Living Conditions of American Families

April 30, 1996


Maya Federman, Department of Economics, Harvard University*
Thesia I. Garner, Bureau of Labor Statistics
W. Boman Cutter IV, Department of Treasury*
John Kiely, National Center for Health Statistics
David Levine, Haas School of Business, University of California, Berkeley*
Duane McGough, Department of Housing and Urban Development
Marilyn McNillen, National Center for Education Statistics
Kathleen Short, Bureau of the Census
Forthcoming, Monthly Labor Review, 1996.


Acknowledgments:
Comments, statistical assistance, and direction from Richard Bavier and John Greenlees were integral to the project. Additional comments and statistical assistance were provided by Stacy Bondanella, Paul Burke, Barbara Hawkins, Tom Kane, Joanne Pascale, Anna Sanders, Beth Schlaline, Martina Shea, Stephanie Shipp, Toby Stickler, and Wolf Weber. All interpretations are the responsibility of the authors, and not their agencies.


* At the time this study prepared, Federman and Levine were at the Council of Economics. In addition, Cutter has since left the Department of Treasury and is currently serving in the Peace Corps.

Abstract
Related Research
Methods
Results
Income Sources
Income Sources Table
Spending Patterns
Spending Patterns Table
Housing
Housing Table
Consumer Durables and Utilities
Consumer Durables and Utilities Table
Crime and Neighborhood
Crime and Neighborhood Table
Health and Nutrition
Health and Nutrition Table
Education
Education Table
Overall Deprivation
Overall Deprivaiton Table
Discussion
Conclusions
Selected Bibliography
Appendix A: Description of Surveys
Appendix B: Poverty Rates Accross the Surveys
Poverty Rates Accross the Surveys Table
Notes


Living Conditions of American Families

Abstract: This paper analyzes a broad array of national surveys that shed light on the living conditions of American families, following a methodology that promotes comparability across surveys as much as possible. We focus our attention on the status of persons living in poor families, persons living in poor, single-parent families, and persons living in families receiving welfare, as these groups are most directly affected by welfare reform - a major issue in the current political environment. In most of the measures we discuss, individuals in these groups are significantly worse off than those in non-poor families. For example:
  • Average family incomes of the non-poor are about six times as large as for the poor
  • Seventy-one percent of the expenditures of the families of poor* individuals is for food, shelter, utilities, and apparel, compared to 46 percent for families of the non-poor. For those in poor, single-parent families, the share spent on these necessities is 80 percent.
  • Seventy-eight percent of the non-poor live in homes their families own, compared to 41 percent of the poor and 24 percent of those living in poor, single-parent families.
  • Those living in poor households are twice as likely to be victims of violent crimes (robbery, assault, and rape) as are the non-poor. Those is poor, single-parent families are more than three times as likely.
  • 13.5 out of every 1000 infants born to poor mothers and 14.6 out of every 1000 infants born to poor, single mothers die within their first year, compared to 8.3 per 1000 the non-poor.
  • Twenty-seven percent of the poor live in families that report two or more of the following: eviction in the past year, crowding (more than one person per room), having moderate or severe housing upkeep problems, having gas or electricity turned off in the past year, having the phone disconnected in the past year, not having enough food in the past four months, living without a refrigerator, living without a stove, and living without a telephone. Only 3 percent of the non-poor report two or more of these events.

* Here, poverty status is determined using expenditures rather than income

The level of income and the general material well-being of American families has been an issue of growing concern in national discussions. In particular, the ongoing welfare debate has focused attention on the living conditions of poor families, both in an absolute sense and relative to those of other families. To inform this debate, this paper summarizes results based on data from nine national surveys that shed light on the living conditions of individuals living in poor and non-poor families. In addition, by separating out results for individuals in both poor, single-parents families and families receiving welfare, we are able to better focus on those individuals most likely to be affected by welfare reform. Along most of the dimensions we discuss, the poor, especially those in single-parent families, are significantly worse off than the non-poor.

To understand the relationship between poverty and living conditions, a multi-faceted understanding of what it means to be poor is required. In one sense, the answer to the question "What does it mean to be poor?" is straightforward -- having cash incomes below the official poverty line for a given family size. In a broader sense, the living conditions of the poor are difficult to measure, both because annual cash income is only one factor related to living conditions, and because the poor are so heterogeneous. We have attempted to address both of these issues.

A primary difference between this study and earlier examinations of living conditions and the material well-being of American families is that we draw upon a broader set of household surveys and attempt to maximize uniformity in the definition of family types and poverty. This work represents a coordinated effort of representatives of various government agencies which produce and analyze data from nationally representative surveys. Our aim in this process has been to produce measurements of material well-being for an expanded set of dimensions, following a methodology that would promote comparability across surveys as much as possible.

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Related Research

Although the official poverty measure in the United States is defined in terms of current cash income, some aspects of economic welfare can be more accurately gauged by measuring consumption or other dimensions of living conditions. Income measures ignore home ownership and other assets that can be important sources of consumption. Thus, some people, such as those who are retired or those whose incomes are only temporarily low, may be classified as poor based on income but do not have low consumption. Furthermore, the official poverty rate based on income does not account for taxes or in-kind transfers such as Food Stamps or government-provided medical insurance, which improve living conditions without affecting official poverty status. The National Academy of Science Poverty Panel recently released a report recommending several changes to the official poverty measure including adjusting for taxes and transfers (Citro and Michael, 1995).

To address the limitations of basing the measure of poverty solely on cash income, Cutler and Katz (1992) compare poverty rates constructed using consumption expenditure data from the Consumer Expenditure Survey with the official poverty rates based on income from the Current Population Survey. They find that while the poverty rate is lower when measured using consumption data, trends in poverty rates measured by both income and expenditures are similar and both rose in the 1980s, particularly for the non-elderly.

Slesnick (1993) also finds that consumption expenditure-based poverty rates are lower than income-based measures. In contrast to Cutler and Katz, however, he finds no rising trend in expenditure poverty in the 1980s. Slesnick assumes the poverty line for female-headed families is only 62 percent of the poverty line for male-headed families of the same size. This assumption, coupled with the rising proportion of female-headed families, may be driving his results.

Others researchers (e.g., Rector 1992, Sherman 1994, Jargowsky 1995, Mayer and Jencks 1995, Passero 1996a and 1996b, and Lino 1996) have analyzed measures of specific dimensions of material and economic well-being such as housing, neighborhood quality, consumer durables, income sources, spending patterns, and health to study the living conditions of low income children and families.

Rector (1992) analyzes the 1989 American Housing Survey and finds that nearly 40 percent of all households with incomes below the poverty line own their own home, but that only 18% of poor, single-parent families are homeowners. The median value of homes owned by the poor is 58 percent of the median value of all homes owned in America. In addition, he finds that only 8 percent of poor households are overcrowded (defined as more than one person per room), and 53 percent of poor households have air conditioning.

