

(See table 1.) In contrast, the average

annual tobacco expenditure for those

CUs whose reference person had a college degree was nearly half at $167.

High school graduates had the highest average annual tobacco expenditure at $441, while those with a master’s,

professional, or doctoral degree had

the lowest at $130—a difference of 239

percent.

When comparing all CUs (both

households that do and do not report

tobacco expenditures), there is less

variation in the average annual tobacco

expenditures among the different education levels when the analysis is restricted to those consumers who actually reported tobacco expenditures.

The average annual tobacco expenditure for those who reported such expenditures was $1,321 per year, with the

highest average for the high school

group at $1,453 and the lowest average

for the bachelor’s degree group at

$1,161— a 25-percent difference.

Less than 1 percent of total average

annual CU expenditures was spent on

tobacco in 2002. The percent share of

the average annual amount spent on

tobacco varies among those households with less than a college degree.

For those households with less than a

high school degree, the tobacco share

of average annual expenditures was 1.4

percent, compared with 1.3 percent for

those with a high school degree, 0.9

percent for high school graduates with

some college, and 0.7 percent for those

households with an associate degree.

The share spent on tobacco was lower

for those households with a college

degree—0.4 percent for those with a

bachelor’s degree and 0.2 percent for

those with a master’s, professional, or

doctoral degree. On average, when

looking at all CUs, including those CUs

not reporting tobacco expenditures, as

CUs achieve higher levels of education,

the share that they spend on tobacco

becomes smaller. However, as noted in

the previous paragraph, the differences

in average annual tobacco expenditures

by CUs who reported tobacco expenditures show less variation among education levels.

Twenty-four percent of CUs reported tobacco expenditures in 2002.

Thirty percent of high school graduates with no college—the highest of

all educational groups—reported making tobacco purchases, followed by the

group with less than a high school degree and those high school graduates

with some college, both at 27 percent,

and the group with an associate degree at 24 percent. On the other hand,

fewer college graduates reported tobacco purchases with 16 percent of

those CUs with a bachelor’s degree and

10 percent of those with a master’s, professional, or doctoral degree reporting

such expenditures.

The amount spent on tobacco compared with the amount spent on food

and alcohol is also interesting. Overall, for all CUs, the amount spent on

tobacco averaged about 6 percent of

that spent on food; but for those with

a high school degree, the amount was

9 percent, whereas it was only 2 percent for those with a master’s, professional, or doctoral degree. The amount

spent on tobacco averaged about 85

percent of that spent on alcoholic beverages for all CUs. For those with less

than a high school degree, the amount

was 191 percent; for those with an associate degree, the amount was 67 percent; and for those with a master’s, professional, or doctoral degree, the

amount was only 22 percent. (See table

2.)

Households with less than a college

degree made up 74 percent (this group’s

population share) of all CUs but accounted for 86 percent of total tobacco

expenditures in 2002, while those with

a college degree made up 26 percent of

all CUs but accounted for only 14 percent of tobacco expenditures.

Occupation. CE Survey data are published for the following occupation

groups: Self-employed workers; CUs

with retired reference persons; wage

and salary earners, which includes five

occupation groups—managers and

professionals; technical, sales, and

clerical workers; service workers; construction workers and mechanics; and

operators, fabricators and laborers—

and all others, including those not reporting. CUs with retired reference persons had the lowest average annual

tobacco expenditures at $163. The two

more traditional blue-collar occupation

groups, construction workers and mechanics, and operators, fabricators,

and laborers, had the highest average

annual tobacco expenditures at $582

and $482, respectively. In comparison,

managers and professionals spent

$251, and self-employed workers spent

$315.
Consumer Expenditure Survey Anthology, 2005 53

There is less variation in average

annual tobacco expenditures among

occupation groups for those CUs who

reported tobacco expenditures, when

compared with the average for all CUs

in the demographic group. The average annual tobacco expenditure for

those who reported tobacco expenditures was $1,321 per year, with the highest average expenditure for the construction workers and mechanics group

at $1,464 and the lowest for the retired

group at $1,189.

The percent share of the average

annual amount spent on tobacco also

varies greatly among occupation

groups. Managers’ and professionals’

share of average annual tobacco expenditures was 0.4 percent, compared

with 0.6 percent for CUs with retired

reference persons, and 0.7 percent for

self-employed workers. The share was

higher for the more traditional bluecollar households, with a share of 1.1

percent for service workers, and 1.4 percent for both construction workers and

mechanics, and operators, fabricators,

and laborers.

Forty percent of the construction

workers and mechanics group—the

highest of all occupational groups—

reported tobacco expenditures in 2002,

followed closely by operators, fabricators, and laborers at 35 percent, and

service workers at 30 percent. In contrast, 19 percent of managers and professionals and 14 percent of the retired

group reported tobacco expenditures.

As noted above, for all CUs, the

amount spent on tobacco averaged 6

percent of that spent on food; but for

construction workers and mechanics,

the amount was 11 percent, compared

with only 4 percent for managers and

professionals, as well as CUs with retired reference persons. The amount

spent on tobacco averaged 137 percent

of that spent on alcoholic beverages

for operators, fabricators, and laborers,

compared with 117 percent for service

workers, 63 percent for self-employed

workers, and only 45 percent for managers and professionals.

In 2002, the households of managers and professionals made up 24 percent of CUs but accounted for 19 percent of total tobacco expenditures. The

households with retired reference persons made up 17 percent of all CUs and

accounted for 9 percent of tobacco expenditures. In contrast, the households of construction workers and mechanics, and operators, fabricators,

and laborers made up 4 percent and 10

percent of all CUs, respectively, but accounted for 8 percent and 15 percent

of tobacco expenditures.

Age. The CE Survey publishes data

for the following age classes: Under

the age of 25, 25 to 34 years, 35 to 44

years, 45 to 54 years, age 65 and over,

65 to 74 years, and age 75 and over.

Households headed by someone 45 to

54 years of age had the highest average annual tobacco expenditure at $415,

whereas the 75-and-over households

had the lowest at $81—a difference of

412 percent. In comparison, the average annual tobacco expenditure for the

under-25 group was $286, compared

with $376 for the 35-to-44 age group,

and $220 for the 65-to-74 age group.

There is less variation in average

annual tobacco expenditures among

age groups for those CUs who reported

tobacco expenditures when compared

to the average annual expenditures for

all CUs (including those who did not

report having tobacco expenditures).

