Monthly Labor Review April 2005 11

Between 1981 and 2001, economic inequality

among groups in the general population

has increased in the United States;

two measures of income and consumption

are used to gauge relative well-being

Economic inequality through the prisms

of income and consumption

David S. Johnson,

Timothy M.

Smeeding, and

Barbara Boyle Torrey

David S. Johnson is

Assistant

Commissioner

of Consumer Prices

and

Price Indexes in the

Office of Prices

and Living Conditions,

U.S. Bureau of Labor

Statistics, E-mail:

Johnson.DS@bls.gov;

Timothy M. Smeeding

is Maxwell Professor

of Public Policy

at Syracuse University,

E-mail:

tmsmeed@maxwell.syr.

edu; and

Barbara Boyle Torrey is

Visiting Fellow,

Population Reference

Bureau, E-mail:

btorrey@prb.org.

Economic Inequality

A

lan Greenspan recently stated, “There is a

surprising difference between the trends

in the dispersion of holdings of claims to

goods and services (income and wealth) and trends

in the dispersion of actual consumption, which is,

of course, the ultimate determinant of material or

economic well-being.”1 The “surprising difference”

between income and consumption distribution

trends is the subject of this article.

Between 1981 and 2001, economic inequality has

increased substantially in the United States. This

increase occurs regardless of which data or

formulas are used to measure it. And inequality

increases regardless of whether the resource

measured is income or consumption.2

Most studies of poverty and inequality are

based on income measurements for practical

reasons. But conceptual limitations of income have

led to an increasing number of studies using

consumption measures, even if they are not as

complete as the income measures that we have

available. We think that income and consumption

are two different prisms through which to view

well-being. Their spectrums overlap, but it is their

differences that this article addresses.

This article begins with a brief discussion of the

strengths and weaknesses of both income and

consumption measures. It then uses both measures

to show how the trends in inequality differ by

household type and for the individuals in each of

those households. It illustrates how the two

resource measures produce different individuals at

the top and bottom of the general population’s

distribution. The article concludes with an

examination of the group that looks the most

disadvantaged regardless of the prism used—

children and the adults they live with.

Hypotheses, data, and definitions

The life-cycle hypothesis suggests that income

will increase through working ages and then

decline after retirement.3 Because of this

predictable pattern, most people will save in their

higher income years and dissave in their lower

income years to smooth their consumption over

time. The permanent income hypothesis suggests

that current income has both permanent and

transitory components and that consumer units

base their long- term consumption patterns on their

permanent income. “The transitory components of

income show up primarily in changes in the

consumer units’ assets and liabilities, that is, in [its]

measured savings.”4 The combination of these two

hypotheses suggests that individual income levels

will generally vary more than consumption levels,

and consumption will be higher than incomes at

both younger and older ages. This implies that

levels of relative poverty and measures of

inequality tend to be lower using consumption

rather than income.5

Which measure of well-being? Most studies

of well-being and its inequality are still based on

annual income data.6 This is partly because of

history and also partly because of habit. Income
12 Monthly Labor Review April 2005

Economic Inequality

data are accessible, comparable over time, and of high quality.

They are also readily understandable as a means by which

well-being can be achieved. Moreover, international

standards for household income distribution comparability

have been established,7 whereas those for consumption or

expenditure inequality have not. But income is often

underreported in surveys. And because it varies by age over

the life cycle, an estimate of income inequality at any point in

time may be an overestimate of longer period income

inequality.8 Income inequality also increases within cohorts

over time. Therefore, aggregate inequality will depend, in part,

on the national population age structure and also on the

pattern of intergenerational transfers. Also, Gottschalk and

Moffitt found that one-third to one-half of the increase in

income inequality during the 1980s was accounted for by

transitory income changes and not from changes in

permanent income.9 This may be good news because permanent income is a better measure of long-term well-being

than transitory income. But it may be bad news if researchers

have interpreted transitory changes as permanent changes.

Because of the limitations of income as a resource measure

of well-being and its inequality, many researchers have

suggested that consumption may be a more appropriate

resource to measure economic well-being.10 They argue that

consumption is a more appropriate indicator because utility

is derived from the consumption of goods and services rather

than the receipt of income. Also, consumption is a better

measure of permanent income, which is closer in concept to a

measure of well-being than is measured income. However,

consumption expenditures do not capture all of the

dimensions of well-being, such as leisure or household

production. And adjustments have to be made to convert the

consumption of durable goods to the value of their services

over time. Measuring “actual” consumption rather than

expenditures is exceedingly difficult, especially when

durables are involved.11

Using both measures. Income and consumption measures

have different strengths and weaknesses. Rather than choose

between them, Borooah and McGregor suggest that

consumption should be used as a measure of the standard of

living and that income should be used as a measure of the

level of resources.12 Although permanent income would be

the preferred measure of economic well-being, obtaining an

estimate of permanent income using cross-sectional survey

data is difficult. The National Academy of Sciences committee

report on poverty measurement also argued:

“Conceptually, an income definition is more appropriate

to the view that what matters is a family’s ability to attain

a living standard above the poverty level by means of its

own resources....In contrast to an income definition, an

expenditure (or consumption) definition is more

appropriate to the view that what matters is someone’s

actual standard of living, regardless of how it is attained.

In practice the availability of high-quality data is often a

prime determinant of whether an income- or expenditurebased family resource definition is used.” 13

For these reasons, Johnson and Smeeding suggested using

measures of both income and consumption for each household

to evaluate their well-being and the resulting distribution of

resources.14 They suggest that our understanding of economic

well-being is improved when both measures are used.

High quality data are not only important to determine which

resource definition to use, but they are also important to the

comparisons between the two resources. Therefore, this article

compares income and consumption data from the same survey.

