Poverty in the United States: 2013
Thomas Gabe
Specialist in Social Policy
January 29, 2015
Congressional Research Service
7-5700
www.crs.gov
RL33069


Poverty in the United States: 2013

Summary
In 2013, 45.3 million people were counted as poor in the United States under the official poverty
measure—a number statistically unchanged from the 46.5 million people estimated as poor in
2012. The poverty rate, or percent of the population considered poor under the official definition,
was reported at 14.5% in 2013, a statistically significant drop from the estimated 15.0% in 2012.
Poverty in the United States increased markedly over the 2007-2010 period, in tandem with the
economic recession (officially marked as running from December 2007 to June 2009), and
remained unchanged at a post-recession high for three years (15.1% in 2010, and 15.0% in both
2011 and 2012). The 2013 poverty rate of 14.5% remains above a 2006 pre-recession low of
12.3%, and well above an historic low rate of 11.3% attained in 2000 (a rate statistically tied with
a previous low of 11.1% in 1973).
The incidence of poverty varies widely across the population according to age, education, labor
force attachment, family living arrangements, and area of residence, among other factors. Under
the official poverty definition, an average family of four was considered poor in 2013 if its pre-
tax cash income for the year was below $23,834.
The measure of poverty currently in use was developed some 50 years ago, and was adopted as
the “official” U.S. statistical measure of poverty in 1969. Except for minor technical changes, and
adjustments for price changes in the economy, the “poverty line” (i.e., the income thresholds by
which families or individuals with incomes that fall below are deemed to be poor) is the same as
that developed nearly a half century ago, reflecting a notion of economic need based on living
standards that prevailed in the mid-1950s.
Moreover, poverty as it is currently measured only counts families’ and individuals’ pre-tax
money income against the poverty line in determining whether or not they are poor. In-kind
benefits, such as benefits under the Supplemental Nutrition Assistance Program (SNAP, formerly
named the Food Stamp program) and housing assistance, are not accounted for under the
“official” poverty definition, nor are the effects of taxes or tax credits, such as the Earned Income
Tax Credit (EITC) or Child Tax Credit (CTC). In this sense, the “official” measure fails to capture
the effects of a variety of programs and policies specifically designed to address income poverty.
A congressionally commissioned study conducted by a National Academy of Sciences (NAS)
panel of experts recommended, some 20 years ago, that a new U.S. poverty measure be
developed, offering a number of specific recommendations. The Census Bureau, in partnership
with the Bureau of Labor Statistics (BLS), has developed a Supplemental Poverty Measure
(SPM) designed to implement many of the NAS panel recommendations. The SPM is to be
considered a “research” measure, to supplement the “official” poverty measure. Guided by new
research, the Census Bureau and BLS intend to improve the SPM over time. The “official”
statistical poverty measure will continue to be used by programs that use it as the basis for
allocating funds under formula and matching grant programs. The Department of Health and
Human Services (HHS) will continue to issue poverty income guidelines derived from “official”
Census Bureau poverty thresholds. HHS poverty guidelines are used in determining individual
and family income eligibility under a number of federal and state programs. Estimates from the
SPM differ from the “official” poverty measure and are presented in a final section of this report.

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Poverty in the United States: 2013

Contents
Trends in Poverty ............................................................................................................................. 1
The U.S. “Official” Definition of Poverty ....................................................................................... 2
Poverty among Selected Groups ...................................................................................................... 6
Racial and Ethnic Minorities ..................................................................................................... 6
Nativity and Citizenship Status ................................................................................................. 6
Children ..................................................................................................................................... 6
Adults with Low Education, Unemployment, or Disability ...................................................... 8
The Aged ................................................................................................................................... 9
Receipt of Need-Tested Assistance Among the Poor ....................................................................... 9
The Geography of Poverty ............................................................................................................... 9
Poverty in Metropolitan and Nonmetropolitan Areas, Center Cities, and Suburbs ................. 10
Poverty by Region ................................................................................................................... 10
State Poverty Rates .................................................................................................................. 10
Change in State Poverty Rates: 2002-2013 ............................................................................. 14
Poverty Rates by Metropolitan Area ....................................................................................... 20
Congressional District Poverty Estimates ............................................................................... 22
“Neighborhood” Poverty—Poverty Areas and Areas of Concentrated and Extreme
Poverty ................................................................................................................................. 23
The Research Supplemental Poverty Measure .............................................................................. 25
Poverty Thresholds .................................................................................................................. 29
SPM Poverty Thresholds ................................................................................................... 29
Resources and Expenses Included in the SPM ........................................................................ 30
Poverty Estimates Under the Research SPM Compared to the “Official” Measure ................ 31
Poverty by Age .................................................................................................................. 31
Poverty by Type of Economic Unit ................................................................................... 32
Poverty by Region ............................................................................................................. 34
Poverty by Residence ........................................................................................................ 35
Poverty by State ................................................................................................................ 36
Marginal Effects of Counting Specified Resources and Expenses on Poverty
under the SPM ................................................................................................................ 41
Distribution of the Population by Ratio of Income/Resources Relative to Poverty .......... 42
Discussion................................................................................................................................ 44

Figures
Figure 1. Trend in Poverty Rate and Number of Poor Persons: 1959-2013, and
Unemployment Rate from January 1959 through August 2014 ................................................... 4
Figure 2. U.S. Poverty Rates by Age Group, 1959-2013 ................................................................. 5
Figure 3. Child Poverty Rates by Family Living Arrangement, Race and Hispanic Origin,
2013 .............................................................................................................................................. 7
Figure 4. Composition of Children, by Family Type, Race and Hispanic Origin, 2013 .................. 8
Figure 5. Percentage of People in Poverty in the Past 12 Months by
State and Puerto Rico: 2013 ....................................................................................................... 11
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Poverty in the United States: 2013

Figure 6. Poverty Rates for the 50 States and the District of Columbia: 2013 American
Community Survey (ACS) Data ................................................................................................. 13
Figure 7. Distribution of Poor People by Race and Hispanic Origin, by Level of
Neighborhood (Census Tract) Poverty, 2009-2013 .................................................................... 24
Figure 8. Poverty Thresholds Under the “Official” Measure and the Research
Supplemental Poverty Measure for Units with Two Adults and Two Children: 2013 ................ 30
Figure 9. Poverty Rates Under the “Official”* and Research Supplemental Poverty
Measures, by Age: 2013 ............................................................................................................. 32
Figure 10. Poverty Rates Under the “Official”* and Research Supplemental Poverty
Measures, by Type of Economic Unit: 2013 .............................................................................. 34
Figure 11. Poverty Rates Under the “Official”* and Research Supplemental Poverty
Measures, by Region: 2013 ........................................................................................................ 35
Figure 12. Poverty Rates Under the “Official”* and Research Supplemental Poverty
Measures, by Residence: 2013 ................................................................................................... 36
Figure 13. Difference in Poverty Rates by State Using the “Official”* Measure and the
SPM: Three-Year Average 2011-2013 ........................................................................................ 37
Figure 14. Poverty Rates by State Using the “Official”* Measure and the SPM: Three-
Year Average 2010-2013............................................................................................................. 39
Figure 15. Poverty Rates by State Using the “Official”* Measure and the SPM: Three-
Year Average 2010-2013............................................................................................................. 40
Figure 16. Percentage Point Change in Poverty Rates Attributable to Selected Income and
Expenditure Elements Under the Research Supplemental Poverty Measure, by Age
Group: 2013 ................................................................................................................................ 42
Figure 17. Distribution of the Population by Income/Resources to Poverty Ratios Under
the “Official”* and Research Supplemental Poverty Measures, by Age Group: 2013 ............... 43

Tables
Table 1. Poverty Rates for the 50 States and the District of Columbia, 2002 to 2013
Estimates from the American Community Survey (ACS) .......................................................... 16
Table 2. Large Metropolitan Areas Among Those with the Lowest Poverty Rates: 2013 ............. 20
Table 3. Large Metropolitan Areas Among Those with the Highest Poverty Rates: 2013 ............ 21
Table 4. Smaller Metropolitan Areas Among Those with the Lowest Poverty Rates: 2013 .......... 21
Table 5. Smaller Metropolitan Areas Among Those with the Highest Poverty Rates: 2013 ......... 22
Table 6. Poverty Measure Concepts Under “Official” and Supplemental Measures ..................... 26
Table A-1. Poverty Rates (Percent Poor) for Selected Groups, 1959-2013 ................................... 45
Table B-1. Metropolitan Area Poverty: 2013 ................................................................................. 47
Table C-1. Poverty by Congressional District: 2013 ..................................................................... 60

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Appendixes
Appendix A. U.S. Poverty Statistics: 1959-2013 ........................................................................... 45
Appendix B. Metropolitan Area Poverty Estimates ....................................................................... 47
Appendix C. Poverty Estimates by Congressional District ........................................................... 60

Contacts
Author Contact Information........................................................................................................... 76

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Poverty in the United States: 2013

Trends in Poverty1
In 2013, the official U.S. poverty rate was 14.5%, compared to 15.0% in 2012, and marked the
first statistically significant drop in the rate since 2006. In 2013, 45.3 million persons were
estimated as having income below the official poverty line, a number statistically unchanged from
the estimated 46.5 million poor in 2012. (See Figure 1.)
Figure 1 shows a clear relationship between poverty and the economy. The level of poverty tends
to follow the economic cycle quite closely, tending to rise when the economy is faltering and fall
when the economy is in sustained growth.
The poverty rate increased markedly over the past decade, in part a response to two economic
recessions (periods marked in red). A strong economy during most of the 1990s is generally
credited with the declines in poverty that occurred over the latter half of that decade, resulting in a
record-tying, historic low poverty rate of 11.3% in 2000 (a rate statistically tied with the previous
lowest recorded rate of 11.1% in 1973). The poverty rate increased each year from 2001 through
2004, a trend generally attributed to economic recession (March 2001 to November 2001), and
failed to recede appreciably before the onset of the December 2007 recession. This most recent
recession, which officially ended in June 2009, was the longest recorded (18 months) in the post-
World War II period.2 Over the course of the most recent recession, the unemployment rate
increased from 4.9% (January 2008) to 7.2% (December 2008), and continued to rise over most
of 2009, peaking at 10.0% in October of that year. Even as the economy has been recovering,
poverty has remained well above pre-recessionary levels. Although the unemployment rate has
generally been falling since late 2009, it has not been until this past year that we have seen a
marked (statistically significant) decline in the official poverty rate. That the unemployment rate
has continued to fall over 2014 suggests that poverty levels are likely to fall in 2014. Poverty
statistics for 2014 poverty will be issued in the late summer of 2015. The recession especially
affected non-aged adults (persons age 18 to 64) and children. (See Figure 2.) The poverty rate of
non-aged adults reached 13.8% in 2010, the highest it has been since the early 1960s.3 In 2013 the
non-aged poverty rate of 13.6% remained statistically unchanged from rates seen in the prior
three years. The poverty rate for non-aged adults will need to fall to 10.8% to reach its 2006 pre-
recession level.
The 2013 poverty data provide one encouraging sign with respect to children. Both the estimated
number of poor children and their poverty rate fell from 2012 to 2013. In 2013, the number of
poor children fell by an estimated 1.3 million (15.4 million in 2012 to 14.1 million in 2013), and
their poverty rate fell from 21.3% in 2012 to 19.5% in 2013. The 2013 child poverty rate is still
well above its pre-recession low of 16.9% (2006). Child poverty appears to be especially sensitive
to economic cycles, as it often takes two working parents to support a family, and a loss of work
by one may put the family at risk of falling into poverty.4 Moreover, roughly one-third of all

1 Supporting data are based on the following: U.S. Census Bureau, Income and Poverty in the United States: 2013;
Current Population Report No. P60-249, September 2014; and unpublished Census Bureau tables, available on the
Internet at http://www.census.gov/hhes/www/poverty/data/incpovhlth/2013/index.html.
2 Periods of recession are officially defined by the National Bureau of Economic Research (NBER) Business Cycle
Dating Committee. See http://www.nber.org/cycles/main.html.
3 The poverty rate of non-aged adults was 17.0% in 1959. Comparable estimates are not available from 1960 through
1965. By 1966, the non-aged poverty rate stood at 10.5%. See Table A-1.
4 CRS Report RL33615, Parents’ Work and Family Economic Well-Being, by Thomas Gabe and Gene Falk.
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children in the country live with only one parent, making them even more prone to falling into
poverty when the economy falters.
In 2013, the aged poverty rate (9.5%) was statistically unchanged from 2012, although the
number of poor rose by an estimated 305,000 (from 3.9 million in 2012 to 4.2 million in 2013). In
spite of the recession, the aged poverty rate remains near an historic low level. The longer-term
secular trend in poverty has been affected by changes in household and family composition and
by government income security and transfer programs. In 1959, over one-third (35.2%) of
persons age 65 and over were poor, a rate well above that of children (26.9%). Social Security, in
combination with a maturing pension system, has helped greatly to reduce the incidence of
poverty among the aged over the years, and as recent evidence seems to show, it has helped
protect them during the economic downturn.
The U.S. “Official” Definition of Poverty5
The Census Bureau’s poverty thresholds form the basis for statistical estimates of poverty in the
United States.6 The thresholds reflect crude estimates of the amount of money individuals or
families, of various size and composition, need per year to purchase a basket of goods and
services deemed as “minimally adequate,” according to the living standards of the early 1960s.
The thresholds are updated each year for changes in consumer prices. In 2013, for example, the
average poverty threshold for an individual living alone was $11,888; for a two-person family,
$15,142; and for a family of four, $23,834.7
The current official U.S. poverty measure was developed in the early 1960s using data available
at the time. It was based on the concept of a minimal standard of food consumption, derived from
research that used data from the U.S. Department of Agriculture’s (USDA’s) 1955 Food
Consumption Survey. That research showed that the average U.S. family spent one-third of its
pre-tax income on food. A standard of food adequacy was set by pricing out the USDA’s
Economy Food Plan—a bare-bones plan designed to provide a healthy diet for a temporary period
when funds are low. An overall poverty income level was then set by multiplying the food plan by
three, to correspond to the findings from the 1955 USDA Survey that an average family spent
one-third of its pre-tax income on food and two-thirds on everything else.
The “official” U.S. poverty measure8 has changed little since it was originally adopted in 1969,
with the exception of annual adjustments for overall price changes in the economy, as measured
by the Consumer Price Index for all Urban Consumers (CPI-U). Thus, the poverty line reflects a

5 For a more complete discussion of the U.S. poverty measure, see CRS Report R41187, Poverty Measurement in the
United States: History, Current Practice, and Proposed Changes
, by Thomas Gabe.
6 The Department of Health and Human Services (HHS) releases poverty income guidelines that are derived directly
from Census poverty thresholds. These guidelines, a simplified approximation of the Census poverty thresholds, are
used by HHS and other federal agencies for administering programs, particularly for determining program eligibility.
For current guidelines and methods for their computation, see http://aspe.hhs.gov/poverty/index.shtml.
7 See http://www.census.gov/hhes/www/poverty/data/threshld/index.html.
8 The poverty measure was adopted as the “official poverty measure” by a directive issued in 1969 by the Bureau of the
Budget, now the Office of Management and Budget (OMB). The directive was revised in 1978 to include revisions to
poverty thresholds and procedures for updating thresholds for inflation using the Consumer Price Index (CPI). See OMB
Statistical Policy Directive 14, available on the Internet at http://www.census.gov/hhes/povmeas/methodology/
ombdir14.html.
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measure of economic need based on living standards that prevailed in the mid-1950s. It is often
characterized as an “absolute” poverty measure, in that it is not adjusted to reflect changes in
needs associated with improved standards of living that have occurred over the decades since the
measure was first developed. If the same basic methodology developed in the early 1960s was
applied today, the poverty thresholds would be over three times higher than the current
thresholds.9
Persons are considered poor, for statistical purposes, if their family’s countable money income is
below its corresponding poverty threshold. Annual poverty estimates are based on a Census
Bureau household survey (Annual Social and Economic Supplement to the Current Population
Survey, CPS/ASEC, conducted February through April). The official definition of poverty counts
most sources of money income received by families during the prior year (e.g., earnings, social
security, pensions, cash public assistance, interest and dividends, alimony, and child support,
among others). For purposes of officially counting the poor, noncash benefits (such as the value
of Medicare and Medicaid, public housing, or employer provided health care) and “near cash”
benefits (e.g., food stamps, renamed Supplemental Assistance Nutrition (SNAP) benefits
beginning in FY2009) are not counted as income, nor are tax payments subtracted from income,
nor are tax credits added (e.g., Earned Income Tax Credit (EITC)). Many believe that these and
other benefits should be included in a poverty measure so as to better reflect the effects of
government programs on poverty.
The Census Bureau, in partnership with the Bureau of Labor Statistics (BLS), has recently
released a Supplemental Poverty Measure (SPM), designed to address many of the perceived
flaws of the “official” measure. The SPM is discussed in a separate section at the end this report
(see “The Research Supplemental Poverty Measure”).

9 Based on U.S. Department of Labor Bureau of Labor Statistics Consumer Expenditure Survey data, in 2013 the
average family spent an estimated 10.3% of pre-tax income on food (including food consumed at home and away from
home), as opposed to one-third in the mid-1950s. This implies that the multiplier for updating poverty thresholds based
on food consumption would be 9.7 (i.e., 1/0.103), or 3.2 times the multiplier of 3 subsumed under poverty thresholds
developed in the 1960s. Author’s calculations from http://www.bls.gov/cex/2013/aggregate/age.pdf.
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Figure 1. Trend in Poverty Rate and Number of Poor Persons: 1959-2013,
and Unemployment Rate from January 1959 through August 2014
(recessionary periods marked in red)

Source: Prepared by the Congressional Research Service (CRS) using U.S. Census Bureau, “Income and Poverty United States: 2013,”
Table B-1, Current Population Report P60-249, September 2014, available on the Internet at http://www.census.gov/content/dam/Census/library/publications/2014/demo/
p60-249.pdf. Unemployment rates are available on the Internet at http://www.bls.gov/cps/. Recessionary periods defined by National Bureau of Economic Research Business
Cycle Dating Committee: http://www.nber.org/cycles/main.html.
CRS-4



Figure 2. U.S. Poverty Rates by Age Group, 1959-2013

Source: Prepared by the Congressional Research Service using U.S. Census Bureau, “Income and Poverty in the United States: 2013,” Tables
B-1 and B-2, Current Population Report P60-249, September 2014, available on the Internet at http://www.census.gov/content/dam/Census/library/publications/2014/demo/
p60-249.pdf.
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Poverty in the United States: 2013

Poverty among Selected Groups
Even during periods of general prosperity, poverty is concentrated among certain groups and
in certain areas. Minorities; women and children; the very old; the unemployed; and those with
low levels of educational attainment, low skills, or disability, among others, are especially prone
to poverty.
Racial and Ethnic Minorities10
The incidence of poverty among African Americans and Hispanics exceeds that of whites by
several times. In 2013, 27.2% of blacks (11.0 million) and 23.5% of Hispanics (12.7 million) had
incomes below poverty, compared to 9.6% of non-Hispanic whites (18.8 million) and 10.5% of
Asians (1.8 million). Although blacks represent only 13.0% of the total population, they make up
24.4% of the poor population; Hispanics, who represent 17.3% of the population, account for
28.1% of the poor. Poverty rates for Hispanics fell from 25.6% in 2012 to 23.5% in 2013, as did
the number of poor Hispanics, from 13.6 million in 2012, to 12.7 million in 2013. Poverty rates
and the numbers estimated as poor were statistically unchanged from 2012 to 2013 for white non-
Hispanics, blacks, and Asians.
Nativity and Citizenship Status
In 2013, among the native-born population, 13.9% (37.9 million) were poor—a rate and number
statistically unchanged from 2012 (14.3%, 38.8 million). Among the foreign-born population,
18.0% (7.4 million) were poor in 2013—a statistically significant drop in the poverty rate (from
19.7%), but not in the number estimated as poor. The poverty rate among foreign-born
naturalized citizens (12.7%, in 2013) was lower than that of the native-born U.S. population
(13.9%). In 2013, the poverty rate of non-citizens (22.8%) dropped significantly from 2012
(24.9%), as did the estimated number who were poor (about one-half million, dropping from 5.4
million in 2012, to 4.0 million in 2013).
Children
Poverty among children dropped significantly from 2012 to 2013. Their estimated poverty rate
fell from 21.3% in 2012, to 19.5% in 2013. In 2013, an estimated 1.3 million fewer children were
poor than in 2012 (14.1 million versus 15.4 million, respectively). However, the 2013 child
poverty rate (19.5%) is still well above its pre-recession low of 16.9% (2006). The lowest
recorded rate of child poverty was in 1969, when 13.8% of children were counted as poor.
Children living in single female-headed families are especially prone to poverty. In 2013 a child
living in a single female-headed family was nearly five times more likely to be poor than a child

10 Beginning with the March 2003 CPS, the Census Bureau allows survey respondents to identify themselves as
belonging to one or more racial groups. In prior years, respondents could select only one racial category. Consequently,
poverty statistics for different racial groups for 2002 and after are not directly comparable to earlier years’ data. The
terms black and white, above, refer to persons who identified with only a single racial group. The term Hispanic refers
to individuals’ ethnic, as opposed to racial, identification. Hispanics may be of any race.
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living in a married-couple family. In 2013, among all children living in single female-headed
families, 45.8% were poor. In contrast, among children living in married-couple families, 9.5%
were poor. The increased share of children who live in single female-headed families has
contributed to the high overall child poverty rate. In 2013, one quarter (25.0%) of children were
living in single female-headed families, more than double the share who lived in such families
when the overall child poverty rate was at a historical low (1969). Among all poor children,
nearly 6 in 10 (58.7%) were living in single female-headed families in 2013.
In 2013, 38.0% of black children were poor (4.2 million), compared to 30.0% of Hispanic
children (5.3 million) and 10.1% of non-Hispanic white children (3.8 million). (See Figure 3.)
Among children living in single female-headed families, more than half of black children (54.0%)
and Hispanic children (52.3%) were poor; in contrast, one-third of non-Hispanic white children
(33.6%) were poor. The poverty rate among Hispanic children who live in married-couple
families (19.9%) was above that of black children (16.8%), and four times that of non-Hispanic
white children (4.9%) who live in such families. Contributing to the high rate of overall black
child poverty is the large share of black children who live in single female-headed families
(54.0%) compared to Hispanic children (30.1%) or non-Hispanic white children (15.7%). (See
Figure 4.)
Figure 3. Child Poverty Rates by Family Living Arrangement,
Race and Hispanic Origin, 2013

