Attachment Q - BLS Handbook of Methods

Chapter 16.
Consumer Expenditures and Income

C

onsumer expenditure surveys are specialized studies
in which the primary emphasis is on data related to
family expenditures for goods and services used in
day-to-day living. The Consumer Expenditure Survey (CE)
of the Bureau of Labor Statistics (BLS, the Bureau) also
collects 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
Current Survey......................................................... 1
Interview Survey................................................... 2
Diary Survey......................................................... 3
Integrated survey data........................................... 3
Data collection and processing............................. 3
Sample Design......................................................... 5
Selection of households........................................ 5
Cooperation levels................................................ 5
Estimation methodology....................................... 6
Precision of the estimates...................................... 6
Presentation.............................................................. 7
Evaluation Research................................................. 7
Survey Uses............................................................. 8
Survey Limitations................................................... 8

Background
The Bureau’s studies of family living conditions rank among
its oldest data-collecting functions. The first nationwide
expenditure survey was conducted during 1888–1891 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 20th century, a second survey was administered
in 1901. The resulting data provided the weights for an index
of prices of food purchased by workers that was used as a
deflator for workers’ incomes and expenditures for all kinds
of goods until World War I. A third survey, conducted during
1917–1919, 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, during 1934–1936,
primarily to revise CPI weights.
During the Great 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 1934–1936 investigation, the
Bureau cooperated with four other Federal agencies in a
fifth survey, the 1935–1936 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 1935–1936 study. The seventh survey, the 1960–1961
Survey of Consumer Expenditures, once again included both
urban and rural families, and provided the basis for revising
the CPI weights, while 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 1972–1973. 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 CPI
weights.

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 CE remain the same: to provide the basis for revising
1

Quality control is provided by a re-interview 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 re-interview
is conducted by a senior field representative. A subsample
of approximately 12 percent of households in the Interview
Survey and 10 percent in the Diary Survey is re-interviewed
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. The information
that respondents provide is used solely for statistical
purposes. All Census Bureau data collectors take an oath of
confidentiality and are subject to fines and imprisonment for
improperly disclosing information provided by respondents.
Names and addresses are removed from all forms and
datasets prior to transmission from the Census Bureau to
BLS and are not included in any statistical releases. At BLS,
the data are processed and stored on secure servers, with
access limited to employees having security clearances. As
a further precaution, BLS applies certain restrictions to the
microdata shown on the public-use CD-ROMs. These include
geographical and value restrictions that prevent identification
of respondents.

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 1972–1973 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 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 for 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 that
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 by any member of the consumer unit during
the reporting period, whether payment was or was not made
at the time of purchase. Expenditure amounts include all sales
and excise taxes for all items purchased by the consumer unit.
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 average, it takes 60
minutes to complete the interview.
In the Diary Survey, detailed data are collected on all
expenditures made by consumer units during their 2-week
participation in the survey. 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 estimated that it takes the respondent 15 minutes each
day to complete the diary.

Interview Survey
The Interview Survey is designed to collect data on the types
of expenditures that 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 those for property, automobiles, or major appliances,
or expenditures that 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 treated
independently, so that estimates are not dependent upon a
particular 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, medical, and education), form
the basis of the expenditure estimates derived from the
2

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.
Expenditure data are collected via two major types of
questions. The first set of questions asks the respondent for
the month of purchase of each reported expenditure. The
second asks for a quarterly amount of expenditures. The
use of these two 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. A 12-month recall period is used in the
collection of income- and asset-type data.

Integrated survey data
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 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
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 every 2 years.

