that did not receive rental assistance were those
which responded negatively to the two questions.
The third group of renters, ineligible renters, was
selected for comparison with the two eligible
renter groups.

Twelve quarters of data (the first quarter of
1988 through the fourth quarter of 1990) were
used to obtain sample sizes large enough to com-
pute reliable sample statistics. The total sample
size of all renters in the CE Survey during this
time was 24,855. Those in public housing (n =
868), those not reporting any amount of assist-
ance received (n = 553), and those reporting as-
sistance other than governmental (n = 1,383)
were removed. The resulting sample sizes for the
three groups were as follows: eligible for and
receiving assistance (n = 487); eligible for, but
not receiving assistance (n = 8,290); and ineli-
gible (n = 13,274).

While the CE Survey does not explicitly ask
respondents whether or not they participate in a
Section 8 housing certificate or voucher program,
the group of income-eligible renters who receive
housing assistance is functionally the same in that
regard; that is, a portion of the rental charge to
these households is paid for by some government
housing program. For consistency, demographic
comparisons of income-eligible renters as iden-
tified in the 1989 American Housing Survey were
made with income-eligible renters as identified
in the 1988-90 CE Survey. The results indicated
that both samples were very similar with respect
to race, age, educational attainment, household
composition and size, and income level.

Selected weighted geographic, housing, and
demographic characteristics for the three renter
groups are listed in table 2. In many respects,
the demographic and geographic characteristics
of renters who receive housing assistance and
those who are eligible for, but do not receive,
assistance are similar. Almost 50 percent of both
groups live in the central city of a metropolitan
statistical area. A slightly greater percentage of
the first group (23 percent) live in rural areas,
compared with the second group (17 percent).
The average household size of renters receiving
assistance (2.6) is greater than that of renters who
are eligible for, but do not receive, assistance
(2.3). This is accounted for by the greater prob-
ability that a household that receives assistance
has children, compared with a household that is
eligible for, but does not receive, assistance. The
distribution of the age of the reference person is
similar in both groups, with the average age (ap-
proximately 43 years) being higher than that of
the reference person in ineligible households. The
proportion of eligible renters that are 65 years
and older (19 percent) is much larger than that
of ineligible renters (8 percent).

One of the most obvious differences among
the three groups is family composition. Roughly
AO percent of all renters receiving assistance are
single parents, compared with only 13 percent
of eligible renters who do not receive assistance
and only 6 percent of ineligible renters. Further-
more, a greater percentage of households receiv-
ing assistance are headed by a black reference
person (32 percent), compared with the other two
groups.

Another major demographic difference among
the groups is the occupation of the reference per-
son. Of all renters who receive housing assist-
ance, 45 percent did not work due to unemploy-
ment or other reasons, compared with only 20
percent of those who were eligible for, but did
not receive, assistance and 5 percent of ineligible
renters. This factor helps explain the major dif-
ferences in sources of income among the three
groups. Almost half of all the income of renters
receiving assistance comes from transfer pay-
ments (unemployment compensation, workers’
compensation, veterans’ payments, public assist-
ance and welfare, supplemental security income,
food stamps, and other financial assistance).
Social Security and retirement income make up
an additional 22 percent. (See chart 2.) Renters
who were eligible for, but did not receive, assist-
ance are almost twice as likely to have income

Table 2. Continued — Selected weighted sample statistics for
renters, by category of assistance, Consumer Expenditure
Survey, 1988-90'

Eligible tor assistance
Ineligible
Variable tor
Receiving Not
f receiving
assistance
Education of reference person:
Less than high school graduate....... | 49.0 28.4 159
High school graduate . . eee 49.9 51.9 57.4
College graduate or more Mw 87 28.7
Occupation of reference person:
Wage or salary eamer............. | 968 62.4 a4
Self-employed . 3 34 51
Rotifed.......0 cvs 180 149 55
Unemployed 28 19 47
Not working, other reasons* |... 42.4 184 2
Below poverty threshold:
Yes 59.4 Ere 78
No.. ae 32.7 478 826
Income not reported =... 73 178 39

* Sample size of all renters was 24,855. Those in public housing (n = 868), those not
reporting amount of assistance (n = 553), and those reporting assistance other than gov-
ernmental (n = 1,363) were removed from sample.

? Other types of consumer unit arrangements include husband and wife with others, and
unrelated individuals living together.

$ Other races include American Indian, Alaut, Eskimo, and Asian or Pacitic Islander.

* Other reasons for not working include being disabled, taking care of home or family,
going to school, and doing something else.

Monthly Labor Review May 1994 21



Rental Assistance and Spending Behavior

Table 5. Ordinary least square and TosiT regression results, assisted renters only