A recent Children's Defense Fund report (Sherman, 1994) summarizes findings along a large number of dimensions of disparities in resources and outcomes between poor and non-poor children. The evidence ranges from analysis of national data sources to studies analyzing a specific state or community. Poor children have higher rates of various health problems, inferior housing, inferior schools, less access to computers and educational materials at home, inferior child care, higher rates of child abuse, higher rates of parental substance abuse, more frequent moves, more exposure to toxic chemicals and pollution, higher rates of lead poisoning, and other disadvantages.

Using data from the American Housing Survey, the Decennial Census, the Consumer Expenditure Survey, and the National Health Interview Survey, Mayer and Jencks (1995) examine trends in various measures of the material well-being of children from 1969 to 1989. They find that children in families in the lowest quintile of income made both absolute and relative gains over time across a variety of measures of housing quality. Low-income children are now less likely to live in crowded housing and more likely to have indoor plumbing, central heat, and major appliances such as air conditioners and dishwashers. In addition, they are now more likely to have seen a doctor in the preceding year. At the same time, low-income children are now less likely to live in households that own their own home or have access to an automobile, and are more likely to live in neighborhoods identified by their parents as having a crime problem.

Mayer and Jencks suggest that some of the improvement in housing conditions may have resulted from increases in the availability of modern housing for the low income as more affluent families moved out to the suburbs. Government programs may also have played a role in improving living conditions in some dimensions. For example, the proportion of low income children having access to a telephone grew during the 1970s when universal access was a government policy, but ceased growing during the 1980s when universal access declined as a policy priority. Finally, despite the gains experienced by low-income children, their measured living conditions remain significantly lower relative to other children's.

Using data from the 1992-94 Consumer Expenditure Survey, Passero (1996a) examines selected characteristics and spending patterns of poor families, defined as those reporting receipt of some type of welfare. (1) Seventy percent of poor families are female headed. Seventy-seven percent of poor families rent their place of residence, while only 18 percent own their homes. Half of poor homeowners have a mortgage, the others do not. In contrast, 65 percent of families who do not receive welfare are homeowners. In terms of spending patterns, Passero finds that 65 percent of total expenditures by poor families is allocated to food, shelter, utilities, and apparel while non-poor families report spending 45 percent of total expenditures on these commodities. Results on spending patterns for families receiving any type of public assistance are presented in Passero (1996b).

Lino (1996) examines income sources, spending patterns, and characteristics of poor households with have children under 18 years of age, using the 1990-92 Consumer Expenditure Survey. Lino applies a stricter definition of poverty than has generally been used by others. A household is poor if its before-tax income is below its official poverty threshold and its total expenditures are below its official poverty threshold. (2) He finds that a majority of these poor households are headed by single parents (51 percent) and that 97 percent of these are mothers. Food stamps is the most commonly reported source of income for these families. (69 percent of poor households reported income from this source). Fifty-four percent of these poor families report receiving wages or salaries, and 54 percent report receiving some type of public assistance. In addition, Lino finds that for those household heads who are unemployed, 65 percent report not working because they were taking care of family members and 18 percent report not working because of illness.

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Methods

To create a comprehensive picture of the living situations of families, we have analyzed nine nationally representative surveys: the American Housing Survey (AHS) 1993, the Consumer Expenditure Survey (CE) 1992-93, the Current Population Survey (CPS) October 1993 and March 1994, the High School and Beyond Survey (HS&B) 1992, the National Crime Victimization Survey (NCVS) 1992, the National Health Interview Survey (NHIS) 1993, the National Household Education Survey (NHES) 1993, the National Maternal and Infant Health Survey (NMIHS) 1988, and the Survey of Income and Program Participation - Extended Measures of Well Being topical module (SIPP) 1992. These surveys are described in Appendix A.

Results are presented for individuals living in both poor and non-poor families. Families are defined as including a household head or reference person and household members related to head by blood, marriage, or other legal arrangement. Thus, individuals living alone and unrelated individuals living in the household are not included. The one exception is the NCVS which tabulates results for all households, as data on families was not available.

The poor are defined as those individuals living in families whose incomes fall below the official poverty thresholds for their family type (3) , with the exception of the CE which uses family expenditures instead of income. In each survey, family income is defined as closely as possible to the definition of gross cash income used by the Census Bureau in calculating official poverty rates. Because of differences in the questions asked and in definition of income used, it is not possible to match income levels exactly across surveys. However, because poverty rates for individuals in each family type are similar across most of the surveys, any differences are likely to be minimal. (4)

We have chosen to tabulate all results on a person-weighted rather than family-weighted basis. (5) This is in contrast to the procedure followed in most of the previous research cited (e.g., Rector 1992, US Department of Labor 1995b, Lino 1996, and Passero 1996). In these other studies, averages across families rather than across individuals are produced when tabulating results by family characteristics of the poor and non-poor. In most cases, person weighted and family-weighted results are similar. Results from the AHS and SIPP differed only slightly when run with both person-weights and family-weights. For the CE and CPS, the use of person-weights lead to higher total family expenditures and income than those typically reported in official publications in which household weights are most often used.

We decided to use person-weights rather than family-weights for two reason. First, we use person-weights because we are concerned with the economic well-being of individuals. By giving equal weight to each person in a family, this approach counts all individuals in a population equally, regardless of the size of their family. Thus, our results are presented for the average person living in the family type identified in our analysis. Second, person-weighted results for surveys where the unit of data collection is the family (AHS, CE, CPS - income sources, taxes, and benefits, and SIPP) are more directly comparable to results from the surveys where the unit of data collection is the individual (CPS - education and health insurance, HS&B, NCVS, NHES, NHIS, and NMHIS). For example, we can compare the percent of poor individuals whose families have access to a washing machine to the percent of poor individuals who have private health insurance.

In addition to the results produced for poor and non-poor families, we also produce results for two sub-populations that are most relevant for welfare policy analysis: individuals in poor, single-parent families and individuals in families receiving welfare. Poor, single-parent families are defined as families who have incomes below their official poverty threshold and have an unmarried head of household and at least one child under age 18. (6) Families receiving welfare are defined as families with children that report receiving welfare assistance some time during the reference period. To allow for maximum comparability of results, the text usually focuses on poor, single-parent families because the definition of families receiving welfare varies across some surveys and is absent in others. (7) We have chosen to present tabulations for all families receiving welfare assistance rather than for poor families that receive assistance. It is not uncommon for families to receive welfare at some point over the reference period, even if they do not fall below the poverty line measured over the entire interval. For example, job loss or divorce could make a family eligible for welfare assistance at some point in the period, even if the average income over the whole period is above the poverty line. In addition, some programs have eligibility thresholds above the poverty line. Because results are similar for both groups, we present tabulations for only one. In those cases where results are substantially different, results for poor families receiving welfare are also noted.

