PPA786: Urban Policy Class 14: Poverty: Concepts and Evidence.

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PPA786: Urban Policy Class 14: Poverty: Concepts and Evidence

Transcript of PPA786: Urban Policy Class 14: Poverty: Concepts and Evidence.

PPA786: Urban PolicyClass 14:Poverty: Concepts and Evidence

PPA786, Class 14: Poverty

•Class Outline

▫Poverty Concepts

▫The Extent of Poverty

▫Weaknesses in Current Poverty Measures

Note: Much of the material for this lecture comes from Census and HHS websites.

▫Poverty and Inequality

PPA786, Class 14: Poverty

•Approaches to Measuring Family Poverty

▫Absolute poverty

Not enough income to meet a “reasonable” or “minimally decent” standard of living.

The approach used in the U.S.

▫Relative poverty

Low income relative to others, usually the median

Used in most international comparisons

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Relative versus Absolute Poverty

Household Income

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Absolute Poverty Line

Half of Teal Median

Half of Blue Median

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•Other Dimensions of Poverty

▫Poverty and Inequality

Poverty measures focus on the bottom of the income distribution

Measures of inequality summarize the entire distribution and need not be correlated with poverty

▫Poverty Spells

Like many other social phenomena, poverty can be measured with a snapshot or as a flow

Poverty lines are snapshots; we will also look at flows

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•History of the U.S. Poverty Thresholds

▫ The poverty thresholds were devised by Mollie Orshansky and first published in 1965.

She started with the Department of Agriculture’s “economy food plan,” which provided a nutritionally adequate diet “for temporary or emergency use when funds are low.”

She combined this with a finding from the DoA’s 1955 Household Food Consumption Survey that families of 3 or more people spent about 1/3 of their after-tax money income on food.

So: poverty threshold = 3 × cost of the economy food plan.

▫ Orshansky differentiated her thresholds by family size, by farm/nonfarm status, by the sex of the family head, by the number of family members who were children, and (for one- and two-person units only) by aged/non-aged status. 

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•History of the U.S. Poverty Line, Continued

▫ In 1969, Bureau of the Budget (the predecessor of the Office of Management and Budget) decided to index the thresholds by the Consumer Price Index and to set the farm poverty thresholds at 85 percent rather than 70 percent of corresponding nonfarm thresholds. 

▫ In 1981, the distinctions between farm and nonfarm thresholds and between “female-headed” and “male-headed” thresholds were eliminated.

▫The poverty thresholds are simplified by HHS into poverty guidelines for determining program eligibility.

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Poverty Thresholds for 2013 by Size of Family and Number of Related Children Under 18 Years  Related children under 18 years Size of family unit None One Two Three Four Five Six Seven ≥ Eight

One person (unrelated individual).                   Under 65 years.................. 12,119               

65 years and over.............. 11,173               Two people.........................                  

Householder under 65 years......... 15,600 16,057             

Householder 65 years and over. 14,081 15,996             

Three people...................... 18,222 18,751 18,769           

Four people........................ 24,028 24,421 23,624 23,707         

Five people....................... 28,977 29,398 28,498 27,801 27,376       

Six people....................... 33,329 33,461 32,771 32,110 31,128 30,545     

Seven people....................... 38,349 38,588 37,763 37,187 36,115 34,865 33,493   

Eight people...................... 42,890 43,269 42,490 41,807 40,839 39,610 38,331 38,006 

Nine people or more.......…… 51,594 51,844 51,154 50,575 49,625 48,317 47,134 46,842 45,037Source: U.S. Census Bureau.                  