The group with the highest average

expenditure was the 45-to-54 age group

at $1,413, and the group with the lowest was the under-25 group at $1,100—

a 28 percent difference.

For the 75-and-older group, the

share of average annual expenditures

for tobacco was 0.3 percent, compared

with 0.5 percent for the 65-and-older

group, and 0.8 percent for the 25-to-34,

35-to-44, and 55-to-64 age groups. The

share of average annual expenditures

on tobacco was highest for the youngest households, with a share of 1.2 percent for the under-25 group.

As previously mentioned, 24 percent

of all CUs reported tobacco expenditures

in 2002. Twenty-nine percent of the 45-

to-54 group—the highest of all age

groups—reported tobacco expenditures, followed closely by the 35-to-44

age group at 27 percent and by the 25-

to-34, 55-to-64, and under-25 age groups

at 26 percent. In contrast, only 12 percent of the 65-and-over age group, 17

percent of the 65-to-74 age group, and 7

percent of the 75-and-over age group

reported tobacco expenditures.

A comparison of the amount spent

on tobacco with the amount spent on

food shows that, for the under-25

group—the highest of all age groups—

the amount spent on tobacco was 8

percent, compared with only 3 percent

for the 75-and-over group. The amount

spent on tobacco averaged 103 percent

of that spent on alcoholic beverages

for the 35-to-44 group, 89 percent for

the 45-to-54 group, 80 percent for the

25-to-34 group, 73 percent for the under-25 group, 68 percent for the 65-to74 group, and 56 percent for the 75-

and-over group.

In 2002, households headed by

someone aged 65 and over made up 20

percent of CUs but accounted for only

9 percent of total tobacco expenditures,

whereas those households headed by

someone under 25 years old made up

8 percent of all CUs and accounted for

7 percent of tobacco expenditures. In

contrast, the 35- to 44-year-old group

and the 45- to 54-year-old group made

up 22 percent and 20 percent of all CUs,

respectively, but accounted for 26 percent of the tobacco expenditures.

In summary, CE 2002 data shows

that, as CUs achieve higher levels of

education, the amounts and shares that

they spend on tobacco becomes

smaller. Among occupation groups (excluding retired households), households of managers and professionals

and self-employed workers spend a

smaller amount and have the lowest

share of tobacco expenditures. Construction workers and mechanics as

well as operators, fabricators, and laborers spend a larger amount and share

on tobacco. As age increases among

groups, the amounts and the shares

that they spend on tobacco becomes

smaller. While the percent of CUs who

purchase tobacco differs by age, education, and occupation, the average

annual expenditure on tobacco by CUs

who purchase tobacco does not differ

as widely by these factors.
54 Consumer Expenditure Survey Anthology, 2005

Table 1. Average annual expenditures and spending on tobacco for all consumer units, by education level, occupation, and age of reference

person, Consumer Expenditure Survey, 2002

All consumer units ........................................... 112,108 $40,677 $320 24.2 $1,321 0.8 100.0 100.0

Education level:

Total less than college graduate: .................. 82,690 34,631 375 27.9 1,346 1.1 86.3 73.8

Less than high school graduate ................. 17,075 24,930 354 27.2 1,301 1.4 16.8 15.2

High school graduate ................................. 31,961 33,708 441 30.4 1,453 1.3 39.2 28.5

High school graduate with some

 college ..................................................... 23,260 38,654 340 26.6 1,277 .9 22.0 20.8

Associate degree ....................................... 10,395 44,406 289 24.0 1,205 .7 8.3 9.3

Total college graduate: .................................. 29,417 57,384 167 14.1 1,189 .3 13.7 26.2

Bachelor’s degree ...................................... 19,082 53,732 186 16.0 1,161 .4 9.9 17.0

Master’s, professional, or

 doctoral degree ........................................ 10,335 64,118 130 10.4 1,248 .2 3.8 9.2

Occupation:

Total wage and salary: .................................. 74,695 45,296 354 26.6 1,332 .8 73.6 66.6

Managers and professionals ...................... 27,104 57,200 251 19.3 1,303 .4 18.9 24.2

Technical sales and clerical

 workers .................................................... 20,964 42,069 354 26.8 1,321 .8 20.7 18.7

Service workers ......................................... 10,704 34,515 377 30.1 1,254 1.1 11.2 9.5

Construction workers and

 mechanics ............................................... 4,885 40,711 582 39.8 1,464 1.4 7.9 4.4

Operators, fabricators, and laborers .......... 11,038 34,601 482 34.9 1,382 1.4 14.8 9.8

Self-employed workers ................................. 5,106 46,880 315 21.8 1,447 .7 4.5 4.6

Retired .......................................................... 19,204 27,535 163 13.7 1,189 .6 8.7 17.1

All others, including not reporting .................. 13,102 31,099 363 27.3 1,330 1.2 13.2 11.7

Age:

Under 25 ....................................................... 8,737 24,229 286 26.0 1,100 1.2 6.9 7.8

25 to 34 ......................................................... 18,988 40,318 315 25.9 1,218 .8 16.7 16.9

35 to 44 ......................................................... 24,394 48,330 376 27.2 1,384 .8 25.5 21.8

45 to 54 ......................................................... 22,691 48,748 415 29.4 1,413 .9 26.2 20.2

55 to 64 ......................................................... 15,314 44,330 361 26.1 1,384 .8 15.4 13.7

65 and over ................................................... 21,983 28,105 152 12.3 1,237 .5 9.3 19.6

65 to 74 ......................................................... 11,216 32,243 220 17.2 1,278 .7 6.9 10.0

75 and over ................................................... 10,767 23,759 81 7.2 1,128 .3 2.4 9.6

Average

quarterly

percent

reporting

(percent)

Average

annual

tobacco

expenditures

(consumer

units who

reported

tobacco

expenditures)

Average

annual

tobacco

share of

average

annual

expenditures

(percent)

Total

share of

tobacco

expenditure

(percent)

Population

share of

consumer

units

(percent)

Item

Number of

consumer

units

(in

thousands)

Average

annual

expenditures

per

consumer

unit

Average

annual

tobacco

expenditures

per

consumer

unit
Consumer Expenditure Survey Anthology, 2005 55

Table 2. Percent ratio of average annual expenditures on tobacco to average annual expenditures on food and on alcoholic

beverages, by education level, occupation, and age of reference person, Consumer Expenditure Survey, 2002

