# Poverty in the United States: 2013 > Briefs, arguments, decisions, and more. URL: https://www.frixlaw.com/law-library/documents/crs%3ARL33069 ## Record - **Collection:** Congressional research report - **Document type:** CRS Report - **Published:** January 29, 2015 - **Citation:** RL33069 ## Text Poverty in the United States: 2013 /name redacted/ Specialist in Social Policy January 29, 2015 Congressional Research Service 7-.... www.crs.gov RL33069 Poverty in the United States: 2013 Summary In 2013, 45.3 million people were counted as poor in the United States under the official poverty measure—a number statistically unchanged from the 46.5 million people estimated as poor in 2012. The poverty rate, or percent of the population considered poor under the official definition, was reported at 14.5% in 2013, a statistically significant drop from the estimated 15.0% in 2012. Poverty in the United States increased markedly over the 2007-2010 period, in tandem with the economic recession (officially marked as running from December 2007 to June 2009), and remained unchanged at a post-recession high for three years (15.1% in 2010, and 15.0% in both 2011 and 2012). The 2013 poverty rate of 14.5% remains above a 2006 pre-recession low of 12.3%, and well above an historic low rate of 11.3% attained in 2000 (a rate statistically tied with a previous low of 11.1% in 1973). The incidence of poverty varies widely across the population according to age, education, labor force attachment, family living arrangements, and area of residence, among other factors. Under the official poverty definition, an average family of four was considered poor in 2013 if its 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. Congressional Research Service Poverty in the United States: 2013 Contents Trends in Poverty ............................................................................................................................. 1 The U.S. “Official” Definition of Poverty ....................................................................................... 2 Poverty among Selected Groups ...................................................................................................... 6 Racial and Ethnic Minorities ..................................................................................................... 6 Nativity and Citizenship Status ................................................................................................. 6 Children ..................................................................................................................................... 6 Adults with Low Education, Unemployment, or Disability ...................................................... 8 The Aged ................................................................................................................................... 9 Receipt of Need-Tested Assistance Among the Poor ....................................................................... 9 The Geography of Poverty............................................................................................................... 9 Poverty in Metropolitan and Nonmetropolitan Areas, Center Cities, and Suburbs ................. 10 Poverty by Region ................................................................................................................... 10 State Poverty Rates .................................................................................................................. 10 Change in State Poverty Rates: 2002-2013 ............................................................................. 14 Poverty Rates by Metropolitan Area ....................................................................................... 20 Congressional District Poverty Estimates ............................................................................... 22 “Neighborhood” Poverty—Poverty Areas and Areas of Concentrated and Extreme Poverty ................................................................................................................................. 23 The Research Supplemental Poverty Measure .............................................................................. 25 Poverty Thresholds .................................................................................................................. 29 SPM Poverty Thresholds ................................................................................................... 29 Resources and Expenses Included in the SPM ........................................................................ 30 Poverty Estimates Under the Research SPM Compared to the “Official” Measure................ 31 Poverty by Age .................................................................................................................. 31 Poverty by Type of Economic Unit ................................................................................... 32 Poverty by Region ............................................................................................................. 34 Poverty by Residence ........................................................................................................ 