18  Monthly Labor Review • December 20

Household Liability Data

KathleenW.Johnson

is a senior economist,

and Geng Li is an

economist, in the

Division of Research

and Statistics, Board

of Governors of the

Federal Reserve System,

Washington, DC. The

opinions, analysis, and

conclusions put forth

in this article are solely

the authors’and do

not necessarily reflect

those of the Board

of Governors of the

Federal Reserve System

or itsstaff. All errors

are the authors’. E-mail:

kathleen.w.johnson@

frb.gov or geng.li@frb.

gov

KathleenW.Johnson

and

Geng Li The Consumer Expenditure Survey 

(CE) is the only household survey that 

records both a wide variety of household expenditures and the household’s balance sheet. Although its primary purpose is to 

provide weights for the market basket used to 

construct the Consumer Price Index (CPI) the 

CE has been used extensively by researchers to 

study household consumption and saving, distributions of personal income and wealth, the 

effect of income taxes, and issues related to the 

poor and the elderly.

Several studies have validated the quality 

of CE data. As the Bureau of Labor Statistics 

(BLS) notes, “consumer 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.”1

 With this description in 

mind, many studies seeking to validate CE data 

focus on the ability of the data to replicate aggregate expenditure measures, such as personal 

consumption expenditures (PCE) reported 

quarterly by the Bureau of Economic Analysis 

(BEA). In general, these studies conclude that 

annual aggregate expenditures reported in the 

CE are below those reported by the BEA.

2

Although validation studies have been conducted on expenditure data in the CE, there 

does not appear to be any study that has 

validated CE liability data. This article seeks 

to bridge that gap by comparing household 

debt payments and balances measured in the 

Household liability data in the

Consumer Expenditure Survey

Liability data from the Consumer Expenditure Survey (CE), the 

Survey of Consumer Finances, and an analogous aggregate measure

show that the major types of household debt balances and payments are

measured reasonably well in the CE; thus, CE data may be used to

examine household debt and its relation to household economic decisions

CE with those measured in the Survey of 

Consumer Finances (SCF). A triennial survey 

conducted by the Federal Reserve, the SCF

collects high-quality data on household wealth 

and liabilities, as well as rich covariates such 

as household demographics and income data. 

The accuracy of the SCF has been established 

in several studies. For example, a year-2000 

study showed that several balance sheet categories measured by the SCF lined up well with 

those in the Federal Reserve System’s Flow of 

Funds Accounts,3

 and another study compared 

estimates of income and wealth from the SCF 

with administrative tax data and found that 

the two sources compared favorably.4

 On the 

basis of this research, and because of its focus 

on measuring the household balance sheet, the 

SCF data are presumed to be accurate in this 

article, which then goes on to compare SCF

debt payment and balance information with 

the same information in the CE.

In general, the results of the comparison 

provide good evidence that balance and 

payments for the major types of household debt are measured reasonably well in 

the CE. The article also compares the trend 

in payments on household debt relative to 

household income, as measured in the CE, 

with the trend in an analogous aggregate 

statistic, the household debt service ratio, 

as measured by the Federal Reserve System. 

The trend in the CE debt payment-to-income ratio over the past 15 years is quite 
Monthly Labor Review • December 2009  

similar to that of the aggregate debt service ratio.

Measurement of debt in the CE

The BLS has conducted the CE consistently since the early 

1980s to provide weights for the market basket the Agency 

uses to construct the CPI. The CE interviews a consumer 

unit five times, once every 3 months. The first interview is 

conducted to establish contact with, and collect data on, the 

interviewee; the subsequent four interviews are carried out to 

collect most of the expenditure data. After the fifth interview, 

the consumer unit leaves the sample and new units are added 

to the sample. As part of its expenditure data collection, the 

BLS asks households to report their payments on mortgages 

and vehicle loans, as well as credit card debt balances. From 

this information, the majority of household debt payments 

can be estimated. In this study, debt payments of the 1992 

to 2007 waves of the CE were compared with debt payments 

measured in the SCF, which has been systematically collecting such data since 1992.5

 