This ensures that the comparison of measures of inequality is

as comparable as possible because the sampling frame, time

periods, and definitions of households and individuals are

identical.15

The methodology. We use the only data set in the United

States that contains both income and consumption

information—the Consumer Expenditure (CE) Interview

Survey data.16 The CE survey has been a continuing quarterly

survey since 1980. Data are collected from consumer units

five times over a 13-month period.17 Also collected in this

survey is the inventory of certain durable goods, for example,

homes, real estate, vehicles and major appliances, and income.

(See appendix for a complete description of the data.)

We use the CE data to develop four resource measures:

 1. Income (equivalent to pre-tax/post-cash transfer money

income as used in the Current Population Survey)

 2. Disposable income (income post direct tax, including

the Earned Income Tax Credit (EITC), plus the value of food

stamps)

3. Consumption–expenditures (the total spending for

current consumption)

4. Consumption, which is closer to a measure of real

“consumption.”

This final measure of consumption is consumptionexpenditures less the costs of home ownership and the

purchase price of vehicles plus the rental equivalence of

owned home and the service flows from vehicles. Table 1

shows the actual calculation of these four measures averaged

over all consumer units in the CE survey. (See data appendix.)

Not surprisingly, disposable income is lower than income in

every year, consumption is higher than consumption

expenditures, and disposable income is always higher than

consumption.
Monthly Labor Review April 2005 13

The CE survey collects data for consumer units, which will be

referred to as household units in this article. But a shortcoming

of a household or consumer unit of measurement is that it does

not take into account differences in household size. Therefore, in

this article, we disaggregate household information by age of

each individual within the household so that we can examine the

inequality of individuals by age group. Using individuals as the

unit of analysis is consistent with the welfare theory underlying

inequality and poverty measures.18

To obtain a measure of well-being for individuals, we adjust

the income and consumption resources of a consumer unit by

an equivalence scale, and use the consumer unit size

(multiplied by the unit’s sample weight) as a weight. Adjusting

resources in this manner yields “equivalent resources per

person,” and provides us with a population of individuals

whose resources are given by the equivalent resources of

their consumer unit.19 We use the single-parameter, constant

elasticity equivalence scales reviewed by Buhmann and

others 20 and Ruggles,21 which are used most often in international comparisons of inequality.22 This particular scale is

given by the square root of family size and indicates that the

resources for a two-person family must be 41 percent more

than that of a single-person family for the two families to have

an equivalent standard of living. In general, the constant

elasticity scales are given by (family size)e, in which e is the

scale elasticity. Notice that if the elasticity equals one, then

the scale equals family size; there are no assumed economies

of scale in living arrangements and the equivalent resources

are simply the per capita resources. Alternatively, if the

elasticity equals zero, then there is no adjustment for family

size, there are complete economies of scale in living and the

marginal cost of another person is zero. Our chosen elasticity

of 0.5 lies halfway between these two implausible extremes

and results in “equivalent” consumer unit resources.

Trends and sensitivities in the measurements

Mean equivalent disposable income increased 35 percent in

real terms between 1981 and 2001, while consumption

increased 17 percent (table 2). During this period, inequality

has increased in the United States, regardless of whether

income or consumption is measured or whether Current

Population Survey or Consumer Expenditure Survey data are

used. The inequality of equivalent income based on CE data

increased 16 percent, while the inequality of equivalent

consumption increased 9 percent (table 3). The level of

equivalent consumption inequality is about 70 percent of the

level of disposable income inequality; the percentage increase

in equivalent consumption inequality is 55 percent of the

increase in inequality of disposable income.

Both the time period selected and the business cycle appear

to be important for trends of income and consumption levels and

their distribution. Most of the increases in inequality occurred

between 1981 and 1990, whereas the trend during the 1990s

indicated a much smaller increase in income inequality and a

decrease in consumption inequality. Johnson and Shipp showed

that income and consumption-expenditure inequality respond

similarly to these business cycles 23; during the 1980s, neither

measure appears to fall with growth, however, in the 1990s, both

measures appear to be more procyclical.

The measurement of inequality is, of course, sensitive to

the resource measured, data source, and unit of analysis. Table

3 includes consumption expenditure measures of the previous

table plus inequality estimates using Current Population

Survey data from 1981 to 2001. The levels of measured

inequality among the two different data sources are quite

different, but the trends are similar. Inequality in all measures

increased between 1981 and 1990. The income measure

increases more modestly between 1990 and 2001, while the

Mean resources and components of consumption by household, selected years

 [In current dollars]

Component 1981 1990 1994 2001

Income ........................................................................ $20,409 $36,471 $38,498 $48,085

Taxes (net of transfers) ................................................. 3,322 5,468 5,968 5,875

Disposable income ........................................................ 17,157 31,117 32,679 42,157

Total consumption ......................................................... 15,135 24,801 27,368 32,479

Consumption-expenditures ........................................... 13,958 23,759 25,921 29,975

Shelter:

Expenditure measure ............................................ 2,308 4,494 5,121 6,621

Consumption measure .......................................... 3,895 6,444 7,502 10,166

 Vehicles:

Expenditure measure ............................................ 1,178 2,586 2,868 3,457

Consumption measure .......................................... 769 1,678 1,935 2,417

 Medical care expenditures ....................................... 731 1,485 1,736 1,812

SOURCE: Authors’ calculations from the Consumer Expenditure microdata.

Table 1.
14 Monthly Labor Review April 2005

Economic Inequality

consumption measures decrease slightly over this period.

Both CPSand CE data yield similar trends in inequality of

income for households over the entire period. The increases

in the inequality of after-tax income and in the inequality of

before-tax income are similar in both data sources. This

suggests that although taxes may affect the level of

inequality, they do not change the rate of increase in

inequality based on these data.24 However, the noticeable

differences in the distribution of resources begin to emerge

when the inequality trends are disaggregated by household

type.