Diary Survey
The primary objective of the Diary Survey is to obtain
expenditures 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, as well as 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 in which respondents record a detailed
description of all expenses for two consecutive 1-week
periods. Data collected each week are considered statistically
independent. 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 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 surveys. 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 a 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 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
3

the next quarter. This way, a few fields are updated each
quarter, rather than re-collecting the entire data record. (As
mentioned earlier, names and addresses of respondents are
not transmitted.)
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. During this data review, BLS conducts the following
steps: verifies counts and means by region, checks family
relationship coding inconsistencies, and inspects selected
extreme values for expenditure and income categories. Other
adjustments convert mortgage and vehicle payments 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. Additionally, 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 natural 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 data adjustment routines, to analyze the results.
The CE implemented multiple imputations of income
data, starting with the publication of 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. One 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.
The CE Interview questionnaire is revised every 2 years
to incorporate new products and services and to make such
changes as clarifying instructions, improving navigation
through the instrument, incorporating changes required for
the CPI, and streamlining the interview by deleting outdated
items. Whereas changes to the questionnaire are made
biennially, CE staff continuously monitor the emergence

of new goods and services available in the marketplace, as
well as changes in the relative importance of existing items
in consumers’ budgets. New items are incorporated in a
product index that enables Census field representatives to
classify these new items by the appropriate item codes. Also,
updated information on how to report new goods and services
is provided to the field representatives on a regular basis.
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 that the
respondent may have and leaves a second diary. At the end
of the second week, the interviewer picks up the second diary
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. After the diaries are sent to the
Census Bureau’s National Processing Center, expenditure data
captured in the diaries are key-entered into electronic formats;
and a computer file of the database containing these data is
produced and transmitted monthly to Census headquarters,
along with image files of the diaries. Census headquarters
merges the expenditure data with the data collected in the
Household Characteristics Questionnaire and transmits
the merged file monthly to BLS. Names and addresses of
respondents are removed prior to transmitting the data.
At BLS, data are processed by computer to calculate
population weights, 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.
Like the Interview Survey, three monthly diary data files
are combined into quarterly databases; and BLS screens the
data 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.
4

Sample Design

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.

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 small clusters of counties grouped
together into geographic entities called “core-based statistical
areas” (CBSAs). There are two types of CBSAs: metropolitan
and micropolitan. Metropolitan CBSAs are areas that
have an urban “core” with 50,000 or more people, plus the
adjacent areas that have a high degree of social and economic
integration with the core, as measured by commuting ties.
Micropolitan CBSAs are areas that have an urban core of
10,000 to 50,000 people, plus the adjacent areas that have a
high degree of social and economic integration with the core,
as measured by commuting ties.
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. The 91 PSUs are classified
into four categories:
•

21 “A” PSUs, which are metropolitan CBSAs with a
population over 2 million people

•

38 “X” PSUs, which are metropolitan CBSAs with a
population under 2 million people

•

16 “Y” PSUs, which are micropolitan CBSAs

•

16 “Z” PSUs, which are non-CBSA areas and are often
referred to as “rural” PSUs

Cooperation levels
Response data for the 2009 CE 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, 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.
There are three general categories of nonresponse:
•

Type A nonresponses are refusals, temporary absences,
and noncontacts.

•

Type B nonresponses are vacant housing units, housing
units with temporary residents, and housing units under
construction.

•

Type C nonresponses are nonresidential addresses, such
as destroyed or abandoned housing units, and housing
units converted to nonresidential 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 2009 Interview Survey, there were 47,609
eligible housing units, from which 35,756 usable interviews
were collected, resulting in a response rate of 75.1 percent.
In the 2009 Diary Survey, there were 18,879 eligible housing
units, from which 14,495 usable interviews were collected,
resulting in a response rate of 76.8 percent.

Within these 91 PSUs, the sampling frame (the list of
addresses from which the sample is drawn) is generated from
the 2000 Census 100-Percent Detail File. The sampling frame
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 CE is the total U.S.
civilian noninstitutional population, both urban and rural. The
population includes people living in houses, condominiums,
apartments, and group quarters such as college dormitories.
Excluded are: 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 15,000 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”

Table 1. Analysis of response in the Consumer Expenditure
Survey, 2009
Sample unit
Housing units designated for
  survey
Less: Type B and C
  nonresponses
Equals: Eligible units
Less: Type A nonresponses
Equals: Interviewed units
Percent of eligible units
  interviewed
  1 

Interview
Survey
59,691

Diary Survey
1

25,266

12,082
47,609
11,853
35,756

6,387
18,879
4,384
14,495

75.1

76.8

The number of Diary Survey addresses (12,633) multiplied by two
weekly diaries

5

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 or renter), consumer unit
size, and race of the reference person.