Many of the types of debt covered by the CE have counterparts in the SCF. Both surveys report payments on firstlien mortgages, home equity loans, and lines of credit on the 

household’s primary residence. However, for debt collateralized by other properties, the SCF reports only total payments, 

while the CE breaks these payments down by type of loan 

(first lien, home equity loan, and so forth). Both the CE and 

the SCF include payments on vehicle loans and the amount of 

credit card debt, which can be used to estimate the required 

monthly payment. Finally, the CE has only limited information on other types of consumer loans, such as the balance 

of credit extended by medical service providers and “other 

credit sources,” whereas the SCF provides more detail, breaking payments down by type of loan (student loan, installment loan, personal loan, and other lines of credit). Because 

it is difficult to reconcile both the concept and measurement 

of the “other loans” category between the two surveys, only 

payments on loans secured by real estate and automobiles 

and payments on credit card loans are included in the comparison presented here. Still, these two types of loans account 

for about 85 percent of total debt payments measured in the 

SCF. Exhibit 1 lists the categories of debt from the SCF and 

the corresponding Universal Classification Codes (UCCs) in 

the CE used to construct total debt payments.

The first issue that arises in constructing comparable debt 

payments is the timing of each survey relative to the date the 

payment actually was made. In this article, debt payments 

in each survey are converted to an annual, calendar-year 

measure. Because the SCF debt payment questions refer to 

payments within the relevant SCF year, this conversion was 

straightforward: the payments simply were converted from 

the frequency actually reported by the household to an annual payment. In the CE, however, converting debt payment 

to an annual, calendar-year frequency was challenging for a 

number of reasons. First, the CE is a rolling sample, so the 12 

months to which the survey refers in interviews do not always 

match with a calendar year. Second, debt payments can have 

household-specific variations within a year. Third, the CE

longitudinal sample is unbalanced, because not all consumer 

units participate in all five interviews. Fourth, the CE weights 

are assigned quarterly, so the same consumer unit gets a different weight in each interview in which it participates.

These challenges were dealt with in turn. First, the CE sample was restricted to consumer units that participated in all 

interviews and reported valid income data. Second, for mortgage and auto-related debt, the annual payment was calculated as the sum of payments reported in all four interviews. 

These payments were obtained with the use of the monthly 

UCC-level data in the detailed expenditure (MTAB) file. To 

approximate payments in a given calendar year, consumer 

units that had at least two quarters overlapping with the SCF 

calendar year were included in the sample. For example, to 

match with the SCF 2001 wave, consumer units that entered 

the CE survey from the second quarter of 2000 to the second 

quarter of 2001 were included in the sample.5

 Consequently, 

the CE data presented here cover eight quarters bracketing 

Exhibit 1. Summary of debt payment 

 variables in the Survey of Consumer 

 Finances and the Consumer

 Expenditure Survey

SCF debt payment categories

Corresponding Consumer

Expenditure Survey Universal

Classification Code (UCC)

Mortgages on primary

residences

220311, 830201

Other real-estate-backed loans

Home equity loanssecured

by primary residence

220313, 830203

Lines of creditsecured by

primary residence

880110, 880120

Mortgages, home equity

loans, and lines of credit on

vacation homes and other

properties

220314, 790940, 830204,220312,

790920, 830202, 880210, 880220,

880310, 880320

Vehicle loans 850100, 870103, 870203, 870803

Credit cards Not computed from UCC-level

da

Other consumer loans Not comparable
Household Liability Data

20  Monthly Labor Review • December 2009

the SCF year.6 Third, because the reported payments on credit 

card debt in the CE data include only interest payments, debt 

service on credit card debt was calculated by means of the 

concept employed by the Federal Reserve System in its aggregate debt service ratio measure.7

 The calculation used 

the second-interview credit card debt balance.8

 Fourth, the 

arithmetic average of weights in the four quarters was used 

to approximate the consumer unit’s annual weight.

Total payments on household debt, defined as the sum 

of payments on mortgages for primary residences, mortgages on other property, auto loans, and credit cards, nearly doubled between the 1992 and 2007 waves of the CE, 

rising from about $4,900 in 1992 to about $9,500 in 2007. 

(See table 1.) This increase reflects, in part, an increase in 

the share of households with total debt payments greater 

than zero. The share reflects the fraction of consumers 

that made any debt payment in a year. In 1992, about 68 

percent of CE respondents had total debt payments greater than zero. By 2007, the share had reached 73 percent. 

