when combined with

Program Logo

U.S. Department of Commerce

Economics and Statistics Administration

U.S. CENSUS BUREAU

Issue 1990

to 1997

Demographic Programs

Issued June 1999

P60-205

Report Title

Current Population Reports

Consumer Income

Current Population Reports

Experimental

Poverty Measures

By Kathleen Short, Thesia Garner,

David Johnson, and Patricia Doyle
This report was prepared under the general direction of Charles T. Nelson,

Assistant Division Chief for Income and

Poverty Characteristics, Housing and

Household Economic Statistics Division.

Other important contributors were

Jessica Banthin of the Agency for Health

Care Policy Research, Richard Bavier of

the Office of Management and Budget, and

Donald J. Hernandez, John Iceland,

and Mary Naifeh of the Census Bureau.

Bernadette Proctor provided statistical

assistance. Cheryl Curtis provided clerical assistance.

Special thanks are extended to David

Betson, University of Notre Dame,

Constance F. Citro, Committee on

National Statistics of the National Academy

of Sciences, Robert T. Michael, University of Chicago, Denton Vaughan, Social

Security Administration, and Katherine K.

Wallman, Office of Management and Budget, who chairs the Technical Working

Group on Improving the Measurement of

Income and Poverty, for reviewing and providing comments on this report.Additional

thanks go to Stephen Malpezzi and

Barbara Wolfe of the University of Wisconsin, and Anthony Yezer at George

Washington University for their expertise

and assistance.

Sampling review was conducted by

Alfred G. Meier of the Demographic Statistical Methods Division.Data collection

was conducted by Census Bureau field representatives under the overall direction of

Richard L. Bitzer, Assistant Division

Chief, Field Division.

The staff of the Administrative and Customer Services Division, Walter C. Odom,

Chief, performed planning, design, composition, editorial review, and printing planning and procurement for publications,

Internet products, and report forms.

Cynthia G. Brooks provided publication

coordination and editing.

Thesia Garner and David Johnson are

in the Division of Price and Index Number

Research, Bureau of Labor Statistics.

Patricia Rozaklis, Ralph Bradley, Raj

Jain, Robert McClelland, Robert Bradford, and Steve Holden, also of the

Bureau of Labor Statistics, provided technical and computer programming assistance. The findings presented here do

not necessarily reflect the views of

the Bureau of Labor Statistics.

ACKNOWLEDGMENTS
Issue 1990

to 1997

Issued June 1999

P60-205

Report Title

Demographic Programs

Current Population Reports

Experimental

Poverty Measures

U.S. Department of Commerce

William M. Daley,

Secretary

Robert L. Mallett,

Deputy Secretary

Economics and Statistics Administration

Robert J. Shapiro,

Under Secretary

for Economic Affairs

U.S. Census Bureau

Kenneth Prewitt,

Director

Current Population Reports

Consumer Income
Paula J. Schneider,

Principal Associate Director

for Programs

Nancy M. Gordon,

Associate Director

for Demographic Programs

Daniel H. Weinberg,

Chief, Housing and Household

Economic Statistics Division

SUGGESTED CITATION

Short, Kathleen, Thesia Garner, David

Johnson, and Patricia Doyle,

Experimental Poverty Measures: 1990 to

1997, U.S. Census Bureau, Current Population Reports, Consumer Income,

P60-205, U.S. Government Printing

Office, Washington, DC, 1999.

For sale by Superintendent of Documents, U.S. Government Printing Office, Washington, DC 20402.

ECONOMICS

AND STATISTICS

ADMINISTRATION

Economics

and Statistics

Administration

Robert J. Shapiro,

Under Secretary

for Economic Affairs

U.S. CENSUS BUREAU

Kenneth Prewitt,

Director

William G. Barron,

Deputy Director
Experimental Poverty Measures ........................ 1

I. Executive Summary............................. 1

Key Findings ............................... 1

Effect of Experimental Poverty Measures on Various Subgroups .... 1

Time Series Estimates .......................... 1

Data Issues and Future Research .................... 1

II. Overview and Introduction ........................ 2

The National Research Council Report and Recommendations ..... 2

Purpose and Plan of This Report..................... 3

III. Effects of the NAS Panel Recommendations on Poverty Estimates ... 4

Recommendations Pertaining to Thresholds .............. 4

Recommendations Pertaining to Resources ............... 7

Recommendations Pertaining to Thresholds and Resources ...... 10

Updating Thresholds Over Time ..................... 13

IV. Combining the NAS Panel Recommendations .............. 15

Poverty Rates by Selected Characteristics ................ 16

Experimental Poverty Estimates Over Time ............... 20

V. Data Issues and Opportunities....................... 23

Survey of Income and Program Participation (SIPP) ........... 23

Consumer Expenditure Survey...................... 26

Decennial Census, the American Community Survey, and the Census

Bureau’s Small Area Income and Poverty Estimates (SAIPE) Program . 26

VI. Future Research .............................. 26

References .................................. 27

Appendixes

A. Detailed Tables for Section III ...................... A–1

B. Detailed Tables for Section IV ..................... B–1

C. Definitions of Elements in the Experimental Poverty Measures .... C–1

D. Summary of NAS Panel Recommendations ............... D–1

E. Source and Accuracy of Estimates ................... E–1

F. Data Quality: Current Population Survey ................ F–1

CONTENTS

iii
Experimental Poverty Measures

I. EXECUTIVE SUMMARY

This report presents experimental measures of poverty

in the United States. These measures are illustrative variations of the recommendations of the Panel on Poverty and

Family Assistance: Concepts, Information Needs, and Measurement Methods of the National Research Council.1 The

experimental measures presented here:

• Incorporate, in a way that the official measure does not,

the effects of key government policies aimed at the

most needy families in the United States.

• Use an after-tax income measure.

• Add the value of in-kind benefits, such as food stamps,

to income.

• Take account of variations in expenses that are necessary to hold a job or to obtain medical care.

Key Findings

• Considering all in-kind transfers together reduces the

incidence of poverty substantially, even though the

reductions from any single program are generally quite

small.

• The increase in poverty rates when one accounts for

necessary expenses can be substantial but depends on

the method used to value those expenses.

• Because of the earned income credit, deducting taxes

from income on balance reduces the percentage of

people who are viewed as being poor.

Effect of Experimental Poverty Measures on

Various Subgroups

To examine the effect of changing the poverty measure

on the poverty rates of different population subgroups, we

compute ‘‘standardized’’ poverty rates, which constrain

the experimental poverty rate for all persons to match the

official rate. Holding overall poverty rates constant in this

way allows us to illustrate the differential incidence of

poverty on different groups. When we do this, we find:

• The experimental measures result in lower standardized

poverty rates for children and higher rates for the elderly compared to the official measure.

• Standardized poverty rates are lower for Blacks under

the experimental measures than under the official measure.

• The experimental measures show lower standardized

poverty rates for people in families with a female householder (no spouse present) than are shown under the

official measure. On the other hand, married couples are

slightly more likely to be poor under the experimental

measures.

• The experimental measures that account for geographic

differences in the cost of housing show higher standardized poverty rates for people in the Northeast and the

West and also for people residing in suburban areas

than poverty rates based on the official measure.

• People with disabilities are considerably less likely to be

counted as poor under the experimental measures than

they are under the official measure.

Time Series Estimates

We also compare standardized poverty rates from 1990

to 1997 to the official poverty measure over the same

time period. We find:

• The experimental measures follow trends that are similar to the official measure over this period. This is true

for all experimental measures shown here.

• Patterns over time are similar for all measures whether

the thresholds are updated using expenditure data or

using changes in prices from year to year. However, a

slightly more pronounced decline in poverty rates from

1993 to 1997 is observed when thresholds based on

expenditure data are used.

Data Issues and Future Research

• The NAS panel recommended that the Survey of Income

and Program Participation should become the source of

official income and poverty statistics. All the measures

presented in this report are based on the Current Population Survey. Steps needed to make this change are

described in Section V.

• Various elements of the alternative poverty measures

presented in this report would benefit from additional

methodological research and improved data sources.

These issues are discussed in the final section of the

report.

1

Citro, Constance F. and Robert T. Michael (eds.), Measuring

Poverty: A New Approach, Washington, DC: National Academy

Press, 1995.

1

U.S. Census Bureau
This report represents our first step toward improving the

official measure of poverty. We invite comments from

readers on any of the issues presented in this report.

Please send your suggestions to Kathleen Short, Housing

and Household Economic Statistics Division, U.S. Census

Bureau, Washington, DC 20233-8500, or via electronic

mail to kshort@census.gov.

II. OVERVIEW AND INTRODUCTION

At the request of Congress, the National Research

Council of the National Academy of Sciences established

the Panel on Poverty and Family Assistance to address

increasing concerns about weaknesses in the current official poverty measure for the United States. The major conclusion of the panel was that the current measure needs to

be revised because it no longer accurately portrays trends

in economic poverty or differences among population

groups and geographic areas of the country. Based on its

evaluation of the limitations of the current measure, the

panel recommended a new measure which, in its opinion,

would better reflect far-reaching changes that have

occurred during the past 30 years in the society, the

economy, and in government policies.

This report presents estimates indicating the extent to

which the official poverty rate would have been different

in 1997 if each of a series of specific recommendations

made by the panel were implemented, and for calendar

years 1990-1997 if many of the recommendations were

implemented simultaneously. The purpose of this report is

to provide information for evaluating the implications of

many of the panel’s recommendations for a new poverty

measure. We do this by showing the change in the poverty

estimates relative to the current measure for each recommendation. In some cases, we show alternative methods

for implementing specific recommendations. This report

contains no recommendations on which new approaches

should be adopted. However, in Section IV, we present

alternative measures that follow closely the panel’s recommendations. The experimental measures presented differ

methodologically but not conceptually from the measure

described in the panel’s report.

A. The National Research Council Report and

Recommendations

The current official poverty measure was developed in

the early 1960s, and only a few minor changes have been

implemented since it was first adopted in 1965. This measure consists of a set of thresholds for families of different

sizes and compositions. These are compared to a resource

measure to determine a family’s poverty status. The

thresholds were chosen to represent the cost of a minimum diet multiplied by three (to allow for expenditures on

other goods and services). Family resources were defined

as before-tax money income. Concerns about the

adequacy of the measure have increased during the past

two decades, culminating in a Congressional appropriation

for an independent scientific study of the concepts, measurement methods, and information needs for a poverty

measure. In response, the Committee on National Statistics of the National Research Council of the National Academy of Sciences (NAS) established the Panel on Poverty

and Family Assistance, which released its report titled

Measuring Poverty: A New Approach in the spring of 1995.

Based on its assessment of the weaknesses of the current

poverty measure, the NAS panel members recommended a

new measure that they suggest better reflects contemporary social and economic realities and government policy.

Weaknesses of the current measure. The NAS panel

identified several major weaknesses of the current poverty

measure, including the definitions of both thresholds and

incomes (or resources), that have become more apparent

and problematic during the past three decades.

• The current income measure does not reflect the effects

of key government policies that alter the disposable

income available to families and, hence, their poverty

status. Examples include payroll taxes, which reduce

disposable income, and in-kind public-benefit programs,

such as the food stamps program, which free up

resources to spend on nonfood items.

• The current poverty thresholds do not adjust for rising

income levels and standards of living that have occurred

since 1965, despite evidence suggesting that the trend

in the income level commonly thought necessary to lift

a family out of poverty follows the trend in overall consumer expenditures.

• The current measure does not take into account variation in expenses that are necessary to hold a job and to

earn income— expenses that reduce disposable income.

These expenses include transportation costs pertaining

to work, and, perhaps more importantly, the increasing

costs of child care for working families resulting from

the increased labor force participation of mothers.

• The current measure does not take into account variation in medical costs across population groups which

are a function of differences in health status and insurance coverage.

• The current poverty thresholds use family size adjustments that are anomalous and do not take into account

important changes in family situations, including payments made for child support and increasing cohabitation among unmarried couples.

• The current poverty thresholds do not adjust for geographic differences in the cost of living across the

nation, although there are significant variations in

prices across geographic areas.

General recommendations. The NAS panel reviewed

several alternative approaches to measuring poverty, each

with merits and limitations, noting that any decision to

2

U.S. Census Bureau
accept or reject a particular approach must involve judgment as well as scientific evidence.2 The NAS panel did,

however, recommend specific changes to the official poverty measure based on the best scientific evidence available, its best judgment, and the criteria that the resulting

poverty measure should be acceptable and understandable to the public, statistically defensible, and feasible to

implement. At the broadest level, the NAS panel recommended that the new poverty measure should consist of a

set of poverty thresholds and a definition of family

resources for comparison to the thresholds to determine

who is in or out of poverty. The panel stressed that the

definition of family income or resources should be consistent with the concept underlying the poverty threshold.

They elaborated these recommendations by providing specific, detailed procedures for implementation, though

often within a range, or by identifying research needed to

provide the basis for decisions to fully implement the

more general recommendations.

Threshold recommendations. The panel recommended

that the thresholds should represent a dollar amount for

food, clothing, shelter (including utilities), and a small

additional amount to allow for other common, everyday

needs (e.g., household supplies, personal care, and

nonwork-related transportation). One threshold should be

developed for a reference family type using Consumer

Expenditure Survey data, and the reference family threshold should be adjusted to reflect the needs of different

family types and geographic differences in the cost of living. The reference family should consist of two adults and

two children. Adjustments to thresholds should be made

over time to reflect changes in real growth in basic consumer expenditures.

Family resource recommendations. The panel recommended that family resources should be defined as the

value of money income from all sources, plus the value of

near-money benefits that are available to buy goods and

services covered by the new thresholds, minus expenses

that divert money that can no longer be used to buy these

critical goods and services. Near-money benefits include

nonmedical in-kind benefits, such as food stamps, subsidized housing, school lunches, and home energy assistance. Expenses to be subtracted include income taxes,

social security payroll taxes, child care and other workrelated expenses, child support payments to another

household, and household contributions toward the costs

of medical care and health insurance premiums (i.e., medical out-of-pocket costs or MOOP).

Data recommendations. Several of the panel’s recommendations dealt with survey methodology. Most significantly,

the panel recommended that the Survey of Income and

Program Participation (SIPP) should become the basis of

official income and poverty statistics, replacing the March

income supplement to the Current Population Survey

(CPS). In this recommendation, the panel recognized that

the SIPP asks more relevant questions than the March CPS

and obtains income data of higher quality. The panel also

encouraged a review of the Consumer Expenditure Survey

(CEX) to improve the quality and usefulness of the data for

poverty measurement. Finally, they recommended that

consideration should be given to the practical problems of

implementing fully an improved measure of poverty when

using other surveys that do not collect the detailed information that is needed.