 Trends by households and age cohorts

The average levels of real income and consumption by

household type provide a useful comparison of the prisms of

income and consumption. Six quarters of CE data are combined

to provide reliable estimates of disposable income and

consumption for eight different household types (as listed in

table 4). To examine the distribution of income and consumption

for age cohorts, we use the age of each member of the household,

and weight by the household unit size. We assume that each

family member shares equally in the distribution of resources

within the household. Hence, the equivalent resource for the

household is used as a measure for each member’s well-being.

In general, consumption is lower than disposable income for

most households as predicted by the permanent income

hypotheses and empirically verified by many researchers. But

two household types stand out. Single elderly and single mothers

have the lowest level of adjusted income and consumption of

any households examined. (See tables 5 and 6.) They are also

the only two family types that have higher consumption than

income in all years. But those are the only characteristics

these two disadvantaged households share. The single elderly

had the largest percentage improvements of any of the other

family types in the 1981–2001 period. Single mothers began and

ended this period with the lowest average levels of both

consumption and income. Between 1981 and 1994, single mothers

saw their average real equivalent income and consumption

increase only slightly (8 percent for average real income and 4

Mean real equivalent resources, selected years

 [Adjusted to 2001 dollars using CPI-U-RS]

Year Income1 Disposable income2 Consumption4

1981 ......................................................................... $24,171 $20,327 $16,536 $17,859

1986 ......................................................................... 26,496 22,919 18,435 18,064

1990 ......................................................................... 30,338 25,901 19,818 20,538

1994 ......................................................................... 29,188 24739 19,635 20,557

1999 ......................................................................... 30,088 24,914 19,345 20,879

2001 ......................................................................... 31,255 27,440 19,454 20,861

Percent change: 1981–2001 ........................................... 29.3 35.0 17.6 16.8

Table 2.

Consumption

expenditures3

NOTES: The mean real equivalent resources are obtained by using

square root equivalence scale. See text for more information.

Also, see text and appendix for information on definitions of each term.

1 Equivalent to pretax/postcash transfer money income as used in the

Current Population Survey.

2

 Income post direct tax, including the Earned Income Tax Credit (EITC),

 plus the value of food stamps.

3

 The total spending for current compensation.

4

 Consumption, which is closer to a measure of real "consumption."

 SOURCE: Authors’ calculations from the Consumer Expenditure

microdata.

Table 3.

Percentage

change

1981–2001

Sensitivity of inequality measurement using different resource definitions, units of analysis, and inequality

measures, selected years

Resource measure 1981 1986 1990 1994 1999 2001

Gini coefficient:

Official census figures

Household income .............................................. .406 .425 .428 .456 .458 .466 14.8

Household income after taxes and

Transfers (definition 14) ................................... .358 .409 .386 .400 .408 .412 15.1

Family income .................................................... .369 .392 .396 .426 .428 .435 17.9

 Consumer Expenditure data:

Equivalent disposable income .............................. .342 .394 .403 .396 .406 .400 16.3

Equivalent consumption-expenditures ................... .273 .316 .314 .313 .305 .307 12.0

Equivalent consumption ....................................... .256 .283 .293 .294 .281 .280 8.9

Equivalent nondurable expenditures ...................... .254 .283 .286 .287 .275 .274 7.5

SOURCE: Authors’ calculations from Census, and Consumer Expenditure microdata.
Monthly Labor Review April 2005 15

percent for consumption); however, between 1994 and 2001, their

real resources increased substantially (18 percent rise in

consumption and a 20-percent increase in income), albeit from a

low base. This foreshadows a more detailed analysis of relative

resource inequality by age groups in the following sections.

To get a better understanding of the dispersion of income and

consumption within the United States, we focus on the three

major age groups—children, adults, and the elderly.25 The subsequent analysis compares the distribution of the three major

age groups relative to the distribution of the total population.

We examine how adults, the elderly and children have fared

relative to the total population by looking at the quintile distribution of each group relative to quintiles for the total population.

A comparison of one group with the total population is a zerosum game. If one group does better than the general population,

then another must do worse. If age and household type does not

influence the household’s relative economic position, then we

would expect that 20 percent of each age group or family type

would reside in each quintile. If, however, certain age groups

have fewer resources than others, they will be overrepresented

in the bottom quintile and underrepresented at the top.

For each age group, the quintile break points are the same as

those for the entire population. Because overall inequality has

increased since 1981, the quintile break points are farther apart in

2001 than in 1981.26 With increasing inequality over time, a change

indicating more dispersion within an age group (for example,

more children living in households at the bottom and top

quintiles) suggests that there has been a greater increase in

inequality within the group. But the reverse is not necessarily

true. Because overall inequality has increased, a change in the

quintile composition of one group, indicating less dispersion,

does not necessarily mean that inequality within that group has

fallen.27

Adults. This is the largest age group in the population; they

are also the largest group in the labor force and the largest

consumer group. In terms of disposable income and consumption, adults are relatively better off than the general

population. Historically, income and consumption provide a

similar picture of the well-being of adults.28 Therefore, they are

overrepresented in the higher quintiles and underrepresented in

the lower quintiles (chart 1). However, by 2001, the relative income

advantage of adults remains, while they have lost some of their

relative advantage as measured by consumption. The

distribution of adults without children present in the

household, however, indicates that these childless adults are

faring much better than other adults. (See chart 2.) For

instance, chart 2 shows that 30 percent of childless adults are

in the top quintile for both income and consumption, but again,

the fraction in the top quintile declines over the 20-year period.