, Dependent variables
——e Ordinary lest square models “oer models
Food Rent? Transportation pparel Entertainment | Health care? | _Housewares*
Bot f t Bb ' B t 8 t B t B t
Intercept. vse 195 | -725 -07 | 12615 -1.44 | 2511 60 | -1920 -51 | 45531 %1629 | 9998-098
Total expenditures 13 $10.32 19 4.47 46 1241 o7 511.64 05 "9.72 13° 2621 08 5720
Renial assistance 085 234 | -008  -16 -03 -72 | -01  -89 2 6.13 «| -018 2.33 TS
Size of congumer unit 3755 207 | 1103-58 | -3806 4240 | 1417 188 31346 | -2769 “817 208-12
‘Age of reference person 270 218 | 278 220 | -254 4205 | -94 -159 | -103 -189 643 "26.35 a97  -161
Minority dummy... poe 237 | 571-14 | 5286 145 | 483 "346 | 406-24 | 212 “279 | 2290-65
Composition of consumer unit
{single parent):
CT een -20397 +320 |-19317 “204 | 3408 54 90.04 1.07 | 4624 450 aig
Husband and wie on 19082 -184 | 3107-92 | (958597 455-80 | -1951 47.68 2 Ht
Husband and wife with children nas -52 | 3945 63 | 12935 211 0846-152 | 16947 6.99 4129072
Other consumer units 9780-179 | 4066 73 | 520996 9 199 | 770 326 | 3797-73
Season (fourth quarter:
First quarier an 80.06 4.06
Second quarter. -20 3052187
Third quater 87 26533
Region (west):
Northeast seer 126 | -a187 ~62 3233 | 1320-27
Midwest .. 92.03 -189 | 81.95 -1.86 151.96 °7.00 1B 1.27
South 10424 +220 |-10043 +208 177.87 591 7074187
‘Urban locaton (rural):
Centar city. 25255 *4.86 114.98 422
Subutb 14001 276 10300 +220
Building type (high fsa)
Single family, detached goat 1.93 1-3
Town house ........ 402982 a 90
Garden apartment ........ 8126 1.26 733?
Garage, atic, or basement 9056 1.46 602 Bt
OMME eee ecsscceeeees BR -32 1780-16
‘Age-of-housing-unit dummy tee : :
‘Number of bedrooms. 197968 vies 1584-87
‘Number of vehicles .. : | 29877 51:55 “938 $284
‘Value of food stamps... 08 5439 ee
amar composition (none):
One . bee 4841-94
Two or more. -H62  -53
Adjusted A-square® A “4 AD 19 ATs 14. 10
Festal? Ps) 20 440 80 62 2 7

+ Omitted (control) group for categorical variables in parentheses.
? Rent includes rent and utlities paid by consumer unit.

3 Health care includes health insurance, medical services, drugs, medical supplies, and personal care products and services.

* Housewares include household operations, housekeeping supplies, and household furnishings and equipment.

5 Parameter estimate is significantly different trom zero at the 95-percent confidence interval.

© For rosrr models, this statistic is the log likelihood ratio index and is equal to [1 — (log likelihood full model/log likelihood restricted model)].
7 For rosrr models, this statistic is a pseudo chi-square, equal to [2 x (log likelihood full modet/og likelihood restricted model)).

toward food and rent, compared with the former
group. The elasticities for apparel and house-
wares were not significantly different between
the twa groups. Renters who received assistance
had higher elasticities than renters who did not
only for transportation and health and personal care.

To isolate the influence of rental assistance on
spending behavior, a second set of similar re-
gressions was run, this time using only the sample
of renters receiving housing assistance. Instead
of regressing the interaction term Y,S, and the
rental assistance dummy, the models involved
in these regressions used the income proxy vari-
able and a variable representing the dollar value
of rental assistance. That way, the significance

26 Monthly Labor Review May 1994

of the rental assistance amount after controlling
for variation in income could be measured. The
results of these further regressions are listed in
table 5. The parameter estimate for the rental as-
sistance variable proved to be significantly dif-
ferent from zero in only the food and health care
models. Results from both sets of regressions
were used to estimate income elasticities and “sub-
sidy” elasticities for the seven expenditure catego-
ties tested and are presented in table 6. The elas-
ticities are point elasticities evaluated at the mean.

“Subsidy” elasticities were calculated using
the parameter estimate of the rental assistance
variable from the second set of regressions. These
elasticities measure the marginal effect of a larger



from wages and salary, compared with renters
who received housing assistance.

Average annual income and average total quar-
terly expenditures are listed in table 3 for all three
renter groups. On average, both eligible groups
spend less than one-half of the amount spent by
ineligible renters. By far, the largest portion—
42 percent—of the total budget of renters who
were eligible for, but did not receive, assistance
is allocated to rent and utilities. Food is the sec-
ond largest budget item of this group, account-
ing for roughly 25 percent of total expenditures.
The distribution of expenditures is manifestly
different for renters receiving assistance, whose
average subsidy is $918 per quarter (or $306 per
month). The portion of total expenditures allo-
cated to rent and utilities by this group (30 per-
cent) is significantly less than that of renters who
were eligible for, but did not receive, assistance
and approaches the share of ineligible renters (28
percent). With the exception of transportation
(and, of course, rent and utilities), the budget
share of all of the expenditure categories is
slightly higher for renters receving housing as-
sistance, compared with renters who were eli-
gibie for, but did not receive, assistance.

Ta the 1989 American Housing Survey, the
median monthly rent of renters participating in
certificate and voucher programs was $185, com-
pared with $334 for renters who were eligible
for, but did not receive, assistance. In the Con-
sunier Expenditure Survey described above, the
monthly averages of these two groups were $221
and $337, respectively. Thus, the findings of the
two surveys are quite similar.

Regression models and results

To control for demographic differences between
those receiving rental assistance and those who
were eligible for, but did not receive, assistance,
ordinary least squares and TOBIT regression mod-
els were used to measure the influence of the
rencal subsidy on various expenditures. The first
set uf regressions was run for the sample of all
eligible renters, to isolate any differences in
spending behavior due to potentially varying in-
come elasticites between those households which
did, and those which did not, receive assistance.
Seven separate regressions were run, in turn, on
the following dependent variables: food, rent and
utilities, household furnishings and operations,
transportation, apparel, entertainment, and health
and personal care.'? All expenditure categories
were defined as the total quarterly out-of-pocket
expenses of each consumer unit for each item.
To control for variations in income, an income
variable had to be included as an independent
variable in the models. As mentioned earlier,

Table 3. Weighted income and expenditure statistics for renters,
by category of assistance, Consumer Expenditure
Survey, 1988-90"