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 that is the number of
similar consumer units in the U.S. civilian noninstitutional
population the sampled consumer unit represents. Using
these weights, BLS estimates the average expenditure per
consumer unit on a particular item category by

∑w y
y=
∑w
i

i∈s

i∈s

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 or renter), region of the country, and urban
or 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 CE 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).

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
and

th

consumer unit in the sample,

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

s = the sample of consumer units that participated in the
survey.
For example, if yi is the expenditure on butter made by
the i th 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 wants 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 i th
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 that
is equal to the inverse of the consumer unit’s probability of
being selected for the sample. Base weights in the CE 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:

SE ( y ) =

1 44
( yr − y ) 2
∑
44 r =1

where y r is the r th replicate estimate of y .
The coefficient of variation is a related measure of sampling
variability and measures the variability of the survey estimate
relative to the mean. The coefficient of variation 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 ) =

6

SE ( y )
× 100%
y

Articles that include analyses of CE data are published
online in the Monthly Labor Review (MLR), in the publication,
Focus on Prices and Spending, and in CE anthologies. Other
survey information is available on the Internet, including
answers to frequently asked questions, copies of the
Interview and Diary Survey instrument, a glossary of terms,
and order forms for survey products. Starting with the 2000
data, estimates of standard errors for integrated Diary and
Interview Survey data are available on the BLS website.

Table 2. Precision of the Consumer Expenditure Survey
expenditure estimates, integrated Diary and Interview Survey
data, 2009

Item
category

Total expenditures
Food

Average
annual
expenditure
per
consumer
unit, ( y )

Standard
error, SE
(y)

Coefficient of
variation,
CV ( y )
(in percent)

$595

1.21

$49,067
6,372

84

1.31

Housing

16,895

194

1.15

Apparel

1,725

50

2.90

Transportation

7,658

165

2.16

Healthcare

3,126

58

1.86

Entertainment

2,693

64

2.38

Personal care
Cash contributions

596

9

1.58

1,723

84

4.90

5,471

155

2,83

2,808

…

…

Evaluation Research
Consumer expenditure surveys undergo continuous evaluation
by comparing results with other data and by performing
internal statistical, qualitative, and cognitive analyses to
address current methodological concerns. To improve
expenditure estimates, research related to the data collection
instruments, field procedures, and sources of potential survey
error (e.g., nonresponse bias or measurement error) began in
the mid-1980s, and have since become standard practice. A
separate Branch of Research and Program Development was
established within the Division of Consumer Expenditure
Survey in 1999, with the mission of developing and conducting
methodological studies to improve survey instruments, field
procedures, and overall survey data quality.
The user-friendly diary form introduced in 2005 is one
example of a research-driven survey improvement. This diary
was 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, thus eliminating the need for respondents to
provide this information. Checkboxes have the added benefit
of facilitating data coding, and so contribute to streamlined
processing. In addition to being more efficient, the new diary
is visually more appealing, as it is smaller, contains fewer
pages, and is printed in brighter colors than its predecessor.
An evaluation of use of results from the new diary shows that
it is more effective and demonstrated marked improvements
in collection of some types of expenditures.
Other in-house Bureau studies recently completed include:
1) examining the effect of incentives on response rates and
data quality 2) investigating the dimensions of nonresponse
bias 3) 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 4) exploring ways to increase withinhousehold 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 proceedings of the Joint
Statistical Meetings.