35 Poverty by State ................................................................................................................ 36 Marginal Effects of Counting Specified Resources and Expenses on Poverty under the SPM ................................................................................................................ 41 Distribution of the Population by Ratio of Income/Resources Relative to Poverty .......... 42 Discussion................................................................................................................................ 44 Figures Figure 1. Trend in Poverty Rate and Number of Poor Persons: 1959-2013, and Unemployment Rate from January 1959 through August 2014 ................................................... 4 Figure 2. U.S. Poverty Rates by Age Group, 1959-2013 ................................................................. 5 Figure 3. Child Poverty Rates by Family Living Arrangement, Race and Hispanic Origin, 2013 .............................................................................................................................................. 7 Figure 4. Composition of Children, by Family Type, Race and Hispanic Origin, 2013 .................. 8 Figure 5. Percentage of People in Poverty in the Past 12 Months by State and Puerto Rico: 2013 ....................................................................................................... 11 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 ................................................................................................. 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 Congressional Research Service Poverty in the United States: 2013 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 Congressional Research Service Poverty in the United States: 2013 Trends in Poverty1 In 2013, the official U.S. poverty rate was 14.5%, compared to 15.0% in 2012, and marked the first statistically significant drop in the rate since 2006. In 2013, 45.3 million persons were estimated as having income below the official poverty line, a number statistically unchanged from the estimated 46.5 million poor in 2012. (See Figure 1.) Figure 1 shows a clear relationship between poverty and the economy. The level of poverty tends to follow the economic cycle quite closely, tending to rise when the economy is faltering and fall when the economy is in sustained growth. The poverty rate increased markedly over the past decade, in part a response to two economic recessions (periods marked in red). A strong economy during most of the 1990s is generally credited with the declines in poverty that occurred over the latter half of that decade, resulting in a record-tying, historic low poverty rate of 11.3% in 2000 (a rate statistically tied with the previous lowest recorded rate of 11.1% in 1973). The poverty rate increased each year from 2001 through 2004, a trend generally attributed to economic recession (March 2001 to November 2001), and failed to recede appreciably before the onset of the December 2007 recession. This most recent recession, which officially ended in June 2009, was the longest recorded (18 months) in the 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 1 Supporting data are based on the following: U.S. Census Bureau, Income and Poverty in the United States: 2013; Current Population Report No. P60-249, September 2014; and unpublished Census Bureau tables, available on the Internet at http://www.census.gov/hhes/www/poverty/data/incpovhlth/2013/index.html. 2 Periods of recession are officially defined by the National Bureau of Economic Research (NBER) Business Cycle Dating Committee. See http://www.nber.org/cycles/main.html. 3 The poverty rate of non-aged adults was 17.0% in 1959. Comparable estimates are not available from 1960 through 1965. By 1966, the non-aged poverty rate stood at 10.5%. See Table A-1. 4 CRS Report RL33615, Parents’ Work and Family Economic Well-Being, by (name redacted) and (name redacted). Congressional Research Service 1 Poverty in the United States: 2013 children in the country live with only one parent, making them even more prone to falling into poverty when the economy falters. In 2013, the aged poverty rate (9.5%) was statistically unchanged from 2012, although the number of poor rose by an estimated 305,000 (from 3.9 million in 2012 to 4.2 million in 2013). In spite of the recession, the aged poverty rate remains near an historic low level. The longer-term secular trend in poverty has been affected by changes in household and family composition and by government income security and transfer programs. In 1959, over one-third (35.2%) of persons age 65 and over were poor, a rate well above that of children (26.9%). Social Security, in combination with a maturing pension system, has helped greatly to reduce the incidence of poverty among the aged over the years, and as recent evidence seems to show, it has helped protect them during the economic downturn. The U.S. “Official” Definition of Poverty5 The Census Bureau’s poverty thresholds form the basis for statistical estimates of poverty in the United States.6 The thresholds reflect crude estimates of the amount of money individuals or families, of various size and composition, need per year to purchase a basket of