BLS Handbook of Methods

Chapter 16.
Consumer Expenditures
and Income (Updated 04/2007)

C

onsumer expenditure surveys are specialized studies
in which the primary emphasis is on collecting data
related to family expenditures for goods and services
used in day-to-day living. Consumer expenditure surveys of
the Bureau of Labor Statistics (BLS, the Bureau) also collect information on the amount and sources of family income,
changes in assets and liabilities, and demographic and economic characteristics of family members.

IN THIS CHAPTER
Background............................................................... 1
The Current Survey................................................... 1
Interview Survey.................................................. 2
Diary Survey........................................................ 3
Integrated survey data.......................................... 3
Data collection and processing............................ 3
Sample Design.......................................................... 4
Selection of households....................................... 4
Cooperation levels................................................ 5
Estimation methodology...................................... 5
Precision of the estimates..................................... 6
Presentation............................................................... 6
Evaluation Research.................................................. 7
Uses and Limitations................................................. 7

Background
The Bureau’s studies of family living conditions rank among
its oldest data-collecting functions. The first nationwide expenditure survey was conducted in 1888-91 to study workers’ spending patterns as elements of production costs. With
special reference to competition in foreign trade, the survey
emphasized the worker’s role as a producer rather than as a
consumer. In response to rapid price changes prior to the turn
of the century, a second survey was administered in 1901.
The resulting data provided the weights for an index of prices
of food purchased by workers, which was used as a deflator for workers’ incomes and expenditures for all kinds of
goods until World War I. A third survey, conducted in 191719, provided weights for computing a cost-of-living index,
now known as the Consumer Price Index (CPI). The Bureau
conducted its next major survey, covering only urban wage
earners and clerical workers, in 1934-36, primarily to revise
the CPI weights.
During the economic depression of the 1930s, the use of
consumer expenditure surveys extended from the study of the
welfare of selected groups to more general economic analysis. Concurrent with its 1934-36 investigation, the Bureau
cooperated with four other Federal agencies in a fifth survey,
the 1935-36 study of consumer purchases, which presented
consumption estimates for both urban and rural segments of
the population. The sixth survey, in 1950, covered only urban consumers; it was an abbreviated version of the 1935-36
study. The seventh survey, the 1960-61 Survey of Consumer Expenditures, once again included both urban and rural
families, and provided the basis for revising the CPI weights
while also supplying material for broader economic, social,
and market analyses.

The next major survey to collect information on expenditures of householders in the United States was conducted
in 1972-73. That survey, while providing continuity with the
content of the Bureau’s previous surveys, departed from the
past in its collection techniques. Unlike earlier surveys, the
U.S. Census Bureau, under contract to BLS, conducted all
sample selection and field work. Another significant change
was the use of two independent surveys to collect the information—a diary survey and an interview panel survey. A third
major change was the switch from an annual recall to a quarterly recall (in the Interview Survey) and daily recordkeeping
of expenditures (in the Diary Survey). Again, the resulting
data were used to revise the CPI weights.

The Current Survey
The need for more timely data than could be supplied by
surveys conducted every 10 to 12 years, intensified by the
rapidly changing economic conditions of the 1970s, led to
the initiation of the current continuing survey in late 1979.
Since then, data have been available annually. The objectives
of the survey remain the same: to provide the basis for revis

