Text Table 9. Comparison of aggregate expenditures for food, Consumer Expenditure Diary Survey, Personal Consumption Ex-
penditures (PCE), Supermarket Business, and Progressive Grocer, 1991

Diary survey Ratio of Ratio of Ratio of
aggregate Diary to Diary to Diary to
Food categories expenditures PCE Supermarket Progressive

(in billions) Business Grocer
Food at home, total .. $255 | 0.74 4.10 1.22
Cereals and cereal 4 | 69 1.09 1.43
Bakery products 25 68 1.06 4.12
Meat including pot 58 83 1.07 4.07
Fish and seafood 8 1.20 | 1.19 2.68
Eggs . . 3 1.47 2.04 1.44
Fresh m 13 1.01 4.74 1.86
Other dairy products . 16 76 1.38 132
Fresh fruits and vege! . 25 92 73 | 92
Processed fruits and vegetab! 16 59 106 | 1.37
‘Sugar and other sweets . 10 37 1.32 2.48
Fats and oils - 7 76 1.09 1.74
Nonalcohol es. 22 53 1.02 1.20
Miscellaneous prepared foods . 37 | 85 1.28 1.16

Source: BLS Consumer Expenditure Survey; Supermarket Business, Consumer Expenditure Study (September 1991); and Progressive Grocer (July 1991).

Detailed food comparisons. Supermarket Business con-
ducts a comprehensive annual survey of food manufactur-
ers, packers, wholesalers, and retailers to construct a de-
tailed picture of grocery store sales by product line. Total
grocery store sales for the study are based on U.S. Bureau
of the Census estimates, and include sales by specialty food
stores. Estimates are also available annually from a similar
study by Progressive Grocer. The Progressive Grocer data
are limited to stores with annual food sales of $2 million or
more, accounting for only 75 to 80 percent of grocery store
food sales.

Text table 9 compares the industry data, as well as PCE
data, with detailed CE Diary survey estimates of food ex-
penditures. These comparisons show that the estimates for
1991 CE food at home expenditures are generally lower
than PCE but that the CE estimates are almost always
higher than those of Supermarket Business and Progressive
Grocer. In the case of the Progressive Grocer estimates, this
is due in part to the truncated store sample, as noted above.
The results shown in text table 9 for 1991 are, in general,
similar to those from previous years.

Residential Energy Consumption Survey. The Energy In-
formation Administration of the U.S. Department of En-
ergy (DOE) publishes data collected in the Residential En-
ergy Consumption Survey (RECS) on expenditures for
electricity, natural gas, fuel oil and kerosene, and liquified
petroleum gas. The data are published triennially. The
RECS focuses on obtaining detailed data from energy
suppliers on residential energy use. To make the compari-
son, time periods and fuel types were matched to the extent
possible. Fuel oil and kerosene are not compared because
of differences in how the items are categorized and the in-
clusion of expenditures for wood fuel in RECS.

The data in text table 10 show aggregate expenditures
and ratios from the two surveys for periods back to 1984.
Some difference between the CE survey and RECS is to be

expected because imputations are made in the DOE sur-
veys for money value of utilities included in residential
rents. In addition, the RECS covers military households
who live on base, but the CE survey does not include such
households. The 1990 data show that consumer expendi-
ture estimates for natural gas and electricity combined are
very close to those from the Energy Department survey.
The consumer expenditure estimate for electricity expen-
ditures, which is 3 percent higher than the RECS estimate,
more than offset the lower expenditure amount for natural
gas.

National Health Accounts. The Health Care Financing
Administration (HCFA) of the U.S. Department of
Health and Human Services publishes total aggregate
health costs of the United States in the National Health
Accounts (NHA). Total health care costs include pay-
ments from all sources, public and private. The CE survey
data are compared with the out-of-pocket expenditures in
the NHA. Out-of-pocket expenditures for health care in-
clude copayment and deductible amounts required by
third party payers (governments, commercial insurance
companies, and other nonhousehold sources) and medical
care services and products not covered by third parties. To
derive the out-of-pocket estimates, HCFA uses CE data
along with data from administrative and industry sources.
For the comparisons, estimates of insurance premiums are
based on detailed data in NHA on the financing of health
care.
Text table 11 shows a comparison of aggregate out-of-
pocket health care expenditures from the CE survey and
NHA. Expenditures by patients in nursing homes, which
are not covered in the CE survey, are excluded from the
comparison. Because of methodological changes in NHA,
ratios in the comparison below should not be compared
with those published in earlier bulletins.