Among the major types of household debt, mortgage debt 

on a primary residence represents the largest share, accounting for 58 percent of total debt payments in 2007. 

Mortgages on other real estate accounted for 14 percent 

of the total debt payments in 2007, auto loan payments 

made up 21 percent, and required minimum payments on 

credit cards accounted for the remaining 8 percent. 

Broadly speaking, the level of total household payments 

for these four types of debt calculated from the CE sample 

lines up reasonably well with that calculated from the SCF 

sample. (See table 1 and chart 1.) From 1992 through 2007, 

the mean of total household debt payments calculated from 

the CE sample was always a bit lower than that calculated 

from the SCF data, but the difference varies from year to 

year. The gap was smaller than 3 percent in 2001, but widened somewhat in 2004 and 2007. In addition, apart from 

1995 and 2007, the mean of total debt payments in the CE 

data was not statistically different from that in the SCF data. 

However, debt payments in the CE vary less than those in the 

SCF, most likely because of the topcoding of such payments 

in the CE.

9

Much of the difference in total payments between the two 

surveys reflects mortgage payments on primary residences, 

which account for more than one-half of total debt payments. 

This difference ranges between 8 and 15 percent, with the CE

seemingly consistently underestimating mortgage payments 

relative to the SCF, and is typically statistically significant.10

The gap between loans for other real estate calculated from 

the CE and those calculated from the SCF is the second-largest source of the difference between the two estimates in 

terms of dollar amount. Although this gap suggests that the 

CE estimates of payments on loans for other real estate are, 

on average, 25 percent lower than the SCF estimates, the variances of the estimates are quite high, so, except for 2007, the 

hypothesis that the gap is zero cannot be rejected. These underestimates of mortgage payments in the CE are somewhat 

offset by overestimates of payments on auto loans. The gap 

in payments on automobile loans between the two surveys is 

typically around 10 percent and is statistically insignificant in 

several years. In 2007, the auto loans payment in the SCF and 

the CE were essentially identical. 

The required minimum payments on credit cards aligned 

very well in earlier waves. However, of late it appears that 

the CE underestimated credit card debt relative to the SCF, 

reversing the pattern observed in the 1995 and 1998 SCF. 

Overall, estimates of debt payments in the CE appear to be 

reasonably comparable to those in the SCF, with the difference 

varying somewhat over time and across categories.

Debt payments also display similar patterns across 

demographic groups in the two surveys. Many of these patterns 

mirror those of household income. Total debt payments in 

the CE rise with the age of the head of the household until 

around age 45 and then fall steadily, a pattern mimicked by 

other types of debt as well. (See table 2.) Households whose 

head is White had higher debt payments, on average, than 

those whose head is non-White. Debt payments also rise 

with education: households whose head had at least a college 

degree had more than 4 times the debt payments of those 

whose head had less than a high school diploma. Finally, 

married households had more than twice the debt payments 

of unmarried households. Each of these patterns in the 

CE sample is evident as well in debt payments in the SCF 

sample.

Average outstanding household debt in the CE increased 

by more than 160 percent between 1992 and 2007, mainly 

because of a rapid increase in mortgages on primary residences. (See table 3.) In general, the CE underestimates 

total household debt somewhat relative to the SCF. (See 

table 3 and chart 2.) On average, the CE estimate of total 

debt is within 10 percent of the SCF estimate; for two of 

the six waves examined, it is within 5 percent. The bulk 

of the underestimate stems from mortgages on primary 

residences, which account for more than 80 percent of 

total household debt. The CE estimate of other mortgage 

debt also differs significantly from the SCF estimate, but 

these mortgages account for only about 5 percent of total 

household debt.

