Poverty in the United States: 2013

Congressional research reportJan 29, 2015

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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 pretax 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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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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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: ThreeYear Average 2010-2013............................................................................................................. 39

Figure 15. Poverty Rates by State Using the “Official”* Measure and the SPM: ThreeYear 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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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 postWorld 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 prerecession 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

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.

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.

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.

CRS Report RL33615, Parents’ Work and Family Economic Well-Being, by (name redacted) and (name redacted).

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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

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 (name redacted).

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.

See http://www.census.gov/hhes/www/poverty/data/threshld/index.html.

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”).

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.

CRS-5

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 nonHispanics, 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

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 34year-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

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.

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 substate 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 collected between

January and December 2013, for the prior 12 months. For example, for the sample with data collected in January, the

reference period is from January 2012 to December 2013, and for the sample with data collected 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

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

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.

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

. Two estimates

error for the difference between two estimates may be calculated as: SE StateA − SE StateB = SE StateA

+ SE 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., PovrateStateA − PovrateStateB > 1.645 x( SE StateA − SE 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

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

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 upwardpointing 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

Statistically significant differences are based on a 90% statistical confidence interval.

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

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

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

Differencesa

Estimated Poverty Rates and Statistically Significant Differences over Previous Year

2005

2013

vs.

2007

2002

2003

2004

2005

2006b

2007b

2008b

2009b

2010b

2011b

2012b

2013b

2001

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

18.7

0.4

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

Arizona

14.2

15.4 ▲

14.2

14.7

16.5 ▲

17.4 ▲

19.0 ▲

18.7

18.6

0.0

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

California

13.0

13.4

13.3

13.1

12.4 ▼

13.3 ▲

14.2 ▲

15.8 ▲

16.6 ▲

17.0 ▲

16.8

0.3

Colorado

9.7

9.8

11.1

12.0 ▲

12.0

11.4

12.9 ▲

13.4

13.5

13.7

13.0

Connecticut

7.5

8.1

7.6

8.3

7.9

9.3 ▲

9.4

10.1 ▲

10.9 ▲

10.7

0.9

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

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

▼

1.4

1.9 ▲

▲

0.4 ▲

4.5 ▲

▲

1.8 ▲

4.4 ▲

▲

1.0 ▲

2.8 ▲

▲

1.9 ▲

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

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

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

11.5

11.8

12.6 ▲

12.8

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

(0.4)

2.8 ▲

CRS-16

Change in Poverty

Rates over

Selected Periods

and Statistically

Significant

Differencesa

Estimated Poverty Rates and Statistically Significant Differences over Previous Year

2005

2013

vs.

2007

2002

2003

2004

2005

2006b

2007b

2008b

2009b

2010b

2011b

2012b

2013b

2001

Kentucky

15.6

17.4

16.8

17.0

17.3

18.6 ▲

19.0

19.1

19.4

18.8

1.2

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

Maine

11.1

10.5

12.3 ▲

12.6

12.9

12.0

12.3

12.9

14.1 ▲

14.7

14.0

1.5

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

Massachusetts

8.9

9.4

9.2

10.3 ▲

9.9

10.0

10.3

11.4 ▲

11.6

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

21.6 ▲

21.3

21.1

20.6

21.2

21.9

22.4

22.6

24.2 ▲

24.0

1.5

▲

3.4 ▲

▲

2.9 ▲

▲

1.4 ▲

1.1 ▲

▲

1.9 ▲

1.8 ▲

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

Montana

14.6

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 ▲

▲

1.2

▲

2.9 ▲

▲

(0.4)

New Jersey

7.5

8.4 ▲

8.5

8.7

8.6

8.7

9.4 ▲

10.3 ▲

10.4

10.8

11.4

New Mexico

18.9

18.6

19.3

18.5

18.1

17.1

18.0

20.4 ▲

21.5

20.8

21.9

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

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

▲

Oklahoma

15.0

16.1

15.3

16.5

17.0

15.9 ▼

15.9

16.2

16.9 ▲

17.2

16.8

1.5

Oregon

13.2

13.9

14.1

13.3 ▼

12.9

13.6 ▲

14.3

15.8 ▲

17.5 ▲

17.2

16.7

0.9

CRS-17

3.8 ▲

▲

2.3 ▲

2.8 ▲

0.9 ▲

3.7 ▲

Change in Poverty

Rates over

Selected Periods

and Statistically

Significant

Differencesa

Estimated Poverty Rates and Statistically Significant Differences over Previous Year

2005

2013

vs.