goods and services deemed as “minimally adequate,” according to the living standards of the early 1960s. The thresholds are updated each year for changes in consumer prices. In 2013, for example, the average poverty threshold for an individual living alone was $11,888; for a two-person family, $15,142; and for a family of four, $23,834.7 The current official U.S. poverty measure was developed in the early 1960s using data available at the time. It was based on the concept of a minimal standard of food consumption, derived from research that used data from the U.S. Department of Agriculture’s (USDA’s) 1955 Food Consumption Survey. That research showed that the average U.S. family spent one-third of its pre-tax income on food. A standard of food adequacy was set by pricing out the USDA’s Economy Food Plan—a bare-bones plan designed to provide a healthy diet for a temporary period when funds are low. An overall poverty income level was then set by multiplying the food plan by three, to correspond to the findings from the 1955 USDA Survey that an average family spent one-third of its pre-tax income on food and two-thirds on everything else. The “official” U.S. poverty measure8 has changed little since it was originally adopted in 1969, with the exception of annual adjustments for overall price changes in the economy, as measured by the Consumer Price Index for all Urban Consumers (CPI-U). Thus, the poverty line reflects a 5 For a more complete discussion of the U.S. poverty measure, see CRS Report R41187, Poverty Measurement in the United States: History, Current Practice, and Proposed Changes, by (name redacted). 6 The Department of Health and Human Services (HHS) releases poverty income guidelines that are derived directly from Census poverty thresholds. These guidelines, a simplified approximation of the Census poverty thresholds, are used by HHS and other federal agencies for administering programs, particularly for determining program eligibility. For current guidelines and methods for their computation, see http://aspe.hhs.gov/poverty/index.shtml. 7 See http://www.census.gov/hhes/www/poverty/data/threshld/index.html. 8 The poverty measure was adopted as the “official poverty measure” by a directive issued in 1969 by the Bureau of the Budget, now the Office of Management and Budget (OMB). The directive was revised in 1978 to include revisions to poverty thresholds and procedures for updating thresholds for inflation using the Consumer Price Index (CPI). See OMB Statistical Policy Directive 14, available on the Internet at http://www.census.gov/hhes/povmeas/methodology/ ombdir14.html. Congressional Research Service 2 Poverty in the United States: 2013 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. 9 Congressional Research Service 3 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 10 Beginning with the March 2003 CPS, the Census Bureau allows survey respondents to identify themselves as belonging to one or more racial groups. In prior years, respondents could select only one racial category. Consequently, poverty statistics for different racial groups for 2002 and after are not directly comparable to earlier years’ data. The terms black and white, above, refer to persons who identified with only a single racial group. The term Hispanic refers to individuals’ ethnic, as opposed to racial, identification. Hispanics may be of any race. Congressional Research Service 6 Poverty in the United States: 2013 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. Congressional Research Service 7 Poverty in the United States: 2013 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 11 The CPS asks several questions to determine whether individuals are considered to have a work disability. Persons are identified as having a work disability if they (1) reported having a health problem or disability that prevents them (continued...) Congressional Research Service 8 Poverty in the United States: 2013 those with a severe work disability, 35.6% were poor, compared to 17.0% of those with a less severe disability and 11.4% who reported having no work-related disability. The Aged In 2013, the 9.5% poverty rate among persons age 65 and older was statistically unchanged from the 2012 rate (9.1%), but statistically higher than the all-time low-poverty rate among the aged of 8.7% attained in 2011. The number of aged poor grew by 305,000 from 2012 to 2013, from 3.9 million to 4.2 million,. Among persons age 75 and over, 11.2% were poor in 2013, compared to 8.3% of those ages 65 to 74. Measured by a slightly raised poverty standard (125% of the poverty threshold), 15.1% of the aged could be considered poor or “near poor” in 2013; 12.6% who are ages 65 to 74, and 18.4% who are 75 years of age and over, could be considered poor or “near poor.” Receipt of Need-Tested Assistance Among the Poor In 2013, nearly three of every four poor persons (73.8%) lived in households that received any means-tested assistance during the year.12 Such assistance could include cash aid, such as Temporary Assistance for Needy Families (TANF), Supplemental Security Income (SSI) payments, SNAP benefits (Food Stamps), Medicaid, subsidized housing, free or reduced price school lunches, and other programs. In 