Personal insurance
and pensions
Other

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“Other” includes alcoholic beverages, reading, education,
tobacco, and miscellaneous expenditures.
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Presentation
Information from the CE is available in press releases,
reports, and analytical papers. Microdata from the survey
are available on CD-ROM. Data are also available from the
Bureau of Labor Statistics website (http://www.bls.gov/cex)
and the BLS Consumer Expenditure Survey Division.
Publications from the CE 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 (crosstabulations) 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 starting with 1984 are available on the
BLS website.
The Diary and Interview Survey microdata that are
available on CD-ROM contain files of expenditure and
income reports of each consumer unit. To protect the identities
of respondents, selected geographic detail is eliminated, and
selected income and expenditure variables may be topcoded.
The Interview files contain expenditure data in two formats:
MTAB files that present monthly values in an item-coding
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 specific questions asked; and files also contain relevant
non-expenditure information not found on the MTAB files.
The annual Interview and Diary microdata files are available
on CD-ROM beginning with 1990, as well as for selected
earlier years.
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Since 2009, research efforts have placed an emphasis
on updating the design of the Consumer Expenditure
Survey. At that time, the CE program initiated the Gemini
Project, with the goal of promoting improved expenditure
estimates in the CE—through an improved survey design—
by reducing measurement error, particularly error caused
by underreporting. The multi-year survey redesign project
includes research, pilot testing, and transition to the new
survey design. The scope of the redesign project is broad
and open to a wide range of design alternatives, such as
new modes, modular surveys, and innovative technologies.
During the course of the Gemini Project, program staff will
develop and test potential survey design changes, large
and small, aimed at improving data quality, increasing the
analytic value of the data to users, and supporting greater
operational flexibility to respond to changes in the datacollection environment.
Redesign-related research has focused on a variety of
topics aimed at assessing the potential of design alternatives.
Ongoing studies feature evaluating the feasibility and impact
of split questionnaire designs; shorter interview length;
alternative recall periods; varying interviewing frequencies;
recall aids; and new data collection technologies, such as
data-capture devices, financial software, and an online diary.
In addition, the program is researching the use of transaction
records in a variety of formats, supplemented by respondent
recall, as the primary data source for information about
respondent expenditures.
In early 2011, the program contracted with the National
Academies Committee on National Statistics to form a
consensus expert panel, coordinate several research events,
and produce a report containing redesign recommendations
and other outside independent proposals. For further
information on the Gemini Project, see www.bls.gov/cex/
geminiproject.htm.
As an important part of the CE quality assurance
program, estimates from CE data are compared regularly
with corresponding estimates from other data sources to
evaluate the soundness of CE estimates at any point in time,
as well as the consistency of estimates over time. Among
the comparisons that are made are those for a wide range
of expenditure categories as well as comparisons of data
on income and on assets and liabilities. For information
on published articles and presentations comparing CE
data with those from other sources, see www.bls.gov/cex/
cecomparison.htm.

effects of policy changes on levels of living among diverse
socioeconomic groups, and econometricians find the data
useful in constructing economic models. Market researchers
find consumer expenditure data valuable in analyzing the
demand for groups of goods and services. Additionally, 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, and the Department of Defense uses
the data in determining cost-of-living allowances for military
personnel.
As in the past, the revision of the Consumer Price Index
remains a primary reason for undertaking this extensive
survey. Results from the Consumer Expenditure Survey are
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, 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-CPI-U
from the existing CPI measures, which use only a single
expenditure base period to compute the price change over
time. The chained index is designed to measure the change
in the “cost of living,” as compared with 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.

Survey Limitations
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 and arises regardless
of whether data are collected from a sample or from the entire
population. 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, etc.
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. 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

Survey Uses
The importance of the Consumer Expenditure Survey is that
it allows data users to correlate expenditures and income
of consumers to the characteristics of those consumers.
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. Data
also are used by economic policymakers interested in the
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and its bias must 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 is the primary reason for the significant expansion
in the sample for both the Interview and Diary Surveys that
occurred in 1999. Going forward, the Bureau will strive to
reduce non-sampling error through a series of computerized
and professional data reviews, as well as through continuous
survey process improvements and theoretical research.

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