Source: Figure prepared by the Congressional Research Service (CRS) based on U.S. Census Bureau data from
the 2014 Current Population Survey Annual Social and Economic Supplement, available at
http://www.census.gov/hhes/www/cpstables/032014/pov/pov05_000.htm.
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Figure 4. Composition of Children, by Family Type, Race and Hispanic Origin, 2013

Source: Figure prepared by the Congressional Research Service (CRS) based on U.S. Census Bureau data from
the 2014 Current Population Survey Annual Social and Economic Supplement, available at
http://www.census.gov/hhes/www/cpstables/032014/pov/pov05_000.htm.
Adults with Low Education, Unemployment, or Disability
Adults with low education, those who are unemployed, or those who have a work-related
disability are especially prone to poverty. Among 25- to 34-year-olds without a high school
diploma, between one-third and two-fifths (36.8%) were poor in 2013. In 2013, 1 in 10 25- to 34-
year-olds lacked a high school diploma. Within the same age group whose highest level of
educational attainment was a high school diploma, about one in five (20.7%) were poor. In
contrast, only about 1 in 16 (6.5%) of 25- to 34-year-olds with at least a bachelor’s degree were
found to be living below the poverty line.
Among persons between the ages of 16 and 64 who were unemployed in March 2014, nearly 3
out of 10 (29.8%) were poor based on their families’ incomes in 2013; among those who were
employed, 6.9% were poor.
In 2013, persons who had a work disability11 represented 11.3% of the 16- to 64-year-old
population, and about one-quarter (26.0%) of the poor population within this age range. Among

11 The CPS asks several questions to determine whether individuals are considered to have a work disability. Persons
are identified as having a work disability if they (1) reported having a health problem or disability that prevents them
(continued...)
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those with a severe work disability, 35.6% were poor, compared to 17.0% of those with a less
severe disability and 11.4% who reported having no work-related disability.
The Aged
In 2013, the 9.5% poverty rate among persons age 65 and older was statistically unchanged from
the 2012 rate (9.1%), but statistically higher than the all-time low-poverty rate among the aged of
8.7% attained in 2011. The number of aged poor grew by 305,000 from 2012 to 2013, from 3.9
million to 4.2 million,. Among persons age 75 and over, 11.2% were poor in 2013, compared to
8.3% of those ages 65 to 74. Measured by a slightly raised poverty standard (125% of the poverty
threshold), 15.1% of the aged could be considered poor or “near poor” in 2013; 12.6% who are
ages 65 to 74, and 18.4% who are 75 years of age and over, could be considered poor or “near
poor.”
Receipt of Need-Tested Assistance Among the Poor
In 2013, nearly three of every four poor persons (73.8%) lived in households that received any
means-tested assistance during the year.12 Such assistance could include cash aid, such as
Temporary Assistance for Needy Families (TANF), Supplemental Security Income (SSI)
payments, SNAP benefits (Food Stamps), Medicaid, subsidized housing, free or reduced price
school lunches, and other programs. In 2013, somewhat over one in five (17.4%) poor persons
lived in households that received cash aid; half (49.5%) received SNAP benefits (formerly named
Food Stamps); 6 in 10 (61.3%) lived in households where one or more household members were
covered by Medicaid; and about 1 in 7 (14.8%) lived in subsidized housing. Poor single-parent
families with children are among those families most likely to receive cash aid. Among poor
children who were living in single female-headed families, about one-fifth (21.9%) were in
households that received government cash aid in 2013, down from 24.0% in 2012. The share of
poor children in single female-headed families receiving cash aid is well below historical levels.
In 1993, 70.2% of these children’s families received cash aid. In 1995, the year prior to passage
of sweeping welfare changes under PRWORA, 65% of such children were in families receiving
cash aid.
The Geography of Poverty
Poverty is more highly concentrated in some areas than in others; it is about twice as high in
center cities as it is in suburban areas and nearly three times as high in the poorest states as it is in
the least poor states. Some neighborhoods may be characterized as having high concentrations of

(...continued)
from working or that limits the kind or amount of work they can do; (2) ever retired or left a job for health reasons; (3)
did not work in the survey week because of long-term physical or mental illness or disability which prevents the
performance of any kind of work; (4) did not work at all in the previous year because they were ill or disabled; (5) are
under 65 years of age and covered by Medicare; (6) are under age 65 years of age and a recipient of Supplemental
Security Income (SSI); or (7) received veteran’s disability compensation. Persons are considered to have a severe work
disability if they meet any of the criteria in (3) through (6), above. See http://www.census.gov/hhes/www/disability/
disabcps.html.
12 See http://www.census.gov/hhes/www/cpstables/032014/pov/pov26_000.htm
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poverty. Among the poor, the likelihood of living in an area of concentrated or extreme poverty
varies by race and ethnicity.
Poverty in Metropolitan and Nonmetropolitan Areas, Center Cities,
and Suburbs

Within metropolitan areas, the incidence of poverty in central city areas is considerably higher
than in suburban areas—19.1% versus 11.1%, respectively, in 2013. Nonmetropolitan areas had a
poverty rate of 16.1%. A typical pattern is for poverty rates to be highest in center city areas, with
poverty rates dropping off in suburban areas, and then rising with increasing distance from an
urban core. In 2013, only nonmetropolitan areas experienced a statistically significant decline in
poverty (both rate and numbers poor) from 2012, with the poverty rate decreasing from the 17.7%
in 2012 to 16.1% in 2013, and the number of poor declining by an estimated 891,000 persons.
Poverty rates and estimated numbers of poor people remained statistically unchanged in
metropolitan areas, center cities, and suburbs from 2012 to 2013.
Poverty by Region
In 2013, poverty rates were lowest in the Northeast (12.7%) and Midwest (12.9%), followed by
the West (14.7%), with the South (16.1%) having the highest poverty rate. Poverty remained
statistically unchanged (measured both in terms of numbers poor and rates) in each of the four
regions from 2012 to 2013.
State Poverty Rates

American Community Survey (ACS) State Poverty Estimates—2013
Up to this point, the poverty statistics presented in this report come from the U.S. Census Bureau’s Annual Social
and Economic Supplement (ASEC) to the Current Population Survey (CPS). For purposes of producing state and sub-
state poverty estimates, the Census Bureau now recommends using the American Community Survey (ACS)—
because of its much larger sample size, the ACS produces estimates with a much smaller margin of statistical error
than that of the CPS/ASEC. However, it should be noted that the ACS survey design differs from the CPS/ASEC in a
variety of ways, and may produce somewhat different estimates than those obtained from the ASEC/CPS. Based on
the 2013 ACS, the U.S. poverty rate was estimated to be 15.8%, compared to 14.5% based on the 2014 CPS/ASEC.
The CPS/ASEC estimates are based on a survey conducted in February through April 2013, and account for income
reported for the previous year. In contrast, the ACS estimates are based on income information col ected between
January and December 2013, for the prior 12 months. For example, for the sample with data col ected in January, the
reference period is from January 2012 to December 2013, and for the sample with data col ected in December, from
December 2012 to November 2013. The ACS data consequently cover a time span of 23 months, with the data
centered at mid-December 2012.

Based on 2012 American Community Survey (ACS) data, poverty rates were highest in the South
(with the exception of Virginia), extending across to Southwestern states bordering Mexico
(Texas, New Mexico, and Arizona). (See Figure 5.) Poverty rates in several states bordering the
Ohio River (Ohio, West Virginia, Kentucky) also exceeded the national rate, as did those of
Congressional Research Service
10


Poverty in the United States: 2013

Michigan and New York, and the District of Columbia, in the eastern half of the nation, and
California, Oregon, and Montana in the western half.
States along the Atlantic Seaboard from Virginia northward tended to have poverty rates well
below the national rate, as did three contiguous states in the upper Midwest/plains (Iowa,
Minnesota, and North Dakota), as well as Utah, Wyoming, Alaska, and Hawaii.
Figure 5. Percentage of People in Poverty in the Past 12 Months by
State and Puerto Rico: 2013

Source: U.S. Census Bureau, 2012 American Community Survey, 2013 Puerto Rico Community Survey.
Alemayehu Bishaw, Poverrty: 2012 and 2013, U.S. Census Bureau, American Community Survey Briefs,
ACSBR/13-0101, Washington, DC, September 2014, p. 4, http://census.gov/content/dam/Census/library/
publications/2014/acs/acsbr13-01.pdf.
Figure 6 shows estimated poverty rates for the United States and for each of the 50 states and the
District of Columbia on the basis of the 2013 American Community Survey (ACS), the most
recent ACS data currently available. In addition to the point estimates, the figure displays a 90%
statistical confidence interval around each state’s estimate, indicating the degree to which these
estimates might be expected to vary based on sample size. Although the states are sorted from
lowest to highest by their respective poverty rate point estimates, the precise ranking of each state
is not possible because of the depicted margin of error around each state’s estimate. All states
with non-overlapping statistical confidence intervals have statistically significant different
Congressional Research Service
11

Poverty in the United States: 2013

poverty rates from one another. Some states with overlapping confidence intervals may also have
significantly different poverty rates from one another, measured at the 90% confidence interval.13
For example, New Hampshire, shown as having the lowest poverty rate (8.7%) in 2013, is
statistically tied with Alaska (9.3%). Mississippi clearly stands out as the state with the highest
poverty rate (24.0%) and New Mexico, with a poverty rate of 21.8%, has the second-highest
poverty rate. Louisiana, a state ranked as having the third-highest poverty rate (19.7%), is
statistically tied with Arkansas (19.7%) and the District of Columbia (18.9%), but not with
Georgia (19.0%), even though Louisiana and Georgia’s statistical confidence intervals overlap.

13 Two states’ poverty rates are statistically different at the 90% statistical confidence interval if the confidence intervals
bounding their respective poverty rates do not overlap with one another. However, some states with overlapping
confidence intervals may also statistically differ at the 90% statistical confidence interval. In order to precisely determine
whether two states’ poverty rates differ from one another, a statistical test of differences must be performed. The standard
error for the difference between two estimates may be calculated as:
2
2
SE
SE
= SE
+ SE
. Two estimates
StateA
StateB
StateA
StateB
are considered statistically different if at the 90% statistical confidence interval the absolute value of the difference is
greater than 1.645 times the standard error of the difference (i.e., Povrate
Povrate
> 1 645
.
x(SE
SE
) .
StateA
StateB
StateA
StateB
Note that the standard error for a state’s poverty estimate may be obtained by dividing the margin of error depicted in
Figure 6 by 1.645.
Congressional Research Service
12


Poverty in the United States: 2013

Figure 6. Poverty Rates for the 50 States and the District of Columbia:
2013 American Community Survey (ACS) Data

Source: Prepared by the Congressional Research Service on the basis of U.S. Census Bureau 2013 American
Community Survey (ACS) data.
Congressional Research Service
13

Poverty in the United States: 2013

Change in State Poverty Rates: 2002-2013
Table 1 provides estimates of state and national poverty rates from 2002 through 2013 from the
ACS. Statistically significant changes from one year to the next are indicated by an upward-
pointing arrow (▲) if a state’s poverty rate was statistically higher, and by a downward-pointing
arrow (▼) if statistically lower, than in the immediately preceding year or for other selected
periods (i.e., 2005 vs. 2002, 2013 vs. 2007).14 It should be noted that ACS poverty estimates for
2006 and later are not strictly comparable to those of earlier years, due to a change in ACS
methodology that began in 2006 to include some persons living in non-institutionalized group
quarters who were not included in earlier years.15
Table 1 shows that three states (New Jersey, New Mexico, and Washington) experienced
statistically significant increases in their poverty rates from the 2012 to 2013 ACS. New Jersey’s
estimated poverty rate increased from 10.8% in 2012 to 11.4% in 2013, New Mexico’s rate
increased from 20.8% to 21.9%, and Washington’s rate increased from 13.5% to 14.1%. Four
states (Colorado, New Hampshire, Texas, and Wyoming) experienced statistically significant
decreases in their poverty rates from 2012 to 2013.
The table shows that poverty among states generally increased over the 2002 to 2005 period, as
measured by the ACS, consequent to the 2001 (March to November) economic recession. From
the 2002 to 2003 ACS, five states (including the District of Columbia) experienced statistically
significant increases in their poverty rates, whereas none experienced a statistically significant
decrease. From 2003 to 2004, eight states saw their poverty rates increase, whereas two saw
decreases. From 2004 to 2005, 13 states saw their poverty rates increase, whereas only 1 saw its
poverty rate decrease. Comparing poverty rates from the 2005 ACS to those from the 2002 ACS,
poverty was statistically higher in 22 states, and lower in only one.
By 2007, poverty rates among states were beginning to improve, with 13 states (including the
District of Columbia) experiencing statistically significant declines in their poverty rates from
2006; only Michigan experienced a statistically significant increase in its poverty rate in 2007
compared to a year earlier.
Since 2007, state poverty rates have generally increased consequent to the 18-month recession
(December 2007 to June 2009). From 2007 to 2008, the ACS data showed eight states (California,
Connecticut, Florida, Hawaii, Indiana, Michigan, Oregon, and Pennsylvania) as experiencing
statistically significant increases in their poverty rates, whereas three states (Alabama, Louisiana,
and Texas) experienced statistically significant decreases. From 2008 to 2009, 32 states saw their
poverty rates increase, and no state experienced a statistically significant decrease, and from 2009
to 2010, 34 states experienced statistically significant increases in poverty, and again, no state
experienced a decrease. As noted above, from 2012 to 2013, three states saw their poverty rates

14 Statistically significant differences are based on a 90% statistical confidence interval.
15 Beginning in 2006, a portion of the population living in non-institutional group quarters has been included in the
ACS in estimating poverty. The population living in institutional group quarters, military barracks, and college
dormitories has been excluded in the ACS poverty estimates for all years. The part of the non-institutional group
quarters population that has been included in the poverty universe since 2006 (e.g., people living in group homes or
those living in agriculture workers’ dormitories) is considerably more likely to be in poverty than people living in
households. Consequently, estimates of poverty in 2006 and after are somewhat higher than would be the case if all
group quarters residents were excluded—thus, comparisons with earlier year estimates are not strictly comparable.
Congressional Research Service
14

Poverty in the United States: 2013

rise, and four saw a decline. Comparing 2013 to 2007, poverty rates were statistically higher in 48
states (including the District of Columbia), and no state had a poverty rate statistically below its
prerecession rate.
Congressional Research Service
15


Table 1. Poverty Rates for the 50 States and the District of Columbia, 2002 to 2013
Estimates from the American Community Survey (ACS)
(percent poor)
Change in Poverty
Rates over
Selected Periods
and Statistically
Significant

Estimated Poverty Rates and Statistically Significant Differences over Previous Year
Differencesa
2005
2013
vs.
vs.
2002
2003
2004
2005
2006b 2007b
2008b
2009b
2010b
2011b
2012b
2013b
2001
2007
United States
12.4

12.7 ▲
13.1 ▲
13.3 ▲
13.3

13.0 ▼
13.2

14.3 ▲
15.3 ▲
15.9 ▲
15.9
15.8
0.9 ▲
2.9 ▲
Alabama
16.6

17.1
16.1
17.0 ▲
16.6
16.9
15.7 ▼
17.5 ▲
19.0 ▲
19.0

19.0
18.7
0.4

1.9 ▲
Alaska 7.7

9.7 ▲
8.2 ▼
11.2 ▲
10.9

8.9 ▼
8.4
9.0

9.9
10.5

10.1
9.3
3.5 ▲
0.4 ▲
Arizona 14.2

15.4 ▲
14.2
14.2
14.2
14.2
14.7

16.5 ▲
17.4 ▲
19.0 ▲
18.7
18.6
0.0

4.5 ▲
Arkansas 15.3

16.0


17.9 ▲
17.2
17.3
17.9
17.3
18.8 ▲
18.8
19.5

19.8
19.7
1.9 ▲
1.8 ▲
California
13.0

13.4
13.3
13.3

13.1

12.4 ▼
13.3 ▲
14.2 ▲
15.8 ▲
16.6 ▲
17.0 ▲
16.8
0.3

4.4 ▲
Colorado
9.7

9.8
11.1
11.1

12.0 ▲
12.0
11.4
12.9 ▲
13.4
13.5

13.7
13.0

1.4 ▲
1.0 ▲
Connecticut
7.5

8.1
7.6
8.3

8.3

7.9

9.3 ▲
9.4

10.1 ▲
10.9 ▲
10.7
10.7
0.9

2.8 ▲
Delaware
8.2

8.7
9.9
10.4

11.1

10.5

10.0

10.8

11.8
11.9

12.0
12.4
2.2 ▲
1.9 ▲
Dist. of Col.
17.5

19.9 ▲
18.9
19.0
19.6
16.4 ▼
17.2
18.4

19.2
18.7

18.2
18.9
1.6

2.5 ▲
Florida 12.8

13.1


12.2 ▼
12.8 ▲
12.6

12.1 ▼
13.2 ▲
14.9 ▲
16.5 ▲
17.0 ▲
17.1
17.0
0.0

4.9 ▲
Georgia 12.7

13.4


14.8 ▲
14.4
14.7
14.3
14.7
16.5 ▲
17.9 ▲
19.1 ▲
19.2
19.0
1.7 ▲
4.7 ▲
Hawaii
10.1

10.9
10.6
9.8

9.3

8.0 ▼
9.1 ▲
10.4 ▲
10.7
12.0 ▲
11.6
10.8
(0.3)

2.9 ▲
Idaho
13.8

13.8
14.5
13.9

12.6 ▼
12.1
12.6
14.3 ▲
15.7 ▲
16.5

15.9
15.6
0.0

3.4 ▲
Illinois
11.6

11.3
11.9
12.0

12.3

11.9

12.2

13.3 ▲
13.8 ▲
15.0 ▲
14.7
14.7
0.4 ▲
2.7 ▲
Indiana
10.9

10.6
10.8
12.2 ▲
12.7
12.3
13.1 ▲
14.4 ▲
15.3 ▲
16.0 ▲
15.6
15.9
1.3 ▲
3.6 ▲
Iowa
11.2
10.1

9.9


10.9 ▲
11.0
11.0
11.5
11.8

12.6 ▲
12.8

12.7
12.7
(0.3)

1.6 ▲
Kansas
12.1

10.8
10.5
11.7 ▲
12.4

11.2 ▼
11.3

13.4 ▲
13.6
13.8

14.0
14.0
(0.4)

2.8 ▲
CRS-16


Change in Poverty
Rates over
Selected Periods
and Statistically
Significant

Estimated Poverty Rates and Statistically Significant Differences over Previous Year
Differencesa
2005
2013
vs.
vs.
2002
2003
2004
2005
2006b 2007b
2008b
2009b
2010b
2011b
2012b
2013b
2001
2007
Kentucky
15.6

17.4
17.4
16.8

17.0

17.3

17.3

18.6 ▲
19.0
19.1

19.4
18.8
1.2 ▲
1.4 ▲
Louisiana
18.8

20.3
19.4
19.8

19.0

18.6

17.3 ▼
17.3

18.7 ▲
20.4 ▲
19.9
19.8
1.0

1.1 ▲
Maine 11.1

10.5


12.3 ▲
12.6
12.9
12.0
12.3
12.3

12.9
14.1 ▲
14.7
14.0
1.5 ▲
1.9 ▲
Maryland
8.1

8.2
8.8
8.2

7.8

8.3

8.1

9.1 ▲
9.9 ▲
10.1

10.3
10.1
0.2

1.8 ▲
Massachusetts
8.9

9.4
9.2
10.3 ▲
9.9
9.9
10.0
10.3

11.4 ▲
11.6

11.9
11.9
1.4 ▲
2.0 ▲
Michigan
11.0

11.4
12.3
13.2 ▲
13.5

14.0 ▲
14.4 ▲
16.2 ▲
16.8 ▲
17.5 ▲
17.4
17.0
2.2 ▲
3.0 ▲
Minnesota
8.5

7.8
8.3
9.2 ▲
9.8 ▲
9.5
9.6
11.0 ▲
11.6 ▲
11.9

11.4 ▼
11.2
0.6 ▲
1.7 ▲
Mississippi 19.9

19.9


21.6 ▲
21.3
21.1
20.6
21.2
21.9

22.4
22.6

24.2 ▲
24.0
1.5 ▲
3.4 ▲
Missouri
11.9

11.7
11.8
13.3 ▲
13.6

13.0 ▼
13.4

14.6 ▲
15.3 ▲
15.8

16.2
15.9
1.4 ▲
2.9 ▲
Montana
14.6

14.2
14.2
14.4

13.6

14.1

14.8

15.1

14.6
14.8

15.5
16.5
(0.3)

2.4 ▲
Nebraska
11.0

10.8
11.0
10.9

11.5

11.2

10.8

12.3 ▲
12.9
13.1

13.0
13.2
0.0

2.0 ▲
Nevada
11.8

11.5
12.6
11.1

10.3

10.7

11.3

12.4 ▲
14.9 ▲
15.9

16.4
15.8
(0.7) ▼
5.1 ▲
New Hampshire
6.4

7.7 ▲
7.6
7.5

8.0

7.1 ▼
7.6

8.5 ▲
8.3
8.8

10.0 ▲
8.7

1.1 ▲
1.6 ▲
New Jersey
7.5

8.4 ▲
8.5
8.7

8.7

8.6

8.7

9.4 ▲
10.3 ▲
10.4

10.8
11.4

1.2 ▲
2.9 ▲
New Mexico
18.9

18.6
19.3
18.5

18.5

18.1

17.1

18.0

20.4 ▲
21.5

20.8
21.9

(0.4)

