Adjusting for Living Costs Can Change Who Is Considered
Poor
Adjusting Federal poverty
measures to account for geographic cost-of-living
differences reverses the rankings of metro and nonmetro
poverty.
Dean
Jolliffe
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The
prevalence of poverty has been greater
in nonmetro than metro areas in every
year since the 1960s when poverty rates
were first officially recorded. |
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Adjusting
the official poverty measure for cost-of-living
differences reverses the rankings of
metro and nonmetro poverty. |
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Such
a reversal could have important implications
for the geographic and demographic distribution
of Federal funding of poverty-based
programs. |
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In 1960, the Census Bureau began
recording poverty rates by area of residence across
the U.S. Every year since then, the prevalence of
poverty has been greater in nonmetropolitan (nonmetro)
areas than in metropolitan (metro) areas. During
the late 1960s, poverty in nonmetro areas was almost
twice as high as in metro areas. This difference
declined over time, and by the 1990s, the nonmetro
poverty rate was between 12 and 30 percent higher
than the metro rate. In 2003, 12.1 percent of the
metro population was poor, while the poverty rate
for nonmetro areas was 14.2 percent.
Poverty estimates figure prominently
in the distribution of Federal and State assistance
funds. More than 25 different Federal assistance
programs link their eligibility criteria in part
to poverty lines or rates. Given the higher rates
of nonmetro poverty and the link between program
eligibility and poverty, it follows that more Federal
assistance funds per capita are distributed in nonmetro
areas. For example, to receive food stamps, a household’s
income must be equal to or less than 130 percent
of the poverty line. In 2004, the Food Stamp Program
distributed more than $24 billion in program benefits,
and Current Population Survey data indicate that
per capita benefits were 32 percent higher in nonmetro
areas than metro areas. Overall, in 2001, the per
capita distribution of Federal funds for income
security programs was 17 percent higher in nonmetro
than in metro areas.
The National Academy of Sciences
has recommended several changes in how the Federal
Government measures poverty. ERS examined one of
these recommendations—adjusting for geographic
differences in the cost of living—and found
that such an adjustment would change the geographic
distribution of poverty. Currently, the official
Federal poverty thresholds assume that the cost
of living is the same over the entire U.S. However,
the Census Bureau has developed experimental poverty
measures that use rent data to create an index for
geographic differences in the cost of living. Using
this index to adjust for differences in the cost
of living reverses the ranking of metro and nonmetro
poverty.
Cost of Living Varies
Geographically
The major components of a low-income
household’s budget are housing, food, transportation,
and health care. The purpose of many assistance
programs is to boost the purchasing power of needy
Americans so they can purchase basic necessities
and attain a minimum standard of living. The cost
of purchasing many of the basic necessities—the
cost of living—varies across the U.S. For
Federal assistance programs to boost the purchasing
power of program participants by similar amounts,
regardless of where they live, it is necessary to
account for cost-of-living differences.
The Census Bureau has developed
a geographic cost-of-living index based on 2001
Fair Market Rent (FMR) data collected by the U.S.
Department of Housing and Urban Development (HUD).
FMR data provide full coverage of the U.S., including
metro and nonmetro areas, and they reflect the costs
of rent and utilities faced by lower income households
(see box, “How the Index Is
Constructed”). HUD produces annual estimates
for 354 metro areas and 2,350 nonmetro counties.
The cost-of-living index aggregates the FMR estimates
to 100 different price levels, one for metro and
one for nonmetro counties of each State plus the
District of Columbia (NJ and DC have no nonmetro
areas). For the index, metro counties are defined
as any county that (1) contains a city with a population
of at least 50,000, (2) has an urbanized area as
defined by the Census Bureau, or (3) is adjacent
to and economically tied to a metropolitan area.
The cost-of-living index is based
on data from 2001 and consists of two components—housing
and all other goods and services. The index assumes
that variation in the FMR data across the U.S. reflects
variation in housing costs for the poor. It also
assumes that the prices of all other goods and services
do not vary (see box, “What
the Index Does Not Measure”). Housing
is a critical component of the index because it
is both the largest budget item for poor families
and the most important source of cost-of-living
differences in the U.S. Following the recommendations
of the National Academy of Sciences, the index assigns
a weight of 44 percent for housing expenses and
56 percent for all other goods and services. If
the FMR data indicate that rents in a particular
area are 10 percent higher than the baseline, then
the cost of living in this area is assumed to be
4.4 percent higher than the baseline.
Adjusting for Living Costs
Reverses Poverty Rates
The data used in this article
are the 2001 cost-of-living index and the 1992-2003
March Supplement to the Current Population Survey
(CPS). CPS data are the basis for the official U.S.
poverty estimates and, in more recent years, provide
information on more than 80,000 families in each
year. The sample represents the civilian, noninstitutionalized
population and members of the Armed Forces living
either off base or with their families on base.
