ment retirement. This reflects the higher average age of
the head of the one-earner consumer unit, in which one
spouse may be retired and the other still working. Heads
of one-earner households are, on average, 6 years older
than heads of two-earner households.

One-earner families earn two to three times more from
interest and other property income, both as a share of
income and in absolute dollar terms, than two-earner
families. This may be because one-earner families are
older and therefore more likely to have accumulated
wealth. It may also be because single-earner families may
invest and save more than dual-earner families to offset
somewhat their reliance on a single paycheck. A wife's
earnings may diminish a family’s motive to save as a
hedge against a husband’s possible job loss. In addition, if
a working wife is covered by a pension plan, which is in
part employer financed, the family’s motivation to save
for retirement may be lessened.'?

Income is 23 percent higher for two full-time earner
families when compared to one-earner families, whereas it
is only 7 percent higher for two-earner families in which
the wife works part time. Income for one-earner and two-
earner (wife works part time) families are about the same
for the two lowest income groups. If the wife works full
time, income is between 6 and 10 percent higher than the
income of one-earner families in the two lowest income
groups. In the highest income group, the one-earner fam-
ily appears to be a different type. Income is 14 percent
higher than that of families in which the wife works full
time and 9 percent higher than that of families with wives
employed part time. This can be explained by the fact
that the higher income group is open ended. One-earner
families in this income group have more self-employed
earners, and interest, dividends, and other property in-
come are also substantial.

In families in which the husband earns an income that
is considerably above average, a high proportion of the

wives do not work. The benefit of additional income from
the wife is probably relatively low. Also, if the wife does
not have the training or inclination for professional work,
it may be relatively difficult for her to find work that
befits the social status she derives from her husband. Ac-
cording to Barbara R. Bergmann, “Such families con-
stitute the last bastion of the full-time housewife.””"*

This review of the characteristics and income of these
households emphasizes that there are other variables be-
sides earner status that influence spending patterns, and
that many of these variables are related to each other.

Regression analysis

Multivariate tobit regression analysis was used to ex-
amine whether expenditure differences exist between one-
and two-earner families after controlling for differences in
demographic characteristics. The tobit statistical proce-
dure is particularly well suited to the analysis of data
when some consumer units incur no expenditures for
some items during the interview period. Weights were
used in the regression analysis, so that the results apply to
the total population.

The analysis was limited to those expenditures gener-
ally perceived to be influenced more by the earner status
of the wife than by other demographic characteristics.
Eight equations were estimated. The eight dependent
variables were expenditures'® for food away from home,
child care and babysitting, gasoline and motor oil, pur-
chase of new vehicles, purchase of used vehicles, women’s
apparel, public transportation, and shelter.

Independent variables and hypotheses. We are investi-
gating whether the working status of the wife accounts for
differences in expenditures among husband-wife families
or whether the differences are due to income, family size,
the presence of children, or some other characteristic. The
working status of the wife is the variable of interest for
this study. To isolate the effect of that variable, we are

Table 4. Percent distribution of income by source for husband-wife families’ classified by wife's employment status, 1984-86
amity income and wife's employment status
a swite families ul
Income by source Less than $20,000 $20,000 to $34,999 $35,000 and over
Not working| Partstime | Fulltime |Not working] Part-time | Full-time |Not working| Part-time | Full-time |Notworking| Part-time | Fulltime
Income betore taxes ...| 1000 | 1000 | 1000 | tooo | 1000 | 100.0 | 1000 | 1000 | 100.0 | 1000 |) 1000 | 100.0
Wages and salaries .......]_ 77.3 86.2 91.0 79.4 822 873 86.1 92.6 918 78.4 02.8 873
Self employment. 92 73 ay 47 52 42 54 34 40 97 W7 a1
Social Security, private,
and government
retirement... 74 26 16 94 59 34 50 18 18 48 20 14
Interest, dividends,
rental income, and
‘other property income ... 46 24 14 24 20 ww 26 13 12 66 26 22
Other income? 1.6 14 13 46 46 | 43 1.0 09 12 05 08 1.0
‘Data are for complete income reporters. See text footnote 10.
ZOther income includes unemployment and workers’ compensation, veterans’ benefits, public assistance, supplemental security income, food stamps, and regular
contributions for support.

19


MONTHLY LABOR REVIEW February 1989 e

one-earner and two-earner families in which the wife
works part time have the same number of children, on
average, and thus have similar space requirements and
housing needs. In addition, the average income of families
in which the wife works part time is only slightly higher
than that of one-earner households.

While the employment status of the wife is statistically
significant in explaining differences in the levels of ex-
penditures for child care, food away from home, gasoline
and motor oil, women’s apparel, and shelter, it is impor-
tant to note the relative impact of the wife’s working
status on expenditures. One way to do this is by looking at
the effect of the wife’s working status on the predicted
expenditures. After controlling for other explanatory
variables, the working status of the wife has a small, al-
though significant, impact on the predicted expenditures
for these items. For example, families of employed wives
spend an average of 17 to 18 percent more per year on
child care and about 4 percent more on women’s apparel
than families of wives who are not employed. Expendi-
tures on food away from home are between 2 and 3
percent higher if the wife works. Thus, the relative impact
on expenditures of the wife’s working appears small. This
is supported by previous studies that yielded similar re-
sults, in that significant differences are found but the
actual dollar differences are relatively small.2* What ap-
pears to be happening is that these same expenditures rise
as the income of the one-earner family rises. Therefore,
the difference in expenditures at the same income level is
not as great as might be expected.