3.8 ▲
New York
13.1

13.5
14.2 ▲
13.8

14.2 ▲
13.7 ▼
13.6

14.2 ▲
14.9 ▲
16.0 ▲
15.9
16.0
0.7 ▲
2.3 ▲
North Carolina
14.2

14.0
15.2
15.1

14.7

14.3

14.6

16.3 ▲
17.5 ▲
17.9

18.0
17.9
0.8

3.6 ▲
North Dakota
12.5

11.7
12.1
11.2

11.4

12.1

12.0

11.7

13.0 ▲
12.2

11.2
11.8
(1.3)

(0.3)

Ohio
11.9

12.1
12.5
13.0

13.3

13.1

13.4

15.2 ▲
15.8 ▲
16.4 ▲
16.3
16.0
1.2 ▲
2.8 ▲
Oklahoma
15.0

16.1
15.3
16.5

17.0

15.9 ▼
15.9
16.2

16.9 ▲
17.2

17.2
16.8
1.5 ▲
0.9 ▲
Oregon
13.2

13.9
14.1
14.1

13.3 ▼
12.9

13.6 ▲
14.3

15.8 ▲
17.5 ▲
17.2
16.7
0.9

3.7 ▲
CRS-17


Change in Poverty
Rates over
Selected Periods
and Statistically
Significant

Estimated Poverty Rates and Statistically Significant Differences over Previous Year
Differencesa
2005
2013
vs.
vs.
2002
2003
2004
2005
2006b 2007b
2008b
2009b
2010b
2011b
2012b
2013b
2001
2007
Pennsylvania 10.5

10.9


11.7 ▲
11.9
12.1
11.6 ▼
12.1 ▲
12.5 ▲
13.4 ▲
13.8

13.7
13.7
1.4 ▲
2.1 ▲
Rhode Island
10.7

11.3
12.8 ▲
12.3
11.1
12.0
11.7
11.5

14.0 ▲
14.7

13.7
14.3
1.6

2.3 ▲
South Carolina
14.2

14.1
15.7
15.6

15.7

15.0

15.7

17.1 ▲
18.2 ▲
18.9 ▲
18.3
18.6
1.3 ▲
3.5 ▲
South Dakota
11.4

11.1
11.0
13.6 ▲
13.6
13.1
12.5
14.2 ▲
14.4
13.9

13.4
14.2
2.3

1.1

Tennessee
14.5

13.8
14.5
15.5

16.2

15.9

15.5

17.1 ▲
17.7
18.3

17.9
17.8
1.0 ▲
1.9 ▲
Texas
15.6

16.3
16.6
17.6 ▲
16.9 ▼
16.3 ▼
15.8 ▼
17.2 ▲
17.9 ▲
18.5 ▲
17.9 ▼
17.5

2.0 ▲
1.3 ▲
Utah
10.5

10.6
10.9
10.2

10.6

9.7 ▼
9.6

11.5 ▲
13.2 ▲
13.5

12.8
12.7
(0.3)

3.0 ▲
Vermont
8.5

9.7
9.0
11.5 ▲
10.3
10.1
10.6
11.4

12.7 ▲
11.5 ▼
11.8
12.3
2.9 ▲
2.2 ▲
Virginia
9.9

9.0
9.5
10.0

9.6

9.9

10.2

10.5

11.1 ▲
11.5 ▲
11.7
11.7
0.0

1.8 ▲
Washington 11.4

11.0


13.1 ▲
11.9 ▼
11.8
11.4
11.3
12.3 ▲
13.4 ▲
13.9

13.5
14.1

0.5

2.7 ▲
West Virginia
17.2

18.5
17.9
18.0

17.3

16.9

17.0

17.7

18.1
18.6

17.8
18.5
0.8

1.6 ▲
Wisconsin
9.7

10.5
10.7
10.2

11.0 ▲
10.8
10.4
12.4 ▲
13.2 ▲
13.1

13.2
13.5
0.5 ▲
2.7 ▲
Wyoming
11.0

9.7
10.3
9.5

9.4

8.7

9.4

9.8

11.2
11.3

12.6
10.9

(1.5) ▼
2.2 ▲
Number of states
with statistical y
significant change in
poverty:

5

10


14

7

14

11

32

34 18 5
7
23

48
Increase in poverty


5 ▲
8 ▲
13 ▲
4 ▲
1 ▲
8 ▲
32 ▲
34 ▲
17 ▲
3 ▲
3 ▲
22 ▲
48 ▲
Decrease in poverty


0 ▼
2 ▼
1 ▼
3 ▼
13 ▼
3 ▼
0 ▼
0 ▼
1 ▼
2 ▼
4 ▼
1 ▼
0 ▼
Source: Congressional Research Service (CRS) estimates from U.S. Census Bureau American Community Survey (ACS) data, 2002 to 2013.
Notes: ▲ Statistical y significant increase in poverty rate at the 90% statistical confidence level.
▼ Statistically significant decrease in poverty rate at the 90% statistical confidence level.
CRS-18


Numbers in parentheses are negative.
a. Depicted changes in poverty rates over selected periods may differ slightly from differences calculated directly from the table, due to rounding.
b. Comparisons to 2002 through 2005 estimates are not strictly comparable, due to inclusion of persons living in some non-institutional group quarters beginning in 2006
and after.
CRS-19

Poverty in the United States: 2013

Poverty Rates by Metropolitan Area
The four tables that follow provide poverty estimates for large metropolitan areas having a
population of 500,000 and over, and for smaller metropolitan areas having a population of 50,000
or more but less than 500,000. Among large metropolitan areas, 10 areas with some of the lowest
poverty rates are shown in Table 2, and the 10 areas with some of the highest poverty rates are
shown in Table 3. Among smaller metropolitan areas, 10 areas with some of the lowest poverty
rates are shown in Table 4, and 10 among those with the highest poverty rates in Table 5. It
should be noted that metropolitan areas shown in these tables may not be statistically different
from one another, or from others not shown in the tables. Poverty estimates for all metropolitan
areas in 2013 are shown in Appendix B. Table B-1.
Table 2. Large Metropolitan Areas Among Those with the
Lowest Poverty Rates: 2013
(Metropolitan Areas with Population of 500,000 and Over)
Poverty Rate


Number Poor
(Percent Poor)
Total
Margin of
Margin of
Metropolitan Area
Population
Estimate
Errora Estimate Errora
Washington-Arlington-Alexandria, DC-VA-
5,846,655
495,683
+/-19,944
8.5% +/-0.3%
MD-WV
Urban Honolulu, HI
951,718
89,684
+/-7,816
9.4%
+/-0.8%
Bridgeport-Stamford-Norwalk, CT
921,302
88,808
+/-6,895
9.6%
+/-0.7%
Minneapolis-St. Paul-Bloomington, MN-WI
3,397,278
349,161
+/-13,880
10.3%
+/-0.4%
Boston-Cambridge-Newton, MA-NH
4,525,102
470,178
+/-18,981
10.4%
+/-0.4%
Lancaster, PA
514,196
53,694
+/-5,804
10.4%
+/-1.1%
Ogden-Clearfield, UT
615,823
64,161
+/-7,360
10.4%
+/-1.2%
San Jose-Sunnyvale-Santa Clara, CA
1,891,182
198,842
+/-12,625
10.5%
+/-0.7%
Colorado Springs, CO
660,782
71,297
+/-7,162
10.8%
+/-1.1%
Hartford-West Hartford-East Hartford, CT
1,169,485
125,923
+/-9,009
10.8%
+/-0.8%
Source: Table prepared by the Congressional Research Service (CRS) based on analysis of U.S. Census Bureau
2012 American Community Survey (ACS) data, table series S1701: Poverty Status in the Past 12 Months, from
the Census Bureau’s American FactFinder, available at http://factfinder2.census.gov/faces/nav/jsf/pages/
index.xhtml.
Notes: Areas are included based on their estimated 2013 poverty rates. Areas shown may not be statistical y
different from one another, or from others not shown in the table.
a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted
from an estimate, the range reflects a 90% statistical confidence interval bounding the estimate.

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Table 3. Large Metropolitan Areas Among Those with the
Highest Poverty Rates: 2013
(Metropolitan Areas with Population of 500,000 and Over)
Poverty Rate


Number Poor
(Percent Poor)
Total
Margin of
Margin of
Metropolitan Area
Population Estimate Errora Estimate Errora
McAl en-Edinburg-Mission, TX
803,934
275,681
+/-16,441
34.3%
+/-2.0%
Fresno, CA
937,990
270,072
+/-12,767
28.8% +/-1.4%
Bakersfield, CA
831,344
189,484
+/-13,393
22.8%
+/-1.6%
El Paso, TX
816,158
184,427
+/-12,589
22.6%
+/-1.5%
Modesto, CA
518,152
114,628
+/-9,386
22.1%
+/-1.8%
Jackson, MS
557,607
122,754
+/-7,806
22.0%
+/-1.4%
Winston-Salem, NC
636,242
127,378
+/-10,165
20.0%
+/-1.6%
Greensboro-High Point, NC
722,405
143,646
+/-9,658
19.9%
+/-1.3%
Stockton-Lodi, CA
690,366
137,663
+/-9,607
19.9% +/-1.4%
Augusta-Richmond County, GA-SC
565,819
111,863
+/-8,976
19.8%
+/-1.6%
Source: Table prepared by the Congressional Research Service (CRS) based on analysis of U.S. Census Bureau
2012 American Community Survey (ACS) data, table series S1701: Poverty Status in the Past 12 Months, from
the Census Bureau’s American FactFinder, available at http://factfinder2.census.gov/faces/nav/jsf/pages/
index.xhtml.
Notes: Areas are included based on their estimated 2013 poverty rates. Areas shown may not be statistical y
different from one another, or from others not shown in the table.
a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted
from an estimate, the range reflects a 90% statistical confidence interval bounding the estimate.
Table 4. Smaller Metropolitan Areas Among Those with the
Lowest Poverty Rates: 2013
(Metropolitan Areas with Populations Between 50,000 and 499,999)
Poverty Rate


Number Poor
(Percent Poor)
Total
Margin of
Margin of
Metropolitan Area
Population
Estimate
Errora
Estimate
Errora
California-Lexington Park, MD
106,530
6,831
+/-2,204
6.4%
+/-2.1%
Winchester, VA-WV
124,642
8,432
+/-1,934
6.8%
+/-1.5%
Anchorage, AK
386,833
27,596
+/-3,586
7.1%
+/-0.9%
Fairbanks, AK
96,578
7,442
+/-2,543
7.7%
+/-2.6%
Rochester, MN
208,650
16,523
+/-2,572
7.9%
+/-1.2%
Appleton, WI
226,221
18,291
+/-2,940
8.1%
+/-1.3%
Fond du Lac, WI
98,663
8,023
+/-1,707
8.1%
+/-1.7%
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Bismarck, ND
121,277
10,119
+/-1,758
8.3%
+/-1.5%
Gettysburg, PA
97,009
8,620
+/-2,132
8.9%
+/-2.2%
Napa, CA
136,394
12,286
+/-2,875
9.0%
+/-2.1%
Source: Table prepared by the Congressional Research Service (CRS) based on analysis of U.S. Census Bureau
2012 American Community Survey (ACS) data, table series S1701: Poverty Status in the Past 12 Months, from
the Census Bureau’s American FactFinder, available at http://factfinder2.census.gov/faces/nav/jsf/pages/
index.xhtml.
Notes: Areas are included based on their estimated 2013 poverty rates. Areas shown may not be statistical y
different from one another, or from others not shown in the table.
a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted
from an estimate, the range reflects a 90% statistical confidence interval bounding the estimate.
Table 5. Smaller Metropolitan Areas Among Those with the
Highest Poverty Rates: 2013
(Metropolitan Areas with Population of 500,000 and Over)
Poverty Rate


Number Poor
(Percent Poor)
Total
Margin of
Margin of
Metropolitan Area
Population Estimate Errora Estimate Errora
Brownsville-Harlingen, TX
412,432
134,170
+/-8,943
32.5%
+/-2.2%
Laredo, TX
258,684
80,403
+/-7,285
31.1%
+/-2.8%
Visalia-Porterville, CA
448,360
135,066
+/-9,722
30.1%
+/-2.2%
Athens-Clarke County, GA
186,981
53,388
+/-5,015
28.6%
+/-2.6%
Col ege Station-Bryan, TX
224,477
63,800
+/-6,284
28.4%
+/-2.8%
Las Cruces, NM
208,101
57,908
+/-6,390
27.8%
+/-3.1%
Valdosta, GA
139,018
37,443
+/-4,673
26.9%
+/-3.3%
Gainesville, FL
256,894
68,758
+/-5,496
26.8%
+/-2.1%
Greenville, NC
168,611
43,223
+/-5,197
25.6%
+/-3.1%
Monroe, LA
168,802
42,735
+/-5,063
25.3%
+/-3.0%
Source: Table prepared by the Congressional Research Service (CRS) based on analysis of U.S. Census Bureau
2012 American Community Survey (ACS) data, table series S1701: Poverty Status in the Past 12 Months, from
the Census Bureau’s American FactFinder, available at http://factfinder2.census.gov/faces/nav/jsf/pages/
index.xhtml.
Notes: Areas are included based on their estimated 2013 poverty rates. Areas shown may not be statistical y
different from one another, or from others not shown in the table.
a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted
from an estimate, the range reflects a 90% statistical confidence interval bounding the estimate.
Congressional District Poverty Estimates
Poverty estimates for congressional districts are shown in Appendix C. Table C-1 includes
poverty rate estimates for 2012. Congressional districts in 2012 are not directly comparable to
earlier years, due to re-districting.
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“Neighborhood” Poverty—Poverty Areas and Areas of
Concentrated and Extreme Poverty

The estimates presented here are based on five years of American Community Survey (ACS)
data (2009-2013 ACS).
Neighborhoods can be delineated from U.S. Census Bureau census tracts. Census tracts usually
have between 2,500 and 8,000 persons and, when first delineated, are designed to be
homogeneous with respect to population characteristics, economic status, and living conditions.
The Census Bureau defines “poverty areas” as census tracts having poverty rates of 20% or more.
Figure 7 groups census tracts according to their level of poverty. The first two groupings are
based on poor persons living in census tracts with poverty rates below the national average
(15.4% based on the five-year ACS data), and from 15.4% to less than 20.0%. Poor persons living
in census tracts with poverty rates of 20% or more meet the Census Bureau definition of living in
“poverty areas.” Poverty areas are further demarcated in terms of poor persons living in areas of
“concentrated” poverty (i.e., census tracts with poverty rates of 30% to 39.9%), and areas of
“extreme” poverty (i.e., census tracts with poverty rates of 40% or more). The figure is based on
five years of data (2009-2013) from the U.S. Census Bureau’s American Community Survey
(ACS). Five years of data are required in order to get reasonably reliable statistical data at the
census tract level while at the same time preserving the confidentiality of survey respondents.
Figure 7 shows that over the five-year period 2009-2013, over half of all poor persons (55.0%)
lived in “poverty areas” (i.e., census tracts with poverty rates of 20% or more). Among the poor,
about three out of ten (30.7%) lived in areas with poverty of 30% or more, and about one in seven
(14.5%) lived in areas of “extreme” poverty, having poverty rates of 40% or more. Among the
poor, African Americans, American Indian and Alaska Natives, and Hispanics are more likely to
live in poverty areas than either Asians or white non-Hispanics. Among poor blacks, nearly half
(48.0%) live in neighborhoods with poverty rates of 30% or more, and one-quarter (25.2%) live
in “extreme” poverty areas, with poverty rates of 40% or more. Among poor Hispanics, about
two-fifths (39.6%) live in areas with poverty rates of 30% or more, and about one in six (17.5%)
live in areas of “extreme” poverty. Among poor white non-Hispanics, over half (53.2%) live
outside poverty areas, while nearly one-quarter (23.2%) live in areas with poverty rates of 30% or
more.

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Figure 7. Distribution of Poor People by Race and Hispanic Origin,
by Level of Neighborhood (Census Tract) Poverty, 2009-2013

Source: Congressional Research Service (CRS) analysis of U.S. Census Bureau American Community Survey five-year (2009-2013) data.
CRS-24

Poverty in the United States: 2013


The Research Supplemental Poverty Measure
On October 16, 2014, the Census Bureau released its fourth annual report using a new
Supplemental Poverty Measure (SPM).16 As its name implies, the SPM is intended to
“supplement,” rather than replace, the “official” poverty measure. The “official” Census Bureau
statistical measure of poverty will continue to be used by programs that allocate funds to states or
other jurisdictions on the basis of poverty, and the Department of Health and Human Services
(HHS) will continue to derive Poverty Income Guidelines from the “official” Census Bureau
measure.
Many experts consider the “official” poverty measure to be flawed and outmoded.17 In 1990,
Congress commissioned a study on how poverty is measured in the United States, resulting in the
National Academy of Sciences (NAS) convening a 12-member expert panel to study the issue.
The NAS panel issued a wide range of specific recommendations to develop an improved
statistical measure of poverty in its 1995 report Measuring Poverty: A New Approach.18
In late 2009, the Office of Management and Budget (OMB) formed an Interagency Technical
Working Group19 (ITWG) to suggest how the Census Bureau, in cooperation with the Bureau of
Labor Statistics (BLS), should develop a new Supplemental Poverty Measure, using the NAS
expert panel’s recommendations as a starting point. Referencing the work of the ITWG,20 the
Department of Commerce announced in March 2010 that the Census Bureau was developing a
new Supplemental Poverty Measure, as “an alternative lens to understand poverty and measure
the effects of anti-poverty policies,” with the intention that the new measure “will be dynamic and
will benefit from improvements over time based on new data and new methodologies.”21
The SPM is intended to address a number of weaknesses of the “official” measure. Criticisms of
the “official” poverty measure raised by the NAS expert panel include the following:
The “official” poverty measure, by counting only families’ total cash, pre-tax
income as a resource in determining poverty status, ignores a host of government
programs and policies that affect the disposable income families may actually
have available.
For example, the official measure ignores the effects of payroll
taxes paid by families, and tax benefits they may receive such as the EITC and

16 Kathleen Short, The Supplemental Poverty Measure: 2013, U.S. Census Bureau, P60-251, Washington, DC, October
2014, http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf.
17 For a discussion of the history and development of the U.S. poverty measure, and efforts to improve poverty
measurement, see CRS Report R41187, Poverty Measurement in the United States: History, Current Practice, and
Proposed Changes
, by Thomas Gabe.
18 National Research Council, Panel on Poverty and Family Assistance, “Measuring Poverty: A New Approach,”
Constance F. Citro and Robert T. Michael, eds. (Washington, DC: National Academy Press, 1995). (Hereinafter cited
as Citro and Michael, Measuring Poverty…)
19 The working group included representatives from BLS, the Census Bureau, the Council of Economic Advisors, the
Department of Commerce, the Department of Health and Human Services, and OMB.
20 The ITWG’s guidance is available at http://www.census.gov/hhes/www/poverty/SPM_TWGObservations.pdf.
21 Census Bureau to Develop Supplemental Poverty Measure, March 2, 2010 News Release, Economics and Statistics
Administration, U.S. Department of Commerce. Available on the Internet at http://www.esa.doc.gov/news/2010/03/02/
census-bureau-develop-supplemental-poverty-measure.
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the Child Tax Credit. It ignores a variety of in-kind benefits, such as SNAP
benefits and free or reduced-price lunches under the National School Lunch
Program, that free up resources to meet other needs. Similarly, it ignores housing
subsidies that help make housing more affordable.
The “official” poverty income thresholds used in determining families’ and
individuals’ poverty status, devised in the early 1960s, have changed little since.
Except for minor technical changes and adjustments for price inflation, poverty
income thresholds have essentially been frozen in time, reflecting living
standards of a half-century ago.
The “official” poverty measure does not take into account necessary work-
related expenses, such as child care and transportation costs that are associated
with getting to work.
Child care expenses are much more common today than
when the “official” poverty measure was originally developed, as mothers’ labor
force participation has since increased.
The “official” poverty measure does not take into account medical expenses that
individuals and families may incur, affecting their ability to meet other basic
needs.
These costs, which tend to vary by age, health status, and insurance
coverage of individuals, may differentially affect families’ abilities to meet other
basic needs, especially given rising health care costs.
The “official” poverty measure does not take into account changing family
situations, such as cohabitation among unmarried couples, or child support
payments.

The “official” poverty measure does not adjust for differences in prices across
geographic areas, which may affect the cost of living from one area to another.
The ITWG, using the NAS-panel recommendations as a starting point, suggested an approach to
developing the SPM that addressed how income thresholds should be set and resources counted in
measuring poverty. Conceptual differences between the “official” and supplemental poverty
measures are summarized in Table 6.

