TRENDS IN INEQUALITY USING CONSUMER EXPENDITURES: 1960 TO 1993

David Johnson and Stephanie Shipp

Bureau of Labor Statistics, Washington DC 20212

I. Introduction

Although inequality of income has historically been

the predominant measure of well-being, recently there has

been a movement to expand consideration of well-being to

include the distribution of consumption (Slesnick (1993),

Cutler and Katz (1991)). In this paper, we examine

inequality over time using consumption-expenditure data

from the U.S. Consumer Expenditure (CE) Survey.

Changes in the demographic characteristics of families are

examined to determine their effect on the inequality of

consumer expenditures.

Using data from the CE Survey, various measures of

inequality indices are examined for five time periods:

1960-61, 1972-73, 1980-81, 1989-90, and 1992-93. Our

indices indicate that inequality for individuals was fairly

constant between 1960-61 and 1972-73, rose between

1972-73 and 1980-81, widened considerably between

1980-81 and 1989-90, and fell during the early 1990’s.

The mean log deviation inequality measure is then

decomposed by demographic characteristics (family type

and education). The main finding of this decomposition is

that most of the inequality is due to within-group rather

than between-group inequality and that within-group

inequality increased over the 30 year period.

This paper is organized as follows. The next section

describes the issues involved in measuring inequality.

Section three outlines the methodology used and section

four describes the CE Survey and definitions used in this

study. Section five presents the results and the last section

concludes.

II. Measuring inequality: what are the issues?

In measuring inequality in a society, there are

several issues to be addressed: what resource is to be

measured, for which time period, and whose resources.

The first issue concerns whether we measure the

inequality of income, income-potential, consumption or

some other measure of well-being. The second issue is

which time period should we use to measure resources.

Finally, should measures of inequality be for households,

families or individuals.

The first issue concerns whether we measure the

inequality of income, income-potential, consumption or

some other measure of well-being. Income before taxes

as a measure of well-being is criticized for several reasons

(see Joint Committee on Taxation (1993)). Income after

taxes might be a more appropriate measure; however, a

tax system changes an individual’s level of work and

savings (Burtless (1987)). Income received through inkind transfers are not included in income and even if they

were, imputing a value for some transfers, such as

Medicaid, is difficult (Moffitt (1992)). Income underreporting is a common problem in household surveys and

is compounded by the growth of income earned in the

underground economy and means-tested transfers.

Income is also more likely to be subject to transitory

fluctuations. The life-cycle hypothesis suggests that

people smooth their consumption over their lifetime so

that even if income varies significantly over the life-cycle,

consumption would be less variable from year to year than

income. Poterba (1989) shows that household income

measured over long horizons is less variable than annual

household income. If households base their spending

plans on their expected lifetime income, then consumption

provides a more accurate picture of lifetime resources than

does annual income. Thus, consumption is less subject to

transitory variations and better reflects material well-being

in terms of past, current, and expected future income.

In this paper, household well-being is measured

using consumption-expenditures, which represent the

expenditures by households on consumer goods and

services. We believe that consumption-expenditures may

be a better indicator of well-being and permanent income

than is annual income before taxes. While consumptionexpenditures can approximate consumption, the data do

not measure the flow of services from ownership of a

home and durable goods. To obtain a better measure of

consumption, some researchers have adjusted the data to

reflect the flow of services from these goods (Cutler and

Katz (1991) and Slesnick (1993)).

The second issue is which period to use in

measuring inequality. Most research examines the

inequality of annual income (see Karoly (1993)).

Problems with this approach were discussed above.

Obtaining an estimate of life-time income may also be

difficult. In terms of consumption-expenditures, these will

also be more volatile, the shorter the period used. For

example Garner (1993) shows that expenditures are more

volatile on a quarterly basis and thus will show more

inequality. Recent studies use panel data to obtain

estimates of average income over longer periods (see

Jenkins and Cowell (1993) and Slemrod (1993)).

The final issue is whether we should measure the

inequality of households, families or individuals.

Inequality measures for individuals in the U.S. are

examined by adjusting the consumption-expenditures of a

household by an equivalence scale and multiplying by

household size. Thus the inequality measures for

individuals take into account economies of scale when

there is more than one person in a household. For

example, if two families have the same level of

consumption-expenditures but one family is twice the size

of the other, individuals in the smaller family have access

to a higher level of spending. The equivalence scale used

is the one implicit in the poverty thresholds for average

family size (age and composition of the family is not taken

into account). 1 These scales indicate that for a two-person

 

1

 See Census (1991), Table A-3.
2

family to have the same standard of living as one person,

their consumption only has to be 28 percent higher. This

adjustment is made so that the impact of family spending

on the well-being of individuals can be examined.