2007

2002

2003

2004

2005

2006b

2007b

2008b

2009b

2010b

2011b

2012b

2013b

2001

Pennsylvania

10.5

10.9

11.7 ▲

11.9

12.1

11.6 ▼

12.1 ▲

12.5 ▲

13.4 ▲

13.8

13.7

1.4

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

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

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

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)

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

▼

▲

2.1 ▲

2.3 ▲

▲

3.5 ▲

1.1

3.0 ▲

▲

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

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 statistically

significant change in

poverty:

Increase in poverty

5▲

8▲

13 ▲

4 ▲

1 ▲

8▲

32 ▲

34 ▲

17 ▲

3 ▲

22 ▲

48 ▲

Decrease in poverty

0▼

2▼

1 ▼

3 ▼

13 ▼

3▼

0 ▼

1 ▼

2 ▼

4 ▼

0 ▼

Source: Congressional Research Service (CRS) estimates from U.S. Census Bureau American Community Survey (ACS) data, 2002 to 2013.

Notes: ▲ Statistically 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.

Depicted changes in poverty rates over selected periods may differ slightly from differences calculated directly from the table, due to rounding.

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)

Number Poor

Metropolitan Area

Washington-Arlington-Alexandria, DC-VAMD-WV

Total

Population

Estimate

Margin of

Errora

Poverty Rate

(Percent Poor)

Estimate

Margin of

Errora

5,846,655

495,683

+/-19,944

8.5%

+/-0.3%

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%

1,891,182

198,842

+/-12,625

10.5%

+/-0.7%

660,782

71,297

+/-7,162

10.8%

+/-1.1%

1,169,485

125,923

+/-9,009

10.8%

+/-0.8%

San Jose-Sunnyvale-Santa Clara, CA

Colorado Springs, CO

Hartford-West Hartford-East Hartford, CT

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 statistically

different from one another, or from others not shown in the table.

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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Poverty in the United States: 2013

Table 3. Large Metropolitan Areas Among Those with the

Highest Poverty Rates: 2013

(Metropolitan Areas with Population of 500,000 and Over)

Number Poor

Metropolitan Area

Total

Population

McAllen-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%

Estimate

Margin of

Errora

Poverty Rate

(Percent Poor)

Estimate

Margin of

Errora

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 statistically

different from one another, or from others not shown in the table.

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)

Number Poor

Metropolitan Area

Total

Population

Estimate

Margin of

Errora

Poverty Rate

(Percent Poor)

Estimate

Margin of

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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Poverty in the United States: 2013

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 statistically

different from one another, or from others not shown in the table.

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)

Number Poor

Metropolitan Area

Total

Population

Estimate

Margin of

Errora

Poverty Rate

(Percent Poor)

Estimate

Margin of

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%

College 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 statistically

different from one another, or from others not shown in the table.

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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Poverty in the United States: 2013

“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.

Congressional Research Service

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

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.

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 (name redacted).

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…)

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.

The ITWG’s guidance is available at http://www.census.gov/hhes/www/poverty/SPM_TWGObservations.pdf.

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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Poverty in the United States: 2013

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 workrelated 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

Measurement units

Congressional Research Service

Families and unrelated individuals

Supplemental Poverty Measure

All related individuals who live at the

same address, including any coresident unrelated children who are

cared for by the family (such as foster

children) and any cohabitors and their

children

Poverty in the United States: 2013

Poverty threshold

“Official” Poverty Measure

Supplemental Poverty Measure

Three times the cost of a minimum

food diet in 1963

A range around the 33rd percentile

(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, nontransportation-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

age of householder

A three parameter equivalence scale

for number of adults and children in

the family

Geographic adjustments for

differences in housing costs

Updating thresholds

Congressional Research Service

Consumer Price Index for Urban

Consumers (CPI-U) based on all items

Five-year moving average of

expenditures on FCSU from the BLS

Poverty in the United States: 2013

“Official” Poverty Measure

Resource measures

Gross before-tax cash income

Supplemental Poverty Measure

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

payroll 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 in the United States: 2013

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

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.