In contrast to the CE estimates of mortgage debt, CE estimates of vehicle debt and credit card debt are exceedingly 

close to estimates from the SCF. Over the six waves, the gap 

between the two surveys’ estimates of vehicle and credit card 
Monthly Labor Review • December 2009  

Table 1. Household debt payments, by year and survey, 3-year intervals, 1992–2007

Measure

1992 1995 1998

Survey of 

Consumer

Finances

Consumer 

Expenditure 

Survey

Ratio of

Consumer

Expen 

diture

Survey to 

Survey of

Consumer

Finances

Survey of

Consumer

Finances

Consumer

Expenditure

Survey

Ratio of

Consumer

Expenditure

Survey to

Survey of 

Consumer

Finances

Survey of 

Consumer 

Finances

Consumer

Expenditure

Survey

Ratio of 

Consumer 

Expenditure 

Survey to 

Survey of 

Consumer 

Finances

Total:

Mean....................................................................................... $4,974 $4,888 0.98 $5,456 $4,913 0.90 $6,791 $6,345 0

Standard deviation............................................................ 10,067 14,968 1.49 10,138 7,428 .73 21,788 8,486 

Share of positive payments............................................ .66 .68 1.02 .68 .69 1.01 .69 .73 1

Difference-in-means test................................................. . . . . . . .22 . . . . . . 2.11 . . . . . . 1

Primary mortgage:

Mean....................................................................................... 2,888 2,657 .92 3,107 2,641 .85 3,830 3,358 

Standard deviation............................................................ 5,957 4,713 .79 6,335 4,876 .77 6,665 5,404 

Share of positive payments............................................ .38 .39 1.03 .39 .41 1.05 .41 .43 1

Difference-in-means test................................................. . . . . . . 1.59 . . . . . . 2.81 . . . . . . 2

Other mortgage:

Mean....................................................................................... 747 794 1.06 712 518 .73 1,015 660 

Standard deviation............................................................ 6,420 13,783 2.15 6,271 3,471 .55 19,733 3,658 

Share of positive payments............................................ .13 .11 .82 .11 .09 .79 .14 .13 

Difference-in-means test................................................. . . . . . . .14 . . . . . . 1.43 . . . . . . 1

Vehicle :

Mean....................................................................................... 1,036 1,131 1.09 1,214 1,325 1.09 1,401 1,747 1

Standard deviation............................................................ 1,981 2,147 1.08 2,191 2,466 1.13 3,375 3,187 

Share of positive payments............................................ .29 .35 1.18 .32 .37 1.17 .31 .40 1

Difference-in-means test................................................. . . . . . . 1.60 . . . . . . 1.46 . . . . . . 3

Credit card:

Mean....................................................................................... 303 306 1.01 424 429 1.01 545 579 1

Standard deviation............................................................ 799 736 .92 1,099 1,077 .98 1,475 1,368 

Share of positive payments............................................ .44 .45 1.04 .47 .48 1.02 .44 .50 1

Difference-in-means test................................................. . . . . . . .14 . . . . . . .15 . . . . . . 

N................................................................................................... 3,906 1,828 . . . 4,299 1,311 . . . 4,305 1,657 . . .

2001 2004 2007

Total:

Mean....................................................................................... $7,701 $7,438 .97 $8,975 $7,952 .89 $10,983 $9,470 

Standard deviation............................................................ 13,006 9,817 .75 44,575 9,752 .22 17,368 12,546 

Share of positive payments............................................ .71 .75 1.05 .72 .73 1.01 .72 .73 1

Difference-in-means test................................................. . . . . . . .93 . . . . . . 1.48 . . . . . . 3

Primary mortgage:

Mean....................................................................................... 4,483 4,117 .92 5,085 4,593 .90 6,332 5,487 

Standard deviation............................................................ 8,244 6,470 .78 7,963 6,914 .87 10,901 8,178 

Share of positive payments............................................ .42 .45 1.06 .45 .49 1.09 .45 .49 1

Difference-in-means test................................................. . . . . . . 1.99 . . . . . . 2.65 . . . . . . 3
Household Liability Data

22  Monthly Labor Review • December 2009

Other mortgage:

Mean....................................................................................... $967 $844 0.87 $1,284 $606 0.47 $1,691 $1,308 0

Standard deviation............................................................ 7,332 4,161 .57 43,131 2,990 .07 8,635 6,069 

Share of positive payments............................................ .12 .13 1.03 .15 .11 .74 .16 .16 1

Difference-in-means test................................................. . . . . . . .87 . . . . . . 1.05 . . . . . . 2

Vehicle

Mean....................................................................................... 1,700 1,875 1.10 1,895 2,109 1.11 1,947 1,943 1

Standard deviation............................................................ 3,278 3,455 1.05 3,704 3,682 .99 4,596 3,604 

Share of positive payments............................................ .35 .38 1.11 .36 .42 1.18 .35 .38 1

Difference-in-means test................................................. . . . . . . 1.99 . . . . . . 2.28 . . . . . . . 