As reported in the CE survey, aggregate health care ex-
penditures were $150 billion in 1991, or about 73 percent


Text table 10. Comparison of aggregate expenditures for household fuels, Consumer Expenditure Interview Survey and
Residential Energy Consumption Survey, April 1984-March 1985, 1987, and 1990

Interview survey
(in billions) Ratio of CE to RECS
Item L
‘Apr. 84- Apr. 84-
Mar. 85 1987 1990 Mar. 85 | 1987 1990
Natural gas and electricity, total . . $850 | $87.1 $97.4 1.01 99 99
Natural gas . 26.6 21.9 23.9 89 84 88
Electricity | 584 65.2 73.5 1.07 1.06 1.03
|

Note: The Residential Energy Consumption Survey was conducted annual- Source: The Residential Energy Consumption Survey data for 1984-85 and

ly from 1978 to 1982, and triennially since then. Estimates through March 1985 1987 are from Consumption and Expenditures, Part 1: National Data, DOE/
are for 12-month periods from April to March. Beginning in 1987, estimates are E1A-0321 and-for 1990 are from Household Energy Consumption and Expendi-
on a calendar year basis. No RECS data are available for April 1983 to March — tures 1990, DOE/EIA-0321.

1984,

Text table 11. Comparison of estimated aggregate expenditures for health care, Consumer Expenditure Survey and National
Health Accounts, 1988-91

| i
| ee Survey Ratio of CE to NHA
Expenditure categories T —— =
1968 | 1989 | 1990 | 1901 | 1988 | 1989 | 1990 1991
Health care, total ...... si19 | $132 | si4t | $150 | 0.74 0.75 0.76 0.73
Health insurance premiums ' 450) 51 56 64 a” 72 a” 74
Medical care, total? ..... 74 81 85 86 76 76 79 72
Medical commodities, total . 28 | 3t 33 34 66 69 66 65
Drugs and sundries 3 . 220 | 25 26 27 64 | 64 63 60
Medical equipment and supplies ° 5 | 7 6 7 80 | 1.03 83 90
Medical services, total . : 46 | 50 52 52 83 | 83 82 79
Professional services : 36 | 40 45 | 43 80 81 85 76
Hospital care......... 10 | 10 8 | 10 99 89 73 96
| i 1
1 NHA data used to obtain the ratios are derived form NHA out-of-pocket Note: Sums may not equal totals due to rounding.
estimates of health insurance data from Levit, Katherine R. and Cathy A. Co- Source: NHA data are from the U.S. Department of Health and Human Ser-
‘The Burden of Health Care Costs: Business, Households, and Govern. _vices, Health Care Financing Administration, “National Health Expenditures,
” Health Care Financing Review, Winter 1990, table 1. 1991," Health Care Financing Review, Spring 1993. Estimates have been re-
2 Excludes nursing home care and medical equipment repairs. vised using a rebenchmarking procedure which adjusts the category estimates
3 CE categories have been rearranged to match NHA. to proportions from the CE survey.

Text table 12. Comparison of money income before taxes, Consumer Expenditure Interview Survey and Current Population
Survey (CPS), total United States, 1988-91

| CE aggregate money income before taxes! ‘
{in bilhons) Ratio of CE to CPS.
Income catetory ]

1988 | 1989 | 1990 | 1991 | 1988 | 1989 | 1990 1991
Money income before taxes? . . | $2,694 | $2,987 | $3,077 | $3,300 0.85 0.87 0.87 0.90
Wage and salary income . : | 2086 | 2,228 | 2,344 | 2,502 87 87 80 93
Self-employment income ....... » | 170 | 243 225 250 84 1.08 98 111
Social Security and retirement income 201 | 325 332 351 98 1.02 97 97
Property income ...... oes 96 | 120 103 114 43 48 39 46

Unemployment, workers’ compensation,
and veterans’ benefits . 23 20 at 24 80 66 59 52

Public assistance and supplement

security income ......-2..0-2.0+ 24 20 23 2 686 | 7 79 80
Regular contributions and other income 28 33 30 ed 68

1 CE data are for complete reporters of income; see glossary. Source: CPS data are from U.S. Department of Commerce, Bureau of the
2 Money income before taxes excludes the value of food stamps, mealsas Census, Money Income of Households, Families, and Persons in the United
pay, and rent as pay. States, annual, Series P-60, No. 172, tables 33 and 63, and Series P-60, Nos.