Eligible for assistance
Ineligible
Variable for
Not
Receiving
receiving
assistance | Svistance
Mean quarterly rental assistance $918.49 $0.00 $0.00
Mean annual income before taxes 7,723.82 | 9,646.48 | 25,987.15
Wages and salary:
Mean 2,418 6,506 21,198
Percent reporting. cee 39.0 56.7 82.7
Percent of total income ......... 31.3 67.4 83.2
Self-employment and farm income:
Mean : : wee 74.11 214.67 1,825.81
Percent reporting... =... : 1.6 35 ot
Percent of total income . .. 1.0 22 52
Social Security and retirement income:
Mean 1,689.98 | 1,503.02 4,111.32
Percent reporting................ 29.6 227 12.0
Percent of total income 219 156 44
Assistance income:*
Mean .. fees 3,485.18 | 1,242.24 683.28
Percent reporting 71.3 33.3 18.6
Percent of total income .......... 45.1 12.9 27
Dividend and interest income:
Mean ..... 12.66 144.73 418.22
Percent reporting... sss... 76 13.3 29.7
Percent of total income... 2 15 16
Other types of income:
Mean . 43.73 39.68 730.52
Percent reporting... 44 17 29
Percent of total income 6 4 3
Total quarterly expenditures®.......... 2,246.07 | 2,401.06 5,827.43
Food:
Mean beens 658.35 604.56 1,023.78
Percent reporting.............- 99.2 99.4 99.9
Budget share 2... 29.3 25.2 176
Alcohol and tobacco:
Mean ... vce neces 80.84 88.64 173.16
Percent reporting.......... 56.1 56.6 76.7
Budget share... ee 3.6 a7 3.0
Rent and uti
Mean . 663.54 | 1,012.19 1,630.49
Percent reporting 99.6 99.3 99.9
Budget share . cece ee eee 29.5 42.2 28.0
Household operations and furnishings
Mean ..... . 112.74 60.54 323.88
Percent reporting... 0... 68.0 54.8 80.6
Budget share... : 5.0 25 56
Apparel and services:
Mean .... ve ceetee eee 152.44 113.86 359.54
Percent reporting... : 90.8 83.5 95.2
Budget share 68 47 62
Transportation:
Mean . 232.03 272.16 1,180.29
Percent reporting............... 77.8 83.8 98.3
Budget share 10.3 11.3 20.3

See footnotes at end of table.

Monthly Labor Review May 1994 23



Rental Assistance and Spending Behavior

Chart 2. Sources of income, by category of rental assistance, 1989

Recelving assistance

Wages and salary
Social security and retirement (31 percent)

(22 percent)

Other income
(2 percent)

Assistance income
(45 percent)

Eligible for, but not
receiving, assistance

Wages and salary
(67 percent)

Other income
| ~t— (4 percent)

Assistance income
(13 percent)
Social security and retirement

(16 percent) WT

Ineligible

Wages and salary
(83 percent)

Other income
(10 percent)

Assistance income
<< (3 percent)

AN Social security and retirement
(4 percent)

22 Monthly Labor Review May 1994


Table 4. Ordinary least square and Tost regression results, all eligible renters
: Dependent variables
oe Ordinary lest square models Toe models
Food Rent? Transportation Apparel Entertainment | Healthcare’ | Housewares*
6 ot 6 ' Bot 8 t B t B t 8 t

Intercept. 3232 1.68 | -266 009 | -21402+1028 | -3551 +357 tor 010. | -25157 “1684 | 11972 36.18
Total expenditures : 20 748.45 38 °7353 45 34.88 o7 33.18 6 °29.15 08 "26.27 08 23.89
Total expenditure dummy . ~056 609 | -159 *13.59 05 %495 | ~006 -1.25 | -01 42.24 029 4.92 05-63
‘Assisiance dummy ye166 6.27 | 4749 145 | -2957 120 | 6668 “465 | 7396 5.95 | 4076 *211 | 11524 5.09
Size of consumer unit vow | 5255 1593 | 609 -149 | -2473 750 | 948 '5.45 68 ‘461 | -1939 4825 “B17 2.86
‘Ago of reference person ............. 23 1:96 | 395 “1849 | -299 511.99 | -157 *16.78 89 2081 380 26.47 =92 4.98
Minority dummy 707-37 | 6458 897 317 at | 1231 308 | 25.86 659 | -1527 +264 | -2243 4346
‘Composition of consumer unit

{single parent)

Single... cesses | 62.46 446 | 0925 607 | 60a ‘496 | 370 58 | 1903 219 | 3882 448 | 61.96 2498
Husband and wile only 39 03 |-11888 +622 | $358 "332 | 4576 *543 | 1190 -148 | B461 "762 ) 8157 “3.82
Husband an wie with children a o7-| ta80 594) 1017 77 | 4877 +750 | 337 ~54 | $774 6.90 49-48
(Other consumer units. : 2047-173 | 4628 *394 | 2873 ‘221 | -3732 +800 | 340 -57 | 2903 "318 | S012 +500
Season (fourth quarter:

First quarter 26.91 3.12 1692 196 | 1219 254 | 31.93

Second quarter A516 -178 2317 59 | -1938 *408 | -326

Third quarter 535-60 649-69 | 12.12 +245 | -144
Region (west):

Northeast .. oso 663 | -928 -76 | -2074 +2139 | 2056 ‘410 | 2709 +526 | 286 -43 | 2118 *245
Midwest 43.79 5.11 | 9639 786 | 441 ‘5.02 | 903° 157 | -do4e 565 | 4367 *7.01 50 9397
South 1760 “200 | 216 +735 | 4675 %508 ] 982 1.70 | -2018 +559 | 3833 "595 2874 3.65
Urban location (rural:

Center city 1281 1.92 | 71.36 ‘553 3123 4.36

‘Suburb 19.56 -1.92 8054 6.10 17.27 $2.31
Building type (high rise}

Single family, detached 128388 31.99 2.42
Town house 3455 1.90 “909 =72
Garden apartment ......... 5404 °3.03 4798
Garage, atic, or basement 2240 71.32 886-74
Other vescenees 1531-87 “MoT 214
‘Age-ol-housing-unit dummy ... 14754 1.18 9.30 %-2.82
‘Number of bedrooms. 1287 *-2.82 . . 938 2.84
Number of vehicles fee fe 14255 3496 setae
Value of food stamps 03 6.82 tee
Eamer composition (none)

One 7548 °807 4-56

Two or more. 8077 %681 3582-87
Adjusted Pesquare® a. 52 oe oo oo a2 8
FstalsticTM 408 437 18 Mo Dove 56 8
Omitted (control) group for categorical variables in parentheses.