What about the expenditure categories for which the
wife’s earner status is not significant, such as for the pur-
chase of vehicles? All husband-wife families own more than
two vehicles, on average. Purchase of new vehicles is deter-
mined by income and age while purchase of used vehicles is
determined by income, age, family size, and education. A
similar finding about other consumers’ durable goods was
made by Myra H. Strober: “ . . . although initial labor
force participation may be associated with an increase in
the durables to income ratio, after wives have been at work
for a few years, most of the substitution out of home pro-
duction is likely to be into the time-saving nondurables and
services,”?>

Public transportation is another expenditure category
for which the wife’s earner status is not significant. In the
regression equations, public transportation includes large
ticket items which are often used as vacation transporta-
tion, such as airline fares, train tickets, and ship fares, as
well as local transit. The commuter component is rela-
tively small. Therefore, it is not surprising that the wife’s
earner status is not significant. Public transportation ex-
penditures for husband-wife families are positively related
to income and age and negatively related to the presence
of children under age 12. Another indication that this is

22

Expenditures of Families of Working Wives

vacation transportation is that the regression results indi-
cate that expenditures are highest in the summer.

Summary

The results from the longitudinal analysis and regres-
sion analysis are similar although not identical. Both
analyses yield similar findings for expenditures on child
care, gasoline, and vehicles. Child care and gasoline ex-
penditures were found to be higher for the families of
working wives, while vehicle purchases and public trans-
portation expenditures were comparable for all husband-
wife families regardless of the wife’s employment status.
The low increases in shelter in the longitudinal analysis
may be explained in part by the mixed result in the regres-
sion analysis section. Two full-time earner families do
spend significantly more than one-earner families on shel-
ter, while two-earner families in which the wife works
part time spend the same amount on shelter as one-earner
families.

Expenditures for food away from home and women’s
apparel are significantly higher for all two-earner husband-
wife families when compared to one-earner husband-wife
families, according to the regression results. The longitudi-
nal analysis also shows increases in expenditures for food
away from home and women’s apparel for families in
which the wife returns to work. The only puzzling result
here is that expenditures for food away from home and
women’s apparel increased more for the “control” (one-
earner) households than for the “new earner” (two-earner)
households.

The labor force is now growing at slightly more than 1
percent a year, compared to double that rate during the
1970's and early 1980's. Labor shortages in some industries
are already beginning to appear. The Census Bureau's 1982
Current Population Survey found that 26 percent of non-
working mothers with preschoolers would look for work if
“reasonably priced child care were available.”¢ This repre-
sents a potential addition to the labor force of 1.7 million
women. Thirteen percent of employed women with pre-
schoolers (about 700,000 workers) said they would work
longer hours if additional or better child care were avail-
able. Given these attitudes toward work and tighter labor
supplies, it is likely that more employers will begin to offer
child care benefits to induce women to enter the labor
force. Hence, the number of two-earner families may be
expected to continue to grow. The ongoing Consumer Ex-
penditure Survey will allow for future examination of the
spending patterns of these families. o

———FOOTNOTES.

"The data used in this study were drawn from the Interview portion of
the 1984, 1985, and 1986 Consumer Expenditure Survey. The Interview
survey is the most comprehensive survey of demographic characteristics
of American consumer units. The Interview sample, selected on a rotat-