All consumer units ........................................................................................... 6.0 85.1

Education level:

Total less than college graduate .................................................................... 7.8 123.8

Less than high school graduate ................................................................. 8.6 191.4

High school graduate ................................................................................. 9.4 161.5

High school graduate with some college ................................................... 6.7 91.4

Associate degree ....................................................................................... 5.1 66.7

Total college graduate: .................................................................................. 2.5 29.8

Bachelor’s degree ...................................................................................... 2.8 34.6

Master’s, professional, or doctoral degree ................................................ 1.8 21.5

Occupation:

Total wage and salary: .................................................................................. 6.1 81.2

Managers and professionals ...................................................................... 3.7 45.3

Technical sales and clerical workers .......................................................... 6.4 94.7

Service workers ......................................................................................... 7.4 116.7

Construction workers and mechanics ........................................................ 10.6 136.0

Operators, fabricators, and laborers .......................................................... 9.8 130.6

Self-employed workers ................................................................................. 5.3 63.0

Retired ....................................................................................................... 4.3 78.4

All others, including not reporting .................................................................. 7.5 162.1

Age:

Under 25 ....................................................................................................... 7.9 72.6

25 to 34 ....................................................................................................... 5.8 79.7

35 to 44 ....................................................................................................... 6.0 102.5

45 to 54 ....................................................................................................... 6.7 89.2

55 to 64 ....................................................................................................... 6.5 86.0

65 and over ................................................................................................... 3.9 64.1

65 to 74 ....................................................................................................... 4.9 67.9

75 and over ................................................................................................... 2.5 56.3

Item

Ratio of amount spent on

tobacco to amount spent on

food (percent)

Ratio of amount spent on

tobacco to amount spent on

alcoholic beverages (percent)
56 Consumer Expenditure Survey Anthology, 2005

Spending by Singles

Meaghan Duetsch is an economist in the

Branch of Information and Analysis, Division of Consumer Expenditure Surveys, Bureau of Labor Statistics.

MEAGHAN DUETSCH Do single women spend their

money differently than single

men do? If so, can their spending differences be attributed to differences in characteristics between the

two groups? In addition, have the

spending patterns of single men and

single women changed over the past

decade? These are some of the questions that can be answered with data

from the Consumer Expenditure Survey.

Given that people are choosing to marry

at a later age and that the life expectancy of women continues to be greater

than that of men, more people are single

now than ever before, so the answers

to the preceding questions loom large

in the economic life of a significant proportion of the Nation’s population.

This article examines the expenditures of single-person consumer units,

both men and women. A single-person

consumer unit may differ slightly from

a single-person, or one-person, household. Financial independence is a criterion used to determine consumer unit

status. A one-person household is a

single-person consumer unit; but if two

people are living together and are financially independent of one another,

as in a roommate situation, then the two

people are two separate single-person

consumer units. Single parents with

children present are not single-person

consumer units. Using data for 1991–

92 and 2001–02 from the interview and

diary portions of this Consumer Expenditure Survey, this article compares expenditures and demographic

characteristics between and during

those two periods. Two years of data

are used for each period, in order to

obtain a sufficient sample for examining expenditures by age and gender.

Only single men and single women are

compared, as opposed to all men and

all women, due to the way data are collected. The Consumer Expenditure Survey collects data on expenditures for

the consumer unit as a whole, with no

distinction as to who made the expenditures. Therefore, in a consumer unit

of more than one person, it cannot be

determined who made the expenditures,

whereas that is not the case in a singleperson consumer unit. Expenditures are

examined to determine whether they

changed for each gender over the period from 1991–92 through 2001–02 and

also to determine whether the expenditure relationship between genders

changed during that time. Finally, expenditures are examined for a specific

age group, to analyze the role of age in

expenditure decisions.

Characteristics

The average age of single women was

about 13 years older than the average

age for single men for the 1991–92 period (56.6 years and 43 years, respectively) and about 11 years older for the
Consumer Expenditure Survey Anthology, 2005 57

2001–02 period (56.3 years and 45.3

years, respectively). (See table 1.) Since

men and women’s birthrates are approximately equal and women have a

longer life expectancy, there are more

older women than older men. This difference could also explain the higher

homeownership rates for single women,

48 percent in 1991–92, compared with

36 percent for single men. Both groups

had increased homeownership rates in

2001–02, with women at 56 percent and

men at 45 percent. Across the two periods, more female homeowners were

without a mortgage than with, a statistic again most likely attributable to the

longevity of women, which results in

many older widows. Male homeowners

were fairly evenly split between those

with a mortgage and those without, and

this ratio stayed constant over the two

periods, despite an increase in men’s

homeownership. Both groups experienced an increase in the percentage

with a college education: in 1991–92,

46 percent of single women and 54 percent of single men had a college education—figures that increased to 54

percent for single women and 61 percent for single men in 2001–02.

Single men had higher average incomes than did single women for both

1991–92 and 2001–02, and the difference increased over the period. Men’s

income grew from $20,615 to $31,688,

(an increase of 54 percent), while

women’s rose from $16,432 to $22,930

(an increase of 40 percent). Although

single men still owned more vehicles

than did single women, the men’s rate

of ownership remained constant. On

average, men had 1.3 vehicles in both

periods, while women had 0.8 vehicles

in 1991–92 and 0.9 in 2001–02.

Expenditures

Single men and single women allocate

their expenditures differently. Expenditure patterns were examined by looking at shares of total expenditures, because nominal dollar amounts of the

expenditures, as well as the nominal

amount of average annual expenditures,

change over time. The difference in

shares held for both periods. Single

men spent a larger share of annual expenditures on food than did single

women (13.5 percent as opposed to 12.6

percent in 1991–92, and 12.5 percent

compared with 11.6 percent in 2001–

02). The genders also allocated their

spending differently between food at

home and food away from home, with

men apportioning a larger share of their

food dollar to food away from home

and women a larger share to food at

home. This distinction may be explained by the fact that single women

as a group are older than single men

and, therefore, take more meals at home.

Also, traditionally, women cook more

than men. In addition, only about half

of all single women are earners. (See

table 1.) This fact may contribute to

women allocating a larger share of expenditures to food at home, because

food at home is usually less expensive.

