CPI for the Poor

of goods and services.** It is based on the average expendi-
ture pattern of a representative sample of U.S. urban house-
holds, as taken from the cg Survey. A separate Point of
Purchase Survey is used to determine from which specific out-
lets goods and services will be priced for the index and to
assess the types of establishments at which its representative
sample purchases goods and services. The cri aims at pricing
the same fixed market basket of goods and services each month,
using that market basket as the reference “standard of living.”

The cri is a fixed-quantity price index, described by the
equation

a Lite

= 41 #1000,
2 Pod

ho

36 Monthly Labor Review September 1996

Table 1. ou o where p, is the price of item i in pe-
en ae eens nes Consumer Expenciture Survey samPle | riod sq, is the quantity of item in the
expenditure base period b, and p,, is
All Consumer | income poor | Expenditure | — Program the price of item i in base period 0.
Charactertstic ‘units ” participants :
ine ti23e | 71) | ey Pzen (n= 1,313) ‘When the base and expenditure refer-
ence periods coincide (that is, when b
= 0), this formula is the Laspeyres in-
224 65 53 47 i
312 194 136 185 dex and can be expressed in terms of
48 66 62 96 expenditure shares and price ratios as
58 158 15.7 19.6
25.6 33.3 415 20.1 n
10.6 18.6 176 21.6 Q Loz > wif 2) *100.0,
, i=l Pio
23.4 21.6 21.8 25.5
28.1 25.4 25.0 24.9 ji i
319 379 99.3 30.2 where w/t is the average expenditure
18.6 154 13.9 19.4 share for item i for the sample of
households, H. While, for the cet, the
e42 449 34.8 29.6
sample H represents all urban house-
81 994 96.7 50.8 holds, the formula may be used to cal-
5.6 34.5 29.1 45.7 culate a price index for subgroups of
37 19.8 21.8 32.2 7
34 20.4 473 254 that sample, based on any chosen de-
29 12.7 142 25.4 mographic characteristics.
Because it is a fixed-weight index,
the Laspeyres index does not allow for
675 43.3 376 98.7 ituti
Wt 25.2 204 303 substitution by consumers across
goods and services when the relative
Less than high schoo! 26.1 51.9 63.7 $4.9 i ‘
High onool graduate 30.2 239 224 28.7 prices of those goods and services
‘Some college 21.3 15.3 10.3 13.2 change. Such substitution permits con-
224 88 36 82 sumers to adjust their market basket
7.0 85 12.6 78 and achieve the same level of
0S at oat 33 satisfaction in response to certain rela-
2nd 26.5 33.6 26.8 tive price changes that they enjoyed
" Other married couples are married-couple families that include persons other than the couples’ own | With the previous basket. By ignoring
children, this flexibility in consumer behavior,
aa STc rats a eu sear ese geckos wrwerea | the Lawpeyes forma becomes, ia
ingle-par persons, other iren, rel ingle parent. .
terms of economic theory, an upper
2
Consumer Units mey recelve mutipe forms of assistance end therefore can fal! more than one | 4 65 the true cost-of-living index
measure.””
Other indexes also may be used as

measures of changes in prices or the “cost of living.” If cur-
rent-period expenditure shares are used as weights, one can
calculate the Paasche index,

P= a *100.0,

isl

GB)

where wi! is the average expenditure share for group H in
period r. Although the expenditure weights are from the pe-
riod t, whereas the Laspeyres index uses period 0, the Paasche
index is less useful for official measures because the time
needed to estimate these shares from survey data creates a
lag in publishing the current value of the index. It also re-
quires more resource costs, because one must estimate a new



Requests for indexes for the poor originate from a belief
that the movement of relative prices for this group may differ
from that of the general population. If poor consumers do
face differential price inflation, it could have major implica-
tions for governments providing benefits to these consumers
and for the measurement of poverty in general. Based on our
research, however, we conclude that the poor and the general
population have faced similar trends in relative prices over
the last several years; thus, the level of assistance rendered
the poor, as well as poverty rates, would not be expected to
have been different with a price index specifically designed
to reflect the spending patterns of the poor. This conclusion,
of course, is limited in that it is based on data available at the
current time; also, methodological problems in measuring
differences in price indexes between the poor and the general
population were identified.

The differences between our experimental indexes and the
indexes calculated using the aggregate components suggest
some interesting issues for research. For example, it is pos-
sible that small price increases in a given category of goods
or services (such as entertainment or automobile expenses)

Footnotes

may induce large shifts away from expenditures on these cat-
egories, especially for households on the economic margin.
This hypothesis could be tested using a discrete-choice de-
mand model if sufficient data were available. The importance
of how component categories of goods and services are de-
fined in the context of computing indexes also appears to be
an interesting question when comparing index values across
households or household groups.

Finally, if prices from rural areas were available, we might
report a higher or lower cet for the poor if relative prices faced
by consumers living and shopping in rural areas are different
from relative prices faced by urban consumers. At the
present time, we cannot test the robustness of our indexes
relative to this geographic variable. Also not addressed in this
study are the interarea differences, both across and within
urban areas, in prices faced by U.S. consumers;® this could
be tested in future research. Whether the poor shop in differ-
ent types of outlets or whether they purchase commodities of
different quality than the nonpoor do cannot easily be tested
without conducting a Point of Purchase Survey specifically
addressing the poor population. oO

ACKNOWLEDGMENT: The authors would like to thank Rob Cage, John
Greenlees, Brent Moulton, Bill Passero, and Stephanie Shipp of the Bureau
of Labor Statistics; Vee Burke of the Congressional Research Service; Gor-
don Fisher of the Department of Health and Human Services; Kathleen Scholl
of the General Accounting Office; Helen Stebbins of the Department of Ag-
riculture; and Javier Ruiz Castillo, 1996 ASA/BSA/NSF Fellow, for their
assistance and comments.

' Vee Burke, Cash and Noncash Benefits for Persons with Limited In-
come: Eligibility Rules, Recipient and Expenditure Data, FY 1992-1994,
Congressional Research Service Report 96-159 erw (Library of Congress,
1996).

? See Burke, Cash and Noncash Benefits; and Gordon M. Fisher, “Pov-
erty Guidelines for 1992,” Social Security Bulletin, vol. 35, no. 1, Spring
1992.