MONTHLY LABOR REVIEW February 1989 Expenditures of Families of Working Wives

Table 3. Demographic characteristics of husband-wife families’ classified by wife's employment status, 1984-86
ni Family income and wite's employment status
husband-wite u
Characteristic families Less than $20,000 ‘$20,000 - $34,999 ‘$35,000 and over
Nat Part. | Full wot | Pate | Full Not Pat | Fuk Not Pi Full.
working | _ time time | working | time time | working | time time | working | time time
Number of consumer
units (in thousands) 14052 | 9,951 | 18,774] 6178 | 3.414] 4,558] 4674 | 3562 7,496 | 3,200| 2975] 6,786
Income before taxes .....] $28,929 | $90,820 | $36,282 | $12,607 | sta,s82 | 14216 | sz0.014 | $20,084 | $20,069 | se4,140 | $60,430 | ss7.114
Income after taxes . $26,499 | $28,221 | $92,579 | $11,725 | $11,673 | $12,679 | $26,184 | $26,043 | $27,046 | $58,973 | $59,929 | $51,441
Size of consumer unit. 34 34 3.0 33 32 34 34 35 3.0 33 38 20
Age of reference person.| 44.5 98.3 37.9 444 38.1 366 43.8 36.8 36.6 46.5 41.0 40.1
Number in consumer unit:
EaMmers oo..eecccsesessees 1.0 20 20 10 20 20 1.0 20 20 1.0 20 20
Vehicles 22 25 25 19 22 22 24 28 28 25 28 27
Children under 18... 13 14 1.0 13 42 mT 43 15 1.0 13 14 or)
Percent reporting
Housing tenure:
Homeowner with
Mortgage... 50 60 62 33 39 98 56 66 62 72 82 78
Homeowner without
MOPGEG® ...eeecersessee 26 15 12 28 20 18 24 13 1" 20 10 ry
Renter... 24 25 26 39 4 44 20 a 27 8 8 13
Race of reference
Person:
BIQCk vosseesseeeeseesscee 5 5 8 8 9 12 3 3 8 2 3 7
White and other... 95 95 1 92 31 88 97 97 a1 98 97 93
Education of reterence
Person:
Elementary (1-8) 10 4 5 17 40 8 5 1 4 1 1 2
High school (9-12) 47 39 43 55 53 59 53 “4 48 24 a1 27
Collage... 2 43 57 52 28 a7 32 42 55 48 75 78 7
‘Data are for complete income reporters. See text footnote 10

however, we examine the characteristics of all husband-
wife families classified by the wife’s earner status.

Families in which both the husband and wife work are
a major and growing segment of American society. In
almost 70 percent of husband-wife families, the wife
works outside the home. Two-thirds of these women work
full time, while one-third work part time. (See table 3.)

There are differences in the characteristics of families in
which the wife works full time and those in which the wife
is not employed. For example, families in which both the
husband and wife work full time are younger, are more
likely to have attended college, and have fewer children.
The homeownership rate is about the same for the two
types of families, but the two full-time earner family is
only half as likely to own its home mortgage free. A
higher proportion of families with two full-time workers
are black. Also, two full-time earner families own more
vehicles than one-earner families, although both average
at least two.

Families in which the wife works part time exhibit
some of the characteristics of families in which the wife
works full time and some of the characteristics of those in
which the wife does not work outside the home. Families
in which the wife works part time are, on average, the
same age and own the same number of vehicles as two
full-time earner families. However, two-earner families in
which the wife works part time are more like one-earner

18

families in that, on average, they have about the same
number of children. This may explain, in part, why the
wife works part time, as it may not be economically feasi-
ble to pay for extra child care. She may arrange her work
schedule around the schoolday or her husband’s work
schedule, or both.

A look at the characteristics presented in table 3 shows
that approximately the same relationships hold across all
income levels. However, there are some interesting differ-
ences. Not surprisingly, the wife works full time in more
than half of the families in the highest income group,
compared to only one-third of the families in the lowest
income group. The average age of the highest income
group is higher. It is possible that the children are also
older, permitting more women to work full time.

On average, women contributed substantially to family
income. Earnings of women working part time repre-
sented about 29 percent of their families’ total income.
Women who work full time contribute 40 percent of their
families’ income."

The sources of income are somewhat different in gen-
eral between one-earner and two-earner households. (See
table 4.) Two-earner families obtain a higher share of their
income from wages and salaries and a lower share from
self-employment income than one-earner families. As one
would expect, one-earner families receive a higher share
of their income from Social Security, private, and govern-


MONTHLY LABOR REVIEW February 1989 ¢ Expenditures of Families of Working Wives

Table 5. Tobit regression coefficients
Dependent variables
Independent variable! Food away trom | Child New Used Gasoline Public Women's Shelter
home caret vehicles vehicles transportation | apparel
motor oi
Employment status of wite (not
working}

Part-time 49.00" 523.37" | -1198.57 -70.44 42.30° 4059 -36.19"° | -25.48

Fulltime 2778 785.04" 870.19 20.25 24.89" 29.40 36.23" ar
Total expenditures? 331" 1.79° 144.55" 30.38° 0.56" 3.89" 165° 11.42*
‘Age of reference person . 5.12" 46.62" ~699,29" | -408.71° mt 9.00"* 2.83" 11.16"
‘Age-squared ~0.04+ 0.53" 6.22" 3.19" -0.08" 0.06 ~0.03" ~0.23"
Age" part-time employment

SLAIUS Of Wife ss ccssessene - -8.86" _ - - - 152° -
Age" fulltime employment

StAtUS OF WIE scncsenerece - ~ 13.64" - - - - 0.34 -
Family size ss <3. -1490" | 1559.68 2r262*| 18.98 17.67 -12.48" ~21.05"*
Presence of children (age 12 or

over):

Under age 6 79.00" 822.16" - - -28.88° | -141.64" 28.40" 4787"

Ages 6-11 6.45 208.96" = = = 18.52" ~75.00" ~27.08" 32.77
Education (high schoo

Less than 12 years ~83.76" -97.08" | -1385.39 1274.58" | -16.42" 15.27 ~40.67" ~43,93