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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Poverty in the United States: 2013

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 workrelated 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.

“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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Poverty in the United States: 2013

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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Poverty in the United States: 2013

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 coresident 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.

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.

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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Poverty in the United States: 2013

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

Significant differences based on a 90% statistical confidence level.

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Poverty in the United States: 2013

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

Significant difference at a 90% statistical confidence level.

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Poverty in the United States: 2013

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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Poverty in the United States: 2013

Figure 15. Poverty Rates by State Using the “Official”* Measure and the SPM: ThreeYear 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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Poverty in the United States: 2013

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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Poverty in the United States: 2013

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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Poverty in the United States: 2013

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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Poverty in the United States: 2013

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 workrelated 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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Poverty in the United States: 2013

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

Year

All

Persons

Total

FemaleHeaded

Families

2013

14.5

19.5

45.8

10.7

13.6

2012

15.0

21.3

47.2

12.5

2011

15.0

21.4

47.6

2010r

15.1

21.5

2009

14.3

2008

Race/Ethnicityb—All Ages

Whiteb

White

NonHispanicb

Blackb

Hispanic

(any

race)

Asianb

9.5

12.3b

9.6b

27.2b

23.5b

10.5b

13.7

9.1

12.7b

9.7b

27.2b

25.6

11.7b

12.1

13.7

8.7

12.8b

9.8b

27.6b

25.3

12.3b

46.6

12.9

13.8

8.9

13.0b

9.9b

27.4b

26.5

12.2b

20.1

44.4

12.3

12.9

8.9

12.3b

9.4b

25.8b

25.3

12.5b

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

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

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

9.4

30.6

30.7

n/a

1993

15.1

22.0

53.7

12.4

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

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

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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In All

Other

Families

Ages

1864

Age

65+

Poverty in the United States: 2013

Related Children

Under Age18a

Adults

Year

All

Persons

Total

FemaleHeaded

Families

1983

15.2

21.8

55.5

13.5

12.4

1982

15.0

21.3

56.0

13.0

1981

14.0

19.5

52.3

1980

13.0

17.9

1979

11.7

1978

In All

Other

Families

Ages

1864

Age

65+

Race/Ethnicityb—All Ages

Whiteb

White

NonHispanicb

Blackb

Hispanic

(any

race)

Asianb

13.8

12.2

10.8

35.7

28.1

n/a

12.0

14.6

12.0

10.6

35.6

29.9

n/a

11.6

11.1

15.3

11.1

9.9

34.2

26.5

n/a

50.8

10.4

10.1

15.7

10.2

9.1

32.5

25.7

n/a

16.0

48.6

8.5

8.9

15.2

9.0

8.1

31.0

21.8

n/a

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

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

1971

12.5

15.1

53.1

9.3

21.6

9.9

n/a

32.5

n/a

1970

12.6

14.9

53.0

9.2

9.0

24.6

9.9

n/a

33.5

n/a

1969

12.1

13.8

54.4

8.6

8.7

25.3

9.5

n/a

32.2

n/a

1968

12.8

15.3

55.2

10.2

9.0

25.0

10.0

n/a

34.7

n/a

1967

14.2

16.3

54.3

11.5

10.0

29.5

11.0

n/a

39.3

n/a

1966

14.7

17.4

58.2

12.6

10.5

28.5

11.3

n/a

41.8

n/a

1959

22.4

26.9

72.2

22.4

17.0

35.2

18.1

n/a

55.1

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.

Beginning in 1979, restricted to children in primary families only. Before 1979, includes children in unrelated

subfamilies.