2013, somewhat over one in five (17.4%) poor persons lived in households that received cash aid; half (49.5%) received SNAP benefits (formerly named Food Stamps); 6 in 10 (61.3%) lived in households where one or more household members were covered by Medicaid; and about 1 in 7 (14.8%) lived in subsidized housing. Poor single-parent families with children are among those families most likely to receive cash aid. Among poor children who were living in single female-headed families, about one-fifth (21.9%) were in households that received government cash aid in 2013, down from 24.0% in 2012. The share of poor children in single female-headed families receiving cash aid is well below historical levels. In 1993, 70.2% of these children’s families received cash aid. In 1995, the year prior to passage of sweeping welfare changes under PRWORA, 65% of such children were in families receiving cash aid. The Geography of Poverty Poverty is more highly concentrated in some areas than in others; it is about twice as high in center cities as it is in suburban areas and nearly three times as high in the poorest states as it is in the least poor states. Some neighborhoods may be characterized as having high concentrations of (...continued) from working or that limits the kind or amount of work they can do; (2) ever retired or left a job for health reasons; (3) did not work in the survey week because of long-term physical or mental illness or disability which prevents the performance of any kind of work; (4) did not work at all in the previous year because they were ill or disabled; (5) are under 65 years of age and covered by Medicare; (6) are under age 65 years of age and a recipient of Supplemental Security Income (SSI); or (7) received veteran’s disability compensation. Persons are considered to have a severe work disability if they meet any of the criteria in (3) through (6), above. See http://www.census.gov/hhes/www/disability/ disabcps.html. 12 See http://www.census.gov/hhes/www/cpstables/032014/pov/pov26_000.htm Congressional Research Service 9 Poverty in the United States: 2013 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 10 Poverty in the United States: 2013 Michigan and New York, and the District of Columbia, in the eastern half of the nation, and California, Oregon, and Montana in the western half. States along the Atlantic Seaboard from Virginia northward tended to have poverty rates well below the national rate, as did three contiguous states in the upper Midwest/plains (Iowa, Minnesota, and North Dakota), as well as Utah, Wyoming, Alaska, and Hawaii. Figure 5. Percentage of People in Poverty in the Past 12 Months by State and Puerto Rico: 2013 Source: U.S. Census Bureau, 2012 American Community Survey, 2013 Puerto Rico Community Survey. Alemayehu Bishaw, Poverrty: 2012 and 2013, U.S. Census Bureau, American Community Survey Briefs, ACSBR/13-0101, Washington, DC, September 2014, p. 4, http://census.gov/content/dam/Census/library/ publications/2014/acs/acsbr13-01.pdf. Figure 6 shows estimated poverty rates for the United States and for each of the 50 states and the District of Columbia on the basis of the 2013 American Community Survey (ACS), the most recent ACS data currently available. In addition to the point estimates, the figure displays a 90% statistical confidence interval around each state’s estimate, indicating the degree to which these estimates might be expected to vary based on sample size. Although the states are sorted from lowest to highest by their respective poverty rate point estimates, the precise ranking of each state is not possible because of the depicted margin of error around each state’s estimate. All states with non-overlapping statistical confidence intervals have statistically significant different Congressional Research Service 11 Poverty in the United States: 2013 poverty rates from one another. Some states with overlapping confidence intervals may also have significantly different poverty rates from one another, measured at the 90% confidence interval.13 For example, New Hampshire, shown as having the lowest poverty rate (8.7%) in 2013, is statistically tied with Alaska (9.3%). Mississippi clearly stands out as the state with the highest poverty rate (24.0%) and New Mexico, with a poverty rate of 21.8%, has the second-highest poverty rate. Louisiana, a state ranked as having the third-highest poverty rate (19.7%), is statistically tied with Arkansas (19.7%) and the District of Columbia (18.9%), but not with Georgia (19.0%), even though Louisiana and Georgia’s statistical confidence intervals overlap. 13 Two states’ poverty rates are statistically different at the 90% statistical confidence interval if the confidence intervals bounding their respective poverty rates do not overlap with one another. However, some states with overlapping confidence intervals may also statistically differ at the 90% statistical confidence interval. In order to precisely determine whether two states’ poverty rates differ from one another, a statistical test of differences must be performed. The standard 2 2 . 