The reference period for income-related questions
is the preceding calendar year; therefore, the 1992-2003
CPS data provide poverty estimates for 1991 through
2002.
Income, following the Federal
definition of poverty, includes all pre-tax income
but does not include capital gains or noncash
benefits, such as public housing, Medicaid, or
food stamps. A person is poor if this measure
of income is less than thresholds set by the U.S.
Government. Poverty thresholds account for differences
in need by setting different thresholds for families
of varying sizes. So, for example, in 2001, a
three-person family consisting of two adults and
one child was poor if its family income was less
than $14,255.
One way to account for cost-of-living
differences is to adjust the poverty threshold
by the cost-of-living index. For example, the
index for metro Illinois is 1.08, which means
that the three-person family threshold of $14,255
would be increased by 8 percent to $15,395. The
index for nonmetro Florida is 0.90 which means
that the three-person poverty threshold would
decline to $12,830.
Following the official definition
of poverty, 11.1 percent of the metro population
was poor in 2001. For nonmetro areas, the poverty
rate was 14.2 percent—about 28 percent higher.
Once the poverty thresholds are adjusted using the
cost-of-living index, this ranking reverses. The
adjusted nonmetro poverty rate drops to 10.5 percent,
and the adjusted metro rate increases to 12.0 percent.
Where the official poverty rate indicates that the
incidence of poverty is 28 percent higher in nonmetro
areas, the poverty rate that is adjusted for cost-of-living
differences suggests that the incidence of poverty
is 12 percent lower in nonmetro areas.
The reversal of poverty rankings
is not unique to 2001. Using the 2001 cost-of-living
index for multiple years indicates that the reversal
holds for every year considered (1991-2002). The
use of the 2001 index assumes that the geographic
variation in prices over the last decade has been
somewhat stable. (This assumption is found to be
reasonable from examining earlier years of FMR data.)
In most of the years considered, the official nonmetro
poverty rate has been more than 15 percent higher
than the metro poverty rate. When adjusted for cost-of-living
differences, the nonmetro poverty estimates are
10-25 percent less than the metro estimates.
Nonmetro Elderly Affected the Most
Previous research indicates that
the nonmetro poor are somewhat older on average
and more likely to be retired, while the metro poor
are younger and more likely to be going to school.
In 2001, the average age of the poor living in nonmetro
areas was about 2 years greater than that of the
metro poor. Similarly, 25 percent of the nonmetro
poor were age 50 or older, compared with 20 percent
of the metro poor.
In 2001, child poverty rates were
higher in both metro and nonmetro areas than the
poverty rates for other age groups. Children also
comprised a greater share of the population of poor
people in both metro and nonmetro areas. Differences
in the age distribution of the poor across metro
and nonmetro areas are seen in adults. A greater
share of the metro poor falls in the age range of
18-40 years, while more of the nonmetro poor are
middle-aged and elderly.
Adjusting for cost-of-living differences
had a larger effect on the age composition of the
nonmetro poor than the metro poor. A greater proportion
of the nonmetro poor who are reclassified as nonpoor
following the cost-of-living adjustment (those with
incomes just below the poverty line) are older people.
Forty-two percent of the nonmetro poor who are reclassified
as nonpoor are over 40 years old. Among the metro
poor, 33 percent of those reclassified as nonpoor
are over 40.
Adjustment in Poverty
Measures Could Shift Program Funds
With no adjustment for cost-of-living
differences, the prevalence of poverty is consistently
higher in nonmetro than in metro areas. When the
index is used to adjust for cost-of-living differences,
poverty is higher in metro than in nonmetro areas.
The adjustments would reduce the nonmetro poverty
population in 2001 (and increase the metro poverty
population) by 1.9 million people. Given the large
number of Federal assistance programs that tie eligibility
criteria to poverty, adjusting the official definition
of poverty to incorporate cost-of-living differences
could have important implications for the distribution
of Federal funds. In particular, one would expect
to see more funds targeted to people living in metro
areas and fewer funds targeted to nonmetro areas.
Adjusting for cost-of-living differences
would also change the demographics of poverty. Currently,
the nonmetro poor are disproportionately elderly,
many of whom are living on fixed incomes near the
poverty line. Adjusting for differences in the cost
of living would result in reclassifying many of
these elderly poor as nonpoor. Of the 1.9 million
nonmetro poor who would be reclassified as nonpoor,
25 percent are age 60 or older. This adjustment
could significantly affect Federal programs, such
as Supplemental Security Income, Medicaid, the Child
and Adult Care Food Program, and the Commodity Supplemental
Food Program, as the number of elderly who qualify
for these programs would be reduced.