3 The Health and Human Services poverty guidelines are a simplified
version of the Federal Government's official statistical poverty thresholds
and are updated at different times. (See Fisher, “Poverty Guidelines for
1992.")

* Unless otherwise noted, the term cpi-y refers to the index for all items.

5 Constance F. Citro and Robert T. Michael (eds.), Measuring Poverty: A
‘New Approach (Washington, pc, National Academy Press, 1995).

“Kenneth J. Arrow, “The Measurement of Price Changes,” in The Rela-
tionship of Prices to Economic Stability and Growth (Joint Economic Com-
mittee, U. S. Congress, Mar. 31, 1958).

7 Urban areas are defined by the Consumer Price Index program either to
be within metropolitan statistical areas (MSA's), including areas identified as
rural nonfarm (but not rural farm), or to be urbanized areas outside MSA's.
‘An sa is a geographic area consisting of a large population nucleus, to-
gether with adjacent communities which have a high degree of economic
and social integration with that nucleus. (See Consumer Expenditure Survey,
1992-93, Bulletin 2462, Bureau of Labor Statistics, September 1995.)

* Other definitions to identify the poor could have been chosen. See, for
‘example, Citro and Michael, Measuring Poverty; Maya Federman, Thesia I.
Garner, Kathleen Short, W Boman Cutter IV, John Kiely, David Levine, Duane

McGough, and Marilyn McMillen, “What does it mean to be poor in
America?” Monthly Labor Review, May 1996, pp. 3-17; Mark Lino, “In-
come and Spending of Poor Houscholds with Children,” Family Economics
and Nutrition Review, vol. 9, no. 1, 1996; Susan Mayer and Christopher
Jencks, “Has Poverty Really Increased among Children since 19707” Work-
ing Paper 94-14, Center for Urban Affairs and Policy Research, Northwest-
em University, 1995; William D. Passero, “Spending Patterns of Families
Receiving Welfare or Public Assistance, 1992-94,” paper prepared for the
42nd Annual Conference of the American Council on Consumer Interests,
Nashville, tN, March 27-30, 1996; and Patricia Ruggles, Drawing the Line:
Alternative Poverty Measures and Their Implications for Public Policy (Wash-
ington, pc, The Urban Institute Press, 1990).

* A consumer unit comprises members of a household who are related or
who share at least two out of three major expenditures—housing, food, and
other living expenses.

"See Current Population Reports, Series P60-185, Poverty in the United
States: 1992 (Bureau of the Census, 1993).

"" Passero employs this definition to identify the poor, using ce Survey
data; see William D. Passero, “Spending patterns of families receiving pub-
lic assistance,” Monthly Labor Review, April 1996, pp. 21-28.

"Bleanor M. Snyder, “Staff Paper 7: Cost of Living Indexes for Spe-
cial Classes of Consumers,” in The Price Statistics of the Federal Govern-
ment: Review, Appraisal, and Recommendations, a Report to the Office of
Statistical Standards, Bureau of the Budget (National Bureau of Economic
Research, 1961). This report is also known as the 1961 Stigler report.

°° Robert Michael, “Variation across Households in the Rate of Inflation,”
Journal of Money, Credit, and Banking, February 1979, pp. 32-46: and Rob-
ert Hagemann, “The Variability of Inflation Rates across Household Types,”
Journal of Money, Credit, and Banking, November 1982, pp. 494-510.

TM Mary Kokoski, Consumer Price Indices by Demographic Group, Work-
ing Paper No. 167 (Bureau of Labor Statistics, April 1987).

'S Nathan Amble and Ken Stewart, “Experimental price index for elderly
consumers,” Monthly Labor Review, May 1994, pp. 11-16.

¥ See also Michael Boskin and Michael Hurd, “Indexing Social Security

Monthly Labor Review September 1996 41



CPI for the Poor

than those for other commodities. A similar pattern emerges
for relative prices of apparel and upkeep between 1993 and
1994. For purposes of exposition, we also computed
Laspeyres indexes using these seven more aggregated cat-
egories of goods and services as the basic components.

Results

The Laspeyres indexes using the 136 components are pre-
sented in table 5. By means of formula (3), we also calculate
Paasche indexes, using 1994 expenditure weights for the same
136 goods and services categories, rebased to 1984 = 100 for
comparison with the Laspeyres index values. The results are
presented in the first row of Table 6. Consistent with theoreti-
cal expectations, the values of this index are lower than the
corresponding values of the Laspeyres index." Chart 2 shows
the percent differences between each of the inflation rates for
the poor and the overall inflation rate. The 1982-84 Laspeyres
indexes for the income poor and the expenditure poor lie
above the overall index in all but the last 2 years. Alterna-
tively, the index for the program poor lies below the overall
index in all of the years. The differences among all these in-
dexes are small, and the results of other research suggest that
the differences would likely not be statistically significant,
given the small sample sizes of the poor household groups.

Robert G. Michael has suggested that comparing Laspeyres
price indexes across groups may not be an accurate indica-
tion of real differences in the effects of inflation. According
to Michael, Laspeyres price indexes may not capture signifi-
cant consumption responses to price changes.** Substitution
opportunities, he maintains, may be different for households
with different levels of income, and perhaps the degree of
substitution bias may differ across income groups. To exam-
ine this issue, we have used 1992-94 ce Survey shares for
each population group in our study to construct the Paasche
and Fisher’s ideal indexes shown in table 6. The percent dif-
ference between the 1994 Fisher’s ideal index and the corre-
sponding 1994 Laspeyres index represents the degree of sub-
stitution bias:

(5) [Lissassee~ Fissusea)!/ CF snsises 1003] *100.0.

Using the results for the Laspeyres and Fisher ideal in-
dexes, for each population group, we estimated the degree of
bias. The results are presented in table 6. The magnitudes of
the estimates are similar to those obtained by Kokoski in a
comparison of 1972-73 demographic groups with their 1980—
81 counterparts.** Although these results may not be statisti-
cally significant, it is interesting that the bias appears to be
lower for the income poor and program participant poor
groups. Because the statistical significance of the index num-
bers, and thus the substitution bias results, are unknown, this

38 Monthly Labor Review September 1996

observation only suggests further research.