Table 6. Poverty Measure Concepts Under “Official” and Supplemental Measures

“Official” Poverty Measure
Supplemental Poverty Measure
Measurement units
Families and unrelated individuals
All related individuals who live at the
same address, including any co-
resident unrelated children who are
cared for by the family (such as foster
children) and any cohabitors and their
children
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“Official” Poverty Measure
Supplemental Poverty Measure
Poverty threshold
Three times the cost of a minimum
A range around the 33rd percentile
food diet in 1963
(i.e., 30th to 36th percentile) of
expenditures on food, shelter,
clothing, and utilities (FCSU) for
consumer units with exactly two
children multiplied by 1.2 to account
for other family needs (e.g., household
supplies, personal care, non-
transportation-related expenses)
Based on data from the U.S. Bureau of
Labor Statistics Consumer
Expenditure Survey (BLS CE)
Separate thresholds developed for
- homeowners with a mortgage,
- homeowners without a mortgage,
- renters
Threshold adjustments
Vary by family size, composition, and
A three parameter equivalence scale
age of householder
for number of adults and children in
the family
Geographic adjustments for
differences in housing costs
Updating thresholds
Consumer Price Index for Urban
Five-year moving average of
Consumers (CPI-U) based on all items expenditures on FCSU from the BLS
CE
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“Official” Poverty Measure
Supplemental Poverty Measure
Resource measures
Gross before-tax cash income
Sum of cash income
Plus in-kind benefits that families can
use to meet their FCSU needs:

Supplemental Nutritional
Assistance (SNAP)

National School Lunch Program

Supplementary Nutrition
Program for Women, Infants, and
Children (WIC)

Housing Subsidies

Low-Income Home Energy
Assistance (LIHEAP)
Plus refundable tax credits:

Earned Income Tax Credit
(EITC)

Refundable portion of the Child
Tax Credit (CTC), known as the
Additional Child Tax Credit
(ACTC)
Minus nondiscretionary expenses:

federal and state income taxes

payrol taxes

work-related expenses, including
work-related child care expenses

medical out-of-pocket expenses
(MOOP), including insurance
premiums paid

child support paid

Source: Congressional Research Service (CRS). Adapted from Kathleen Short, The Supplemental Poverty
Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014, http://census.gov/content/dam/
Census/library/publications/2014/demo/p60-251.pdf.
The SPM incorporates a more comprehensive income/resource definition than that used by the
“official” poverty measure, including in-kind benefits (e.g., SNAP) and refundable tax credits
(e.g., EITC). It also expands upon the traditional family definition based on blood, marriage, and
adoption to include cohabiting partners and their family relatives as part of a broader economic
unit for assessing poverty status. The SPM subtracts necessary expenses (i.e., taxes, work-related
expenses including child-care, child support paid, medical out-of-pocket [MOOP] expenses) from
resources to arrive at a measure of an economic unit’s disposable income/resources that may be
applied to a standard of need based on food, clothing, shelter, and utilities (FCSU), plus “a little
bit more” for everything else. The SPM income/resource thresholds are initially set at a range in
the distribution (30th to 36th percentile) of what reference families (families with exactly two
children) actually spend on FCSU. Separate thresholds are derived for homeowners with a
mortgage and those without a mortgage, and for renters. Thresholds are adjusted for price
differences in housing costs by geographic area (metropolitan and nonmetropolitan areas in a
state). Thresholds for economic units other than initial reference units (i.e., those with exactly two
children) are adjusted upwards or downwards for the number of adults and number of children in
the unit.
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Poverty Thresholds
As described earlier, the “official” U.S. poverty measure measures cash—pre-tax—income
against income thresholds that vary by family size and composition. The thresholds were derived
from research that showed that the average U.S. family spent one-third of its pre-tax income on
food, based on a USDA 1955 Food Consumption Survey. After pricing minimally adequate food
plans for families of varying sizes and compositions, poverty thresholds were derived by
multiplying the cost of those food plans by a factor of three (i.e., one-third of the thresholds were
assumed to address families’ food needs, and two-thirds addressed everything else). The
thresholds, established in 1963, are adjusted each year for price inflation.
SPM Poverty Thresholds
The SPM poverty thresholds are based on the NAS panel recommendation that thresholds be
based on a point in the empirical distribution that “reference” families spend on food, clothing,
shelter, and utilities (FCSU). Based on ITWG’s suggestions, the Census Bureau derives FCSU
thresholds for “reference” units with exactly two children, between the 30th and 36th percentile of
what such units spend on FCSU, averaged over five years of survey data from the BLS Consumer
Expenditure (CE) Survey.22 Whereas “official” poverty thresholds are based on initial thresholds
adjusted for price changes over time, the SPM thresholds are based on changes in reference
consumer units’ actual spending on FCSU over time.
Following the ITWG’s suggestion, three separate sets of thresholds are established: one set for
homeowners with a mortgage, another set for homeowners without a mortgage, and a third set for
renters. Following NAS panel recommendations, the ITWG suggested that initial poverty
thresholds based on FCSU be multiplied by a factor of 1.2, to account for all other needs (e.g.,
household supplies, personal care, non-work-related transportation).23 Additionally, thresholds are
adjusted upward and downward based on SPM reference unit size using a three parameter
equivalence scale based on the number of adults and children in the unit.
Lastly, the thresholds are adjusted to account for variation in geographic price differences across
metropolitan and nonmetropolitan areas, by state, based on differences in median housing costs
across areas relative to the nation. The geographic housing cost adjustment is applied to the
shelter portion of the FCSU-based thresholds.
Figure 8 depicts poverty threshold levels under the “official” poverty measure and under the
Research SPM for a resource unit consisting of two adults and two children. The figure shows
that in 2013, the official poverty threshold for a family with two adults and two children was
$23,624. In comparison, for a similar family, the SPM poverty threshold for homeowners with a

22 The NAS panel recommended that the reference family for establishing initial thresholds be based on families with
two adults and two children. The ITWG suggested that initial thresholds be based on consumer units with exactly two
children, as children reside in a variety of family types (such as single parent families, presence of one or more
grandparents, and families with cohabiting adult partners). The NAS panel recommended that initial thresholds be
established at between 78% and 83% of median expenditures on FCSU of reference families, which empirically ranged
between the 30th and 35th percentiles. The ITWG suggested that initial thresholds be set at a range around the 33rd
percentile of expenditures on FCSU for the reference consumer units. The ITWC suggested that five years of CE data
be used in establishing thresholds to smooth the change in the thresholds from one year to the next.
23 The 1.2 multiplier applied to FCSU equals the midpoint of the NAS panel’s recommended multiplier of between 1.15
and 1.25.
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Poverty in the United States: 2013

mortgage was $25,639, $2,015 (8.5%) above the official poverty threshold, and for homeowners
without a mortgage, $21,397, or $2,227 (9.4%) below the official threshold. The SPM poverty
threshold for renters was $25,144 or $1,520 (6.4%), above the official measure.
Figure 8. Poverty Thresholds Under the “Official” Measure and the
Research Supplemental Poverty Measure for Units with
Two Adults and Two Children: 2013

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The
Supplemental Poverty Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014,
http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf.
Resources and Expenses Included in the SPM
As discussed earlier, the “official” poverty measure is based on counting families’ and unrelated
individuals’ pre-tax cash income against poverty thresholds that vary by family size and
composition. The SPM expands upon the pre-tax cash income resource definition used by the
“official” measure to develop a more comprehensive measure of “disposable” income that SPM
units might use to help meet basic needs (i.e., poverty thresholds based on FCSU, plus “a little
more”). The SPM resource measure includes the value of a number of federal in-kind benefits,
such as Supplemental Nutrition Assistance Program (SNAP, formerly Food Stamp) benefits; free
and reduced-price school lunches; nutrition assistance for women, infants, and children (WIC);
federal housing assistance; and energy assistance under the Low Income Home Energy Assistance
Program (LIHEAP). It also includes federal tax benefits administered by the Internal Revenue
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Service, such as the Earned Income Tax Credit (EITC) and the partially refundable portion of the
Child Tax Credit (CTC), known as the Additional Child Tax Credit (ACTC).
The SPM subtracts a number of necessary expenses from SPM units’ resources to arrive at a
measure of “disposable” income that units might have available to meet basic needs. Necessary
expenses subtracted from resources on the SPM include child support paid; estimated federal,
state, and local income taxes; estimated social security payroll (FICA) taxes; estimated work-
related expenses other than child care (e.g., work-related commuting costs, purchase of uniforms
or tools required for work); reported work-related child care expenses; and reported medical out
of pocket (MOOP) expenses, including the employee share of health insurance premiums plus
other medically necessary items such as prescription drugs and doctor copayments.
The effects of counting each of these resources and expenses in the SPM are assessed later in this
report (see “Marginal Effects of Counting Specified Resources and Expenses on Poverty under
the SPM”).
Poverty Estimates Under the Research SPM Compared to the
“Official” Measure

In 2013, the overall poverty rate was somewhat higher under the SPM (15.5%) than under an
adjusted official” poverty measure (14.6%)—“adjusted” to include unrelated children typically
excluded from the “official” measure.24 In 2013, an estimated 48.671 million people were poor
under the SPM, 2.9 million people more than the 45.748 million estimated under the “official”
(adjusted) poverty measure. The remainder of this report focuses on differences in poverty rates
among and between various groups under the two measures.
Poverty by Age
The SPM yields a very different impression of the incidence of poverty with respect to age than
that portrayed by the “official” measure. Figure 9 compares poverty rates by age group under the
SPM and the “official” measure in 2013. The poverty rate for adults ages 18 to 64 is somewhat
higher under the SPM than under the “official” measure (15.4% compared to 13.6%). The figure
shows that the poverty rate for children (under age 18) is lower under the SPM than under the
“official” measure (16.4% compared to 20.4%). In contrast, the poverty rate among persons age
65 and over is much higher under the SPM than under the “official” measure (14.6% compared to
9.5%). Although the child poverty rate is lower under the SPM than under the “official” measure,
and the aged poverty rate is considerably higher, the incidence of poverty among children still
exceeds that of the aged under the SPM, as it did under the “official” measure. The SPM paints a
much different picture of poverty among the aged than that conveyed by the “official” measure.
As will be shown later, much of the difference between the aged poverty rate measured under the
SPM compared to the “official” measure is attributable to the effect of medical expenses on the
disposable income among aged units to meet basic needs represented by the SPM resource
thresholds.

24 “Official” published estimates of poverty exclude unrelated children under the age of 15 in the universe for whom
poverty is determined. For comparison with the SPM measure, these children are included in both the “adjusted
official”
poverty measure and the SPM. Under the “official” published poverty measure, the overall poverty rate was
14.5% in 2013; under the adjusted measure shown in this report, the overall “official” poverty rate in 2013 was 14.6%.
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Figure 9. Poverty Rates Under the “Official”* and Research Supplemental Poverty
Measures, by Age: 2013
(Percent poor)

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The
Supplemental Poverty Measure: 2013, U.S. Census Bureau, P60-251, Washington, DC, October 2014,
http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf.
Note: * Differs from published “official” poverty rates as unrelated individuals under age 15 are included in the
universe.
Poverty by Type of Economic Unit
As noted above, the SPM expands the definition of the economic unit considered for poverty
measurement purposes over that used under the “official” poverty measure. The “official” poverty
measure groups all co-residing household members related by marriage, birth, or adoption as
sharing resources for purposes of poverty determination. Unrelated individuals, whether living
alone as a single person household or with other unrelated members, are treated as separate
economic units under the “official” poverty measure. The “official” measure also excludes
unrelated children under age 15 from the universe for poverty determination. As noted earlier, the
“adjusted official” poverty measure presented in this section of the report includes unrelated
children, resulting in a 14.6% poverty rate as opposed to the published rate of 14.5% in 2013.
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The SPM expands the economic unit used for poverty determination beyond that used by the
“official” measure.25 The SPM assesses the relationship of unrelated household members to
others in the household to determine whether they will be joined with others to construct
expanded economic units. For example, the SPM combines unrelated co-residing household
members age 14 and older who are not married and who identify each other as boyfriend,
girlfriend, or partner as cohabiting partners. Cohabiting partners, as well as any of their co-
resident family members, are combined as an economic unit under the SPM. The SPM also
combines unmarried co-residing parents of a child living in the household as an economic unit,
even if the parents do not identify as a cohabiting couple. Any unrelated children who are under
age 15 and are not foster children are assigned to the householder’s economic unit, as are foster
children under the age of 22. Additionally, the SPM combines children over age 18 living in a
household with a parent, and any younger children of the parent, as an economic unit. Under the
“official” poverty measure, a child age 18 and over is treated as an unrelated individual, and the
child’s parent is also treated as an unrelated individual if no other family members are present, or
as an unrelated subfamily head if a spouse or other children (under age 18) are also residing in the
household.
In 2013, an estimated 27.953 million persons, 8.9% of the 313.395 million persons represented in
the CPS/ASEC, were classified as either joining an economic unit or having members added to
their economic unit under the SPM measure, compared to how they would have been classified
under the “official” measure’s economic unit definition. Combining the resources of these
additional household members had the effect of reducing poverty under the SPM measure,
compared to the “official” measure, in 2013.
Figure 10 shows poverty rates in 2013 by type of economic unit. Persons identified as being in a
married-couple unit, or in female- or male-householder units, are persons in those economic units
whose members remained unchanged under the SPM compared to the “official” poverty measure.
Persons who were added to an economic unit, or were part of an economic unit that had members
added to it under the SPM definition, are labeled as being in a “new SPM unit.” The figure shows
that poverty rates for persons in married-couple units, and in male-householder units, are higher
under the SPM than under the “official” poverty measure (9.5% versus 6.7% for persons in
married-couple units, and 23.1% versus 18.7% for persons in male-householder units). Poverty
rates for persons living in female-householder units did not statistically differ from one another,
with about three out of ten persons in such units considered poor under either measure. In
contrast, poverty among persons who were members of “new SPM units” fell by about two-fifths,
from 31.4% under the “official” measure to 17.9% under the SPM.

25 For further discussion, see Ashley J. Provencher, Unit of Analysis for Poverty Measurement: A Comparison of the
Supplemental Poverty Measure and the Official Poverty Measure
, U.S. Census Bureau, SEHSD Working Paper #
2011-22, Washington, DC, August 2, 2011, http://www.census.gov/hhes/povmeas/methodology/supplemental/research/
Provencher_JSM.pdf.
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Figure 10. Poverty Rates Under the “Official”* and Research Supplemental Poverty
Measures, by Type of Economic Unit: 2013
(Percent Poor)

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The
Supplemental Poverty Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014,
http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf.
* Differs from published “official” poverty rates as unrelated individuals under age 15 are included in the
universe.
Poverty by Region
Figure 11 compares poverty rates in 2013 under the SPM with the “official” measure by Census
region. The figure shows that poverty rates in the West are considerably higher (26% higher)
under the SPM (18.7%) than under the “official” measure (14.8%). Poverty rates are about 11%
higher in the Northeast under the SPM (14.3%) compared to the “official” measure (12.8%).
Poverty rates in the Midwest are lower under the SPM than under the “official” measure, and in
the South, essentially equal. The differences in poverty rates within and between regions based on
the SPM compared to the “official” measure are most directly due to the SPM’s geographic price
adjustments to poverty thresholds for differences in the cost of housing in metropolitan and
nonmetropolitan areas across states. The cost of housing tends to be higher in the West and
Northeast, causing their poverty rates to rise under the SPM relative to the “official” measure and
relative to the South and Midwest, where housing tends to be less expensive.

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Figure 11. Poverty Rates Under the “Official”* and Research Supplemental Poverty
Measures, by Region: 2013
(Percent Poor)

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The
Supplemental Poverty Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014,
http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf.
* Differs from published “official” poverty rates as unrelated individuals under age 15 are included in the
universe.
Poverty by Residence
Figure 12 depicts poverty rates by residence in metropolitan (principal city, and outside principal
city [i.e., “suburban”]) and nonmetropolitan areas in 2013.26 The figure shows that under the
SPM, the poverty rate for persons living in Metropolitan Statistical Areas (MSAs) (15.9%) is
somewhat higher than under the “official” measure (14.3%), whereas for persons living outside
MSAs, the poverty rate is lower under the SPM (13.2%) than under the “official” measure
(16.2%). Again, this most likely reflects differences in the cost of housing between MSAs and
non-MSAs. Within MSAs, poverty rates are higher for persons living within principal cities under
both measures than for people living outside them in “suburban” or “ex-urban” areas.

26 The Census Bureau defines Metropolitan Statistical Areas (MSAs) containing a core urban area with a population of
50,000 or more, consisting of one or more counties, that includes the counties containing the urban core area as well as
any adjacent counties that have a high degree of social and economic integration (as measured by commuting to work)
with the urban core. See http://www.census.gov/population/metro/.
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Figure 12. Poverty Rates Under the “Official”* and Research Supplemental Poverty
Measures, by Residence: 2013
(Percent Poor)

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The
Supplemental Poverty Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014,
http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf.
* Differs from published “official” poverty rates as unrelated individuals under age 15 are included in the
universe.
Poverty by State
Figure 13 depicts states according to whether the state’s SPM poverty rate statistically differs
from its “official” poverty rate.27 Estimates are based on three-year (2011 to 2013) averages of
CPS/ASEC data. Three years of data are combined in order to improve the statistical reliability of
CPS/ASEC estimates at the state level. The figure shows that 13 states (Alaska, California,
Connecticut, Florida, Hawaii, Illinois, Maryland, Massachusetts, Nevada, New Hampshire, New
Jersey, New York, and Virginia) and the District of Columbia had higher poverty rates under the
SPM than under the “official” measure. Among the 13 states with higher SPM poverty rates than
their respective “official” poverty rate, only Illinois and Nevada were inland, and with the
exception of Florida and Virginia, none were in the South. The figure shows that the SPM poverty
rate was not statistically different than the “official” poverty rate in 11 states (Arizona, Colorado,
Delaware, Georgia, Minnesota, Oregon, Pennsylvania, Rhode Island, Utah, Vermont, and
Washington). Among the 26 remaining states in which their SPM poverty rates were lower than

27 Significant differences based on a 90% statistical confidence level.
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their respective “official” poverty rates, nearly all (with Maine being the exception) were either in
the South, or inland.
Figure 13. Difference in Poverty Rates by State Using the “Official”* Measure and
the SPM: Three-Year Average 2011-2013

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The
Supplemental Poverty Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014,
http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf.
Notes: Within state difference between official and SPM poverty rates determined at a 90% statistical
confidence level.
* Differs from published “official” poverty rates as unrelated individuals under age 15 are included in the
universe.
Figure 14 and Figure 15 depict poverty rates by state under the official poverty measure and the
SPM based on three years of CPS/ASEC data. Estimates are based on three-year (2011 to 2013)
averages to improve the statistical reliability of estimates attainable from CPS/ASEC data at the
state level. The two figures differ only in terms of the order in which states are sorted. In Figure
14
, states are sorted from lowest to highest based on their respective “official” poverty rate point
estimates, whereas in Figure 15 states are sorted from lowest to highest based on their respective
SPM poverty rate point estimates. In neither figure are precise rankings of states possible because
of the depicted margin of error around each state’s estimate. Within a state, a statistically
significant difference28 between a state’s official poverty rate and its SPM poverty rate is signified

28 Significant difference at a 90% statistical confidence level.
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by solid-filled markers, indicating the point estimate under each measure, and a line connecting
them, indicating the estimated difference (which is also shown in parentheses after each state
name). The figures show the magnitude of the difference among the 13 states and the District of
Columbia that had statistically significant higher poverty rates under the SPM than under the
“official” measure, as well as for the 26 states in which the state’s SPM rate was lower than its
“official” poverty rate and the 11 states in which the incidence of poverty under the two measures
did not differ statistically.
Differences in state poverty rates based on the SPM compared to the “official” measure may be
due to a variety of factors. Geographic adjustments to SPM poverty income thresholds to account
for differences in housing costs tend to result in higher poverty rates in areas with higher-priced
housing than in areas with lower-priced housing. The mix of housing tenure (e.g., owner
occupied, with or without a mortgage, renter occupied) may account for some of the difference
between “official” and SPM poverty rates, within and between areas. Similarly, taxes may differ
among areas. Also, populations may differ across areas in terms of household composition (e.g.,
share of households with cohabiting partners). The composition of the population based on age,
or health insurance status, may also affect the incidence of SPM poverty relative to “official”
poverty within and between geographic areas, by affecting medical out of pocket spending
(MOOP), which is considered by SPM in estimating poverty.
Among the states with a statistically significant increase in poverty under the SPM, California’s
poverty rate increased by more than any other state’s, increasing from 16.0% under the “official”
measure to 23.4% under the SPM, or 7.4 percentage points. Under the “official” measure,
California’s poverty rate was substantially above the U.S. rate (14.6%), but under the SPM,
California’s poverty rate is estimated as the highest in the nation.
Other states with comparatively large increases in their poverty rates (in the four to five
percentage point range) under the SPM compared to the “official” measure include Florida (a
15.1% to 19.1% increase), Hawaii (an increase from 12.4% to 18.4%), and New Jersey (a 10.7%
to 15.9% increase).
Four states had decreases in their SPM poverty rate compared to their “official” rate in the four to
five percentage point range. Among the states with the highest “official” poverty rates, New
Mexico and Mississippi, (21.5% and 20.7%, respectively) both have estimated SPM poverty rates
(16.0% and 15.3%, respectively) statistically tied with U.S. SPM rate (15.9%). Kentucky and
West Virginia’s “official” poverty rates (18.1% and 17.4%, respectively) are well above the
“official” U.S. rate (14.9%), but their SPM poverty rates (13.8% and 13.2%) fall well below the
U.S. SPM rate (15.9%).
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Figure 14. Poverty Rates by State Using the “Official”* Measure and the SPM:
Three-Year Average 2010-2013
(States Ranked in Ascending Order by Official Poverty Rate; Percentage Point Difference in Parentheses)

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The Supplemental
Poverty Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014, http://census.gov/content/dam/
Census/library/publications/2014/demo/p60-251.pdf.
* Differs from published “official” poverty rates as unrelated individuals under age 15 are included in the universe.
** Within state difference between official and SPM poverty rates determined at a 90% statistical confidence level.


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Figure 15. Poverty Rates by State Using the “Official”* Measure and the SPM: Three-
Year Average 2010-2013
(States Ranked in Ascending Order by SPM Poverty Rate; Percentage Point Difference in Parentheses)

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The Supplemental Poverty
Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014, http://census.gov/content/dam/Census/
library/publications/2014/demo/p60-251.pdf.
* Differs from published “official” poverty rates as unrelated individuals under age 15 are included in the universe.
** Within state difference between official and SPM poverty rates determined at a 90% statistical confidence level.