We present percent distributions and mean income and expenditures for four categories of individuals living in families. These include people in non-poor families; people in poor families; people in poor, single-parent families; and people in families receiving welfare.

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Results

Results for poor and non-poor families are divided into seven categories: income sources, spending patterns, housing, consumer durables and utilities, crime and neighborhood, health and nutrition, and education. In the first four categories, the unit of analysis is the family; thus, family characteristics for the average individual in each family type are presented. For example, the family income of the average non-poor individual is $51,857. For the last two categories, the unit of analysis is the individual; thus, results are for the average individual of the relevant population: 27 percent of poor children age 5-7 years have fewer than 10 books. The crime and neighborhood category has measures of both family and individual characteristics. Finally, we present calculations of an index of deprivation for individuals that is comprised of several family characteristics.

Summary tables of all variables discussed in the text are provided for each category. The source for each variable is noted in tables. All differences discussed in the text are statistically significant at the 1% level. More extensive tables are presented at the end of the working paper.

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Income Sources

Poor families differ from non-poor families both in the level and source of their income. The average poor person lives in a family whose income is about a sixth as much as the family income of the average non-poor person ($8,401 versus $51,857). For the single-parent poor and those in families receiving welfare, average family incomes are $6,665 and $12,511. (8)

The average non-poor person lives in a family that receives 84 percent of its income from wages, salaries, and self-employment earnings, compared to 52 percent for the poor and only 37 percent for those in poor, single-parent families. For the poor, a larger proportion of family income comes from public assistance and welfare: 20 percent compared with only 0.2 percent for the non-poor. For those in poor, single-parent families, 39 percent of family income comes from public assistance and welfare.

Not surprisingly, poor families pay less taxes and receive more government transfers than do the non-poor. On average, the Earned Income Tax Credit (EITC) fully offsets the federal and state income and FICA payroll taxes for the family of the average poor person. Additional taxes, such as sales taxes, are not included in these calculations. The family of the average non-poor person pays an estimated $11,151 in federal and state income and FICA taxes (less the EITC). The average poor person lives in a family that receives $1,716 in public assistance and welfare and $1,367 in food stamps. For those in poor, single-parent families, welfare and food stamp transfers are $2,628 and $1,797 ($4,367 and $2,204 for families receiving welfare).

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Income Sources (1)

People in Non-poor Families People in Poor Families People in Poor, Single-Parent Families People in Families Receiving Welfare
CURRENT POPULATION SURVEY 1994
Total Income $51,857 $8,401 $6,665 $12,511
Wages and Salaries 78.5% 50.1% 36.3% 45.8%
Self Employment Earnings 5.7% 1.7% 0.6% 1.3%
Public Assistance/ Welfare 0.2% 20.4% 39.4% 34.9%
Federal Income Tax $6,384 $15 $6 $261
State Income Tax $1,798 $19 $7 $93
FICA Payroll Tax $3,087 $366 $186 $440
Earned Income Tax Credit ($118) ($484) ($358) ($322)
Public Assistance/Welfare $116 $1,716 $2,628 $4,367
Food Stamps $65 $1,367 $1,797 $2,204
1 family level data, person-weighted

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Spending Patterns

In this section, expenditure data from the Consumer Expenditure Survey (CE), in conjunction with the official poverty thresholds are used to determine if an individual is poor. Thus, individuals defined as poor using expenditure data may not necessarily have the same characteristics as individuals identified as income-poor in others sections of this paper. Poverty rates, measured using expenditure data, are generally lower than in the other surveys, though trends across family types are similar.

Differences in average family expenditures are smaller than differences in average family incomes between the poor and non-poor. While average family incomes of the non-income-poor are about six times as large as for the income-poor, average family expenditures of the non-expenditure-poor are only about three times as large as for the expenditure-poor ($36,926 versus $11,596). For the single-parent poor and those in families receiving welfare, average family expenditures are $9,172 and $16,280.2 (9)

Families also vary according to the composition of their spending. Not surprisingly, a greater share of total expenditures is allocated to purchasing items frequently classified as necessities: food, shelter, utilities, and apparel. Seventy-one percent of poor persons' family expenditures are spent on these necessities, compared to 46 percent for the non-poor. For those in expenditure-poor, single-parent families, an even larger share of total family expenditures, 80 percent, is spent on necessities.

Spending a larger share of total expenditures on necessities leaves a smaller portion for other items such as transportation, health care, personal insurance and pensions, and entertainment (including admissions to events, television, toys, and pets).

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SPENDING (1)

People in Non-poor Families People in Poor Families People in Poor, Single-Parent Families People in Families Receiving Welfare
CONSUMER EXPENDITURE INTERVIEW SURVEY 1992-93
Total Expenditures $36,926 $11,596 $9,172 $16,280
Food 15.6% 29.8% 34.3% 25.5%
Shelter 18.6% 22.3% 25.5% 24.0%
Utilities 6.9% 14.0% 13.7% 10.8%
Apparel 4.9% 5.1% 6.7% 6.0%
Transportation 20.1% 10.3% 6.4% 13.3%
Health care 5.4% 2.8% 1.2% 2.2%
Entertainment 5.4% 2.8% 2.8% 3.9%
Personal insurance and pensions 10.9% 5.4% 2.1% 4.8%
1 family level data, person-weighted

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Housing

Rates of home ownership vary dramatically across both income levels and family types. Seventy-eight percent of the non-poor live in homes that their families own, compared with only 41 percent of the poor. For those in poor, single-parent families and those in families receiving welfare, the home ownership rate is even lower, 24 percent. Thus, the non-poor are three times more likely to live in homes they own than those in poor, single-parent families.

A main reason for the difference in ownership rates between all individuals in poor families and individuals in poor, single-parent families is the high rate of ownership among individuals in poor, elderly families, 63 percent of whom live in homes they own. In addition, 51 percent of people in poor two-parent families live in homes they own.

The poor are at greater risk of being evicted from their home or apartment, with eviction rates 5 times as high as the non-poor. While only 0.4 percent of the non-poor were evicted in the past year, 2.1 percent of the poor, 2.4 percent of the single-parent poor, and 2.6 percent of those in welfare-recipient families were evicted for not paying the rent or mortgage. Twenty-six percent of the poor and 29 percent of those receiving welfare are in families that did not pay the full rent or mortgage at some point in the last year. The rate for the non-poor was much lower, only 7.5 percent.