The difficulty in making comparisons of index values us-
ing the Laspeyres formula is also illustrated by comparing
the figures listed in table 5 with those shown in table 7, which
are based on the more aggregate components presented in
table 4 and illustrated in chart 1. It is well known, as Bert M.
Balk points out, that higher levels of aggregation of com-
modities tend to reduce the magnitude of the differences in
index values between groups. The more aggregated index
values in table 7 are closer to the official cri for the years
shown, as well as closer to each other when compared across
groups in any given year. Interestingly, if one starts with a
higher level of aggregation to construct the indexes, the pat-
tern of differences appears to change. Taken at face value, the

| Tobie 4. er ‘expenditure shares over the 1962-84
period, for all consumer units and for poor

Consumer units, for each definition of poverty

Al Program
Expenditure — | consumer| Income | Expendi-| partici-
category units’ | poor | tue poor! “pants
18.3 211 26.1 24.4
AT 445 50.9 42.9
5.7 5.3 45 55
20.6 15.7 88 15.2
47 47 40 47
41 33 16 26
48 56 40 47

‘The relative importance figures for the seven categories, according to
J. L. Marcoot and R. C. Bahr, are 18.0, 42.4, 6.6, 18.9, 4.7, 4.5, and 5.1,
respectively. (See J. L. Marcoot and R. C. Bahr, “The revised Consumer
Price Index: changes In definitions and availability” Monthly Labor Review,
July 1986, pp. 15-23.)

2 Food and beverages consist of food at home, food away from home,
and alcoholic beverages.

Housing consists of residential rent; lodging out of town; othar lodging;
tenants’ insurance; rental equivalence for homeowners; fuel oil; other fuel
commodities; electricity; utility gas; telephone services; water and sewer
services; textile house furnishings; bedroom fumiture; sofas; living room
furniture; other fumiture; televisions; audio equipment; video equipment;
‘efrigerators and freezers; laundry equipment; stoves, ovens, and dishwash-
‘rs; floor and window coverings; clocks, lamps, and related articles; table-
‘ware; lawn equipment and related items; housekeeping supplies; and appll-
ance repair.

“ Apparel and upkeep consists of men’s apparel, women's apparel, boys
apparel, giris' apparel, infants’ appare!, sewing materials, watches and jew-
elry, footwear, other apparel services, and taundry services.

* Transportation consists of new cars; used cars; motor fuel; auto body
repair; auto drive train repair; auto maintenance; auto power plant repair,
motor oil, coolant, and other fluids; tires; other auto parts; auto insurance;
auto finance charges; auto registration; other auto fees; airline fares; other
intercity transportation; and intracity transportation.

* Medical care consists of prescription drugs; nonprescription medical
commodities; physician services; dental services; and eye care, hospital
room, and other inpatient services.

7 Entertainment consists of newspapers, magazines, sport vehicles, other
sporting goods, toys, photo supplies, pet supplies, club memberships, fees
for participation sports, and admissions.

* Other commodities consist of tobacco and smoking commodities, toilet
goods, beauty parlor services, haircuts for males, schoolbooks, college tu-
itlon, elementary and high school tuition, personal expenses, and informa-
tion-processing equipment.



set of expenditure shares for each successive period in the
index series. If both Paasche and Laspeyres indexes are cal-
culated, however, it is possible to produce an index that is, in
theory, a very close approximation to a true cost-of-living
index. This is Fisher’s ideal index, written

() Fy, = (L,0)” *(Po

This formula, which is of the class of “superlative indexes,”>*
is the geometric mean of the Laspeyres and Paasche indexes.
Used as the true, benchmark cost-of-living index, Fisher’s
ideal index can assess the degree of substitution bias inherent
in the fixed-weight Laspeyres calculation.”

Within the framework of the cri program, the only way to
construct price indexes for demographic subgroups of the
population is to adjust the expenditure weights to represent
those groups. There are no data on prices paid for items by
specific types of consumers, the outlets in which different
groups are most likely to shop, differences in the quality of
items across demographic groups, or differences in house-
holds’ costs of time or use of technology in shopping for
goods and services. Thus, to empiri-
cally compare the effects of price

a

care, entertainment, and other items. These represent the av-
erage expenditure shares for the 1982-84 period. The shares
for our annualized urban sample are similar to the relative
importance weights used for the cpi-u during the same pe-
tiod.*’ As expected, the poor populations have larger shares
than the entire sample for items generally considered neces-
sities, such as food and housing, and smailer shares for enter-
tainment and transportation. The table also shows that the
expenditure poor have spending patterns that are most dis-
similar to that of the entire sample. Chart 1 plots the Con-
sumer Price Indexes for the seven commodity groups listed
in the table and for all items. Plainly, relative prices of most
commodities exhibit the same increasing trend. The two ex-
ceptions are medical care and other commodities; however,
because these account for small expenditure shares, we did
not expect their price changes to affect our experimental in-
dexes substantially.

From 1985 to 1986, the transportation index decreased
slightly and then continued to follow a path similar to that
of the other major groups. Also, between 1991 and 1992, rela-
tive food and beverage prices increased, but at a lower rate

changes on different subgroups within
the U.S. urban sample, one must as-

FREER Percent cistrisution of 1982-84 sample, by ratios of oxpenciures and
income to poverty thresholds

sume. that the distribution or Prices ‘Expenditures os a percent of poverty threshold Percent oO

paid for the same items, as well as dif- ‘consumer

ferences in the quality of items pur- necovery eects HT (100 Rercent|160 percent) Greater | unis with

chased, is the same across population percent | 160 percent|200 percent| percent remoctve

subgroups. Consumption costs be-

yond the purchase price of each item

(for example, the cost in time of pub- 73 34 1 23 144

lic transportation to suburban outlets 25 A 33 28 2

for inner-city residents) are beyond : 37 80 a7 847

the scope of the cei framework. 13 24 22 59 15
The expenditure weights are calcu-

lated for the 136 categories of goods 9 163 178 842 100.0

and services defined by the crt that are

consistent with the data collected in
the Interview portion of the ce Sur-

vey.” The price indexes for these cat-
egories are published by the Bureau
of Labor Statistics at the national av-
erage level and are subindexes of the
cri-u. This level was therefore the

most disaggregated one at which we
could define goods and services in the
construction of our indexes.