2 Rent includes rent and utilities paid by consumer unit

3 Health care includes health insurance, medical services, drugs, medical supplies, and personal care products and services.

+ Housewares include household operations, housekeeping supplies, and household furnishings and equipment.

5 Parameter estimate is significantly different from zero at the 95-percent confidence interval.

® For toair models, this statistic is the log likelihood ratio index and is equal to [1 — (og likelihood full modeV/iog likelihood restrictad model)]

7 For roerr models, this statistic is a pseudo chi-square, equal to (2 x (log likelihood full modeV/iog likelihood restricted model)}.

models. This indicates that renters who received
assistance and renters who were eligible for, but
did not receive, assistance had significantly dif-
ferent income elasticities for food, rent, trans-
portation, entertainment, and health care. Such
a result is not surprising, because income elas-
ticities usually vary along the income distribu-
tion, and the former group of renters is more
likely to have less income than the latter group.
Furthermore, the rental assistance dummy was sig-
nificant in the food, apparel, entertainment, health
care, and housewares models, indicating that the
levels of expenditure for these items were also sig-
nificantly different for the two groups of renters.

Allitems had a positive estimated income elas-
ticity, indicating that they were “normal” (spend-
ing increases as income increases) goods for eli-
gible renters. The income elasticities for food and
for rent and utilities were less than 1.0, indicat-
ing that these items were necessities for eligible
renters; those items with elasticities greater than
1.0 would be considered luxuries. For renters
who did not receive assistance, the elasticities
for food and rent were higher, indicating that
these items were less of a necessity for this group
than for the former. Hence, given an increase in
income, renters who did not receive assistance
would be more likely to allocate more money

Monthly Labor Review

May 1994 25



Robert Cage

Robert Cage is an
economist in the Division
of Consumer Expenditure
Surveys, Bureau of Labor
Statistics.

How does rental assistance
influence spending behavior?

Rental assistance results in more of a housing effect
than a welfare effect; that is, those receiving assistance
seek higher valued housing and keep the share of income
spent on rent constant, rather than reduce their rent
burdens and allocate money to other expenditures

ith the passage of the 1937 Housing
W Act and subsequent amendments, the
Federal Government of the United
States established as a goal that all citizens have
“safe, sanitary, and affordable housing.”' Recent
increases in rental prices and renter cost burdens
for shelter, a leveling of homeownership rates, and
an increased awareness of the plight of the home-
less have challenged the reality of this Federal hous-
ing policy. For example, the cost of shelter as a
percent of income increased from 23 percent in
1970 to about 30 percent in 1991 for renters.
Early government intervention in housing
markets came in the form of public housing
projects. Then, the 1980’s saw increased inter-
est and experimentation with various other forms
of market intervention, such as housing vouch-
ers and rental certificates. To measure the rami-
fications of rental assistance as a market inter-
vention strategy, this article analyzes the spend-
ing behavior of households receiving such
assistance. On the basis of data collected from
the 1988-90 Consumer Expenditure Surveys,
households that received rental assistance from
Federal, State, or local government agencies were
identified and compared with those households that
were eligible to receive assistance, but did not, and
with households that were ineligible for assistance.
The article is divided into three parts. First, a
brief background and review of government in-
tervention in housing markets is presented, and

the Department of Housing and Urban Develop-
ment's housing certificate and voucher programs
are outlined. Sociodemographic characteristics
of the aforementioned three groups are then com-
pared and contrasted, and differences among
them in renter cost burdens and distribution of
total expenditures are identified. Finally, ordi-
nary least square and TOBIT regression models
that were run to calculate income elasticities and
“subsidy” elasticities for various expenditure
categories are presented.

Market intervention and assistance

Historically, it has been the general housing
policy of the Federal Government to let the
laissez-faire, free-market system meet the de-
mand for housing across all levels of income.
Even after the passage of the 1937 Housing Act,
the extent of involvement by the Federal Gov-
ernment in low-income housing markets was lim-
ited to the provision of public housing and the
replacement of substandard and blighted hous-
ing structures. During the Carter administration,
most development of new public housing
projects began to be phased out and various other
experimental assistance programs phased in.
Among the latter forms of assistance were hous-
ing certificates and vouchers, low-income hous-
ing tax credits, community development block
grants, and below-market interest rate programs.

Monthly Labor Review May 1994 17



Rental Assistance and Spending Behavior

of their income on shelter. The “subsidy” elas-
ticity for rent and utilities tumed out not to be
significantly different from zero, indicating that
the value of the rental subsidy had little influ-
ence on rent expenditures among recipients.
Rental assistance proved to have a significant
influence only on food and health care expendi-
tures, even after controlling for differences in

Footnotes

income and demographics. Correlations among
food stamp subsidies, medicaid coverage, and
rental assistance that were unaccounted for in the
regression models may have contributed to this
result. In any event, the result does suggest that
any budget substitutions that may be made be-
cause of the rental subsidy would most likely be
in the direction of increased food spending. |

' Dolores Hayden, Redesigning the American Dream: The
Future of Housing, Work, and Family Life (New York,
‘W. W. Norton and Company, 1986), p. 122.

2 Department of Health and Human Services, Social Se-
curity Bulletin, Vol. 54, No. 9, 1991.

3 Characteristics of uup-Assisted Renters and Their Units
in 1989 (Department of Housing and Urban Development,
March 1992), p. 4.