Research recommendations. There are several elements in

the proposed poverty measure for which the panel recommended additional research. Among them are improved

estimation of the geographic cost-of-living differences, an

assessment of the extent of resource sharing among nonfamily household members for the purpose of broadening

the unit of analysis, development of methods to value the

benefits of owning a home and development of one or

more medical care risk indexes (separate from the measure of economic poverty) that would measure the risk of

having inadequate or no health insurance coverage.

B. Purpose and Plan of This Report

The purpose of this report is to provide information

regarding the implications of many of the NAS panel recommendations. The report shows how estimated levels of

poverty would differ from official levels as specific recommendations of the NAS panel are implemented individually

and how estimated trends would differ when many recommendations are implemented simultaneously. Estimates

are developed for calendar years 1990-1997 using data

from the CPS, the CEX, and other sources. We address

issues related to the development of poverty estimates

using the SIPP in a later section on data issues and opportunities.

The following two sections of the report describe and

implement particular approaches recommended by the

NAS panel and provide a few illustrative variations of

these recommendations. First, we present results showing

how the official poverty estimates for 1997 would be

affected by implementing various recommendations one

or two at a time. This first section focuses, in turn, on recommendations pertaining to poverty thresholds, on family

resources, on both thresholds and resources, and on various methods for updating the thresholds over time. Second, we present results showing the implications of simultaneously implementing several recommendations for the

distribution of poverty among subgroups of the population in 1997 and for trends between 1990 and 1997.

These estimates are ‘‘standardized’’; that is, they are

adjusted so that the overall experimental poverty rate is

the same as the current official measure in 1997 (the latest year of available data). 2

Citro and Michael, pp. xvi, xvii, and 3.

3

U.S. Census Bureau
The NAS panel proposed changes to the poverty thresholds, the resource definition, family equivalence scales,

and methods for updating the thresholds from year to

year, but recognized that setting a poverty level is a separate matter. The panel members suggested a level that

they regarded as reasonable; it was higher than the current level. This report does not advocate any particular

poverty level, but takes a ‘‘standardized’’ approach to

facilitate comparisons of alternatives.

Some recommendations could not be implemented here

because necessary data (or model estimates) are not available from the March CPS. They include deducting child

support payments from the disposable income of the

payer3 and adding the value of benefits received under the

Special Supplemental Nutrition Program for Women,

Infants, and Children (WIC) and the School Breakfast Program to income. These suggestions will be investigated in

the future using the SIPP, where data on these items are

readily available.

The report closes with two sections, one that discusses

data limitations and opportunities in major surveys for

more completely implementing the NAS panel recommendations, and another that identifies directions for future

research. The appendixes provide a more extensive set of

empirical estimates reflecting the specific recommendations, as well as estimates showing results from implementing several recommendations simultaneously where

the levels of poverty have not been adjusted to match the

actual official rate in 1997. More detailed descriptions of

the methods used to derive experimental poverty estimates are presented in Appendix C.4

III. EFFECTS OF THE NAS PANEL RECOMMENDATIONS ON POVERTY ESTIMATES

This section describes results from estimating the effect

of modifications recommended by the NAS panel, one or

two at a time, on the overall level of poverty and on the

number of people classified as poor in 1997.5 Corresponding results for particular subgroups in the population are

presented in Appendix A. The reader should note that

results presented in this section regarding the effects of

one or two specific recommendations cannot simply be

summed to estimate the overall effect of implementing

multiple recommendations. It is also important to note

that the measures presented in this section do not achieve

consistency between resources and thresholds. While this

analysis is informative and relevant to our understanding

of the elements in a poverty measure, no measure in this

section can be considered a technically sound measure of

who is poor. These measures are presented to provide an

incremental view of the effect of each recommended

change.

A. Recommendations Pertaining to Thresholds

Thresholds based on Consumer Expenditure Survey

data. The NAS panel recommended that poverty thresholds represent a budget for food, clothing, shelter (including utilities), and a small additional amount to allow for

other common needs (such as household supplies, personal care, and nonwork-related transportation). A threshold for a reference family type should be developed using

actual consumer expenditure data and updated annually

to reflect changes in expenditures on food, clothing, and

shelter over the previous 3 years or the most recent 3

years for which data are available. The reference family

threshold should be adjusted to obtain additional thresholds that reflect the needs of different family types.

The NAS panel recommended, more specifically, that

the reference family threshold be calculated by multiplying a ‘‘designated percentage’’ of median expendituresmoney spent on food, clothing, and shelter and utilities

(FCSU) for two-adult, two-child families—by another ‘‘designated multiplier’’ to account for other common needs.

These other needs refer to such goods and services as

household supplies, personal care items, and other items

not explicitly measured in the amount for FCSU.

Based on its review of data from the Consumer Expenditure Survey, the NAS panel concluded that a reasonable

range is between 78 percent and 83 percent for the ‘‘designated percentage’’ of the median FCSU expenditures and

between 1.15 and 1.25 for the ‘‘designated multiplier.’’

These conclusions were based on an analysis of consumer

expenditure data, consideration of the values of other

thresholds (such as expert budgets, half-of-median relative thresholds, and a threshold derived from subjective

survey questions about the poverty line), and the panel’s

judgment.6

Figure 1 presents estimates of the poverty rates when

this range of assumptions is used to produce the thresholds. The resource measure used here to determine poverty status is money income. The results are poverty estimates that range from 11.7 percent to 14.2 percent in

1997, compared with the official poverty rate of 13.3 percent. The first measure uses the high end of both recommended ranges, i.e., 83 percent of median FCSU and 1.25

as the multiplier for other needs. These calculations result

in a poverty threshold for the reference family of $17,160

for 1997. The last measure uses 78 percent of the median

3

Citro and Michael, p. 244.

4

The March CPS microdata files are available for independent

research at http://www.ferret.bls.census.gov/cgi-bin/ferret. A povertymeasurementresearchdatafileisavailableathttp://www.census.gov/

ftp/pub/housing/povmeas/. 5

Unless noted otherwise, poverty status in this report is estimated only for those persons in the poverty universe, as traditionally defined. The poverty universe excludes inmates of institutions,

Armed Forces members in barracks, and unrelated individuals

under 15 years of age.

6

Citro and Michael, pp. 6 and 146. Also, see pp. 54-57, 106, and

147-154.

4

U.S. Census Bureau
and 1.15 as the multiplier, yielding a threshold of

$14,836. Using midpoints of the ranges yields a poverty

threshold of $15,998 for 1997. This compares with the

official threshold for a two-adult, two-child family of

$16,276. The poverty rate based on using the midpoints

of the ranges for the two multipliers is 12.9 percent,

slightly under the 13.3 percent official poverty rate.

Because these thresholds, calculated for the two-adult,

two-child family only, do not by themselves take account

of different family sizes and composition, the results presented above are implemented using the equivalence scale

implicit in the official thresholds to make these adjustments. The next section discusses various alternative

approaches to equivalence scales.

Adjusting thresholds for family size and composition. Given an appropriate poverty threshold for a reference family of two adults and two children, the NAS panel

recommended that adjustments should be made to reflect

the needs of different family types, that is, families with

different numbers of adults and/or children. The panel

recommended that the reference threshold be adjusted by

means of an ‘‘equivalence scale’’ to determine thresholds

for other family types.

More specifically, the panel recommended a twoparameter equivalence scale. One parameter reflects that

children under age 18 consume less on average than

adults consume - 70 percent as much in the panel’s proposal. The other parameter reflects economies of scale

available to larger families by adding a decreasing amount

to the scale value for a single person for each additional

family member. Although a four-person family may need

approximately twice as much for food and clothing as a

two-person family, other needs, such as housing and

transportation, are not additive in the same way. Acknowledging that the choice of an equivalence scale cannot

avoid arbitrariness, the panel suggested a range of 0.65 to

0.75 for the economies of scale parameter.

Reflecting the lack of scientific consensus on the most

appropriate form for the equivalence scale, this report presents estimates showing the range recommended by the

panel. They are supplemented with estimates based on a

scale that treats children as though they consume as much

as adults, and an alternative three-parameter scale. (See

Appendix C for details.)

The NAS panel’s choice of a two-parameter scale was an

attempt to be consistent with the cost-of-raising-children

literature and to smooth out increases in the scale for

larger family sizes. Recent research suggests an alternative three-parameter scale that might be more appropriate

for childless families.7 This scale attempts to reconcile differences between singles and childless couples, singleparent and two-parent families, and the cost-of-raisingchildren literature.

The three-parameter scale shown here allows for the

first child in a single-adult family to increase the scale

more than the first child in a two-adult family. It also

restricts the relationship between two-adult and one-adult

families so that the scale for the two-adult family is 41

percent more than the scale for the single-adult family.

This implies a ratio of economies of scale for these two

groups that is in between those implied by the current

official measure, 29 percent, and that of the panel’s lower

bound, 57 percent, respectively.

Figure 2 shows that using the equivalence scales recommended by the panel and comparing those thresholds

with money income yields poverty rates ranging from

12.3 percent to 13.4 percent. The figure illustrates the

effect of varying the scale parameter and the adult equivalent parameter used in each calculation of the twoparameter scale. Using the midpoint of their recommended range for both parameter values, 0.70, produces

a poverty rate of 12.7 percent, which is smaller than the

13.3 percent based on the current measure. The alternative three-parameter scale results in a poverty rate of 13.1

percent.

7

Betson, 1996.

 

 	
 

 
	



 

 	

		











 
      

 
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5

U.S. Census Bureau
Adjusting thresholds for geographic differences in

housing costs. Variations in housing costs can be significant across areas of the country and housing expenditures are a large component of the poverty budget. As a

first and partial step to account for cost-of-living differences among geographic areas, the NAS panel recommended that the housing component of poverty thresholds be adjusted for geographic differences in the cost of

housing. Available data from the 1990 decennial census,

analyzed with a methodology developed by the Department of Housing and Urban Development (HUD) to estimate rents for comparable units in different localities, permit the development of adjustments for metropolitan

areas that fall within several population size groups in

each of the nine Census Bureau divisions of the country.

The NAS panel implemented a modified version of the

HUD approach with 1990 census data to determine

whether interarea housing cost index values could be

developed that were reasonably similar to findings in the

scientific literature. The panel concluded that this

approach represents a modest step in a necessary direction but that limitations remain. The procedure takes

account of geographic differences in housing costs, but

not differences in other costs, and even for housing costs

it assigns index values to people in some areas that are in

error.8 Because of limitations of the available data, the

panel recommended additional research to determine a

method for updating measures of housing costs more frequently than every 10 years.

Figure 3 presents the results from implementing the

panel’s procedure for adjusting thresholds for geographic

differences in the costs of housing using the current official thresholds (see Appendix C for details). Again, money

income is used to compare to these thresholds to determine poverty status. As shown, this approach leads to a

poverty rate of 13.0 percent in 1997, slightly lower than

the official rate of 13.3 percent.

While overall rates are quite close, the important effect

of the geographic adjustments is that there are fewer poor

in areas with relatively low living costs and more in areas

with relatively high living costs. Thus, standardized poverty rates estimated with these geographic adjustments

are lower in the South and Midwest, where housing costs

are lower, and higher in the Northeast and the West (see

Appendix Table A3a for more details).

8

Citro and Michael, p. 199.

 

 	
 

 
	 	
 	
 

	


 

 	

 





 


 


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6

U.S. Census Bureau
B. Recommendations Pertaining to Resources

Adjusting resources for food stamps and school

lunch programs. To take account of the increase in

family resources associated with receiving food stamps

and subsidized school lunches, the NAS panel recommended that the value of these near-money benefits be

added to money income in calculating resources available

to the individual or family. Following the panel’s recommendations for calculating available resources, estimates

are derived by adding to reported cash income the face

value of food stamps as reported in the CPS, and the subsidized value of school lunches for recipients as calculated

by the U.S. Department of Agriculture9 (see Appendix C

for details).

To show the effect on poverty estimates of these programs we add the value of these benefits to money

income and compare the total to the official poverty

thresholds. Figure 4 shows that adding the face value of

food stamps to resources reduces the overall poverty rate

in 1997 from 13.3 percent to 12.7 percent. Including only

the subsidy for school lunches as a resource results in a

poverty rate of 13.0 percent, while including both reduces

the poverty rate to 12.4 percent.

Adjusting resources for the value of housing subsidies and home energy assistance. Housing subsidies

are significant additions to resources, and the NAS panel

recommended that their value be included in the resource

measure. Because the March CPS ascertains residence in

such housing but not the values of rent paid or of rent

subsidies, more complex procedures are necessary to estimate the value of these subsidies. While noting both the

need for additional research to improve the accuracy of

subsidy estimates and the virtues of using the SIPP for this

purpose, the panel recommended as an interim approach

the procedure developed by the U.S. Census Bureau using

the 1985 American Housing Survey (AHS) updated to the

current year using the Consumer Price Index (CPI) for residential rent (see Appendix C for details). As shown in Figure 5, using official thresholds and including this valuation

of subsidies for housing in resources would reduce the

overall poverty rate from 13.3 percent to 12.8 percent in

1997.

Home energy assistance is another means-tested government subsidy which the NAS panel recommended be

included as a resource. These benefits are valued based

on reports of home energy assistance received for heating

during the six coldest months of the year (see Appendix C

for details). The effect of including these benefits on the

overall poverty rate in 1997 was quite small, resulting in a

9

This amount includes not only a subsidy for free and reduced

price meals but also a subsidy for regular priced school lunches.

 

 	
 
 	 
 	

	
 
 

	


   

 	

 

  



 
      

 
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U.S. Census Bureau
poverty rate of 13.2 percent, as shown in Figure 5. Computing the combined effect of both programs results in a

poverty rate that is not different from that of including

housing subsidies only.

Adjusting resources for child care and other workrelated expenses. For many families with children,

child care costs must be paid if both parents are to earn

labor market income. Regardless of whether they have

children, workers usually must also pay the costs of commuting between home and work, and many have other

work-related expenses (such as uniforms, union dues,

licenses, permits, and tools). Because income that is used

to pay such work-related expenses is not available for

consumption, the NAS panel recommended that these

costs be subtracted from income to calculate individual or

family resources.

We implement three approaches to estimate child care

expenses. The first approach closely follows the method

used in the panel’s report to subtract these costs from the

income of families in which all resident parents work. The

amount subtracted cannot exceed the earnings of the parent with lower earnings or a cap that is adjusted annually

for inflation (whichever value is lower). Because the March

CPS does not ask about actual child care expenses, the

panel offered an approach to impute whether a family

incurred child care expenses and, if so, the amount spent

using SIPP data (see Appendix C for details).