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

Appendix B. Metropolitan Area Poverty Estimates

Table B-1. Metropolitan Area Poverty: 2013

Number Poor

Poverty Rate (Percent Poor)

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

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%

Albany, OR

117,252

23,986

+/-4,096

20.5%

+/-3.5%

320

Metropolitan Area

Albany-Schenectady-Troy, NY

846,922

105,640

+/-8,545

12.5%

+/-1.0%

Albuquerque, NM

890,054

173,028

+/-10,925

19.4%

+/-1.2%

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

Amarillo, TX

249,194

39,748

+/-3,969

16.0%

+/-1.6%

212

Ames, IA

84,045

19,770

+/-2,273

23.5%

+/-2.6%

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%

Appleton, WI

226,221

18,291

+/-2,940

8.1%

+/-1.3%

376

214

Asheville, NC

429,282

68,399

+/-5,793

15.9%

+/-1.4%

Athens-Clarke County, GA

186,981

53,388

+/-5,015

28.6%

+/-2.6%

Atlanta-Sandy Springs-Roswell, 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%

Augusta-Richmond County, GA-SC

Austin-Round Rock, TX

Bakersfield, CA

565,819

111,863

+/-8,976

19.8%

+/-1.6%

1,841,572

262,644

+/-14,918

14.3%

+/-0.8%

281

831,344

189,484

+/-13,393

22.8%

+/-1.6%

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

Baltimore-Columbia-Towson, MD

CRS-47

Poverty Rate (Percent Poor)

Number Poor

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

Errora

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%

Metropolitan Area

Rankb

Bellingham, 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

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%

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%

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

Birmingham-Hoover, AL

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%

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%

Brunswick, GA

111,440

22,111

+/-4,204

19.8%

+/-3.8%

257

Buffalo-Cheektowaga-Niagara Falls, NY

1,103,165

164,100

+/-8,568

14.9%

+/-0.8%

Burlington, NC

150,206

31,103

+/-4,266

20.7%

+/-2.8%

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-Massillon, 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%

CRS-48

Poverty Rate (Percent Poor)

Number Poor

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

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%

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

2,298,466

339,434

+/-15,265

14.8%

+/-0.7%

263

Metropolitan Area

Charlotte-Concord-Gastonia, NC-SC

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

Chicago-Naperville-Elgin, IL-IN-WI

Chico, CA

93,972

8,952

+/-2,894

9.5%

+/-3.1%

361

9,375,444

1,347,179

+/-32,543

14.4%

+/-0.3%

277

217,808

46,895

+/-5,012

21.5%

+/-2.3%

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%

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

College Station-Bryan, TX

224,477

63,800

+/-6,284

28.4%

+/-2.8%

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%

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%

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

436,129

75,592

+/-7,264

17.3%

+/-1.6%

146

Corpus Christi, TX

Corvallis, OR

81,212

18,762

+/-2,296

23.1%

+/-2.8%

Crestview-Fort Walton Beach-Destin, FL

246,364

38,598

+/-5,626

15.7%

+/-2.3%

222

Cumberland, MD-WV

Dallas-Fort Worth-Arlington, TX

Dalton, GA

CRS-49

93,006

16,404

+/-2,954

17.6%

+/-3.2%

136

6,724,464

1,005,325

+/-30,615

15.0%

+/-0.5%

253

140,291

30,592

+/-4,719

21.8%

+/-3.4%

Poverty Rate (Percent Poor)

Number Poor

Metropolitan Area

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

Errora

Rankb

Danville, IL

77,461

14,964

+/-2,398

19.3%

+/-3.1%

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

2,663,509

323,179

+/-15,703

12.1%

+/-0.6%

328

Denver-Aurora-Lakewood, CO

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%

El Paso, TX

816,158

184,427

+/-12,589

22.6%

+/-1.5%

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%

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%

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%

CRS-50

Poverty Rate (Percent Poor)

Number Poor

Metropolitan Area

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

Errora

Rankb

Flint, MI

409,193

88,579

+/-7,484

21.6%

+/-1.8%

Florence, SC

201,368

46,093

+/-5,753

22.9%

+/-2.9%

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%

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%

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%

Gainesville, GA

185,118

40,630

+/-5,458

21.9%

+/-2.9%

Gettysburg, PA

97,009

8,620

+/-2,132

8.9%

+/-2.2%

372

316

Glens Falls, NY

124,199

15,784

+/-2,676

12.7%

+/-2.2%

Goldsboro, NC

120,867

25,910

+/-5,137

21.4%

+/-4.2%

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

159

Grants Pass, OR

82,361

14,035

+/-3,095

17.0%

+/-3.8%

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%

Greenville, NC

168,611

43,223

+/-5,197

25.6%

+/-3.1%

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%

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%

Hanford-Corcoran, CA

133,031

28,473

+/-5,298

21.4%

+/-4.0%

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

Poverty Rate (Percent Poor)