“To identify public housing and privately owned hous-
ing projects that received rental assistance, HUD asked all
public housing authorities and all private sponsors of subsi-
dized multifamily rental projects to list the mailing addresses
of all units in the projects under their management that re-
ceived such assistance. The Census Bureau matched these
addresses with those of the approximately 17,000 renters
responding to the American Housing Survey, who represent
the 33,767,000 total renter households in the United States
Each respondent in the sample represents about 2,000 rent-
ers. Public housing units were matched separately, and all
other subsidy programs were matched as a group. Of the
1.3 million public housing units reported to HuD, 221 cases
were matched, so that each respondent identified as belong-
ing to this category represents more than 6,000 units. Of the
.5 million other permanently subsidized respondents reported
to HuD, 298 were matched, representing 5,500 units each.

5 Facts About Section 8” (Department of Housing and
Urban Development, 1992).

6 Actually, the tenant must pay the highest of the follow-
ing alternatives: (1) 30 percent of gross monthly income,
adjusted for family size; (2) 10 percent of gross monthly
income; (3) for families receiving welfare assistance, the
portion of such assistance designated as the monthly hous-
ing cost for the family.

7 The maximum housing voucher subsidy is set by the
difference between the payment standard and 30 percent of
the household’s monthly adjusted income. For example, if
the payment standard for a particular metropolitan statisti-
cal area is $525, and an eligible household’s monthly ad-
justed income equals $800, the maximum housing voucher
subsidy would be $285. The local public housing adminis-
tration would pay this amount to the landlord on behalf of
the family. If the total rent equals the payment standard of
$525, the family would have to pay only $240 out of its
own pocket. However, if the family can find acceptable hous-
ing that rents for less than $525, the public housing admin-
istration would still pay $285, and the family’s share would
be less than $240. The only restriction in the program is
that recipients must pay at least 10% of their gross monthly
income toward rent and utilities.

® See Katherine Bradbury and Anthony Downs, eds., Do
Housing Allowances Work? (Washington, oc, The Brookings
Institution, 1981).

Eric A. Hanushek and John M. Quigley, “Market Ef-

28 Monthly Labor Review May 1994

fects,” in Bradbury and Downs, Do Housing Allowances
Work? p. 236.

9 Data were selected from interviews collected in 1988—
90 for the following reasons: (1) 3 years of data were neces-
sary (o obtain large enough sample sizes for statistical analy-
sis; (2) data were required to center around calendar year
1989 so that data from the ce Survey could be compared
with 1989 data from the American Housing Survey; and (3)
the 1991 redesign of the ce Interview Survey questionnaire
dropped the question that asked how much rent was paid by
anyone who was not a member of the consumer unit. This
means, of course, that the analysis presented is restricted to
data collected prior to 1991.

"yup classifies households in the lower end of the in-
come distribution as (1) low-income households, that is,
those households with income less than or equal to 80% of
the median household income of the geographic area in
which they are located, and (2) very low income households,
that is, those households with income less than or equal to
50% of the median household income of the geographic area
in which they are located.

'2See H. S. Houthakker and Lester D. Taylor, Consumer
Demand in the United States (Cambridge, Ma, Harvard Uni-
versity Press, 1970), p. 59.

}3 Food includes both food at home and food away from
home. Rent is defined as the consumer unit's contribution
to the total rental charge, plus any utility expenses. Trans-
portation expenditures include the monthly principal and
interest paid for the purchase of an automobile if the auto-
mobile was purchased and financed; the net purchase amount
for a vehicle purchased without financing; expenditures for
gasoline and motor oil; and other vehicle expenses, such as
maintenance and repair costs. Apparel expenses include
expenses for clothing, footwear, jewelry, and other clothing
products and services. Health care expenditures include (1)
health insurance premiums and the consumer unit's contri-
bution to expenses for total medical services, drugs, and
medical supplies and (2) expenditures for personal care prod-
ucts and services. Expenditures for household furnishings
and operations include those for personal services such as
babysitting, other household services, housekeeping sup-
plies, household textiles, furniture, appliances, floor cover-
ings, and miscellaneous household equipment.

"4 See Houthakker and Taylor, Consumer Demand, p. 59.
Total expenditures equal the #1s published definition, mi-
us personal insurance and pensions and vehicle monthly
payments, instead of net purchase price and interest.

'S Because an intercept was calculated in the regression
model, it was necessary to remove one variable from each
group of dummy demographic variables modeled in the re-
gression. These control dummies are listed in table 4

'6See Jean Kinsey, “Probit and Tobit Analysis,” paper

Presented at American Council of Consumer Interest Con-
ference, Atlanta, Apr. 11-14, 1984.



subsidy on households receiving assistance, hold-
ing income (total expenditures) constant. This
parameter estimate was statistically significant
in only the food and health care models; the elas-
ticities listed for the remaining expenditure cat-
egories were not significantly different from zero.
The elasticity of approximately zero for rent and
utilities indicates that, regardless of the rental as-
sistance amount, households receiving assistance
will contribute approximately the same amount
to rent and utilities, roughly 30 percent of their
total expenditures. This implies that these house-
holds would be more likely to seek better qual-
ity or higher valued apartments, given their rental
subsidy, and less likely to reduce their contribu-
tion toward the rental payment so as to free up
income for other goods, Whatever budgetary
substitution they make would be to the purchase
of more food.

Renters who received assistance allocated 29
percent of their budget to food, compared with
only 25 percent of renters who did not receive
assistance. Much of this difference could be ex-
plained by the fact that the former were more
likely than the latter to receive food stamps. The
negative coefficient on health care indicates that
renters who received larger subsidy amounts
spent less on health and personal care. This per-
haps indicates, in turn, that a large proportion of
the subsidized group may receive medicaid and
have very little out-of-pocket health care expend-
itures. There may also be correlations among
health care expenditures, age of household mem-
bers, and rental assistance that are unaccounted
for or misspecified in the models.

Table 6. Estimated elasticities for selected

expenditure categories, 1989
Income
Not
Category Receiving recelving | Subsidy
rental
Sasiatance | asaistance
Food....... ‘87 “79 “42
Rant and
utilities... ‘st 187 01
Transportation .} "1.78 4.93 =12
Apparel .... 14.92 1.45 ~07
Entertainment 1.58 1.94 02
Health and
personal care "2.15 1.58 112
Housewares ...| 12.72 ‘2.90 Pa

* Elasticity significantly diferent from zero at 95-percent
confidence interval.