ing the weights and associated pricing samples for the CPI
and to meet the need for timely and detailed information on
the spending patterns of different types of families.
Like the 1972-73 survey, the current survey consists of
two separate surveys, each with a different data collection
technique and sample. In the Interview Survey, each family
in the sample is interviewed every 3 months over five calendar quarters. The sample for each quarter is divided into
three panels, with consumer units being interviewed every 3
months in the same panel of every quarter. The Diary (or recordkeeping) Survey is completed at home by the respondent
family for two consecutive 1-week periods.
The sample housing unit is notified in advance by a letter
informing the occupants about the purpose of the survey and
the upcoming visit by the interviewer. Both the Interview and
the Diary Survey are conducted primarily by personal visits
with some telephone usage. The interviewer uses a structured
questionnaire to collect both the demographic and expenditure data in the Interview Survey. The demographic data in
the Diary Survey are collected by the interviewer, whereas
the expenditure data are entered on the diary form by the respondent. If, after attempts to contact the household, no adult
is available, both surveys accept responses from any eligible
household member who is at least 16 years old.
The unit for which expenditure reports are collected is the
set of eligible individuals constituting a consumer unit, which
is defined as (1) all members of a particular housing unit who
are related by blood, marriage, adoption, or some other legal
arrangement, such as foster children; (2) a person living alone
or sharing a household with others, or living as a roomer in a
private home, lodging house, or in permanent living quarters
in a hotel or motel, but who is financially independent; or
(3) two or more unrelated persons living together who pool
their income to make joint expenditure decisions. Students
living in university-sponsored housing are also included in
the sample as separate consumer units.
Survey participants report dollar amounts for goods and
services purchased during the reporting period whether payment was or was not made at the time of purchase. The expenditure amounts include all sales and excise taxes for all
items purchased by the consumer unit for itself or for others.
Excluded from both surveys are all business-related expenditures and expenditures for which the family is reimbursed.
The Interview Survey collects detailed data on an estimated 60 to 70 percent of total family expenditures. In addition,
global estimates—that is, estimated average expenditures 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. On the average, it takes approximately 65 minutes to complete the interview.
In the Diary Survey, detailed data are collected on all expenditures made by consumer units during their participation
in the survey. It is estimated that it takes approximately 25
minutes over three visits for the interviewer to collect the
demographic data and to instruct the respondent on how to
keep the diary. It is also estimated that it takes the respondent
about 12 minutes each day to complete the diary.

Quality control is provided by a reinterview program,
which constitutes a means of evaluating the performance of
the individual interviewer to determine how well the procedures are being carried out in the field. The reinterview is
conducted by a member of the supervisory staff. A subsample
of approximately 8 percent of households in the Interview
Survey and 11 percent in the Diary Survey is reinterviewed
on an ongoing basis.
All data collected in both surveys are subject to Census
Bureau and BLS confidentiality requirements that prevent the
disclosure of the respondents’ identities. All employees have
taken an oath to that effect.
Interview Survey
The Interview Survey is designed to collect data on the types
of expenditures respondents can be expected to recall for a
period of 3 months or longer. In general, expenditures reported in the Interview Survey are either relatively large, such as
for property, automobiles, or major appliances, or occur on a
fairly regular basis, such as for rent, utility bills, or insurance
premiums.
Each occupied sample unit is interviewed once per quarter for five consecutive quarters. After the fifth interview, the
sample unit is dropped from the survey and replaced by a
new sample unit. For the survey as a whole, 20 percent of the
sample is replaced each quarter. New families are introduced
into the sample on a regular basis as other families complete
their participation. Data collected in each quarter are considered independently, so that estimates are not dependent upon
a family participating in the survey for a full five quarters.
For the initial interview, information is collected on demographic and family characteristics and on the inventory of
major durable goods of each consumer unit. Expenditure information is also collected in this interview, using a 1-month
recall, but is used, along with the inventory information,
solely for bounding purposes, that is, to classify the unit for
analysis and to prevent duplicate reporting of expenditures in
subsequent interviews.
The second through fifth interviews use uniform questionnaires to collect expenditure information in each quarter.
Data collected in these questionnaires, which are arranged by
major expenditure component (for example, housing, transportation, healthcare, and education), form the basis of the
expenditure estimates derived from the Interview Survey.
Wage, salary, and other information on the employment of
each member of a consumer unit is also collected or updated
during each of these interviews. The expenditure data are
collected via two major types of questions. The first set of
questions asks the consumer unit member for the month of
purchase directly for each reported expenditure. The second
asks for a quarterly amount of expenditures. The use of these
two types of questions varies, depending on the types of expenditures collected. Approximately 65 percent of the data
are collected using the direct monthly method, whereas about
35 percent are collected with the quarterly recall approach.
In the fifth and final interview, an annual supplement is
used to obtain a financial profile of the consumer unit. This


profile consists of information on the income of the consumer unit as a whole, including unemployment compensation;
income from royalties, dividends, and estates; alimony and
child support; and so forth. A 12-month recall period is used
to collect income- and asset-type data.

global estimates such as those for food and alcoholic beverages, average about 95 percent of the total estimated spending, based on integrated Diary and Interview data. 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 the overlap, the integration of the data presents the problem of determining the appropriate survey component from
which to select the expenditure items. When data are available from both survey sources, the more reliable of the two is
selected as determined by statistical methods. The selection
of the survey source is evaluated periodically.