The second method for valuing child care costs imputes

the incidence of child care expenses, as in the method

above, but then subtracts a flat amount from resources

based on earlier deduction guidelines from the Food

Stamp program and the former Aid to Families With

Dependent Children (AFDC) program for child care. In particular, these programs have permitted parents to deduct

from countable income some out-of-pocket spending for

child care deemed necessary for the parent to work or participate in training. We base child care valuations on these

figures because these program deductions for child care

are a clear normative statement of what the Federal government regarded as a ceiling on the cost that is necessary

for employment. To take account of changing costs over

time, we update them for inflation using the Consumer

Price Index for all items (CPI-U).

Imputing child care expenses only for some of the

working families with dependent children, as is done in

both methods described above, is somewhat problematic.

Since no information about child care expenditures is

available in the CPS, which families are assigned expenses

is determined on the basis of a probability model in the

first two methods described above (see Appendix C). The

third approach for estimating child care expenses avoids

this difficulty by subtracting a fixed amount from the

income of all families with children and working parents.

We implement this approach for parents with children who

worked by subtracting from income a value representing

85 percent of the median cost of child care paid by families as reported in the SIPP (see Appendix C for details).

This method follows the panel’s method for valuing other

work-related expenses described below.

Regarding other work-related expenses, the NAS panel

recommended that for each working adult, following a

similar argument as above, a flat amount (adjusted annually for inflation and not to exceed earnings) be subtracted

from earnings to account for work-related transportation

and miscellaneous expenses. In developing empirical estimates, the panel chose to subtract from earnings a value

representing 85 percent of the median work-related

expenses for all workers. We apply these procedures to

estimate the effect on poverty of these other work-related

expenditures individually, and in combination with child

care expenses.

For families with child care expenses, the panel recommended that the total of child care costs plus other workrelated expenses for the parent with the lower earnings

should not exceed that parent’s earnings. We implement

this cap when estimating combined expenses using the

model and the median child care methods, but not with

the method using welfare deduction guidelines (see

Appendix C for details).

 

 	
 
 

 





	 	
 



	 

 

	


 

 	



















 
      

 
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As shown in Figure 6, subtracting child care and other

work-related expenses from money income results in poverty rates ranging from 14.4 to 14.7 percent depending on

which estimation method is used. Each measure shown

here represents a different method of valuing child care

costs. The first measure shown uses a model similar to

that used by the panel, the second measure uses the child

care deduction based on the AFDC program, and the third

measure uses 85 percent of median expenses as measured in the SIPP. Other work-related expenses are valued

the same in all three measures.

Including such expenses in a poverty measure affects

the kinds of families who are classified as poor. As can be

seen in Appendix Table A6, these calculations result in

higher poverty rates for children and for people in families

with one or more workers than we normally see under the

official measure.

Adjusting resources for taxes. The payment of Federal and state income taxes and social security payroll

taxes is mandatory. Such tax payments represent a cost of

obtaining income, and hence are not available for consumption spending. The refundable Federal Earned Income

Credit (EIC), however, increases income available for consumption spending. The NAS panel recommended that the

value of taxes be subtracted from income and the value of

the EIC be added to income to obtain a more appropriate

measure of available resources. Sales and property taxes

do not, according to the panel, need to be subtracted from

income, because they are counted as expenditures on the

threshold side, as recommended by the panel.

Taxes paid and income received from the EIC are not

directly measured in the CPS, and must be estimated using

microsimulation models. The panel noted that the simulation of social security payroll taxes is quite straightforward, but the Census Bureau’s current simulation model

using the CPS to estimate other tax effects has important

limitations. One important limitation is that simulated tax

estimates assign values based on liability or eligibility

rather than on actual taxes paid or credits received. Therefore, the effect of taxes on poverty estimates, as illustrated, may be overstated if actual taxes paid or earned

income credits received are markedly lower than values

assigned by the model. However, while urging the Census

Bureau to continue its work to develop improved estimates using the SIPP, the panel highlighted the CPS tax

model as providing the best currently available estimates.

Figure 7 presents estimates of the effects of taxes and

the EIC on the overall poverty rate in 1997 using the CPS

tax models (see Appendix C for details). Taking account of

Federal taxes, but excluding the role of the EIC, has virtually no effect on overall poverty; the rate is unchanged at

13.3 percent. This result follows because families with

pre-tax income near the official poverty thresholds do not

have significant Federal income tax liabilities. State

income taxes by themselves have no overall effect on poverty, but the social security payroll tax (FICA) by itself

leads to a higher poverty rate of 14.1 percent. Taking

account of these taxes and the EIC, the poverty rate falls

to 12.7 percent, because the increase in poverty rates

resulting from the social security payroll tax is more than

counterbalanced by the reduction that results from the

EIC.

Using after-tax income rather than before-tax, as the

current official measure does, alters estimates of poverty

rates for different population subgroups. As shown in

Appendix Table A7, accounting for taxes with the EIC has

the effect of lowering poverty rates for such groups as

children and for people in families with one or more workers.

Taking account of in-kind transfers combined,

before and after taxes. We have shown the effect of

different in-kind transfer programs individually on poverty

estimates, and have seen that, generally, these effects are

quite small. Often, however, people who are economically

disadvantaged receive benefits from more than one program.The joint effect of all in-kind transfer programs on

poverty estimates can be shown by combining together

the value of benefits received from food stamps, school

lunches, housing subsidies, and heating assistance

together and recalculating poverty rates.

 

 	
 
	 	 		
 

	 

  

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As shown in Figure 8, including a value for all the in-kind

transfers listed above and adding these to money income

reduces poverty rates from 13.3 percent under the official

measures to 11.8 percent. If we alternatively add these

values to after-tax income in order to also capture the

effect of the EIC, the overall poverty rate is additionally

reduced to 11.1 percent for the year 1997, a decline of 2.2

percentage points.

C. Recommendations Pertaining to Thresholds and

Resources

Taking account of medical care costs. Highlighting

the enormous value of public and private health insurance

coverage, the NAS panel concludes from a detailed evaluation of existing and proposed approaches that there is a

fundamental problem with trying to combine nonmedical

and medical care needs and resources in a poverty measure because the two components measure fundamentally

different things.10 The nonmedical measure assesses, for

the previous year, the actual ability of families and individuals to meet their needs for goods, such as food and

housing; needs that are universal and cannot be deferred.

The medical component, in contrast, measures a risk that

may or may not actually materialize. Hence, someone in a

10Moon, 1993.

 

 	
 	
   	
 
 

 

	




 	


 









 







  





 

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U.S. Census Bureau
high-risk health category may have a good year and need

only minimal medical care, but no one can have a year in

which he or she does not need to eat. In recognition of

this difference in nonmedical and medical needs, the NAS

panel recommended the development of one or more distinct ‘‘medical care risk’’ indexes, but that such indexes

should be kept separate from the measure of economic

poverty. Work is proceeding at the Department of Health

and Human Services to examine the possibility of developing such an index.11

Noting that medical out-of-pocket (MOOP) expenses

reduce disposable income, the NAS panel recommended

that these expenses be subtracted from the family

resource measure. This yields an economic poverty measure that is sensitive to changes in the health care financing system that increase (or reduce) disposable income

and thereby reduce (or increase) economic poverty. The

panel’s recommended measure excludes amounts spent

on medical care from both sides of the comparison, i.e.,

the thresholds do not account for medical care needs, and

resources are calculated net of expenditures on health

care. For this reason, we show a measure which compares

cash income minus MOOP with two different thresholds.

The first measure uses the official threshold to show the

incremental effect of subtracting MOOP from cash income.

Figure 9 shows that this calculation yields a poverty rate

of 16.3 percent, three percentage points above the official

rate. The second measure shown compares income minus

MOOP with the experimental thresholds that, by construction, do not include medical needs. Doing this, the procedure recommended by the NAS panel, leads to an overall

poverty rate of 15.6 percent in 1997, compared to the

official rate of 13.3 percent (see Figure 9.)

The panel’s recommendations on handling the need for

medical care have inspired more debate than any other

element in its report. Their recommendations also raised

issues of implementation. Their treatment of medical

needs would require surveys and administrative data sets

either to ask families directly and extensively about outof-pocket medical expenditures or, as was done for this

report, to use statistical methods to assign amounts to

each family. Their estimate of the impact of MOOP on poverty rates was relatively large, as is ours.12

The method that the panel used to value these

expenses in a poverty measure using survey data such as

the CPS is somewhat complex. Data from the 1987

National Medical Expenditure Survey (NMES) were used to

develop a model that assigned the occurrence of such

expenditures and the amount spent. Once these amounts

were assigned to families then the aggregate amount

assigned across all families is adjusted to match benchmarks developed from the Health Care Financing Administration’s National Health Accounts.13 This step introduces

some inconsistency in a complete poverty measure in that

no other element described so far in the construction of a

poverty measure is adjusted to match independent aggregate estimates. Other elements in the panel’s proposed

poverty measures suffer from nonsampling error, such as

underreporting of benefits, but nevertheless are used

unadjusted in the measures reported here, as they are in

the official measure. The result of this inconsistent treatment may be an overstatement of the effect of MOOP on

poverty rates (see Appendixes C and F for further discussion of these issues).

In light of both the conceptual and practical issues

raised by the panel’s proposal for handling medical needs,

an alternative treatment might be to include medical outof-pocket expenses on both the threshold and resource

sides, adding out-of-pocket needs to the thresholds and

11See Doyle, 1997a and Short and Banthin, 1995. 12See Betson et al., 1997c. Other research (Doyle, 1997) has

shown the marginal impact of MOOP to be less, though methods

underlying these estimates differ.

13See Betson, 1995b.

 

 	
 	
  


	 	 

	




 	

 		

 















  


 		

 





     
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U.S. Census Bureau
leaving income to cover such expenses in resources.14

This treatment would parallel the panel’s recommendations for poverty thresholds based on expenditures for

food, clothing, shelter, and a little more, but adds amounts

to those thresholds for out-of-pocket medical spending.

The threshold for the reference family would include medical out-of-pocket spending as reported in the CEX along

with spending on the basic bundle of food, clothing, shelter, and utilities. This threshold could be applied to different family types based on health care spending patterns

as observed in the CEX or the NMES. This second method

of accounting for medical needs would result in different

threshold amounts based on size of family, age of family

members, and health insurance coverage status.

The panel did not pursue this alternative because it

would require a much larger number of thresholds to

reflect different levels of medical care need.15 They argued

that medical care needs differ from the need for food or

housing in that not every family requires medical care in a

given year, but when they do, the associated costs may be

extraordinarily large. Assigning an average or median

expenditure to incorporate medical care needs in the

thresholds may overestimate the costs for many families

and underestimate the cost for a few families. The panel

concluded that it would be impossible to capture the

actual variation of medical needs by variations in the

thresholds and that this could lead to what the panel

termed ‘‘erroneous poverty classification.’’ For these reasons we use only the panel’s recommended method in the

experimental measures shown, but encourage additional

research in this area.16

Adjusting for homeownership. For homeowners with

high or no mortgage payments or other expenses, out-ofpocket shelter expenditures can differ substantially from

those paid by renters. The NAS panel noted that this difference could be taken into account if a measure were developed indicating the amount that homeowners would pay if

they were renting their homes.17 This measure, the estimated shelter costs for owner occupants, could replace

the owner’s out-of-pocket expenditures on the threshold

side (see Appendix C). To balance this, a measure of the

implicit income of homeownership should be included in

the incomes of homeowners to adjust for their advantaged

situation regarding housing costs. The NAS panel used an

out-of-pocket measure for ‘‘processing convenience,’’ but

their preferred approach would account for the cost of the

flow of services for homeowners.18

The Census Bureau publishes annually a poverty measure that includes a measure of net return to home equity

for homeowners. This value represents the hypothetical

income that a household would receive if it chose to shift

the amount held as home equity into an interest bearing

account (see Appendix C for details). Although this measure provides a basis for illustrating the potential importance of developing and implementing a well-founded

measure of imputed rent, it is not complete. It is not consistent with a threshold measure that only counts out-ofpocket expenses as reported in the CEX.

In order to prepare a more consistently defined measure, we substitute out-of-pocket shelter expenditures

with estimated rental shelter costs for homeowners in the

calculation of thresholds, and we add net return to home

equity to resources (see Appendix C for details). This calculation brings consistency to our poverty measure

because both sides account for the implicit costs and the

implicit income of homeowners.

In addition to accounting for imputed shelter costs for

homeowners, this method would also allow us to value

the total cost of subsidized housing in our thresholds,

rather than the out-of-pocket costs that would be counted

without this imputation. This method of constructing the

thresholds would also be consistent with the addition of

housing subsidies received as income on the resource

side, as shown earlier, because it would then reflect the

total cost of housing that subsidized renters face. Without

this imputation on the threshold side, it is inconsistent to

add the value of housing subsidies to income. However,

lacking additional research, we have not included this

adjustment here.

Figure 10 shows that including an imputed rental shelter cost for homeowners in the thresholds and comparing

to money income results in a poverty rate of 12.2 percent.

Given that the estimated shelter costs for owner occupants with mortgages are lower than their out-of-pocket

expenditures and that a sizable majority of reference families have mortgages, this is as expected (see Appendix C).

Including the value of homeownership as income, by adding net return on home equity, reduces the overall poverty

rate in 1997 from 13.3 percent to 12.1 percent.19 When

these two pieces are combined so that the resource and

14See Bavier, 1998 and a summary of Marilyn Moon’s proposal in

Citro and Michael, p. 236. 15Citro and Michael, pp. 223-237. 16Another method to address medical care is to add health

insurance benefits to income, as the Census Bureau does in its

annual publication of alternative poverty statistics. This approach

was not recommended by the panel and is the subject of some

debate. To achieve consistency when we add a value for total

insurance benefits to resources, we must add the value of total

medical needs, not just out-of-pocket needs, into the thresholds.

While there is not agreement on the degree of inclusion of medical

needs in the original official thresholds, it is reasonable to state that

the current thresholds do not reflect medical needs sufficiently,

especially for the aged. Thus, adding insurance benefits to resources

without adjusting thresholds is not appropriate. However, we show

that adding the value of these insurance benefits to income reduces

the poverty rate in 1997 from 13.3 percent to 12.0 percent (see

Appendix C for details). 17The panel referred to this value as ‘‘imputed rent.’’ This value

would include expenditures for maintenance as well as rent.