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HOUSING (1)

People in Non-poor Families People in Poor Families People in Poor, Single-Parent Families People in Families Receiving Welfare
AMERICAN HOUSING SURVEY, 1993
Owned home 77.6% 40.8% 24.3% 24.9%
Over 1 person per room (Crowding) 4.2% 19.2% 16.7% 23.6%
Moderate upkeep problems 3.3 11.3% 12.5% 11.9%
Severe upkeep problems 1.7% 3.8% 4.4% 4.3%
SURVEY OF INCOME AND PROGRAM PARTICIPATION, 1992
Conditions in home unsatisfactory enough that one would like to move 9.5% 26.6% 33.5% 34.5%
In the past 12 months, there was a time when the household:
did not pay the full amount of the rent or mortgage 7.5% 25.9% 26.0% 29.1%
was evicted from home/apartment for not paying rent/mortgage 0.4% 2.1% 2.4% 2.6%
1 family level data, person-weighted

Those in poor and non-poor families differ according to the characteristics and condition of their housing as well. For example, poor individuals are more than twice as likely to live in crowded housing; 19 percent of those in poor families live in housing with more than one person per room, compared to only 4 percent of the non-poor. Similarly, those in poor families are about twice as likely to live in housing with upkeep problems as are the non-poor. Eleven percent of the poor have housing with moderate upkeep problems and 4 percent have severe upkeep problems. For persons living in non-poor families, 4 percent have housing with moderate problems and 2 percent have severe problems. (10)

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Consumer Durables and Utilities

For some major consumer durables, the poor and non-poor differ little in access. Almost all of the poor, like the non-poor have access to refrigerators and stoves: 98 percent versus 99.5 percent. Also, 92 percent of people in poor and single-parent poor families and 98 percent of people living in non-poor families have access to a color television. Mayer and Jencks (1995) note that color televisions are a low-cost form of entertainment for poor families.

For several other consumer durables, the poor have considerably lower rates of access, although for most of the items measured, their access rates are still above 50 percent. For example, 77 percent of the poor and 70 percent of the single-parent poor have access to a telephone, compared with 97 percent of the non-poor. Similarly, 72 percent of the non-poor live in families that have an air conditioner, while 50 percent of those in poor families and 46 percent of those in poor, single-parent families do. People in poor families are also considerably less likely to have access to washing machines and apparel dryers. Finally, 77 percent of the poor and 64 percent of those in poor, single-parent families have a household car or truck available, compared to 97 percent of the non-poor. Because the SIPP asks whether the family has these items in either the home or the building, actual ownership rates of some items are likely lower.

Finally, the poor are more likely to have problems paying utility bills and more likely to have services cut off. The poor and the single-parent poor are over three times as likely as the non-poor to have not paid their utility bill at some time during a 12 month period. The poor are over four times as likely to have their utilities cut off, while the single-parent poor are over five times as likely. Finally, the poor are five times as likely as the non-poor to have their telephone service disconnected because payments were not made, while the single-parent poor are six times as likely.

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CONSUMER DURABLES AND UTILITIES (1)

People in Non-poor Families People in Poor Families People in Poor, Single-Parent Families People in Families Receiving Welfare
SURVEY OF INCOME AND PROGRAM PARTICIPATION 1992
Items currently in the home or building that are in working condition
Washing machine 92.7% 71.7% 67.5% 66.3%
Apparel dryer 87.3% 50.2% 43.9% 44.8%
Refrigerator 99.5% 97.9% 98.1% 98.2%
Color television 98.5% 92.5% 92.1% 92.2%
Stove 99.5% 97.7% 97.3% 98.0%
Air conditioner 71.9% 49.6% 46.0% 40.7%
Telephone 97.2% 76.7% 69.9% 67.5%
In the past 12 months, there was a time when household:
did not pay the full amount of the gas, oil, or electricity bill 9.8% 32.4% 37.0% 40.7%
had service turned off by the gas, electric, or oil company 1.8% 8.5% 10.1% 10.5%
had telephone service disconnected because payment was not made 3.2% 16.0% 18.0% 20.3%
AMERICAN HOUSING SURVEY 1993
Car or truck 97.2% 76.8% 64.1% 65.3%
1 family level data, person-weighted

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Crime and Neighborhood

Individuals who live in poor households (11) especially those in poor, single-parent households are much more likely to be victims of crime than those who live in non-poor households. Those living in poor households are twice as likely as the non-poor to be victims of violent crimes (rape, assault, and robbery); those in poor, single-parent households are more than three times as likely.

The difference between incidence of personal theft for the poor and the non-poor is not statistically significant, but those in poor, single-parent households again suffer crimes at a higher rate. Rates of theft for the non-poor are 60 per 1000 people per year, compared to 66 for the poor and 85 for those in poor, single-parent households. The rate of incidence for household crimes (burglary, household theft, or motor vehicle theft) are high for both the poor and the poor in single-parent households. Poor households are almost one and a half times as likely and poor, single-parent households are over twice as likely as non-poor households to suffer these crimes.

Consistent with these statistics on crime victimization, the poor are less likely to report living in safe neighborhoods. Ninety-three percent of the non-poor live in families where the family head reports that the neighborhood is safe from crime compared to only 78 percent of the poor, 72 percent of those in poor, single-parent families, and 67 percent of those in families receiving welfare. Similarly, the poor are more likely to live in families where the head reports being afraid to go out: (12) only 9 percent for the non-poor, compared with 19.5 percent for the poor, 21 percent for those in poor, single-parent families, and 25 percent for those in families receiving welfare.

Overall, the poor are more likely to express dissatisfaction with their communities: 18 percent of the poor and 25 percent of those in poor, single-parent families are in families that report that their neighborhood condition is bad enough that they would like to move, compared with only 6 percent of the non-poor. Similarly, 15 percent of the poor and 20 percent of persons in poor, single-parent families are in families that report that community services in their neighborhoods are bad enough that they would like to move, compared with only 6 percent of the non-poor.

Given that these are measures of safety and neighborhood quality are subjective, it is plausible that differences would be greater if measured on an absolute scale because people tend to adjust their expectations according to their experiences (Frank, 1989).

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CRIME AND NEIGHBORHOOD (1)

People in Non-poor Families People in Poor Families People in Poor, Single-Parent Families People in Families Receiving Welfare
NATIONAL CRIME VICTIMIZATION INTERVIEW SURVEY 1992
Violent crimes, per 1000 people per year 26.15 53.68 87.50 ----
Theft, per 1000 people per year 59.69 66.01 84.66 ----
Household crimes, per 1000 households per year 143.29 207.1 317.59 ----
SURVEY OF INCOME AND PROGRAM PARTICIPATION 1992
Neighborhood safe from crime 93.0% 78.1% 72.4% 67.4%
Afraid to go out 8.7% 19.5% 20.7% 24.6%
Neighborhood condition bad enough that one would like to move 6.5% 18.4% 24.5% 27.5%
Community Services bad enough that one would like to move 5.5% 15.1% 19.7% 20.5%
1 family and household level data (except as noted in the NCVS), person-weighted

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Health and Nutrition

Poor mothers are much more likely than non-poor mothers to experience problems in birth and pregnancy. The number of infant deaths within the first year is higher: 13.5 per 1000 live births for poor mothers and 14.6 for poor, single mothers compared to 8.3 for non-poor mothers. Similarly, the percentage of live births with low weight and the rate of pre-term births is about twice as high for poor and single, poor mothers as for non-poor mothers. (13)

Poor and non-poor mothers also differ in quality of prenatal care. The Centers for Disease Control (CDC) defines inadequate prenatal care as lack of prenatal doctor visits in the first trimester, a strong predictor of birth outcomes. Forty-three percent of poor mothers and 49 percent of poor, single mothers had no prenatal doctor visits in the first trimester compared with only 16 percent of non-poor mothers.