III. Methods and assumptions

In order to gauge the level of income inequality and

its changes over time, it is necessary to have an

appropriate yardstick. In this paper, we use four summary

measures of inequality -- the Gini coefficient and three

Generalized Entropy measures. The Generalized Entropy

inequality measures are half the square of the coefficient

of variation, the Theil entropy coefficient, and the Theil

mean logarithmic deviation (see Coulter et al., (1992)).

The weighting schemes and implicit welfare

functions vary across measures. For example, the mean

log deviation is more sensitive to changes at the lower end

of the distribution while the coefficient of variation is

responsive to changes in the upper end. The Gini is

sensitive to changes in inequality around the median.

Consequently, these measures of inequality may not rank

two distributions the same way nor will time series

patterns necessarily be the same for different measures

(Karoly 1992). By computing a variety of measures of

inequality, even if the level and the percentage changes

differ, if all indices are increasing or decreasing, one can

draw conclusions about changes in inequality.

The mean logarithmic deviation has the property of

decomposability. Decomposition is a desirable property

because it facilitates an exploration of the factors behind

the levels of inequality and the changes in such levels. To

illustrate this property, let’s suppose we divide the

equivalent consumption-expenditure distribution into

mutually exclusive groups that encompass the entire

population, say, singles, individuals in married couple

families, and other families. For each of these groups, it is

possible to calculate: 1) a mean level of consumption

expenditures 2) a measure of inequality for the group; and

3) the proportion of the population in each of the groups.

An inequality measure is said to be decomposable if the

measure of inequality for the entire population can be

calculated using these three components and has the

property that an increase in inequality in one group raises

overall inequality. As an example of the last property, if

the inequality of consumption-expenditures among those

in married-couple families changes and everything else

regarding the three components stays the same, then

overall inequality must have increased when measured by

a decomposable inequality measure.

Often times, it is convenient to use these three

components to decompose the level of inequality into two

parts. A “between” part, calculated using the mean

consumption-expenditures and each group’s share in the

population, gives a sense of how much average individuals

in each of the groups differ from each other. A “within”

part is a weighted sum of the inequality within each of

each groups, which suggests how much individuals within

a particular group differ from each other. One useful

aspect of decomposing inequality into “between” and

“within” parts is that such calculations allow the source of

inequality to be pinpointed. If the “between” share of

overall inequality is rather large, then this indicates that

the average consumption-expenditures for each of the

family types are quite different, while the dispersion

within each family type is fairly small. A large “within”

share indicates the opposite.

In addition to being useful for examining levels of

inequality, the ability to decompose is also useful for

assessing changes over time. Using appropriate

techniques, it is possible to divide changes in the total

level of inequality into components that reflect changes in

the differences “between” groups and components that

reflect changes in the differences “within” groups.

Differences “between” groups can change if the

shares of each population group change and average

consumption expenditures for each of these groups become

closer or further apart. Changes in the differences

“within” groups can result from changes in the shares of

each population group and consumption expenditures

within each group becoming more disperse.

IV. The Consumer Expenditure Survey

Expenditure and demographic information are

collected by the Census Bureau, under contract for the

Bureau of Labor Statistics. The CE Survey has been

collected on a continuous basis since 1980. Prior to 1980,

CE data were collected at approximately 10 year intervals

beginning in 1901. Data used in this paper are from the

1960-61 survey and forward. The 1960-61 survey

collected expenditures using annual recall--an interviewer

visited a consumer unit2

 and reconstructed the relevant

year's expenditures. Expenditures and income were

reconciled using a balancing criteria. The 1972-73

Interview survey collected data, on a quarterly basis, using

two separate annual samples--one for each year. Although

data were collected on quarterly basis for 1972-73, they

were totaled to obtain annual values and only consumer

units who completed all 4 interviews, or for whom

expenditures could be reconstructed for a missed period,

were included in the final estimates.

The Interview surveys conducted since 1980 are

similar to the 1972-73 survey, except that a rotating

sample design is used. Consumer units are interviewed

once each quarter for five consecutive quarters. Twenty

percent of the respondents complete their fifth interview

as another twenty percent begin. The first interview is a

bounding interview to reduce telescoping so the data are

not used in estimation.