Elders. The relative position of the elderly, compared with the

general population is the reverse of the childless adults. The

elderly are overrepresented in the lowest disposable income

quintiles (especially in the second quintile), and underrepresented

in the top quintiles, as would be expected because many are

retired. But when we switch to consumption, they are underrepresented in the lowest quintiles and modestly overrepresented in the upper quintiles. As can be seen in chart 3, their

relative distribution of consumption has improved much more

than has their relative distribution of disposable income since

1981. The increase in elderly home ownership, along with the

increase in value of home ownership, is most likely the largest

contributor to the relative improvement in consumption relative

to income; in 2001, 82 percent of elderly persons lived in an

owned home, up from 76 percent in 1981.29 They also may be able

to smooth their consumption in ways not available to families

with children or younger adults, such as spending from

accumulated assets. This suggests that accumulated wealth

(financial, as well as housing wealth) may be an important

determinant of elderly consumption.

The relative consumption of the elderly by household type

provides another perspective on their well-being. Married elder

couples—more likely to be the “younger” elderly—have a

Distribution of persons in family types for selected years

1981 1990 1994 1999 2001

Single nonelderly ........................................................... 5.1 5.2 6.1 7.2 7.1

Single elderly ................................................................ 3.0 3.1 3.6 3.6 4.1

Nonelderly couples ........................................................ 16.6 19.1 17.8 16.8 16.5

Elderly couples ............................................................. 7.2 8.4 7.5 7.9 6.6

Married couples with children .......................................... 51.3 44.7 43.6 43.6 43.0

Single-mother families .................................................... 6.4 5.9 7.3 5.9 6.0

Other families with children ............................................. 4.7 7.1 7.0 8.0 8.4

Other families ............................................................... 5.6 6.5 7.1 7.1 8.5

Table 4.

Distribution of persons

Family type
16 Monthly Labor Review April 2005

Economic Inequality

relative consumption distribution which has improved even more

than for the elderly in general. (See chart 4.) By 2001, they are

now underrepresented in the bottom two consumption quintiles

relative to the general population and the elderly in general and

overrepresented in the three top quintiles. The relative consumption distribution of married elder couples is now similar to

that of the adult distribution.

Relative distributions for both disposable income and consumption for single elderly women have also improved since

1981 (chart 5). This group used to be overrepresented in the

bottom of both income and consumption distribution. With

respect to relative income, single elderly women are still overrepresented at the bottom, but not by as much as those are in

1981. Their consumption distribution relative to the general

population is almost equal in 2001 and much better than is their

income distribution.

Although both the elderly married couples and elderly single

women have improved their relative income and consumption

distribution since 1981, it is the consumption status of the single

older women that has improved most dramatically. Much of this

added consumption takes the form of medical spending and

housing, both of which are likely to improve their overall wellbeing.30 Both national and cross-national analyses of income

poverty suggest that single elderly women are among the poorest

in society. 31 However, if we look at consumption levels for this

group, and if we treat medical consumption in the same vein as all

other consumption, this is no longer the case. If we are to form a

more complete picture of the well-being of the elderly, especially

older women, we need to examine both income and consumption.

We also need to consider health status and medical care spending

and their effect on well-being.

In general, consumption is lower than disposable income

Means of real equivalent disposable income and consumption by household type, selected years

[In 2001 dollars using CPI-U-RS]

1981 1990 1994

Income Income Income Income Income

Single nonelderly ................................ 19,226 21,105 23,179 27,848 21,387 24,824 22,201 27,992 15.5 32.6

Single elderly ..................................... 13,700 11,173 18,078 17,376 19,257 16,867 20,781 17,063 51.7 52.7

Nonelderly couples ............................. 23,384 28,888 26,741 37,290 27,388 36,496 26,279 39,286 12.4 36.0

Elderly couples .................................. 18,819 19,627 22,671 24,052 24,502 24,098 23,224 23,442 23.4 19.4

All couples with children ...................... 17,323 20,164 19,739 25,909 19,834 24,957 20,576 28,751 18.8 42.6

Single mother families ......................... 11,396 10,274 11,892 11,967 11,841 11,131 13,969 13,376 22.6 30.2

Other families with children .................. 13,512 12,755 13,662 14,665 13,076 14,199 14,493 17,490 7.3 37.1

Other families .................................... 17,181 19,401 19,430 22,135 19,992 22,901 19,997 25,110 16.4 29.4

SOURCE: Authors’ calculations from the Consumer Expenditure microdata. See appendix for definition of consumption.

Table 5.

Family type

Percent

change

1981–2001

2001

ConsumptionConsumptionConsumptionConsumptionConsumption

Means of real equivalent consumption expenditures and consumption less shelter, vehicles, and medical care

by household type, selected years

[In 2001 dollars using CPI-U-RS]

1981 1990 1994

Single nonelderly ................................ 18,601 12,130 22,339 13,632 21,051 12,357 20,759 12,098 11.6 –0.3

Single elderly ..................................... 10,664 6,977 14,522 8,861 15,262 8,894 15,208 8,841 42.6 26.7

Nonelderly couples ............................. 21,243 15,083 25,683 16,710 25,866 16,237 24,232 14,673 14.1 –-2.7

Elderly couples .................................. 15,380 10,690 19,268 12,317 20,513 12,579 18,642 11,174 21.2 4.5

All couples with children ...................... 16,460 11,698 19,857 12,638 19,669 12,461 19,959 12,148 21.3 3.8

Single-mother families ......................... 10,906 7,661 11,810 7,865 11,749 7,709 13,635 8,520 25.0 11.2

Other families with children .................. 12,726 9,282 12,912 8,898 12,958 8,615 13,949 8,863 9.6 –4.5

Other families .................................... 15,687 10,822 18,308 11,852 18,557 12,013 18,716 11,332 19.3 4.7

Table 6.