18Citro and Michael, p. 148. 19This figure is not significantly different from the poverty rate

of 12.2 percent that results from including an imputed rental shelter

cost in the thresholds.

12

U.S. Census Bureau
threshold measures are consistent, the resulting poverty

rate is 11.0 percent. This method of accounting for homeownership, then, results in fewer people being classified

as poor.

Changing the unit of analysis. The NAS panel recommended that the definition of ‘‘family’’ should be broadened for the purposes of poverty measurement to include

cohabiting couples and that research should be conducted

on the extent of resource sharing among roommates and

other household and family members to determine if the

definition of the unit of analysis should be modified further. This research, as recommended by the panel, should

include an assessment of the effects on poverty rates of

changing the unit of analysis by treating cohabiting

couples as ‘‘families.’’

The panel noted that insofar as cohabiting couples,

roommates, and other household members benefit from

economies of scale, the current measure overstates the

poverty rate for such people. The panel also noted that

cohabiting couples typically pool resources, and many

exhibit considerable stability in their living arrangements,

so that it makes sense to treat them like married-couple

families for purposes of poverty measurement.

This report pursues the panel’s recommendations

regarding the family definition used to measure poverty

by implementing four new units of analysis. First, the

‘‘cohabiting-couple unit of analysis’’ begins with the official unit of analysis — the primary family (the householder

and any relatives of the householder) — but also includes

in the unit of analysis the unmarried (cohabiting) partner

and any children of the unmarried partner who are present

in the home. Second, the ‘‘housemate-roommate unit of

analysis’’ begins with the primary family but also includes

any housemates, roommates, and foster children of the

householder, and any children of these persons. Third, the

‘‘roomer-boarder unit of analysis’’ begins with the primary

family but also includes any roomers and boarders in the

home. Fourth, the ‘‘household unit of analysis’’ includes all

persons in the household as a single unit (see Appendix C

for details).

Poverty estimates computed based on these different

units of analysis are shown in Figure 11. Broadening the

unit of analysis by assuming that more and more people

in a housing unit share resources results, not surprisingly,

in lower poverty rates. The official poverty rate of 13.3

percent in 1997 would be 12.7 percent using the

cohabiting-couple unit, 11.7 percent combining the

cohabiting-couple and housemate-roommate units, and

11.5 percent using the household as the unit of analysis.

D. Updating Thresholds Over Time

The NAS panel recommended a procedure for annually

updating the reference family threshold that would automatically, over time, reflect real changes in the consumption of basic goods and services. They argued that this

procedure would avoid the need for periodic readjustments in the threshold level to account for real changes in

basic consumption that would inevitably produce disruptions in the time series. The panel believed that this procedure represented a middle ground between the current

approach of updating the thresholds only for price

changes (inflation), and an approach to updating thresholds which tracks changes in total consumption. The panel’s intent was to update the thresholds in a ‘‘quasirelative’’ manner that would change with changes in the

real consumption of basic necessities.

The panel recommended using the same procedure to

calculate the initial thresholds for each subsequent year.

Basically, this amounts to using the change in the median

expenditures on the basic bundle composed of food,

clothing, shelter, and utilities (FCSU) for the reference family in the CEX. The panel also recommended producing a

second set of poverty rates using thresholds that are

updated only for price changes.

The panel expected that the median expenditures on

the basic bundle by the reference household would

increase by more than the inflation rate but by less than

the change in total consumption (as measured by per

capita Personal Consumption Expenditures (PCE)20). It was

20U.S. Department of Commerce, Statistical Abstract of the United

States, 1997, Table No. 685.

 	

 	
 	
  


 

 





 	







 

	

	 	

	

 

  







 
      

 
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U.S. Census Bureau
thought that this method of updating would produce an

elasticity with respect to total consumption of 0.65.21 That

is, using the National Income and Product Accounts (NIPA)

for PCE, the panel estimated that the cost of the basic

bundle will rise at a rate of 65 percent of the increase in

the cost of total consumption minus health care. The panel’s motivation came from the observation that the poverty threshold did not keep up with increases in median

income since the 1960s.

Table 1 shows the percent changes in five alternative

indexes for three time periods — 1961-73, 1973-86 and

1986-96.22 The first column shows the panel’s recommended method for updating the thresholds — the percent change in the median expenditures on the basic

bundle for the reference family. The next column shows

the current method for updating the official thresholds —

the CPI-U.23 The third column shows the percent change in

a measure of total consumption — the per-capita PCE (less

medical care). The fourth column shows the changes in

Table 1. Percent Changes in Alternative Indexes for

Updating the Thresholds for Three Time

Periods

Time period Change

in

median

FCSU

Change

in

CPI-U

Per

capita

PCE

less

medical

care

Median

aftertax

income

for

family

of four

Change

using

elasticity of

0.80

1961-1973 . . . . . . . . . . . . . . 58.4 48.5 108.7 105.6 94.2

1973-1986 .............. 135.2 146.8 188.1 138.6 140.2

1986-1996 . . . . . . . . . . . . . . 44.9 43.2 56.4 53.6 51.5

the median nominal after-tax income for a family of four,

and the final column shows the changes based on using

80 percent of the changes in real median after-tax income

for the family of four.

The table confirms the intuition of the panel for the first

time period. Between 1961 and 1973, the median expenditures on the basic bundle increased more than the CPI-U

but less than the per capita PCE. The table also shows that

this relationship between the change in the median expenditures and change in the CPI-U does not hold for all time

periods (see footnote about CPI-U-X1). It is also true that

the year-to-year changes in the median expenditures are

subject to substantial measurement error (due to the small

CEX sample size) that causes these changes to be more

volatile.

Table 1 also reflects that the increase in CPI-U adjusted

thresholds (the official poverty thresholds) during the

1960s did not keep up with the increase in living levels

and standards as given by the median after-tax income for

a reference family of four. Although these procedures yield

very different time trends between 1961-1973 because

enormous increases occurred both in real consumption of

basic goods and in real disposable income, they produce

similar results for the period from 1973-1986, and yield

nearly identical results for 1986-1996.

The table also presents another alternative updating

method – an 80 percent share of the change in the real

median after-tax income for the reference family of four.

This alternative index is a more relative updating method

and may more closely provide ‘‘an automatic mechanism

for updating the thresholds on an annual basis for real

changes in living standards.’’ How much the index

responds to changes in the typical level of consumption

(loosely reflected in median after-tax income) depends

upon what one chooses for an elasticity parameter. This

parameter would determine the responsiveness of the

thresholds over time to changes in after-tax median family

income. For example, those who believe that, over long

periods of time, the evolution of minimum resource needs

21Citro and Michael, pp. 154-157. 22These time periods are chosen to reflect the collection of the

CEX.

23The new CPI-U definition, based on rental equivalency, was

introduced in 1983. Prior to 1983, a comparable index is the

CPI-U-X1. The CPI-U-X1 increased 45.2% in the 1961-1973 period

and 132.2% in the 1973-1986 period.

 

 	
 

 
	



  
	

 

	




 	










 










 
      

 
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is fully relative would argue for an elasticity parameter of

1.0, which would yield a 1 percent change in the thresholds for each percent change in the after-tax median

income. Research based on the change in the views of the

U.S. adult population regarding poverty level income over

more than 40 years of the post World War II period, suggests that an elasticity of 0.80 would be appropriate.24 By

construction, this alternative index always lies in between

the changes in the CPI and the changes in the nominal

median income. As Table 1 shows, this alternate index

results in relatively similar changes during the other periods and a much larger change in the thresholds during the

1961-73 period.

Following the panel’s recommendation, in this report

we produce a time-series of poverty rates using two sets

of thresholds. One set is adjusted from year to year by the

change in the median expenditures on FCSU and another

set by changes in the CPI-U (see Table 2).

IV. COMBINING THE NAS PANEL RECOMMENDATIONS

In this section of the report we compute poverty measures that combine many of the elements shown in the

previous section. Any alternative measure of poverty will

combine most of these elements, but which combination

of elements is a matter for additional consideration and

broad policy discussion. In this section, we present several

illustrations of the many possible combined measures.

The measures that we present are only slightly different

variations on the overall poverty measure described in the

panel’s report. While we have presented and discussed

many alternatives in the previous section, several of these

alternatives are the subject of ongoing research and are,

therefore, not included here. The measures presented here

are, for the most part, complete and consistent measures

of poverty.

Table 2. Experimental Thresholds Using Alternative

Updating Methods: 1990-1997

[Dollars. 1997 as base year]

Year Current

official

threshold

FCSU

backdated

with

change in

median

FCSU

FCSU

1997

backdated

with CPI-U

1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . 13,254 13,342 13,028

1991 . . . . . . . . . . . . . . . . . . . . . . . . . . . 13,812 13,843 13,576

1992 . . . . . . . . . . . . . . . . . . . . . . . . . . . 14,228 14,253 13,985

1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . 14,654 14,791 14,403

1994 . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,029 15,166 14,772

1995 . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,455 15,545 15,191

1996 . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,911 15,744 15,639

1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . 16,276 15,998 15,998

The first experimental measure we show is referred to

as the NAS measure. This is a measure that is calculated in

a manner most similar to the measure described in the

panel’s report. While there are a few minor differences

from the measure that the panel recommended, they are

computational rather than conceptual in nature. More precisely, this measure is constructed in the following way:

Thresholds:

• Thresholds are set at the midpoints of the ranges recommended by the NAS panel - averaged over the three

most recent years - i.e., data for 1995, 1996, and 1997

are averaged for the 1997 threshold.

• The equivalence scale is a two-parameter version.

• Geographic indexes are those listed in the panel report.

Resources:

• Include the value of food assistance programs.

• Include the value of housing subsidies.

• Include the value of energy assistance (only heating

assistance).

• Subtract work-related and child care expenses using the

panel’s child care model.

• Take account of taxes as modeled in the CPS.

• Subtract medical out-of-pocket expenses (MOOP), modeled and calibrated to spending totals.

The second and third experimental measures that we

report use a different method of valuing child care

expenses, as described in Section III. These complete measures are referred to as DCM1 (Different Child Care

Method 1) and DCM2 (Different Child Care Method 2). The

second measure, DCM1, uses a percentage of median

child care expenditures estimated from the SIPP and the

third measure, DCM2, uses the amounts based on deductions for necessary child care in the AFDC and Food Stamp

programs. The third measure, DCM2, which uses the welfare method of valuing child care, is similar to the panel’s

method in its effect on poverty estimates but is easier to

implement (see Appendix C for details).

The fourth experimental measure we refer to as the

DES-DCM2 measure. This measure is constructed like the

DCM2, but, in addition to changing the child care computation, we also use a Different Equivalence Scale. For this

measure we use the three-parameter equivalence scale

described in Section III and AFDC allowances to value child

care expenses. We include it here to show the effect of

using a different equivalence scale in a complete poverty

measure.

Finally we show the NAS and the DES-DCM2 measures

without a geographic adjustment. These measures are

referred to as the NGA and the DES-DCM2-NGA measures.

These two measures are calculated exactly as the NAS and 24See Vaughan, 1993 and Fisher, 1995.

15

U.S. Census Bureau
the DES-DCM2 measures but the thresholds are not

adjusted for differences in the cost of housing in different

parts of the country. The geographic adjustment is

excluded because, as the panel noted, this element

requires more research and better data sources. This measure, then, reflects the assumption that the cost of meeting basic needs does not vary by geographic area.

Table 3 shows the poverty rates for all groups under

the official measure and the experimental measures

described above for the year 1997. As shown earlier, the

effects of varying different elements in these combined

measures are similar to the effects shown in Section III.

For example, the child care method based on median estimates from SIPP yields a larger proportion of families facing these expenses and, thus, results in higher poverty

rates. The geographic adjustment has the effect of lowering the poverty rate because relatively more officially poor

people become reclassified as nonpoor in low-cost areas

than nonpoor classified as poor in high-cost areas when it

is implemented. All measures shown here use the family

as the unit of analysis.

Table 3. Number of Poor and Poverty Rates of All

Persons Using Alternative Measures: 1997

Measure Number

(1,000)

Rate

(percent)

Official . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35,574 13.3

NAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41,224 15.4

DCM1a . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42,688 15.9

DCM2b . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41,460 15.4

DES-DCM2c

. . . . . . . . . . . . . . . . . . . . . . . . . . . 43,232 16.1

NGAd . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42,288 15.8

DES-DCM2-NGAe

. . . . . . . . . . . . . . . . . . . . . . 44,270 16.5

a Child care method based on SIPP medians. b Child care method based on AFDC program allowances. c Child care method based on AFDC program allowances and threeparameter equivalence scale. d NAS measure with no geographic adjustment. e Child care method based on AFDC program allowances, threeparameter equivalence scale, and no geographic adjustment.

A. Poverty Rates by Selected Characteristics

The next series of figures show poverty rates calculated

for various subgroups of the population for 1997 using

the official measure and some of the experimental measures described above. In the charts we show only three

of the alternative measures and the official measure for

comparison. The three alternative measures shown are the

NAS measure, the DES-DCM2 measure (with a different

equivalence scale and child care expense valuation

method), and the NGA measure (no geographic adjustments). Estimates for the other measures are in the tables

in Appendix B. All of the general results discussed below

apply similarly to those measures.

In this section, all alternative poverty measures are

‘‘standardized’’ to the official poverty rate for all persons

(see Appendix B for unstandardized rates). To do this, all

thresholds are adjusted by a factor, one for each measure,

in order to match the poverty rate of 13.3 percent for

1997.25 These measures are shown this way in order to

compare the differential incidence of poverty for these

subgroups implied by the alternative combined measures.

This method essentially holds constant the total poverty

rate, so that these comparisons can be made.26

As shown, the computation of different experimental

poverty measures changes our perception of the incidence

of poverty across the various subgroups listed there. For

example, as shown in Figure 12, all of the experimental

measures produce standardized poverty rates that are

lower for children under 18 years of age and higher for

the elderly (those over 65). In other words, under the

alternative measures, children make up a smaller share of

the poverty population while the elderly comprise a larger

share. Standardized poverty rates for nonelderly adults are

virtually unchanged by the experimental measures.

The experimental poverty measures also show differences in the incidence of poverty by other demographic

characteristics such as race and ethnicity. As seen in Figure 13, standardized poverty rates are somewhat lower

for Blacks using any of the experimental measures relative

to the official measure. This result is due to the inclusion

of in-kind benefits in the poverty measure and the relatively lower medical out-of-pocket expenses assigned to

Blacks in the alternative measure.

For people of Hispanic origin, who may be of any race,

poverty rates are similar across all the measures except

that they are lower using the experimental measures with

no geographic adjustment. This suggests that the additional elements in the experimental measure lower the

poverty rates of Hispanics but that they tend to reside

where housing costs are relatively high.

