document: In 2013, the official U.S. poverty rate was 14.5%, compared to 15.0% in 2012, and marked the first statistically significant drop in the rate since 2006. In 2013, 45.3 million persons were estimated as having income below the official poverty line, a number statistically unchanged from the estimated 46.5 million poor in 2012. (See Figure 1 .) Figure 1 shows a clear relationship between poverty and the economy. The level of poverty tends to follow the economic cycle quite closely, tending to rise when the economy is faltering and fall when the economy is in sustained growth. The poverty rate increased markedly over the past decade, in part a response to two economic recessions (periods marked in red). A strong economy during most of the 1990s is generally credited with the declines in poverty that occurred over the latter half of that decade, resulting in a record-tying, historic low poverty rate of 11.3% in 2000 (a rate statistically tied with the previous lowest recorded rate of 11.1% in 1973). The poverty rate increased each year from 2001 through 2004, a trend generally attributed to economic recession (March 2001 to November 2001), and failed to recede appreciably before the onset of the December 2007 recession. This most recent recession, which officially ended in June 2009, was the longest recorded (18 months) in the post-World War II period. 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. In 2013 the non-aged poverty rate of 13.6% remained statistically unchanged from rates seen in the prior three years. The poverty rate for non-aged adults will need to fall to 10.8% to reach its 2006 pre-recession level. The 2013 poverty data provide one encouraging sign with respect to children. Both the estimated number of poor children and their poverty rate fell from 2012 to 2013. In 2013, the number of poor children fell by an estimated 1.3 million (15.4 million in 2012 to 14.1 million in 2013), and their poverty rate fell from 21.3% in 2012 to 19.5% in 2013. The 2013 child poverty rate is still well above its pre-recession low of 16.9% (2006). Child poverty appears to be especially sensitive to economic cycles, as it often takes two working parents to support a family, and a loss of work by one may put the family at risk of falling into poverty. Moreover, roughly one-third of all 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 Census Bureau's poverty thresholds form the basis for statistical estimates of poverty in the United States. 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. 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 measure 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 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. 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 "). 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. The incidence of poverty among African Americans and Hispanics exceeds that of whites by several times. In 2013, 27.2% of blacks (11.0 million) and 23.5% of Hispanics (12.7 million) had incomes below poverty, compared to 9.6% of non-Hispanic whites (18.8 million) and 10.5% of Asians (1.8 million). Although blacks represent only 13.0% of the total population, they make up 24.4% of the poor population; Hispanics, who represent 17.3% of the population, account for 28.1% of the poor. Poverty rates for Hispanics fell from 25.6% in 2012 to 23.5% in 2013, as did the number of poor Hispanics, from 13.6 million in 2012, to 12.7 million in 2013. Poverty rates and the numbers estimated as poor were statistically unchanged from 2012 to 2013 for white non-Hispanics, blacks, and Asians. 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). 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 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 .) Adults with low education, those who are unemployed, or those who have a work-related disability are especially prone to poverty. Among 25- to 34-year-olds without a high school diploma, between one-third and two-fifths (36.8%) were poor in 2013. In 2013, 1 in 10 25- to 34-year-olds lacked a high school diploma. Within the same age group whose highest level of educational attainment was a high school diploma, about one in five (20.7%) were poor. In contrast, only about 1 in 16 (6.5%) of 25- to 34-year-olds with at least a bachelor's degree were found to be living below the poverty line. Among persons between the ages of 16 and 64 who were unemployed in March 2014, nearly 3 out of 10 (29.8%) were poor based on their families' incomes in 2013; among those who were employed, 6.9% were poor. In 2013, persons who had a work disability 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 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. 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." In 2013, nearly three of every four poor persons (73.8%) lived in households that received any means-tested assistance during the year. 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. 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 poverty. Among the poor, the likelihood of living in an area of concentrated or extreme poverty varies by race and ethnicity. 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. 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. 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 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 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 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. 