Diary Survey
The primary objective of the Diary Survey is to obtain expenditure data on small, frequently purchased items, which
are normally difficult to recall. These items include food and
beverage expenditures, at home and in eating places; housekeeping supplies and services; nonprescription drugs; and
personal care products and services. The Diary Survey is not
limited to these types of expenditures, but, rather, includes
all expenses that the consumer unit incurs during the survey
week. Expenses incurred by family members while away
from home overnight and for credit and installment plan payments are excluded.
Two separate questionnaires are used to collect Diary data:
a Household Characteristics Questionnaire and a Record of
Daily Expenses. In the Household Characteristics Questionnaire, the interviewer records 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 the Bureau to classify the consumer unit for
publication of statistical tables and for economic analysis.
Data on household characteristics also provide the link in the
integration of Diary expenditure data with Interview expenditure data that permits the publication of a full profile of
consumer expenditures by demographic characteristics.
The daily expense record is designed as a self-reporting,
product-oriented diary on which respondents record a detailed description of all expenses for two consecutive 1-week
periods. Data collected each week are considered independently. The diary is divided by day of purchase and by four
classifications of goods and services—food away from home,
food at home, clothing, and all other goods and services—a
breakdown designed to aid the respondent in recording the
entire consumer unit’s daily purchases. The items reported
are subsequently coded by the Census Bureau so that BLS
can aggregate individual purchases for representation in the
CPI and for presentation in statistical tables.

Data collection and processing
Due to differences in format and design, the Interview Survey
and the Diary Survey are collected and processed separately.
The U.S. Census Bureau, under contract with BLS, carries
out data collection for both. In addition to its collection duties, the Census Bureau does field editing and coding, checks
consistency, ensures quality control, and transmits the data to
BLS. In preparing the data for analysis and publication, BLS
performs additional review and editing procedures.
Quarterly Interview Survey. Beginning April 2003, Census
Field Representatives (FR) started collecting the Interview
data using a Computer Assisted Personal Interview (CAPI)
instrument. This was a major improvement from the paper
and pencil data collection that had been in place since 1980.
The CAPI instrument enforces question skip patterns, allows for data confirmation of high expenditure values, and
reduces processing time. The FR performs some coding of
expenses—by selecting from a predetermined list—for vehicle make and model, trip destination, and job types for alterations, maintenance and repair.
Data are electronically transferred from the FR’s laptop
at completion of the interview to the Census Master Control
System. The Census Bureau’s Demographics Surveys Division then reformats the data into SAS® datasets and does
some special processing for output to BLS (such as converting missing values to special characters and merging data
records into the required BLS output structure.) Some data,
like vehicle and mortgage records, are copied into an input
file that is loaded on the laptops for subsequent interviews the
next quarter. This way, a few fields are updated each quarter,
rather than recollecting the entire data record.
At BLS, a series of automated edits are applied to monthly
data. These edits check for inconsistencies, identify missing
expenditure amounts for later imputation, impute missing demographic variables, calculate weights, and adjust data to include sales tax and exclude business expenses or reimbursed
expenditures.
Monthly data files are then combined into quarterly databases, and a more extensive data review is carried out. This
step includes a review of the following: Counts and means
by region, family relationship coding inconsistencies, and selected extreme values for expenditure and income categories.
Other adjustments convert mortgage and vehicle payments