Table 4 presents the aggregate
shares for seven commodity groups:
food and beverages, housing, apparel
and upkeep, transportation, medical

Income to poverty
Expenditures a8 a percent of poverty threshold Percent o
Income asa percent of — | Less than fico percent |is0 percent| Greater | Constmer
poverty thesshoid 100 to fo 200 | than 200, | yobs ta,
Percent /150 percent) percent percent income
Complete income reporters:
Less than 100 percent 41.0 10.5 1.8 16 SAD
100 percent to 150 percel 8.6 67 20 13 18.6
150 percent to 200 percent. 5 39 28 8 7.9
‘Greater than 200 percent a 28 2.0 72 12.0
Incomplete income reporters ...... 41 16 4 4 6.6
Percent of all participant poor
with respective expenditures ..... 543 256 a9 11.2 100.0

Monthly Labor Review September 1996 37



CPI for the Poor

results would indicate that the poor subgroups have gener-
ally experienced higher levels of inflation than the overall
population. However, because we are comparing Laspeyres
indexes, which are upper bounds on the true cost-of-living
indexes and not, in general, true cost-of-living indexes them-
selves, these results are difficult to interpret. It appears that
the expenditure patterns within each of the seven aggregate
categories are different for the poor households in our sample,
with higher relative shares for those goods and services in
each aggregate category with more rapidly increasing prices.
Within transportation, for example, the share spent on new
cars was lower for all three of the poor household groups
(indeed, it was zero for the expenditure poor) than for all con-
sumer units in the sample, and new-car prices rose relatively
more slowly than the other components of transportation.

Finally, we can use our experimental price indexes to in-
flate the 1984 poverty thresholds and examine how sensitive
the poverty rates for individuals are to different adjustments
for inflation. The following shows 1992-94 poverty rates for
the income poor and the expenditure poor, calculated in four
different ways—three using the experimental Laspeyres in-
dexes (to adjust the 1984 official poverty thresholds, first for
the entire sample, then for the income poor, and then for the
expenditure poor) and the fourth using the thresholds pub-
lished by the Census Bureau for the 1992-94 period:

Income Expenditure
poor poor
Updated 1984 thresholds
using index—
For all consumer units 13.9 17
For income poor .. 13.9 ”
For expenditure poor oy 11.6
Published Census Bureau
thresholds 141 121

Because our experimental indexes are similar to the over-
all index, the poverty rates are minimally affected. For ex-
ample, using the experimental index for the expenditure poor
to inflate the 1984 poverty thresholds yields a poverty rate
for the expenditure poor of 11.6 percent, which is only 0.1
percent lower than that obtained using the overall index to
inflate the thresholds (11.7 percent). Alternatively, using the
indexes calculated with the more aggregate components
yields a poverty rate for the expenditure poor that is 0.1 per-
cent higher than that obtained using the overall index (based
on the aggregate components). For comparison, the average
poverty rates for persons, using the official Census Bureau
poverty thresholds for 1992-94, are 14.1 percent for the in-
come poor and 12.1 percent for the expenditure poor.”

‘THIS ARTICLE HAS PRESENTED experimental Laspeyres, Paasche,
and Fisher price indexes for poor consumers. Data on rela-

40 Monthly Labor Review September 1996

rate 5 | Laspeyres Indexes for 1964 fo 1994, based on
136-commodity aggregation
a Income | Expendi- ck
veer jecommer| sce | Rett | rei
100.0 100.0 100.0 400.0
103.6 103.6 103.6 103.4
105.6 106.1 106.1 105.4
109.6 109.9 109.9 109.2
1139 1141 1144 11384
119.3 1198 1198 119.0
125.4 1262 126.2 125.2
130.1 130.7 1306 1296
133.7 134.0 133.9 133.0
137.6 137.5 137.4 136.6
141.4 140.7 1406 139.8
-
Price indexes and substitution bias in Laspeyres
. index,1984 and 1994
[1984 = 100)
Ai Program
Income | Expendi-
Index and bles | consumer partic!
poor ture poor pants
139.5 138.6 139.1 139.6
140.3 140.0 139.8 139.7
144.4 140.7 140.6 199.8
1.99 4.78 2.01 25
iCleliwa Laspeyres indexes for 1984 to 1994, using
aggregation of seven commodity groups
[1964 = 100}
all Program
Income | Expendi-
Yeor consumer partici-
‘units poor | ture poor | ‘pants
400.0 100.0 100.0 100.0
103.5 103.6 103.5 103.5
105.5 105.9 106.3 105.9
109.3 108.8 110.2 108.7
113.7 1143 1147 1142
1192 1198 120.0 119.8
125.6 126.2 126.4 126.2
130.8 131.6 131.7 1315
1347 195.5 135.5 135.3
138.6 139.5 139.3 139.2
1423 143.1 1428 142.8

tive prices from 1982 through 1994 for urban areas were used,
in conjunction with data on expenditure shares from the
1982-84 and 1992-94 Interview portion of the ce Survey.
Based on the analysis set forth in the article, we find that
there is little difference between our indexes for the poor and
the indexes for the entire urban population. Given the small
differences, it should come as no surprise that poverty rates
based on thresholds adjusted using the Laspeyres index for
the poor are only marginally different from the rates based on
an index for the total urban population.



CPI for the Poor

Thesia !. Garner,
David S. Johnson,
and

Mary F Kokoski

Thesia |. Gamer, David
S. Johnson, and Mary
F Kokoski are econo-
mists in the Division of
Price and Index
Number Research,
Bureau of Labor
Statistics. The views
expressed in this article
are those of the
authors and do not
necessarily represent
an officiat position of
the Bureau of Labor
Statistics or the views
of other as staff
members.