Number Poor

Metropolitan Area

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

Errora

Rankb

Hartford-West Hartford-East Hartford, CT

351

1,169,485

125,923

+/-9,009

10.8%

+/-0.8%

Hattiesburg, MS

144,861

34,291

+/-4,546

23.7%

+/-3.1%

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

Hinesville, GA

79,128

16,111

+/-3,079

20.4%

+/-3.9%

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%

Houma-Thibodaux, LA

205,658

27,916

+/-4,139

13.6%

+/-2.0%

292

6,228,091

1,021,922

+/-32,157

16.4%

+/-0.5%

184

354,931

71,701

+/-6,538

20.2%

+/-1.8%

Houston-The Woodlands-Sugar Land, TX

Huntington-Ashland, WV-KY-OH

Huntsville, AL

423,978

63,797

+/-6,818

15.0%

+/-1.6%

247

Idaho Falls, ID

135,972

15,189

+/-3,087

11.2%

+/-2.3%

343

1,909,800

290,647

+/-12,942

15.2%

+/-0.7%

242

152,657

23,856

+/-3,159

15.6%

+/-2.1%

224

Ithaca, NY

88,377

17,907

+/-2,704

20.3%

+/-2.9%

Jackson, MI

150,916

29,064

+/-3,814

19.3%

+/-2.5%

Jackson, MS

557,607

122,754

+/-7,806

22.0%

+/-1.4%

Jackson, TN

125,360

26,178

+/-3,335

20.9%

+/-2.7%

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%

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%

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

2,018,783

255,291

+/-12,778

12.6%

+/-0.6%

318

266,874

38,878

+/-5,751

14.6%

+/-2.2%

269

Indianapolis-Carmel-Anderson, IN

Iowa City, IA

Kansas City, MO-KS

Kennewick-Richland, WA

CRS-52

Poverty Rate (Percent Poor)

Number Poor

Metropolitan Area

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

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%

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%

Lakeland-Winter Haven, FL

608,424

118,007

+/-11,131

19.4%

+/-1.8%

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%

Las Cruces, NM

208,101

57,908

+/-6,390

27.8%

+/-3.1%

2,002,803

321,455

+/-16,823

16.1%

+/-0.8%

205

156

Las Vegas-Henderson-Paradise, NV

Lawrence, KS

105,235

17,967

+/-4,054

17.1%

+/-3.8%

Lawton, OK

121,949

24,842

+/-3,444

20.4%

+/-2.8%

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

Louisville/Jefferson County, KY-IN

1,237,895

171,328

+/-12,460

13.8%

+/-1.0%

288

292,742

51,653

+/-5,743

17.6%

+/-1.9%

134

Lubbock, TX

CRS-53

Poverty Rate (Percent Poor)

Number Poor

Metropolitan Area

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

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%

Madera, CA

144,954

34,242

+/-5,853

23.6%

+/-4.0%

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%

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%

Medford, OR

205,687

38,784

+/-7,040

18.9%

+/-3.4%

104

1,319,206

261,291

+/-11,676

19.8%

+/-0.9%

256,177

64,552

+/-6,551

25.2%

+/-2.6%

5,751,004

1,017,832

+/-27,848

17.7%

+/-0.5%

131

101,722

17,699

+/-3,213

17.4%

+/-3.2%

143

Memphis, TN-MS-AR

Merced, CA

Miami-Fort Lauderdale-West Palm Beach, FL

Michigan City-La Porte, IN

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%

Modesto, CA

518,152

114,628

+/-9,386

22.1%

+/-1.8%

Monroe, LA

168,802

42,735

+/-5,063

25.3%

+/-3.0%

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%

Morgantown, WV

126,795

24,361

+/-2,922

19.2%

+/-2.3%

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%

Muskegon, MI

163,873

33,809

+/-3,737

20.6%

+/-2.3%

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

Poverty Rate (Percent Poor)