Family type

Percent

change

1981–2001

2001

Consumption

expenditure

Consumption

expenditure

Consumption

expenditure

Consumption

expenditure

Consumption

expenditure

Less

shelter,

vehicle

and

medical

care

Less

shelter,

vehicle

and

medical

care

Less

shelter,

vehicle

and

medical

care

Less

shelter,

vehicle

and

medical

care

Less

shelter,

vehicle

and

medical

care

NOTE: Consumption less shelter, vehicles, and medical care is equal to

consumption-expenditures less shelter, vehicles, and medical care. See

appendix for definition of consumption.

SOURCE: Authors’ calculations from the Consumer Expenditure

microdata.
Monthly Labor Review April 2005 17

Chart 1. Distribution of all adults (ages 18–64) relative to the general population by quintile,

using equivalent disposable income and consumption

Disposable income Consumption

Percent Percent

1981 1986 1990 1994 1999 2001 1981 1986 1990 1994 1999 2001

0

5

10

15

20

25

30

35

40

0

5

10

15

20

25

30

35

40

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5

Chart 2. Distribution of adults without children present relative to the general population by quintile,

using equivalent disposable income

Disposable income Consumption

Percent Percent

1981 1986 1990 1994 1999 2001 1981 1986 1990 1994 1999 2001

0

5

10

15

20

25

30

35

40

0

5

10

15

20

25

30

35

40

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
18 Monthly Labor Review April 2005

Economic Inequality

for most households as predicted by the permanent income

hypothesis and found by many researchers. This is true for every

kind of family type except for the single mothers and single

elderly. (See table 5.) The substantial increase in both consumption and income for the single elderly occurred largely

between 1981 and 1990 and was spread across the entire elderly

consumption distribution. Increases in both income and

consumption for these households continued in the 1990s, but

at more modest rates.

The measure of consumption in table 5 includes the value of

the flow of services and durables such as housing, vehicles and

medical care. If consumption is defined as only the actual

expenditure of money (consumption expenditure in table 6) then

the percentage increase in consumption is still the highest for

the single elderly families, but it is reduced from 51.7 percent to

42.6 percent. That is still a substantial increase, and again, most

of it occurred between 1981 and 1990.

The increases in consumption (defined both as consumption

with service flows and actual expenditures of money) between

1981 and 2001 were substantial for all households. But table 6

suggests that most of those increases are accounted for by the

service flows and actual expenditures for three items: shelter,

vehicles, and medical care. If these three items are left out of the

calculation of consumption expenditures, then the increase over

20 years for most family types varies from –5 percent to 5 percent.

The only exceptions, again, are the single elderly families and

single-mother families who enjoyed larger consumption increases

even when expenditures do not include shelter, vehicles and

medical care.

Children. Once again, we emphasize that the distributions

we have created are zero-sum games. If one group improves

its relative distribution over time, it is at the expense of another

one. In this case, the improvements in the relative advantages

adults have in their distribution of income, and the relative

advantage the elderly have in consumption, has been at the

expense of the third group, the children (chart 6). Not only is

the distribution of income and consumption for the general

population becoming more unequal since 1980 as shown in

table 3, but the relative distribution of children’s consumption

is becoming even more unequal, as compared with the overall

population. Children’s overrepresentation in the bottom

income quintile in 2001 is about the same as that in 1981 (and the

other quintiles remained similar as well). But with respect to

consumption, their overrepresentation at the bottom has grown

(especially between 1981 and 1994), with some improvement from

Chart 3. Distribution of elderly using equivalent disposable income and consumption

Disposable income Consumption

Percent Percent

1981 1986 1990 1994 1999 2001 1981 1986 1990 1994 1999 2001

0

5

10

15

20

25

30

35

0

5

10

15

20

25

30

35

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Monthly Labor Review April 2005 19

Chart 4. Distribution of elderly married couples relative to the general population, using equivalent

disposable income and consumption

Disposable income Consumption

Percent Percent

1981 1986 1990 1994 1999 2001 1981 1986 1990 1994 1999 2001

0

5

10

15

20

25

30

35

40

0

5

10

15

20

25

30

35

40

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5

Chart 5. Distribution of single elderly women relative to the general population, using equivalent

disposable income and consumption

Disposable income Consumption

Percent Percent

1981 1986 1990 1994 1999 2001 1981 1986 1990 1994 1999 2001

0

10

20

30

40

50

60

0

10

20

30

40

50

60

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
20 Monthly Labor Review April 2005

Economic Inequality

1994 to 2001, while the share of children in the top quintile has

grown (albeit more modestly). The fact that children are

overrepresented in the bottom quintiles and under-represented

in the top quintiles comes as no surprise. Other researchers have

similar findings.32 But the relative consumption changes we

documented here are unprecedented. Unlike any other group in

the general population, the relative deterioration of children’s

consumption distribution is larger than is the change in their

income distribution over this 20-year period.33

When we disaggregate the relative distribution of consumption by type of family with children, it is clear why their

consumption has deteriorated (chart 7). It is not attributed to

children living in married two-parent families, because their

situation has remained relatively unchanged (except for some

growth in the top quintile share) since 1981. The deterioration in

the distribution has occurred mainly to different levels of

consumption for children in single-mother households (which

have not changed very much) and children in “other”

(nonmarried couple) families, and because of the increasing

number of children in these “other” families. As chart 7 shows,

the relative well-being of children in single-mother families

deteriorated between 1981 and 1994, while the relative well-being

of children in other families improved slightly. For both groups,

the distribution improved in the latter part of the 1990s. In

addition, table 4 shows that the percent of persons living in

these families increased during the 1981–2001 period, even

though the percent of persons living in single-mother families

has declined since 1994. 34 The share of married couples with

children, who had modestly improving consumption

distributions since 1981, decreased from 51 percent to 43 percent

of all family types. Both the share and the unequal consumption

distribution of single-mother families living alone did not change

much during this period. However, “other families with children”

almost doubled from 4.7 percent to 8.4 percent. And the

consumption distribution worsened for this family type as well.