Figure 14 shows that people in families in which there

are no workers have lower standardized poverty rates

under the experimental measures. This result is due to the

greater likelihood of receiving in-kind benefits and incurring no work-related expenses. This figure also shows that

these experimental measures yield higher poverty rates

for people in married-couple families and lower rates for

those in female-householder families with no spouse

present, than the rates under the official measure.

While the net effect of geographic adjustment on overall poverty rates is small across most demographic subgroups, these adjustments do affect regional measures of

25The factors used are 0.91 for the NAS measure and the DCM2

measure, 0.90 for DCM1 and NGA measures, 0.89 for the DES-DCM2

measure and 0.88 for the DES-DCM2-NGA measures. The resulting

thresholds have no intrinsic meaning as a reference family threshold. They should be interpreted as artifacts of the analysis employed

here which include the effects of implementing all other proposed

changes described in the text (Citro and Michael, p. 248). 26While standardizing these rates helps us to compare between

groups, it can slightly distort our interpretation of who is poor. If

one group is more likely to have incomes near the poverty line, then

adjusting the poverty thresholds in this way can differentially affect

that group relative to others. See Johnson et al. (1998) for more

details.

16

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U.S. Census Bureau
poverty. Figure 15 shows that the main effect of the geographic adjustments is to increase poverty rates in the

Northeast and the West and to decrease standardized rates

in the Midwest and the South. The next chart shows

higher standardized rates in suburban areas, and lower

rates in nonmetropolitan areas (shown in Figure 16).

These results reflect the differential housing costs in these

areas as constructed in the geographic indexes.

Figure 17 shows the same poverty measures for a more

detailed list of age groups than we have shown earlier.

Here we see that, overall, the experimental measures

show lower standardized poverty rates than the official

measure for children. This is primarily true for children

over 6 years of age rather than for younger children. Nevertheless, these standardized rates still remain highest for

small children than any other age group, even under the

experimental measures. For the elderly, differences

between the experimental measures and the official measure are generally more pronounced for those over 75

than for those aged 65 to 75 years of age.

With regard to detailed racial and ethnic categories, the

experimental measures, with and without an adjustment

for geography, show slightly higher poverty rates for

White non-Hispanics than under the official measure (see

Figure 18). As we have seen, standardized poverty rates

for Hispanics are higher when the geographic adjustment

is included because many reside in the West where housing costs are higher. Poverty rates for Blacks, regardless of

ethnicity, are lower under the experimental measures than

under the official measure.

Poverty rates by family size reflect, among other things,

the choice of equivalence scales. Most of the alternative

measures shown here are adjusted using the twoparameter equivalence scale discussed earlier. Only the

DES-DCM2 measure uses a different equivalence scale, in

this case, the three-parameter scale discussed in Section

III. These experimental measures all show higher poverty

rates for families with two or three members than the official measure and lower poverty rates for all other family

sizes. The effect of the different equivalence scales is

most noticeable in the poverty rates for single people (see

Figure 19). The measure using the three-parameter equivalence scale shows higher poverty rates for this group than

the other measures yield. That scale also yields lower poverty rates for people in families of five or more members.

Differences between the official and the experimental

measures are greatest for the largest families.

Citizenship status is correlated with poverty status,

with noncitizens having a higher probability of being poor

than citizens under the official measures and the experimental measures. Under the experimental measures that

adjust for geographic differences, poverty rates are higher

 	  

  
 

 

	 
	
 	 
 
 
	 

	  	 

 	

 
  

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U.S. Census Bureau
for both naturalized citizens and noncitizens than they are

under the other measures that do not account for geographic differences (see Figure 20).

Finally, while poverty rates are higher for the disabled

than the nondisabled under all measures, standardized

poverty rates shown here are considerably lower for the

work-disabled under the experimental measures than they

are under the official measure.27 In other words, the workdisabled, people with a health problem that prevents them

from working, represent a smaller share of the poor under

the alternative measures. This difference is primarily due

to the lower nondiscretionary expenses, such as workrelated expenses, attributed to the work-disabled poor

under the experimental measures. It is important to note

here that none of the methods discussed in Section III on

valuing medical out-of-pocket expenses takes account of

health or disability status. The average of MOOP expenses

that are assigned to the poor disabled is slightly below

that for all poor persons.

B. Experimental Poverty Estimates Over Time

Thus far, we have seen how the experimental measures

differ from the current official measure for a given calendar year, 1997, and for different subgroups of the population. Now we examine how these measures behave over

time relative to the official measure. To do this we construct two separate time series. The first one uses 3-year

averages from the CEX to estimate thresholds for each

year from 1990 to 1997. The second series uses the same

threshold as the first for the year 1997, but then backcasts to generate a new set of thresholds based only on

changes in the CPI-U between years. Both sets of thresholds are shown in Table 2 of section III for the reference

two-adult, two-child family.

Again, we examine only ‘‘standardized’’ poverty rates.28

For these standardized measures, the experimental poverty thresholds are adjusted to produce the same rate as

the official rate for 1997. Thresholds for the other years in

the series are adjusted by that same factor. They do not

necessarily match the official rate in those earlier years.

27More specifically, a person is work-disabled if he or she meets

any of the following criteria: 1) has health problems which prevent

or limit work, 2) ever retired or left work for health reasons, 3) was

not working because of long-term physical or mental illness, 4) did

not work at all in previous year because of illness, 5) under age 65

and covered by medicare, 6) under age 65 and a recipient of SSI, or

7) received veteran’s disability compensation.

28Poverty rates that are not standardized are shown in the

appendix tables.













       	 
              	 	


 	

	 
	
 	 
 		 	  

 	

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This approach allows us to examine trends in the rates

while essentially holding the initial level constant.29

Figure 21 shows three of these standardized poverty

rates using thresholds updated with CEX data. The figure

shows that, over the 1990-97 period, rates under the official and experimental measures behave similarly: increasing over the 1990-93 period and decreasing over the

1993-97 period. The official rate rose from 13.5 percent to

15.1 percent from 1990 to 1993 and fell to 13.3 percent

by 1997 (not significantly different from 1990). All of the

standardized experimental rates show similar patterns

with only some slight differences.

In 1990, the experimental measures are higher than the

official measure. The increase in poverty rates from 1990

to 1993, however, is similar across all the measures. All of

the experimental rates, while constrained to be equal in

1997, are higher than the official rate in 1993, suggesting

that these measures declined at a faster rate over this

period than the official measure. One important reason for

the accelerated decline in the experimental poverty rates

in this later period was the effect of an expanded EIC, a

program that is not accounted for in the official poverty

measure.

Differences in trends in poverty rates are also partly

explained by the different trends in the thresholds (see

Table 2 for the thresholds). Between 1990 and 1993, the

official thresholds and the experimental FCSU thresholds

increased by a similar percentage, about 11 percent. From

1993 to 1997, the experimental thresholds updated using

the CEX increased at a lower rate than the official thresholds, 8 percent as opposed to 11 percent.

Figure 22 shows trends based on varying the thresholds from year to year with changes in the CPI-U only. Here

we see that the trends of the measures are not statistically

significantly different from that of the official measure.

Figure 23 shows the difference between the two updating

methods more clearly. Looking only at the NAS measure

using the two updating methods shows that both measures follow a similar trend over the period. While the

measure updated with the CEX is above the measure

updated for price changes over this time period, increases

from 1990 to 1993 and decreases in poverty rates from

1993 to 1996 are not statistically different using the two

measures.

29As noted earlier, see Johnson et al., 1998, for an explanation of

the possible problems associated with this approach.



















	
 


	 
	
 	 
 	 

 
 

 	

   


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V. DATA ISSUES AND OPPORTUNITIES

We have shown a variety of elements that could be

included in an improved measure of poverty. We have also

shown combinations of most of these elements to illustrate alternative poverty measures. This section discusses

the strengths and limitations of key data sets for implementing an alternative poverty measure, and the opportunities for a more complete implementation of the NAS panel’s recommendations in view of current and possible

future data collection.

A. Survey of Income and Program Participation

(SIPP)

A primary recommendation of the NAS panel was to

make the SIPP rather than the CPS the official source for

measuring income or resources in our poverty statistics.

The panel made this recommendation because SIPP collects more information than the CPS that is relevant to the

measurement of poverty. SIPP is an income survey rather

than a supplement to a labor force survey and is, therefore, better able to satisfy the data requirements for an

improved measure of poverty.

The SIPP is a continuing panel survey, begun in late

1983, in which all respondent household members are followed even if they move. SIPP is sponsored and conducted

by the Census Bureau. Until 1993, the design introduced a

new sample panel each February. Beginning in 1996, an

enlarged 4-year panel was introduced, with no further

panels planned until 2000. The sample covers the U.S.

civilian noninstitutionalized population and members of

the Armed Forces living off post or with their families on

post. Sample size historically has varied from 12,500 to

23,500 households per panel; the 1996 panel is composed of 36,700 households. The reporting unit is the

household, with unrelated individuals and families also

identified.

We have partially implemented the NAS measure using

the 1991 panel of the SIPP in previous work.30 That work

presented poverty estimates using thresholds derived

from the CEX for 1991, and family resources based on

data from the 1991 panel of the SIPP and the March 1992

CPS. The resulting poverty rates were compared with

those based on the official measure.

The poverty rates estimated in our previous work

employ the current official definitions using CPS data, and

a similarly defined measure using SIPP data.31 Annual

before-tax cash income is compared against the official

30Short et al., May 1998. 31Official U.S. poverty estimates are based only on the CPS.





















    	  



 

	 
	
 	  	

	   

 	

    

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U.S. Census Bureau
poverty thresholds to determine poverty status. No adjustment for taxes paid was made to the SIPP resource measure reported in that paper. While taxes paid are collected

in a topical module in the SIPP, these data are not well

reported. Ongoing efforts to model taxes in SIPP32 will be

incorporated in a resource measure in future work.

Estimates show that, in 1991, the official poverty rate

for all persons was 14.2 percent and a similarly defined

estimate in the SIPP yielded a poverty rate of 12.1 percent.

There are many reasons why the SIPP produces poverty

rates below those in the CPS. One reason is that, as an

income survey, SIPP is designed to do a more complete job

of collecting income data.33 Other possible factors are

sub-annual changes in family composition, accounted for

in the SIPP measure, and attrition bias in the SIPP. Consequently, the measure based on the official definition

results in poverty rates that are consistently lower when

the SIPP rather than the CPS is used.

As noted in earlier sections of this report, experimental

poverty rates calculated using the CPS are higher for all

groups than official rates. Using the SIPP, the overall rate

increases from 12.1 percent under the official definition to

13.6 percent under the NAS measure.34

It is important to note that the SIPP estimates reported

in Short et al. (1998) are based on data from the 1991

panel. These estimates combine information reported

every 4 months across the calendar year. They are

weighted using the calendar year weights for 1991.

Research has been conducted to investigate the degree of

attrition bias measurable in SIPP longitudinal files, particularly in the area of poverty statistics. This research suggests that there is a significant degree of this bias present

in our estimates. Since research shows that people who

are struggling to get along are less likely to remain in the

survey, poverty estimates using the SIPP are biased downward.35

As noted earlier, the 1996 panel of SIPP is a 4-year

panel. Methodological investigation by the Census Bureau

32Dickert et al., 1994. 33Coder and Scoon-Rogers, 1996.

34See also Iceland et al., 1999, for alternative poverty rate

estimates using 1992 SIPP data. 35Huggins and Winters, 1995, reported that the poverty rate for

the first quarter of 1991 for those respondents who left the panel at

some point was 15.7 percent, while the first-quarter poverty rate

for those with a complete set of interviews was only 11.5 percent.





















    	  



 

	 
	
 	  	 	

 
   

 	

    

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U.S. Census Bureau
has concluded that a time series of official statistics, such

as poverty, must be based on surveys with consistent

design characteristics. For a longitudinal survey like the

SIPP, this means that the characteristics of the sample

(consisting of households which stay in sample for several

years) must not change from year to year. But we know

from past research that families in poverty leave the

sample at higher rates than nonpoverty families. As a consequence, direct survey estimates cannot be used without

accounting for and correcting the bias introduced by this

differential attrition.

To address this problem, we have proposed a survey

redesign for SIPP with constant attrition bias (similar to the

design of the CPS) that allows us to measure year-to-year

changes accurately (if both years’ estimates are biased in

the same way, their difference is not biased). Constant

attrition bias for an annual statistic like poverty can be

obtained by starting a new SIPP panel each year just as the

CPS adds a new sample each month to permit accurate

measurement of month-to-month changes in unemployment. Specifically, we propose fielding a new SIPP panel

each year, with each panel collecting data for 3 years.36 As

part of this design the sample size must be sufficient to

produce a time series of poverty statistics with the same

variance (or less) as the March CPS estimates. Each panel

would provide a complete measure of calendar-year

income. The current plan is to supplement the existing

longitudinal panel with two additional smaller panels.

These additional panels will enable us to produce stable

cross-section estimates and to allow time-series comparisons.

Adopting the SIPP as the official data source for poverty

measurement, as recommended by the NAS panel, would

place special demands on the SIPP and the imputation

methods used to estimate values for the additions and

subtractions to obtain a SIPP-based resource measure. For

example, we will continue working on the medical out-ofpocket valuations. We have demonstrated in an earlier section that medical out-of-pocket imputations have a great

impact on poverty rates over time and on specific population subgroups at any point in time. Thus, it is imperative

that we focus on the valuation methods used for this

important element of poverty measurement. In the future,

we plan to statistically match new data collected in the

SIPP with data collected in the 1996 (and later) Medical

Expenditure Panel Survey. 36Weinberg et al., 1998.





















    	  



 

	 
	
 	  		 	  	

	    
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25

U.S. Census Bureau
B. Consumer Expenditure Survey

The CEX survey has two components — an Interview

Survey and a Diary Survey. Interview survey data alone are

used for this study. About 5,000 consumer units participate in the Interview Survey each quarter. Consumer units

are interviewed five times, at 3-month intervals during 1

year. Data from the first interview are used to ‘‘bound’’

expenditures for subsequent interviews and are not used

in estimation. The sample is a rotating panel in which 20

percent of the sample units are interviewed for the first

time each quarter while 20 percent are interviewed for the

last time. The Interview Survey covers about 95 percent of

total expenditures.