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Marginal Effects of Counting Specified Resources and Expenses on Poverty
under the SPM

Figure 16 focuses strictly on the SPM, examining the marginal effects on poverty rates
attributable to the inclusion of each selected income/resource or expenditure element on the
measure. The marginal effects of each element on the SPM are displayed by age group. Elements
that marginally contribute resources, and thereby have a poverty reducing effect when included in
the SPM, are ranked from left to right in terms of their effect on poverty reduction among all
persons. Similarly, expenditure elements, which are subtracted from resources and thereby
marginally increase poverty as measured by the SPM, are ranked from left to right by their
marginal poverty increasing effects on all persons.
The figure shows, for example, that the EITC has a greater poverty reducing effect than any of the
other depicted resource elements. Overall, the EITC lowers the SPM poverty rate for all persons
by 2.9 percentage points. The EITC is followed by SNAP benefits (1.6 percentage point
reduction), housing subsidies (1.3 percentage point reduction), school lunch (0.5 percentage point
reduction), and WIC (0.2 percentage point reduction) and LIHEAP (0.1 percentage point
reduction).
In contrast, on the expenditure side, child support paid to members outside the household has a
relatively small effect on increasing the overall poverty rate. Federal income taxes before
considering refundable credits, such as the EITC (counted on the resource side), result in an
increase in overall poverty of 0.4 percentage points. FICA payroll taxes have a larger effect on
marginal poverty (1.5 percentage point increase) than federal income taxes, as do work expenses
(1.9 percentage points). Among all of the expense elements presented, medical out of pocket
expenses (MOOP) contribute to the largest increase in poverty (3.5 percentage point increase for
all persons).
Among the three age groups, the additional resources included in the SPM have a greater effect
on reducing poverty among children (persons under age 18) and poverty among working age
adults (ages 18 to 64) than on the aged (age 65 and older), with the exception of housing
subsidies, which reduce the aged poverty rate by about the same amount as that of children. The
EITC has a greater effect of reducing poverty among children (6.4 percentage point reduction)
than any of the other added SPM resources.
On the expenditure side, FICA payroll taxes and work expenses have a greater effect on
increasing poverty among children (due to a working parent) and non-aged adults than on the
aged, who are less likely to be in the labor force and incur work-related taxes and expenses.
Notably, under the SPM, MOOP expenses contribute to a substantial increase in poverty among
the aged, contributing to a 6.3 percentage point increase in their poverty rate.
The relative distribution of additional resources and expenses in the SPM by age group helps to
explain why poverty among children is lower under the SPM than it is under the “official”
measure, whereas it is considerably higher for the aged.
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Figure 16. Percentage Point Change in Poverty Rates Attributable to Selected
Income and Expenditure Elements Under the Research Supplemental Poverty
Measure, by Age Group: 2013

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The
Supplemental Poverty Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014,
http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf.

Distribution of the Population by Ratio of Income/Resources
Relative to Poverty

Figure 17 shows the distribution of the population by age group according to the degree to which
their income and resources fall below or above poverty under the “official” and SPM definitions.
The figure breaks out the poor population, depicted by brackets, into the share whose income and
resources fall below half of their respective poverty lines (a classification sometimes referred to
as “deep poverty”) and the remainder. Others are categorized by the extent to which their
income/resources exceed poverty under the two definitions, with those who fall below twice the
poverty line also demarcated by brackets.
The figure shows, for example, that the share of children in “deep poverty” under the SPM is
considerably lower than under the “official” measure (4.4% compared to 9.3%). As shown earlier,
the SPM child poverty rate (16.4%) is lower than the “official” rate (20.3%). However, under the
SPM, a much greater share of children live in “families” with income/resources between one and
two times the poverty line than under the “official” measure (38.2% compared to 22.5%,
respectively). Altogether, well over half of the children live in “families” having
income/resources below twice the poverty line under the SPM (54.6%) compared to about two-
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fifths (42.8%) under the “official” measure. Thus, while the SPM appears to result in fewer
children being counted as poor than under the “official” measure, under the SPM a greater share
than under the “official” measure are concentrated at income levels just above poverty.
Among persons age 65 and over, a greater share are poor under the SPM than under the “official”
measure, as shown earlier (14.6% compared to 9.5%), and a greater share are in “deep poverty”
under the SPM (4.8%) than under the “official” measure (2.7%). In contrast to the “official”
measure, under which one-third (33.1%) of the aged have income below 200% of poverty,
somewhat under half (45.1%) have income/resources below that level under the SPM.
Figure 17. Distribution of the Population by Income/Resources to Poverty Ratios
Under the “Official”* and Research Supplemental Poverty Measures, by Age Group:
2013
(Percent distribution)

Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The
Supplemental Poverty Measure: 2013
, U.S. Census Bureau, P60-251, Washington, DC, October 2014,
http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf.
* Differs from published “official” poverty rates as unrelated individuals under age 15 are included in the
universe.
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Discussion
As a research measure, the SPM offers potential for improved insight leading to better
understanding of the nature and circumstances of those deemed to be among the nation’s most
economically and socially vulnerable. The SPM offers the means to better assess the performance
of the economy, government policies, and programs with regard to the population’s ability to
secure sufficient income/resources to be able to meet basic expenditures for food, clothing,
shelter, and utilities (plus “a little bit more”).
The SPM counts considerably more elderly as poor than does the “official” measure. Medical
expenses appear to be the driving factor in increasing poverty among the elderly under the SPM
(see Figure 16). While not negating the improvement in the poverty status of the aged over the
years, based on the “official” measure (see Figure 2), the SPM points more directly to the
economic vulnerability of the aged, based not on income/resources alone, but rather, medical
expenses competing for income that might otherwise be used to meet basic needs (i.e., FCSU plus
“a little bit more”). Rising medical costs in society overall and individuals’ personal health and
insurance statuses pose potential economic risk to the aged being able to meet basic needs, as
captured by FCSU-based poverty thresholds. The SPM provides additional insight that poverty
reduction among the elderly depends not only on improving income, but also on their ability to
reduce exposure to high medical expenses through “affordable” insurance. Rising medical costs
in society also place the aged at increased risk of poverty under the SPM. It is worth noting that
the SPM does not consider financial assets, other than interest, dividends, and annuity income
from those assets, nor non-liquid assets (e.g., home equity) in determining poverty status. The
SPM therefore does not address the means or extent to which the aged might tap those assets to
meet medical or other needs.
The SPM results in fewer children being counted as poor than under the “official” measure. Still,
the incidence of child poverty under the SPM, as under the “official” measure, exceeds that of the
aged, but by a much slimmer margin (see Figure 9). Work-based supports, which both encourage
work and help to offset the costs of going to work, appear be especially important to families with
children, as captured by the SPM. The EITC, not counted under the “official” measure,
significantly reduces child poverty as measured by the SPM, helping to offset taxes and work-
related expenses working families with children incur (also captured by the SPM, but not under
the “official” measure) (see Figure 16). The lack of safe, reliable, and affordable child care may
limit parents’ attachment to the labor force, contributing to poverty by reducing earnings that
parents might otherwise secure. The SPM recognizes child care as a necessary expense many
families face in their decisions relating to work by subtracting work-related child care expenses
from income/resources that might otherwise go to meeting basic needs (i.e., FCSU plus “a little
bit more”). As a consequence, the SPM should be sensitive to measuring the effects of child care
programs and policies on child care affordability and poverty. The SPM captures the policy
effects of assisting the poor through the provision of in-kind benefits, as opposed to just cash,
whereas the “official” measure does not. For example, SNAP benefits, not captured under the
“official” poverty measure, appear to have a sizeable effect in reducing child poverty under the
SPM. Additionally, the expansion of the economic unit under the SPM to include cohabiting
partners and their relatives may also contribute to lower child poverty rates under the SPM than
under the “official” poverty measure, which is based on family ties defined by blood, marriage,
and adoption.

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Appendix A. U.S. Poverty Statistics: 1959-2013
Table A-1. Poverty Rates (Percent Poor) for Selected Groups, 1959-2013
Related Children

Under Age18a
Adults
Race/Ethnicityb—All Ages
In
Female-
In All
Ages
White
Hispanic
All
Headed
Other
18-
Age
Non-
(any
Year Persons Total Families Families
64
65+
Whiteb Hispanicb Blackb
race)
Asianb
2013
14.5 19.5
45.8
10.7 13.6 9.5 12.3b 9.6b 27.2b 23.5b 10.5b
2012
15.0 21.3
47.2
12.5 13.7 9.1 12.7b 9.7b 27.2b 25.6
11.7b
2011
15.0 21.4
47.6
12.1 13.7 8.7 12.8b 9.8b 27.6b 25.3
12.3b
2010r
15.1 21.5
46.6
12.9 13.8 8.9 13.0b 9.9b 27.4b 26.5
12.2b
2009
14.3 20.1
44.4
12.3 12.9 8.9 12.3b 9.4b 25.8b 25.3
12.5b
2008
13.2 18.5
43.5
10.7 11.7 9.7 11.2b 8.6b 24.7b 23.2
11.8b
2007
12.5 17.6
43.0
9.5 10.9 9.7 10.5b 8.2b 24.5b 21.5
10.2b
2006
12.3 16.9
42.1
9.0 10.8 9.4 10.3b 8.2b 24.3b 20.6
10.3b
2005
12.6 17.1
42.8
9.3 11.1 10.1 10.6b 8.3b 24.9b 21.8
11.1b
2004r
12.7 17.3
41.9
9.7 11.3 9.8 10.8b 8.7b 24.7b 21.9
9.8b
2003
12.5 17.2
41.8
9.6 10.8 10.2 10.5b 8.2b 24.4b 22.5
11.8b
2002
12.1 16.3
39.6
9.2 10.6 10.4 10.2b 8.0b 24.1b 21.8
10.1b
2001
11.7 15.8
39.3
8.8 10.1 10.1
9.9
7.8 22.7
21.4
n/a
2000r 11.3 15.6 40.1
8.6 9.6 9.9 9.5
7.4 22.5 21.5 n/a
1999
11.8 16.3
41.9
9.0 10.0 9.7
9.8
7.7 23.6
22.8
n/a
1998
12.7 18.3
46.1
9.7 10.5 10.5 10.5
8.2 26.1
25.6
n/a
1997
13.3 19.2
49.0
10.2 10.9 10.5 11.0
8.6 26.5
27.1
n/a
1996
13.7 19.8
49.3
10.9 11.3 10.8 11.2
8.6 28.4
29.4
n/a
1995
13.8 20.2
50.3
10.7 11.4 10.5 11.2
8.5 29.3
30.3
n/a
1994
14.5 21.2
52.9
11.7 11.9 11.7 11.7
9.4 30.6
30.7
n/a
1993
15.1 22.0
53.7
12.4 12.4 12.2 12.2
9.9 33.1
30.6
n/a
1992r
14.8 21.6
54.6
11.8 11.9 12.9 11.9
9.6 33.4
29.6
n/a
1991r
14.2 21.1
55.5
11.1 11.4 12.4 11.3
9.4 32.7
28.7
n/a
1990
13.5 19.9
53.4
10.7 10.7 12.2 10.7
8.8 31.9
28.1
n/a
1989
12.8 19.0
51.1
10.4 10.2 11.4 10.0
8.3 30.7
26.2
n/a
1988r
13.0 19.0
52.9
10.0 10.5 12.0 10.1
8.4 31.3
26.7
n/a
1987r
13.4 19.7
54.7
10.9 10.6 12.5 10.4
8.7 32.4
28.0
n/a
1986
13.6 19.8
54.4
10.8 10.8 12.4 11.0
9.4 31.1
27.3
n/a
1985
14.0 20.1
53.6
11.7 11.3 12.6 11.4
9.7 31.3
29.0
n/a
1984
14.4 21.0
54.0
12.5 11.7 12.4 11.5
10.0 33.8
28.4
n/a
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Related Children

Under Age18a
Adults
Race/Ethnicityb—All Ages
In
Female-
In All
Ages
White
Hispanic
All
Headed
Other
18-
Age
Non-
(any
Year Persons Total Families Families
64
65+
Whiteb Hispanicb Blackb
race)
Asianb
1983
15.2 21.8
55.5
13.5 12.4 13.8 12.2
10.8 35.7
28.1
n/a
1982
15.0 21.3
56.0
13.0 12.0 14.6 12.0
10.6 35.6
29.9
n/a
1981
14.0 19.5
52.3
11.6 11.1 15.3 11.1
9.9 34.2
26.5
n/a
1980
13.0 17.9
50.8
10.4 10.1 15.7 10.2
9.1 32.5
25.7
n/a
1979
11.7 16.0
48.6
8.5 8.9 15.2
9.0
8.1 31.0
21.8
n/a
1978
11.4 15.7
50.6
7.9 8.7 14.0
8.7
7.9 30.6
21.6
n/a
1977
11.6 16.0
50.3
8.5 8.8 14.1
8.9
8.0 31.3
22.4
n/a
1976
11.8 15.8
52.0
8.5 9.0 15.0
9.1
8.1 31.1
24.7
n/a
1975
12.3 16.8
52.7
9.8 9.2 15.3
9.7
8.6 31.3
26.9
n/a
1974
11.2 15.1
51.5
8.3 8.3 14.6
8.6
7.7 30.3
23.0
n/a
1973
11.1 14.2
52.1
7.6 8.3 16.3
8.4
7.5 31.4
21.9
n/a
1972
11.9 14.9
53.1
8.6 8.8 18.6
9.0
n/a 33.3
n/a
n/a
1971
12.5 15.1
53.1
9.3 9.3 21.6
9.9
n/a 32.5
n/a
n/a
1970
12.6 14.9
53.0
9.2 9.0 24.6
9.9
n/a 33.5
n/a
n/a
1969
12.1 13.8
54.4
8.6 8.7 25.3
9.5
n/a 32.2
n/a
n/a
1968
12.8 15.3
55.2
10.2 9.0 25.0 10.0
n/a 34.7
n/a
n/a
1967
14.2 16.3
54.3
11.5 10.0 29.5 11.0
n/a 39.3
n/a
n/a
1966
14.7 17.4
58.2
12.6 10.5 28.5 11.3
n/a 41.8
n/a
n/a
1959
22.4 26.9
72.2
22.4 17.0 35.2 18.1
n/a 55.1
n/a
n/a
Source: Prepared by the Congressional Research Service using U.S. Bureau of the Census data based on the
“official” measure of poverty.
Notes: r = revised estimates. n/a = not available.
a. Beginning in 1979, restricted to children in primary families only. Before 1979, includes children in unrelated
subfamilies.
b. Beginning in 2002, CPS respondents could identify themselves as being of more than one race.
Consequently, racial data for 2002 and after are not comparable to earlier years. Here, in 2002 and after,
the term white means of white race alone, the term black means of black race alone, and the term Asian
means Asian alone. Hispanics, who may be of any race, are included among whites and blacks unless
otherwise noted.

Congressional Research Service
46


Appendix B. Metropolitan Area Poverty Estimates
Table B-1. Metropolitan Area Poverty: 2013


Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora
Rankb
Abilene, TX
154,458
26,016
+/-3,491
16.8%
+/-2.2%
169
Akron, OH
690,331
106,377
+/-7,877
15.4%
+/-1.1%
237
Albany, GA
150,485
37,441
+/-4,405
24.9%
+/-2.8%
15
Albany, OR
117,252
23,986
+/-4,096
20.5%
+/-3.5%
60
Albany-Schenectady-Troy, NY
846,922
105,640
+/-8,545
12.5%
+/-1.0%
320
Albuquerque, NM
890,054
173,028
+/-10,925
19.4%
+/-1.2%
86
Alexandria, LA
147,861
27,656
+/-3,989
18.7%
+/-2.7%
110
Allentown-Bethlehem-Easton, PA-NJ
804,393
99,692 +/-6,980
12.4%
+/-0.9%
324
Altoona, PA
123,730
20,392
+/-3,212
16.5%
+/-2.6%
182
Amaril o, TX
249,194
39,748
+/-3,969
16.0%
+/-1.6%
212
Ames, IA
84,045
19,770
+/-2,273
23.5%
+/-2.6%
22
Anchorage, AK
386,833
27,596
+/-3,586
7.1%
+/-0.9%
379
Ann Arbor, MI
335,915
56,191
+/-5,089
16.7%
+/-1.5%
175
Anniston-Oxford-Jacksonville, AL
113,722
24,825
+/-3,340
21.8%
+/-2.9%
38
Appleton, WI
226,221
18,291
+/-2,940
8.1%
+/-1.3%
376
Asheville, NC
429,282
68,399
+/-5,793
15.9%
+/-1.4%
214
Athens-Clarke County, GA
186,981
53,388
+/-5,015
28.6%
+/-2.6%
6
Atlanta-Sandy Springs-Roswel , GA
5,430,037
865,858
+/-28,129
15.9%
+/-0.5%
213
Atlantic City-Hammonton, NJ
270,136
48,716
+/-5,187
18.0%
+/-1.9%
123
Auburn-Opelika, AL
144,867
30,038
+/-4,160
20.7%
+/-2.9%
56
Augusta-Richmond County, GA-SC
565,819
111,863
+/-8,976
19.8%
+/-1.6%
80
Austin-Round Rock, TX
1,841,572
262,644
+/-14,918
14.3%
+/-0.8%
281
Bakersfield, CA
831,344
189,484
+/-13,393
22.8%
+/-1.6%
26
Baltimore-Columbia-Towson, MD
2,702,706
301,630
+/-13,812
11.2%
+/-0.5%
344
Bangor, ME
146,466
23,644
+/-3,195
16.1%
+/-2.2%
200
Barnstable Town, MA
212,139
19,313
+/-2,984
9.1%
+/-1.4%
368
CRS-47




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Baton Rouge, LA
797,912
149,025
+/-10,622
18.7%
+/-1.3%
111
Battle Creek, MI
130,542
24,261
+/-3,240
18.6%
+/-2.4%
113
Bay City, MI
105,498
18,310
+/-2,533
17.4%
+/-2.4%
145
Beaumont-Port Arthur, TX
387,482
72,048
+/-7,227
18.6%
+/-1.8%
112
Beckley, WV
118,651
25,833
+/-3,422
21.8%
+/-2.8%
40
Bel ingham, WA
200,426
34,135
+/-4,708
17.0%
+/-2.3%
160
Bend-Redmond, OR
164,655
26,397
+/-4,828
16.0%
+/-2.9%
207
Billings, MT
161,276
20,745
+/-2,832
12.9%
+/-1.7%
310
Binghamton, NY
236,898
38,784
+/-4,249
16.4%
+/-1.8%
189
Birmingham-Hoover, AL
1,116,257
188,610
+/-9,521
16.9%
+/-0.9%
166
Bismarck, ND
121,277
10,119
+/-1,758
8.3%
+/-1.5%
374
Blacksburg-Christiansburg-Radford, VA
166,843
37,896
+/-4,544
22.7%
+/-2.6%
27
Bloomington, IL
184,309
27,681
+/-3,555
15.0%
+/-1.9%
249
Bloomington, IN
148,709
33,760
+/-3,426
22.7%
+/-2.2%
28
Bloomsburg-Berwick, PA
80,653
13,275
+/-2,443
16.5%
+/-3.0%
183
Boise City, ID
637,683
107,713
+/-12,906
16.9%
+/-2.0%
167
Boston-Cambridge-Newton, MA-NH
4,525,102
470,178
+/-18,981
10.4%
+/-0.4%
357
Boulder, CO
300,101
41,700
+/-4,077
13.9%
+/-1.4%
287
Bowling Green, KY
156,092
30,727
+/-3,873
19.7%
+/-2.4%
82
Bremerton-Silverdale, WA
245,971
27,727
+/-4,028
11.3%
+/-1.6%
342
Bridgeport-Stamford-Norwalk, CT
921,302
88,808
+/-6,895
9.6%
+/-0.7%
359
Brownsville-Harlingen, TX
412,432
134,170
+/-8,943
32.5%
+/-2.2%
2
Brunswick, GA
111,440
22,111
+/-4,204
19.8%
+/-3.8%
76
Buffalo-Cheektowaga-Niagara Fal s, NY
1,103,165
164,100
+/-8,568
14.9%
+/-0.8%
257
Burlington, NC
150,206
31,103
+/-4,266
20.7%
+/-2.8%
57
Burlington-South Burlington, VT
205,647
21,596
+/-3,045
10.5%
+/-1.5%
353
California-Lexington Park, MD
106,530
6,831
+/-2,204
6.4%
+/-2.1%
381
Canton-Massil on, OH
394,097
61,713
+/-5,716
15.7%
+/-1.4%
223
Cape Coral-Fort Myers, FL
649,199
107,225
+/-8,880
16.5%
+/-1.4%
181
Cape Girardeau, MO-IL
91,588
16,457
+/-2,819
18.0%
+/-2.9%
124
Carbondale-Marion, IL
120,496
27,530
+/-3,465
22.8%
+/-2.8%
25
CRS-48




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Carson City, NV
52,168
7,885
+/-2,319
15.1%
+/-4.4%
245
Casper, WY
79,240
7,448
+/-1,658
9.4%
+/-2.1%
364
Cedar Rapids, IA
255,759
23,609
+/-3,504
9.2%
+/-1.4%
367
Chambersburg-Waynesboro, PA
148,856
19,211
+/-3,790
12.9%
+/-2.5%
305
Champaign-Urbana, IL
217,009
44,185
+/-3,690
20.4%
+/-1.7%
62
Charleston, WV
220,824
36,049
+/-4,747
16.3%
+/-2.1%
191
Charleston-North Charleston, SC
693,815
112,715
+/-7,581
16.2%
+/-1.1%
194
Charlotte-Concord-Gastonia, NC-SC
2,298,466
339,434
+/-15,265
14.8%
+/-0.7%
263
Charlottesville, VA
211,108
33,811
+/-4,219
16.0%
+/-2.0%
208
Chattanooga, TN-GA
527,350
85,002
+/-7,650
16.1%
+/-1.4%
202
Cheyenne, WY
93,972
8,952
+/-2,894
9.5%
+/-3.1%
361
Chicago-Naperville-Elgin, IL-IN-WI
9,375,444
1,347,179
+/-32,543
14.4%
+/-0.3%
277
Chico, CA
217,808
46,895
+/-5,012
21.5%
+/-2.3%
45
Cincinnati, OH-KY-IN
2,084,132
301,214
+/-13,602
14.5%
+/-0.7%
273
Clarksville, TN-KY
262,145
42,952
+/-4,799
16.4%
+/-1.8%
187
Cleveland, TN
116,431
23,016
+/-4,071
19.8%
+/-3.5%
81
Cleveland-Elyria, OH
2,023,498
315,381
+/-14,229
15.6%
+/-0.7%
226
Coeur d'Alene, ID
142,546
17,161
+/-3,928
12.0%
+/-2.8%
330
Col ege Station-Bryan, TX
224,477
63,800
+/-6,284
28.4%
+/-2.8%
7
Colorado Springs, CO
660,782
71,297
+/-7,162
10.8%
+/-1.1%
350
Columbia, MO
161,119
34,118
+/-3,949
21.2%
+/-2.4%
52
Columbia, SC
757,614
125,517
+/-9,093
16.6%
+/-1.2%
180
Columbus, GA-AL
299,327
64,754
+/-6,177
21.6%
+/-2.0%
43
Columbus, IN
77,877
9,387
+/-2,413
12.1%
+/-3.1%
329
Columbus, OH
1,913,546
283,702
+/-15,369
14.8%
+/-0.8%
258
Corpus Christi, TX
436,129
75,592
+/-7,264
17.3%
+/-1.6%
146
Corval is, OR
81,212
18,762
+/-2,296
23.1%
+/-2.8%
23
Crestview-Fort Walton Beach-Destin, FL
246,364
38,598
+/-5,626
15.7%
+/-2.3%
222
Cumberland, MD-WV
93,006
16,404
+/-2,954
17.6%
+/-3.2%
136
Dal as-Fort Worth-Arlington, TX
6,724,464
1,005,325
+/-30,615
15.0%
+/-0.5%
253
Dalton, GA
140,291
30,592
+/-4,719
21.8%
+/-3.4%
39
CRS-49