Some college.......... 50.24" 82.08° 87415 | -1574.48" 292 109.33" 27.54" 90.59°

College graduate or more. 99.03° 166.42" | -g800.40" | -246119" | -10.85° 293.42" 57.01* 445.23"
Seasons (Fall: October- Decem-

ber):

Winter (January-March) . ~ 45.35" - 11.20 | ~449.43 8.47 = 11.06 46.81° ~46.48"*

Spring (April-June) .. 8.72 = 697.57 518.29 5.94 -3.17 -7.73 ~117.68*

‘Summer (July~ September) 1237 = 992.17 | -103.24 33.57" 108.72 | 13.02%" | -a7.41"*
Region (South):

Northeast 33.32" ~ 46,82" 645.68, - ~53.09° 222.62" 18.75* 92.84

Midwest 27.93" 25.73 24.18 -34.75" 28.43 11.73 9.95

West 2 14.13 48.05 2856.01" = =11:38° 213.55° -0.09 396.26"
Urbanization (urban)

Rural cccssssee . —44,69° -36.31° 138.42 | -s12.16 22.99° -300.53" | -20.15* | -315.08"
Number of vehicles . - - 2008.12" | 1928.87+ 32.85" -76.98" - -
Housing tenure (renter):

Homeowner... ~- - - - - - - 92.94
Constant --|__-75.63"" | -2149.00" | -21401.44" | 6608.70" 4.54 1261177 | -84.11° 227.31"

"Where appropriate, characteristics of the reference group are indicated in parentheses. “Significant at the alpha =.01 level
“Child care includes day care and babysitting **Signiticant at the alpha = .05 level
Values have been multiplied by 100. Nore: Dash indicates that the variable was not used in the model.

controlling the other socioeconomic variables. These vari-
ables are listed in table 5 and are similar, although not
identical, for each of the eight models being estimated.

Where appropriate, the characteristics of the reference
group are indicated in parentheses in the table. The refer-
ence group is the group to which the comparison is made.
For instance, in table 5, the reference group is “wife not
working.” The coefficients for “Part-time” and “Full-
time” are compared to the “not working” group. By way
of example, the coefficient of 19.00 for food away from
home for wives working part time indicates that these
women’s families spend more on food away from home
than families in which the wife does not work. Unlike
ordinary least squares regression estimates, tobit regres-
sion coefficients indicate only the direction, and not the
magnitude, of the differences between groups.

The working status'® of the wife is defined as follows:
(1) the wife is not employed outside the home (the refer-

20

ence group); (2) the wife is working part time; or, (3) the
wife is working full time. Working part time is defined as
working fewer than 35 hours per week or working full
time for part of the year. Working full time is defined as
working 35 hours or more per week for at least 50 weeks,
It is hypothesized that working will be positively related
to the expenditures under study.

Consistent with classical consumption theory and the re-
sults of previous research, income is hypothesized to be
positively related to expenditures. Total expenditures are
chosen as a proxy for income for three reasons."’ First, the
permanent income hypothesis suggests that total expendi-
tures are an appropriate measure of income because, in the
short run, families have more control over expenditures
than over incomes. Second, total expenditures have been
shown to give a better fit than income in models designed to
predict expenditures in a number of expenditure catego-
ties.'* Third, in addition to the economic reasons, there are



ing panel basis, is targeted at 5,000 consumer units per quarter. Each
quarter, one-fifth of the sample is new to the survey. Consumer units
who participate in the survey are interviewed five times, once per quar-
ter; the first interview is used only for bounding purposes. Data for
interviews 2 through 5 are used for publication and analysis. Over the
1984-86 time frame, data for a consumer unit may be available from one
to four times. Each quarter is considered as a separate sample when
estimates are calculated.

*The terms “household,” “family,” and “consumer unit” are used
interchangeably throughout the text.

3Vicki Schram Fitzsimmons, “Family Money Management: How
One-Earner and Two-Earner Families Handle Money,” poster presenta-
tion at the annual meeting of the American Council on Consumer
Interests, Chicago, iL, April 1988.

‘Victor Fuchs, “Sex Differences in Economic Well-Being,” Science,
Apr. 25, 1986, pp. 459-64.

°G.S. Becker, “A Theory of the Allocation of Time,” The Economic
Journal, September 1965, pp. 493-517.

‘Robert T. Michael and Gary S. Becker “On the New Theory of
Consumer Behavior,” Swedish Journal of Economics, September 1973,
pp. 378-95.

"Don Bellante and Ann C. Foster, “Working Wives and Expenditure
on Services,” Journal of Consumer Research, September 1983, pp.
700-07.

"Elizabeth Waldman and Eva E. Jacobs, “Working Wives and Family
Expenditures,” Proceedings of the Social Statistics Section of the Ameri-
can Statistical Association, 1978.

°For the initial interview, information is collected on demographic
and family characteristics and on the inventory of major durable goods
of each consumer unit. Expenditure information is also collected in this
interview, using a 1-month recall, but is used, along with the inventory
information, solely for bounding purposes; that is, to classify the unit for
analysis and to prevent duplicate reporting of expenditures in subsequent
interviews. Data from the first interview are not used in the estimates.