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2014 HHS Poverty Guidelines

Persons in Family or Household Mainland U.S. Alaska Hawaii

1 $11,670 $14,580 $13,4202 $15,730 $19,660 $18,0903 $19,790 $24,760 $22,7604 $23,850 $29,820 $27.4305 $27,910 $34,900 $33,1006 $31,970 $39.980 $36,7707 $36,030 $45.060 $41,4408 $40,090 $50,140 $46,110

For each additional person, add $4,060 $5,808 $4,670

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•Poverty Guidelines and Program Eligibility

▫ HHS: Community Services Block Grant, Head Start, Low-Income Home Energy Assistance, Children's Health Insurance Program

▫ Department of Agriculture: Food Stamps (now SNAP), Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), the National School Lunch and School Breakfast programs

▫ Department of Energy: Weatherization Assistance

▫ Department of Labor: Job Corps, Senior Community Service Employment Program, National Farmworker Jobs Program

▫ Legal Services Corporation: Legal services for the poor

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•Poverty Guidelines and Program Eligibility, Cont.

▫ Certain recent provisions of Medicaid use the poverty guidelines, but most of the program does not.

▫ Major means-tested programs that do NOT use the poverty guidelines for eligibility include Temporary Assistance for Needy Families, Supplemental Security Income, the Earned Income Tax Credit, HUD’s means-tested housing assistance programs, and the Social Services Block Grant.

▫ Some state and local governments use the federal poverty

guidelines in some of their own programs.

Examples include state health insurance programs, financial guidelines for child support enforcement, and determination of legal indigence for court purposes.

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•Extent of Poverty in the U.S. (Census)

▫The official poverty rate in 2012 was 15.0% (versus 15.1 in 2010), and 46.5 million people were in poverty.

▫Poverty rates in 2012 were 12.7% for non-Hispanic Whites, 27.2% for Blacks, 25.6% for Hispanics, and 11.7% for Asians—all down slightly from 2011.

▫The poverty rate for children under 18 years old was 21.8% and the rate for the elderly was 9.1%.

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PPA786, Class 14: Poverty

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1972 1976 1980 1984 1988 1992 1996 2000 2004 2008 20120

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Poverty Rates, 1973-2012

White Black Hispanic

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•Dynamics of Poverty, 2004 to 2006 (Census)

▫About 28.9% of people were poor for at least 2 months between 2004 and 2006, but only 2.8% were poor every month of the 3-year period.

▫Of those who were poor in 2004, 68.6% remained poor in 2005 and 58.4% were poor in 2006. Of those who were not poor in 2004, only 3.5% became poor in 2005 and 4.2% were poor in 2006.

▫Based on a monthly poverty measure, the median spell length in the 2004-2006 period was 4.5 months.

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PPA786, Class 14: Poverty

PPA786, Class 14: Poverty

Source: Smeeding (2008)

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•Weaknesses of the U.S. Poverty Line (NAS Panel)

▫ It excludes in-kind benefits, such as food stamps and housing assistance, when counting family income.

▫ It ignores the cost of earning income, including child care costs, when calculating the net income.

▫ It disregards regional variation in the cost of living (housing).

▫ It ignores direct tax payments, such as payroll and income taxes, when measuring family income.

▫ It ignores differences in health insurance coverage and medical care needs.

▫ It has never been updated to account for changing consumption patterns of U.S. households. For example, expenditures for food accounted for about one-third of family income in the 1950s, but they now account for as little as one-seventh.

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•Correcting the U.S. Poverty Line

▫Correcting for in-kind benefits, the costs of earning income, tax payments, and health/insurance does not have a large impact on the poverty rate, because their effects are offsetting.

▫Correcting for the declining share of food consumption would be a huge deal: Current poverty thresholds would have to be multiplied by 7/3!

▫Correcting for the higher cost of housing in urban areas would be a huge deal: Housing costs are many times higher in large cities than in rural areas.

▫That’s why the last two corrections, both of which make perfect sense, are unlikely to be implemented!

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•Metro vs. Nonmetro Poverty, Joliffe (2006)

▫ Adjusting poverty thresholds with a fair market rent (FMR) index results in a reversal of the nonmetro-metro poverty profile.