Credit card:

Mean....................................................................................... 551 602 1.09 712 643 .90 1,013 731 

Standard deviation............................................................ 1,718 1,539 .90 1,831 1,689 .92 2,773 1,754 

Share of positive payments............................................ .44 .46 1.04 .46 .43 .93 .46 .42 

Difference-in-means test................................................. . . . . . . 1.23 . . . . . . 1.56 . . . . . . 4

N................................................................................................... 4,442 2,255 . . . 4,519 2,347 . . . 4,418 1,904 . . .

Table 1. Continued—Household debt payments, by year and survey, 3-year intervals, 1992–2007

Measure

2001 2004 2007

Survey of 

Consumer

Finances

Consumer 

Expenditure 

Survey

Ratio of

Consumer

Expenditure

Survey to 

Survey of

Consumer

Finances

Survey of

Consumer

Finances

Consumer

Expenditure

Survey

Ratio of

Consumer

Expenditure

Survey to

Survey of 

Consumer

Finances

Survey of 

Consumer 

Finances

Consumer

Expenditure

Survey

Ratio of 

Consumer 

Expenditure 

Survey to 

Survey of 

Consumer 

Finances

 Chart 1. Debt payments, ratio of Survey of Consumer Finance amounts to Consumer Expenditure 

Survey amounts, 3-year intervals, 1992–2007

Percent Percent

Mean total

payments

Mean credit

card payments

Mean vehicle

loan payments

Mean payments

on other

real estate loans

Mean mortgage

payments

1.4

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1992 1995 1998 2001 2004 2007
Monthly Labor Review • December 2009  

Table 2. Household debt payments by demographic characteristics and survey, 2004

Characteristic

Total debt payments Mortgage Other real estate Vehicle Credit card

Survey of 

Consumer

Finances

Consumer 

Expenditure 

Survey

Survey of 

Consumer

Finances

Consumer 

Expenditure 

Survey

Survey of 

Consumer

Finances

Consumer 

Expenditure 

Survey

Survey of 

Consumer

Finances

Consumer 

Expenditure 

Survey

Survey of 

Consumer

Finances

Consumer 

Expenditure 

Survey

Age, years

Under 35............................... $6,808 $7,333 $3,918 $3,953 $414 $269 $1,949 $2,407 $527 $

35–45..................................... 11,849 10,830 7,262 6,950 1,291 703 2,376 2,429 920 

45–55..................................... 12,799 10,871 7,641 6,290 1,925 698 2,224 2,963 1,010 

55–65..................................... 10,291 8,819 5,263 4,841 2,126 1,089 2,185 2,208 717 

65–75 .................................... 4,809 3,615 2,154 1,801 944 382 1,198 1,120 512 

75 and older......................... 2,725 1,421 967 701 965 307 489 304 304 

Race

White...................................... 9,803 8,074 5,526 4,621 1,512 697 1,994 2,088 771 

Non-White............................ 6,823 7,309 3,937 4,449 691 126 1,638 2,221 556 

Education

Less than high school ...... 3,239 3,209 1,576 1,703 316 81 1,026 1,166 321 

High school.......................... 6,387 5,940 3,338 2,939 529 487 1,876 2,107 645 

Some college ...................... 8,839 8,238 4,828 4,475 1,176 650 1,976 2,320 859 

College and above............ 13,468 11,913 8,057 7,688 2,350 937 2,214 2,378 847 

Marital status

Married.................................. 12,132 10,298 6,914 5,972 1,782 819 2,579 2,748 857 

Unmarried............................ 4,622 4,763 2,563 2,720 597 316 952 1,241 510 