Integrated survey data
The 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. Some expenditure items are collected only by
either the Diary or Interview Survey. For example, the Diary
collects data on detailed food expenditures and items such as
postage and nonprescription drugs, which are not collected in
the Interview. The Interview collects data on expenditures for
overnight travel and information on reimbursements, such as
for medical-care costs or automobile repairs, which are not
collected in the Diary. Data on average annual expenditures
that come exclusively from the Interview Survey, including


into principal and interest (using associated data on the interest rate and term of the loan). In addition, BLS verifies the
various data transformations it performs. Cases of questionable data values or relationships are investigated, and errors
are corrected prior to release of the data for public use.
Three major types of data adjustment routines—imputation, allocation, and time adjustment—improve estimates
derived from the Interview Survey. Data imputation routines
account for missing or invalid entries and affect all fields in
the database, except assets. Missing or invalid attributes or
expenditures are imputed. Allocation routines are applied
when respondents provide insufficient detail to meet tabulation requirements. For example, combined expenditures for
the fuels and utilities group are allocated among the components of that group, such as gas and electricity. Time adjustment routines are used to classify expenditures by month,
prior to aggregation of the data to calendar-year expenditures.
Tabulations are made before and after the data adjustment
routines, to analyze the results.
The Survey implemented multiple imputations of income
data starting with the publication of the 2004 data. Prior
to that, only income data collected from complete income
reporters were published. However, even complete income
reporters did not provide information on all sources of income for which they reported receipt. With the collection of
bracketed income data starting in 2001 this problem was reduced, but not eliminated. A limitation is that bracketed data
only provide a range in which income falls, rather than a
precise value for that income. In contrast, imputation allows
income values to be estimated when they are not reported.
In multiple imputations, several estimates are made for the
same consumer unit, and the average of these estimates is
published.

each household member, and industry and occupation codes
are entered for each working member. After an initial clerical screening, data are key-entered into electronic formats
and a computer file of the database containing these data is
produced and transmitted monthly to BLS, along with image
files of questionnaires.
Data are then processed by computer to calculate population weights based on BLS specifications, impute demographic characteristics for missing or inconsistent demographic
data, impute values for weeks worked when nonresponse is
encountered, and apply appropriate sales taxes to the expenditure items.
Using three monthly diary data files, BLS creates a quarterly data base and screens it for invalid coding and inconsistent relationships, as well as for extreme values recorded
or keyed erroneously. BLS then corrects any coding and extreme-value errors found.
Two types of data adjustment routines—allocation and
imputation—improve the Diary Survey estimates. Allocation
routines transform reports of nonspecific items into specific
ones. For example, when respondents report expenditures for
meat rather than beef or pork, allocations are made, using
proportions derived from item-specific reports in other completed diaries. BLS imputes missing attributes, such as age or
sex or package type, needed for mapping Diary expenditures.
Income data from the Diary Survey are processed in the same
way as in the Interview Survey.

Sample Design
Selection of households
The Consumer Expenditure Survey is a nationwide household survey designed to represent the total U.S. civilian noninstitutional population. The selection of households begins
with the definition and selection of primary sampling units
(PSUs). PSUs are counties (or parts thereof), groups of counties, or independent cities grouped together into geographic
entities called “core-based statistical areas” (CBSAs). The
sample of PSUs currently used in the survey consists of 91
areas, of which 75 urban areas are also used by the Consumer
Price Index program.

Diary Survey. At the beginning of the 2-week collection period, the Census Bureau interviewer, using the Household
Characteristics Questionnaire (a CAPI instrument), records
demographic information on members of each sampled consumer unit. At this time, the interviewer also leaves the Diary
questionnaire—or daily expenditure record—with the consumer unit, to record expenditures for the week.
At the end of the first week, the interviewer collects the
diary, reviews the entries, answers any questions, and leaves
a second diary. The interviewer picks up the second diary at
the end of the second week and reviews the entries. During
this time, the interviewer again uses the Household Characteristics Questionnaire to collect previous-year information
on work experience and income. Each week of a consumer
unit’s participation in the survey is treated as a separate occurrence.
The Census Bureau performs preliminary processing activities, including a number of data edits and adjustments.
Data in the diaries are reviewed during a field edit for completeness and consistency. All notes are reviewed, so expenditure data can be transcribed to the questionnaire for keying.
In addition, item codes are assigned to reported expenditure
items, household and consumer unit codes are assigned to