An experimental Consumer
Price Index for the poor

Experimental Laspeyres, Paasche, and Fisher price indexes
are derived for poor consumers; the minimal differences
between these indexes and the Consumer Price Index

for All Urban Consumers (cpi-u) in the calculation

of poverty rates indicate that the poor

and the general population face similar price trends

lach year, price inflation adjustments are
made for various Federal, State, and lo-
cal programs in the United States. Accord-
ing to the Congressional Research Service,’ ap-
proximately 80 benefit programs provide cash
and noncash aid, primarily to persons with lim-
ited incomes. The combined cost of these pro-
grams in fiscal year 1994 was almost $345 bil-
lion, up 11 percent from the previous fiscal year.
Federal funds accounted for nearly 72 percent of
total spending.
The benefit levels and eligibility guidelines for
a substantial number of these programs are ad-
justed annually for inflation.” For example, food
stamp levels are adjusted each October for
changes in the Consumer Price Index for All Ur-
ban Consumers (cri-u) for food. Similarly, the
U.S. Department of Health and Human Services
poverty guidelines (or some adaptation of them)?
are adjusted each year using the cpi-u for all
items.’ All of these adjustments can lead to sig-
nificant changes in eligibility requirements for
the receipt of government benefits and in in-
creases or decreases in benefit levels, thereby
directly influencing government budgets.
Perhaps one of the most visible results of ad-
justing for price inflation with respect to a spe-
cific group in the population is in the use of the
CPI-U to update the official poverty thresholds
published by the Bureau of the Census. Since
1969, the cri-u has been used for this purpose;
prior to that date, the U.S. Department of

32. Monthly Labor Review September 1996

Agriculture’s Economy Food Plan cost index was
used.5 These thresholds are generally used for
Statistical purposes—for example, to determine
the number of persons or families that are poor.
Poverty rates, based on the use of the official
poverty thresholds, are sometimes used to target
government funds to poor areas.

In this article, we produce an experimental
price index for poor consumers in order to deter-
mine whether such an index would be lower than,
higher than, or equal to the current crt-v. If a sig-
nificant difference results, this could have major
implications for funding and eligibility require-
ments for poverty programs, as well as for gov-
ernment budgeting and decisionmaking in gen-
eral. Requests for price indexes for specific sub-
populations were made as early as 1958, when
Kenneth Arrow noted that lower income people
are likely to have consumption patterns that dif-
fer from those of higher income people; for ex-
ample, lower income people spend more of their
budget, on average, on necessities than they
spend on luxuries. In fact, Arrow states that
“there should be a separate cost-of-living index
number for each income level.”* Whether such
price indexes should really be used to adjust pov-
erty thresholds or eligibility requirements is not
addressed in our study, although adjustments us-
ing them are made for expository purposes.

In this article, we use internal sts Consumer
Expenditure (ce) Survey data from 1982-84 and
1992-94 to obtain expenditure weights for the



CPI for the Poor

Benefits: A Price Index for the Elderly,” Public Finance Quar-
terly, October 1985, pp. 436-49; and Dale Jorgenson and Dan Slesnick, “In-
dividual and Social Cost-of-Living Indexes,” in W. Erwin Diewert and Claude
Montmarquette, eds., Price Level Measurement (Ottawa, Ont., Canada, Sta-
tistics Canada, 1983), pp. 241-323,

"The MERGE file is a statistical match of responses from the Census
Bureau's March 1971 Current Population Survey, a uniform sample of about
50,000 households, and the Internal Revenue Service's 1970 Individual In-
come Tax Model File, a stratified sample of 100,000 personal income tax
returns, including a 100-percent sample of returns with adjusted gross in-
come greater than $200,000. (Both samples are without individual identify-
ing information.) The Merce file has detailed demographic information, to-
gether with complete data on income and income taxes, permitting precise
computation of the latter and accurate estimation of ail other taxes. (See
Joseph Minarik, “The Size Distribution of Income During Inflation,” Re-
view of Income and Wealth, vol. 25, 1979, pp. 377-392, for more details.

'* Minarik, “Size Distribution of Income,” p. 389.

¥ Joseph Minarik, “Inflation in the Necessities?” Brookings Bulletin,
Spring 1980, pp. 8-10.

® See Rebecca M. Blank and Alan S. Blinder, “Macroeconomics, Income
Distribution, and Poverty,” in Shelton Danzinger and Daniel Weinberg, eds.,
Fighting Poverty (Cambridge, Ma, Harvard University Press, 1986); Robinson
G. Hollister, Jr., and John L. Palmer, “The Impact of Inflation on the Poor,”
in K. E. Boulding and M. Pfaff, eds., Redistribution to the Rich and the Poor
(Belmont, ca, Wadsworth, 1972); and Thad W. Mirer, “The Distributive Im-
pact on Purchasing Power of Inflation during Price Controls, Quarterly Re-
view of Economics and Business, vol. 15, 1975, pp. 93-96.

2 Daniel H, Weinberg, Implications of Mismeasuring the Consumer Price
Index for Poverty Statistics, Technical Analysis Paper No. 34 (Department
of Health and Human Services, 1987); and John C. Weicher, “Mismeasuring
Poverty and Progress,” American Enterprise Institute, mimeo., 1986.

TM See Citro and Michael, Measuring Poverty.

® The authors thank John Greenlees for pointing out the distinction be-
tween the crr-v prior to 1983 and the ci-u-x1.

* Weinberg, Implications of Mismeasuring. p. 4.

5 We used relative prices for total food for our analysis; the official cet-u
is based on detailed information about food from the Diary portion of the ce
Survey. This difference in methodology seems to make very little difference
in the expenditure share used for this study compared with the official index.

% The sociodemographic characteristics and population weights of con-
‘sumer units are also from the fifth interview.

7 For a definition of “complete income reporter,” see Consumer Expend-
iture Survey, 1992-93,

% For the actual poverty thresholds in those years, see Poverty in the
United States: 1984, Series P-60 (Bureau of the Census, 1985), table A-2.

® The ce Survey publication definition of total expenditures is used in
this article. According to the definition, these expenditures consist of the
transaction costs, including excise and sales taxes, of goods and services
acquired during the period covered by the interview. They include expendi-
tures for gifts, but exclude purchases or portions of purchases directly as-
signable to business purposes. Also excluded are periodic credit or install-
ment payments on goods or services already acquired, with the exception of
payments for housing that has been purchased. For such housing, all ex-
Penses, including mortgage interest repayments, but not mortgage principal
‘ones are included in the total. (See Consumer Expenditure Survey,

® See Passero, “Families receiving public assistance,” for a more com-
plete definition of “program participants.”
3 See the three Census Bureau publications titled “Characteristics of the

Population Below the Poverty Level,” for the years 1982, 1983, and 1984.
The publications are from series P~60 and are numbered 144, 147, and 152.

” The figures in table 1 are similar to those in Passero, “Families receiv-
ing public assistance.”

* This rate is calculated from tables published in the Census Bureau's

42 Monthly Labor Review September 1996

Poverty in the United States: 1984, data for 1984 are not comparable.

John M, Rogers and Maureen B. Gray, “ce data: quintiles of income
versus quintiles of outlays,” Monthly Labor Review, December 1994, pp.
32-37; outlays are simply total expenditures plus principal payments on home
mortgages and financed vehicles, minus the purchase price of financed
vehicles.