 Chart 2. Debt, ratio of Survey of Consumer Finances amounts to Consumer Expenditure Survey 

amounts, 3-year intervals, 1992–2007

Mean total

debt balance

Mean credit

card balance

Mean vehicle

loan balance

Mean balance

on other

real estate loans

Mean mortgage

balance

Percent

1.8

1.6

1.4

1.2

1.0

0.8

0.6

0.2

0.4

0.0

Percent

1.8

1.6

1.4

1.2

1.0

0.8

0.6

0.2

0.4

0.0

1992 1995 1998 2001 2004 2007
Household Liability Data

24  Monthly Labor Review • December 2009

Table 3. Household debt, by year and survey, 1992–2007

Measure

1992 1995 1998

Survey of 

Consumer

Finances

Consumer 

Expenditure 

Survey

Ratio of

Consumer

Expenditure

Survey to 

Survey of

Consumer

Finances

Survey of

Consumer

Finances

Consumer

Expenditure

Survey

Ratio of

Consumer

Expenditure

Survey to

Survey of 

Consumer’

Finances

Survey of 

Consumer 

Finances

Consumer

Expenditure

Survey

Ratio of 

Consumer 

Expenditure 

Survey to 

Survey of 

Consumer 

Finances

Total

 Mean........................................................... $29,158 $27,522 0.94 $33,518 $34,775 1.04 $42,702 $37,755 0.88 

 Standard Deviation................................ 71,855 45,113 .63 75,630 52,857 .70 84,205 59,367 .71 

 Difference in means test...................... . . . . . . 1.17 . . . . . . .76 . . . . . . 2.89 

Primary mortgage

 Mean........................................................... 24,959 22,739 .91 28,637 29,244 1.02 36,153 30,491 .84 

 Standard Deviation............................... 67,264 41,142 .61 72,879 49,576 .68 79,719 54,964 .69 

 Difference in means test..................... . . . . . . 1.71 . . . . . . .39 . . . . . . 3.53 

Other mortgage

 Mean........................................................... 1,170 1,733 1.48 863 1,376 1.59 1,360 2,003 1.47 

 Standard Deviation............................... 12,836 10,013 .78 7,292 7,287 1.00 11,264 9,067 .80 

 Difference in means test..................... . . . . . . 2.07 . . . . . . 2.60 . . . . . . 2.64 

Vehicle

 Mean........................................................... 2,018 2,036 1.01 2,605 2,640 1.01 3,371 3,379 1.00 

 Standard Deviation................................ 5,036 4,572 .91 6,313 5,287 .84 12,121 7,068 .58 

 Difference in means test...................... . . . . . . .16 . . . . . . .23 . . . . . . .04 

Credit card

 Mean........................................................... 1,011 1,014 1.00 1,413 1,516 1.07 1,817 1,882 1.04 

 Standard Deviation............................... 2,662 2,443 .92 3,662 3,677 1.00 4,917 4,461 .91 

 Difference in means test..................... . . . . . . .05 . . . . . . 1.04 . . . . . . .57

N...................................................................... 3,906 3,172 . . . 4,299 1,996 . . . 4,305 2,768 . . .

Year 2001 2004 2007

Total

 Mean.......................................................... $50,342 $45,961 .91 $74,045 $67,156 .91 $91,248 $72,822 .80 

 Standard Deviation............................... 94,062 72,436 .77 163,049 100,909 .62 175,462 110,421 .63 

 Difference in means test...................... . . . . . . 2.42 . . . . . . 2.31 . . . . . . 5.08 

Primary mortgage

 Mean........................................................... 42,673 38,252 .90 62,600 57,479 .92 78,502 61,060 .78 

 Standard Deviation............................... 87,227 68,138 .78 145,477 95,404 .66 162,416 100,724 .62 

 Difference in means test...................... . . . . . . 2.61 . . . . . . 1.89 . . . . . . 5.23 

Other mortgage

 Mean........................................................... 1,904 2,194 1.15 4,270 2,768 .65 4,281 4,889 1.14 

 Standard Deviation............................... 19,331 10,194 .53 46,757 13,675 .29 32,263 22,118 .69 

 Difference in means test..................... . . . . . . .88 . . . . . . 2.05 . . . . . . .87 

Vehicle

 Mean........................................................... 3,928 3,606 .92 4,803 4,712 .98 5,088 4,395 .86 

 Standard Deviation................................ 9,395 7,327 .78 22,300 9,412 .42 19,091 9,528 .50 

 Difference in means test...................... . . . . . . 1.77 . . . . . . .25 . . . . . . 1.93 

Credit card

 Mean........................................................... 1,837 1,908 1.04 2,372 2,198 .93 3,376 2,478 .73 

 Standard Deviation................................ 5,725 5,230 .91 6,105 5,835 .96 9,242 6,101 0.66 

 Difference in means test...................... . . . . . . .60 . . . . . . 1.29 . . . . . . 4.59 

N...................................................................... 4,442 4,050 . . . 4,519 3,381 . . . 4,418 1,964 . . .
Monthly Labor Review • December 2009  

debt is within 5 percent, on average, and the differences are 

not statistically significantly different from one another for 

most waves.

