Chart notes | Poverty

Tables

Table 7.1. Comparison of poverty measures. Table is adapted from Short (2011), “Resource Estimates” table.

Table 7.2. Contribution of hours versus hourly wages to annual wage growth for working-age households, selected years, 1979–2007. See note to Table 2.16.

Table 7.3. Impact of changes in U.S. economic and demographic composition on the poverty rate, selected periods, 1979–2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement microdata; see Appendix A for details. The methodology for this decomposition is taken from Danziger and Gottschalk (1995, Chapter 5), which explores the role of changes in socioeconomic characteristics (e.g., changes in average income, changes in income inequality, and demographic changes such as the change in racial groups’ shares of the overall population) on the poverty rate (using the official poverty rate) between any two years. We focus specifically on the 1979–1989, 1989–2000, 2000–2007, 2007–2010, and 1979–2007 periods. To examine the impact of average income of the U.S. population on the poverty rate, we assign the average real income growth across the period to be the growth for all individuals between years t0 and t1 and simulate a new poverty rate. This procedure holds the shape of the distribution (inequality) constant in t0 while allowing incomes to grow equally for all individuals. This simulated poverty rate for t1 is then compared to the actual poverty rate in year t0, and the percentage-point difference is the change in the mean, i.e. the impact of income growth. The change due to income inequality is the percentage-point difference between the simulated poverty distribution in t1 and the actual poverty rate in t1.

We repeat this exercise using the demographic composition of each variable of interest to see the effect of these demographic changes on the overall poverty rate. First we calculate the weight of each demographic factor (such as individuals with college degrees) by its population share and simulate the poverty rate in t1 for all persons between t0 and t1, allowing for income to grow equally among all families and holding the demographic composition of the population in t0 constant. Then, we calculate a second simulated rate that incorporates both the mean income growth and the demographic changes across the period. The difference between these two simulated rates in t1 is the percentage point-change in the poverty rate due to demographic changes.

The interaction, or error, term states to what degree the demographic variables are conflated, which could lead to bias in measurement of a factor’s impact. Since our error term is negative and relatively small (.4 from 1979–2007), the reported relationship might slightly overstate the degree to which the simulated income decreases the poverty rate for each demographic group, but it is not enough to change the story.

Figures

Figure 7A. Poverty and twice-poverty rates, 1959–2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables, Table 2, “Poverty Status, by Family Relationship, Race, and Hispanic Origin,” and Table 5, “Percent of People by Ratio of Income to Poverty Level.”

Figure 7B. Poverty rate, by age, 1959–2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables, Table 3, “Poverty Status, by Age, Race, and Hispanic Origin” and Current Population Survey Annual Social and Economic Supplement microdata (see Appendix A for details).

Figure 7C. Poverty rate, by race and ethnicity, nativity, and citizenship status, 1973–2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables, Table 2, “Poverty Status, by Family Relationship, Race, and Hispanic Origin” and Table 23, “People in Poverty by Nativity.” As with most other CPS data analyses presented in the book, race/ethnicity categories are mutually exclusive (i.e., white non-Hispanic, black non-Hispanic, and Hispanic any race).

Figure 7D. Poverty rate, by race and ethnicity and age, 2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement (CPS-ASEC) Historical Poverty Tables, Table 3, “Poverty Status, by Age, Race, and Hispanic Origin” and from CPS-ASEC microdata; see Appendix A for details. As with most other CPS data analyses presented in the book, race/ethnicity categories are mutually exclusive (i.e. white non-Hispanic, black non-Hispanic, and Hispanic any race).

Figure 7E. Poverty rates of various types of families, 1959–2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables, Table 4, “Poverty Status, by Type of Family, Presence of Related Children, Race and Hispanic Origin.”

Figure 7F. Length of time in poverty over a two-year period, 2008–2009. Underlying data are from Survey of Income and Program Participation microdata (2008 panel).

Figure 7G. Share of the poor in “deep poverty,” 1975–2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables, Table 2, “Poverty Status, by Family Relationship, Race, and Hispanic Origin,” and Table 22, “Number of People Below 50 Percent of Poverty Level.”

Figure 7H. Poverty rate, official and under the Supplemental Poverty Measure, by age group, 2010. Underlying data are from the U.S. Census Bureau’s Current Population Reports (Short 2011), Table 1, “Number and Percent of People in Poverty by Different Poverty Measures: 2010.”

Figure 7I. Official and relative poverty rate, 1979–2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables, Table 2, “Poverty Status, by Family Relationship, Race, and Hispanic Origin,” and Current Population Survey Annual Social and Economic Supplement microdata; see Appendix A for details. To be consistent with international comparisons, median income includes noncash transfers such as food stamps and housing subsidies.

Figure 7J. Demographic characteristics of poverty-level-wage workers vs. non-poverty-level-wage workers, 2011. Underlying data are from Current Population Survey Outgoing Rotation Groups microdata; see Appendix B for details. As with most other CPS microdata analyses presented in the book, race/ethnicity categories are mutually exclusive (i.e. white non-Hispanic, black non-Hispanic, and Hispanic any race).