Poor children are more likely to have had a disability or health impairment lasting more than 6 months: 24 percent of poor children (age 3-7) compared to 17 percent of non-poor children. Similarly, 25 percent of poor children in single-parent families have had a disability.

Poor and non-poor children under age 18 do not differ significantly in the amount of time since their last doctor visit, perhaps because of Medicaid availability for poor children. Poor children are, however, less likely to see a dentist regularly. Sixty-two percent of non-poor children have seen a dentist within the last year compared with only 41 percent of the poor.

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HEALTH AND NUTRITION (1)

People in Non-poor Families People in Poor Families People in Poor, Single-Parent Families People in Families Receiving Welfare
NATIONAL MATERNAL AND INFANT HEALTH SURVEY 1988
Infant deaths in first year (per 1000 live births) 8.3 13.5 14.6 14.3
Low birth weight (Less than 2500 grams) 5.5% 10.2% 12.8% 11.6%
Pre-term (gestation under 37 weeks) 7.3% 13.0% 15.2% 15.1%
Inadequate prenatal care 15.6% 43.1% 48.8% 42.1%
CURRENT POPULATION SURVEY 1993
Covered by private health insurance for all or part of the year 80.0% 21.1% 16.0% -----
Covered by Medicaid for all or part of the year 6.1% 54.5% 71.6% -----
Not covered by health insurance at any time during the year 12.1% 26.8% 18.0% -----
NATIONAL HOUSEHOLD EDUCATION SURVEY 1993 (ages 3-7)
Children age 3-7 years
Is there a particular clinic, health center, doctor's office, or other place the child is usually taken when sick?
Yes, an emergency room 5.3% 14.7% 17.2% -----
No 3.1% 8.3% 6.1% -----
Child has a usual place where they are taken for routine care 41.8% 40.1% 40.2% -----
Child ever had 1 or more disabling conditions 17.5% 23.8% 24.7% -----
SURVEY OF INCOME AND PROGRAM PARTICIPATION 1992
Household had enough food in the past 4 months 98.6% 89.0% 86.9% 85.8%
NATIONAL HEALTH INTERVIEW SURVEY 1993
Non-poor Children Poor Children
Children under age 18 years
Doctor visit in the past year 84.0% 80.0%
Dentist visit in the past year 62.0% 41.0%
1 individual level data (for SIPP - family level data, person-weighted)

Differences also exist in the presence and source of health insurance coverage. Twelve percent of those in non-poor families compared with 27 percent of those in poor families are not covered by health insurance at any time during the year. Those in poor single-parent families actually have a lower rate than do all poor, 18 percent. The higher coverage of the single-parent poor most likely results from their access to Medicaid. The poor are less likely to be covered by private health insurance and are more likely to be covered by Medicaid for all or part of the year. Only 21 percent of the poor (16 percent of those in poor, single-parent families) have private health insurance while 55 percent are covered by Medicaid (72 percent of the single-parent poor). In contrast, 80 percent of the non-poor have private health insurance and only 6 percent are covered by Medicaid.

Poor children also are less likely to have a particular clinic, health center, or doctor's office that they usually visit when sick, and are more likely to use an emergency room as their usual clinic if they have one. Twenty-three percent of poor children usually use an emergency room or have no usual clinic when sick, compared to only 8 percent of non-poor children. Poor and non-poor children do not differ in whether they have a usual place to which they go for routine care.

Finally, the poor are more likely to live in families that report sometimes or often not having enough food to eat. Ninety-nine percent of the non-poor live in families where the head reports having enough food to eat, compared to 89 percent of persons in poor families and 87 percent of persons in poor, single-parent families.

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Education

Poor students are more likely to have repeated a grade and to have been expelled from school. Thirty-one percent of poor youth (grades 3-12) are reported by their parents to have repeated a grade, which is twice as high as the rate for non-poor students, 15 percent. Poor students are over three times as likely as non-poor students to be expelled from school, 3.4 percent versus 1.0 percent. Also, poor students are considerably more likely to attend schools with security guards and metal detectors.

Both poor and non-poor students have high expectations that they will attend and graduate from college. Ninety percent of poor students expect to attend school after high school and 83 percent anticipate graduating. Ninety-six percent of non-poor students, expect to continue their education and 90 percent expect to graduate college. On the other hand, actual attendance and graduation rates exhibit differences. Forty-eight percent of poor students and 70 percent of non-poor students attend either a two year or four year college; 17 percent of poor students and 33 percent of non-poor students complete a bachelor's degree. (14)

Home computer use by children (age 14 and under) varies dramatically by income. Twenty-three percent of children in non-poor families use a computer at home, compared with only 3 percent of children in poor families and 2.5 percent of children in poor, single-parent families. Children have more equitable use of computers at school: 63 percent of non-poor students compared with 55 percent of poor students and 52 percent of students in poor, single-parent families use a computer at school.

Most poor and non-poor pre-kindergarten children are enrolled in a nursery or preschool program; only 9 percent of poor and 6 percent of non-poor children were not in a preschool program. The poor are much more likely to attend a Head Start program or other public preschool.

For young children, the poor watch more television than the non-poor and have fewer books. Almost one third of poor children watch more than 4 hours per day, compared to only 15 percent of non-poor children. Twenty-seven percent of poor children and 29 percent of poor children in single-parent families have fewer than 10 books, compared to only 5 percent of non-poor children.

Finally, poor children move more often. Twenty-eight percent of poor children age 5-7 years moved three or more times before their fifth birthday, compared to 20 percent of non-poor children. The pattern is similar for older children as well.

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EDUCATION (1)

People in Non-poor Families People in Poor Families People in Poor, Single-Parent Families
CURRENT POPULATION SURVEY - EDUCATION SUPPLEMENT 1993
Children age 14 years and under
Percent of children (in school) who use a computer at school 63.3% 54.8% 51.9%
Percent of children who use a computer at home 23.0% 3.2% 2.5%
NATIONAL HOUSEHOLD EDUCATION SURVEY 1993
Students grades 6-12
Student thinks he/she will attend school after high school 96.1% 90.1% 90.2%
Student thinks he/she will graduate from a 4-year college 89.7% 82.7% 82.3%
School has security guards 28.8% 43.3% 46.2%
School has metal detectors 4.1% 11.5% 12.8%
Students grades 3-12
Student has repeated a grade since starting school 15.4% 31.3% 31.6%
Student has been expelled from school (at some point) 1.0% 3.4% 3.5%
Pre-kindergarten
Child not enrolled in preschool 5.8% 8.6% 7.1%
Child enrolled in public preschool or Head Start program 31.0% 75.5% 78.2%
Children age 5-7 years
Child has 9 or fewer books 5.4% 27.2% 28.5%
Child watches more than 4 hours of television per day 15.1% 29.2% 30.8%
Child moved 3 or more times between birth and 5th birthday 19.5% 28.0% 27.9%
HIGH SCHOOL AND BEYOND SURVEY 1992
Attended either a 2 or a 4-year college 69.6% 48.3% 47.6%
Completed a BA 32.6% 16.9% 13.2%
1 individual level data

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Overall Deprivation

The tables discussed previously provide information on the distribution of various assets, consumption commodities, and income. However, correlation across measures are not apparent. Families with limited resources may choose different allocations of commodities in order to make ends meet. Examining one dimension of living conditions at a time likely understates the extent to which families forego important other elements of material well-being.