Defining consumption as consumption-expenditures

(ignoring the service flows) reduces the relative inequality

among children. Unlike the single-elderly family type, however, the relative distribution of consumption expenditures

minus the expenditures on housing vehicles, and health care

does not make a major difference. The value of housing flows,

vehicles, and medical care are less important to the relative

consumption distribution of households with children than

for those of the elderly. No matter how consumption is defined,

the relative consumption distribution of households with

children is worse than any other group in the country.

Chart 6. Distribution of children (under age 18) relative to the general population, using equivalent

disposable income and consumption

Disposable income Consumption

Percent Percent

1981 1986 1990 1994 1999 2001 1981 1986 1990 1994 1999 2001

0

5

10

15

20

25

30

35

0

5

10

15

20

25

30

35

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Monthly Labor Review April 2005 21

Discussion

Children are more likely to live in households with adults who are

younger than the general adult population and are not yet in

their highest income years. Over the life cycle, these households

should improve their income and consumption positions. And,

in fact, children in single-mother households have absolute levels

of consumption shown in tables 5 and 6 that are higher than

income in both 1981 and 2001, even if both are at relatively low

levels in each period.

If relative consumption inequality is deteriorating for families

with children, but the mobility of children among consumption

quintiles is high, then children may be relatively consumptionpoor for only a short period. Unfortunately, estimates of the

mobility of children among consumption quintiles do not provide

much support for such a hypothesis. Like the rest of the

population, mobility is least at the first and the top quintiles for

both income and consumption. And mobility among the other

quintiles is modest. Therefore, mobility patterns cannot

ameliorate the deteriorating relative consumption of households

with children. 35

Because of the life-cycle pattern of both income and

consumption, children may not necessarily be worse off for their

entire lifetime. The trends over the 1981–2001 period, however,

suggest that successive cohorts of children are moving down

the relative consumption distribution of the general population.

Although the average well-being of children had begun to

improve slightly in the later 1990s, chart 6 suggests that we are

finding increases in the relative numbers of children in both the

bottom and top quintiles, suggesting that this increase may be

being unequally shared.

The distribution of home ownership is also contributing to the

relative consumption positions of the old and the young.

Housing has a large adjustment for the service flows, and a higher

percentage of the elderly own their own homes than do families

with children, especially single-parent families. In fact, consumption-expenditures for shelter, vehicles, and medical needs

increased as a share of all consumption expenditure between

1981 and 2001 for every family type shown in table 5. In 1981, the

share was 29 percent for couples with children and 35 percent for

single elderly and nonelderly. By 2001, the share had increased

to 39 percent for couples with children and 42 percent for single

elderly and nonelderly. This suggests that the increasing

consumption share of these three items may help explain the

consumption patterns and trends described in this article.

Chart 7. Distribution of children (under age 18) by family type relative to the general population, using

equivalent consumption

Percent

Living in

married couple families

Living in other

non-married families

Living in single-mother families

Percent

1981 86 90 94 99 2001 1981 86 90 94 99 2001 1981 86 90 94 99 2001

0

10

20

30

40

50

60

70

0

10

20

30

40

50

60

70

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
22 Monthly Labor Review April 2005

Economic Inequality

INCOME AND CONSUMPTION are clearly different prisms with

which to view well-being. In many cases, it does make a

difference which prism is used. The prism of income makes

adults look relatively more advantaged than the general

population. The prism of consumption makes the elderly

appear more advantaged than the general population. Therefore, the selection of a measure of well-being may have real

consequences for how government policies are evaluated,

especially for the elderly.

Most surprising, however, is that households with children

are at a disadvantage, relative to the general population through

both prisms. And households with children are the only group

whose distribution of consumption was relatively more unequal

than their distribution of disposable income throughout the

1981–2001 period studied. Comparison with the general

population is a zero-sum game where households with children

are relatively less well off, regardless of whether disposable

income or consumption is used as the resource measure.

Notes

1

 A. Greenspan, “Job Insecurity and Technology,” in J.C. Fuhrer and

J. Sneddon Little, eds., Technology and Growth: Conference Series

No. 40 (Federal Reserve Bank of Boston, 1996).

2

 D. Johnson, and T. M. Smeeding, “Measuring the Trends in

Inequality of Individuals and Families: Income and Consumption,”

manuscript (Bureau of Labor Statistics, 1998).

3 F. Modigliani, and R. Brumberg, “Utility analysis and the

consumption function: An interpretation of cross-section data,” in K.

Kurihara, ed., Post-Keynsian Economics (New Brunswick, NJ, Rutgers

University Press, 1954).

3

 M. Friedman, A Theory of the Consumption Function (Princeton,

NJ, Princeton University Press, 1957).

4

 Johnson and Smeeding, “Measuring the Trends in Inequality of

Individuals and Families, 1998; D. Cutler and L. Katz “Macroeconomic Performance and the Disadvantaged,” Brookings Papers on

Economic Activity 2 (The Brookings Institution, Washington, DC,

1991); and Supplemental Measures of Material Well-Being:

Expenditures, Consumption, and Poverty, 1998 and 2001, Series P–

23, no. 201 (U.S. Census Bureau, September 2003).