Figure 7K. Industry, occupation, and union status of poverty-level-wage workers vs. non-poverty-level-wage workers, 2011. Underlying data are from Current Population Survey Outgoing Rotation Groups microdata; see Appendix B for details. Occupations do not sum to 100 percent because the figure excludes the “Other Occupations” category, which constitutes less than 2 percent of the workforce.

Figure 7L. Share of poverty-level-wage and non-poverty-level-wage workers with employer-sponsored health insurance and pension coverage, 2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement microdata; see Appendix A for details. The analysis includes workers in both the private and public sectors and does not have age limits or work requirements. Coverage is defined as being included in an employer-sponsored plan for which the employer paid for at least some of the coverage.

Figure 7M. Poverty rate, actual and simulated, 1959–2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables, Table 2, “Poverty Status, by Family Relationship, Race, and Hispanic Origin,” and Table 4, “Poverty Status, by Type of Family, Presence of Related Children, Race and Hispanic Origin,” and from Bureau of Economic Analysis National Income Product Accounts public data, Table 7.1, “Selected Per Capita Product and Income Series in Current and Chained Dollars.” The analysis is an adaptation of analysis by Danziger and Gottschalk (1995), whose method was to regress the poverty rate of the growth of real per capita gross domestic product from 1959–1973 and then simulate poverty rates based on that simple model. The link between GDP and poverty in the earlier period (1959–1973) and the potential for GDP to eradicate poverty by the 1980s holds true for alternative specifications including using only the under-age-65 poverty rate (to remove elderly, the main recipients of Social Security, also growing over this period) and controlling for one target demographic: female headed families.

Figure 7N. Change in productivity, 20th-percentile wages, unemployment, and poverty, selected periods, 1979–2010. Productivity data, which measure output per hour, are from the Bureau of Labor Statistics Major Sector Productivity and Costs Index public data series; the figure shows the average annual growth rate of productivity over the periods covered. The figure also shows the average annual growth rate of wages at the 20th percentile of the wage distribution for the given periods, using data from Current Population Survey Outgoing Rotations Group microdata; see Appendix B for details. The percentage-point changes in the unemployment rate across the periods shown come from the monthly Current Population Survey public data series, while percentage-point changes in the poverty rate come from Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables, Table 2, “Poverty Status, by Family Relationship, Race, and Hispanic Origin.”

Figure 7O. Increase in wages from a 1-percentage-point decline in the unemployment rate, by gender. Estimates use Current Population Survey Outgoing Rotation Group microdata (see Appendix B), and are computed based on a model employed by Katz and Krueger (1999). Annual changes in log wages are regressed on unemployment, lagged log-changes in the CPI-U-RS (but, following Katz and Krueger the coefficient on this is constrained to equal 1), lagged productivity growth, and dummies for 1989–1995, 1996–2000, and 2001–2007 (excluded period is 1979–1988). The sample covers the years 1979–2007.

Figure 7P. Impact of changes in family structure on the poverty rate, selected periods, 1979–2010. The figure looks at the overall composition of family structure in the United States (e.g., the share of families headed by a single mother) and measures how much the change in the composition has affected the poverty rate in given periods. For more information on the methodology underlying the figure, see the note to Table 7.3.

Figure 7Q. Impact of changes in U.S. economic and demographic composition on the poverty rate, 1979–2007. See note to Table 7.3.

Figure 7R. Per capita Social Security expenditures and the elderly poverty rate, 1959–2010. Underlying data are from Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables, Table 2, “Poverty Status, by Family Relationship, Race, and Hispanic Origin,” and Table 3, “Poverty Status, by Age, Race, and Hispanic Origin.” Data are also from the Social Security Administration Trustees Report 2009: Annual Statistical Supplement, Table 4a, “Old-Age and Survivors Insurance Trust Fund Expenditures”

Figure 7S. Poverty rate absent targeted government programs, by age group, 2010. Underlying data are from Short (2011), Table 3a, “Effect of Excluding Individual Elements on SPM Rates: 2010.”

Figure 7T. Share of bottom-fifth household income accounted for by wages, cash transfers, and in-kind income, 1979–2007. Underlying data are from the 2010 Congressional Budget Office, Average Federal Taxes by Income Group, “Sources of Income for all Households, by Household Income Category, 1979–2007” [Excel spreadsheet]. The Congressional Budget Office definition of in-kind income includes employer-paid health insurance premiums, food stamps, school lunches and breakfasts, housing assistance, energy assistance, and the fungible value of Medicare and Medicaid, as estimated by the Current Population Survey. CBO’s definition of cash transfers includes payments from Social Security, unemployment insurance, Supplemental Security Income, Aid to Families with Dependent Children, Temporary Assistance for Needy Families, veterans’ benefits, and workers’ compensation.