The 91 PSUs are classified into four categories:
• 21 “A” PSUs, which are metropolitan CBSAs with a
population over 2.7 million people
• 38 “X” PSUs, which are metropolitan CBSAs with a
population under 2.7 million people
• 16 “Y” PSUs, which are micropolitan CBSAs, defined
as areas that have at least one urban cluster of at least
10,000 but less than 50,000 population, plus adjacent
territory that has a high degree of social and economic
integration with the core as measured by commuting ties
• 16 “Z” PSUs, which are non-CBSA areas, and are of-
ten referred to as “rural” PSUs


Within these 91 PSUs, the sampling frame (the list of addresses from which the sample is drawn) is now generated
from the 2000 Census 100-Percent Detail File. It is augmented by a sample of addresses drawn from new construction
permits and by extra housing units identified through coverage improvement techniques.
The population represented by the survey is the total U.S.
civilian noninstitutional population, both urban and rural. It
includes people living in houses, condominiums, apartments,
and group quarters such as college dormitories. It excludes
people such as military personnel living on base, nursing
home residents, and people in prisons.
The U.S. Census Bureau selects a sample of approximately 12,000 addresses per year to participate in the Diary Survey. Usable diaries are obtained from approximately 7,100
households at those addresses. Diaries are not obtained from
the other addresses due to refusals, vacancies, ineligibility,
or the nonexistence of a housing unit at the selected address.
The actual placement of diaries is spread equally over all 52
weeks of the year.
The Interview Survey is a rotating panel survey in which
approximately 14,000 addresses are contacted in each calendar quarter of the year. One-fifth of the addresses contacted
each quarter are new to the survey and provide “bounding”
interviews that provide baseline data, which are not used to
compute the survey’s published expenditure estimates. Excluding these bounding interviews and interviews not completed due to refusals, vacancies, ineligibility, or the nonexistence of a housing unit at the selected address, usable
interviews are obtained from approximately 7,100 households
each quarter. After a housing unit has been in the sample for
five consecutive quarters, it is dropped from the survey and a
new housing unit is selected to replace it.

There are three general categories of nonresponse:

Note: The sample design described above with 91 PSUs
is based on information collected in the 2000 Census, and
has been in use since 2006. The original 2000 census-based
sample design was introduced in 2005 and consisted of 102
PSUs: 28 “A” PSUs, 42 “X” PSUs, 16 “Y” PSUs, and 16 “Z”
PSUs. However, budget cuts in 2006 forced seven “A” PSUs
to be changed to the “X” category, and 11 “X” PSUs to be
dropped from the sample. Dropping 11 “X” PSUs from the
sample reduced the number of sampled addresses and interviewed households by approximately 8 percent. Otherwise
the original and current 2000 census-based sample designs
are the same.

Estimation methodology
The estimation of population quantities of interest, such as
the average expenditure per consumer unit on a particular
item, is achieved through the use of weights. Each consumer
unit in the survey is assigned a weight, which is the number
of similar consumer units in the U.S. civilian noninstitutional population the sampled consumer unit represents. Using
these weights, the average expenditure per consumer unit on
a particular item category is estimated by

• Type A nonresponses are refusals, temporary absenc-
es, and noncontacts
• Type B nonresponses are vacant housing units, hous-
ing units with temporary residents, and housing units
under construction
• Type C nonresponses are destroyed or abandoned hous-
ing units, and housing units converted to nonresiden-
tial use
Response rates are defined to be the percent of eligible
housing units (that is, the designated sample less Type B and
Type C nonresponses) from which usable interviews are collected. In the 2005 Interview Survey there were 39,988 eligible housing units from which 29,804 usable interviews were
collected, resulting in a response rate of 74.5 percent. In the
2005 Diary Survey there were 21,309 eligible housing units
from which 15,126 usable interviews were collected, resulting in a response rate of 71.0 percent.
Table 1. Analysis of response in the Consumer Expenditure
Survey, 2005

Sample unit

Interview Survey

Housing units designated
for the survey.............................
Less: Type B and C
nonresponses........................
Equals: Eligible units.................
Less: Type A nonresponses.....
Equals: Interviewed units..........
Percent of eligible units
interviewed.............................

y=

i∈s

Cooperation levels
Response data for the 2005 Consumer Expenditure Survey
are shown in table 1. For the Interview survey, the totals refer to housing units in the second through fifth quarters of
the survey (the non-bounding interviews), with each unique
housing unit providing up to four usable interviews. For the
Diary Survey, the totals refer to housing units in weeks 1 and
2 of the survey, with each unique housing unit providing up
to two usable interviews. Most Diary respondents participate
for both weeks.