To address this, we have created an index of deprivation using data from the Survey of Income and Program Participation (SIPP). We identify as deprivations nine family characteristics: evicted in the past year, gas or electricity turned off in the past year, phone disconnected in the past year, did not have enough food in the past four months, lives in crowded housing (more than one person per room), lives in housing with moderate or severe upkeep problems, (15) lives without a refrigerator, lives without a stove, and lives without a telephone. For each individual, the number of deprivations reported is the total number of these characteristics reported by the individual's family. The number of deprivations is between zero and nine for each individual. Each of these hardships was chosen because they are relatively rare in the overall U.S. population and represent an element of material well-being important in day to day life in this country that has been forgone.

(16) The majority of the poor live with at least one of these deprivations: 55 percent of the poor compared with 13 percent of the non-poor. Similarly, 27 percent of the poor face two or more deprivations compared with only 3 percent of the non-poor. Fifty-seven percent of those in poor, single-parent families suffer at least one deprivation and 30 percent live with two or more; 65 percent of those in families receiving welfare suffer at least one deprivation and 34 percent live with two or more. Overall, the average number of deprivations for the poor, the poor in single-parent families, and those in families receiving welfare are 5 to 6 times higher than for the non-poor.

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MEASURES OF WELL-BEING: Deprivation Index (1)

People in Non-poor Families People in Poor Families People in Poor, Single-Parent Families People in Families Receiving Welfare
SURVEY OF INCOME AND PROGRAM PARTICIPATION 1992
Percent of persons with:
0 deprivations 87.0% 44.9% 43.2% 34.6%
1 or more deprivations 13.0% 55.1% 56.8% 65.4%
2 or more deprivations 3.2% 26.9% 29.8% 33.6%
3 or more deprivations 1.0% 11.8% 12.9% 14.6%
4 or more deprivations 0.3% 4.0% 4.5% 4.9%
5 or more deprivations 0.1% 1.1% 1.1% 1.7%
6 or more deprivations 0.0% 0.1% 0.1% 0.1%
7 or more deprivations 0.0% 0.0% 0.0% 0.0%
8 or more deprivations 0.0% 0.0% 0.0% 0.0%
9 deprivations 0.0% 0.0% 0.0% 0.0%
Average number of deprivations 0.19 0.99 1.06 1.21
1 Averages for individuals of family level data

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Discussion

There are several factors that may lead to over- or underestimates of the differences in living conditions between the poor and non-poor.

Our measures may overstate the actual deprivation of the poor because differences in possessions may reflect differences in preferences rather than differences in resources. These data do not allow us to distinguish for each difference in living conditions that we identify, the relative importance of choice versus limited resources. Moreover, one's lack of interest in material goods would be reflected in lower expenditures and fewer possessions. This lack of interest may also translate into lower income.

Working in the other direction, the use of short-term measures of poverty, such as employed in this study, probably understates the relationship between persistent poverty and various outcomes. Roughly half of those who are poor one year will remain poor for some years to come (Ruggles, 1990). Some past studies have found that differences are more pronounced for the persistently poor than those poor in only one year. For example, poverty is associated with deficits in children's cognitive development; the correlation is roughly twice as large for children who are in poor families three years in a row as for those poor a single year (Korenman, Miller, and Sjaastad, 1995). Miller and Korenman (1994) find that differentials in children having low height for their age (stunting) and low weight for their height (wasting) are also greater for those living in long-term rather than short-term poverty.

An understatement of the difference between poor families and the general population is likely to result because, following standard procedure, we consider negative and zero income and expenditure values to be valid responses and include them in the calculation for the below-poverty population. Negative incomes are often due to business losses or capital losses and, thus, are a bad indicator that a family is poor. Calculations from the American Housing Survey suggest that excluding families reporting negative or zero annual incomes from the poverty population increases the gap between the poor and the non-poor for most variables. For example, home ownership among persons in poor families falls from 41 percent to 36 percent when persons in families with negative and zero income are excluded. Persons in families with negative or zero income have relatively high home ownership rates, 64 percent.

The difference in living conditions may also be understated due to a lack of adjustment for quality. If, for example, the durables owned by the poor are older, of lower quality, or located in the building but not in the individual housing unit, the differences between poor and non-poor families would be understated.

Finally, certain populations, such as the homeless or the institutionalized population are rarely included in the sample design of federal household surveys such as these. It is likely that the most severe deprivation is concentrated among some of these underrepresented groups. If so, the results presented here understate the differences between the poor and the non-poor. To more fully identify the poor, changes in sample design and survey instruments need to be developed to specifically get at these vulnerable populations.

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Conclusions

The results presented here paint a broad picture of the living conditions of individuals in American families across a variety of measures of well-being and allow comparisons across family types and income levels. Clear differences between the poor and non-poor are evident.

The differences across family types detailed here make clear that analyses that generalize across the entire poverty population can be misleading. For example, home ownership rates for people in poor, single-parent families and people in families receiving welfare are only three-fifths the rate for those in all poor families. Since recent policy debates have primarily focused on changes that would likely have a larger effect on individuals in poor, single-parent families and welfare recipient families, using results based on the total poor may significantly underestimate the differences between the policy relevant group and the non-poor.

The results presented do not necessarily reflect a causal relationship between income and living conditions. Furthermore, they do not indicate which, if any, differences should be addressed by policy; nor do they indicate whether specific government interventions should be continued, or modified, or introduced. By definition, raising a family's income will end its poverty. At the same time, higher income may not remove the differences in the living conditions or deprivations which we have identified. For example, if low parental education highly related to both low income and a low probability that a child will attend college, then raising family income will not necessarily lead to an increase in the likelihood that the child will attend college. Problems with interpreting the causality of these relations has important implications for moving from these analyses to the evaluation and design of policies.