Single women spent a larger share of

their expenditures on housing than did

single men (38 percent and 33 percent,

respectively). The reason could be the

higher homeownership rate for single

women, or it may be that single women

had lower incomes and, thus, spent a

larger proportion on necessities. Single

women allocated a larger share to apparel and services, while single men

allocated a larger share to transportation. This larger share that men allocated to transportation is attributed to

the higher average number of vehicles

owned by men, together with the associated costs, such as gasoline, maintenance, and insurance. Single women allocated a larger share to health care,

compared with single men, while single

men spent a larger share of annual expenditures on entertainment than did

single women. Both groups spent

about the same share on cash contributions.

There were several similarities in the

trends of expenditure shares for men

and women between 1991–92 and

2001–02. Over the 10-year interval, each

group decreased its share spent on

food, including food at home and food

away from home. The shares allocated

for housing, shelter, and utilities remained relatively constant. Both

groups spent a smaller share on apparel

in 2001–02 than in 1991–92. By contrast, both groups allocated a larger

share to transportation in 2001–02 than

in 1991–92. The expenditure share

spent on health care rose slightly for

both men and women, while the shares

spent on entertainment and cash contributions remained relatively unchanged.

The preceding discussion of single

men and single women encompasses

all singles, ranging from young adults

to those who have reached retirement

age and beyond. Many differences in

the spending patterns described can

be attributed to the average difference

in age between single men and single

women. The analysis that follows compares income levels and spending patterns between men and women in a

specific age group to see if the spending differences between the genders

remain for men and women of a similar

age. The 25- to 34-year-old age group

is examined because it represents those

often thought of when the word

“singles” is used. The men and women

of this group have similarities and differences. In 1991–92, single women and

single men had similar average incomes

($24,721 and $24,719, respectively) and

similar average annual expenditures

($21,312 and $21,858, respectively).

However, in that same period, the

single men allocated a larger share to

food (13.4 percent compared with 11.8

percent), but both the men and the

women allocated about the same share

to food at home (5.6 percent and 5.2

percent, respectively). (See table 2.)

Single men allocated a larger share to

food away from home (7.7 percent as

opposed to 6.6 percent). Single women

in this group allocated a slightly larger

share to housing overall (36.4 percent

compared with 34.2 percent) and also

allocated a slightly larger share to shelter (25.4 percent versus 23.8 percent).

By contrast, and unlike the situation

for all age groups taken together, single

women aged 25 to 34 years had a lower

homeownership rate (17 percent) than

did single men (24 percent). Women and

men in the group allocated about the

same share to utilities (5.6 percent and

5.4 percent, respectively), even though

the women were a higher percentage
58 Consumer Expenditure Survey Anthology, 2005

Summary

Single women overall are older than

single men and have higher rates of

homeownership. Single men have a

larger number of vehicles. However,

both groups had an increase in the rate

of homeownership from 1991–92 to

2001–02. Both groups also had an increase in the number of college educated among them from the first period

to the second. Both single men and

single women spent less of their total

expenditures in 2001–02 on food and

apparel and services, although men

spent more on food and women more

on apparel and services. As incomes

increase, people tend to spend less on

necessities, such as food. Also, the

decrease in the costs of apparel and

services relative to other goods,

coupled with increasing incomes,

across the two periods, has enabled

consumers to allocate less of their total expenditures to apparel and services. Single men and single women

aged 25 to 34 years exhibited spending patterns more similar to each other

than did the overall groups of single men

and single women. The 25- to 34-yearold men and women had similar rates

of homeownership and similar levels

of education and also spent similarly

on shelter, as well as on entertainment.

However, single men spent more on

transportation and single women more

on apparel and services. Overall, single

men and single women had different

spending patterns that changed little

from 1991–92 to 2001–02.

of renters (83 percent) than were the

men (76 percent). (Because utilities are

often included in rent payments, it is

not possible to capture the true expenditure for utilities by renters.) Single

women aged 25 to 34 years allocated a

larger share to apparel and services (7.6

percent) than did single men in the same

age group (4.5 percent). In the 1991–92

period, the 25- to 34-year-old men spent

a larger share on transportation (17.9

percent) than did the 25- to 34-year-old

women (15.7 percent). Men had an average of 1.4 vehicles; women an average of 0.9 vehicles. Also in 1991–92,

single women allocated a larger share

to health care (3.1 percent) than did

single men (2.1 percent). However,

single men spent a larger share (2.5

percent) on cash contributions than did

single women (0.9 percent).

The picture for singles 25 to 34

years old changed some by 2001–02.

In that period, single men had average

incomes of $38,936 and average annual

expenditures of $29,736, while single

women had lower incomes ($31,432)

and lower average annual expenditures

($27,110). Also in 2001–02, 90 percent of

single women were earners, compared

with 100 percent of single men. The

homeownership rate increased over

the1991–92 figures for both men and

women, to 33 percent and 30 percent,

respectively. Also, more women in this

age group had a college education (80

percent) than did men (75 percent), although the differences between the

groups were narrower than in 1991–92

(77 percent of women and 70 percent of

men).

Although there were some differences from the 1991–92 period, in 2001–

02 single men still allocated a larger

share to food (12.9 percent) than did

single women (11.8 percent), as well as

a larger share to food away from home

(8.8 percent compared with 6.0 percent).

Single women still allocated a larger

share to housing overall (37.7 percent

as opposed to 33.7 percent), even

though a larger percentage of 25- to

34-year-old single men were homeowners. In addition, single women allocated a larger share to shelter (25.9

percent) than did single men (23.8 percent). In 2001–02, the share allocated

to apparel and services by all singles

25 to 34 years decreased from the 1991–

92 figure; however, the share spent by

single women decreased more, to 5.7

percent, compared with single men’s

share of 4.1 percent. As in the 1991–92

period, 25- to 34-year-old single men

spent a larger share on transportation

(20.4 percent) than did single women

(17.7 percent) in 2001–02. Single men

had slightly fewer vehicles, 1.2, compared with 1.4 vehicles in 1991–92;

single women had 1.0 and 0.9 in the

respective periods. Single men continued to allocate a larger share—more

than twice as much—to cash contributions (2.9 percent) than did single

women (1.4 percent), possibly due to

child support payments that single men

make, as they may be fathers of young

children who live elsewhere.
Consumer Expenditure Survey Anthology, 2005 59

Table 1. Characteristics, average annual expenditures, and expenditure shares, all single women and men, Consumer