The panel recommended that the CEX be used for deriving and updating the poverty thresholds, as we have done

in this report. In these calculations we have used 3-year

averages to estimate median expenditures for a reference

family of two adults with two children on the basic bundle

of commodities. The 3 years of data are used to compensate for the relatively small sample sizes of the survey

(currently approximately 5,000 consumer unit interviews

each quarter, increasing to 7,800 per quarter in 1999) and

also to smooth any fluctuations from year to year. The reference family represented about 9.5 percent of all consumer units participating in the interview survey in the

1988-1997 period.

Improvements to the CEX were also recommended by

the panel. Among these were an increase in the sample

size to improve the quality of the data for updating poverty thresholds. The panel also suggested development of

methods to reduce reporting errors and to improve

response rates. In addition, the panel recommended an

evaluation of the CEX in terms of overall design, which

might include following family members over time in

order to collect expenditures on an annual basis, the reference period used here to assess poverty status.

We have identified several other areas for improvement,

not mentioned by the panel, which we consider need to be

made in the CEX if it is to be more useful in the production

of poverty thresholds. Among these are the collection of

information related to school breakfast and lunch programs, WIC programs, and energy assistance. If, as the

panel suggested, the preferable consumption definition of

shelter for owner occupants were adopted for the thresholds, additional data on housing and neighborhood quality

would be desirable. Also, if at some time in the future the

CEX were used as a source of medical care expenditure

information, the total number of persons in the consumer

unit with private coverage would be needed. Currently,

while information about private policies is collected, determination of which members are covered is not possible.

The total number of members covered by public insurance

is already being collected in the CEX. Related to medical

care expenditures, data on the health status of members

of the family would also be needed in order to permit

more accurate matching of medical care expenditures to

particular persons and families.

C. Decennial Census, the American Community

Survey, and the Census Bureau’s Small Area

Income and Poverty Estimates (SAIPE) Program

One effect of adopting a more complex definition of

resources as specified by the panel would be to make the

poverty definition less ‘‘portable’’ across surveys. At the

present time, any survey that collects basic income information can be used to compute poverty estimates that

are, for the most part, conceptually consistent with the

U.S. official poverty measure (though the actual rates may

vary significantly from the official poverty rates, particularly if the income questions are not as detailed as those

asked on the CPS or if the accounting period or unit of

analysis differs).

This is particularly important when one considers the

decennial census, which is the premier source of small

area poverty data. Decennial poverty data are used to allocate billions of dollars in Federal funds annually. The 2000

census long form includes questions on money income

only. If the panel’s recommendations were to be largely

adopted, future funding formulas that employ poverty as a

criterion would either have to make extensive use of modeling (to impute the components of the resource definition

not included in the decennial census), use a definition of

poverty that differs from the official measure, or ensure

that questions are added to obtain the required data. We

see these issues as challenges that would have to be met

rather than as reasons not to make the changes to the

resource definition.

These same issues apply to other programs and surveys that are available to provide estimates of poverty for

small geographic areas, such as the Census Bureau’s Continuous Measurement program. This program includes

both the American Community Survey (ACS) and the Small

Area Income and Poverty Estimates (SAIPE) program. The

ACS includes questions similar to those on the decennial

census long form. Thus, like the census, the ACS does not

collect the necessary information to produce a measure as

complex as that recommended by the NAS panel, though

questionnaire changes could be made in 2003. The ACS is

expected to have more flexibility to respond to the new

content needs of a revised poverty definition than the

decennial long form. The SAIPE estimates, which use

decennial poverty information as a predictor variable, currently do not have access to the wide variety of information required to fully implement this measure.

VI. FUTURE RESEARCH

Future poverty measurement research should focus on

refining the poverty thresholds and further examining the

resource measure. This section describes a number of

such possibilities.

26

U.S. Census Bureau
Determining how one adjusts poverty thresholds for

geographic differences in the cost of housing and in the

overall cost of living is a critical area for further

research.37 The procedure used by the panel and in this

research is a ‘‘modest step in the right direction,’’ in that it

is understandable, operationally feasible, and produces

results that conform to other research.38 However, the procedure does not account for housing cost differences

within areas, such as differences in costs between central

cities or suburbs of large metropolitan areas, or for differences in areas like Alaska and Hawaii versus other areas in

the Pacific division. The method also does not account for

housing quality differences. This topic requires further

research and development.

Additional research is also needed on the resource side.

For example, the imputations used in the measure for

work-related expenses, including child care costs, are

based on methods used by the panel, but other methods

are available for imputing such costs.39 Alternative methods to value housing subsidies for the CPS and the SIPP

are currently being investigated.40

Work is also proceeding on the imputation of medical

out-of-pocket expenses. This report has shown that its

effect on poverty rates is significant. Statistical matches

across surveys may provide the most promising method

of more accurately imputing these expenses. Specifically,

questions are being added to the 1996 SIPP to improve

this measure and facilitate statistical matches between the

1996 SIPP and the 1996 Medical Expenditure Panel Survey.

Also, since the imputed values of medical expenditures

are sensitive to the values of the benchmark totals used, it

is imperative that further research be conducted to specify

more appropriate sources for these inputs. Research

should also examine whether benchmark totals should be

used more widely to adjust other types of income that are

known to be underreported.

Further research should continue on whether medical

needs and other necessary expenses should be included

on the resource or the threshold side. The methods of

accounting for medical needs described in Section III of

this report would result in different amounts of medical

care needs being assigned to families which further

change our interpretation of which groups are most likely

to be poor. The issue of how to incorporate the medical

care needs of families in a poverty measure is one that

remains to be satisfactorily resolved.

Two more general issues for further research are the

treatment of cohabitants and the treatment of the flow of

services from owner-occupied housing. The panel recommended pooling resources and the needs of cohabiting

persons to determine poverty status. Some work has been

done in this report comparing poverty rates based on the

official definition which uses families, as defined by the

Census Bureau, with others that include cohabiting individuals as the relevant unit of analysis.41 Changing the

relevant unit for poverty analysis from the family to

include persons who are cohabiting might be an issue for

some population subgroups, such as young single people.

Research is necessary on the extent of resource sharing

among roommates and other household and family members to determine if the unit of analysis should be modified further.

Accounting for the flow of services from owneroccupied housing would affect both thresholds and

resources. As noted by the panel, economists have long

argued that the economic resources for owners and renters should be treated comparably because the resources

available are related to a household’s expenses. For

example, if the household owns its home without a mortgage, then more money is available to purchase other

needed goods and services although the household’s consumption need for housing may not differ from that of

owners with a mortgage or from that of renters. This

study defines thresholds using the out-of-pocket shelter

expenses reported (not including the reduction in mortgage principal) by the reference units for both renters and

owners. The other method shown here estimated these

costs by replacing the owners’ expenses with their

imputed rental shelter costs. An adjustment is also made

in the resource measure to account for the flow of services

of owner-occupied housing (see section III of this report).

REFERENCES

(Many of the papers listed here are available at

http://www.census.gov/www/hhes/povmeas.htm)

Banthin, Jessica S. and Thomas M. Selden, ‘‘Accounting

for Medical Care Burdens in Poverty Measures,’’ paper presented at the Southern Economic Association Meeting,

November 1998.

Bauman, Kurt, ‘‘Shifting Family Definitions: The Effect of

Cohabitation and Other Non-family Household Relationships on Measures of Poverty,’’ Poverty Measurement

Working Paper, Census Bureau, 1997.

Bavier, Richard, ‘‘Medical Needs and the Poverty Thresholds,’’ Poverty Measurement Working Paper, Census

Bureau, 1998.

Betson, David, ‘‘Effect of Home Ownership on Poverty

Measurement,’’ University of Notre Dame, unpublished

manuscript, 1995a.

––––––, ‘‘Poor Old Folks: Have Our Methods of Poverty

Measurement Blinded Us to Who is Poor?’’ University of

Notre Dame, unpublished manuscript, 1995b.

37U.S. General Accounting Office 1995; Kokoski et al., 1994. 38Citro and Michael, 1995, p. 199. 39Short et al., 1996. 40Naifeh and Eller, 1997 and Shea et al., 1997.

41Bauman, Kurt 1996, Carlson and Danziger, 1996 and Hernandez, 1998.

27

U.S. Census Bureau
––––––, ‘‘Is Everything Relative? The Role of Equivalence

Scales in Poverty Measurement,’’ University of Notre Dame,

unpublished manuscript, 1996.

––––––, ‘‘Imputing Medical Out-of-Pocket Expenditures

from NMES Data,’’ University of Notre Dame, unpublished

manuscript, December 1997a.

––––––, ‘‘In Search of an Elusive Truth, ‘How Much Do

Americans Spend on Their Health Care?’ ’’ University of

Notre Dame, unpublished manuscript, April 7, 1997b.

––––––, Constance F. Citro, and Robert T. Michael, ‘‘Measuring Poverty—A New Approach: The Report of the Panel

on Poverty and Family Assistance: An Overview and

Update,’’ Economics Department, University of Notre

Dame, 1997c.

Bumpass, Larry, and Hsien-Hen Lu, ‘‘Trends in Cohabitation and Implications for Children’s Family Contexts.’’

Paper presented at the annual meetings of the Population

Association of America, 1998.

Bureau of Labor Statistics, Urban Family Budgets and

Comparative Indexes for Selected Urban Family Budgets

and Comparative Indexes for Selected Urban Areas, USDL

82-139, Washington, DC, Autumn 1982.

Carlson, Marcia, and Sheldon Danziger, ‘‘Cohabitation

and Child Poverty,’’ Poverty Measurement Working Paper,

Census Bureau, 1996.

Casper, Lynn M., Philip N. Cohen, and Tavia Simmons,

‘‘How Does POSSLQ Measure Up? Historical Estimates of

Cohabitation,’’ Population Division Working Paper, Series

No. 36, U.S. Census Bureau, 1999.

Citro, Connie F., and Robert T. Michael (eds.), Measuring

Poverty: A New Approach, Washington, DC: National Academy Press, 1995.

Coder, John, and Lydia Scoon-Rogers, ‘‘Evaluating the

Quality of Income Data Collected in the Annual Supplement to the March Current Population Survey and the Survey of Income and Program Participation,’’ SIPP Working

Paper 215, Census Bureau, July 1996.

Commerce Clearing House, Inc., State Tax Handbook,

Chicago, Illinois, October 1991.

Dalaker, Joseph and Mary Naifeh, Poverty in the United

States: 1997, U.S. Census Bureau, Current Population

Reports, Series P60-201, Washington, DC, September

1998.

Dickert, Stacy, Scott Houser, and John Karl Scholz,

‘‘Taxes and the Poor: A Microsimulation Study of Implicit

and Explicit Taxes,’’ National Tax Journal, 47, September

1994.

Doyle, Pat, ‘‘Who’s at Risk? Designing a Medical Care

Risk Index,’’ unpublished paper, Census Bureau, May

1997a.

––––––, ‘‘How Do We Deduct What We Do Not Collect?,’’

in Proceedings of the Government and Social Statistics Section. Alexandria, VA: American Statistical Association,

August 1997b, pp. 38-47.

Fisher, Gordon, ‘‘Is There Such a Thing as an Absolute

Poverty Line Over Time? Evidence From the United States,

Britain, Canada, and Australia on the Income Elasticity of

the Poverty Line,’’ Poverty Measurement Working Paper,

1995.

Follain, James R. Jr., and Stephen Malpezzi, ‘‘Are Occupants Accurate Appraisers?,’’ Review of Public Data Use,

Vol. 9, 1981, pp. 47-55.

Garner, Thesia I., Stephanie Shipp, Geoffrey Paulin,

Kathleen Short, and Charles Nelson, ‘‘Poverty Measurement in the 1990s,’’ Monthly Labor Review, March 1998,

pp. 39-61.

General Accounting Office, Poverty Measurement:

Adjusting for Geographic Cost-of-Living Difference,

GAO/GGD-95-64, March 1995.

Gillingham, R.F., ‘‘Place-to-Place Rent Comparisons,’’

Annals of Economics and Social Measurement 4, 153-173,

1975.

Greene, William H. Econometric Analysis, First Edition,

New York: MacMillan Publishing Company, 1990.

Hernandez, Donald, ‘‘Official Poverty in the U.S.:

Re-Conceiving the Unit of Analysis,’’ unpublished manuscript, October 1998.

Huggins, Vicki J., and Franklin Winters, ‘‘Income and

Poverty Time Series Data From the Survey of Income and

Program Participation,’’ paper presented at the annual

meeting of the American Statistical Association, August

1995.

Iceland, John, Kathleen Short, Thesia I. Garner, and

David Johnson, ‘‘Are Children Worse Off? Evaluating Child

Well-Being Using a New (and Improved) Measure of Poverty,’’ Poverty Measurement Working Paper, 1999.

Institute for Research on Poverty, ‘‘Revising the Poverty

Measure,’’ Focus, Volume 19, Number 2, Spring 1998.

Johnson, David, Stephanie Shipp, Thesia I. Garner,

‘‘Developing Poverty Thresholds Using Expenditure Data,’’

in Proceedings of the Government and Social Statistics Section. Alexandria, VA: American Statistical Association,

August 1997, pp. 28-37.

Johnson, David, Kathleen Short, and Thesia I. Garner,

‘‘Poverty Measurement Research at the Bureau of the Census and the Bureau of Labor Statistics,’’ paper presented at

the annual meeting of the Association for Public Policy

Analysis and Management, October 1998.

Kokoski, Mary F., Patrick Cardiff, and Brent Moulton,

‘‘Interarea Price Indices for Consumer Goods and Services:

An Hedonic Approach Using CPI Data,’’ BLS Working Paper

256, Office of Prices and Living Conditions, U.S. Department of Labor, Washington, DC, 1994.

Malpezzi, Stephen, Larry Ozanne, and Thomas Thibodeau, ‘‘Characteristic Prices of Housing in Fifty-nine Metropolitan Areas,’’ The Urban Institute, Washington, DC,

December, 1980.

28

U.S. Census Bureau
Malpezzi, Stephen, Gregory Chun, and Richard Green,

‘‘New Place-to-Place Housing Price Indexes for U.S. Metropolitan Areas, and Their Determinants: An Application of

Housing Indicators,’’ Real Estate Economics, 26(2), Summer

1998, pp. 235-275.

Moon, Marilyn, ‘‘Incorporating Health Issues in Poverty

Measurement,’’ unpublished paper prepared for the Panel

on Poverty Measurement and Family Assistance, Committee on National Statistics, Urban Institute, Washington, DC,

1993.

Moulton, Brent R, ‘‘Interarea Indexes of the Cost of Shelter Using Hedonic Quality Adjustment Techniques,’’ Journal of Econometrics, 86(1), 1995, pp. 181-204.