Nore: Elasticities are celoulated at the mean income and
mean expenditure values.

Conclusions

The analysis presented in this article supports the
thesis that there are demographic differences
between renters who receive housing assistance
and renters who are eligible for, but do not re-
ceive, such assistance. These differences help to
explain some of the variation in the distribution
of total expenditures between the two groups. A
large proportion (40 percent) of the first group
is made up of single parents, and almost 30 per-
cent of the group are over the age of 55. By con-
trast, those in the second group are more likely
to be younger and single. The greatest difference
between the two groups is that almost two-thirds
of all renters who receive assistance are unem-
ployed, retired, or not working for some other
reason. This fraction is much lower for renters
who are eligible for, but do not receive, assist-
ance—about one-third.

The analysis further supports the idea that
rental assistance programs are effective in reduc-
ing the cost burden of shelter for low-income
households: while renters who were eligible for,
but did not receive, assistance allocated more
than 40 percent of their total expenditures to rent
and utilities, those receiving assistance allocated
only about 30 percent to this major category, a
budget share just slightly greater than the 28 per-
cent allocated to the category by renters who
were ineligible to receive housing assistance.
With the exception of transportation, renters re-
ceiving assistance allocated a greater percentage
of their budget to all other expenditure catego-
ties, compared with renters who were eligible
for, but did not receive, assistance. In fact, their
spending pattern more closely mirrored that of
the ineligible group.

Income elasticities for selected expenditure
categories also proved to be slightly different be-
tween renters who did and renters who did not
receive assistance. Elasticities for food, rent and
utilities, and entertainment were lower for the
former group, compared with the latter, while elas-
ticities for apparel and housefurnishings were not
significantly different between the two groups.

While there are differences in expenditures
between the groups, the regression analysis sug-
gests that rental assistance has more of a hous-
ing effect (increasing housing expenditures) than
a welfare effect (reducing the rent burden). On
average, renters who received assistance allo-
cated 10 percent less of their total budget to rent
and utilities than did renters who were eligible
for, but did not receive, assistance. Further, the
second set of regression tests indicated that those
receiving assistance are more likely to seek
higher valued housing and, regardless of the
rental subsidy amount, spend roughly 30 percent

Monthly Labor Review May 1994 27



Rental Assistance and Spending Behavior

underreporting and nonresponse are a larger
problem in the CE Survey for income than for
expenditures. Accordingly, it is common prac-
tice to substitute total expenditures as a proxy
for income with CE Survey data." In the regres-
sions employed in this analysis, total quarterly
expenditures were used as a proxy variable for
income. To capture differences among eligible rent-
ers, also included were a dummy variable denot-
ing whether a renter received assistance (value =
1) or not (value = 0) and an interaction term be-
tween the dummy variable and total expendi-
tures. The remaining independent variables com-
mon to all regressions were family size; number
of children; age of reference person; a dummy
variable denoting race or ethnicity, with a value
of 1 if the race of the reference person was Afro-
American, Asian, Eskimo, Aleut, or another mi-
nority and a value of 0 if the race of the refer-
ence person was white; four dummy variables
representing family composition, namely, single,
husband and wife only, husband and wife with
children, or other consumer units (single parents

Table 3. Continued — Weighted income and expenditure statistics
for renters, by category of assistance, Consumer
Expenditure Survey, 1988-90"

Ineligible
Variable tor
essistence
Health and personal care:
Mean . . 134.87 118.84 323.31
Percent reporting _ 74.3 78.5 95.0
Budget share 6.0 49 55
Entertainment:
Mean feces 100.07 70.92 321.12
Percent reporting 745 67.6 93.7
Budget share... 45 3.0 55
Other expenditures.”
Mean tence 91.39 57.26 370.89
Percent reporting . 65.1 66.9 92.6
Budget share 41 24 64
* Sample size of all renters was 24,855. Those in public housing (n = 868), those not

reporting amount of assistance (n = 553), and those reporting assistance other than gov-
ernmental (n = 1,363) were removed.

? Self-employment and farm income includes all earnings from self-employment, both
farm and nonfarm.

Social Security and retirement income includes Social Security income and income
from pensions or annuities from private companies, the Federal Government, of individual
retirement accounts.

* Assistance income includes unemployment compensation, workers’ compensation,
veterans’ payments, public assistance, supplemental security income, food stamps, and
other financial assistance.

5 Other types of income include money received from care of foster children, cash schol-
arships, and stipends not based on working.

® Total quarterly expenditures equal ats published definition, minus personal insurance
and pensions and vehicle monthly payment, instead of purchases and interest.

7 Other expenditures include expenditures for reading and education, miscellaneous
expenditures, cash contributions, and other housing expenditures.

24 Monthly Labor Review May 1994

were excluded as the control category); three
dummy variables representing the quarter dur-
ing which the interview took place, namely, the
first, second, or third quarter (the fourth quarter
was excluded as the control quarter); and two
dummy variables representing geographic loca-
tion, namely, center city or suburb (rural was ex-
cluded as the control group).