Expenditure Survey, 1991–92 and 2001–02

Number of consumer

 units (thousands) ...................... 15,583 18,316 12,531 14,603

Average age ................................. 56.6 56.3 43 45.3

Income before taxes ................... $16,432 $22,936 $20,615 $31,688

Number of earners ...................... .5 .5 .8 .7

Number of vehicles ..................... .8 .9 1.3 1.3

Percent distribution:

Housing tenure:

Homeowner ............................ 48 56 36 45

with mortgage .................... 15 21 18 22

without mortgage .............. 32 35 19 23

Renter ..................................... 52 44 64 55

Highest level of education:

Elementary school ................. 14 8 10 7

High school ............................. 39 39 35 32

College .................................... 46 54 54 61

Average annual expenditures ..... $16,440 100.0 $22,209 100.0 $19,118 100.0 $25,904 100.0

Food ........................................ 2,074 12.6 2,583 11.6 2,582 13.5 3,230 12.5

Food at home .................... 1,309 8.0 1,598 7.2 1,210 6.3 1,482 5.7

Food away from home ..... 765 4.7 985 4.4 1,372 7.2 1,749 6.8

Housing ................................... 6,337 38.5 8,434 38.0 6,208 32.5 8,576 33.1

Shelter ............................... 3,766 22.9 5,111 23.0 4,139 21.6 5,671 21.9

Utilities ............................... 1,356 8.2 1,844 8.3 1,133 5.9 1,645 6.4

Household operations,

 housekeeping supplies,

 household furnishings

 and equipment ................ 1,214 7.4 1,478 6.7 936 4.9 1,260 4.9

Apparel and services ................ 1,030 6.3 1,030 4.6 852 4.5 725 2.8

Transportation ........................... 2,081 12.7 3,223 14.5 3,217 16.8 4,863 18.8

Health care ................................ 1,238 7.5 1,772 8.0 770 4.0 1,118 4.3

Entertainment ............................ 649 3.9 986 4.4 1,040 5.4 1,345 5.2

Cash contributions .................... 700 4.3 915 4.1 853 4.5 1,175 4.5

Other expenditures ................... 2,331 14.2 3,266 14.7 3,596 18.8 4,872 18.8

Single Women Single Men

Item

1991–92 Expenditure

share

Expenditure

share

Expenditure

share

Expenditure

share 2001–02 1991–92 2001–02
60 Consumer Expenditure Survey Anthology, 2005

Table 2. Characteristics, average annual expenditures, and expenditure shares, single women and men aged 25–34 years,

Consumer Expenditure Survey, 1991–92 and 2001–02

Number of consumer

 units (thousands) ....................... 1,917 1,674 3,076 2,612

Average age.................................. 29.1 29.4 29.5 29.4

Income before taxes .................... $24,721 $31,432 $24,719 $38,936

Number of earners ....................... 1.0 .9 1.0 1.0

Number of vehicles ...................... .9 1 1.4 1.2

Percent distribution:

Housing tenure:

Homeowner ................................ 17 30 24 33

with mortgage .......................... 15 23 21 25

without mortgage ..................... 2 7 3 8

Renter ......................................... 83 70 76 67

Highest level of education:

Elementary school ..................... 1 1 2 1

High school................................. 22 19 28 24

College ........................................ 77 80 70 75

Average annual expenditures ...... $21,312 100.0 $27,110 100.0 $21,858 100.0 $29,736 100.0

Food ............................................ 2,507 11.8 3,202 11.8 2,926 13.4 3,831 12.9

Food at home .......................... 1,107 5.2 1,562 5.8 1,233 5.6 1,459 4.9

Food away from home ............ 1,400 6.6 1,640 6.0 1,693 7.7 2,372 8.0

Housing ...................................... 7,762 36.4 10,218 37.7 7,477 34.2 10,021 33.7

Shelter...................................... 5,412 25.4 7,029 25.9 5,210 23.8 7,078 23.8

Utilities ...................................... 1,199 5.6 1,803 6.7 1,186 5.4 1,727 5.8

Household operations,

 housekeeping supplies,

 household furnishings

 and equipment ....................... 1,151 5.4 1,385 5.1 1,081 4.9 1,216 4.1

Apparel and services ................. 1,613 7.6 1,536 5.7 985 4.5 1,206 4.1

Transportation ............................ 3,338 15.7 4,797 17.7 3,905 17.9 6,061 20.4

Health care ................................. 655 3.1 875 3.2 451 2.1 604 2.0

Entertainment ............................. 1,026 4.8 1,221 4.5 1,168 5.3 1,667 5.6

Cash contributions ..................... 182 .9 375 1.4 549 2.5 875 2.9

Other expenditures .................... 4,229 19.8 4,886 18.0 4,397 20.1 5,471 18.4

Single Women, 25–34 Single Men, 25–34

Item

1991–92 Expenditure

share

Expenditure

share

Expenditure

share

Expenditure

share 2001–02 1991–92 2001–02
Consumer Expenditure Survey Anthology, 2005 61

Trends in Airfare

Expenditures

George Janini is an economist in the Branch

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

Statistics.

GEORGE JANINI According to published reports

by the Air Transport Association,1

 the airline travel industry is looking to rebound from the September 11, 2001, (9/11) terrorist attacks.

As reported, Americans were traveling

in record numbers before 9/11 but decreased their traveling considerably

after 9/11. In addition to customers’

wariness regarding flying just following 9/11, a sluggish economy in late

2001 and 2002 contributed to this decrease. This article examines trends in

spending on travel in the years prior to

and just after 9/11, using data from the

U.S. Bureau of Labor Statistics Consumer Expenditure Interview Survey.

The focus is specifically on airfare expenditures, which are compared across

age groups and regions of residence.

Age was selected because of the different lifestyles among the various age

groups, as well as the income differences among them. Region was selected, to see if there was a larger effect

in those regions that were the primary

focus of the attacks.

Methodology

Travel expenditures in the Consumer

Expenditure Survey (CE) are broken

down into five main groups: transportation, food, lodging, entertainment,

and purchase of gifts. Transportation

expenditures include all costs traveling to and from the destination, as well

as transportation costs incurred while

on the trip. This study focused on

spending on airfares. Data are reported

as aggregate and average expenditures

per consumer unit2 for each of the

spending groups. Average expenditures per consumer unit are used in

comparing regions, due to varying

population counts among them. Quarterly data from the Consumer Expenditure Interview Survey are used for the

period 1998 through 2002. Aggregate

amounts were estimated with weights

derived from the survey. Excluded are

all business-related expenditures for

which the consumer unit was reimbursed.