Number Poor

Metropolitan Area

Naples-Immokalee-Marco Island, FL

Nashville-Davidson—Murfreesboro—Franklin, TN

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

Errora

Rankb

336,570

43,152

+/-6,178

12.8%

+/-1.8%

311

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%

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%

365

Ocean City, NJ

94,252

8,835

+/-1,881

9.4%

+/-2.0%

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

151

2,221,209

380,933

+/-21,384

17.1%

+/-1.0%

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-Titusville, 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%

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

137

4,325,550

760,706

+/-27,227

17.6%

+/-0.6%

Pine Bluff, AR

85,065

20,736

+/-3,415

24.4%

+/-3.8%

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

Pocatello, ID

81,080

13,900

+/-2,892

17.1%

+/-3.5%

152

CRS-55

Poverty Rate (Percent Poor)

Number Poor

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

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

2,281,296

308,138

+/-15,086

13.5%

+/-0.7%

295

211,524

34,138

+/-5,228

16.1%

+/-2.5%

201

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%

Punta Gorda, FL

160,389

22,628

+/-3,501

14.1%

+/-2.2%

283

Metropolitan Area

Portland-Vancouver-Hillsboro, OR-WA

Prescott, AZ

Providence-Warwick, RI-MA

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%

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

276

Roanoke, VA

303,618

43,633

+/-5,158

14.4%

+/-1.7%

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

Sacramento—Roseville—Arden-Arcade, CA

91,478

20,423

+/-4,011

22.3%

+/-4.3%

2,182,441

363,182

+/-16,433

16.6%

+/-0.8%

178

127

Saginaw, MI

190,729

34,020

+/-4,382

17.8%

+/-2.3%

Salem, OR

387,689

75,096

+/-8,212

19.4%

+/-2.1%

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

Poverty Rate (Percent Poor)

Number Poor

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

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%

Metropolitan Area

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

3,555,501

446,327

+/-18,551

12.6%

+/-0.5%

319

Seattle-Tacoma-Bellevue, WA

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%

Sierra Vista-Douglas, AZ

116,375

22,254

+/-3,418

19.1%

+/-2.9%

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%

Spartanburg, SC

310,176

58,165

+/-6,323

18.8%

+/-2.1%

107

Spokane-Spokane Valley, 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 College, PA

139,046

27,490

+/-3,453

19.8%

+/-2.5%

Staunton-Waynesboro, VA

111,589

12,717

+/-2,542

11.4%

+/-2.2%

338

CRS-57

Poverty Rate (Percent Poor)

Number Poor

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

Errora

Stockton-Lodi, CA

690,366

137,663

+/-9,607

19.9%

+/-1.4%

Sumter, SC

105,762

21,047

+/-3,419

19.9%

+/-3.2%

Syracuse, NY

635,056

101,432

+/-7,069

16.0%

+/-1.1%

211

Tallahassee, FL

353,498

76,104

+/-5,983

21.5%

+/-1.7%

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%

Texarkana, TX-AR

143,188

30,643

+/-4,351

21.4%

+/-2.9%

354

Metropolitan Area

Tampa-St. Petersburg-Clearwater, FL

Rankb

The Villages, FL

98,007

10,283

+/-2,179

10.5%

+/-2.2%

Toledo, OH

590,850

114,978

+/-7,622

19.5%

+/-1.3%

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%

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%

Vallejo-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%

304

Virginia Beach-Norfolk-Newport News, VA-NC

1,636,396

212,866

+/-11,713

13.0%

+/-0.7%

Visalia-Porterville, CA

448,360

135,066

+/-9,722

30.1%

+/-2.2%

Waco, TX

246,267

52,469

+/-6,245

21.3%

+/-2.5%

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 Falls, 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

Poverty Rate (Percent Poor)

Number Poor

Total

Population

Estimate

Margin of Errora

Poverty

Rate

Margin of

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%

Winchester, VA-WV

124,642

8,432

+/-1,934

6.8%

+/-1.5%

380

Metropolitan Area

Winston-Salem, NC

636,242

127,378

+/-10,165

20.0%

+/-1.6%

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%

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.

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.