Figure 7U. Earnings at the 10th percentile as a share of median worker earnings in selected OECD countries, late 2000s. Underlying data are metadata from the Organisation for Economic Co-operation and Development’s Distribution of Gross Earnings of Full-time Employees and Gender Wage Gap database. Earnings for all countries are defined as gross earnings for full-time, full-year workers, with the exception of Denmark, which is for all workers, the Netherlands, which is for full time, full-year equivalent workers, and Switzerland, which is net earnings for full-time workers. The shares are earnings at the 10th percentile as a share of the median earnings in each country’s respective currency.

Figure 7V. Earnings at the 10th percentile in selected OECD countries relative to the United States, late 2000s. Underlying data are metadata from the Organisation of Economic Co-operation and Development’s Distribution of Gross Earnings of Full-time Employees and Gender Wage Gap database. See note for Figure 7U on definition of earnings. Data for earnings at the 10th percentile are converted into weekly earnings and are then converted into equivalent U.S. dollars using a purchasing power parity index from the International Monetary Fund World Economic Outlook Database. The figure shows the share of each country’s 10th percentile earnings relative to the 10th percentile earnings in the United States.

Figure 7W. Relative poverty rate in the United States and selected OECD countries, late 2000s. Underlying data are from the Organisation for Economic Co-operation and Development’s Stat Extracts public data series. Household-size-adjusted income, or equivalent income, is household income divided by the square root of the household size. Countries were chosen based on their productivity per worker hour using the “PPP Converted GDP Laspeyres Per Hour Worked by Employees at 2005 Constant Prices” series from Penn World Table Version 7.0 (Heston, Summers, and Aten 2011). We chose to exclude countries whose productivity is less than half that of the United States. The OECD data base uses slightly different methods than that found in 7I (e.g., its handling of taxes and transfers are different), therefore, the relative rates for the United States are not exactly the same.

Figure 7X. Child poverty rate in selected developed countries, 2009. Underlying data are from UNICEF Innocenti Research Centre Report Card 10 (Adamson 2012), Figure 1b, “Child Poverty Rate.” The poverty rate is the percentage of children (age 0–17) living in households with equivalent income lower than 50 percent of the national median, where equivalent income is disposable income, adjusted for family size and composition. UNICEF uses a modified equivalence scale to adjust for household size by weighting the first adult in the household by 1, the subsequent adults by .5, and children under age 14 by .3, then summing the weights up and dividing total household income by the total weight. We chose countries based on their productivity per worker hour using the “PPP Converted GDP Laspeyres Per Hour Worked by Employees at 2005 Constant Prices” series from Penn World Table Version 7.0 (Heston, Summers, and Aten 2011) and excluded countries whose productivity is less than half that of the United States.

Figure 7Y. Child poverty gap in selected developed countries, 2009. Underlying data are from UNICEF Innocenti Research Centre Report Card 10 (Adamson 2012), Figure 7, “The Poverty Gap.” The child poverty gap is the distance between the poverty line and the median family income of children below the poverty line, expressed as a percentage of the poverty line. This is calculated by lining up all individuals in households by household-size-adjusted income (with children taking their family income value) and then locating the poverty line, which is 50 percent of national median income. UNICEF uses a modified equivalence scale to adjust for household size by weighting the first adult in the household by 1, the subsequent adults by .5, and children under age 14 by .3, then summing the weights up and dividing total household income by the total weight. The median income of children below the poverty line is then calculated. Then the gap between the poverty line and the median income of children is then taken as a share of the poverty line. For example, for a country with a median income of $50,000, the poverty line is $25,000. If the median income for children living below $25,000 is $15,000, the difference is $25,000$15,000 = $10,000. This difference, taken as a share of the poverty line, yields a child poverty gap of $10,000/$25,000 (40 percent). We chose countries from the UNICEF list based on their productivity per worker hour using the “PPP Converted GDP Laspeyres Per Hour Worked by Employees at 2005 Constant Prices” series from Penn World Table Version 7.0 (Heston, Summers, and Aten 2011), and excluded countries whose productivity is less than half that of the United States.

Figure 7Z. Extent to which taxes and transfer programs reduce the relative poverty rate, selected developed OECD countries, late 2000s. Underlying data are from the Organisation for Economic Co-operation and Development’s Stat Extracts public data series. Household-size-adjusted income, or equivalent income, is household income divided by the square root of the household size. We chose countries based on their productivity per worker hour using the “PPP Converted GDP Laspeyres Per Hour Worked by Employees at 2005 Constant Prices” series from Penn World Table Version 7.0 (Heston, Summers, and Aten 2011), and excluded countries whose productivity is less than half that of the United States.

Figure 7AA. Social expenditure and relative poverty rates selected in OECD countries, late 2000s. Underlying data are from the Organisation for Economic Co-operation and Development’s Stat Extracts public data series. The relative poverty rate is the share of individuals living in households with income below half of household-size-adjusted median income, which is household income divided by the square root of the household size. We chose countries based on their productivity per worker hour using the “PPP Converted GDP Laspeyres Per Hour Worked by Employees at 2005 Constant Prices” series from the Penn World Table Version 7.0 (Heston, Summers, and Aten 2011), and excluded countries whose productivity is less than half that of the United States.

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