How the Index Is Constructed
The cost-of-living index
uses 2001 Fair Market Rent data, which are
collected by HUD to determine eligibility
of rental housing units for the Section 8
Housing Assistance Payments program. FMR data
estimate the cost of rent plus utilities at
the 40th percentile of reported rental expenditures
for standard-quality housing.
The index assumes that differences
in Fair Market Rents across the U.S. reflect
variation in the cost of shelter for low-income
families. But people need other goods besides
shelter, and the cost-of-living index accounts
for these needs by assuming that housing consumes
44 percent of expenditures for a low-income
family and that all other goods consume the
remaining 56 percent. The costs of these other
goods are assumed not to vary across the U.S.
The resulting index estimates differences
in the cost of living across the U.S. by taking
a weighted average of FMR (with a weight of
44 percent) and all other goods, which are
assumed not to vary in costs.
Just how accurately does
the index portray cost-of-living differences?
We don’t know, but we can examine whether
the findings hold if we were to change some
of the assumptions. One concern is that the
cost-of-living index assumes that prices of
all goods and services, other than housing,
do not vary geographically. This assumption
is unlikely to be accurate, but the U.S. has
no national price index to measure cost-of-living
differences across areas to correct it.
State-level analysis suggests
that the prices of housing and all other goods
are positively correlated. Or, in other words,
counties with high housing costs also tend
to be counties with high costs for other goods
and services. If this positive correlation
is true at the national level, then the reversal
of the poverty rankings reported here would
be amplified. Adjusted nonmetro poverty rates
would drop and metro poverty rates would increase
by even more than the rates presented here.
Alternatively, assuming that areas with high
costs of housing are areas with low costs
in all other goods would weaken the findings.
But the negative correlation between housing
costs and costs of all other goods would have
to be large (i.e., a coefficient of correlation
greater in magnitude than 0.2) for the findings
to disappear.
Another concern is that
the assumption that the cost of shelter plus
utilities makes up 44 percent of the budget
for a poor person might overstate housing
expenses. If we maintain the assumption of
no variation in the cost of nonhousing goods
but reduce the share of the index for housing
costs, then geographic variation in the cost
of living would be dampened. The change in
the budget share for housing, though, would
have to drop below 33 percent before the reversal
of the metro and nonmetro poverty rankings
would no longer hold.
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What the Index Does Not Measure
After housing, food and transportation
are the next largest expenses, each taking
about 15 percent of a poor family’s
budget. The 2001 cost-of-living index assumes
no variation across metro and nonmetro areas
in food and transportation costs, but ERS
research indicates otherwise.
Households in nonmetropolitan
areas report that they can, on average, meet
their basic food needs at a lower cost than
similar households in metropolitan areas can.
Using nationally representative data from
the CPS Food Security Supplements on how much
households say they would need to spend just
to meet their food needs, ERS researchers
developed and assessed cost-of-enough-food
indexes for 470 geographic areas. At the national
level, the research showed that, on average,
the cost of enough food is between 11 and
14 percent less for nonmetro households than
for otherwise similar households in metro
areas. Costs for nonmetro households vary
considerably across States.
In contrast, evidence suggests
that nonmetro residents face higher transportation
costs than individuals living in metro areas.
Slightly less than one-third of transportation
costs for a poor family consist of expenditures
on gasoline. According to data from the Census
Bureau and the U.S. Department of Energy,
rural households with vehicles consumed nearly
40 percent more gasoline and drove almost
a third more vehicle-miles than urban households
in 2001. Rural residential vehicles also tend
to be less fuel efficient than their urban
counterparts—averaging 19.5 vs. 20.5
miles per gallon in 2001. Nonmetro counties
located near major metro areas and those located
in mountainous areas, such as in Appalachia,
have among the longest commutes in America.
Public transportation may
help to meet the mobility needs of carless
individuals and can also help to offset the
higher transportation costs of nonmetro areas.
However, significant gaps exist in the nonmetro
transit network, with about 4 out of 10 nonmetro
counties having no public transportation services
at all, according to the Community Transportation
Association of America. Even in nonmetro counties
offering transit service, 28 percent offer
only limited service (less than 25 trips taken
each year per carless household). Lack of
access to public transportation can force
residents to rely on costlier taxi services.
While the cost-of-enough-food
indexes suggest that the 2001 cost-of-living
index understates nonmetro-metro differences
in living costs, evidence on transportation
costs suggests that the index overstates differences.
The size of the bias in the index from ignoring
differences in transportation costs is about
the same as from ignoring differences in food
costs, which suggests that the net effect
is small. With housing accounting for more
than twice the budget share of either food
or transportation, the small net effect is
unlikely to alter this article’s findings.
Dennis
Brown (transportation)
Ephraim
Leibtag (food)
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