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Danville, IL
77,461
14,964
+/-2,398
19.3%
+/-3.1%
90
Daphne-Fairhope-Foley, AL
192,943
28,028
+/-5,351
14.5%
+/-2.8%
270
Davenport-Moline-Rock Island, IA-IL
373,851
54,024
+/-5,283
14.5%
+/-1.4%
274
Dayton, OH
776,921
127,254
+/-9,611
16.4%
+/-1.2%
188
Decatur, AL
150,726
26,408
+/-3,888
17.5%
+/-2.6%
139
Decatur, IL
105,437
19,243
+/-3,025
18.3%
+/-2.9%
119
Deltona-Daytona Beach-Ormond Beach, FL
589,119
95,566
+/-8,042
16.2%
+/-1.4%
195
Denver-Aurora-Lakewood, CO
2,663,509
323,179
+/-15,703
12.1%
+/-0.6%
328
Des Moines-West Des Moines, IA
588,147
64,790
+/-5,793
11.0%
+/-1.0%
346
Detroit-Warren-Dearborn, MI
4,252,247
717,584
+/-17,780
16.9%
+/-0.4%
168
Dothan, AL
146,190
26,816
+/-2,595
18.3%
+/-1.8%
116
Dover, DE
164,302
20,334
+/-3,558
12.4%
+/-2.2%
325
Dubuque, IA
92,158
12,633
+/-1,868
13.7%
+/-2.0%
291
Duluth, MN-WI
269,518
45,693
+/-4,614
17.0%
+/-1.7%
163
Durham-Chapel Hill, NC
510,288
86,378
+/-6,899
16.9%
+/-1.3%
165
East Stroudsburg, PA
164,528
17,845
+/-3,781
10.8%
+/-2.3%
349
Eau Claire, WI
157,876
18,956
+/-3,155
12.0%
+/-2.0%
332
El Centro, CA
165,902
36,645
+/-5,905
22.1%
+/-3.5%
35
El Paso, TX
816,158
184,427
+/-12,589
22.6%
+/-1.5%
30
Elizabethtown-Fort Knox, KY
147,225
23,253
+/-3,377
15.8%
+/-2.3%
220
Elkhart-Goshen, IN
195,903
31,743
+/-5,292
16.2%
+/-2.7%
197
Elmira, NY
83,345
14,217
+/-2,131
17.1%
+/-2.6%
158
Erie, PA
267,946
49,005
+/-5,936
18.3%
+/-2.2%
118
Eugene, OR
349,317
75,232
+/-7,088
21.5%
+/-2.0%
44
Evansville, IN-KY
305,403
49,315
+/-5,336
16.1%
+/-1.7%
199
Fairbanks, AK
96,578
7,442
+/-2,543
7.7%
+/-2.6%
378
Fargo, ND-MN
214,216
29,879
+/-3,940
13.9%
+/-1.8%
285
Farmington, NM
125,488
28,442
+/-4,450
22.7%
+/-3.5%
29
Fayetteville, NC
365,455
68,554 +/-5,288
18.8%
+/-1.4%
106
Fayetteville-Springdale-Rogers, AR-MO
480,149
80,859 +/-8,372
16.8%
+/-1.7%
170
Flagstaff, AZ
127,378
30,726
+/-3,789
24.1%
+/-2.9%
17
CRS-50




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Flint, MI
409,193
88,579
+/-7,484
21.6%
+/-1.8%
42
Florence, SC
201,368
46,093
+/-5,753
22.9%
+/-2.9%
24
Florence-Muscle Shoals, AL
144,987
23,034
+/-2,993
15.9%
+/-2.1%
218
Fond du Lac, WI
98,663
8,023
+/-1,707
8.1%
+/-1.7%
375
Fort Collins, CO
307,412
43,846
+/-4,203
14.3%
+/-1.4%
280
Fort Smith, AR-OK
275,581
65,557
+/-6,172
23.8%
+/-2.2%
19
Fort Wayne, IN
416,163
66,755
+/-5,712
16.0%
+/-1.4%
206
Fresno, CA
937,990
270,072
+/-12,767
28.8%
+/-1.4%
5
Gadsden, AL
102,633
19,363
+/-3,161
18.9%
+/-3.1%
102
Gainesville, FL
256,894
68,758
+/-5,496
26.8%
+/-2.1%
10
Gainesville, GA
185,118
40,630
+/-5,458
21.9%
+/-2.9%
37
Gettysburg, PA
97,009
8,620
+/-2,132
8.9%
+/-2.2%
372
Glens Falls, NY
124,199
15,784
+/-2,676
12.7%
+/-2.2%
316
Goldsboro, NC
120,867
25,910
+/-5,137
21.4%
+/-4.2%
47
Grand Forks, ND-MN
94,728
14,555
+/-1,687
15.4%
+/-1.8%
238
Grand Island, NE
81,981
12,340
+/-2,849
15.1%
+/-3.5%
246
Grand Junction, CO
143,253
23,910
+/-4,425
16.7%
+/-3.1%
176
Grand Rapids-Wyoming, MI
993,281
139,139
+/-8,997
14.0%
+/-0.9%
284
Grants Pass, OR
82,361
14,035
+/-3,095
17.0%
+/-3.8%
159
Great Falls, MT
80,102
12,814
+/-2,715
16.0%
+/-3.4%
210
Greeley, CO
263,036
35,126
+/-4,926
13.4%
+/-1.9%
300
Green Bay, WI
304,580
36,549
+/-5,101
12.0%
+/-1.7%
333
Greensboro-High Point, NC
722,405
143,646
+/-9,658
19.9%
+/-1.3%
75
Greenville, NC
168,611
43,223
+/-5,197
25.6%
+/-3.1%
11
Greenville-Anderson-Mauldin, SC
826,492
143,919
+/-11,385
17.4%
+/-1.4%
142
Gulfport-Biloxi-Pascagoula, MS
375,050
72,312
+/-7,842
19.3%
+/-2.1%
93
Hagerstown-Martinsburg, MD-WV
246,865
30,667
+/-4,873
12.4%
+/-2.0%
322
Hammond, LA
121,122
26,234
+/-4,042
21.7%
+/-3.3%
41
Hanford-Corcoran, CA
133,031
28,473
+/-5,298
21.4%
+/-4.0%
48
Harrisburg-Carlisle, PA
538,015
61,268
+/-5,964
11.4%
+/-1.1%
339
Harrisonburg, VA
119,953
20,308
+/-3,245
16.9%
+/-2.7%
164
CRS-51




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Hartford-West Hartford-East Hartford, CT
1,169,485
125,923
+/-9,009
10.8%
+/-0.8%
351
Hattiesburg, MS
144,861
34,291
+/-4,546
23.7%
+/-3.1%
20
Hickory-Lenoir-Morganton, NC
356,214
61,715
+/-6,542
17.3%
+/-1.8%
148
Hilton Head Island-Bluffton-Beaufort, SC
192,499
30,949
+/-5,259
16.1%
+/-2.7%
204
Hinesvil e, GA
79,128
16,111
+/-3,079
20.4%
+/-3.9%
63
Homosassa Springs, FL
136,633
22,952
+/-3,284
16.8%
+/-2.4%
172
Hot Springs, AR
94,437
22,668
+/-3,723
24.0%
+/-3.9%
18
Houma-Thibodaux, LA
205,658
27,916
+/-4,139
13.6%
+/-2.0%
292
Houston-The Woodlands-Sugar Land, TX
6,228,091
1,021,922
+/-32,157
16.4%
+/-0.5%
184
Huntington-Ashland, WV-KY-OH
354,931
71,701
+/-6,538
20.2%
+/-1.8%
67
Huntsvil e, AL
423,978
63,797
+/-6,818
15.0%
+/-1.6%
247
Idaho Fal s, ID
135,972
15,189
+/-3,087
11.2%
+/-2.3%
343
Indianapolis-Carmel-Anderson, IN
1,909,800
290,647
+/-12,942
15.2%
+/-0.7%
242
Iowa City, IA
152,657
23,856
+/-3,159
15.6%
+/-2.1%
224
Ithaca, NY
88,377
17,907
+/-2,704
20.3%
+/-2.9%
66
Jackson, MI
150,916
29,064
+/-3,814
19.3%
+/-2.5%
94
Jackson, MS
557,607
122,754
+/-7,806
22.0%
+/-1.4%
36
Jackson, TN
125,360
26,178
+/-3,335
20.9%
+/-2.7%
54
Jacksonville, FL
1,366,441
202,025
+/-12,483
14.8%
+/-0.9%
262
Jacksonville, NC
170,510
28,935
+/-4,900
17.0%
+/-2.8%
161
Janesville-Beloit, WI
156,924
22,915
+/-4,090
14.6%
+/-2.6%
268
Jefferson City, MO
138,359
18,375
+/-3,729
13.3%
+/-2.7%
302
Johnson City, TN
193,692
37,292
+/-4,251
19.3%
+/-2.1%
95
Johnstown, PA
132,298
21,707
+/-2,741
16.4%
+/-2.1%
185
Jonesboro, AR
121,308
25,933
+/-3,668
21.4%
+/-3.1%
50
Joplin, MO
171,028
29,190
+/-4,347
17.1%
+/-2.6%
157
Kahului-Wailuku-Lahaina, HI
158,710
15,013
+/-2,564
9.5%
+/-1.6%
362
Kalamazoo-Portage, MI
322,236
57,240
+/-5,097
17.8%
+/-1.6%
129
Kankakee, IL
107,450
18,358
+/-3,669
17.1%
+/-3.4%
155
Kansas City, MO-KS
2,018,783
255,291
+/-12,778
12.6%
+/-0.6%
318
Kennewick-Richland, WA
266,874
38,878
+/-5,751
14.6%
+/-2.2%
269
CRS-52




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Killeen-Temple, TX
401,026
57,065 +/-7,797
14.2%
+/-1.9%
282
Kingsport-Bristol-Bristol, TN-VA
302,495
54,895
+/-5,958
18.1%
+/-2.0%
121
Kingston, NY
173,358
19,549
+/-4,087
11.3%
+/-2.4%
341
Knoxville, TN
831,129
145,567
+/-9,055
17.5%
+/-1.1%
140
Kokomo, IN
81,130
12,612
+/-2,234
15.5%
+/-2.7%
228
La Crosse-Onalaska, WI-MN
130,300
20,554
+/-3,101
15.8%
+/-2.4%
221
Lafayette, LA
468,912
76,884
+/-8,310
16.4%
+/-1.8%
186
Lafayette-West Lafayette, IN
194,061
37,427
+/-5,210
19.3%
+/-2.6%
92
Lake Charles, LA
198,778
30,927
+/-4,825
15.6%
+/-2.4%
227
Lake Havasu City-Kingman, AZ
195,730
41,429
+/-6,226
21.2%
+/-3.1%
53
Lakeland-Winter Haven, FL
608,424
118,007
+/-11,131
19.4%
+/-1.8%
87
Lancaster, PA
514,196
53,694
+/-5,804
10.4%
+/-1.1%
355
Lansing-East Lansing, MI
447,127
80,872
+/-7,023
18.1%
+/-1.6%
122
Laredo, TX
258,684
80,403
+/-7,285
31.1%
+/-2.8%
3
Las Cruces, NM
208,101
57,908
+/-6,390
27.8%
+/-3.1%
8
Las Vegas-Henderson-Paradise, NV
2,002,803
321,455
+/-16,823
16.1%
+/-0.8%
205
Lawrence, KS
105,235
17,967
+/-4,054
17.1%
+/-3.8%
156
Lawton, OK
121,949
24,842
+/-3,444
20.4%
+/-2.8%
61
Lebanon, PA
131,958
14,367
+/-2,930
10.9%
+/-2.2%
348
Lewiston, ID-WA
60,924
8,151
+/-2,133
13.4%
+/-3.5%
299
Lewiston-Auburn, ME
104,601
17,884
+/-3,007
17.1%
+/-2.9%
154
Lexington-Fayette, KY
472,058
80,728
+/-6,536
17.1%
+/-1.4%
153
Lima, OH
101,118
15,154
+/-2,407
15.0%
+/-2.4%
251
Lincoln, NE
302,836
46,833
+/-5,684
15.5%
+/-1.8%
232
Little Rock-North Little Rock-Conway, AR
711,357
107,972
+/-9,231
15.2%
+/-1.3%
244
Logan, UT-ID
125,695
18,371
+/-3,207
14.6%
+/-2.5%
266
Longview, TX
207,330
39,098
+/-5,262
18.9%
+/-2.5%
103
Longview, WA
100,113
14,491
+/-3,004
14.5%
+/-3.0%
272
Los Angeles-Long Beach-Anaheim, CA
12,940,754
2,283,272
+/-40,149
17.6%
+/-0.3%
135
Louisvil e/Jefferson County, KY-IN
1,237,895
171,328
+/-12,460
13.8%
+/-1.0%
288
Lubbock, TX
292,742
51,653
+/-5,743
17.6%
+/-1.9%
134
CRS-53




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Lynchburg, VA
247,740
38,287
+/-5,316
15.5%
+/-2.1%
234
Macon, GA
221,779
55,647
+/-5,641
25.1%
+/-2.5%
14
Madera, CA
144,954
34,242
+/-5,853
23.6%
+/-4.0%
21
Madison, WI
612,386
82,323
+/-6,973
13.4%
+/-1.1%
297
Manchester-Nashua, NH
395,786
38,127
+/-5,228
9.6%
+/-1.3%
360
Manhattan, KS
88,998
18,070
+/-2,763
20.3%
+/-3.0%
65
Mankato-North Mankato, MN
92,795
15,470
+/-2,101
16.7%
+/-2.2%
177
Mansfield, OH
114,496
20,114
+/-3,059
17.6%
+/-2.6%
138
McAllen-Edinburg-Mission, TX
803,934
275,681
+/-16,441
34.3%
+/-2.0%
1
Medford, OR
205,687
38,784
+/-7,040
18.9%
+/-3.4%
104
Memphis, TN-MS-AR
1,319,206
261,291
+/-11,676
19.8%
+/-0.9%
77
Merced, CA
256,177
64,552
+/-6,551
25.2%
+/-2.6%
13
Miami-Fort Lauderdale-West Palm Beach, FL
5,751,004
1,017,832
+/-27,848
17.7%
+/-0.5%
131
Michigan City-La Porte, IN
101,722
17,699
+/-3,213
17.4%
+/-3.2%
143
Midland, MI
82,183
13,625
+/-2,449
16.6%
+/-3.0%
179
Midland, TX
153,451
14,293
+/-3,501
9.3%
+/-2.3%
366
Milwaukee-Waukesha-West Allis, WI
1,539,233
244,752
+/-10,718
15.9%
+/-0.7%
217
Minneapolis-St. Paul-Bloomington, MN-WI
3,397,278
349,161
+/-13,880
10.3%
+/-0.4%
358
Missoula, MT
108,797
19,469
+/-3,626
17.9%
+/-3.3%
125
Mobile, AL
404,637
80,960
+/-7,633
20.0%
+/-1.9%
72
Modesto, CA
518,152
114,628
+/-9,386
22.1%
+/-1.8%
34
Monroe, LA
168,802
42,735
+/-5,063
25.3%
+/-3.0%
12
Monroe, MI
147,322
18,984
+/-2,984
12.9%
+/-2.0%
307
Montgomery, AL
363,458
69,589
+/-6,497
19.1%
+/-1.8%
97
Morgantown, WV
126,795
24,361
+/-2,922
19.2%
+/-2.3%
96
Morristown, TN
112,273
19,831
+/-3,735
17.7%
+/-3.3%
133
Mount Vernon-Anacortes, WA
116,391
20,682
+/-3,644
17.8%
+/-3.1%
128
Muncie, IN
110,512
24,950
+/-2,907
22.6%
+/-2.6%
31
Muskegon, MI
163,873
33,809
+/-3,737
20.6%
+/-2.3%
59
Myrtle Beach-Conway-North Myrtle Beach, SC-NC
400,485
73,380
+/-6,568
18.3%
+/-1.6%
117
Napa, CA
136,394
12,286
+/-2,875
9.0%
+/-2.1%
369
CRS-54




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Naples-Immokalee-Marco Island, FL
336,570
43,152
+/-6,178
12.8%
+/-1.8%
311
Nashvil e-Davidson—Murfreesboro—Franklin, TN
1,718,322
235,823
+/-13,134
13.7%
+/-0.8%
290
New Bern, NC
124,576
19,936
+/-3,616
16.0%
+/-2.8%
209
New Haven-Milford, CT
836,150
107,710
+/-8,771
12.9%
+/-1.0%
308
New Orleans-Metairie, LA
1,221,794
235,888
+/-11,662
19.3%
+/-1.0%
91
New York-Newark-Jersey City, NY-NJ-PA
19,589,817
2,861,640
+/-41,911
14.6%
+/-0.2%
267
Niles-Benton Harbor, MI
150,975
24,561
+/-2,696
16.3%
+/-1.8%
193
North Port-Sarasota-Bradenton, FL
722,807
103,748
+/-8,231
14.4%
+/-1.1%
278
Norwich-New London, CT
261,938
23,568
+/-3,613
9.0%
+/-1.4%
370
Ocala, FL
329,035
64,222
+/-7,962
19.5%
+/-2.4%
83
Ocean City, NJ
94,252
8,835
+/-1,881
9.4%
+/-2.0%
365
Odessa, TX
147,095
21,501
+/-5,010
14.6%
+/-3.4%
265
Ogden-Clearfield, UT
615,823
64,161
+/-7,360
10.4%
+/-1.2%
356
Oklahoma City, OK
1,286,744
191,830
+/-11,090
14.9%
+/-0.9%
256
Olympia-Tumwater, WA
257,962
33,003
+/-5,603
12.8%
+/-2.2%
314
Omaha-Council Bluffs, NE-IA
878,790
111,619
+/-8,137
12.7%
+/-0.9%
317
Orlando-Kissimmee-Sanford, FL
2,221,209
380,933
+/-21,384
17.1%
+/-1.0%
151
Oshkosh-Neenah, WI
161,299
20,803
+/-2,586
12.9%
+/-1.6%
306
Owensboro, KY
114,097
18,450
+/-3,272
16.2%
+/-2.8%
198
Oxnard-Thousand Oaks-Ventura, CA
827,429
98,572
+/-8,115
11.9%
+/-1.0%
334
Palm Bay-Melbourne-Titusvil e, FL
545,062
81,662
+/-8,274
15.0%
+/-1.5%
252
Panama City, FL
186,734
33,000
+/-4,984
17.7%
+/-2.7%
132
Parkersburg-Vienna, WV
91,264
17,462
+/-2,480
19.1%
+/-2.7%
98
Pensacola-Ferry Pass-Brent, FL
439,944
70,881
+/-7,697
16.1%
+/-1.8%
203
Peoria, IL
372,862
47,768
+/-5,937
12.8%
+/-1.6%
312
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD
5,884,173
792,981
+/-24,235
13.5%
+/-0.4%
296
Phoenix-Mesa-Scottsdale, AZ
4,325,550
760,706
+/-27,227
17.6%
+/-0.6%
137
Pine Bluff, AR
85,065
20,736
+/-3,415
24.4%
+/-3.8%
16
Pittsburgh, PA
2,300,779
294,363
+/-10,892
12.8%
+/-0.5%
313
Pittsfield, MA
123,230
15,214
+/-2,321
12.3%
+/-1.9%
326
Pocatel o, ID
81,080
13,900
+/-2,892
17.1%
+/-3.5%
152
CRS-55




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Port St. Lucie, FL
432,472
74,415
+/-8,455
17.2%
+/-1.9%
150
Portland-South Portland, ME
508,937
57,943
+/-5,961
11.4%
+/-1.2%
340
Portland-Vancouver-Hillsboro, OR-WA
2,281,296
308,138
+/-15,086
13.5%
+/-0.7%
295
Prescott, AZ
211,524
34,138
+/-5,228
16.1%
+/-2.5%
201
Providence-Warwick, RI-MA
1,546,498
221,286
+/-10,882
14.3%
+/-0.7%
279
Provo-Orem, UT
548,963
75,447
+/-6,089
13.7%
+/-1.1%
289
Pueblo, CO
156,624
31,544
+/-4,177
20.1%
+/-2.6%
68
Punta Gorda, FL
160,389
22,628
+/-3,501
14.1%
+/-2.2%
283
Racine, WI
190,473
24,323
+/-3,718
12.8%
+/-1.9%
315
Raleigh, NC
1,185,900
142,633
+/-10,445
12.0%
+/-0.9%
331
Rapid City, SD
137,575
19,947
+/-2,955
14.5%
+/-2.2%
271
Reading, PA
399,792
57,698
+/-6,204
14.4%
+/-1.5%
275
Redding, CA
176,419
35,501
+/-4,281
20.1%
+/-2.4%
69
Reno, NV
432,828
64,933
+/-5,926
15.0%
+/-1.4%
250
Richmond, VA
1,207,277
167,791
+/-9,831
13.9%
+/-0.8%
286
Riverside-San Bernardino-Ontario, CA
4,298,913
781,792
+/-23,534
18.2%
+/-0.5%
120
Roanoke, VA
303,618
43,633
+/-5,158
14.4%
+/-1.7%
276
Rochester, MN
208,650
16,523
+/-2,572
7.9%
+/-1.2%
377
Rochester, NY
1,042,829
153,728
+/-9,277
14.7%
+/-0.9%
264
Rockford, IL
339,554
52,494
+/-5,842
15.5%
+/-1.7%
233
Rocky Mount, NC
147,408
27,825
+/-3,839
18.9%
+/-2.6%
100
Rome, GA
91,478
20,423
+/-4,011
22.3%
+/-4.3%
32
Sacramento—Roseville—Arden-Arcade, CA
2,182,441
363,182
+/-16,433
16.6%
+/-0.8%
178
Saginaw, MI
190,729
34,020
+/-4,382
17.8%
+/-2.3%
127
Salem, OR
387,689
75,096
+/-8,212
19.4%
+/-2.1%
89
Salinas, CA
409,021
73,031
+/-9,276
17.9%
+/-2.3%
126
Salisbury, MD-DE
371,597
57,065
+/-6,429
15.4%
+/-1.7%
239
Salt Lake City, UT
1,124,872
139,442
+/-12,915
12.4%
+/-1.1%
323
San Angelo, TX
110,830
13,518
+/-3,197
12.2%
+/-2.9%
327
San Antonio-New Braunfels, TX
2,235,950
363,769
+/-18,299
16.3%
+/-0.8%
192
San Diego-Carlsbad, CA
3,129,334
475,773
+/-21,393
15.2%
+/-0.7%
243
CRS-56