Naifeh, Mary, and T.J. Eller, ‘‘Valuing Housing Subsidies

in a New Measure of Poverty: CPS,’’ in Proceedings of the

Government and Social Statistics Section, Alexandria, VA:

American Statistical Association, August 1997, pp. 382-

387.

Ozanne, Larry and Stephen Malpezzi, ‘‘The Efficacy of

Hedonic Estimation With the Annual Housing Survey, Evidence From the Demand Experiment,’’ Journal of Economic

and Social Measurement, Vol. 13, 1985, pp. 153-172.

Renwick, Trudi J., ‘‘Budget-Based Poverty Measurement:

1992 Basic Needs for American Families,’’ in Proceedings

of the Social Science Section of the American Statistical

Association, Alexandria, VA: American Statistical Association, 1993a.

––––––, and Barbara R. Bergmann, ‘‘A Budget-Based Definition of Poverty With an Application to Single-Parent Families.’’ Journal of Human Resources, 28(2), 1993, pp. 1-24.

Ruggles, Patricia, Drawing the Line—Alternative Poverty

Measures and Their Implications for Public Policy, Washington, DC: Urban Institute Press, 1990.

Schwarz, John E., and Thomas J. Volgy, Forgotten Americans, New York: W.W. Norton and Company, 1992.

Shea, Martina, Mary Naifeh, and Kathleen Short, ‘‘Valuing Housing Subsidies in a New Measure of Poverty: SIPP,’’

in Proceedings of the Government and Social Statistics Section, Alexandria, VA: American Statistical Association,

August 1997, pp. 376-381.

Short, Kathleen, Martina Shea, and T.J. Eller, ‘‘WorkRelated Expenditures in a New Measure of Poverty,’’ paper

presented at the annual meeting of the American Statistical Association, August 1996.

Short, Kathleen, Martina Shea, David Johnson, and Thesia I. Garner, ‘‘Poverty-Measurement Research Using the

Consumer Expenditure Survey and the Survey of Income

and Program Participation,’’ American Economic Review,

Vol. 88, No. 2, May 1998, pp. 352-356.

Short, Kathleen, Thesia Garner, David Johnson, and Martina Shea, ‘‘Redefining Poverty Measurement in the U.S.:

Examining the Impact on Inequality and Poverty,’’ paper

presented at the 25th Conference of The International

Association for Research in Income and Wealth; Cambridge, England, September 1998.

Short, Pamela F., and J. Banthin, ‘‘New Estimates of the

Underinsured Younger Than 65 Years,’’ Journal of the

American Medical Association, 274, No. 16, 1995, pp.

1302-1306.

Social Security Administration, Annual Statistical

Supplement, 1997, U.S. Government Printing Office, Washington, DC, December 1997.

Thibodeau, Thomas G., ‘‘House Price Indices From the

1984-1992 MSA American Housing Surveys,’’ Journal of

Housing Research, Vol. 6, Issue 3, 1995, pp. 439-481.

U.S. Census Bureau, Technical Paper No. 50, Alternative

Methods for Valuing Selected In-Kind Transfer Benefits and

Measuring Their Effect on Poverty, U.S. Government Printing Office, Washington, DC, 1982.

––––––, Measuring the Effect of Benefits and Taxes on

Income and Poverty: 1979 to 1991, Current Population

Reports, Series P60-182RD, Washington, DC, August 1992.

––––––, Measuring the Effect of Benefits and Taxes on

Income and Poverty: 1992, Current Population Reports,

Series P60-186RD, Washington, DC, September 1993.

U.S. Department of Health and Human Services, ‘‘Low

Income Home Energy Assistance Program: Report to Congress for Fiscal Year 1995,’’ August 1997.

U.S. General Accounting Office, Poverty Measurement:

Adjusting for Geographic Cost-of-Living Difference,

GAO/GGD-95-64, March 1995.

Vaughan, Denton R., ‘‘Exploring the Use of the Public’s

View to Set Income Poverty Thresholds and Adjust Them

Over Time,’’ Social Security Bulletin, Vol. 56, No. 2, 1993,

pp. 22-46.

––––––, ‘‘Reflections on the Income Estimates From the

Initial Panel of the Survey of Income and Program Participation,’’ SIPP Working Paper, No. 8906, 1989.

Weinberg, Daniel, Kathleen Short, and Donald Hernandez, ‘‘The Census Bureau’s Plans for Poverty Measurement

Research,’’ Poverty Measurement Working Paper, Census

Bureau, 1998.

Wolfe, Barbara, ‘‘Incorporating Health Care Needs Into a

Measure of Poverty: An Exploratory Proposal,’’ Focus, Volume 19, Number 2, Spring 1998, pp. 29-31.

Wolfson, Michael C., and J.M. Evans, ‘‘Statistics Canada’s

Low-Income Cutoffs: Methodological Concerns and Possibilities–A Discussion Paper,’’ Research Paper Series, Analytical Studies Branch, Ottawa: Statistics Canada, 1989.

Yezer, Anthony, ‘‘Housing Adequacy and Affordability in

the United States,’’ Annual Housing Survey Study Series,

Report #7, U.S. Department of Housing and Urban Development, Washington, DC, 1980.

29

U.S. Census Bureau
Appendix A.

Detailed Tables for Section III

A1a. Poverty Rates Using Experimental Thresholds: 1997.............................. A–2

A1b. Distribution of the Population Using Experimental Thresholds: 1997 ............. A–3

A2a. Poverty Rates Using Alternative Equivalence Scales: 1997 ....................... A–4

A2b. Distribution of the Population Using Alternative Equivalence Scales: 1997 ...... A–5

A3a. Poverty Rates With Geographic Adjustment: 1997................................. A–6

A3b. Distribution of the Population With Geographic Adjustment: 1997 ................ A–7

A4a. Poverty Rates Adding Food Stamp and School Lunch Subsidies to Resources:

1997.................................................................................. A–8

A4b. Distribution of the Population Adding Food Stamp and School Lunch Subsidies

to Resources: 1997 ................................................................. A–9

A5a. Poverty Rates Adding Housing Subsidies and Heating Assistance to

Resources: 1997 .................................................................... A–10

A5b. Distribution of the Population Adding Housing Subsidies and Heating

Assistance to Resources: 1997 .................................................... A–11

A6a. Poverty Rates Subtracting Alternative Valuations of Work-Related Expenses

From Resources: 1997.............................................................. A–12

A6b. Distribution of the Population Subtracting Alternative Valuations of WorkRelated Expenses From Resources: 1997 ........................................ A–13

A7a. Poverty Rates Taking Account of Taxes in Resources: 1997 ...................... A–14

A7b. Distribution of the Population Taking Account of Taxes in Resources: 1997 ..... A–15

A8a. Poverty Rates Including All In-Kind Transfers in Resources, Before and After

Tax: 1997 ............................................................................ A–16

A8b. Distribution of the Population Including All In-Kind Transfers in Resources,

Before and After Tax: 1997 ......................................................... A–17

A9a. Poverty Rates Taking Account of Medical Care: 1997 ............................. A–18

A9b. Distribution of the Population Taking Account of Medical Care: 1997............. A–19

A10a. Poverty Rates Taking Account of Owner-Occupied Housing: 1997 ............... A–20

A10b. Distribution of the Population Taking Account of Owner-Occupied Housing:

1997.................................................................................. A–21

A11a. Poverty Rates Using Alternative Units of Analysis: 1997 .......................... A–22

A11b. Distribution of the Population Using Alternative Units of Analysis: 1997.......... A–23

APPENDIX A A–1

U.S. Census Bureau
Table A1a. Poverty Rates Using Experimental Thresholds: 1997

[Percent poor]

Number

(1,000) Official measure

Low point of

ranges

Midpoint of

ranges

High point of

ranges

Total persons ...................................... 268,480 13.3 11.7 12.9 14.2

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71,069 19.9 17.8 19.4 21.0

Nonelderly adults .................................. 165,329 10.9 9.7 10.7 11.7

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32,082 10.5 8.3 10.1 12.0

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10,634 21.0 16.4 20.2 23.9

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . 19,445 5.3 4.2 5.1 6.0

Other relative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,003 6.1 5.2 5.9 7.1

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221,200 11.0 9.6 10.8 11.8

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34,458 26.5 23.9 26.0 28.2

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12,822 16.1 15.0 15.6 16.9

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30,637 27.1 23.6 26.5 29.0

No workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38,072 36.3 33.1 35.6 38.2

One or more workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230,408 9.5 8.2 9.2 10.2

Persons in family of type:

Married couple .................................. 175,892 6.4 5.4 6.2 7.0

Male householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31,137 16.1 14.3 15.9 17.1

Female householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61,452 31.5 28.4 30.8 33.4

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51,202 12.6 11.2 12.3 13.3

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62,499 10.4 9.2 10.1 11.3

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94,235 14.6 12.8 14.3 15.6

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60,545 14.6 12.9 14.3 15.7

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80,089 18.8 16.5 18.3 20.0

Not central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136,055 9.0 8.0 8.8 9.7

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52,337 15.9 14.0 15.6 17.1

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–2 APPENDIX A

U.S. Census Bureau
Table A1b. Distribution of the Population Using Experimental Thresholds: 1997

[Percent]

Total population

Poverty population

Official measure

Low point of

ranges

Midpoint of

ranges

High point of

ranges

All. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 40.4 39.7 39.1

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.6 50.8 51.1 51.0 50.8

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 8.5 9.4 10.1

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 6.3 5.6 6.2 6.7

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 2.9 2.6 2.8 3.1

Other relative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.3 0.3 0.4

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 67.6 68.5 68.8

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 26.3 25.8 25.6

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 6.1 5.8 5.7

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.1 23.3 23.3

No workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 40.2 39.0 38.2

One or more workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.8 61.2 59.9 61.0 61.8

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.5 31.5 30.2 31.3 32.2

Male householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 14.1 14.2 14.3 14.0

Female householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.9 54.4 55.6 54.5 53.8

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 18.2 18.1 17.9

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 18.4 18.2 18.6

South. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 38.6 38.8 38.5

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 24.8 24.9 25.0

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 42.2 42.2 42.0

Not central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.7 34.5 34.5 34.3 34.5

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 23.3 23.3 23.5 23.5

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–3

U.S. Census Bureau
Table A2a. Poverty Rates Using Alternative Equivalence Scales: 1997

[Percent poor]

Official

measure

Two-parameter scales1

Threeparameter

scale2

Canadian

scale3

f=0.65

p=0.70

f=0.75

p=0.70

f=0.70

p=0.70

f=0.5

p=1.00

f=0.65

p=.85

f=0.6

p=1.0

All persons . . . . . . . . . . . . . . . . . . . . . . . 13.3 13.1 12.3 12.7 13.4 12.7 12.7 13.1 13.8

Children. . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 19.1 19.1 19.2 19.3 19.4 19.5 19.3 20.0

Nonelderly adults . . . . . . . . . . . . . . . . . 10.9 10.8 10.2 10.4 11.0 10.3 10.4 10.9 11.3

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 11.2 8.6 10.0 12.8 9.8 9.7 11.0 12.8

Unrelated individuals . . . . . . . . . . . . 21.0 18.7 12.0 15.8 24.0 15.9 16.6 19.9 24.0

Family members:

Householder or spouse . . . . . . . . 5.3 7.5 6.9 7.1 7.3 6.7 6.3 6.4 7.3

Other relative . . . . . . . . . . . . . . . . . 6.1 7.7 7.0 7.0 6.9 6.7 6.3 7.6 7.2

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 10.8 10.2 10.5 11.2 10.5 10.6 10.9 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 26.1 24.9 25.4 26.8 25.5 25.6 26.4 27.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 16.4 15.6 15.9 15.8 15.6 15.5 15.8 16.7

Hispanic origin4 . . . . . . . . . . . . . . . . . . . 27.1 26.5 26.1 26.3 26.4 26.1 26.2 26.8 27.7

No workers. . . . . . . . . . . . . . . . . . . . . . . 36.3 36.5 33.1 34.8 38.5 34.7 34.9 36.1 38.4

One or more workers . . . . . . . . . . . . . . 9.5 9.2 8.9 9.0 9.3 9.0 9.1 9.3 9.7

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . 6.4 6.6 6.6 6.6 6.3 6.5 6.3 6.5 6.7

Male householder . . . . . . . . . . . . . . . 16.1 14.9 12.9 13.9 16.4 13.8 14.4 15.3 16.3

Female householder. . . . . . . . . . . . . 31.5 30.5 28.5 29.4 32.3 29.8 30.3 31.0 32.8

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . 12.6 12.3 11.5 11.9 12.7 11.9 12.0 12.4 13.0

Midwest. . . . . . . . . . . . . . . . . . . . . . . . 10.4 10.1 9.5 9.8 10.6 9.8 9.9 10.1 10.9

South. . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 14.7 13.8 14.3 15.0 14.2 14.2 14.7 15.3

West . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 14.2 13.7 13.9 14.4 13.8 13.9 14.3 15.1

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . 18.8 18.3 17.3 17.7 18.8 17.7 17.9 18.4 19.4

Not central city . . . . . . . . . . . . . . . . . 9.0 8.9 8.4 8.6 9.1 8.6 8.6 8.8 9.3

Nonmetropolitan area. . . . . . . . . . . . . . 15.9 16.0 15.1 15.6 16.5 15.5 15.5 16.1 16.7

Number of persons in family:

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.9 18.6 15.1 16.8 21.4 16.9 17.7 19.2 21.4

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 9.2 8.4 8.8 9.6 8.6 8.5 8.6 9.4

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 11.9 11.4 11.6 12.2 11.7 11.7 12.6 12.0

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 10.3 10.2 10.2 10.4 10.3 10.4 10.4 10.5

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 13.6 13.8 13.7 13.2 13.6 13.5 13.6 13.9

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 19.4 20.5 19.8 17.8 19.8 19.4 18.9 20.3

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.1 27.5 28.7 27.9 25.4 27.2 26.8 27.3 28.7

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.3 23.8 25.2 23.8 21.7 25.2 24.8 22.9 26.9

9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.9 26.5 28.3 28.3 17.7 26.5 26.5 21.6 30.2

10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45.9 39.1 48.1 45.3 33.4 41.3 39.5 36.5 50.3

1

Two-parameter scale = (adults + p * children)f

2

Three-parameter scale = (ratio of the scale for 2 adults to one adult is 1.41

For single parents (adults + .8 + .5 * children - 1).7

All other families (adults + .5 * children).7) 3

Canadian scale = (1 + .4 * (adults - 1) + .4 * (first child) + .3 * (children - 1))

4

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–4 APPENDIX A

U.S. Census Bureau
Table A2b. Distribution of the Population Using Alternative Equivalence Scales: 1997