5

 L. Karoly, “The Trend in Inequality Among Families, Individuals,

and Workers in the United States: A Twenty Five Year Perspective,” in

S. Danziger and P. Gottschalk, eds., Uneven Tides Rising Inequality in

America ( New York, Russell Sage Foundation,1993); and P. Gottschalk

and S. Danziger, “Income Mobility and Exits from Poverty of

American Children,” in B. Bradbury, S. P. Jenkins, and J. Micklewright,

eds., The Dynamics of Child Poverty in Industrialised Countries

(Cambridge, MA, Cambridge University Press, 2001).

6

 Canberra Group, Expert Group on Household Income Statistics,

Final Report and Recommendations (Ottawa, United Nations, 2001).

7

 D. Fullerton and D. L. Rogers, Who Bears the Lifetime Tax Burden?

(Washington, DC, The Brookings Institution, 1993); and A. Deaton

and C. Paxson, “Intertemporal Choice and Inequality,” Journal of

Political Economy, 1994, vol. 102, no. 3, pp. 437–67.

8

 P. Gottschalk, and R. Moffitt, “The Growth of Earnings Instability

in the U.S. Labor Market,” Brookings Papers on Economic Activity,

1994, vol. 2, pp. 217–72.

9

 D. Slesnick, “Consumption, Needs and Inequality,” International

Economic Review, 1994, vol. 35, no. 3; Cutler and Katz, “Macroeconomic

Performance and the Disadvantaged,” 1991; Supplemental Measures of

Material Well-Being: Expenditures, Consumption, and Poverty, 1998 and

2001, Series P-23 no. 201 (U.S. Census Bureau, September 2003); J.

Sabelhaus and U. Schneider, “Measuring the Distribution of Well-Being:

Why Income and Consumption Give Different Answers?” Applied

Economics Quarterly (Konjunkturpolitik), vol. 2 (Berlin, Dunker and

Humbolt, 1997); D. Jorgenson, “Did We Lose the War on Poverty?”

Journal of Economic Perspectives 1998, vol. 12, no.1, pp. 79–96;

and D. Johnson and S. Shipp, “Trends in Inequality in the United

States Using Consumption Expenditures: The U.S. from 1960–1993,”

Review of Income and Wealth, 1997, vol. 43, no. 2.

10 See Supplemental Measures of Material Well-Being (U.S. Bureau

of the Census, 2003).

11 V. K. Barooah and P.McGregor, “Is Low Spending or Low Income

a Better Indicator of Whether or Not a Household is Poor: Some Results

From the 1985 Family Expenditure Survey,” Journal of Social Policy,

1992 vol. 21, no. 1, pp. 53–69.

12 C. Citro and R. Michael, eds., Measuring Poverty: A New

Approach (Washington, DC, National Academy Press, 1995).

13 Johnson and Smeeding, “Measuring the Trends in Inequality of

Individuals and Families, 1998.

14 On the other hand, because the survey is designed to measure

consumption, expenditures, and not income, the income data in

consumption surveys may be of lower quality than the expenditure

data. We, therefore, compare our CE income data to CPS income data

(table 3).

15 Consumer Expenditure Survey Anthology, Report 967 (Bureau of

Labor Statistics, September 2003).

16 A consumer unit comprises members of a household who are

related or share at least 2 out of 3 major expenditures—housing, food,

and other living expenses. A person living alone is a single consumer

unit. This article uses the terms consumer unit and households

interchangeably. However, they are not always identical. A few

households consist of more than one consumer unit; therefore, there

are approximately 3 percent more consumer units than households.

17 S. Danziger, and M. Taussig, “The Income Unit and the Anatomy

of Income Distribution.” Review of Income and Wealth, 1979, vol. 25,

no. 4, pp. 365–75.

18 This adjustment assumes that resources within the household are

distributed equally.

19 B. Buhmann, L. Rainwater, G. Schmauss, and T. M. Smeeding,

“Equivalence Scales, Well-being, Inequality, and Poverty: Sensitivity

Estimates across Ten Countries Using the Luxembourg Income Study

Database,” Review of Income and Wealth, 1998, vol. 34, pp. 115–42.

20 P. Ruggles, Drawing the Line (Washington, DC, The Urban Institute

Press, 1990).

21 A. Atkinson, L. Rainwater, and T. M. Smeeding “Income

Distribution in OECD Countries: Evidence from the Luxembourg Income

Study (LIS),” Social Policy Studies vol. 18 (Paris, Organisation for

Economic Co-operation and Development (OECD), October 1995).
Monthly Labor Review April 2005 23

APPENDIX: Constructing total consumption

To get an adequate sample size for each year, we use the four quarters

of data for each year plus data from the last quarter from the year

before and the first quarter for the year after. For 1994, this means

we use data from the fourth quarter of 1993 to the first quarter of

1995. This allows us to have more than 5,000 observations for each

year (1981, 1986, 1990, 1994, 1999, and 2001).

The consumption measure includes the amount that the consumer

unit actually spends for current consumption plus the estimated

service flows from home ownership and vehicles. This includes

expenditures for food, housing, transportation, apparel, medical

care, entertainment, and miscellaneous items for the consumer unit.

Excluded are expenditures for pensions and Social Security, savings,

life insurance, principal payments on mortgages, and gifts (of cash,

goods and services) to organizations or persons outside the consumer

unit.

Housing includes expenses associated with owning or renting a

home or apartment, including rental payments, mortgage interest

and charges, property taxes, maintenance, repairs, insurance, and

utilities. Expenditures for other lodging and household operations

are in the miscellaneous items category. Expenditures for principal

payments for mortgages are excluded.

Transportation includes expenditures for the net purchase price

of vehicles, finance charges, maintenance and repairs, insurance,

rental, leases, licenses, gasoline and motor oil, and public

transportation. Public transportation includes fares for mass transit,

buses, airlines, taxis, school buses and boats.

Medical care expenditures are for out-of-pocket expenses

including payments for medical care insurance.