35 See also Patrick McGregor and Vani K. Borooah, “Is Low Spending or
Low Income a Better Indicator of Whether or Not a Household is Poor:
Some Results From the 1985 Family Expenditure Survey,” Journal of So-
cial Policy, vol, 21, no. 1, 1992, pp. 53-69. Using data from the United
Kingdom, these authors, too, suggest that low spending is a better indicator
of poverty than low income is.

% ats Handbook of Methods, Bulletin 2414 (Bureau of Labor Statistics,
September 1992), p. 176.

"See Bert M. Balk, “On Calculating Cost-of-Living Index Numbers for
Arbitrary Income Levels,” Econometrica, vol. 58, January 1990, pp. 75-92.

TM See W. Erwin Diewert, “The Theory of the Cost-of-Living Index and
the Measurement of Welfare Change,” in W. Erwin Diewert and Claude
Montmarquette, ed., Price Level Measurement (Ottawa, Ont, Statistics
Canada, 1983), pp. 163-233.

%® Substitution bias is inherent in fixed-weight index number formulas
when elasticities of substitution between goods are not zero. As relative prices
change, consumers will substitute relatively cheaper goods for those which
become more expensive. Because the Laspeyres index continues to evaluate
Price changes with respect to a fixed market basket, ignoring this substitu-
tion behavior, it overstates the true changes in the cost of living experienced
by households. Index formulas, such as Fisher's, are closer to the true cost-
of-living measure because they weight each good’s price change in terms of
both the reference- and comparison-period market basket.

“ Categories were aggregated because only the Interview portion of the
survey was used for this study, whereas the official crt uses the detailed in-
formation on expenditures from the Diary portion of the survey as well. For
a detailed list of the categories used in our study, see footnotes 2-8 of table 4,
Note that, in contrast to the measure of expenditures for shelter used in the ce
Survey publication definition, rental equivalence is used for the cPI-v.

“' For a derivation of these weights, see J. L. Marcoot and R. C. Bahr,
“The revised Consumer Price Index: changes in definitions and availabil-
ity, Monthly Labor Review, July 1986, pp. 15-23.

Although the Laspeyres and Paasche indexes are not, strictly speaking,
upper and lower bounds, respectively, on the same true cost-of-living index,
itis usually expected that the Laspeyres index will overstate, and the Paasche
index will understate, the true change in the cost of living. For a detailed
discussion of the properties of the Laspeyres and Paasche indexes, see
Diewert, “Cost-of-Living Index and Welfare Change.”

“ Michael, “Variation in the Rate of Inflation.”

“ See P. J. Lloyd, “Substitution Effects and Biases in Nontrue Price Indi-
ces,” American Economic Review, June 1975, pp. 301-13.

“S See Kokoski, Consumer Price Indices.

“ Balk, “Cost-of-Living Index Numbers,” p. 76.

“ With income as the measure of resources, the poverty rate for the met-
ropolitan population over the 1992-94 period, using the Census Bureau fig-
ures, is 14.3 percent.

“ According to the Bureau of the Census, approximately 20 percent of
the total U.S. population lived in nonmetropolitan areas in 1994 (see
‘www.census.gov, PPL-27, table 2: “Resident Population and Change for
Metropolitan Areas in the United States, April 1, 1990 to July 1, 1994”), and
16 percent of the poor lived in nonmetropolitan areas that year (see table 8,
“Poverty of Persons, by Residence,” from www.census.gov). “Metropoli-
tan” and “urban” are defined slightly differently by the Bureau of Labor
Statistics and the Census Bureau.

© See Citro and Michael, Measuring Poverty; Ruggles, Drawing the Line;
and Mary Kokoski, Patrick Cardiff, and Brent Moulton, “Interarea Price In-
dices for Consumer Goods and Services: An Hedonic Approach Using crt
Data,” ats Working Paper 256 (Bureau of Labor Statistics, July 1994).


[chart 1 | Consumer Prices Indexes for selected commodity groups, 1984-94

Index
(1982-84 = 100)

220
Food and beverages
200 | “Mousina
Apparel and upkeep .
480 |- Transportation . | s80
Medical care
160 | Entertainment + 160
Other commodities
140 All commodities + 140
120 |- -| 120
——
100 |- | 100
n 1 ! L n L ! 1 1 !
1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994

SOURCE: Monthly Labor Review, May 1995, table 33, p. 110; September 1995, table 33, p. 94.

nos 2 differences between Inflation rates for the poor and the overall Inflation rate, using Laspeyres
xeS

Percent Percent
1 1
Income poor
Expenditure poor
os |- ~~ + 05
0 bw BN °
~ ~
-e sy -
~ -7 ” x
Se Loe x
05 + ~ ~ 405
. ~
N
~
4 ~ 4a
| .
15 1 1 1 1 1 1 ids

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994
Nore: Zero line represents Laspeyres index for all consumer units,

Monthly Labor Review September 1996 39



that quarter. Detailed expenditure data are collected at each
interview, while detailed income data are collected only in
the second and fifth interviews.

To obtain estimates of the poor population, the data from
consumer units interviewed between January 1982 and De-
cember 1984 were used. Only consumer units living in urban
areas were included in the sample. This approach is similar
to the official cr procedure of collecting prices only in urban
areas and using the base period of 1982-84. Consumer units
were selected for inclusion in the study sample if they par-
ticipated in the survey for at least two of the last four inter-
views and if they had a fifth interview. Using only those con-
sumer units with data for at least two quarters of expend-
itures yields better estimates of annual expenditures than does
using data from all consumer units, while keeping the sample
fairly representative.

To obtain annual expenditures, the quarterly expenditures
were aggregated over the quarters in which the consumer unit
participated in the survey and then were adjusted to annual
figures using the number of interviews that took place. For
example, the annual expenditures for a consumer unit with
two quarters of expenditures are twice the sum of the ex-
penditures for those two quarters. To get income and expend-
iture data to represent the same annual period, we used in-
come data from the fifth interview. Note that income is to-
tal cash income before taxes and does not include the cash
value of food stamps; this definition is used by the Bureau of
the Census in producing the official poverty statistics.