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 12 Poverty in the United States: 2013 Figure 6. Poverty Rates for the 50 States and the District of Columbia: 2013 American Community Survey (ACS) Data Source: Prepared by the Congressional Research Service on the basis of U.S. Census Bureau 2013 American Community Survey (ACS) data. Congressional Research Service 13 Poverty in the United States: 2013 Change in State Poverty Rates: 2002-2013 Table 1 provides estimates of state and national poverty rates from 2002 through 2013 from the ACS. Statistically significant changes from one year to the next are indicated by an 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 14 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. 15 Congressional Research Service 14 Poverty in the United States: 2013 rise, and four saw a decline. Comparing 2013 to 2007, poverty rates were statistically higher in 48 states (including the District of Columbia), and no state had a poverty rate statistically below its prerecession rate. Congressional Research Service 15 Table 1. Poverty Rates for the 50 States and the District of Columbia, 2002 to 2013 Estimates from the American Community Survey (ACS) (percent poor) Change in Poverty Rates over Selected Periods and Statistically Significant Differencesa Estimated Poverty Rates and Statistically Significant Differences over Previous Year 2005 2013 vs. 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 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 14.2 14.2 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 13.3 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 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 8.3 7.9 9.3 ▲ 9.4 10.1 ▲ 10.9 ▲ 10.7 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 13.8 14.5 13.9 12.6 ▼ 12.1 12.6 14.3 ▲ 15.7 ▲ 16.5 15.9 15.6 0.0 3.4 ▲ Illinois 11.6 11.3 11.9 12.0 12.3 11.9 12.2 13.3 ▲ 13.8 ▲ 15.0 ▲ 14.7 14.7 0.4 ▲ 2.7 ▲ Indiana 10.9 10.6 10.8 12.2 ▲ 12.7 12.3 13.1 ▲ 14.4 ▲ 15.3 ▲ 16.0 ▲ 15.6 15.9 1.3 ▲ 3.6 ▲ Iowa 11.2 10.1 9.9 10.9 ▲ 11.0 11.0 11.5 11.8 12.6 ▲ 12.8 12.7 12.7 (0.3) 1.6 ▲ Kansas 12.1 10.8 10.5 11.7 ▲ 12.4 11.2 ▼ 11.3 13.4 ▲ 13.6 13.8 14.0 14.0 (0.4) 2.8 ▲ CRS-16 Change in Poverty Rates over Selected Periods and Statistically Significant Differencesa Estimated Poverty Rates and Statistically Significant Differences over Previous Year 2005 2013 vs. vs. 2007 2002 2003 2004 2005 2006b 2007b 2008b 2009b 2010b 2011b 2012b 2013b 2001 Kentucky 15.6 17.4 17.4 16.8 17.0 17.3 17.3 18.6 ▲ 19.0 19.1 19.4 18.8 1.2 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 12.3 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 9.9 10.0 10.3 11.4 ▲ 11.6 11.9 11.9 1.4 ▲ 2.0 ▲ Michigan 11.0 11.4 12.3 13.2 ▲ 13.5 14.0 ▲ 14.4 ▲ 16.2 ▲ 16.8 ▲ 17.5 ▲ 17.4 17.0 2.2 ▲ 3.0 ▲ Minnesota 8.5 7.8 8.3 9.2 ▲ 9.8 ▲ 9.5 9.6 11.0 ▲ 11.6 ▲ 11.9 11.4 ▼ 11.2 0.6 ▲ 1.7 ▲ Mississippi 19.9 19.9 21.6 ▲ 21.3 21.1 20.6 21.2 21.9 22.4 22.6 24.2 ▲ 24.0 1.5 ▲ 3.4 ▲ ▲ 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 14.2 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 8.7 8.6 8.7 9.4 ▲ 10.3 ▲ 10.4 10.8 11.4 New Mexico 18.9 18.6 19.3 18.5 18.5 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 17.2 16.8 1.5 Oregon 13.2 13.9 14.1 14.1 13.3 ▼ 12.9 13.6 ▲ 14.3 15.8 ▲ 17.5 ▲ 17.2 16.7 0.9 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. 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 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 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: 5 10 14 7 14 11 32 34 18 5 7 23 48 Increase in poverty 5▲ 8▲ 13 ▲ 4 ▲ 1 ▲ 8▲ 32 ▲ 34 ▲ 17 ▲ 3 ▲ 3 ▲ 22 ▲ 48 ▲ Decrease in poverty 0▼ 2▼ 1 ▼ 3 ▼ 13 ▼ 3▼ 0 ▼ 0 ▼ 1 ▼ 2 ▼ 4 ▼ 1 0 ▼ Source: Congressional Research Service (CRS) estimates from U.S. Census Bureau American Community Survey (ACS) data, 2002 to 2013. Notes: ▲ 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. a. Depicted changes in poverty rates over selected periods may differ slightly from differences calculated directly from the table, due to rounding. b. Comparisons to 2002 through 2005 estimates are not strictly comparable, due to inclusion of persons living in some non-institutional group quarters beginning in 2006 and after. CRS-19 Poverty in the United States: 2013 Poverty Rates by Metropolitan Area The four tables that follow provide poverty estimates for large metropolitan areas having a population of 500,000 and over, and for smaller metropolitan areas having a population of 50,000 or more but less than 500,000. Among large metropolitan areas, 10 areas with some of the lowest poverty rates are shown in Table 2, and the 10 areas with some of the highest poverty rates are shown in Table 3. Among smaller metropolitan areas, 10 areas with some of the lowest poverty rates are shown in Table 4, and 10 among those with the highest poverty rates in Table 5. It should be noted that metropolitan areas shown in these tables may not be statistically different from one another, or from others not shown in the tables. Poverty estimates for all metropolitan areas in 2013 are shown in Appendix B. Table B-1. Table 2. Large Metropolitan Areas Among Those with the Lowest Poverty Rates: 2013 (Metropolitan Areas with Population of 500,000 and Over) 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. a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted from an estimate, the range reflects