49,242

26,054

9,254
39,988
10,184
29,804

4,745
21,309
6,183
15,126

74.5

71.0

∑w y
∑w
i∈s

Diary Survey

i

i

i

where
y = the average expenditure per consumer unit on the
item category,
yi = the expenditure made by the i th consumer unit on
the item category,
wi = the weight of the i th consumer unit in the sample,
and
s = the sample of consumer units that participated in
the survey.


For example, if yi is the expenditure on butter made by the
ith consumer unit in the sample during a given time period,
then y is an estimate of the average expenditure on butter
made by all consumer units in the U.S. civilian noninstitutional population during that time period.
If one wanted to estimate the proportion of consumer
units that purchased butter during a given time period, then
the same formula is applied, where yi is set equal to 1 if the
ith consumer unit purchased butter during the time period, and
0 if it did not. When this 1/0 definition of yi is used, y is an
estimate of the proportion of all consumer units in the U.S.
civilian noninstitutional population that purchased butter during the given time period.
Several factors are involved in computing the weight
of each consumer unit for which a usable interview is received. Each consumer unit is initially assigned a base
weight, which is equal to the inverse of the consumer unit’s
probability of being selected for the sample. Base weights
in the Consumer Expenditure Survey are typically around
10,000, which means that a consumer unit in the sample
represents 10,000 consumer units in the U.S. civilian noninstitutional population―itself plus 9,999 other consumer
units that were not selected for the sample. The base weight
is then adjusted by the following factors to correct for certain
nonsampling errors:

fact that a random sample of consumer units from across the
United States is used instead of collecting data from every
consumer unit in the nation.
Standard errors are estimated using the method of “balanced repeated replication.” In this method the sampled
PSUs are divided into 43 groups (called strata), and the consumer units within each stratum are randomly divided into
two half samples. Half of the consumer units are assigned to
one half sample, and the other half are assigned to the other
half sample. Then 44 different estimates of y are created using data from only one half sample per stratum. There are
many combinations of half samples that can be used to create
these “replicate” estimates, and the Consumer Expenditure
Survey uses 44 of them that are created in a “balanced” way
with a 44 x 44 Hadamard matrix. The standard error of y is
then estimated by

SE ( y ) =

 44
∑ ( yr − y ) 2
44 r =

where y is the r th replicate estimate of y .
The coefficient of variation is a related measure of sampling
variability. It measures the variability of the survey estimate
relative to the mean. It is defined by the equation

Weighting control factor. This adjusts for subsampling in the
field. Subsampling occurs when a data collector visits a particular address and discovers multiple housing units where
only one housing unit was expected.

CV ( y ) =

SE ( y )
× 00%
y

and is usually expressed as a percent.

Noninterview adjustment factor. This adjusts for interviews
that cannot be conducted in occupied housing units due to
a consumer unit’s refusal to participate in the survey or the
inability to contact anyone at the sample unit in spite of repeated attempts. This adjustment is based on region of the
country, household tenure (owner/renter), consumer unit
size, and race of the reference person.

Table 2. Precision of the Consumer Expenditure Survey
expenditure estimates, integrated Diary and Interview Survey
data, 2005

Calibration factor. This adjusts the weights to 24 “known”
population counts to account for frame undercoverage. These
“known” population counts are for age, race, household tenure (owner/renter), region of the country, and urban/rural. The
population counts are updated quarterly. Each consumer unit
is given its own unique calibration factor. There are infinitely
many sets of calibration factors that make the weights add
up to the 24 “known” population counts, and the Consumer
Expenditure Survey selects the set that minimizes the amount
of change made to the “initial weights” (initial weight = base
weight x weighting control factor x noninterview adjustment
factor).