Trends in airfare expenditures

All consumer units

Consumer Expenditure data show that

spending on airfare is cyclical, with the

highest expenditures posted in the

spring and summer months (the second and third quarters). The third quarter of 2001 showed a peak in the data

for the 5-year period.3 (See chart 1 and

table 1.) Aggregate airfare expenditures

1

 See Keith L. Alexander, “Flights Filling

Up, Airlines and Hotels Hiking Prices.” The

Washington Post, May 23, 2004, p. F.01.

2

 See the glossary in the appendix for the

definition of a consumer unit. 3

 This figure could have been even higher

if not for the fact that the events of 9/11

took place in the third quarter and the subsequent closures of airports and restrictions

immediately crippled the industry.
62 Consumer Expenditure Survey Anthology, 2005

reached almost $9 billion that summer.

This was followed by a downturn in

which the lowest aggregate expenditure of the period, $5 billion, was reported in the first quarter of 2002. Although the first quarter is typically the

slowest quarter for any given year, the

average expenditure for the first quarter of the previous years (1998–2001)

was $6 billion. The percentage of consumer units who reported taking a trip

by airplane also declined. From 1998

through 2001, an average of 32 percent

of travelers got to their destination by

flying. By 2002, that number had

slipped to 28 percent. The latter part of

2002 saw a rebound, with $8 billion

spent by consumers in the summer of

2002 and the percentage of travelers

going by plane edging back up to 32

percent.

Age Groups4

Under 25. The events of 9/11 appear

to have had a large effect on airfare expenditures for the under-age-25 group.

The years 1998 through 2001 saw a

steady cyclical pattern of spending,

with the exception being a robust 1998

summer. (See chart 2 and table 1.) Another peak in the summer of 2001

showed expenditures matching the

1998 summer figure of $420 million.

This peak was followed by a decrease

in the fourth quarter of 2001, just after

9/11, in which expenditures fell to the

5-year low of $150 million, marking a

larger decrease in expenditures than

could be explained by the typical cyclical dropoff in the fourth quarter. To put

the decline in perspective, spending on

airfare for the fourth quarters from 1998

through 2000 by those under 25 averaged $215 million, while in the fourth

quarter of 2001, it was $150 million.

Age 25 to 44. Compared with the 25-

and-under group, 25- to 44-year-olds

reported airfare expenditures that had

less volatile swings. The summers of

1998 and 2000 had the biggest peaks,

with the former topping out at $3.2 billion and the latter reaching $3.4 billion.

(See chart 3 and table 1.) Surprisingly,

there was not much of a decrease in

the fourth quarter of 2001, when expenditures dropped just $200 million from

the previous quarter, to 2.6 billion dollars. A bigger drop was felt in the first

quarter of 2002, when expenditures fell

to 2 billion dollars. The age group, consisting of 25- to 44-year-olds, spends

more, on average, and is a larger group,

than the under-age-25 group, so even

a small change between quarters may

have a greater effect on total aggregate

expenditures. For example, the dropoff

in expenditures from the fourth quarter

of 2001 to the first quarter of 2002 was

$600 million, a figure greater than the

highest expenditure reported—$420

million—for any quarter by the lessthan-25 age group.

Age 45 to 64. As with the 25-to-44-year

age group, airfare expenditures for the

45- to 54-year group showed the cyclical pattern common to the data. The

highest expenditures of any quarter

were in the summers of 2001 and 2002,

$3.3 billion for both. (See chart 4 and

table 1.) The fourth quarter of 2001, just

after the events of 9/11, saw an $800

million dropoff in expenditures from the

previous quarter’s figure; the decline

was the biggest from any given quarter to the next.

Age 65 and older. At $2.3 billion, spending on airfares in the summer of 2001

by the age-65-and-older group was the

highest of any quarter for the group

for the 5-year period. (See chart 5 and

table 1.) There was a sharp decline in

the fourth quarter, when expenditures

fell to $780 million. This fall off is of

note because those 65 years and older

posted strong fourth quarters in 1998

and 2000, spending $300 million more

in the fourth quarter than they did in

the previous third quarter, which is typically the quarter in which airfare expenditures are highest. It is possible that

this age group tends to travel more in

the holiday season to be with families,

whereas the other age groups spend

more on summer leisure travel. By the

first quarter of 2002, expenditures by

those age 65 and older were at the lowest level for the 5-year period, 650 million dollars. This figure marked a 1.65

billion dollar decrease in total expenditures from the summer of 2001—the

biggest decrease in total expenditures

among the age groups for the pre- and

post- 9/11 period.

Regions

Northeast. Because the events of 9/11

were centered primarily in the Northeast, it would be reasonable to think

that that region would be most affected

in the aftermath. As was the case for

the country as a whole, the summer of

2001 set a 5-year-period high for the

Northeast region, slightly more than $2

billion spent on airfares. (See table 2

and chart 6.) This quarter also had the

highest average expenditures per consumer unit among any of the regions,

$310. (See table 3.) After 9/11, the fourth

quarter of 2001 saw a 35-percent decline in average expenditures, to $200.

This decline is significant compared

with changes during the other 4 years

in the study, which saw increases in

average expenditures in the fourth

quarter for the Northeast. Spending on

airfare slid even further in the first quarter of 2002, to $174, the second-lowest

average in the 5-year period, apart from

the first quarter of 1998. By the summer

of 2002, average expenditures were a

little higher, at $206, but this figure still

marked a 34-percent decrease from that

of the previous summer. The drop was

the biggest percentagewise among the

regions.

Midwest. The events of 9/11 seemed

to have less of an effect on airline travelers in the Midwest region, which

posted the steadiest set of data in the

5-year period. (See chart 7.) In the Midwest, average annual expenditures per

consumer unit dropped 11 percent from

the summer of 2001 to the summer of

2002—the smallest decrease among the

regions over that period.