The time trend in CEdebt payments

Consistent with the rise in the annual averages, the distribution of the debt service ratio across CE households shifted to 

the right between the early and late years of the CE sample 

examined. (See chart 3.) The share of households with no 

debt payments declined from 21.0 percent in 1992 to 19.4 

percent in 2007. In addition, there is considerable heterogeneity across households.

The rightward shift is consistent with the rise in the aggregate household debt service ratio over the same period. 

As shown in chart 4, the aggregate ratio rose from about 111⁄2 

percent in 1993 to about 141⁄2 percent in 2006, before falling 

back to about 14 percent in early 2009, a rate of increase of 

about 22 basis points per year. At the same time, the average 

debt service ratio in the CE trended upward a little more than 

19 basis points per year. (See chart 5.) 

The key issue is whether this rightward shift reflects a 

broad-based increase in debt service or whether it indicates 

a significant rise among those in a select group. For example, 

the shift in the debt service ratio may have been related, in 

part, to a rise in homeownership and the associated rise in 

the share of households with mortgage payments. The CE 

data show that the share of households with mortgage payments increased from about 40 percent in the earlier years 

of the sample to about 50 percent in recent years. To take 

a closer look at the influence of the rise in homeownership, 

along with changes in other household characteristics, on the 

debt service ratio, the household debt service ratio from the 

CE is regressed on a linear time trend, homeownership and 

other household characteristics as control variables, as given 

by the formula

( )1 DSR time x i = + + α α α 0 1 2 i

where x is a vector that includes homeownership, age, education, marital status, and race.

The solid line in chart 5 shows the time trend in the household debt service ratio without controlling for household 

characteristics.11 The uptrend is broadly similar to that of the 

aggregate ratio over the same period. After controlling for 

household characteristics (dashed line), the slope is substantially reduced, but still trends significantly upward. All told, 

the remaining significant upward trend suggests that some 

part of the rise in the aggregate debt service ratio over time 

 Chart 3. Distribution of the household debt service ratio in the Consumer Expenditure Survey, 1992 

and 2007

Percent

distribution

1992 2007

Percent

distribution

0.0

30.0 30.0

0.0

5.0

10.0

15.0

20.0

25.0

0.0

5.0

10.0

15.0

20.0

25.0

0.1 0.2 0.3 0.4 05 0.6 07 0.8 0.9 1.0 >1.0
Household Liability Data

26  Monthly Labor Review • December 2009

 Chart 4. Aggregate household debt service ratio, 1993–2009

Percent Percent

16.0

10.0

11.0

12.0

13.0

14.0

15.0 Linear

Actual

16.0

10.0

11.0

12.0

13.0

14.0

15.0

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

 Chart 5. Time trend in household debt service ratio, Consumer Expenditure Survey, 1993–2007

Percent Percent

16.0

10.0

11.0

12.0

13.0

14.0

15.0

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

16.0

10.0

11.0

12.0

13.0

14.0

15.0

Without controls

With controls
Monthly Labor Review • December 2009  

reflects a broad trend toward higher debt service across all 

types of households.

A COMPARISON OF HOUSEHOLD LIABILITY information in the Consumer Expenditure Survey (CE) and the 

Survey of Consumer Finances (SCF) indicates that household debt balances and payments are measured reasonably 

well in the CE. In addition, the share of household income 

devoted to required payments on existing household debt 

(a measure of the household debt service ratio) between 

1992 and 2007, constructed from the CE sample, exhibits 

an upward trend that is broadly similar to a publicly available aggregate measure of household debt service. This 

validation suggests that household debt payment data 

from the CE may be used to help examine the relationship 

between household debt and other household economic 

Notes

ACKNOWLEDGMENT: The authors would like to thank Karen Dynan of the 

Brookings Institution; Masao Ogaki of The Ohio State University; and seminar 

participants at the Federal Reserve Board, the 2007 Midwest Macro Meetings, 

the 2007 Federal Reserve System Applied Microeconomics Conference, the 

2007 NBER Summer Institute, the FDIC Center for Financial Research, and the 

Consumer Expenditure Survey Data Users’ Workshop for helpful comments on 

an earlier draft of this article.