Item category

Average

Coefficient
annual
Standard
of
expendi-
error
variation
ture per
SE ( y )
CV ( y )
consumer

(in
unit,

percent)

Total expenditures.................. $46,409
Food.........................................
Housing....................................
Apparel.....................................
Transportation..........................
Healthcare................................
Entertainment...........................
Personal care...........................
Cash contributions....................
Personal insurance and
pensions.................................
Other........................................

Precision of the estimates
The precision of the estimator y is measured by its standard
error. Standard errors measure the sampling variability of the
Consumer Expenditure Survey estimates. That is, they measure the uncertainty in the survey estimates caused by the

$254

0.55

5,931
15,167
1,886
8,344
2,664
2,388
541
1,663

42
120
40
130
25
54
7
43

.71
.79
2.10
1.55
.94
2.26
1.28
2.60

5,204
2,621

59
—

1.13
—

Presentation
Information from the Consumer Expenditure Survey is available in press releases, reports, and analytical papers. Micro

data from the survey are available on CD-ROM. Data are also
available from the Bureau of Labor Statistics Web site on the
Internet (http://www.bls.gov/cex) and from the BLS fax-ondemand service. Publications may be obtained through the
BLS Office of Publications and Special Studies and the BLS
Division of Consumer Expenditure Surveys.
Publications from the Consumer Expenditure Survey generally include tabulations of average expenditures and income
arrayed by consumer unit characteristics, such as consumer
unit size, age of reference person, or income. Tabulations by
two variables (cross-tabulations) are available for selected
characteristics, such as age by income or consumer unit size
by income. Integrated Diary and Interview Survey data are
published on an annual basis and tabulations are available on
the BLS Web site back to 1984.
The Diary and Interview Survey microdata that are available on CD-ROM contain files of the expenditure and income
reports of each consumer unit. In order to protect the identities of respondents, selected geographic detail is eliminated
and selected income and expenditure variables may be reset.
The Interview files contain expenditure data in two different
formats: MTAB files that present monthly values in an itemcoding framework based on the CPI pricing scheme, and
EXPN files that organize expenditures by the section of the
Interview questionnaire in which they are collected. Expenditure values on the EXPN files cover different time periods
depending on the specific questions asked, and the files also
contain relevant non-expenditure information not found on
the MTAB files. The Interview and Diary microdata files are
available on CD-ROM back to 1990 and for selected earlier
years.
Articles that include analyses of Consumer Expenditure
Survey data are published in the Monthly Labor Review
(MLR), as Issues in Labor Statistics, and in consumer expenditure anthologies. Copies of the most recent articles are
posted on the BLS Web site. Other survey information is also
available on the Internet, including answers to frequently
asked questions, a glossary, and order forms for survey products. Beginning with the 2000 data, estimates of standard errors for integrated Diary and Interview Survey data are available on the BLS Web site.

phrasing and on approaches to maintaining or increasing response rates. Attention has also been focused on the demands
placed upon respondents’ time.
The new user-friendly diary form, introduced in 2005 is an
example of research into alternative questionnaire formats.
The new diary is the culmination of an extensive series of
studies, including a large-scale field test. Through group discussions with data collection staff and cognitive testing with
respondents, researchers learned that respondents preferred
a more open format. The diary now obtains purchase data
in four general categories, rather than the numerous detailed
subcategories used previously. Another major improvement
was the addition of checkboxes to collect data about meals
eaten away from home, eliminating the need for respondents
to provide this information. Checkboxes have the added benefit of facilitating data coding, and so contribute to streamlined processing. While the new instrument is more efficient,
it is also visually more appealing, as it is physically smaller,
contains fewer pages, and is printed in brighter colors than
its predecessor. An evaluation of the new form showed that it
was generally effective, and demonstrated marked improvements in collection of some types of expenditures.
Ongoing research has focused on a variety of issues aimed
at reducing respondent burden and improving the quality of
survey data. Research studies underway include: examining
the effect of incentives on response rates and data quality;
investigating the dimensions of nonresponse bias; collecting
and analyzing supplemental information about the survey
(“paradata”) such as data from the Contact History Instrument, which may shed light on improvements to field procedures; and ways to increase within-household participation in
the Diary Survey. Research results have been presented at the
annual conferences of the American Association for Public
Opinion Research and the American Statistical Association
(ASA), and papers from both conferences can be found in the
ASA Conference Proceedings.