South. Like the Midwest, the events of

9/11 seemed to have less of an effect

on airline travelers in the South. It is of

4

 Age classifications are by the age of the

reference person. See the glossary in the

appendix for a definition of reference person.
Consumer Expenditure Survey Anthology, 2005 63

spent a year later, in the third quarter of

2002. The most affected age groups

were the oldest and the youngest, and

the most affected region was the Northeast, followed by the West. This slowdown, which continued into 2002, can

be attributed primarily to the shock of

9/11, but also to a weak economy. Excluding airfare, expenditures involving

other modes of transportation (train,

ship, or car) also went down. Spending

by all consumer units dropped from

roughly $2.8 billion in the third quarter

of 2001 to $1.7 billion in the fourth quarter of 2001. The drop was significant,

as expenditures in the fourth quarter of

2000 were $3.3 billion. By the fourth

quarter of 2002, expenditures had rebounded back up to approximately $3

billion.

note that the summer of 2001 was the

only quarter in the 5-year period to post

an average expenditure per consumer

unit above $200, namely, $214. In the

summer of 2002, average expenditures

fell to $179, a 16-percent drop. (See table

3 and chart 8.)

West. The West was the region second

highest to the Northeast in average

quarterly expenditures per consumer

unit for the entire 5-year period, at $207,

compared with $226 for the Northeast.

(See table 3 and chart 9.) At $162, average quarterly expenditures per consumer unit were at the second-lowest

point of the 5-year period in the fourth

quarter of 2001, just after 9/11, a 34-

percent decrease from the third quarter. Expenditures did not rebound until

the summer of 2002, when average quarterly expenditures per consumer unit

were back above $200. Average annual

expenditures from the summer of 2001

to the summer of 2002 fell 18 percent,

the second-highest percentage drop

after that of the Northeast region’s.

Conclusion

The data presented here show that

spending on airline fares was at a high

point just prior to the events of 9/11.

Thereafter, a sharp decrease ensued.

Total airfare spending by all consumer

units dropped from $8.9 billion in the

third quarter of 2001 to $6.1 billion in

the fourth quarter, a 31-percent decrease. The 8.9 billion dollars spent in

the third quarter of 2001 was 14 percent higher than the 7.8 billion dollars
64 Consumer Expenditure Survey Anthology, 2005

Table 1. Quarterly airfare expenditures, in billions of dollars, by age of reference person, Consumer Expenditure Interview

Survey, 1998–2002

 1998

Quarter 1 ................................................................ 5.60 0.25 2.30 2.10 0.89

Quarter 2 ................................................................ 6.30 .22 2.20 2.90 1.00

Quarter 3 ................................................................ 8.00 .42 3.20 2.80 1.50

Quarter 4 ................................................................ 7.70 .16 2.50 3.20 1.80

 1999

Quarter 1 ................................................................ 5.90 .19 2.10 2.60 .90

Quarter 2 ................................................................ 5.90 .16 2.00 2.20 1.20

Quarter 3 ................................................................ 7.00 .26 2.70 2.70 1.20

Quarter 4 ................................................................ 5.30 .24 2.00 2.60 1.00

 2000

Quarter 1 ................................................................ 6.30 .19 2.60 2.20 1.20

Quarter 2 ................................................................ 6.60 .26 2.40 2.80 1.10

Quarter 3 ................................................................ 8.20 .26 3.40 3.00 1.40

Quarter 4 ................................................................ 7.60 .22 2.80 2.80 1.70

 2001

Quarter 1 ................................................................ 6.20 .16 2.40 2.60 0.89

Quarter 2 ................................................................ 6.00 .32 2.60 2.00 .97

Quarter 3 ................................................................ 8.90 .42 2.80 3.30 2.30

Quarter 4 ................................................................ 6.10 .15 2.60 2.50 .78

 2002

Quarter 1 ................................................................ 5.00 .16 2.00 2.20 .65

Quarter 2 ................................................................ 5.80 .27 2.30 2.50 .69

Quarter 3 ................................................................ 7.80 .26 2.90 3.30 1.10

Quarter 4 ................................................................ 6.90 .24 2.70 2.90 1.00

All consumer

units

Under 25

years Year and quarter 25–44years

45–64

years

65 years and

older

Table 2. Quarterly airfare expenditures, in billions of dollars, by region of residence, Consumer Expenditure Interview

Survey, 1998–2002

 1998

Quarter 1 ........................................................................ 1.00 1.10 1.30 2.00

Quarter 2 ........................................................................ 1.70 1.40 1.30 1.80

Quarter 3 ........................................................................ 1.60 1.20 2.00 3.10

Quarter 4 ........................................................................ 1.90 1.30 2.00 2.40

 1999

Quarter 1 ........................................................................ 1.20 1.40 1.40 1.70

Quarter 2 ........................................................................ 1.60 1.40 1.30 1.40

Quarter 3 ........................................................................ 1.40 1.20 2.20 2.00

Quarter 4 ........................................................................ 1.10 1.00 1.30 1.80

 2000

Quarter 1 ........................................................................ 1.20 1.80 1.40 1.90

Quarter 2 ........................................................................ 1.80 1.60 1.50 1.60

Quarter 3 ........................................................................ 1.60 1.60 2.30 2.60

Quarter 4 ........................................................................ 1.60 1.90 1.90 2.10

 2001

Quarter 1 ........................................................................ 1.10 1.10 1.40 2.30

Quarter 2 ........................................................................ 1.50 1.40 1.40 1.60

Quarter 3 ........................................................................ 2.10 1.70 2.50 2.50

Quarter 4 ........................................................................ 1.50 1.20 1.60 1.70

 2002

Quarter 1 ........................................................................ .99 1.10 1.40 1.50

Quarter 2 ........................................................................ 1.40 1.40 1.30 1.40

Quarter 3 ........................................................................ 1.50 1.50 2.40 2.10

Quarter 4 ........................................................................ 1.70 1.40 1.70 2.10

Year and quarter Northeast Midwest South West
Consumer Expenditure Survey Anthology, 2005 65

Chart 1. Quarterly airfare expenditures, all consumer units, 1998—2002

1998 1999 2000 2001 2002

$ billions $ billions

0.0

2.0

4.0

6.0

8.0

10.0

0.0

2.0

4.0

6.0

8.0

10.0

NOTE: A trend line has been inserted. 