▫ With no adjustment for cost-of-living differences, the prevalence of poverty is higher in nonmetro areas than in metro areas over the last 12 years.

▫ When the FMR index is used to adjust for cost-of-living differences, the prevalence, depth, and severity of poverty are higher in metro areas than in nonmetro areas.

In 2001, for example, the prevalence of nonmetro poverty was 28% higher than in metro areas. Once adjusted for cost-of-living differences, this is reversed and the prevalence of poverty in nonmetro areas is 12% lower than in metro areas.

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P0=standard poverty measure; P1=poverty gap; P2=poverty gap squared.

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•Supplemental Poverty Measure (Census)

▫In response to these problems, the Census now calculates a Supplemental Poverty Measure that accounts for some of them.

▫The Census also continues to work on alternative measures that deal with even more of these problems.

▫The features of the new measure are outlined on the following slide.

PPA786, Class 14: Poverty

PPA786, Class 14: Poverty

PPA786, Class 14: Poverty

PPA786, Class 14: Poverty

PPA786, Class 14: Poverty

PPA786, Class 14: Poverty

•Material Hardship

▫We measure poverty primarily because it links to an issue of great interest to many: the quality of life experienced by our most disadvantaged citizens.

▫Another approach to this issue, covered in the Sullivan, Turner, Danziger reading is material hardship, defined as experiencing food insufficiency, utility shut-off, eviction, or homelessness.

▫Some of their analyses also consider experiencing a disconnected phone, a lack of winter clothing for a mother or her children, and the need for a doctor or dentist without the required funds or insurance.

PPA786, Class 14: Poverty

PPA786, Class 14: Poverty

• Determinants of Material Hardship

▫ Average disposable income over several years (not current income) is significantly related to hardship.

A 10 percent increase in average income is associated with a 1.1 percentage point decrease in the likelihood of experiencing any of four hardships—a drop of about 3.4 percent at the mean.

Thus, for a minimum wage worker, the receipt of the maximum EITC (a 40 percent earnings subsidy) on a permanent basis would be associated with a 16 percent reduction in the likelihood of hardship.

▫ Social programs might better target benefits at those facing the greatest risk of hardship by considering factors associated with low long-run income.

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• Predicting Material Hardship

▫ Other observable factors, such as meeting the diagnostic screening criteria for a mental health disorder, are strongly associated with the risk of hardship.

A woman meeting the screening criteria for a mental health disorder is more than 10 percentage points more likely to experience material hardship than others.

▫ According to S/T/D, welfare agencies, training programs, and service providers should consider gathering information on long-run income or mental health, in addition to information on current income.

This information could be used to predict hardship and to recommend associated treatment or prevention programs.

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•Inequality and Poverty

▫Increases in poverty are usually associated with increases in inequality, but these two concepts are not perfectly correlated.

▫Inequality is usually measured either by the ratio of incomes in a high percentile of the income distribution to incomes in a low percentile,

▫Or by a summary statistic called a Gini coefficient.

PPA786, Class 14: Poverty Measuring Inequality: The Gini Coefficient

Source: Wikipedia

PPA786, Class 14: Poverty

Author: Gorman

PPA786, Class 14: Poverty

PPA786, Class 14: Poverty Increase in Inequality (McCall & Percheski, Ann. Rev. of Sociology, 2010)

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Causes of Inequality (Pre-Recession)

• Heathcote, Perri, and Violante (J. Econ. Dynamics, 2010), found (pre-crash)

▫ “a large and steady increase in wage inequality between 1967 and 2006.

▫ Changes in the distribution of hours worked sharpen the rise in earnings inequality in the first half of the sample, but mitigate rising inequality in the second half.

▫ Taxes and transfers compress the level of income inequality, especially at the bottom of the distribution, but have little overall effect on the trend.

▫ Consumption data suggest that access to financial markets has reduced both the level and growth of economic inequality since 1980.”