Uses and Limitations
The importance of the Consumer Expenditure Survey is that
it allows data users to relate the expenditures and income of
consumers to the characteristics of those consumers. The survey data are of value to government and private agencies interested in studying the welfare of particular segments of the
population, such as the elderly, low-income families, urban
families, and those receiving food stamps. The survey data
are used by economic policy makers interested in the effects
of policy changes on levels of living among diverse socioeconomic groups. Econometricians find the data useful in
constructing economic models. Market researchers find them
valuable in analyzing the demand for groups of goods and
services. The U.S. Department of Commerce uses the survey
data as a source of information for revising its benchmark
estimates of selected items in the expenditure and income
components of the National Accounts.
As in the past, the revision of the Consumer Price Index
remains a primary reason for undertaking such an extensive

Evaluation Research
The surveys undergo continuous evaluation by comparing
Consumer Expenditure Survey results with other data and
by performing internal statistical analyses to address current
concerns. To improve the expenditure estimates, research related to the data collection instruments and statistical studies of underreporting began in the mid-1980s. As a result of
this research, investigations into the cognitive aspects of the
data collection process became standard. A separate branch
was established within the Division of Consumer Expenditure Surveys in 1999 with the mission of conducting methodological studies to improve survey instruments and field collection procedures. Recent research has placed an emphasis
on developing alternative questionnaire formats and question


survey. The results of the Consumer Expenditure Survey
have been used to select new market baskets of goods and
services for the index, to determine the relative importance
of components, and to derive new cost weights for the baskets. In August 2002, the Bureau of Labor Statistics began
publishing a new index called the “Chained Consumer Price
Index for All Consumers” (C-CPI-U), which supplements
the existing consumer price indexes. The use of expenditure
data from different time periods distinguishes the C-CPIU from the existing CPI measures, which use only a single
expenditure base period to compute the price change over
time. The new index is designed to measure the change in the
“cost of living,” as compared to the existing indexes that are
designed to measure the change in the fixed market basket
of goods and services in retail outlets. The C-CPI-U uses
expenditure data from different time periods to reflect the
effect of substitution that consumers make across item categories in response to changes in the relative prices of goods
and services.
Sample surveys are subject to two types of errors—sampling and non-sampling. Sampling error is the uncertainty
caused by the fact that observations are taken from a random sample of population members and not from the entire population. Non-sampling error is the rest of the error.
Non-sampling errors can be attributed to many sources, such
as differences in the interpretation of questions, inability or
unwillingness of respondents to provide correct information,

data processing errors, and so on. Non-sampling error arises
regardless of whether data are collected from a sample or
from the entire population.
Another way of analyzing error is to divide it into variance
and bias. The variance is a measure of how close different estimates would be to each other if it were possible to repeat the
survey over and over using different samples. While it is not
feasible to repeat the survey over and over, statistical theory
allows the variance to be estimated anyway. A small variance
indicates that multiple independent samples would produce
values that are consistently very close to each other. Bias is
the difference between the “expected” value of an estimate
and its “true” value. A statistic may have a small variance but
a large bias, or it may have a large variance but a small bias.
For an estimate to be considered accurate, both its variance
and its bias need to be small.
The Bureau of Labor Statistics is constantly trying to
reduce the error in the Consumer Expenditure Survey estimates. Variance and sampling error are reduced by using a
sample of respondents that is as large as possible given resource constraints. Improving the accuracy of the estimates
was the primary reason for the significant expansion in the
sample for both the Interview and Diary surveys that occurred
in 1999. The Bureau reduces non-sampling error through
a series of computerized and professional data reviews, as
well as through continuous survey process improvements and
through theoretical research.