The poor population is defined in three alternative ways:

1. Income poor. Those consumer units identified by the
Bureau of Labor Statistics as complete income report-
ers”’and whose income is below the Census Bureau’s
poverty threshold (using the annual poverty thresholds
for 1982, 1983, and 1984 by age and family composi-
tion).7*

2. Expenditure poor: Those consumer units whose annu-
alized expenditures are below the annual poverty thresh-
olds.”

3. Program participants: Those consumer units which re-
ceived supplemental security income (ssi) or general
welfare (which encompasses other public assistance and
job-training grants, such as that for the Job Corps) in the
fifth interview, or which received food stamps, medic-
aid, or housing assistance in at least half of the quarters
covered by the interviews.”

Table 1 shows the demographic composition of the
weighted urban sample and each of the poor populations of
consumer units. The latter contain a much larger percentage
of single persons and single parents, and a much smaller per-
centage of married couples, than the overall population does.

These characteristics are similar to those of the poor popula-
tion of households examined by the Bureau of the Census.*!
The poor populations defined in table 1 also contain a larger
percentage of black households and older and younger house-
holds and a smaller percentage of homeowners. The majority
of the reference persons in poor consumer units do not have a
high school education. As expected, the program participa-
tion rate of poor households is higher for all programs.”

The poverty rates for consumer units are 14.1 percent for
the income poor, 11.9 percent for the expenditure poor, and
11.6 percent for program participants. For persons, the rates
are 15.1 percent, 12.6 percent, and 13.6 percent. The average
poverty rate for persons in metropolitan areas for the 1982-83
period, using Census Bureau figures, is 13.7 percent.

Table 2 presents the distribution of our weighted, annual-
ized, urban sample by the ratios of expenditures and income
to the poverty thresholds. While the majority of income poor
are also expenditure poor (and vice versa), many consumer
units are classified as poor under one of the two definitions,
but not the other. More than 75 percent ((7.3 + 3.4)/14.1) of
the income poor have expenditures that are less than 150 per-
cent of the poverty threshold, while more than 80 percent ((7.3
+ 2.5)/11.9) of the expenditure poor have income that is less
than 150 percent of the poverty threshold. John M. Rogers
and Maureen B. Gray find similar results by examining the
quintiles defined by income and expenditure outlays: sixty
percent of the first quintile of either income or outlays are
also in the first quintile using the other measure. They report,
in addition, that 14 percent of the consumer units ranked in
the first income quintile are in the top three outlay quintiles
(with 2.5 percent in the top outlay quintile), while only 0.1
percent of those in the first outlay quintile are in the top in-
come quintile. In a similar manner, table 2 also shows that
there are more income poor who have expenditures greater
than 200 percent of the poverty threshold (2.3 percent) than
there are expenditure poor who have high income (0.3 per-
cent). This suggests that, in the use of ce Survey data, low
expenditures may be a better proxy of resources to identify
the poor population than low income is.>*

Table 3 presents a similar comparison for consumer units
that are program participants. Almost 70 percent of program
participants have income and expenditures less than 150 per-
cent of the poverty thresholds, and about 11 percent have in-
come and expenditures greater than twice the poverty thresh-
olds. Because many of the program eligibility requirements
for income are higher than the poverty thresholds, the latter
finding is not surprising.

Calculating a price index

The official U.S. crt is a measure of the average change in
prices paid by urban consumers for a fixed market basket

Monthly Labor Review September 1996 35



CPI for the Poor

experimental index for the elderly is due in large part to rela-
tively higher price increases over their research period for
specific categories, such as medical care, that represent a
larger relative proportion of the average older household’s
budget. However, as other researchers have found, the expe-
rience that this subgroup has had with inflation does not dif-
fer substantially from that of the general population.'®

Impact of inflation on selected subpopulations. The impact
of inflation on the size distribution of income was simulated
by Joseph Minarik using the Brookings 1970 MERGE file.'”
Minarik found that, because “low income households are
intensive food and fuel consumers,”" individuals living
in these households are more likely to be worse off than in-
dividuals living in other households if overal] inflation is
concentrated in food and fuel commodities. (Such a situa-
tion existed in the 1970s.) In another study, Minarik reported
that the prices of necessities over the 1970-79 period rose
slightly less than did the overall cr1."° Thus, if necessities
compose a larger share of the poor’s budget, then they would
experience a lower inflation rate relative to that of the gen-
eral population.

Other researchers also have examined the price inflation
experienced by those with lower incomes. Rebecca M. Blank
and Alan S. Blinder conclude, from their review of the litera-
ture and their own research, that inflation rates for the poor
are similar to inflation rates for the whole population. They
report that the prices of commodities the poor buy did not
systematically rise faster than did prices in general during the
period from 1947 to 1982.”

Updating the poverty thresholds, The impact of using dif-
ferent indexes to update the official U.S. poverty line was
discussed recently by Daniel H. Weinberg and John C.
Weicher.”! The National Research Council also has exam-
ined this issue.” Weinberg and Weicher chose two different
BLS price indexes and used them to adjust the official poverty
thresholds; one was the official cri-u produced by the Bu-
reau prior to 1983, and the other was an experimental index
known as the cri-u-x1. Before 1983, the official cri-u had
weights for the purchase prices of houses, mortgage interest
(the total interest expected to be paid over half the mortgage
term) for newly purchased homes, and various other compo-
nents (for example, property taxes) that are currently not
included in the crt market basket. The earlier measure over-
stated the cost of homeownership. To correct this problem,
the housing component of the official cri-u has been based
on a rental equivalence concept since 1983. In order for re-
searchers to compare earlier prices with those being produced
on the basis of the rental equivalence adjustment, the Bureau
developed the experimental cpt-u-x1 back to 1967. This in-
dex was based on the rental equivalence concept, although it

34 Monthly Labor Review September 1996

was never as rigorously computed as was the official cri-u.”

Weicher and Weinberg found that by 1981 the cri-U-x1 was
91 percent of the official cpi-u (before the rental equivalence
methodology was introduced). Weicher (as noted by
Weinberg) reported that “As the official cet overstated the
increases in prices for all consumers between 1967 and 1982,
so the official poverty thresholds, adjusted by the cri, over-
stated the increase in prices for the poor.”* Weinberg main-
tains that if the poverty thresholds had been adjusted with the
CPI-U-X1, poverty rates would have been substantially lower
than they officially were reported to be. He states that the
recessions during the 1967-85 period had a smaller effect on
poverty rates when the thresholds were updated using the
CPI-U-X1,

Inaddition, Weinberg reports that population groups would
have been affected differently according to the two indexes.
Using the cri-u-x1 did not significantly affect the trend in eld-
erly or nonelderly poverty compared to using the official cpt
of the period, although the poverty rates for both groups were
smaller when the cpi-u-x1 was applied. In contrast, the pov-
erty rates for families headed by women increased over the
period when the thresholds were updated using the cP!-u-xt.