‘Complete income reporters. The distinction between complete and
incomplete income reporters is based in general on whether the respon-
dent provided values for major sources of income, such as wages and
salaries, self-employment income, and Social Security income. Even
complete income reporters may not have provided a full accounting of
all income from all sources. In the current survey, across-the-board zero
income reporting was designated as invalid, and the consumer unit was
categorized as an incomplete reporter.

Data for the descriptive statistics (tables 2 and 3) are for complete
income reporters only. Data used in the regression analysis are for all
husband-wife families.

"Susan E. Shank, “Women and the labor mark
stronger,” Monthly Labor Review, March 1988, pp. 3-8.

he link grows

"Myra H. Strober, “Wives” Labor Force Behavior and Family Con-
sumption Patterns,” American Economic Review, February 1977, pp.
410-17.

"Barbara R. Bergmann, The Economic Emergence of Women (New
York, Basic Books, Inc., 1986).

“For a description of the methodology, see G.S. Maddala, Limited-
Dependent and Qualitative Variables in Econometrics (New York,
Cambridge University Press, 1983).

'SExpenditures are defined as the transaction cost, including excise
and sales taxes, of goods and services acquired during the interview
period. Expenditure estimates include expenditures for gifts, but exclude
purchases or the portion of purchases directly assignable to business
purposes. Also excluded are periodic credit or installment payments on
goods or services previously acquired. The full cost of each purchase is
recorded when the purchase is made, even though full payment may not
have been made on the date of purchase.

'6Families in which the wife works as a volunteer are not included in
this study. These families were dropped because they could introduce
conflicting results. That is, they probably make use of the same timesav-
ing techniques that employed women use but there is no additional
income.

""In addition, if a wife begins to work during the periods covered by
the third and fourth interviews, that information is collected. This was
discussed in the longitudinal part of this study. However, if the wife
stops working, that information is not recorded until the fifth interview.
Hence, a family may be misclassified for up to two quarters.

'8§. J. Prais and H. S. Houthakker, The Analysis of Family Budgets
(Cambridge, Ma, The University Press, 1971).

"Age is that of the reference person in the consumer unit. The refer-
ence person is the first member mentioned by the survey respondent
when asked to “Start with the name of the person or one of the persons
who owns or rents the home.” It is with respect to this person that the
relationship of other consumer unit members is determined. Thus, age
may refer to the husband or the wife.

*Robert A. Pollack and Terence J. Wales, “Demographic Variables,
in Demand Analysis,” Econometrica, November 1981, pp. 1533-51.

See Robert T. Michael, The Effect of Education on Efficiency in
Consumption, National Bureau of Economic Research Occasional Paper
No. 116 (New York, Columbia University, 1972).

2 The test statistic is x? = -2(log Likelihood R-log Likelihood U).
The statistic is asymptotically chi-square, distributed with the degrees of
freedom equal to the number of coefficients set equal to zero. The log
likelihood function for the restricted model, represented by R, is ob-
tained when the function is maximized with respect to the intercept only.
The log likelihood of the unrestricted model, U, is obtained when the
function is maximized with respect to all the coefficient estimates corre-
sponding to the intercept and all explanatory variables.

>The part-time earner status coefficient for women’s apparel is nega-
tive. However, when the interaction term “age* part-time employment
status of the wife” is included in the equation, the net effect is that, for
families with a reference person over age 24, households with wives
working part time spend more on apparel than those in which the wife
does not work.

**Waldman and Jacobs, “Working Wives.”
**Strober, “Wives' Labor Force Behavior.”

Martin O'Connell and David E. Bloom, “Juggling Jobs and Babies:
America’s Child Care Challenges," Population Trends and Public Policy,
Issue no. 12 (Washington, Population Reference Bureau, February
1987).



Families of working wives spending
more on services and nondurables

When a wife becomes a second earner,
husband-wife families spend more
on work-related and timesaving items

such as child care and food away from home,
according to the Consumer Expenditure Survey

Eva JAcoss, STEPHANIE SHIPP,
AND GREGORY BROWN,

During the post-World War II era, there has been a
dramatic increase in women’s labor force participation.
This has generated a great deal of public interest in the
social and economic consequences of the employment of
women. High rates of labor force participation are preva-
lent for women both with and without children. Today,
more than half of all mothers with children under age 3
work outside the home, compared with fewer than one-
fourth of such mothers in 1967. (See table 1.)

The Consumer Expenditure Survey provides data that
permit us to examine the effects of a wife’s labor force
participation on the income and expenditures of her fam-
ily. The data used in this study are from the 1984-86
Consumer Expenditure Survey.! To determine the eco-
nomic effects on the family of a wage-earning wife, two
groups of consumer units” are compared: (1) husband-wife
families in which only the husband is an earner, and (2)
husband-wife families in which both the husband and wife
(and no others) are earners. These families will be referred
to as one- and two-earner families, respectively. Families
in which the wife is the only earner are not included in this

Eva Jacobs is chief of the Division of Consumer Expenditure Surveys,
Bureau of Labor Statistics, Stephanie Shipp is chief of the Branch of
Information and Analysis in the Division, and Gregory Brown is an
economist formerly with the Division. An earlier version of this article
was presented at the annual meeting of the American Statistical
Association, August 21-25, 1988, in New Orleans.

study. In our analysis, expenditures generally perceived to
be associated with the wife working outside the home are
studied; these include expenditures on women’s apparel,
child care, purchase of vehicles, gasoline, public transpor-
tation, housing, and Social Security and pension plan
costs. We will also discuss the additional income received
from the wife’s employment.