While comparisons across time periods are possible,

the differences in methodology may have differential

effects on the results. The 1960-61 and 1972-73 data are

presented annually whereas the 1980-1993 continuing CE

surveys are quarterly. Because of the rotating panel

design of continuing surveys, a consumer unit may be in

the sample from one to five times over the 1980-81, 1989-

90, or 1992-93 period depending on the quarter in which

 

2

 A consumer unit comprises members of a household who are related

or share at least two out of three major expenditures--housing, food,

and other living expenses.
3

their first interview begins and/or depending on the

response of each consumer unit. If a consumer unit misses

an Interview, no attempt is made to reconstruct the

expenditure data for that quarter. To obtain annual

expenditures for these consumer units, families are

selected if they participated in the survey for at least two

of the last four interviews. Their expenditures are

aggregated over the quarters they participated and then

annualized. Including consumer units who participated in

the survey for at least two interviews is more comparable

to 1960-61 and 1972-73 while still representing the

population distribution. The demographics used for the

annualized sample are for the last quarter the consumer

unit was interviewed--even if they changed throughout the

year.

Consumption-expenditures are defined as the

expenditures that a family makes for current consumption-

-that is, what the family actually spends for themselves.

Consumption-expenditures3

 include expenditures for food,

housing, transportation, apparel, medical care,

entertainment, and miscellaneous expenditures for the

consumer unit. Excluded are expenditures for life

insurance, pensions (including social security), principal

payments on mortgages, and gifts for people outside the

consumer unit. Consumption-expenditures are not a

measure of consumption in the economic sense because no

attempt is made to measure the flows of services provided

by durable goods. The CE survey records what families

spend for consumption, not what they actually consume.

As discussed in section II, expenditures are adjusted for

family size, which yields a measure of equivalent

expenditures per individual in a consumer unit. This

adjustment is made so that the effect of family spending on

the well being of individuals can be examined. The

adjustment also moderates the level of inequality by taking

into account the decline in household size.

V. Results and Analysis

It is well documented that incomes, and hence

consumption, grew at a brisk pace after World War II.

During the 1950s and 1960s income rose by one-third.

Since the early 1970s, the growth in income and

consumption slowed considerably and has become

negative since the late 1980s. These changes, however,

are dissimilar for different family types and education

levels (see table 1). Married couples and the welleducated have fared well during the 1980s while single

parents and those with a high school degree or less have

seen a decline in real income and consumption.

 

3

 In general, 1992-93 definitions were used to define variables over

the five time periods. The one exception to this was the inclusion of

boats, bikes, and trailers in transportation rather than entertainment.

This was done because the 1960-61 transportation variable could not

be redefined to exclude these items.

Table 1.

Average Equivalent ConsumptionExpenditures by Characteristics

(In constant 1993 dollars-adjusted using CPI-U-X1)

1980-81 1989-90 1992-93

Family Type

Single 13717 15709 14981

Married Couple 18326 21661 20357

Married with

children

14933 17365 16667

Single Parent 10806 11274 10994

Other 13099 13911 13144

Education

Less than High

School

11002 11161 10747

High School

Graduate

14619 14646 14019

Some College 15898 18148 17072

College Graduate 20503 24055 22427

Family Type Percentage change

Single 1989-93 1980-93 1992-93

Married Couple 14.52 -4.64 9.21

Married with

children

18.20 -6.02 11.08

Single Parent 16.29 -4.02 11.61

Other 4.33 -2.49 1.74

6.20 -5.51 0.34

Education

Less than High

School

1.44 -3.70 -2.31

High School

Graduate

0.18 -4.28 -4.11

Some College 14.15 -5.93 7.38

College Graduate 17.31 -6.77 9.37

Real consumption expenditures have fallen for all

groups for the 1989-93 period which may help to explain

the leveling off of the inequality indices seen below.

The inequality measures for individuals indicate that

inequality was roughly constant between 1960-61 and

1972-73, rose slightly between 1972-73 and 1980-81,

widened considerably during the 1980s and leveled off

during the early 1990s (see chart 1).

The slight decrease in the early 1990s may reflect

reductions in spending due to changes in savings and

pension contributions. Contributions to savings and

pensions are not included in the consumption-expenditure

definition. The fall in consumption-expenditure inequality

is not always a socially desirable outcome since it could be

that families are less well-off overall. This seems to be

what is happening as the real value of consumption

expenditures fell for all groups between 1989-90 and

1992-93 (see table 1). This could account for the decline

in inequality yet mask the fact that the families within

certain demographic groups are less well-off. In other

words, although the inequality within a certain
4

demographic group, such as high school graduates, has

fallen, it may be because the real income for this group,

and hence consumption, has fallen for all families in this

group.