For purposes of illustration, the National Research Coun-
cil produced poverty thresholds updated using different meth-
ods. The Council reports that if the poverty thresholds had
been updated by changes in the cost of the Department of
Agriculture’s Economy Food Plan, rather than the cr!-u, from
1963 to 1992, the resulting threshold for a two-adult, two-
child househoid would have been 92 percent of the
official poverty threshold. This relationship is quite similar
to that found by Weicher and Weinberg in their comparisons
of the thresholds updated using the cri-v, as against the
CPI-U-X1.

Identifying the poor

To identify the poor population, information on income and
expenditures, as well as demographic information, was used
from the Interview portion of the ce Survey.”* The data are
collected for the Bureau of Labor Statistics by the Bureau of
the Census and have been collected on a continuous basis
since 1980. Consumer units are interviewed once each quar-
ter for five consecutive quarters. Twenty percent of the sample
is replaced each quarter as consumer units that have com-
pleted their fifth interviews are succeeded by new consumer
units beginning their participation in the survey. The first in-
terview is a boundary-fixing interview to reduce telescoping;
thus, these data are not used for purposes of estimation. Be-
cause of the rotating panel design of the continuing survey, a
consumer unit may be in the sample from 1 to 5 times over a
five-quarter period. If a consumer unit misses an interview,
no attempt is made to reconstruct the expenditure data for



poor. Relative price data are from the pts Consumer Price
Index program for 1984 through 1994. Because price data
are collected just in urban areas,” the sample is composed of
urban consumers only (although the ce Survey is used to col-
lect data from consumers in urban and rural areas).

Three concepts of the poor are used to define the sample
from which the expenditure weights are derived: income
poor, expenditure poor, and program participant poor.* A con-
sumer unit? is identified as income poor or expenditure poor
if its income or expenditures, respectively, are below the offi-
cial Bureau of the Census poverty threshold.'° A consumer
unit is program participant poor if someone in the consumer
unit or the consumer unit itself participates in selected wel-
fare programs." (See the section titled “Identifying the poor”
for more information.)

Based on our study, we find there to be very little differ-
ence between the experimental consumer price indexes pro-
duced for the poor and the corresponding cri for the whole
sample. Using these experimental indexes, we derive pov-
erty rates that are only marginally different from rates based
on an index using expenditure weights for the total urban
population. We also calculate Fisher indexes, which are theo-
tetically closer to a true cost-of-living index and which em-
ploy more recent information on expenditures, The results
reveal that the Fisher indexes for the poor are much the same
as those for the whole urban cp1 sample.

We precede our actual analysis with a review of some re-
lated research in the next section. Following that, we define
and give descriptive statistics of the three populations of poor
consumer units. The third section presents the methodology
used in calculating the price indexes. The final section sets
out the results of our analysis and offers concluding remarks.

Related research

Several studies have focused on price indexes for specific
demographic groups within the U.S. population, including
the poor. Related studies have examined the impact of infla-
tion on low-income consumers, and a few have applied dif-
ferent price indexes to adjust poverty thresholds and analyzed
the impact of those adjustments on poverty rates. In this sec-
tion, we briefly review selected studies covering each of these
topics,

Price indexes for subpopulations. Using data on expendi-
tures, income, and prices for selected years from 1936 to
1955, Eleanor M. Snyder produced experimental indexes for
low- and high-income groups.'? She defined the groups in
terms of their incomes and the income elasticity of food com-
modities. Low-income items had a negative or zero elastic-
ity, middle-income items a moderate income elasticity, and
high-income items the highest income elasticity. Snyder’s

Laspeyres indexes for items with a negative or zero income
elasticity were noticeably larger than for items with a posi-
tive income elasticity, for the period 1936-55. She reported
that during recessions, the prices of inferior commodities and
other commodities considered to be of greater importance to
low-income groups (based on income shares) declined more
slowly, relative to the prices of commodities most important
to middle-income households. During periods of full employ-
ment and rising prices, the prices of “low-income” items rose,
but at a more rapid rate than did the prices of commodities
most likely purchased by higher income households. By con-
trast, Snyder’s Paasche indexes, based on data collected in
the 1955 survey of food expenditures conducted by the De-
partment of Agriculture, revealed no significant variation over
the income distribution,

More recent research has focused more broadly on sub-
population-based indexes. Robert Michael and Robert
Hagemann examined not only empirical differences in the
price indexes, for different groups, but also the statistical sig-
nificance of these differences.'? Both researchers constructed
Laspeyres indexes for each household in the ce Survey and
then regressed the index values on a set of variables for house-
hold demographic characteristics. Using the 1960-61 cE
Survey, Michael found some significant differences, but no
group in his study had consistently higher or lower price
changes than the sample as a whole. He discovered little cor-
relation over time in any household’s relative position in the
distribution of price index values. Both studies found that the
price index dispersion within each demographic group was
too great to make the between-group differences statistically
significant. While both found some evidence that poorer
households experienced higher inflation than higher income
households did, the results were not generally statistically
significant.

Mary Kokoski, who also investigated differences in true
cost-of-living indexes, as calculated by the superlative
‘Tornqvist formula, found few statistically significant results
as well.'* While the magnitudes of the differences were small
and insignificant, her study also showed a pattern of lower
than average inflation rates for households in either the up-
permost or the lowest quartile in 1980, with a base period of
1972.

Nathan Amble and Ken Stewart directed a research effort
at another important demographic group: the elderly.'*
They calculated an experimental price index based on the ex-
penditure patterns of elderly households in the ce Survey.
Their index rose somewhat more rapidly than did their refer-
ence cpt, but the statistical significance of this result is un-
known. Like the subset of households that qualify as poor,
the elderly subset of the ce Survey is a small sample, so there
is reason to suspect substantial sampling error. Amble and
Stewart show that the relatively higher inflation rate in their

Monthly Labor Review September 1996 33