The current study can be extended along a number of dimensions. While we analyze a large number of surveys and variables, many important aspects of living conditions remain unmeasured. For example, measures of assets, access to credit, employment patterns, homelessness, environmental hazards, accumulation of "cultural capital" such as connections to social networks, and more objective characteristics of neighborhoods could be included in future research. Further separating the family categories along other dimensions such as length of poverty spells, income to poverty ratios, race, ethnicity, and geographic region would be useful. Similarly, different resource measures other than gross income (e.g. income after taxes, transfers, or other costs such a child care) and different thresholds other than the official poverty thresholds (e.g. a threshold based on the relative position of the family in terms of income or expenditures) could be used. In addition, variations in rates of deprivation and living conditions among the poor may have implications for redefining the official poverty threshold to better identify individuals living in poverty. Perhaps most importantly, it is crucial to disentangle the causal links between poverty and living conditions. Only with this understanding can we design policies that successfully increase well-being, especially for children, with minimal damage to incentives.

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Selected Bibliography

Cage, Robert, Thesia I. Garner, Richard Miller, William Passero, and Elizabeth Reise. "Data Comparability Across Federal Household Surveys." Working document. Bureau of Labor Statistics, 1992.

Cutler, David M. and Lawrence F. Katz, "Macroeconomic Performance and the Disadvantaged," Brookings Papers on Economic Activity, 2: 1991.

Cutler, David M. and Lawrence F. Katz, "Rising Inequality? Changes in the Distribution of Income and Consumption in the 1980's." American Economic Review. 82 (May 1992): 546-551.

Fitzgerald, Hiram E., Barry M. Lester, and Barry Zuckerman, eds. Children of Poverty: Research, Health Care, and Policy Issues. New York: Garland, 1995.

Frank, Robert H. (1989), "Frames of Reference and the Quality of Life," American Economic Review 79 (May): 80-85.

Huston, Aletha C., ed. Children in Poverty: Child Development and Public Policy. New York: Cambridge University Press, 1991.

Huston, Aletha C., Vonnie McLoyd, and Cynthia Garcia Coll. Children and poverty: Issues in contemporary research. Child development (Special Issue: Children and Poverty) 65(2):275-282, 1994.

Jencks, Christopher and Kathryn Edin. "Do poor women have a right to bear children?" The American Prospect. 20 (Winter 1995): 43-52.

Jargowsky, Paul A., "Beyond the Street Corner: The Hidden Diversity of Ghetto Neighborhoods," mimeo., University of Texas at Dallas, 1995.

Korenman, Sanders, Jane E. Miller, and John E. Sjaastad, "Long-term Poverty and Child Development in the United States: Results from the NLSY," Children and Youth Services Review, Vol. 17, nos. 1 and 2, 1994.

Lino, Mark. "Income and Spending of Poor Households With Children." Family Economics and Nutrition Review, Volume 9, Number 1, 1996.

Mayer, Susan and Christopher Jencks "Has Poverty Really Increased Among Children Since 1970," Center for Urban Affairs and Policy Research Working Paper 94-14, Northwestern University, 1995.

Mayer, Susan and Christopher Jencks, "Recent Trends in Economic Inequality in the United States: Income versus Expenditure versus Material Well-being," in Papadimitriou, Dimitri B. and Edward N. Wolff, eds. Poverty and prosperity in the USA in the late twentieth century. New York: St. Martin's Press, 1993.

Miller, Jane E. and Sanders Korenman, "Poverty and Children's Nutritional Status in the United States," American Journal of Epidemiology, vol. 140, No. 3, 1994.

Rector, Robert, "How the Poor Really Live: Lessons for Welfare Reform," Heritage Foundation Backgrounder No. 875, January 31, 1992.

Ruggles, Patricia. Drawing the Line--Alternative Poverty Measures and Their Implication for Public Policy. Washington, DC: The Urban Institute Press, 1990.

Passero, William D. "Spending Behavior of Families Receiving Welfare or Public Assistance, 1992-94." Paper presented at the 42nd Annual Conference of the American Council on Consumer Interests, Nashville, Tennessee, March 27-30, 1996. Available from the author, Bureau of Labor Statistics, Washington, D. C.

Shea, Martina, "Dynamics of Economic Well-Being: Poverty, 1990-1992", U.S. Bureau of the Census Current Population Report P70-42, U.S. Government Printing Office, Washington D.C., 1995

Sherman, Arloc, Wasting America's Future: The Children's Defense Fund Report on the Costs of Child Poverty, Beacon Press, Boston, 1994.

Slesnick, Daniel T. "Gaining Ground: Poverty in the Postwar United States." Journal of Political Economy. 101 (February 1993): 1-38.

Townsend, Peter. Poverty in the United Kingdom: A Survey of Household Resources and Standards of Living. Harmondsworth, England: Penguin Books, 1979.

Townsend, Peter. The International Analysis of Poverty. Hemel Hempstead, England: Harvester-Wheatsheaf, 1992.

U.S. Department of Commerce, Bureau of the Census. Poverty in the United State, 1992, Series P-60-185. 1993

U.S. Department of Labor, Bureau of Labor Statistics (BLS). Consumer Expenditure Survey, 1992-93. Bulletin 2462, September 1995.

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Appendix A: Descriptions of Surveys

American Housing Survey

These data are from a sample of housing units interviewed between July and December 1993, collected by the Department of Housing and Urban Development. The same basic sample of housing units is interviewed every 2 years until a new sample is selected. The sample is updated by adding newly constructed housing units and units discovered through coverage improvement efforts every enumeration.

For the 1993 American Housing Survey-National (AHS-N), a sample of approximately 56,700 housing units was selected for interview. About 3,300 of these units were ineligible because the unit no longer existed or because the unit did not meet the definition of a housing unit (intended for occupancy as separate living quarters, not as group quarters). About 2,300 of the remaining units (both occupied and vacant housing units) were classified as "type A" noninterview because (a) no one was at home after repeated visits, (b) the respondent refused to be interviewed, or (c) the interviewer was unable to find the unit.

Sampled units are followed up, including personal visits, until an interview is obtained, or they are classified as type A's. There is no oversampling. Biases which arise from nonsampling errors, which are larger than sampling errors, such as incomplete data from coverage errors or item refusal, are corrected to the extent possible by weighing changes. Wrong answers, measured by inconsistency checks, cannot be identified or reconciled. Users must be also be aware that, for example, responses to opinion questions have higher inconsistencies than do responses to other questions.


Consumer Expenditure Interview Survey (CE)

The results in the tables presented are based on data collected from January 1992 through December 1993 using the quarterly interview portion of the Consumer Expenditure Survey. The period for which the expenditures refers is October 1991 through November 1993. The survey is sponsored by the Bureau of Labor Statistics with data collected by the Bureau of the Census.

The sample is designed to represent the total civilian noninstitutional population (for example, those living in houses, condominiums, or apartments) and persons living in group quarters such as housing facilities for college students and workers. Military personnel living on base are not included. Approximately 5,000 consumer units are interviewed each quarter.