There are two parts to this analysis. First, we com-
pare the average annual income and expenditures of
those consumer units in which the wife became em-
ployed during the period the consumer unit was in the
survey with similar consumer units in which the wife
was not employed. The economic costs and benefits
from the wife’s employment are defined in terms of the
changes in expenditures and income that result from
the change in the employment status of the wife. In the
second part, we use multivariate regression analysis to
measure the effect of the wife’s employment on con-
sumer-unit expenditures for all husband-wife units. In
this part, we examine all one-earner and two-earner
families and also make the distinction between part-
time and full-time working status of the wife. Each part
of the study will be described in turn.

The price of time

Intuitively, one would expect two-earner households to
spend their money differently than do one-earner house-

15


operational reasons for using total expenditures. Income
data are only collected during interviews 2 and 5. Income
data are collected for the previous year while expenditure
data are collected for the previous 3 months. Thus, there is
a lag between reports of income and expenditures that dis-
appears at the aggregate level but may distort results at the
micro level. Using total expenditures as proxy for income
corrects this timelag problem.

The presence of children by age group is included in the
model because it affects expenditures, particularly for
child care and food away from home. This variable is
entered as a categorical variable and is defined as (1) the
presence of children under age 6; (2) the presence of chil-
dren ages 6 to 11; or, (3) the presence of children age 12
or older (the reference group).

Age and age-squared are included in the model to mea-
sure changes in expenditure patterns over the life cycle.'®
(Recall that one-earner families are, on average, older.)
Family size is also included because it is a major determi-
nant of household consumption patterns,”° although the
direction of its effect may differ depending on the item —
expenditures probably vary negatively with family size for
food away from home, and positively for child care. It is
not clear what the effect on the other expenditure catego-
ries will be. Housing tenure is included in the shelter
model because of the inherent differences in the cost of
renting versus owning a home. Education is controlled for
because previous research indicates that education in-
creases efficiency in all nonmarket activities.?' This
greater efficiency increases a household’s real income. Ed-
ucation also is used as a variable in consumer research to
measure social status.

Regional variation in the availability of and need for
goods and services as well as regional price differences
makes it necessary to control for the region of the country
in which the consumer unit lives. The same is true for
urban and rural differences.

Results

Results of the regression analysis are displayed in table
5. To test the overall significance of the set of variables
included in each expenditure model, the likelihood ratio
test statistic was used.?* The resulting chi-square values
were statistically significant at the 0.01 level. This allowed
for the rejection of the null hypothesis that all of the
coefficients (except the intercept) are equal to zero for all
the models considered. The coefficients from the tobit
regression models were used to calculate the predicted
expenditures and to determine changes in expenditure
patterns over the life cycle.

Expenditures for households in which the wife works
full time or part time were significantly greater for most of
the items under study than for households in which the
wife is not employed, after accounting for the other differ-
ences. Families in which the wife is employed spend

significantly more on food away from home, child care,
women’s apparel,”’ and gasoline and motor oil than do
families in which the wife does not work outside the
home. If the wife works full time, her family also spends
significantly more than the one-earner family on shelter.

Child care expenditures include all expenses for nurs-
ery school, day care, babysitting, camp, and so on. Child
care expenditures are a necessity for mothers employed
outside the home. Whether the wife works part time or
full time, child care expenditures are significantly more
than for families in which the wife is not employed. How-
ever, this difference narrows as these women get older.
This makes intuitive sense because older women are more
likely to have older children, who require less outside
care. It is also confirmed by the presence-of-children vari-
able that shows families with children age 11 or younger
spending significantly more for child care than families
with children age 12 or older. Based on results from the
regression equation, child care expenditures for families
in which the wife works full time increase until age 30 and
continue at that level until about age 35, at which point
they begin to decline steadily. Child care expenditures for
families in which the wife works part time increase
through age 35, when they level out until age 40 and then
begin to decline. The wives in these families have more
children and return to work later or work part time
longer.

Households in which the wife works spend significantly
more on food away from home than the one-earner house-
hold. The working wife often buys lunch or breakfast, or
both, at work. In addition, she may be inclined to cook
dinner less often, due to lack of time. This means her
family will often eat dinner out as well.

Expenditures for vehicles, both new and used, are the
same for one- and two-earner families despite the fact that
two-earner families own more vehicles than do one-earner
families (2.5 versus 2.2 vehicles). Ownership of more vehi-
cles is one reason why gasoline and motor oil expenditures
are higher for two-earner families. In addition, the accrued
mileage that occurs from daily commuting increases gas
and motor oil consumption.