Consumer units

Trend line

Table 3. Average quarterly airfare expenditures per consumer unit, by region of residence, Consumer Expenditure

Interview Survey, 1998–2002

 1998

Quarter 1 ........................................................................ $157 $139 $115 $214

Quarter 2 ........................................................................ 242 166 121 200

Quarter 3 ........................................................................ 200 114 146 278

Quarter 4 ........................................................................ 232 115 158 223

 1999

Quarter 1 ........................................................................ 218 178 129 180

Quarter 2 ........................................................................ 268 168 127 150

Quarter 3 ........................................................................ 186 119 165 192

Quarter 4 ........................................................................ 200 128 135 227

 2000

Quarter 1 ........................................................................ 204 221 138 218

Quarter 2 ........................................................................ 298 181 163 190

Quarter 3 ........................................................................ 197 157 183 247

Quarter 4 ........................................................................ 238 188 158 213

 2001

Quarter 1 ........................................................................ 226 139 144 264

Quarter 2 ........................................................................ 261 160 152 190

Quarter 3 ........................................................................ 310 173 214 247

Quarter 4 ........................................................................ 200 129 148 162

 2002

Quarter 1 ........................................................................ 174 145 137 167

Quarter 2 ........................................................................ 249 178 127 169

Quarter 3 ........................................................................ 206 154 179 202

Quarter 4 ........................................................................ 247 146 149 207

Year and quarter Northeast Midwest South West
66 Consumer Expenditure Survey Anthology, 2005

Chart 2. Quarterly airfare expenditures, persons under age 25, 1998—2002

1998 1999 2000 2001 2002

$ billions $ billions

0.0

0.1

0.2

0.3

0.4

0.5

0.0

0.1

0.2

0.3

0.4

0.5

NOTE: A trend line has been inserted. 

Persons under age 25

Trend line

Chart 3. Quarterly airfare expenditures, persons aged 25—44 years, 1998—2002

1998 1999 2000 2001 2002

$ billions $ billions

0.0

1.0

2.0

3.0

4.0

0.0

1.0

2.0

3.0

4.0

NOTE: A trend line has been inserted. 

Persons aged 25–44

Trend line
Consumer Expenditure Survey Anthology, 2005 67

Chart 4. Quarterly airfare expenditures, persons aged 45—64 years, 1998—2002

1998 1999 2000 2001 2002

$ billions $ billions

0.0

1.0

2.0

3.0

4.0

0.0

1.0

2.0

3.0

4.0

NOTE: A trend line has been inserted. 

Persons aged 45–64

Trend line

Chart 5. Quarterly airfare expenditures, persons aged 65 years and older, 1998—2002

1998 1999 2000 2001 2002

$ billions $ billions

0.0

1.0

2.0

3.0

0.0

1.0

2.0

3.0

NOTE: A trend line has been inserted. 

Persons aged 65 or older

Trend line
68 Consumer Expenditure Survey Anthology, 2005

Chart 6. Quarterly airfare expenditures, Northeast region, 1998—2002

1998 1999 2000 2001 2002

$ billions $ billions

0.0

1.0

2.0

3.0

0.0

1.0

2.0

3.0

NOTE: A trend line has been inserted. 

Northeast region

Trend line

Chart 7. Quarterly airfare expenditures, Midwest region, 1998—2002

1998 1999 2000 2001 2002

$ billions $ billions

0.0

1.0

2.0

3.0

0.0

1.0

2.0

3.0

NOTE: A trend line has been inserted. 

Midwest region

Trend line
Consumer Expenditure Survey Anthology, 2005 69

Chart 8. Quarterly airfare expenditures, South region, 1998—2002

1998 1999 2000 2001 2002

$ billions $ billions

0.0

1.0

2.0

3.0

0.0

1.0

2.0

3.0

NOTE: A trend line has been inserted. 

South region

Trend line

Chart 9. Quarterly airfare expenditures, West region, 1998—2002

1998 1999 2000 2001 2002

$ billions $ billions

0.0

1.0

2.0

3.0

4.0

0.0

1.0

2.0

3.0

4.0

NOTE: A trend line has been inserted. 

West region

Trend line
70 Consumer Expenditure Survey Anthology, 2005

Appendix A: Description

of the Consumer

Expenditure Survey

The current Consumer Expenditure Survey (CE) program beganin 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. Additionally, the data are required for periodic revisions of the U.S.

Bureau of Labor Statistics (BLS) Consumer Price Index (CPI).

The CE, which is conducted by the

U.S. Census Bureau for the U.S. 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 payment is made

at the time of purchase. Expenditure

amounts include all sales and excise

taxes for 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 survey queries an independent sample of consumer units that is representative of the

U.S. population. In the Diary Survey,

about 7,500 consumer units are sampled

each year. Each consumer unit keeps a

diary for two 1-week periods, yielding

approximately 15,000 diaries a year. In

the Interview Survey, the sample is selected on a rotating panel basis, surveying about 7,500 consumer units

each quarter. Each consumer unit is

interviewed once per quarter, for five

consecutive quarters. Data are collected on an ongoing basis in 105 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

to 70 percent of total household expenditures. Global estimates, that is, expenditures for a 3-month period, are obtained for food and other related items,

accounting for an additional 20 to 25

percent of total expenditures.

The Diary Survey is designed to

capture expenditures on small, frequently purchased items that are normally difficult for respondents to recall.
Consumer Expenditure Survey Anthology, 2005 71

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 information on expenditures that

could not be recalled easily over a period of time, 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, which neither survey component alone is designed to

do. Data on some expenditure items

are collected in only one of the components. For example, the Diary Survey

does not collect data on expenditures

for overnight travel or information on

third-party reimbursements of consumer expenditures, as 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

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.

Population coverage and the definition of components of the CE differ

from those of the CPI. Consumer expenditure data cover the total population, whereas the CPI covers only the

urban population. In addition, home

ownership is treated differently in these

two surveys. 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 owneroccupied 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

expenditure by those consumer units

that actually purchased the item. The

less frequently an item is purchased,

the greater 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, 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 when relating

reported averages to individual circumstances.

In addition, sample surveys are subject to two types of errors: sampling

and nonsampling. Sampling errors occur because the data are collected from

a representative sample rather than 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, or 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. Students living in university-sponsored housing

are also 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 acquired during

the interview period. 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 (SSI),

and Food Stamps; rent or meals or both

as pay; and regular contributions for

support, such as alimony and child

support.

Complete income reporters. In general, a consumer unit that provides values for at least one of the major sources

of its income, such as wages and salaries, self-employment income, and Social Security income. Even complete

income reporters may not provide a full

accounting of all income from all

sources.

Quintiles of income before taxes.

Complete income reporters are ranked

in ascending order of income value and

divided into five equal groups. Incomplete income reporters are not ranked

and are shown separately in the

quintiles of income tables.