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
San Francisco-Oakland-Hayward, CA
4,451,868
510,653
+/-18,671
11.5%
+/-0.4%
337
San Jose-Sunnyvale-Santa Clara, CA
1,891,182
198,842
+/-12,625
10.5%
+/-0.7%
352
San Luis Obispo-Paso Robles-Arroyo Grande, CA
260,653
39,910
+/-4,790
15.3%
+/-1.8%
240
Santa Cruz-Watsonville, CA
258,572
38,616
+/-5,176
14.9%
+/-2.0%
255
Santa Fe, NM
144,957
28,106
+/-3,669
19.4%
+/-2.5%
88
Santa Maria-Santa Barbara, CA
417,118
68,116
+/-7,119
16.3%
+/-1.7%
190
Santa Rosa, CA
489,398
60,812
+/-6,883
12.4%
+/-1.4%
321
Savannah, GA
353,391
61,227
+/-5,819
17.3%
+/-1.6%
147
Scranton—Wilkes-Barre—Hazleton, PA
540,307
83,819
+/-6,826
15.5%
+/-1.3%
230
Seattle-Tacoma-Bel evue, WA
3,555,501
446,327
+/-18,551
12.6%
+/-0.5%
319
Sebastian-Vero Beach, FL
140,482
18,836
+/-3,818
13.4%
+/-2.7%
298
Sebring, FL
96,247
18,094
+/-3,330
18.8%
+/-3.4%
105
Sheboygan, WI
111,769
12,842
+/-2,655
11.5%
+/-2.4%
336
Sherman-Denison, TX
119,767
20,052
+/-3,282
16.7%
+/-2.7%
174
Shreveport-Bossier City, LA
437,810
89,134
+/-7,782
20.4%
+/-1.8%
64
Sierra Vista-Douglas, AZ
116,375
22,254
+/-3,418
19.1%
+/-2.9%
99
Sioux City, IA-NE-SD
164,903
24,384
+/-3,514
14.8%
+/-2.2%
261
Sioux Falls, SD
237,869
21,361
+/-3,670
9.0%
+/-1.5%
371
South Bend-Mishawaka, IN-MI
306,908
61,584
+/-5,763
20.1%
+/-1.9%
70
Spartanburg, SC
310,176
58,165
+/-6,323
18.8%
+/-2.1%
107
Spokane-Spokane Val ey, WA
518,992
87,011
+/-6,789
16.8%
+/-1.3%
173
Springfield, IL
207,477
32,420
+/-3,392
15.6%
+/-1.7%
225
Springfield, MA
590,986
99,343
+/-7,727
16.8%
+/-1.3%
171
Springfield, MO
435,561
81,533
+/-7,592
18.7%
+/-1.7%
108
Springfield, OH
132,887
24,653
+/-3,250
18.6%
+/-2.5%
114
St. Cloud, MN
183,531
24,877
+/-3,933
13.6%
+/-2.2%
293
St. George, UT
145,575
23,122
+/-4,312
15.9%
+/-3.0%
219
St. Joseph, MO-KS
119,933
18,614
+/-3,170
15.5%
+/-2.6%
229
St. Louis, MO-IL
2,740,729
352,550
+/-13,984
12.9%
+/-0.5%
309
State Col ege, PA
139,046
27,490
+/-3,453
19.8%
+/-2.5%
79
Staunton-Waynesboro, VA
111,589
12,717
+/-2,542
11.4%
+/-2.2%
338
CRS-57




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Stockton-Lodi, CA
690,366
137,663
+/-9,607
19.9%
+/-1.4%
73
Sumter, SC
105,762
21,047
+/-3,419
19.9%
+/-3.2%
74
Syracuse, NY
635,056
101,432
+/-7,069
16.0%
+/-1.1%
211
Tal ahassee, FL
353,498
76,104
+/-5,983
21.5%
+/-1.7%
46
Tampa-St. Petersburg-Clearwater, FL
2,822,199
435,739
+/-20,238
15.4%
+/-0.7%
235
Terre Haute, IN
155,430
34,599
+/-4,388
22.3%
+/-2.7%
33
Texarkana, TX-AR
143,188
30,643
+/-4,351
21.4%
+/-2.9%
49
The Villages, FL
98,007
10,283
+/-2,179
10.5%
+/-2.2%
354
Toledo, OH
590,850
114,978
+/-7,622
19.5%
+/-1.3%
84
Topeka, KS
229,113
35,331
+/-4,404
15.4%
+/-1.9%
236
Trenton, NJ
352,368
41,667
+/-6,207
11.8%
+/-1.8%
335
Tucson, AZ
970,384
188,765
+/-11,845
19.5%
+/-1.2%
85
Tulsa, OK
945,445
139,947
+/-6,432
14.8%
+/-0.7%
259
Tuscaloosa, AL
224,068
38,697
+/-4,511
17.3%
+/-2.0%
149
Tyler, TX
211,205
35,817
+/-6,103
17.0%
+/-2.9%
162
Urban Honolulu, HI
951,718
89,684
+/-7,816
9.4%
+/-0.8%
363
Utica-Rome, NY
283,034
49,420
+/-4,952
17.5%
+/-1.7%
141
Valdosta, GA
139,018
37,443
+/-4,673
26.9%
+/-3.3%
9
Val ejo-Fairfield, CA
414,410
53,992
+/-6,058
13.0%
+/-1.5%
303
Victoria, TX
94,588
14,419
+/-3,427
15.2%
+/-3.6%
241
Vineland-Bridgeton, NJ
145,220
29,978
+/-4,515
20.6%
+/-3.1%
58
Virginia Beach-Norfolk-Newport News, VA-NC
1,636,396
212,866
+/-11,713
13.0%
+/-0.7%
304
Visalia-Porterville, CA
448,360
135,066
+/-9,722
30.1%
+/-2.2%
4
Waco, TX
246,267
52,469
+/-6,245
21.3%
+/-2.5%
51
Walla Walla, WA
57,958
10,668
+/-3,003
18.4%
+/-4.9%
115
Warner Robins, GA
180,041
28,665
+/-5,206
15.9%
+/-3.0%
216
Washington-Arlington-Alexandria, DC-VA-MD-WV
5,846,655
495,683
+/-19,944
8.5%
+/-0.3%
373
Waterloo-Cedar Fal s, IA
161,729
24,304
+/-3,456
15.0%
+/-2.1%
248
Watertown-Fort Drum, NY
113,014
18,002
+/-3,646
15.9%
+/-3.2%
215
Wausau, WI
133,632
14,731
+/-2,808
11.0%
+/-2.1%
345
Weirton-Steubenville, WV-OH
120,609
19,551
+/-2,770
16.2%
+/-2.3%
196
CRS-58




Number Poor
Poverty Rate (Percent Poor)
Total
Poverty
Margin of
Metropolitan Area
Population
Estimate
Margin of Errora
Rate
Errora Rankb
Wenatchee, WA
112,492
16,636
+/-3,885
14.8%
+/-3.5%
260
Wheeling, WV-OH
138,642
21,491
+/-2,879
15.5%
+/-2.1%
231
Wichita Falls, TX
137,071
25,865
+/-3,446
18.9%
+/-2.4%
101
Wichita, KS
626,159
93,560
+/-7,251
14.9%
+/-1.2%
254
Williamsport, PA
110,934
14,991
+/-3,104
13.5%
+/-2.8%
294
Wilmington, NC
260,957
51,668
+/-6,726
19.8%
+/-2.5%
78
Winchester, VA-WV
124,642
8,432
+/-1,934
6.8%
+/-1.5%
380
Winston-Salem, NC
636,242
127,378
+/-10,165
20.0%
+/-1.6%
71
Worcester, MA-CT
895,779
119,575
+/-10,053
13.3%
+/-1.1%
301
Yakima, WA
243,340
50,581
+/-6,289
20.8%
+/-2.6%
55
York-Hanover, PA
428,323
47,161
+/-5,805
11.0%
+/-1.4%
347
Youngstown-Warren-Boardman, OH-PA
536,084
93,178
+/-6,320
17.4%
+/-1.2%
144
Yuba City, CA
166,398
31,142
+/-4,962
18.7%
+/-3.0%
109
Yuma, AZ
193,953
34,449
+/-4,738
17.8%
+/-2.4%
130
Source: Table prepared by the Congressional Research Service (CRS) based on U.S. Census Bureau 2013 American Community Survey (ACS) data,
table series S1701: Poverty Status in the Past 12 Months, from the Census Bureau’s American FactFinder, available on the Internet at http://factfinder2.census.gov/faces/nav/
jsf/pages/index.xhtml.
a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted from an estimate, the range reflects a 90% statistical
confidence interval bounding the estimate.
b. Ranks are based on areas’ poverty rate estimates for 2013. Because of sampling variability, an area’s rank generally does not statistically differ from other areas with
overlapping margins of error.
CRS-59

Poverty in the United States: 2013

Appendix C. Poverty Estimates by Congressional
District

Table C-1. Poverty by Congressional District: 2013


Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
Alabama






1st
680,039 134,336
+/-9,624 19.8% 1.4% 94
2nd
669,393 131,402
+/-8,126 19.6% 1.2% 97
3rd
677,175 134,678
+/-9,229 19.9% 1.3% 93
4th 676,562
118,192
+/-8,753
17.5%
1.3%
149
5th 684,710
108,037
+/-7,907
15.8%
1.1%
192
6th 684,445
78,856
+/-6,788
11.5%
1.0%
340
7th
643,781 177,870
+/-9,741 27.6% 1.5% 16







Alaska






(at Large)
718,359
67,016
+/-4,778
9.3%
0.7%
388







Arizona






1st
695,472 155,250
+/-8,082 22.3% 1.2% 58
2nd 693,316
118,822
+/-9,247
17.1%
1.3%
162
3rd
698,447 163,662
+/-11,048 23.4% 1.5% 46
4th 705,492
122,569
+/-12,447
17.4%
1.7%
156
5th 755,207
68,362
+/-7,732
9.1%
1.0%
391
6th 733,123
82,235
+/-8,134
11.2%
1.1%
348
7th 740,117
273,768
+/-16,029
37.0%
1.9%
3
8th 729,202
81,101
+/-10,398
11.1%
1.4%
354
9th 726,815
140,691
+/-12,946
19.4%
1.7%
103







Arkansas






1st
700,752 151,217
+/-9,195 21.6% 1.3% 64
2nd 735,135
115,908
+/-10,118
15.8%
1.4%
193
3rd 739,766
140,429
+/-10,887
19.0%
1.5%
113
4th
697,687 157,915
+/-8,674 22.6% 1.2% 53
Congressional Research Service
60

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
California






1st 686,482
127,948
+/-7,972
18.6%
1.1%
123
2nd 698,111
95,297
+/-7,216
13.7%
1.0%
267
3rd 692,439
113,156
+/-9,888
16.3%
1.4%
181
4th 691,590
76,856
+/-8,030
11.1%
1.2%
354
5th 704,754
91,858
+/-7,901
13.0%
1.1%
291
6th
720,620 173,402
+/-12,209 24.1% 1.6% 41
7th 710,789
98,887
+/-10,134
13.9%
1.4%
258
8th
693,599 151,099
+/-9,870 21.8% 1.4% 62
9th
713,742 141,208
+/-11,730 19.8% 1.6% 94
10th 710,043
135,348
+/-10,141
19.1%
1.4%
111
11th 725,609
86,409
+/-8,468
11.9%
1.1%
326
12th 724,204
100,585
+/-7,012
13.9%
1.0%
258
13th 715,115
127,993
+/-9,097
17.9%
1.3%
139
14th 713,923
59,242
+/-6,449
8.3%
0.9%
402
15th 724,469
63,947
+/-7,598
8.8%
1.0%
397
16th 695,284
228,299
+/-14,216
32.8%
1.8%
5
17th 723,712
54,067
+/-5,872
7.5%
0.8%
416
18th 718,830
52,354
+/-7,304
7.3%
1.0%
419
19th 736,944
106,113
+/-9,730
14.4%
1.3%
241
20th 693,918
121,640
+/-11,271
17.5%
1.6%
150
21st 666,828
198,925
+/-13,312
29.8%
1.9%
9
22nd
721,442 162,392
+/-13,227 22.5% 1.7% 57
23rd
705,535 139,601
+/-12,652 19.8% 1.7% 94
24th 687,555
108,598
+/-9,062
15.8%
1.3%
193
25th 703,152
98,322
+/-10,491
14.0%
1.4%
255
26th 701,251
91,980
+/-7,814
13.1%
1.1%
288
27th 705,546
97,711
+/-8,203
13.8%
1.2%
263
28th 702,945
116,658
+/-7,486
16.6%
1.0%
174
29th
686,505 154,924
+/-11,036 22.6% 1.4% 53
30th 736,172
101,938
+/-8,322
13.8%
1.1%
263
31st
704,960 149,510
+/-11,708 21.2% 1.6% 70
32nd 695,234
111,294
+/-10,142
16.0%
1.4%
190
33rd 699,130
71,356
+/-8,189
10.2%
1.1%
375
34th
694,761 204,453
+/-11,977 29.4% 1.5% 10
Congressional Research Service
61

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
35th 712,143
123,251
+/-10,376
17.3%
1.4%
158
36th
710,157 150,803
+/-12,089 21.2% 1.7% 70
37th
721,328 150,105
+/-9,344 20.8% 1.1% 78
38th 716,149
91,962
+/-8,974
12.8%
1.2%
299
39th 713,500
79,713
+/-8,186
11.2%
1.1%
348
40th
713,330 208,796
+/-13,307 29.3% 1.6% 12
41st
721,684 145,863
+/-11,526 20.2% 1.6% 85
42nd 737,375
88,252
+/-11,066
12.0%
1.5%
323
43rd
721,992 154,696
+/-12,164 21.4% 1.6% 67
44th
697,779 169,473
+/-13,325 24.3% 1.7% 39
45th 724,246
59,876
+/-6,525
8.3%
0.9%
402
46th
708,339 147,887
+/-11,656 20.9% 1.6% 75
47th 714,775
127,302
+/-9,765
17.8%
1.4%
145
48th 720,127
81,814
+/-8,059
11.4%
1.1%
343
49th 699,611
87,453
+/-8,497
12.5%
1.2%
306
50th 722,543
96,900
+/-10,044
13.4%
1.3%
282
51st
710,971 175,732
+/-13,156 24.7% 1.7% 37
52nd 690,588
72,736
+/-6,238
10.5%
0.9%
372
53rd 731,261
102,840
+/-12,694
14.1%
1.6%
252







Colorado






1st 759,232
128,553
+/-9,726
16.9%
1.3%
168
2nd 735,914
86,969
+/-6,347
11.8%
0.8%
330
3rd 704,491
114,613
+/-8,093
16.3%
1.1%
181
4th 730,209
81,105
+/-7,648
11.1%
1.1%
354
5th 719,869
80,961
+/-7,616
11.2%
1.1%
348
6th 758,469
88,906
+/-7,620
11.7%
1.0%
335
7th 743,277
86,339
+/-8,100
11.6%
1.1%
336







Connecticut






1st 701,540
87,123
+/-7,184
12.4%
1.0%
310
2nd 673,205
57,137
+/-5,536
8.5%
0.8%
400
3rd 692,492
82,119
+/-8,301
11.9%
1.2%
326
4th 722,098
72,043
+/-6,567
10.0%
0.9%
378
5th 696,018
75,478
+/-8,848
10.8%
1.3%
365
Congressional Research Service
62

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb







Delaware






(at Large)
900,322
111,327
+/-9,589
12.4%
1.1%
310







District of






Columbia
Delegate District
611,788 115,551
+/-7,400 18.9% 1.2% 116
(at Large)







Florida






1st 695,249
111,431
+/-9,748
16.0%
1.4%
190
2nd
664,146 138,714
+/-8,918 20.9% 1.3% 75
3rd 667,485
124,771
+/-8,585
18.7%
1.2%
120
4th 689,505
84,028
+/-7,680
12.2%
1.1%
315
5th
711,039 198,766
+/-12,906 28.0% 1.7% 15
6th 708,733
106,156
+/-8,431
15.0%
1.2%
224
7th 692,433
94,550
+/-9,495
13.7%
1.4%
267
8th 696,381
103,069
+/-9,922
14.8%
1.4%
229
9th
760,571 156,829
+/-15,275 20.6% 1.9% 82
10th 722,655
97,486
+/-10,462
13.5%
1.4%
277
11th 693,689
112,549
+/-10,734
16.2%
1.5%
185
12th 708,043
81,956
+/-6,680
11.6%
0.9%
336
13th 686,676
101,749
+/-10,216
14.8%
1.4%
229
14th
721,858 157,423
+/-12,447 21.8% 1.7% 62
15th 702,978
104,517
+/-10,034
14.9%
1.3%
227
16th 717,345
103,612
+/-8,227
14.4%
1.2%
241
17th 698,886
126,399
+/-10,568
18.1%
1.5%
133
18th 698,549
94,808
+/-9,038
13.6%
1.4%
270
19th 724,927
108,843
+/-8,829
15.0%
1.2%
224
20th
713,673 170,473
+/-12,666 23.9% 1.7% 44
21st 735,327
82,380
+/-7,434
11.2%
1.0%
348
22nd 725,143
110,474
+/-9,617
15.2%
1.3%
212
23rd 715,782
98,480
+/-9,106
13.8%
1.3%
263
24th
710,949 176,066
+/-11,881 24.8% 1.5% 34
25th 730,690
134,139
+/-12,580
18.4%
1.7%
125
26th 727,003
130,805
+/-11,568
18.0%
1.6%
135
Congressional Research Service
63

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
27th
710,235 142,860
+/-10,599 20.1% 1.5% 90







Georgia






1st 696,283
135,297
+/-8,201
19.4%
1.2%
103
2nd
651,114 177,017
+/-10,143 27.2% 1.5% 21
3rd 698,416
114,099
+/-10,317
16.3%
1.4%
181
4th 713,620
130,139
+/-10,983
18.2%
1.4%
131
5th
681,675 171,956
+/-10,676 25.2% 1.5% 32
6th 723,162
77,563
+/-8,599
10.7%
1.1%
369
7th 727,932
89,058
+/-11,176
12.2%
1.5%
315
8th
671,524 145,324
+/-9,494 21.6% 1.4% 64
9th
698,289 140,702
+/-9,000 20.1% 1.3% 90
10th 675,678
131,630
+/-9,051
19.5%
1.4%
100
11th 718,088
100,655
+/-9,127
14.0%
1.2%
255
12th
672,726 167,385
+/-9,407 24.9% 1.4% 33
13th 711,290
131,182
+/-12,045
18.4%
1.6%
125
14th 681,117
131,761
+/-11,132
19.3%
1.6%
105







Hawaii






1st 682,599
60,920
+/-5,936
8.9%
0.9%
395
2nd 685,063
87,448
+/-8,573
12.8%
1.2%
299







Idaho






1st 794,263
123,653
+/-11,335
15.6%
1.4%
197
2nd 788,648
122,897
+/-8,979
15.6%
1.1%
197







Illinois






1st
706,988 142,867
+/-10,464 20.2% 1.3% 85
2nd
688,548 156,163
+/-11,550 22.7% 1.5% 52
3rd 726,153
95,484
+/-10,108
13.1%
1.3%
288
4th
706,214 159,724
+/-13,235 22.6% 1.8% 53
5th 724,010
77,359
+/-7,300
10.7%
1.0%
369
6th 718,055
37,073
+/-4,607
5.2%
0.6%
434
7th
694,980 178,591
+/-11,471 25.7% 1.4% 30
8th 708,838
78,817
+/-9,914
11.1%
1.3%
354
Congressional Research Service
64

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
9th 690,182
88,569
+/-10,431
12.8%
1.4%
299
10th 697,471
68,938
+/-8,091
9.9%
1.2%
379
11th 702,136
72,337
+/-8,170
10.3%
1.2%
374
12th 680,740
124,967
+/-8,488
18.4%
1.2%
125
13th 671,586
126,612
+/-6,875
18.9%
1.0%
116
14th 723,626
46,575
+/-6,539
6.4%
0.9%
427
15th 678,016
102,470
+/-6,889
15.1%
1.0%
216
16th 675,968
88,029
+/-7,114
13.0%
1.0%
291
17th 687,108
125,847
+/-7,516
18.3%
1.1%
129
18th 696,061
74,971
+/-6,694
10.8%
0.9%
365







Indiana






1st 700,997
116,370
+/-8,928
16.6%
1.3%
174
2nd 696,539
127,392
+/-9,910
18.3%
1.4%
129
3rd 714,127
109,110
+/-7,422
15.3%
1.0%
208
4th 706,708
88,829
+/-6,945
12.6%
1.0%
302
5th 725,857
80,839
+/-6,625
11.1%
0.9%
354
6th 701,236
107,593
+/-6,591
15.3%
0.9%
208
7th
724,464 174,561
+/-9,964 24.1% 1.4% 41
8th 689,998
103,928
+/-7,111
15.1%
1.0%
216
9th 707,964
106,505
+/-6,825
15.0%
0.9%
224