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. Table 1 provides estimates of state and national poverty rates from 2002 through 2013 from the ACS. Statistically significant changes from one year to the next are indicated by an upward-pointing arrow (▲) if a state's poverty rate was statistically higher, and by a downward-pointing arrow (▼) if statistically lower, than in the immediately preceding year or for other selected periods (i.e., 2005 vs. 2002, 2013 vs. 2007). 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. 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 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. 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 . 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. 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. On October 16, 2014, the Census Bureau released its fourth annual report using a new Supplemental Poverty Measure (SPM). 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. 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 M easuring Poverty: A New Approach . In late 2009, the Office of Management and Budget (OMB) formed an Interagency Technical Working Group (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, 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." 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 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 individu als' poverty status, devised in the early 1960s, have changed little since . Except for minor technical changes and adjustments for price inflation, poverty income thresholds have essentially been frozen in time, reflecting living standards of a half-century ago. The "official" poverty measure does not take into account necessary work-related expenses, such as child care and transportation costs that are associated with getting to work. Child care expenses are much more common today than when the "official" poverty measure was originally developed, as mothers' labor force participation has since increased. The "official" poverty measure does not take into account medical expenses that individuals and families may incur , affecting their ability to meet other basic needs. These costs, which tend to vary by age, health status, and insurance coverage of individuals, may differentially affect families' abilities to meet other basic needs, especially given rising health care costs. The "official" poverty measure does not take into account changing family situations, such as cohabitation among unmarried couples, or child support payments. The "official" poverty measure does not adjust for differences in prices across geographic areas, which may affect the cost of living from one area to another. The ITWG, using the NAS-panel recommendations as a starting point, suggested an approach to developing the SPM that addressed how income thresholds should be set and resources counted in measuring poverty. Conceptual differences between the "official" and supplemental poverty measures are summarized in Table 6 . 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 (30 th to 36 th 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. 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. 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 30 th and 36 th percentile of what such units spend on FCSU, averaged over five years of survey data from the BLS Consumer Expenditure (CE) Survey. 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). 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 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. 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 Service, such as the Earned Income Tax Credit (EITC) and the partially refundable portion of the Child Tax Credit (CTC), known as the Additional Child Tax Credit (ACTC). The SPM subtracts a number of necessary expenses from SPM units' resources to arrive at a measure of "disposable" income that units might have available to meet basic needs. Necessary expenses subtracted from resources on the SPM include child support paid; estimated federal, state, and local income taxes; estimated social security payroll (FICA) taxes; estimated work-related expenses other than child care (e.g., work-related commuting costs, purchase of uniforms or tools required for work); reported work-related child care expenses; and reported medical out of pocket (MOOP) expenses, including the employee share of health insurance premiums plus other medically necessary items such as prescription drugs and doctor copayments. The effects of counting each of these resources and expenses in the SPM are assessed later in this report (see " Marginal Effects of Counting Specified Resources and Expenses on Poverty under the SPM "). 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. 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. 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. 