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

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-9,624

19.8%

1.4%

131,402

+/-8,126

19.6%

1.2%

677,175

134,678

+/-9,229

19.9%

1.3%

676,562

118,192

+/-8,753

17.5%

1.3%

149

684,710

108,037

+/-7,907

15.8%

1.1%

192

684,445

78,856

+/-6,788

11.5%

1.0%

340

643,781

177,870

+/-9,741

27.6%

1.5%

718,359

67,016

+/-4,778

9.3%

0.7%

388

1st

695,472

155,250

+/-8,082

22.3%

1.2%

2nd

693,316

118,822

+/-9,247

17.1%

1.3%

162

3rd

698,447

163,662

+/-11,048

23.4%

1.5%

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%

8th

729,202

81,101

+/-10,398

11.1%

1.4%

354

9th

726,815

140,691

+/-12,946

19.4%

1.7%

103

1st

700,752

151,217

+/-9,195

21.6%

1.3%

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%

Congressional

District

Total

Population

Estimate

1st

680,039

134,336

2nd

669,393

3rd

4th

5th

6th

7th

Margin of

Errora

Alabama

Alaska

(at Large)

Arizona

Arkansas

Congressional Research Service

Poverty in the United States: 2013

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-7,972

18.6%

1.1%

123

95,297

+/-7,216

13.7%

1.0%

267

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%

7th

710,789

98,887

+/-10,134

13.9%

1.4%

258

8th

693,599

151,099

+/-9,870

21.8%

1.4%

9th

713,742

141,208

+/-11,730

19.8%

1.6%

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%

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%

22nd

721,442

162,392

+/-13,227

22.5%

1.7%

23rd

705,535

139,601

+/-12,652

19.8%

1.7%

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%

30th

736,172

101,938

+/-8,322

13.8%

1.1%

263

31st

704,960

149,510

+/-11,708

21.2%

1.6%

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%

Congressional

District

Total

Population

Estimate

1st

686,482

127,948

2nd

698,111

3rd

Margin of

Errora

California

Congressional Research Service

Poverty in the United States: 2013

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-10,376

17.3%

1.4%

158

150,803

+/-12,089

21.2%

1.7%

721,328

150,105

+/-9,344

20.8%

1.1%

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%

41st

721,684

145,863

+/-11,526

20.2%

1.6%

42nd

737,375

88,252

+/-11,066

12.0%

1.5%

323

43rd

721,992

154,696

+/-12,164

21.4%

1.6%

44th

697,779

169,473

+/-13,325

24.3%

1.7%

45th

724,246

59,876

+/-6,525

8.3%

0.9%

402

46th

708,339

147,887

+/-11,656

20.9%

1.6%

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%

52nd

690,588

72,736

+/-6,238

10.5%

0.9%

372

53rd

731,261

102,840

+/-12,694

14.1%

1.6%

252

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

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

District

Total

Population

Estimate

35th

712,143

123,251

36th

710,157

37th

38th

Margin of

Errora

Colorado

Connecticut

Congressional Research Service

Poverty in the United States: 2013

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-9,589

12.4%

1.1%

310

115,551

+/-7,400

18.9%

1.2%

116

695,249

111,431

+/-9,748

16.0%

1.4%

190

664,146

138,714

+/-8,918

20.9%

1.3%

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%

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%

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%

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%

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%

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

District

Total

Population

Estimate

900,322

111,327

611,788

1st

2nd

3rd

Margin of

Errora

Delaware

(at Large)

District of

Columbia

Delegate District

(at Large)