1

 “Consumer Expenditures and Income,” BLS Handbook of Methods (Bureau 

of Labor Statistics, 2006), chapter 16, p. 1, on the Internet at www.bls.gov/

cex/#publications (visited Dec. 16, 2009).

2

 See, for example, Raymond Gieseman, “The Consumer Expenditure Survey: quality control by comparative analysis,” Monthly Labor Review, March 

1987, pp. 8–14; and E. Raphael Branch, “The Consumer Expenditure Survey: a 

comparative analysis,” Monthly Labor Review, December 1994, pp. 47–55.

3

 Rochelle Antoniewicz, “A Comparison of the Household Sector from the Flow 

of Funds Accounts and the Survey of Consumer Finances,” working paper (Federal 

Reserve Board of Governors, October 2000), on the Internet at www.federalreserve.gov/pubs/oss/oss2/papers/antoniewicz_paper.pdf (visited Dec. 16, 2009).

4

 Barry Johnson and Kevin Moore, “Consider the Source: Differences in Estimates of Income and Wealth From Survey and Tax Data,” working paper (Board 

of Governors of the Federal Reserve System, 2005), on the Internet at www.federdecisions.

 In one example of such research, CE data are used to show 

that ex ante measures of a household’s debt service ratio can 

help to identify liquidity-constrained households. In particular, the consumption growth of households with a ratio in the 

top two quintiles and a low liquid-asset ratio is significantly 

more sensitive to income fluctuations than the consumption 

growth of other households.

Although this article has validated some of the self-reported 

CE liability data relative to another household survey, namely, 

the SCF, it does not fully address whether households report 

their debt accurately in any household survey. This type of 

measurement error may bias the estimated effects of debt 

measures on economic outcomes, suggesting that the study 

of how accurately households self-report debt is an important avenue for further research.

alreserve.gov/pubs/oss/oss2/papers/johnsmoore.pdf (visited Dec. 16, 2009).

5

 Keep in mind that the first interview does not collect expenditure and debt 

payment data.

6

 The sole exception is 2007, for which only six quarters of the CE data are used, 

because data for the second quarter of 2008 are not yet available. 

7

 Households are assumed to be subject to a minimum monthly credit card payment 

of 21⁄2 percent (or 30 percent per annum) of the outstanding credit card balance.

8

 In the CE, credit card debt balance data are collected only in the second and fifth 

quarterly interviews. Accordingly, data recorded for the third and fourth interviews 

were carried forward from the second interview.

9

 Topcoding does not affect the mean of the CE, because topcoded observations 

take a value equal to the mean of the reported values exceeding the topcode.

10 However, when other financial obligations related to mortgages are included, 

such as property taxes, the CE estimate of total mortgage obligations is larger, on 

average, than that of the SCF. Because the split between mortgage payments and 

property taxes is imputed for a substantial fraction of CE respondents, some of the 

difference may reflect the imputation method.

11 The time trend was smoothed by regressing the year effects on time and plotting the resulting regression line.

APPENDIX: Definitions of variables

Debt payments

Debt payments are payments on mortgage, auto, and home equity loans from the MTAB file, plus payments on credit card loans. 

In the MTAB files, debt payments include principal and interest 

expenditures associated with the Universal Classification Codes 

(UCCs) for each type of secured debt. For example, debt payments 

on auto loans include the following UCCs:

850100 Reduction of principal on vehicle loan

870103 Finance charges on loans for new cars, trucks, or vans

870203 Finance charges on loans for used cars, trucks, or vans

870803 Interest, other vehicle, financed

Payments on credit card loans equal 21⁄2 percent of the outstanding 

balance reported in the FN2 file, which is part of the CE microdata 

release.

Debt service ratio

The debt service ratio is the ratio of debt payments to expected 

income. Expected income equals income fitted from a regression 

of the average income from each household’s second and fifth interviews on the age of the reference person, age squared, age cubed, 

and dummy variables for non-White reference persons, high school 

graduates, and college graduates.