The following additional variables were in-
cluded in some models. Building-type dummy
variables, the number of bedrooms, and a dummy
variable representing the age of the housing unit
(value = 1 if the unit was built within the last 10
years, value = 0 if the unit was older) were in-
cluded for the rent and household furnishing
models. A variable representing the number of
automobiles owned or operated by the household
was added to the transportation model, and
dummy variables representing whether a house-
hold had one earner or two or more earners (the
case of no earners was excluded as a control
group) were included in the transportation and
health and personal care models. Finally, the cash
value of food stamps was added to the food
model.!5

The method of ordinary least squares was
employed for the food and rent models, as 100
percent of the sample group reported that they
incurred these expenditures. TOBIT analysis was
used for the remainder of the dependent vari-
ables, because the percent of the sample group
reporting each of these expenditures was about
80 percent or less. TOBIT is a more appropriate
model when the dependent variable is truncated
at a lower bound and there is a large frequency
of that value—in this case, zero.!©

Each of the seven regressions assumed the
functional form

E,= a+ BLY, + BY, *S; + ByS, + BD; +e,

where E, = quarterly expenditure amount of
dependent variable for ith house-
hold;
a intercept;
B; = independent variable parameter

estimates;

Y, = total quarterly expenditures (in-
come proxy) of ith household;

S, = Lif household received rental as-
sistance, 0 otherwise;

D,= vector of various demographic
variables;

e; = error term.

The results of the regressions are listed in table
4, With the exception of apparel and housewares,
the parameter estimate for the interaction term
Y,S, was significantly different from zero in all



Rental Assistance and Spending Behavior

Table 2. Selected weighted sample statistics for renters, by
category of assistance, Consumer Expenditure Survey,

1988-90!
Eligible for assistance
Not Ineligible
Variable Receiving tor
receiving
assietance | J eistance | assistance
Sample size 487 8,290 13,274
Geographic location
Central city ...... . 49.0 498 377
Other places inside metropolitan
statistical area . . 27.6 33.7 44.2
Rural 23.4 16.6 18.4
Region:
Northeast 26.6 214 20.5
South .. 26.5 296 319
Midwest .. 18.0 274 206
West 29.0 222 27.0
Type of building:
Single-family, detached 183 25.7 319
Row or town house 207 17.4 18.2
Multiunit, garden ... 18.9 20.0 219
Multiunit, high rise 16.4 6.0 53
Basement, attic, or garage 25.0 244 18.3
Mobile home or other 26 72 44
Average number of rooms . 44 42 46
Average number of bedrooms .. 19 19 24
Average number of bathrooms . 14 WW 1.2
Family size:
One 315 473 35.9
Two... 235 18.4 298
Three . 21.4 12.7 15.1
Four... . : 11.0 10.6 15
Five or more... esc 12.7 11.0 17
Mean 26 23 23
Number of children:
ne : a74 61.3 62.5
One 244 15.0 18.1
Two... 19.7 128 127
Three 115 67 49
Four... 5.6 27 12
Five or more. 1.6 16 6
Mean ... 1.3 8 7
Family composition:
Single 31.5 473 35.9
Husband and wife only. 39 73 16.7
Husband and wife with children... 85 15.6 23.5
Single parent 39.6 12.9 62
Other type of arrangem: 16.6 17.0 177
Age of reference person:
‘Under 25 years 10.4 19.0 144
25 to 34 years 37.0 29.8 42.0
95 to 44 years 13,7 14.4 18.8
45 to 54 years 8.0 9.9 11.4
55 to 64 years ..... 12.2 81 5.9
65 years and older 18.8 18.8 78
Mean .. 444 424 378
Race of reference person:
White 66.1 73.0 87.0
Black 32.1 22.7 96
Other? . 18 43 34

See footnotes at end of table.

20 Monthly Labor Review May 1994

interchangeably throughout this article. The CE
Survey sample is designed to represent the
noninstitutional civilian population, and approxi-
mately 5,000 consumer units are interviewed
each quarter. '°

Three sample groups were selected from the
set of all renter consumer units described in the
CE Survey, based on their eligibility for, and
whether they received, housing assistance: (1)
income-eligible renters who received assistance;
(2) income-eligible renters who did not receive
assistance; and (3) ineligible renters. Income eli-
gibility was determined by using the 1992 rental
assistance very low income limits, as established
by HUD for the 104 primary sampling units com-
prising the CE Survey sample.'! To determine a
consumer unit’s eligibility, the income limits
were matched against consumer unit records by
family size and place of residence.

To identify eligible households, total expend-
itures, rather than reported income, were used to
approximate a consumer unit’s current income,
for several reasons. First, underreporting and
nonresponse are a larger problem in the CE Sur-
vey for income than for total expenditures. Sec-
ond, using reported income would have resulted
in households that suffered a significant self-em-
ployment or business loss being eligible for rental
assistance. Typically, however, these types of
households have very large expenditures and are
generally not categorized as low-income hou:
holds. Third, it is common practice to substitute
total expenditures as a proxy for income with
data from the CE Survey.'? Usually, this proxy is
made for permanent income, rather than current
income. However, in this case, the assumption
that households which receive rental assistance
generally remain eligible for long periods of time
implies that current income may not differ sig-
nificantly from permanent income.

Because total expenditures are collected on a
quarterly basis in the CE Survey, the HUD income
limits were divided by 4, and if a consumer unit's
total quarterly expenditures were less than or
equal to this critical value, that unit was identi-
fied as income eligible. The 1992 very low in-
come limits were deflated using the Consumer
Price Index for All Urban Consumers (CPI-U) to
match the limits that existed during the quarter
in which each consumer unit was interviewed.

Of the income-eligible consumer units, those
receiving rental assistance were identified as the
ones that responded “yes” to the question, “Are
your housing costs lower because the Federal.
State, or local government is paying for the cost?”
and reported a value to the question, “How much
rent is paid by someone outside of your consumer
unit, including local, State, or Federal govern-
ment agencies?” Income-eligible consumer units



for assisting very low income families in rent-
ing “decent, safe, and sanitary private-market
housing units.”5 While there is a subtle differ-
ence between a housing certificate and a hous-
ing voucher, both programs place the choice of
housing directly in the hands of the consumer.
Hence, the amount of the subsidy can be treated
as a change in income, and the resulting alter-
ation in spending on the part of the household
receiving the assistance can be modeled.