Note: Ratios are based on unrounded data. 174 and 180, table 34.

12


of the $205 billion estimated from the NHA. Of the CE
survey total, $64 billion was spent on health insurance, $34
billion was spent on medical commodities, and $52 billion
was spent on medical services. The medical commodities
total was 65 percent of the NHA estimate, and the medical
services total was 79 percent of the NHA estimate. The ra-
tios for the health insurance estimates are relatively stable
from 1988 through 1991. Moderate variations in the ratios
for the medical commodities total and the medical services
total have occurred over the period.

Current Population Survey. The Bureau of the Census col-
lects income data in the March supplement to the Current
Population Survey (CPS). Using data collected for 1988
through 1990, comparisons are made with CE Interview
survey estimates of total consumer unit income before
taxes and by income component. The CPS aggregate in-
come estimates derive from the mean income of persons
and the number of persons with the specified income.

There are several differences between the CE survey and
the CPS. The CPS collects data in March for the previous
calendar year, while the CE survey collects income data
for the prior 12 months in the second and fifth interviews
of the consumer unit. These interviews may occur any
time during the year. CPS income data which are missing
(because of nonresponse to income questions) are imputed
based on demographic characteristics. By contrast, CE in-
come estimates are for complete income reporters only; in-
come is not imputed in the CE survey. Neither procedure
accounts for underreporting, which is especially prevalent
for property income.

As text table 12 shows, the CE survey total income data
compare well with the CPS for the most part. Total income
for the CE survey averages about 85 to 90 percent of the
CPS. Some difference is expected because the CPS popula-
tion is about 3 percent larger than the CE population. The
low ratios for property income reflect imputations for
missing data in the CPS and underreporting.

interpreting the data

Several factors should be considered when interpreting
the expenditure data, especially when relating averages to
individual circumstances. The data are averages for the to-
tal population—urban and rural. Because not all consum-
er units purchased each item during the survey period, the
average expenditure for an item is generally considerably
lower than the expenditure by those consumer units that
purchased it. The less frequently an item is purchased, the
greater the difference between the average for all consum-

er units and the average of those purchasing the item. For
instance, reference table 1 shows average expenditures for
new cars and trucks of only $1,078, because relatively few
consumer units actually bought a new vehicle. Of course,
the average cost for those who did make the purchase
would be substantially higher than this. For instance, if
about 8 percent of the households reported purchasing a
new car or truck in 1991, the average expenditure on new
cars and trucks for those households would be $13,475.
Even if all consumer units purchased a particular item, an
individual consumer unit may have spent more or less than
the average for that item. Even within a group with similar
characteristics, there may be significant variation. In-
come, family size, age of family members, geographic loca-
tion, and individual tastes and preferences all influence ex-
penditures.

Due to the small sample sizes, take special caution when
using data from the Metropolitan Statistical Area (MSA)
tables (reference tables 19-22). Even though 2 years of data
are used to increase the sample sizes, the average expendi-
tures of the most detailed items may not be reliable because
there may be few reports of expenditures for those items. A
small number of unusually large purchases, or increases or
decreases in the number of expenditures for infrequently
reported items, can cause a large change in the mean from
one year to the next.

Expenditures reported here are the direct out-of-pocket
expenditures. Indirect expenditures, which may be signifi-
cant, may be reflected elsewhere. For example, rental con-
tracts often include utilities. Renters with such contracts
would record no direct expense for utilities and, therefore,
appear to have lower utility expenses. Employers or insur-
ance companies frequently pay other costs. Consumer
units with members whose employers pay for all or part of
their health insurance or life insurance would have lower
direct expenses for these items than those who pay the en-
tire amount themselves.

In addition, use caution in interpreting changes in ex-
penditures over a short time span. Average amounts spent
on different expenditure components may fluctuate from
year to year due to changes in economic conditions. For
example, a decrease in the supply of food products as a re-
sult of poor weather conditions, or a decrease in the oil
supply arising from political events such as an oil embargo
might result in sharp price increases and short-term
changes in expenditure levels. A less volatile measure of
expenditure patterns is the share of total expenditures
spent on major categories of consumption over a period of
several years.