a 90% statistical confidence interval bounding the estimate. Congressional Research Service 20 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. a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted from an estimate, the range reflects a 90% statistical confidence interval bounding the estimate. Table 4. Smaller Metropolitan Areas Among Those with the Lowest Poverty Rates: 2013 (Metropolitan Areas with Populations Between 50,000 and 499,999) 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% Congressional Research Service 21 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. a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted from an estimate, the range reflects a 90% statistical confidence interval bounding the estimate. Table 5. Smaller Metropolitan Areas Among Those with the Highest Poverty Rates: 2013 (Metropolitan Areas with Population of 500,000 and Over) 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. a. Margin of error of an estimate based on a 90% statistical confidence level. When added to and subtracted from an estimate, the range reflects a 90% statistical confidence interval bounding the estimate. Congressional District Poverty Estimates Poverty estimates for congressional districts are shown in Appendix C. Table C-1 includes poverty rate estimates for 2012. Congressional districts in 2012 are not directly comparable to earlier years, due to re-districting. Congressional Research Service 22 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 23 Figure 7. Distribution of Poor People by Race and Hispanic Origin, by Level of Neighborhood (Census Tract) Poverty, 2009-2013 Source: Congressional Research Service (CRS) analysis of U.S. Census Bureau American Community Survey five-year (2009-2013) data. CRS-24 Poverty in the United States: 2013 The Research Supplemental Poverty Measure On October 16, 2014, the Census Bureau released its fourth annual report using a new Supplemental Poverty Measure (SPM).16 As its name implies, the SPM is intended to “supplement,” rather than replace, the “official” poverty measure. The “official” Census Bureau statistical measure of poverty will continue to be used by programs that allocate funds to states or other jurisdictions on the basis of poverty, and the Department of Health and Human Services (HHS) will continue to derive Poverty Income Guidelines from the “official” Census Bureau measure. Many experts consider the “official” poverty measure to be flawed and outmoded.17 In 1990, Congress commissioned a study on how poverty is measured in the United States, resulting in the National Academy of Sciences (NAS) convening a 12-member expert panel to study the issue. The NAS panel issued a wide range of specific recommendations to develop an improved statistical measure of poverty in its 1995 report Measuring Poverty: A New Approach.18 In late 2009, the Office of Management and Budget (OMB) formed an Interagency Technical Working Group19 (ITWG) to suggest how the Census Bureau, in cooperation with the Bureau of Labor Statistics (BLS), should develop a new Supplemental Poverty Measure, using the NAS expert panel’s recommendations as a starting point. Referencing the work of the ITWG,20 the Department of Commerce announced in March 2010 that the Census Bureau was developing a new Supplemental Poverty Measure, as “an alternative lens to understand poverty and measure the effects of anti-poverty policies,” with the intention that the new measure “will be dynamic and will benefit from improvements over time based on new data and new methodologies.”21 The SPM is intended to address a number of weaknesses of the “official” measure. Criticisms of the “official” poverty measure raised by the NAS expert panel include the following: • The “official” poverty measure, by counting only families’ total cash, pre-tax income as a resource in determining poverty status, ignores a host of government programs and policies that affect the disposable income families may actually have available. For example, the official measure ignores the effects of payroll taxes paid by families, and tax benefits they may receive such as the EITC and 16 Kathleen Short, The Supplemental Poverty Measure: 2013, U.S. Census Bureau, P60-251, Washington, DC, October 2014, http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf. 17 For a discussion of the history and development of the U.S. poverty measure, and efforts to improve poverty measurement, see CRS Report R41187, Poverty Measurement in the United States: History, Current Practice, and Proposed Changes, by (name redacted). 