In the case of a housing certificate, the rental
subsidy is the difference between the approved
rent due the owner of the dwelling unit and the
occupant family’s required contribution toward
the rent, which is usually set at 30 percent of the
family’s monthly adjusted income.® In the case
of a housing voucher, the amount of the subsidy
is based on a “payment standard” that varies
among communities. The payment standard is
developed by local public housing administra-
tions and establishes rent standards for differ-
ent-sized units, based on the average rent, includ-
ing utilities, in each community. The amount of
the subsidy a participating family receives equals
the difference between the payment standard and
30 percent of the family’s monthly income, ad-
justed for family size. Families receiving hous-
ing vouchers may choose from a wide variety of
housing, including single-family homes, town
houses, and apartments (either in apartment
buildings or in private homes). They may choose
to rent a unit for more or less than the payment
standard.” Under both the housing certificate and
voucher programs, subsidy payments are made
directly to landlords, and the recipient household
pays the remainder of the rent to the landlord.
Housing must meet an acceptable level of qual-
ity before the local public housing authority will
approve payments.

The budget constraint of recipient households
shifts outward, affording them the opportunity
to reach higher levels of utility. Even though the
rental subsidy is actually given to the landlord,
the reduced rent charged to the recipient house-
hold frees up money that can then be spent on
other items. In the case of a housing voucher,
recipients must spend a minimum of 10 percent
of their adjusted monthly income on rent and
utilities. The rental subsidy allows recipients to
rent higher valued housing units that they would
otherwise not be able to afford. It also allows
them to decide how much of their own income
they want to allocate to shelter and how much to
all other goods.

During the 1980's, the Brookings Institute
sponsored an “experimental housing allowance”
program to research the effectiveness of various
types of housing allowances in reducing the costs
of shelter for eligible households.* As part of this

Table 1. Renter households, by category
of assistance, 1989
[Numbers in thousands}
Category Households | Percent
All renters. . 33,767 100
Income eligible............ 13,808 41
Receiving assistance 4,070 12
In public housing ... 1,360 4
Through certificate
or voucher.......-- 1,060 3
In privately owned
housing project... 1,650 5
Not receiving
assistance .......... 9,378 29
Ineligible... 19,959 59

study, Eric A. Hanushek and John M. Quigley
concluded that unrestricted housing allowances
(such as cash transfers) result in low income elas-
ticities.? This implies that the welfare effects of
such a program (that is, a reduction in the rent
burden) are relatively stronger than the housing
effects (that is, increases in the housing compo-
nent of expenditures). Conversely, the more re-
strictive a housing allowance program (such as
housing vouchers) is, the greater are the housing
effects relative to welfare effects. To measure the
ramifications of rental] assistance on a family’s
total spending behavior, the entire budget out-
lays of renters, classified by whether they are
eligible for assistance and whether they in fact
receive assistance, are examined in the remain-
der of the article.

Descriptive statistics on renters

Data from the 1989 American Housing Survey
include socioeconomic and demographic infor-
mation on renter households, by type of assist-
ance received. However, the survey does not pro-
vide any data on household consumption, with
the exception of expenditures for rent. Accord-
ingly, to analyze the expenditure behavior of
households receiving rental assistance, data from
the 1988-90 Consumer Expenditure (CE) Inter-
view Surveys were used. This survey is a quar-
terly rotating panel survey designed to collect
data on major items of expense, household char-
acteristics, and income. The technical reference
group of the survey is a consumer unit, defined
as (1) all members of a particular household who
are related by blood, marriage, adoption, or some
other legal arrangement; (2) a person living alone
or sharing a household with others, or a person
living as a roomer in a private home or lodging
house, but who is financially dependent; or (3)
two persons or more living together who pool
their income to make joint decisions regarding
the disposition of their expenditures. The terms
consumer unit, household, and family are used

Monthly Labor Review May 1994

19



18

Rental Assistance and Spending Behavior

Today, various Federal, State, and local gov-
emment agencies administer housing programs
for low-income families. Most of these programs
are funded by the Department of Housing and
Urban Development (HUD). Some programs for
rural families are funded by the Department of
Agriculture. Federal budget outlays in fiscal year
1990 for public housing and rental assistance
programs administered by HUD for low-income
families and individuals were approximately $15
billion.? Generally speaking, housing programs
administered by HUD can be classified into three
major categories: privately owned subsidized
housing projects, conventional public housing,
and certificates and vouchers issued under Sec-
tion 8 of the Housing Act. Programs that are
grouped under the first umbrella include rent
supplements; below-market interest rates; pro-
grams for the elderly; new construction, substan-
tial rehabilitation, and moderate rehabilitation
programs; and some other, smaller programs. The
essential feature of this category is that assistance
is given to the administrators of the privately
owned projects, who, in turn, offer households
subsidized rents. This approach contrasts with
that of conventional public housing, in which
projects are owned directly by public housing

authorities or Indian housing authorities. Finally,
in the Section 8 certificate and voucher programs,
assistance is given directly to the low-income
households, which are then free to choose their
own housing units.

According to the 1989 American Housing
Survey, there were roughly 34 million renter
households in the United States. In conjunction
with the Census Bureau, HUD undertook several
efforts to identify which units in the 1989 sur-
vey sample received assistance.* Population
counts of renter households by eligibility and
assistance status are presented in table |. More
than 40 percent of all renter households had in-
comes low enough to be considered eligible for
housing assistance under various HUD subsidy
programs. Of this group, 4 million (30 percent)
actually received some form of rental assistance
in 1989. Chart 1 illustrates the percent distribu-
tion of households that received assistance, by
type of subsidy.

This article focuses on the group of renter
households that receive assistance in the form
of certificates or vouchers. The Section 8 hous-
ing program was established by the 1974 Hous-
ing and Community Development Act. It is the
Federal Government's major operating program

Project-based
assistance
(41 percent)

Chart 1. Distribution of subsidized renters, by category of assistance, 1989

SOURCE: U.S. Department of Housing and Urban Development.

CertificateNoucher
(26 percent)

: ie /
i 7 =
a

Public housing
(33 percent)

Monthly Labor Review May 1994