Table 2

Inequality measures using person weighted

equivalence consumption-expenditures

Year Gini

Coefficient

of Variation

Theil

Entropy

Mean

LogDeviation

1960-61 0.295 0.165 0.146 0.154

1972-73 0.294 0.167 0.145 0.151

1980-81 0.306 0.206 0.162 0.160

1989-90 0.336 0.247 0.193 0.190

1992-93 0.327 0.224 0.181 0.180

The main difference between our results and those

of Cutler and Katz is due to differences in how

expenditures and consumption are defined. The Cutler

and Katz expenditure definition includes more than our

definition because they include gifts, life insurance, and

contributions to retirement plans and social security. The

increase in payroll taxes during the 1980’s could account

for some of the differences in the Gini since payroll taxes

will tend to decrease inequality (Barooah and McGregor

(1990) obtain a similar result using Irish data). The Cutler

and Katz consumption definition adjusts housing and

vehicle expenditures to take into account service flows

from these goods. We do not do this. As these results

indicate, inequality measures depend on the definition of

well-being and its measurement, yet most studies seem to

agree that there is an increase in inequality in the 1980’s.

Decomposing the Mean Log Deviation Indices by

Demographic Groups

Further analysis of these changes in inequality can

be accomplished by decomposing the mean logarithmic

deviation.4

 Decomposing the inequality index allows us to

examine how much of the total inequality is contributed by

differences in consumption-expenditures within each

demographic group and how much is contributed by

differences between these groups. Tables 3 and 4 present

the decomposition results by family composition and

educational level.

Inequality decomposition by family composition.

Family composition influences the living standard a family

enjoys since both the number of people in the consumer

unit as well as the marital status contribute to the level of

economic well-being achieved by a household. Since

family composition has changed over the last 30 years,

these changes may account for some of the increase in

inequality. Families are smaller and an increasing percent

of married couples are having fewer children or no

children at all. In addition, there are more single parents

and other family types. The growing single population is

predominately in the lowest consumption group although

their share in this group has declined over time. Married

 

4 See Jenkins (1994) for a similar procedure.

couple households are predominantly into the top two

consumption groups.
5

Table 3

Decomposition by family composition using mean lLogdeviation

Family type 60-61 72-73 80-81 89-90 92-93

Single 0.206 0.225 0.249 0.208 0.189

Married without

children

0.164 0.149 0.154 0.177 0.162

Married with

children

0.137 0.120 0.118 0.156 0.151

Single parent 0.198 0.186 0.184 0.212 0.191

Other 0.157 0.175 0.180 0.184 0.174

Overall inequality

(within +

between)

0.150 +

0.004

0.143 +

0.007

0.152 +

0.008

0.175 +

0.015

0.165 +

0.015

Between group

inequality as

percent of overall

2.6 4.7 5.3 7.9 8.3

The results in table 3 shows that the within-group

inequality for married couples with children has increased

from .137 in 1960-61 to .151 in 1992-93. This

decomposition also allows us to represent the overall

inequality as the sum of within-group and between-group

inequality. In 1992-93, within-group inequality is .165

and between-group inequality is .015 such that overall

inequality is .180. The results show that most of the

overall inequality in each period is due to inequality

within each family type group--over 90 percent. Betweengroup inequality accounts for a much smaller but

increasing share of inequality--almost 3 percent in 1960-

61 and 8 percent in 1992-93. The result that variations in

consumption-expenditure within each family type group

contribute the most to inequality is consistent with other

studies (Borooah and McGregor (1990), Cowell (1984)).

Inequality decomposition by educationlevel.

Differences in the level of education have been cited as

one of the main reasons for increasing inequality during

the 1980’s. Educational attainment has continued to

increase over this 30 year period; the percentage of the

population completing some schooling beyond high school

has steadily increased. In 1992-93, 36 percent of college

graduates are in the top consumption group while 43

percent of those with less than a high school education are

in the bottom consumption group. More significantly, the

high school graduates which have increased as a share of

the population are increasingly in the bottom consumption

group.

Table 4.