Florida

Congressional Research Service

Poverty in the United States: 2013

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-10,599

20.1%

1.5%

135,297

+/-8,201

19.4%

1.2%

103

651,114

177,017

+/-10,143

27.2%

1.5%

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%

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%

9th

698,289

140,702

+/-9,000

20.1%

1.3%

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%

13th

711,290

131,182

+/-12,045

18.4%

1.6%

125

14th

681,117

131,761

+/-11,132

19.3%

1.6%

105

1st

682,599

60,920

+/-5,936

8.9%

0.9%

395

2nd

685,063

87,448

+/-8,573

12.8%

1.2%

299

1st

794,263

123,653

+/-11,335

15.6%

1.4%

197

2nd

788,648

122,897

+/-8,979

15.6%

1.1%

197

1st

706,988

142,867

+/-10,464

20.2%

1.3%

2nd

688,548

156,163

+/-11,550

22.7%

1.5%

3rd

726,153

95,484

+/-10,108

13.1%

1.3%

288

4th

706,214

159,724

+/-13,235

22.6%

1.8%

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%

8th

708,838

78,817

+/-9,914

11.1%

1.3%

354

Congressional

District

Total

Population

Estimate

710,235

142,860

1st

696,283

2nd

27th

Margin of

Errora

Georgia

Hawaii

Idaho

Illinois

Congressional Research Service

Poverty in the United States: 2013

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-10,431

12.8%

1.4%

299

68,938

+/-8,091

9.9%

1.2%

379

702,136

72,337

+/-8,170

10.3%

1.2%

374

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

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%

8th

689,998

103,928

+/-7,111

15.1%

1.0%

216

9th

707,964

106,505

+/-6,825

15.0%

0.9%

224

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

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

District

Total

Population

Estimate

9th

690,182

88,569

10th

697,471

11th

12th

Margin of

Errora

Indiana

Iowa

Kansas

Congressional Research Service

Poverty in the United States: 2013

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-8,612

20.2%

1.2%

122,473

+/-7,098

17.1%

1.0%

162

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%

6th

719,324

135,150

+/-9,981

18.8%

1.4%

118

1st

766,678

103,791

+/-7,676

13.5%

1.0%

277

2nd

766,962

203,181

+/-11,910

26.5%

1.4%

3rd

753,214

125,639

+/-10,136

16.7%

1.3%

173

4th

739,473

157,598

+/-9,017

21.3%

1.2%

5th

706,617

175,044

+/-9,880

24.8%

1.4%

6th

762,045

122,766

+/-11,353

16.1%

1.4%

187

1st

655,033

78,463

+/-7,100

12.0%

1.1%

323

2nd

638,794

102,176

+/-6,263

16.0%

1.0%

190

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

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

District

Total

Population

Estimate

1st

697,666

141,016

2nd

715,427

3rd

Margin of

Errora

Kentucky

Louisiana

Maine

Maryland

Massachusetts

Congressional Research Service

Poverty in the United States: 2013

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-6,659

8.2%

0.9%

404

64,388

+/-7,237

8.8%

1.0%

397

700,909

147,321

+/-8,826

21.0%

1.2%

742,643

68,341

+/-6,059

9.2%

0.8%

389

702,400

80,420

+/-6,601

11.4%

0.9%

343

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%

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%

14th

695,668

183,707

+/-10,674

26.4%

1.4%

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

1st

737,103

152,530

+/-10,500

20.7%

1.4%

2nd

696,410

226,515

+/-10,737

32.5%

1.5%

Congressional

District

Total

Population

Estimate

5th

726,369

59,426

6th

733,179

7th

8th

9th

Margin of

Errora

Michigan

Minnesota

Mississippi

Congressional Research Service

Poverty in the United States: 2013

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-10,624

22.3%

1.5%

156,147

+/-11,579

21.2%

1.6%

716,639

154,322

+/-10,183

21.5%

1.4%

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%

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%

990,603

163,637

+/-9,336

16.5%

0.9%

176

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

1st

664,608

150,284

+/-10,320

22.6%

1.6%

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

1st

642,184

50,458

+/-5,547

7.9%

0.9%

410

2nd

638,997

61,037

+/-6,572

9.6%

1.0%

384

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

District

Total

Population

Estimate

3rd

722,227

160,723

4th

738,028

1st

Margin of

Errora

Missouri

Montana

(at Large)

Nebraska

Nevada

New Hampshire

New Jersey

Congressional Research Service

Poverty in the United States: 2013

Poverty Rate (Percent Poor)

Number Poor

Estimate

Margin of

Errora

Rankb

+/-7,488

9.6%

1.1%

384

50,882

+/-6,204

7.1%

0.9%

421

712,290

84,373

+/-8,494

11.8%

1.2%

330

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%

11th

721,415

33,693

+/-5,311

4.7%

0.7%

436

12th

728,120

70,260

+/-7,796

9.6%

1.1%

384

1st

685,428

133,437

+/-9,937

19.5%

1.4%

100

2nd

676,488

154,795

+/-8,582

22.9%

1.2%

3rd

683,486

160,229

+/-9,712

23.4%

1.4%

1st

701,

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