Expenditures are defined as the transaction costs, including excise and sales taxes, of goods and services acquired during the interview period. Expenditure estimates include expenditures for gifts, but exclude purchases or portions of purchases directly attributable to business purposes. Also excluded are periodic credit or installment payments on goods or services already acquired, although interest payments are collected. An exception is noted in the case of owned housing: neither the full purchase price of the housing nor the mortgage principle payments is included in expenditures; however, mortgage interest and related charges are included. Each quarter is assumed to be an independent sample and is treated as such to incorporate the weights. Given this assumption, data from each quarterly interview are aggregated and expenditures annualized for the purposes of this study.

Internal BLS CE data were used for this analysis; thus, data are not topcoded.


Current Population Survey (CPS)

These data are obtained from the March 1994, Current Population Survey (CPS) conducted by the Bureau of the Census. The population covered included the civilian noninstitutional population of the United States and members of the Armed Forces in the United States living off post or with their families on post, but excludes all other members of the Armed Forces. The survey includes over 60,000 families and unrelated individuals with over 150,000 people. Coverage does not include residents of U.S. territories or other areas outside the 50 States and the District of Columbia. The reference period for income questions is calendar year 1993. Data from the October 1993 Education Supplement are also used.

Allocations, topcodings, imputations, and edits are those imposed by Census on the CPS file provided to the Department of the Treasury's Office of Tax Policy.


High School and Beyond (HS&B)

The data used here are drawn from the 1992 follow-up survey of the sophomores from 1980 conducted by the National Center for Education Statistics. HS&B has interviewed some 15,000 sampled members of the sophomore cohort as recently as 1992. The HS&B is a longitudinal study of students enrolled in public, private, and parochial secondary schools in 1980 at the sophomore and senior grades. The schools were selected as a stratified probability sample. The HS&B surveyed parents, teachers, and school officials in addition to the students.


National Crime Victimization Survey (NCVS)

The data in the NCVS were collected for the Department of Justice between January 1992 and June 1993 and reflect incidents occurring from January 1 through December 31, 1992. The NCVS collects information on victimization events for a sample of 60,000 households (130,000 persons). Data are gathered from residents living throughout the United States, including persons living in group quarters, such as dormitories, rooming houses, and religious group dwellings. Crew members of merchant vessels, armed forces personnel living in military barracks, and institutionalized persons, such as correctional facility inmates, were not included in the scope of this survey. Similarly, U.S. citizens residing abroad and foreign visitors to this country were excluded. With these exceptions, individuals age 12 or older living in units designated for the sample were eligible to be interviewed.


National Health Interview Survey (NHIS)

The data in the NHIS are collected for the National Center for Health Statistics with a continuing nationwide survey of households on the health and other characteristics of household members for the National Center on Health Statistics. A different, probability-sampled set of households with civilian, non-institutionalized occupants is interviewed each week of the year. The reference period for the NHIS is the entire year. The 1993 NHIS includes a total of 44,978 households containing 109,671 persons.


National Household Education Survey

In 1993 data used here was collected by the National Center for Education Statistics in two components of the NHES: School Readiness and School Safety and Discipline. Nearly 64,000 households were screened. Approximately 11,000 parents of 3-to-7-year-olds completed interviews for the School Readiness component and about 12,700 parents of children in grades 3 through 12 and about 6,500 youth in grades 6 through 12 were interviewed for the School Safety and Discipline component. The NHES is a telephone survey of the noninstitutional civilian population with households selected using random digit dialing methods.


National Maternal and Infant Health Interview Survey (NMIHS)

Data for the NMIHS were collected for the National Center for Health Statistics by drawing stratified systematic samples from calendar year 1988 vital records from 48 states, the District of Columbia, and New York City. Mothers were mailed questionnaires based on information from vital records. Mothers who responded to the questionnaire on the national file included 9,953 women who had live births, 3,309 women who had late fetal deaths, and 5,332 women who had infant deaths.

In order to assure a representative sample by such variables as age of mother and marital status, implicit stratification was employed. That is, after the live birth records were stratified, further sorting of vital records was done by age of mother and marital status within each of the live birth strata. Similar subsorting was carried out for fetal and infant death records.


Survey of Income and Program Participation (SIPP)

These data are compiled from the Extended Measures of Well-Being topical module collected as part of wave 6 of the 1991 panel and wave 3 of the 1992 panel of the SIPP, collected by the Bureau of the Census. The combined panels comprise responses on living conditions by reference persons representing almost 85,000 persons. The reference period is September through December of 1992.

These data were not imputed for nonresponse and therefore frequencies are based only on the proportion of persons answering the questions. For the most part, nonresponse levels for these questions were in the range of 1 or 2 percent.

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Appendix B: Poverty Rates Across the Surveys

Most surveys used here include a measure of whether the family or household's income was below the official poverty threshold for its type, during the reference period of the survey. Most surveys compare annual income to the poverty thresholds; the SIPP uses income over the four month reference period annualized. The CE annualizes quarterly data and also uses expenditures rather than income to determine poverty status.

Because some surveys collect income data in broad categories, it is not possible to use an exact poverty line as in the other surveys. In the National Crime Victimization Survey, a household is considered under the poverty threshold if it had: 1 person and annual income under $7,500, 2 or 3 persons and annual income under $10,000, 4 persons and annual income under $15,000, 5 persons and annual income under $17,500, 6 or 7 persons and annual income under $20,000, 8 persons and annual income under $25,000, and 9 or more persons and annual income under $30,000. In the National Household Education Survey, a family is considered under the poverty threshold if it had: 2 or 3 persons and annual income under $10,000, 4 or 5 persons and annual income under $15,000, 6 or 7 persons and annual income under $20,000, 8 persons and annual income under $25,000, and 9 or more persons and annual income under $30,000. For the High School and Beyond Survey, children who report families incomes below $8,000 were considered poor.

Poverty rates across surveys are fairly similar. Poverty rates are lower in the CE because of the use of expenditures rather than income to determination poverty status. For the NHES and NMHIS, the poverty rates are higher as the samples are comprised of children in the relevant age group in the former and live births in the latter.

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POVERTY RATES OF INDIVIDUALS BY SURVEY
Survey All Families Single-Parent Families Two-Parent Families Families Receiving AFDC
American Housing Survey (AHS) 16.0% 46.1% 11.1% 73.0%
Consumer Expenditure Survey (CE) 13.8% 38.3% 9.6% 64.0%
Current Population Survey (CPS) 14.0% 48.3% 10.2% 77.0%
National Crime Victimization Survey (NCVS) 15.6% 46.7% 14.9%
National Household Education Survey (NHES)
School Readiness 28.1% 54.6% 17.4%
School Safety and Discipline 21.4% 38.7% 13.6%
National Maternal and Infant Health Survey (NMIHS) 24.9% 55.1% 14.5% 74.2%
Survey of Income and Participation (SIPP) 13.0% 45.5% 10.4% 82.0%
All Families Under Age 18
National Health Interview Survey (NHIS) 13% 20%


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