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. The SPM expands the economic unit used for poverty determination beyond that used by the "official" measure. The SPM assesses the relationship of unrelated household members to others in the household to determine whether they will be joined with others to construct expanded economic units. For example, the SPM combines unrelated co-residing household members age 14 and older who are not married and who identify each other as boyfriend, girlfriend, or partner as cohabiting partners. Cohabiting partners, as well as any of their co-resident family members, are combined as an economic unit under the SPM. The SPM also combines unmarried co-residing parents of a child living in the household as an economic unit, even if the parents do not identify as a cohabiting couple. Any unrelated children who are under age 15 and are not foster children are assigned to the householder's economic unit, as are foster children under the age of 22. Additionally, the SPM combines children over age 18 living in a household with a parent, and any younger children of the parent, as an economic unit. Under the "official" poverty measure, a child age 18 and over is treated as an unrelated individual, and the child's parent is also treated as an unrelated individual if no other family members are present, or as an unrelated subfamily head if a spouse or other children (under age 18) are also residing in the household. In 2013, an estimated 27.953 million persons, 8.9% of the 313.395 million persons represented in the CPS/ASEC, were classified as either joining an economic unit or having members added to their economic unit under the SPM measure, compared to how they would have been classified under the "official" measure's economic unit definition. Combining the resources of these additional household members had the effect of reducing poverty under the SPM measure, compared to the "official" measure, in 2013. Figure 10 shows poverty rates in 2013 by type of economic unit. Persons identified as being in a married-couple unit, or in female- or male-householder units, are persons in those economic units whose members remained unchanged under the SPM compared to the "official" poverty measure. Persons who were added to an economic unit, or were part of an economic unit that had members added to it under the SPM definition, are labeled as being in a "new SPM unit." The figure shows that poverty rates for persons in married-couple units, and in male-householder units, are higher under the SPM than under the "official" poverty measure (9.5% versus 6.7% for persons in married-couple units, and 23.1% versus 18.7% for persons in male-householder units). Poverty rates for persons living in female-householder units did not statistically differ from one another, with about three out of ten persons in such units considered poor under either measure. In contrast, poverty among persons who were members of "new SPM units" fell by about two-fifths, from 31.4% under the "official" measure to 17.9% under the SPM. 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. Figure 12 depicts poverty rates by residence in metropolitan (principal city, and outside principal city [i.e., "suburban"]) and nonmetropolitan areas in 2013. 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. Figure 13 depicts states according to whether the state's SPM poverty rate statistically differs from its "official" poverty rate. 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 their respective "official" poverty rates, nearly all (with Maine being the exception) were either in the South, or inland. 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 difference between a state's official poverty rate and its SPM poverty rate is signified 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%). 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. 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-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. As a research measure, the SPM offers potential for improved insight leading to better understanding of the nature and circumstances of those deemed to be among the nation's most economically and socially vulnerable. The SPM offers the means to better assess the performance of the economy, government policies, and programs with regard to the population's ability to secure sufficient income/resources to be able to meet basic expenditures for food, clothing, shelter, and utilities (plus "a little bit more"). The SPM counts considerably more elderly as poor than does the "official" measure. Medical expenses appear to be the driving factor in increasing poverty among the elderly under the SPM (see Figure 16 ). While not negating the improvement in the poverty status of the aged over the years, based on the "official" measure (see Figure 2 ), the SPM points more directly to the economic vulnerability of the aged, based not on income/resources alone, but rather, medical expenses competing for income that might otherwise be used to meet basic needs (i.e., FCSU plus "a little bit more"). Rising medical costs in society overall and individuals' personal health and insurance statuses pose potential economic risk to the aged being able to meet basic needs, as captured by FCSU-based poverty thresholds. The SPM provides additional insight that poverty reduction among the elderly depends not only on improving income, but also on their ability to reduce exposure to high medical expenses through "affordable" insurance. Rising medical costs in society also place the aged at increased risk of poverty under the SPM. It is worth noting that the SPM does not consider financial assets, other than interest, dividends, and annuity income from those assets, nor non-liquid assets (e.g., home equity) in determining poverty status. The SPM therefore does not address the means or extent to which the aged might tap those assets to meet medical or other needs. The SPM results in fewer children being counted as poor than under the "official" measure. Still, the incidence of child poverty under the SPM, as under the "official" measure, exceeds that of the aged, but by a much slimmer margin (see Figure 9 ). Work-based supports, which both encourage work and help to offset the costs of going to work, appear be especially important to families with children, as captured by the SPM. The EITC, not counted under the "official" measure, significantly reduces child poverty as measured by the SPM, helping to offset taxes and work-related expenses working families with children incur (also captured by the SPM, but not under the "official" measure) (see Figure 16 ). The lack of safe, reliable, and affordable child care may limit parents' attachment to the labor force, contributing to poverty by reducing earnings that parents might otherwise secure. The SPM recognizes child care as a necessary expense many families face in their decisions relating to work by subtracting work-related child care expenses from income/resources that might otherwise go to meeting basic needs (i.e., FCSU plus "a little bit more"). As a consequence, the SPM should be sensitive to measuring the effects of child care programs and policies on child care affordability and poverty. The SPM captures the policy effects of assisting the poor through the provision of in-kind benefits, as opposed to just cash, whereas the "official" measure does not. For example, SNAP benefits, not captured under the "official" poverty measure, appear to have a sizeable effect in reducing child poverty under the SPM. Additionally, the expansion of the economic unit under the SPM to include cohabiting partners and their relatives may also contribute to lower child poverty rates under the SPM than under the "official" poverty measure, which is based on family ties defined by blood, marriage, and adoption. Appendix A. U.S. Poverty Statistics: 1959-2013 Appendix B. Metropolitan Area Poverty Estimates Appendix C. Poverty Estimates by Congressional District
summary: In 2013, 45.3 million people were counted as poor in the United States under the official poverty measure—a number statistically unchanged from the 46.5 million people estimated as poor in 2012. The poverty rate, or percent of the population considered poor under the official definition, was reported at 14.5% in 2013, a statistically significant drop from the estimated 15.0% in 2012. Poverty in the United States increased markedly over the 2007-2010 period, in tandem with the economic recession (officially marked as running from December 2007 to June 2009), and remained unchanged at a post-recession high for three years (15.1% in 2010, and 15.0% in both 2011 and 2012). The 2013 poverty rate of 14.5% remains above a 2006 pre-recession low of 12.3%, and well above an historic low rate of 11.3% attained in 2000 (a rate statistically tied with a previous low of 11.1% in 1973). The incidence of poverty varies widely across the population according to age, education, labor force attachment, family living arrangements, and area of residence, among other factors. Under the official poverty definition, an average family of four was considered poor in 2013 if its pre-tax cash income for the year was below $23,834. The measure of poverty currently in use was developed some 50 years ago, and was adopted as the "official" U.S. statistical measure of poverty in 1969. Except for minor technical changes, and adjustments for price changes in the economy, the "poverty line" (i.e., the income thresholds by which families or individuals with incomes that fall below are deemed to be poor) is the same as that developed nearly a half century ago, reflecting a notion of economic need based on living standards that prevailed in the mid-1950s. Moreover, poverty as it is currently measured only counts families' and individuals' pre-tax money income against the poverty line in determining whether or not they are poor. In-kind benefits, such as benefits under the Supplemental Nutrition Assistance Program (SNAP, formerly named the Food Stamp program) and housing assistance, are not accounted for under the "official" poverty definition, nor are the effects of taxes or tax credits, such as the Earned Income Tax Credit (EITC) or Child Tax Credit (CTC). In this sense, the "official" measure fails to capture the effects of a variety of programs and policies specifically designed to address income poverty. A congressionally commissioned study conducted by a National Academy of Sciences (NAS) panel of experts recommended, some 20 years ago, that a new U.S. poverty measure be developed, offering a number of specific recommendations. The Census Bureau, in partnership with the Bureau of Labor Statistics (BLS), has developed a Supplemental Poverty Measure (SPM) designed to implement many of the NAS panel recommendations. The SPM is to be considered a "research" measure, to supplement the "official" poverty measure. Guided by new research, the Census Bureau and BLS intend to improve the SPM over time. The "official" statistical poverty measure will continue to be used by programs that use it as the basis for allocating funds under formula and matching grant programs. The Department of Health and Human Services (HHS) will continue to issue poverty income guidelines derived from "official" Census Bureau poverty thresholds. HHS poverty guidelines are used in determining individual and family income eligibility under a number of federal and state programs. Estimates from the SPM differ from the "official" poverty measure and are presented in a final section of this report.