Decomposition by education using mean log-deviation

Education 60-61 72-73 80-81 89-90 92-93

Less than H. S.l 0.159 0.156 0.160 0.160 0.166

H.S Graduate 0.101 0.112 0.121 0.154 0.131

Some College 0.108 0.111 0.132 0.155 0.153

College Graduate 0.109 0.106 0.128 0.141 0.142

Overall inequality

(within + between)

0.134 +

0.020

0.129 +

0.022

0.137 +

0.023

0.153 +

0.037

0.147 +

0.033

Between group

inequality as percent

of overall

13.0 14.6 14.4 19.5 18.3

While variations in consumption-expenditures

within each group account for most of the total inequality,

the inequality between education level groups is large

when compared to other demographic characteristics.

Between 1960-61 and 1989-90 within-group inequality

increased for all groups, except for those with less than a

high school education. Inequality for this group was

already high when compared to other educational groups

and the fact that inequality does not increase, as it does for

the other groups, could indicate that individuals in this

group are more equally less well off. Ryscavage et al.

(1992) also found that increases in educational attainment

contributed to increasing income inequality.

The changing structure of inequality. While the

level of inequality increased over this 30 year period, most

of the inequality in each period is due to disparities in

consumption-expenditure levels within the demographic

groups examined here. The mean logarithmic deviation

inequality index can also be decomposed across the time

periods to indicate how much of the change in inequality is

due to pure changes in inequality within each group,

changes in the composition of the population, and changes

in the relative consumption-expenditure levels between

groups.

5

The changes in inequality are decomposed for two

time periods: 1980-81 and 1989-90 and then 1989-90 to

1992-93. The results of this decomposition, given in

Table 5 confirm the findings of other studies that the

majority of the increase in inequality is due to an increase

in inequality within each of the groups.6

 Also confirming

other studies, disparities between educational levels have

had the largest effect on inequality during the past

decade.7

 Differences in education levels contributed 60

percent of the increase in inequality in consumptionexpenditures during the 1980’s. Education appears to

have helped decrease inequality during the early 1990’s.

Decomposing the index over time by family

composition also shows that most of the increase in

inequality is due to increasing disparity within each family

type. However, changes in the relative consumptionexpenditure levels between family types do account for

almost 20 percent of the increase in inequality. In

addition, changes in family composition over the twenty

years (the increase in single parents and married couples

without children) account for 15 percent of the increase in

inequality.

 

5 See Jenkins (1994).

6 See Karoly (1993), Levy and Murnane (1992), Ryscavage et. al.

(1992).

7

 See Ryscavage et al. (1992). See also references in Karoly (1993).
6

Table 5

Decomposition of percent change in overall

consumption-expenditure inequality between 1980-81

and 1989-90 using mean-log deviation

Between

80-81 and

89-90

Changes

in withingroup

inequality

Changes in

relative mean

consumption

expenditures

Changes in

population

shares

Total

percent

change

Family

type

12.2% 3.5% 2.7% 18.4%

Education 11.2% 9.1% -1.9% 18.4%

Between

1989-90

and 92-93

Family

type

-5.7% -0.4% 1.1% -5.0%

Education -3.1% -1.7% -0.2% -5.0%

VI. Conclusion

Many studies have examined inequality using

income as a measure of well being. In this paper, we

examine inequality using consumption-expenditures

instead. Consumption-expenditures may be a better proxy

for well-being. Using data from the U.S. Consumer

Expenditure Survey, we examine various measures of

inequality for five time periods between 1960-61 and

1992-93. As Levy and Murnane (1992) discuss, a study’s

conclusion should be invariant to the inequality measure

chosen. Thus, using four summary measures of inequality,

we find that inequality for individuals was fairly stable

between 1960-61 and 1972-73, rose between 1972-73 and

1980 and widened considerable during the 1980’s, and fell

during the early 1990’s.

We decomposed the mean log deviation inequality

measure by demographic characteristics (family type and

education) and found that most of the inequality is due to

within-group rather than between-group inequality and

that within-group inequality first increased during the

1970’s and then increased by an even larger amount

during the 1980’s, and fell slightly during the early

1990’s. Between-group inequality accounted for a small

share of total inequality, increasing moderately when

examined by family type. Between group inequality

increased by a larger amount when examined by

educational level of the household head.

With the availability of data from the ongoing

Consumer Expenditure Survey, future research will

involve examining the annual changes in inequality that

have occurred since 1980 to try to identify when the

change in inequality occurred and, if possible, the source

of the increase.

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