Entertainment expenditures are for fees and admissions, televisions,

radios, sound equipment, pets, toys, playground equipment, and other

entertainment supplies, equipment and services.

Miscellaneous expenditures are for personal care services, reading,

education, tobacco products and smoking supplies, alcoholic

beverages, other lodging, and house furnishings and equipment.

To obtain our measure of consumption, we estimate the service

flows of home ownership, and cars and trucks. For the value of home

ownership, we use the reported rental equivalence value obtained from

the consumer unit. Consumer units who own their home are asked, “If

someone were to rent your home today, how much do you think it

would rent for monthly, unfurnished and without utilities.” The

annualized value of this is then used for home ownership cost in place

of the amount used in the definition of consumption-expenditures.

To estimate the service flows for cars and trucks, we follow a process

similar to that used in the studies of Danziger and others and Slesnick,

estimating the service flow of durable goods by the change in the value

of the durable.1 Using the purchase price, P0, and the age, s, of the

vehicle, the service flow, S, is given by:

St = (r + d) · (1 - d)s · P0,

where r = the interest rate

d = the depreciation rate

and we assume that r = .05 and d = .1

22 D. Johnson and S. Shipp, “Inequality and the Business Cycle: A

Consumption Viewpoint,” Empirical Economics, vol. 24, issue 1,

1999.

23 This is similar to results in Edward Gramlich, Richard Kasten,and

Frank Sammartino, The American Economic Review, Papers and

Proceedings of the Hundred and First Annual Meeting of the American

Economic Association (May, 1989), vol. 79, no. 2 (1993) pp. 315–

19; and D. Krueger, and F. Perri, “Does Income Inequality Lead to

Consumption Inequality? Evidence and Theory,” NBER working paper

no. 9202 (National Bureau of Economic Research, 2002).

24 Adults include all nonelderly persons, those who were never

parents, were once parents (but children have grown and left the house),

and are parents (with children in residence).

25 D. Johnson, and S. Shipp, “Trends in Inequality in the United

States Using Consumption Expenditures,” 1997.

26 The equivalence scale used has a substantial effect on the relative

distributions of children and the elderly within each year. However,

the relationship between these two groups in 2001 and over time is

not affected by the choice of scale.

27 S. Danziger, J. van der Gaag, E. Smolensky, and M. Taussig,

“Income Transfers and the Economic Status of the Elderly,” IRP

Discussion Paper 695–82 (University of Wisconsin, 1982).

28 Calculated using the CE data sample in this article.

29 On the net benefits of health spending, see T. M. Smeeding, and

D. Freund, “The Future Costs of Health Care in an Aging Society: Is

the Glass Half Full or Half Empty,” unpublished manuscript (Center

for Policy Research, Syracuse University, February 2002). The percent

of older single women living in an owned home also increased

dramatically during these 20 years, from 55 percent in 1981 to 73

percent in 2001.

30 T. M. Smeeding, “Income Maintenance in Old Age: Current Status

and Future Prospects for Rich Countries,” Genus LIX, vol. 1, AprilJune 2003, pp. 51–83.

31 L. Rainwater and T. M. Smeeding, Poor Kids in a Rich Country:

America’s Children in Comparative Perspective (New York, Russell

Sage Foundation, 2004).

32 These distributions only demonstrate the relative position of

children with respect to the overall population. They cannot be used

to suggest that consumption inequality for children is higher than that

using income. In fact, using the Gini coefficient for children, the Gini

for income is still higher than the Gini using consumption. Still, chart

7 suggests that the fraction of children in both the bottom and the top

quintiles of consumption are increasing over this period.

33 Children living with their mother and another adult are included in

the “other families with children” category. In 1981, 12.7 percent of

children lived in single-mother families and 7.6 percent lived in other

families. In 2001, the percent of children living in single-mother

families remained at 13 percent, while 14.5 percent lived in other

families.

34 J. Fisher and D. Johnson, “Consumption Mobility in the United

States: Evidence from Two Panel Data Sets,” Paper presented at the

Conference on “Economic Mobility in America and Other Advanced

Countries” (Jerome Levy Economics Institute of Bard College, October

2002); and Gottschalk and Danziger, “Income Mobility and Exits

from Poverty of American Children,” 2001.
24 Monthly Labor Review April 2005

Economic Inequality

The CE Survey collects data on the ownership of vehicles, including

the age and model type, which is classified into 800 categories.

Although the age and model type are asked of all consumer units,

the purchase price is asked only of those households who are

currently financing their automobile (or who recently purchased the

vehicle). Because many of the consumer units have missing values

for the purchase price, we imputed values based on the model type

and year, whether the vehicle was purchased new or used and

whether the vehicle had automatic transmission. Also, because most

of the vehicles had their model type reported, we sorted the data by

model type and whether the vehicle was new or used and obtained

the mean value of the purchase price for each cell. If there were no

observations for a particular cell or the type was missing, we then

used the mean values by year, based on whether the vehicle was new

or used, a car or a truck, and automatic or manual transmission. If

one of these values was missing, we simply used the mean purchase

price for the particular Primary Sampling Unit.

Income and consumption were adjusted to 2001 dollars using the

CPI-U-RS series for the four expenditure quarters for each consumer

unit. 2

Notes to the Appendix

1

 S. Danziger, J. van der Gaag, E. Smolensky, and M. Taussig, “Income

Transfers and the Economic Status of the Elderly,” IRP Discussion Paper

695–82 (University of Wisconsin, 1982).

2

 See Kenneth J. Stewart and Stephen B. Reed, “CPI research series

using current methods, 1978–98,” Monthly Labor Review, June 1999,

pp. 29–38; and updates at: http://www.bls.gov/cpi/cpiurstx.htm.