18 National Research Council, Panel on Poverty and Family Assistance, “Measuring Poverty: A New Approach,” Constance F. Citro and Robert T. Michael, eds. (Washington, DC: National Academy Press, 1995). (Hereinafter cited as Citro and Michael, Measuring Poverty…) 19 The working group included representatives from BLS, the Census Bureau, the Council of Economic Advisors, the Department of Commerce, the Department of Health and Human Services, and OMB. 20 The ITWG’s guidance is available at http://www.census.gov/hhes/www/poverty/SPM_TWGObservations.pdf. 21 Census Bureau to Develop Supplemental Poverty Measure, March 2, 2010 News Release, Economics and Statistics Administration, U.S. Department of Commerce. Available on the Internet at http://www.esa.doc.gov/news/2010/03/02/ census-bureau-develop-supplemental-poverty-measure. Congressional Research Service 25 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 26 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 CE 27 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. Congressional Research Service 28 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 22 The NAS panel recommended that the reference family for establishing initial thresholds be based on families with two adults and two children. The ITWG suggested that initial thresholds be based on consumer units with exactly two children, as children reside in a variety of family types (such as single parent families, presence of one or more grandparents, and families with cohabiting adult partners). The NAS panel recommended that initial thresholds be established at between 78% and 83% of median expenditures on FCSU of reference families, which empirically ranged between the 30th and 35th percentiles. The ITWG suggested that initial thresholds be set at a range around the 33rd percentile of expenditures on FCSU for the reference consumer units. The ITWC suggested that five years of CE data be used in establishing thresholds to smooth the change in the thresholds from one year to the next. 23 The 1.2 multiplier applied to FCSU equals the midpoint of the NAS panel’s recommended multiplier of between 1.15 and 1.25. Congressional Research Service 29 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 Congressional Research Service 30 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. 24 “Official” published estimates of poverty exclude unrelated children under the age of 15 in the universe for whom poverty is determined. For comparison with the SPM measure, these children are included in both the “adjusted official” poverty measure and the SPM. Under the “official” published poverty measure, the overall poverty rate was 14.5% in 2013; under the adjusted measure shown in this report, the overall “official” poverty rate in 2013 was 14.6%. Congressional Research Service 31 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. Congressional Research Service 32 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. 25 For further discussion, see Ashley J. Provencher, Unit of Analysis for Poverty Measurement: A Comparison of the Supplemental Poverty Measure and the Official Poverty Measure, U.S. Census Bureau, SEHSD Working Paper # 2011-22, Washington, DC, August 2, 2011, http://www.census.gov/hhes/povmeas/methodology/supplemental/research/ Provencher_JSM.pdf. Congressional Research Service 33 Poverty in the United States: 2013 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. Congressional Research Service 34 Poverty in the United States: 2013 Figure 11. Poverty Rates Under the “Official”* and Research Supplemental Poverty Measures, by Region: 2013 (Percent Poor) Source: Figure prepared by the Congressional Research Service (CRS), based on Kathleen Short, The Supplemental Poverty Measure: 2013, U.S. Census Bureau, P60-251, Washington, DC, October 2014, http://census.gov/content/dam/Census/library/publications/2014/demo/p60-251.pdf. * Differs from published “official” poverty rates as unrelated individuals under age 15 are included in the universe. Poverty by Residence Figure 12 depicts poverty rates by residence in metropolitan (principal city, and outside principal city [i.e., “suburban”]) and nonmetropolitan areas in 2013.26 The figure shows that under the SPM, the poverty rate for persons living in Metropolitan Statistical Areas (MSAs) (15.9%) is somewhat higher than under the “official” measure (14.3%), whereas for persons living outside MSAs, the poverty rate is lower under the SPM (13.2%) than under the “official” measure (16.2%). Again, this most likely reflects differences in the cost of housing between MSAs and non-MSAs. Within MSAs, poverty rates are higher for persons living within principal cities under both measures than for people living outside them in “suburban” or “ex-urban” areas. 26 The Census Bureau defines Metropolitan Statistical Areas (MSAs) containing a core urban area with a population of 50,000 or more, consisting of one or more counties, that includes the counties containing the urban core area as well as any adjacent counties that have a high degree of social and economic integration (as measured by commuting to work) with the urban core. See http://www.census.gov/population/metro/. Congressional Research Service 35 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 27 Significant differences based on a 90% statistical confidence level. Congressional Research Service 36 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 28 Significant difference at a 90% statistical confidence level. Congressional Research Service 37 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%). Congressional Research Service 38 Poverty in the United States: 2013 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. Congressional Research Service 39 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. Congressional Research Service 40 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. Congressional