Wives who work full time spend more on clothing than
wives who are not working, although the difference closes
with increasing age. Wives who work part time spend
more on apparel than nonworking wives after age 24.

Expenditures for shelter, including both owned dwell-
ings and rental units, are significantly higher for families
in which the wife works full time. These families are
younger and have higher mortgages. Also, fewer two-
earner families own their homes without mortgage—12
percent versus 24 percent of one-earner families. Two full-
time earner families who are renters also have higher
average rental costs. If the wife works part time, shelter
costs are about the same as for families in which the wife
is not employed. This may be explained by the fact that

21


MONTHLY LABOR REVIEW February 1989 Expenditures of Families of Working Wives

holds. First, households in which both the husband and
wife work have less time available for household-related
activities such as cooking and cleaning. This increased
demand on a couple’s time raises the value of time as a
factor of production in household activities. Second, there
is an income effect by which the wife’s additional income
increases expenditures in accordance with the relevant
income elasticities. In addition, the wife’s contribution to
the family income may play an enhanced role in the deci-
sion about how to allocate income among expenditures.
One can envision a pooling of income in which individual
preferences are weighted differently when the wife works.
The relative weighting of these preferences may be altered
by the wife’s decision to work. Vicki Schram Fitzsimmons
found that there was a greater incidence of joint responsi-
bility for money management tasks in two-earner families
than in one-earner families.*

Household production time, we assume, would be a
more valuable “commodity” to two-earner families than to
one-earner families. Some studies suggest that time may be
more valuable today in the United States than in the past or
in other countries. For example, Victor Fuchs found that
women were working 20 minutes longer per day in 1983
than in 1959, if one includes working for pay, housework,
and child care.* As early as 1965, Gary S. Becker pointed
out that Americans are much more wasteful of food and
other goods than persons in poorer countries and much
more conscious of time: “The tendency to be economical
about time and lavish about goods may be no paradox, but
in part simply a reaction to a difference in relative costs.”*

The substitution of goods and services for time induced
by an increase in the cost of time would often include
substitution of more expensive goods and services. For
example, an increase in the value of a mother’s time may
induce her to enter the labor force and spend less time
cooking by using prepared foods and less time on child
care by using day care centers or babysitters. During the
busiest years of raising a family and working, the value of
time is relatively high. It is during the working—child
caring phase of the life cycle that the individual works
more and has less leisure time.® If the wife works outside
the home, she will be more inclined to pay for services
than the nonworking wife. The value of time also changes
for an individual at various states in his life and, later in
the life cycle, these changes induce substitution of rela-
tively cheaper means of household production for pur-
chased goods and services.

Don Bellante and Ann C. Foster used this theory of the
allocation of time as the primary rationale underlying
their 1983 study.’ Because working wives spend fewer
hours per week in housework, Bellante and Foster exam-
ined the influence of the wife’s employment on expendi-
tures for services. They also controlled for a variety of
demographic variables. Their results were mixed, in that
there was a positive relationship between employment and

16

Table 1. Labor force participation rates of women by age,
selected years, 1948-87
Participation rate in—
“e 1948 1967 1977 1987
Total, 16 years and over.....{ 32.7 and 48.4 56.0
16 to 19 years 420 418 51.2 53.3
20 to 24 yoars 45.3 53.3 665 73.0
25 to 94 years 33.2 419 59.7 724
95 to 44 years 36.9 48.1 558 745
45 to 54 years. 36.0 518 55.8 674

some relevant services, such as child care, but not between
employment and domestic services.

Using data from the 1972-73 Consumer Expenditure
Survey, Elizabeth Waldman and Eva E. Jacobs found that
“jt is not employment or nonemployment of the wife that
per se accounts for difference in expenditures, but rather
the interaction between earner status and the contribution
to income of the second earner.”*

Longitudinal aspects of the study

The Consumer Expenditure Survey, which has been
continuous since 1980, has a limited longitudinal aspect.
For the Interview portion of the survey, a sample of con-
sumer units is interviewed every 3 months over five
consecutive quarters, with the number of interviewed
cases expected to be about 5,000 per quarter. For reasons
of operational efficiency, the sample is rotating—one-
fifth of the consumer units are replaced by new units
every quarter. Each quarter of data is treated as statisti-
cally independent. If a survey respondent moves, the new
residents at that address become the sample unit. Movers
are not followed. About 70 percent of the consumer units
participate for all five interviews.”

The interviewer collects extensive expenditure data and
information on the characteristics of the consumer unit.
Among these are the age, income, and work experience of
all the members. Because the interview is lengthy and
time-consuming, the work and income questions are
asked only in the second and fifth interviews.