Iowa






1st 740,372
87,534
+/-6,449
11.8%
0.9%
330
2nd 747,690
103,748
+/-6,748
13.9%
0.9%
258
3rd 771,820
89,857
+/-6,573
11.6%
0.9%
336
4th 731,788
97,988
+/-5,435
13.4%
0.7%
282







Kansas






1st 693,632
107,739
+/-7,630
15.5%
1.1%
203
2nd 686,122
105,331
+/-7,651
15.4%
1.1%
206
3rd 730,158
73,746
+/-6,487
10.1%
0.9%
377
4th 701,810
106,542
+/-7,729
15.2%
1.1%
212







Congressional Research Service
65

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
Kentucky






1st
697,666 141,016
+/-8,612 20.2% 1.2% 85
2nd 715,427
122,473
+/-7,098
17.1%
1.0%
162
3rd 724,794
116,814
+/-9,917
16.1%
1.4%
187
4th 718,449
101,001
+/-7,858
14.1%
1.1%
252
5th
690,896 184,181
+/-7,867 26.7% 1.1% 24
6th 719,324
135,150
+/-9,981
18.8%
1.4%
118







Louisiana






1st 766,678
103,791
+/-7,676
13.5%
1.0%
277
2nd
766,962 203,181
+/-11,910 26.5% 1.4% 26
3rd 753,214
125,639
+/-10,136
16.7%
1.3%
173
4th
739,473 157,598
+/-9,017 21.3% 1.2% 69
5th
706,617 175,044
+/-9,880 24.8% 1.4% 34
6th 762,045
122,766
+/-11,353
16.1%
1.4%
187







Maine






1st 655,033
78,463
+/-7,100
12.0%
1.1%
323
2nd 638,794
102,176
+/-6,263
16.0%
1.0%
190







Maryland






1st 706,758
75,818
+/-6,510
10.7%
0.9%
369
2nd 726,237
86,928
+/-7,834
12.0%
1.0%
323
3rd 722,483
57,302
+/-5,320
7.9%
0.7%
410
4th 733,322
66,977
+/-7,518
9.1%
1.0%
391
5th 729,944
55,364
+/-6,138
7.6%
0.9%
415
6th 724,866
70,066
+/-7,963
9.7%
1.1%
381
7th 699,540
123,371
+/-9,075
17.6%
1.2%
148
8th 745,009
49,745
+/-5,484
6.7%
0.7%
423







Massachusetts






1st 705,884
110,719
+/-8,093
15.7%
1.1%
196
2nd 700,887
97,862
+/-9,167
14.0%
1.3%
255
3rd 723,728
88,513
+/-7,272
12.2%
1.0%
315
4th 720,531
53,523
+/-6,566
7.4%
0.9%
417
Congressional Research Service
66

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
5th 726,369
59,426
+/-6,659
8.2%
0.9%
404
6th 733,179
64,388
+/-7,237
8.8%
1.0%
397
7th
700,909 147,321
+/-8,826 21.0% 1.2% 73
8th 742,643
68,341
+/-6,059
9.2%
0.8%
389
9th 702,400
80,420
+/-6,601
11.4%
0.9%
343







Michigan






1st 677,511
105,897
+/-6,121
15.6%
0.9%
197
2nd 697,928
108,808
+/-8,067
15.6%
1.1%
197
3rd 702,211
104,450
+/-8,143
14.9%
1.2%
227
4th 680,380
125,254
+/-7,395
18.4%
1.1%
125
5th
672,090 143,625
+/-9,525 21.4% 1.4% 67
6th 692,828
116,451
+/-7,098
16.8%
1.0%
171
7th 677,666
98,989
+/-7,538
14.6%
1.1%
237
8th 693,631
84,016
+/-7,169
12.1%
1.0%
319
9th 706,738
104,802
+/-8,448
14.8%
1.1%
229
10th 702,803
81,835
+/-7,088
11.6%
1.0%
336
11th 712,460
47,489
+/-5,567
6.7%
0.8%
423
12th 692,599
124,184
+/-8,814
17.9%
1.2%
139
13th 665,000
218,929
+/-10,358
32.9%
1.5%
4
14th
695,668 183,707
+/-10,674 26.4% 1.4% 27







Minnesota






1st 646,253
74,282
+/-5,790
11.5%
0.9%
341
2nd 669,895
56,383
+/-6,891
8.4%
1.0%
401
3rd 679,780
43,492
+/-6,880
6.4%
1.0%
427
4th 668,045
90,824
+/-6,299
13.6%
0.9%
270
5th 677,566
113,609
+/-9,034
16.8%
1.3%
171
6th 661,749
54,232
+/-5,275
8.2%
0.8%
404
7th 644,866
76,505
+/-4,410
11.9%
0.7%
326
8th 644,194
83,095
+/-4,924
12.9%
0.8%
296







Mississippi






1st
737,103 152,530
+/-10,500 20.7% 1.4% 80
2nd 696,410
226,515
+/-10,737
32.5%
1.5%
6
Congressional Research Service
67

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
3rd
722,227 160,723
+/-10,624 22.3% 1.5% 58
4th
738,028 156,147
+/-11,579 21.2% 1.6% 70







Missouri






1st
716,639 154,322
+/-10,183 21.5% 1.4% 66
2nd 756,366
44,541
+/-6,446
5.9%
0.8%
430
3rd 740,733
83,265
+/-7,766
11.2%
1.0%
348
4th
718,835 141,025
+/-7,822 19.6% 1.1% 98
5th 746,309
134,121
+/-8,703
18.0%
1.1%
135
6th 723,996
96,173
+/-7,357
13.3%
1.0%
286
7th 737,825
131,801
+/-7,212
17.9%
1.0%
139
8th
720,306 145,818
+/-9,106 20.2% 1.3% 85







Montana






(at Large)
990,603
163,637
+/-9,336
16.5%
0.9%
176







Nebraska






1st 608,570
78,276
+/-7,294
12.9%
1.2%
296
2nd 622,083
84,591
+/-6,643
13.6%
1.1%
270
3rd 584,912
76,566
+/-6,430
13.1%
1.1%
288







Nevada






1st
664,608 150,284
+/-10,320 22.6% 1.6% 53
2nd 678,429
96,988
+/-7,124
14.3%
1.0%
246
3rd 716,933
69,515
+/-7,275
9.7%
1.1%
381
4th
690,506 116,789
+/-11,216 16.9% 1.5% 168







New Hampshire






1st 642,184
50,458
+/-5,547
7.9%
0.9%
410
2nd 638,997
61,037
+/-6,572
9.6%
1.0%
384







New Jersey






1st 719,415
97,145
+/-8,049
13.5%
1.1%
277
2nd 711,019
111,174
+/-8,251
15.6%
1.1%
197
3rd 726,173
39,334
+/-4,382
5.4%
0.6%
433
Congressional Research Service
68

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
4th 726,617
69,746
+/-7,488
9.6%
1.1%
384
5th 719,355
50,882
+/-6,204
7.1%
0.9%
421
6th 712,290
84,373
+/-8,494
11.8%
1.2%
330
7th 735,736
35,040
+/-5,067
4.8%
0.7%
435
8th 751,289
144,504
+/-10,611
19.2%
1.4%
108
9th 755,519
113,758
+/-8,908
15.1%
1.2%
216
10th
714,062 148,640
+/-9,667 20.8% 1.3% 78
11th 721,415
33,693
+/-5,311
4.7%
0.7%
436
12th 728,120
70,260
+/-7,796
9.6%
1.1%
384







New Mexico






1st 685,428
133,437
+/-9,937
19.5%
1.4%
100
2nd
676,488 154,795
+/-8,582 22.9% 1.2% 51
3rd
683,486 160,229
+/-9,712 23.4% 1.4% 46







New York






1st 701,326
49,336
+/-5,985
7.0%
0.9%
422
2nd 712,372
46,878
+/-6,011
6.6%
0.8%
425
3rd 712,917
38,868
+/-5,395
5.5%
0.8%
432
4th 702,715
50,575
+/-6,569
7.2%
0.9%
420
5th 756,885
110,838
+/-9,391
14.6%
1.2%
237
6th 713,917
96,359
+/-9,486
13.5%
1.3%
277
7th
751,238 200,749
+/-13,007 26.7% 1.6% 24
8th
729,789 180,209
+/-12,403 24.7% 1.5% 37
9th
731,047 146,945
+/-9,562 20.1% 1.2% 90
10th 698,689
118,623
+/-11,829
17.0%
1.5%
166
11th 721,525
99,117
+/-8,696
13.7%
1.2%
267
12th 700,886
87,458
+/-7,326
12.5%
1.1%
306
13th 753,771
231,790
+/-14,629
30.8%
1.8%
7
14th 708,751
132,359
+/-10,918
18.7%
1.4%
120
15th 734,051
292,239
+/-13,036
39.8%
1.5%
2
16th 716,038
92,855
+/-8,224
13.0%
1.1%
291
17th 722,094
81,843
+/-8,290
11.3%
1.2%
346
18th 694,344
72,932
+/-6,695
10.5%
1.0%
372
19th 678,168
84,606
+/-7,505
12.5%
1.1%
306
Congressional Research Service
69

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
20th 695,685
94,550
+/-7,852
13.6%
1.1%
270
21st 674,976
102,053
+/-7,404
15.1%
1.1%
216
22nd 678,127
111,998
+/-7,800
16.5%
1.1%
176
23rd 671,906
114,125
+/-7,004
17.0%
1.0%
166
24th 688,710
103,904
+/-6,705
15.1%
1.0%
216
25th 698,713
112,337
+/-7,799
16.1%
1.1%
187
26th 696,725
134,322
+/-7,785
19.3%
1.1%
105
27th 688,608
67,777
+/-5,673
9.8%
0.8%
380







North Carolina






1st
691,089 185,667
+/-10,290 26.9% 1.4% 23
2nd 760,912
122,942
+/-9,604
16.2%
1.2%
185
3rd 715,163
123,544
+/-8,781
17.3%
1.2%
158
4th 733,092
133,671
+/-10,387
18.2%
1.3%
131
5th 726,793
137,941
+/-8,718
19.0%
1.1%
113
6th 742,799
111,853
+/-9,124
15.1%
1.2%
216
7th 750,313
144,958
+/-7,926
19.3%
1.0%
105
8th
726,125 148,570
+/-9,452 20.5% 1.3% 84
9th 774,136
61,437
+/-6,755
7.9%
0.9%
410
10th 725,747
128,534
+/-8,986
17.7%
1.2%
147
11th 720,043
136,702
+/-9,351
19.0%
1.3%
113
12th
746,929 204,194
+/-11,575 27.3% 1.4% 19
13th 775,136
75,384
+/-9,217
9.7%
1.2%
381







North Dakota






(at Large)
698,199
82,398
+/-5,117
11.8%
0.7%
330







Ohio






1st 702,707
125,501
+/-8,795
17.9%
1.3%
139
2nd 714,389
110,534
+/-8,590
15.5%
1.2%
203
3rd
717,654 167,292
+/-10,487 23.3% 1.4% 48
4th 679,889
91,334
+/-7,236
13.4%
1.1%
282
5th 710,347
89,156
+/-7,234
12.6%
1.0%
302
6th 689,436
123,434
+/-7,424
17.9%
1.0%
139
7th 703,754
91,533
+/-7,137
13.0%
1.0%
291
Congressional Research Service
70

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
8th 703,535
97,089
+/-8,397
13.8%
1.2%
263
9th
700,743 155,919
+/-9,614 22.3% 1.3% 58
10th 698,963
122,937
+/-8,690
17.6%
1.2%
148
11th
672,657 185,770
+/-8,488 27.6% 1.2% 16
12th 724,734
80,548
+/-8,542
11.1%
1.1%
354
13th
697,304 137,989
+/-8,203 19.8% 1.1% 94
14th 714,373
64,344
+/-6,724
9.0%
0.9%
394
15th 709,268
95,574
+/-9,204
13.5%
1.2%
277
16th 709,000
57,988
+/-7,104
8.2%
1.0%
404







Oklahoma






1st 761,062
116,136
+/-6,147
15.3%
0.8%
208
2nd
722,939 148,957
+/-6,518 20.6% 0.9% 82
3rd 737,954
105,777
+/-6,092
14.3%
0.8%
246
4th 747,633
113,007
+/-6,680
15.1%
0.9%
216
5th 765,619
143,029
+/-8,923
18.7%
1.1%
120







Oregon






1st 784,374
88,715
+/-8,193
11.3%
1.0%
346
2nd 761,782
137,247
+/-10,784
18.0%
1.4%
135
3rd 781,957
140,701
+/-9,197
18.0%
1.2%
135
4th
755,543 157,618
+/-9,833 20.9% 1.3% 75
5th 769,215
117,857
+/-9,483
15.3%
1.2%
208







Pennsylvania






1st
708,585 179,930
+/-12,234 25.4% 1.6% 31
2nd
679,969 187,309
+/-12,997 27.5% 1.7% 18
3rd 675,518
96,849
+/-6,914
14.3%
1.0%
246
4th 686,631
75,245
+/-7,028
11.0%
1.0%
362
5th 653,380
106,830
+/-6,726
16.4%
1.0%
180
6th 702,677
54,490
+/-5,690
7.8%
0.8%
413
7th 698,765
38,806
+/-5,427
5.6%
0.8%
431
8th 699,630
42,426
+/-5,300
6.1%
0.8%
429
9th 677,732
105,526
+/-6,659
15.6%
1.0%
197
10th 677,709
78,320
+/-6,295
11.6%
0.9%
336
Congressional Research Service
71

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
11th 678,516
87,815
+/-7,528
12.9%
1.1%
296
12th 689,855
66,446
+/-5,751
9.6%
0.8%
384
13th 699,764
94,833
+/-9,401
13.6%
1.3%
270
14th 677,236
129,813
+/-6,629
19.2%
1.0%
108
15th 690,532
83,356
+/-7,214
12.1%
1.0%
319
16th 691,003
99,925
+/-7,985
14.5%
1.1%
239
17th 673,191
99,143
+/-7,599
14.7%
1.1%
235
18th 692,563
63,343
+/-6,733
9.1%
1.0%
391







Puerto Rico






Resident
Commissioner
3,581,841 1,626,879
+/-25,081
45.4%
0.7%
1
District (at Large)







Rhode Island






1st 507,705
83,640
+/-7,475
16.5%
1.4%
176
2nd 503,122
60,806
+/-6,404
12.1%
1.2%
319







South Carolina






1st 702,942
93,237
+/-8,472
13.3%
1.2%
286
2nd 652,110
88,521
+/-7,452
13.6%
1.1%
270
3rd 640,182
122,644
+/-8,617
19.2%
1.4%
108
4th 672,211
117,654
+/-11,317
17.5%
1.7%
150
5th 665,846
116,437
+/-8,915
17.5%
1.3%
150
6th
635,209 173,720
+/-12,202 27.3% 1.8% 19
7th
663,301 148,167
+/-9,307 22.3% 1.4% 58







South Dakota






(at Large)
815,049
115,454
+/-6,396
14.2%
0.8%
249







Tennessee






1st 691,578
134,589
+/-8,688
19.5%
1.3%
100
2nd 704,547
115,039
+/-8,035
16.3%
1.1%
181
3rd 704,206
130,627
+/-8,498
18.5%
1.2%
124
4th 708,757
109,876
+/-9,823
15.5%
1.4%
203
5th 717,954
125,063
+/-10,508
17.4%
1.5%
156
Congressional Research Service
72

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
6th 711,308
117,565
+/-8,039
16.5%
1.1%
176
7th 710,702
105,314
+/-7,598
14.8%
1.1%
229
8th 690,620
99,693
+/-7,837
14.4%
1.1%
241
9th
695,623 189,006
+/-10,197 27.2% 1.4% 21







Texas






1st 687,535
131,109
+/-9,739
19.1%
1.4%
111
2nd 713,206
77,574
+/-9,226
10.9%
1.3%
363
3rd 761,975
61,299
+/-7,654
8.0%
1.0%
407
4th 692,508
116,697
+/-7,652
16.9%
1.1%
168
5th 702,251
121,143
+/-9,754
17.3%
1.4%
158
6th 723,550
98,531
+/-9,801
13.6%
1.3%
270
7th 739,161
95,951
+/-12,599
13.0%
1.6%
291
8th 723,034
106,875
+/-12,178
14.8%
1.7%
229
9th
732,651 170,582
+/-15,618 23.3% 1.9% 48
10th 743,786
93,471
+/-9,733
12.6%
1.3%
302
11th 707,102
100,293
+/-8,202
14.2%
1.1%
249
12th 715,352
90,096
+/-9,395
12.6%
1.2%
302
13th 666,624
113,891
+/-7,896
17.1%
1.2%
162
14th 685,799
120,238
+/-10,196
17.5%
1.5%
150
15th
712,583 206,766
+/-14,700 29.0% 1.9% 13
16th
713,506 149,716
+/-11,335 21.0% 1.6% 73
17th
697,313 144,209
+/-9,217 20.7% 1.3% 80
18th
719,940 174,321
+/-12,611 24.2% 1.6% 40
19th 676,937
118,302
+/-7,916
17.5%
1.2%
150
20th
738,710 149,099
+/-11,527 20.2% 1.5% 85
21st 725,911
89,810
+/-8,990
12.4%
1.2%
310
22nd 776,804
62,068
+/-8,980
8.0%
1.1%
407
23rd 704,310
132,124
+/-12,368
18.8%
1.6%
118
24th 737,662
81,517
+/-7,194
11.1%
1.0%
354
25th 698,238
84,487
+/-7,903
12.1%
1.1%
319
26th 754,463
60,365
+/-7,755
8.0%
1.0%
407
27th 700,545
121,425
+/-7,765
17.3%
1.1%
158
28th
716,462 185,834
+/-13,454 25.9% 1.8% 29
29th
725,214 205,537
+/-15,022 28.3% 1.9% 14
Congressional Research Service
73

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
30th
730,093 181,102
+/-12,840 24.8% 1.7% 34
31st 755,146
81,363
+/-8,607
10.8%
1.1%
365
32nd 712,450
102,395
+/-10,552
14.4%
1.4%
241
33rd
718,202 211,105
+/-14,105 29.4% 1.7% 10
34th 699,377
214,124
+/-14,414
30.6%
1.9%
8
35th
734,454 176,578
+/-13,103 24.0% 1.6% 43
36th 691,375
100,042
+/-9,328
14.5%
1.3%
239







Utah






1st 710,878
79,725
+/-6,787
11.2%
0.9%
348
2nd 701,563
99,573
+/-8,257
14.2%
1.1%
249
3rd 703,653
94,122
+/-6,866
13.4%
1.0%
282
4th 735,493
87,761
+/-9,686
11.9%
1.3%
326







Vermont






(at Large)
602,538
74,058
+/-5,273
12.3%
0.9%
313







Virginia






1st 744,218
66,370
+/-8,115
8.9%
1.1%
395
2nd 702,902
75,806
+/-7,226
10.8%
1.0%
365
3rd
713,004 169,763
+/-8,239 23.8% 1.2% 45
4th 706,932
88,229
+/-8,412
12.5%
1.2%
306
5th 705,461
106,670
+/-7,457
15.1%
1.0%
216
6th 698,956
106,450
+/-8,106
15.2%
1.2%
212
7th 746,510
55,579
+/-5,781
7.4%
0.8%
417
8th 768,254
59,318
+/-7,803
7.7%
1.0%
414
9th 691,431
125,424
+/-7,101
18.1%
1.0%
133
10th 775,923
35,554
+/-5,723
4.6%
0.7%
437
11th 756,953
49,570
+/-6,419
6.5%
0.8%
426







Washington






1st 701,188
64,725
+/-7,748
9.2%
1.1%
389
2nd 679,236
98,032
+/-9,375
14.4%
1.4%
241
3rd 684,902
95,133
+/-7,202
13.9%
1.0%
258
4th 688,694
123,122
+/-10,455
17.9%
1.5%
139
Congressional Research Service
74

Poverty in the United States: 2013



Number Poor
Poverty Rate (Percent Poor)
Congressional
Total
Margin of
Margin of
District
Population
Estimate
Errora
Estimate
Errora
Rankb
5th 652,983
116,228
+/-7,411
17.8%
1.1%
145
6th 661,196
97,169
+/-8,145
14.7%
1.2%
235
7th 689,597
84,405
+/-6,843
12.2%
1.0%
315
8th 694,338
79,365
+/-8,803
11.4%
1.2%
343
9th 697,715
107,630
+/-9,397
15.4%
1.3%
206
10th 686,413
101,473
+/-9,503
14.8%
1.3%
229







West Virginia






1st 593,790
101,747
+/-6,634
17.1%
1.1%
162
2nd 613,973
93,591
+/-6,940
15.2%
1.1%
212
3rd
590,503 137,009
+/-8,296 23.2% 1.4% 50







Wisconsin






1st 693,828
81,867
+/-7,526
11.8%
1.1%
330
2nd 716,614
100,772
+/-7,885
14.1%
1.1%
252
3rd 680,168
94,351
+/-5,668
13.9%
0.8%
258
4th
697,611 182,145
+/-7,715 26.1% 1.1% 28
5th 709,150
62,002
+/-5,486
8.7%
0.8%
399
6th 689,717
70,099
+/-4,808
10.2%
0.7%
375
7th 701,635
86,042
+/-5,816
12.3%
0.8%
313
8th 704,474
78,273
+/-5,835
11.1%
0.8%
354







Wyoming






(at Large)
569,307
62,039
+/-5,844
10.9%
1.0%
363
Source: Table prepared by the Congressional Research Service (CRS) based on analysis of U.S. Census Bureau
2013 American Community Survey (ACS) data, table series S1701: Poverty Status in the Past 12 Months, from
the Census Bureau’s American FactFinder, available on the Internet at http://factfinder2.census.gov/faces/nav/jsf/
pages/index.xhtml.
a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted
from an estimate, the range reflects a 90% statistical confidence interval bounding the estimate.
b. Ranks are based on the Congressional Districts’ poverty rate estimates for 2013. Because of sampling
variability, a District’s rank does not generally statistically differ from other Districts with overlapping
margins of error.
Congressional Research Service
75

Poverty in the United States: 2013



Author Contact Information

Thomas Gabe

Specialist in Social Policy
tgabe@crs.loc.gov, 7-7357


Congressional Research Service
76