Research Service 41 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- Congressional Research Service 42 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. Congressional Research Service 43 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. Congressional Research Service 44 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 In 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 10.1 9.9 7.8 22.7 21.4 n/a 2000r 11.3 15.6 40.1 8.6 9.6 9.9 9.5 7.4 22.5 21.5 n/a 1999 11.8 16.3 41.9 9.0 10.0 9.7 9.8 7.7 23.6 22.8 n/a 1998 12.7 18.3 46.1 9.7 10.5 10.5 10.5 8.2 26.1 25.6 n/a 1997 13.3 19.2 49.0 10.2 10.9 10.5 11.0 8.6 26.5 27.1 n/a 1996 13.7 19.8 49.3 10.9 11.3 10.8 11.2 8.6 28.4 29.4 n/a 1995 13.8 20.2 50.3 10.7 11.4 10.5 11.2 8.5 29.3 30.3 n/a 1994 14.5 21.2 52.9 11.7 11.9 11.7 11.7 9.4 30.6 30.7 n/a 1993 15.1 22.0 53.7 12.4 12.4 12.2 12.2 9.9 33.1 30.6 n/a 1992r 14.8 21.6 54.6 11.8 11.9 12.9 11.9 9.6 33.4 29.6 n/a 1991r 14.2 21.1 55.5 11.1 11.4 12.4 11.3 9.4 32.7 28.7 n/a 1990 13.5 19.9 53.4 10.7 10.7 12.2 10.7 8.8 31.9 28.1 n/a 1989 12.8 19.0 51.1 10.4 10.2 11.4 10.0 8.3 30.7 26.2 n/a 1988r 13.0 19.0 52.9 10.0 10.5 12.0 10.1 8.4 31.3 26.7 n/a 1987r 13.4 19.7 54.7 10.9 10.6 12.5 10.4 8.7 32.4 28.0 n/a 1986 13.6 19.8 54.4 10.8 10.8 12.4 11.0 9.4 31.1 27.3 n/a 1985 14.0 20.1 53.6 11.7 11.3 12.6 11.4 9.7 31.3 29.0 n/a 1984 14.4 21.0 54.0 12.5 11.7 12.4 11.5 10.0 33.8 28.4 n/a Congressional Research Service In All Other Families Ages 1864 Age 65+ 45 Poverty in the United States: 2013 Related Children Under Age18a Adults Year All Persons Total In 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 8.3 14.6 8.6 7.7 30.3 23.0 n/a 1973 11.1 14.2 52.1 7.6 8.3 16.3 8.4 7.5 31.4 21.9 n/a 1972 11.9 14.9 53.1 8.6 8.8 18.6 9.0 n/a 33.3 n/a n/a 1971 12.5 15.1 53.1 9.3 9.3 21.6 9.9 n/a 32.5 n/a n/a 1970 12.6 14.9 53.0 9.2 9.0 24.6 9.9 n/a 33.5 n/a n/a 1969 12.1 13.8 54.4 8.6 8.7 25.3 9.5 n/a 32.2 n/a n/a 1968 12.8 15.3 55.2 10.2 9.0 25.0 10.0 n/a 34.7 n/a n/a 1967 14.2 16.3 54.3 11.5 10.0 29.5 11.0 n/a 39.3 n/a n/a 1966 14.7 17.4 58.2 12.6 10.5 28.5 11.3 n/a 41.8 n/a n/a 1959 22.4 26.9 72.2 22.4 17.0 35.2 18.1 n/a 55.1 n/a n/a Source: Prepared by the Congressional Research Service using U.S. Bureau of the Census data based on the “official” measure of poverty. Notes: r = revised estimates. n/a = not available. a. Beginning in 1979, restricted to children in primary families only. Before 1979, includes children in unrelated subfamilies. b. Beginning in 2002, CPS respondents could identify themselves as being of more than one race. Consequently, racial data for 2002 and after are not comparable to earlier years. Here, in 2002 and after, the term white means of white race alone, the term black means of black race alone, and the term Asian means Asian alone. Hispanics, who may be of any race, are included among whites and blacks unless otherwise noted. Congressional Research Service 46 Appendix B. Metropolitan Area Poverty Estimates Table B-1. Metropolitan Area Poverty: 2013 Number Poor Poverty Rate (Percent Poor) Total 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% 15 Albany, OR 117,252 23,986 +/-4,096 20.5% +/-3.5% 60 320 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% 86 Alexandria, LA 147,861 27,656 +/-3,989 18.7% +/-2.7% 110 Allentown-Bethlehem-Easton, PA-NJ 804,393 99,692 +/-6,980 12.4% +/-0.9% 324 Altoona, PA 123,730 20,392 +/-3,212 16.5% +/-2.6% 182 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% 22 Anchorage, AK 386,833 27,596 +/-3,586 7.1% +/-0.9% 379 Ann Arbor, MI 335,915 56,191 +/-5,089 16.7% +/-1.5% 175 Anniston-Oxford-Jacksonville, AL 113,722 24,825 +/-3,340 21.8% +/-2.9% 38 Appleton, WI 226,221 18,291 +/-2,940 8.1% +/-1.3% 376 214 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% 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% 56 Augusta-Richmond County, GA-SC Austin-Round Rock, TX Bakersfield, CA 565,819 111,863 +/-8,976 19.8% +/-1.6% 80 1,841,572 262,644 +/-14,918 14.3% +/-0.8% 281 831,344 189,484 +/-13,393 22.8% +/-1.6% 26 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% 40 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% 27 Bloomington, IL 184,309 27,681 +/-3,555 15.0% +/-1.9% 249 Bloomington, IN 148,709 33,760 +/-3,426 22.7% +/-2.2% 28 Bloomsburg-Berwick, PA 80,653 13,275 +/-2,443 16.5% +/-3.0% 183 Boise City, ID 637,683 107,713 +/-12,906 16.9% +/-2.0% 167 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% 82 Bremerton-Silverdale, WA 245,971 27,727 +/-4,028 11.3% +/-1.6% 342 Bridgeport-Stamford-Norwalk, CT 921,302 88,808 +/-6,895 9.6% +/-0.7% 359 Brownsville-Harlingen, TX 412,432 134,170 +/-8,943 32.5% +/-2.2% 2 Brunswick, GA 111,440 22,111 +/-4,204 19.8% +/-3.8% 76 257 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% 57 Burlington-South Burlington, VT 205,647 21,596 +/-3,045 10.5% +/-1.5% 353 California-Lexington Park, MD 106,530 6,831 +/-2,204 6.4% +/-2.1% 381 Canton-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% 25 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 C [Text truncated at 120,000 characters. The full text is on the page linked above.] --- Source: Frix Law Library, https://www.frixlaw.com/law-library/documents/crs%3ARL33069. Public record. Not legal advice.