We have not heretofore explored the possibilities of
using the limited longitudinal aspect of the Consumer
Expenditure Survey. However, we have investigated the
types of questions we could attempt to answer by follow-
ing the same household over time. Because one of the
current issues being widely discussed is the prevalence of
the two-earner family, we decided to investigate what
happens to the expenditures of a consumer unit when the
wife goes to work during the survey period. For this part
of the study, we examine the income and expenditures of
husband-wife consumer units in which the wife began
working between the second and fifth interviews and con-
sumer units in which the wife was not working during
either the second or fifth interview periods. '°


We identified the first group as “‘new earner” consumer
units. The second group we called the “control” con-
sumer units. The control households, in which the wife
was not employed in either the second or fifth interview,
were selected based on characteristics such as age, family
size, family type, and income that made them similar to
the new earner group. To obtain a sample of sufficient size
for analysis, consumer units were selected from the years
1984-86. The resulting sample in each group was 175
consumer units. We first examined the changes in income
and expenditures between the second and fifth interviews
within each group, and then compared the changes be-
tween the two groups. It should be noted that, for this
study, we did not take account of the actual date on which
the wife started working. Therefore, by the fifth interview
she may have been working for as little as 1 month or as
much as 9 months.

It was hypothesized that income and those expenditures
which are commonly associated with working would be
higher in the fifth interview than in the second interview
for the new earner households. The expenditures are for
food away from home, women’s apparel, child care, vehi-
cles, gasoline, and mass transit. In addition, we looked at
housing, because the desire for homeownership is fre-
quently given as a reason for wives returning to work, and
at Social Security taxes and pension contributions, which
are directly associated with earnings.

The results as shown in table 2 are mixed. For the new
earner group, the components that met expectations are
income, with an increase of 17 percent from interview 2 to
interview 5; food away from home, with a 16-percent
increase; and child care, with a 30-percent increase. Be-
cause gasoline prices were declining during the reference
period, the 7-percent rise in that component reflects a
much larger real increase and can be included as well.
Housing and pension costs also increased, but at a lower
rate, and expenditures on women’s apparel increased only
a small amount. The result for vehicles can probably be
explained by the small number of reports for this cate-
gory, which leads to a high variance. For example, if one
or two consumer units purchase an expensive automobile
or truck in interview 2 and not in interview 5, a high
variance could result with such a small number of obser-
vations. Expenditures for mass transit are a small value,
in addition to being sparsely reported.

It is noteworthy that the average age of the wife in the
new earner group is 42, near the upper age limit of the
high labor force participation group. Considering the
large proportion of younger women employed in the total
population, it appears that a few women are leaving and
rejoining the labor force but that more are employed con-
tinuously. On the other hand, the expenditures show that
those in the younger group often require child care as
soon as they enter or reenter the employed labor force.

When comparing the new earner and control groups,
we run into unexpected anomalies. The increase for the
control group is much larger for food away from home
and women’s apparel. This may be just an aberration. For
most of the categories, the results are generally satisfac-
tory, with the new earner group showing larger changes
than the control group.

If these results reflect reality, one can rationalize the
discrepancy between the increase in income and the in-
crease in expenditures. The new earner group wives could
have entered the labor force to help pay for the earlier or
prospective purchase of a car or house or college tuition,
or to repay previously incurred debts. The improvement
in the financial position of the new earner group, going
from expenditures equalling income after taxes in inter-
view 2 to a surplus in interview 5, may be used for these
purposes. The control group, on the other hand, has a
similar surplus in both periods.

This is our first attempt at using the longitudinal char-
acter of the Consumer Expenditure Survey. We hope to
investigate the effect of other events. One approach would
be to examine the reverse of the labor force movement we
have examined here, that is, to look at consumer units in
which the reference person has retired during the con-
sumer unit’s participation in the survey. Other possi-
bilities are to compare the expenditures of consumer units
with members moving in, newly born members, or other
additions to the unit with consumer units of constant size.
However, the sample size may be statistically inadequate
for some of these investigations until we accumulate more
years of data.

Characteristics of families

Following are our findings about the differences in
expenditures between all one-earner and two-earner con-
sumer units obtained from regression analysis. First,

Table 2. Longitudinal comparison of selected
characteristics and expenditures of one- and two-earner
husband-wife families, 1984-86

New eamers Control group
Mtem Interview Per- Interview Per-
cent cent
2 5 hang 2 5 change

Income before taxes ......|$27,951 |$32,425 | 16 |$27,480 }$28,081| 2
$26,006 |$30,482| 17 |$25,297|$25,913| 3

- 420} —]| — 433|  —
3e|—| — 39] —

$26,160 |$27,912 $23,744 |$23,796| 0
937} 1,092] 17] 733] 1024] 40
456| 469] 3| 385) ‘429| 11

Income after taxes.

‘Age of wife ...
Family size

~

Total expenditures.
Food away from
Women's apparel

Child care.. 122| 158] 30] 130/ 118] -9
Vehicles. 2,423| 1,998|-42] 1,904] 1,494| ~22
Gasoline .... 1io1} 1,180; 7| 1,081] 1,066] -1
Mass transit 4 36 |~15 33 18| -46
Shelter ....... 2,693] 2,736] 6| 2284| 2963/ 3

Social Security, pen-

SIONS o.oo .eees 2,256| 2,380} 5] 2,135| 2,124) 0