[Percent]

Total

population

Poverty population

Official

measure

Two-parameter scales1

Threeparameter

scale2

Canadian

scale3

f=0.65

p=0.70

f=0.75

p=0.70

f=0.70

p=0.70

f=0.5

p=1.00

f=0.65

p=.85

f=0.6

p=1.0

All . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Children. . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 38.8 41.0 40.0 38.0 40.6 40.7 38.9 38.5

Nonelderly adults. . . . . . . . . . . . . . . 61.6 50.8 50.9 50.7 50.6 50.5 50.2 50.2 51.1 50.4

Elderly . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 10.3 8.3 9.4 11.4 9.2 9.2 10.0 11.1

Unrelated individuals . . . . . . . . . 4.0 6.3 5.7 3.8 4.9 7.1 5.0 5.2 6.0 6.9

Family members:

Householder or spouse . . . . . 7.2 2.9 4.1 4.0 4.1 3.9 3.8 3.6 3.6 3.8

Other relative . . . . . . . . . . . . . . 0.8 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4

White . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 68.4 68.1 68.3 68.8 68.2 68.4 68.4 68.6

Black . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 25.6 25.9 25.7 25.6 25.9 25.8 25.9 25.6

Other . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 6.0 6.0 6.0 5.6 5.9 5.8 5.8 5.8

Hispanic origin4 . . . . . . . . . . . . . . . . 11.4 23.4 23.2 24.2 23.7 22.4 23.5 23.5 23.3 23.0

No workers . . . . . . . . . . . . . . . . . . . . 14.2 38.8 39.6 38.0 39.0 40.7 38.9 39.0 39.1 39.5

One or more workers . . . . . . . . . . . 85.8 61.2 60.4 62.0 61.0 59.3 61.1 61.1 60.9 60.5

Persons in family of type:

Married couple. . . . . . . . . . . . . . . 65.5 31.5 33.3 35.1 34.2 30.7 33.4 32.3 32.2 31.7

Male householder . . . . . . . . . . . . 11.6 14.1 13.2 12.1 12.7 14.2 12.7 13.1 13.6 13.8

Female householder. . . . . . . . . . 22.9 54.4 53.4 52.9 53.1 55.2 53.9 54.6 54.2 54.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . 19.1 18.2 18.0 17.8 17.9 18.1 17.9 18.1 18.1 18.0

Midwest. . . . . . . . . . . . . . . . . . . . . 23.3 18.3 18.0 17.9 17.9 18.4 18.1 18.1 18.0 18.5

South . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 39.6 39.2 39.5 39.2 39.5 39.3 39.4 38.9

West. . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 24.4 25.1 24.7 24.2 24.6 24.6 24.6 24.7

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . 29.8 42.2 41.7 41.8 41.7 41.8 41.8 42.0 41.9 42.0

Not central city. . . . . . . . . . . . . . . 50.7 34.5 34.4 34.4 34.3 34.2 34.3 34.2 34.1 34.3

Nonmetropolitan area. . . . . . . . . . . 19.5 23.3 23.9 23.8 24.1 24.0 24.0 23.7 24.0 23.7

Number of persons in family:

1 . . . . . . . . . . . . . . . . . . . . . . . . . . 15.5 24.4 22.2 19.0 20.6 24.7 20.7 21.6 22.7 24.1

2 . . . . . . . . . . . . . . . . . . . . . . . . . . 23.1 14.4 16.4 15.6 16.1 16.5 15.7 15.5 15.1 15.7

3 . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 15.4 17.1 17.3 17.1 17.1 17.4 17.3 18.1 16.4

4 . . . . . . . . . . . . . . . . . . . . . . . . . . 22.1 17.4 17.4 18.3 17.9 17.1 18.0 18.1 17.6 16.9

5 . . . . . . . . . . . . . . . . . . . . . . . . . . 12.4 13.3 13.0 13.9 13.5 12.2 13.4 13.2 12.9 12.6

6 . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 7.4 7.0 7.8 7.4 6.3 7.4 7.2 6.8 6.9

7 . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 4.1 4.0 4.4 4.1 3.6 4.0 4.0 3.9 3.9

8 . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 1.7 1.5 1.6 1.5 1.3 1.6 1.6 1.4 1.6

9 . . . . . . . . . . . . . . . . . . . . . . . . . . 0.3 0.8 0.6 0.7 0.7 0.4 0.6 0.6 0.5 0.6

10 . . . . . . . . . . . . . . . . . . . . . . . . . 0.3 1.2 1.0 1.3 1.2 0.9 1.1 1.1 1.0 1.3

1

Two-parameter scale = (adults + p * children)f

2

Three-parameter scale = (ratio of the scale for 2 adults to one adult is 1.41

For single parents (adults + .8 + .5 * children - 1).7

All other families (adults + .5 * children).7) 3

Canadian scale = (1 + .4 * (adults - 1) + .4 * (first child) + .3 * (children - 1))

4

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–5

U.S. Census Bureau
Table A3a. Poverty Rates With Geographic Adjustment: 1997

[Percent poor]

Official measure

With geographic

adjustment1

Total persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 13.0

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 19.4

Nonelderly adults. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 10.8

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 10.3

Unrelated individuals. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.0 20.5

Family members:1

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 5.1

Other relative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 6.3

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 10.8

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 26.3

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 16.8

Hispanic origin2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 28.0

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 35.9

One or more workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 9.3

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 6.2

Male householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 16.1

Female householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.5 31.1

Geographic regions:

Northeast. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 13.9

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 9.6

South. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 13.1

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 15.8

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 19.3

Not central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0 9.4

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 13.1

1

Geographic adjustments are normalized to achieve a national weighted average =1.00.

2

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–6 APPENDIX A

U.S. Census Bureau
Table A3b. Distribution of the Population With Geographic Adjustment: 1997

[Percent]

Total population

Poverty population

Official measure

With geographic

adjustment1

All . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 39.4

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.6 50.8 51.2

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 9.4

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 6.3 6.2

Family members:1 ................................................

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 2.9 2.8

Other relative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.4

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 68.0

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 25.9

Other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 6.1

Hispanic origin2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 24.5

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 39.1

One or more workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.8 61.2 61.0

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.5 31.5 31.1

Male householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 14.1 14.4

Female householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.9 54.4 54.6

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 20.4

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 17.1

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 35.3

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 27.3

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 44.1

Not central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.7 34.5 36.4

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 23.3 19.5

1

Geographic adjustments are normalized to achieve a national weighted average =1.00.

2

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–7

U.S. Census Bureau
Table A4a. Poverty Rates Adding Food Stamp and School Lunch Subsidies to Resources: 1997

[Percent poor]

Official measure

With food

stamps

With school

lunches With both

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 12.7 13.0 12.4

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 18.8 19.3 18.2

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 10.5 10.8 10.4

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 10.2 10.5 10.1

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.0 20.2 21.0 20.2

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 5.1 5.3 5.1

Other relative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 6.0 6.0 5.9

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 10.6 10.8 10.4

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 25.3 26.1 24.7

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 14.8 15.6 14.7

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 25.8 26.2 25.1

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 35.1 36.1 35.1

One or more workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 9.0 9.2 8.7

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 6.0 6.2 5.9

Male householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 15.7 16.0 15.5

Female householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.5 30.1 31.0 29.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 12.0 12.4 11.8

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 10.0 10.1 9.8

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 14.1 14.4 13.8

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 13.9 14.3 13.6

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 17.9 18.3 17.5

Not central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0 8.6 8.8 8.5

Nonmetropolitan area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 15.2 15.6 14.9

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–8 APPENDIX A

U.S. Census Bureau
Table A4b. Distribution of the Population Adding Food Stamp and School Lunch Subsidies to Resources: 1997

[Percent]

Total population

Poverty population

Official measure

With food

stamps

With school

lunches With both

All. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 39.2 39.2 38.7

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.6 50.8 51.2 51.1 51.6

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 9.6 9.7 9.8

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 6.3 6.3 6.4 6.4

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 2.9 2.9 2.9 3.0

Other relative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.4 0.3 0.4

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 68.8 68.5 68.8

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 25.7 25.8 25.6

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 5.6 5.7 5.7

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.3 23.0 23.0

No workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 39.4 39.4 40.0

One or more workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.8 61.2 60.7 60.7 60.0

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.5 31.5 31.2 31.0 31.1

Male householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 14.1 14.3 14.3 14.5

Female householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.9 54.4 54.4 54.7 54.4

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 18.1 18.2 18.2

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 18.3 18.2 18.3

South. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 39.0 38.9 38.9

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 24.7 24.8 24.7

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 42.1 42.1 42.1

Not central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.7 34.5 34.6 34.5 34.6

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 23.3 23.3 23.4 23.3

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–9

U.S. Census Bureau
Table A5a. Poverty Rates Adding Housing Subsidies and Heating Assistance to Resources: 1997

[Percent poor]

Official measure

With housing

subsidies

With heating

assistance With both

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 12.8 13.2 12.8

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 19.5 19.8 19.4

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 10.6 10.9 10.6

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 9.3 10.5 9.2

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.0 17.5 20.8 17.3

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 5.1 5.2 5.1

Other relative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 5.8 6.1 5.8

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 10.7 11.0 10.6

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 25.4 26.4 25.4

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 15.6 16.1 15.6

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 26.3 27.1 26.3

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 34.4 36.2 34.3

One or more workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 9.2 9.4 9.2

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 6.3 6.4 6.3

Male householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 15.3 16.1 15.3

Female householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.5 30.1 31.4 30.0

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 11.7 12.6 11.6

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 10.1 10.4 10.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 14.3 14.6 14.3

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 14.2 14.6 14.2

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 17.9 18.7 17.9

Not central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0 8.8 9.0 8.7

Nonmetropolitan area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 15.4 15.8 15.4

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–10 APPENDIX A

U.S. Census Bureau
Table A5b. Distribution of the Population Adding Housing Subsidies and Heating Assistance to

Resources: 1997

[Percent]

Total population

Poverty population

Official measure

With housing

subsidies

With heating

assistance With both

All. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 40.3 39.7 40.3

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.6 50.8 51.1 50.9 51.1

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 8.7 9.5 8.6

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 6.3 5.4 6.2 5.4

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 2.9 2.9 2.9 2.9

Other relative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.3 0.3 0.3

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 68.7 68.6 68.6

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 25.5 25.6 25.6

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 5.8 5.8 5.8

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.5 23.4 23.5

No workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 38.2 38.8 38.1

One or more workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.8 61.2 61.8 61.2 61.9

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.5 31.5 32.2 31.5 32.2

Male householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 14.1 13.9 14.1 13.9

Female householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.9 54.4 54.0 54.4 53.9

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 17.4 18.1 17.4

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 18.4 18.2 18.3

South. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 39.2 38.7 39.2

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 25.1 24.9 25.1

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 41.8 42.3 41.8

Not central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.7 34.5 34.7 34.4 34.7

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 23.3 23.5 23.4 23.5

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–11

U.S. Census Bureau
Table A6a. Poverty Rates Subtracting Alternative Valuations of Work-Related Expenses From Resources: 1997

[Percent poor]

Official

measure

Child care

1992 SIPP

model

Child care

85% SIPP

medians

Child care

AFDC

guidelines

Other

work

expenses

All expenses

1992 SIPP

model

85% SIPP

medians

AFDC

guidelines

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 13.6 13.9 13.7 14.0 14.4 14.7 14.5

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 20.7 21.3 20.8 20.8 21.7 22.4 21.9

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 10.9 11.2 11.4 11.2 11.7 12.0 12.2 12.0

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 10.5 10.6 10.5 10.6 10.7 10.7 10.7

Unrelated individuals . . . . . . . . . . . . . . . 21.0 21.0 21.0 21.0 21.1 21.1 21.1 21.1

Family members:

Householder or spouse . . . . . . . . . . . 5.3 5.3 5.3 5.3 5.4 5.4 5.4 5.4

Other relative . . . . . . . . . . . . . . . . . . . . 6.1 6.4 6.4 6.3 6.6 6.9 6.9 6.9

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 11.3 11.6 11.4 11.7 12.0 12.2 12.1

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 27.4 28.2 27.5 27.8 28.7 29.8 29.0

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 16.2 16.4 16.2 16.9 17.0 17.2 17.0

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 27.1 28.0 28.6 28.0 28.9 29.6 30.4 29.8

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 36.3 36.3 36.3 36.3 36.3 36.3 36.3

One or more workers . . . . . . . . . . . . . . . . . 9.5 9.9 10.3 10.0 10.3 10.8 11.2 10.9

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 6.4 6.5 6.7 6.6 6.9 7.1 7.3 7.2

Male householder . . . . . . . . . . . . . . . . . . 16.1 16.4 16.8 16.5 17.1 17.4 17.8 17.5

Female householder. . . . . . . . . . . . . . . . 31.5 32.4 33.4 32.7 32.7 33.6 34.6 33.8

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 12.8 13.0 12.8 13.0 13.3 13.6 13.3

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 10.8 11.0 10.9 11.1 11.5 11.8 11.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 15.0 15.5 15.1 15.5 15.8 16.3 16.0

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 15.0 15.4 15.1 15.6 16.0 16.3 16.1

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 18.8 19.2 19.7 19.3 19.8 20.4 20.8 20.5

Not central city. . . . . . . . . . . . . . . . . . . . . 9.0 9.3 9.5 9.3 9.5 9.8 10.0 9.9

Nonmetropolitan area. . . . . . . . . . . . . . . . . 15.9 16.3 16.8 16.3 16.8 17.2 17.7 17.3

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–12 APPENDIX A

U.S. Census Bureau
Table A6b. Distribution of the Population Subtracting Alternative Valuations of Work-Related Expenses From

Resources: 1997

[Percent]

Total

population

Poverty population

Official

measure

Child care

1992 SIPP

model

Child care

85% SIPP

medians

Child care

AFDC

guidelines

Other

work

expenses

All expenses

1992 SIPP

model

85% SIPP

medians

AFDC

guidelines

All. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Children. . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 40.2 40.5 40.3 39.4 39.9 40.2 40.0

Nonelderly adults . . . . . . . . . . . . . . . . . 61.6 50.8 50.6 50.5 50.5 51.5 51.3 51.1 51.2

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 9.3 9.0 9.2 9.1 8.9 8.7 8.8

Unrelated individuals . . . . . . . . . . . . 4.0 6.3 6.1 6.0 6.1 6.0 5.8 5.7 5.8

Family members:

Householder or spouse . . . . . . . . 7.2 2.9 2.8 2.7 2.8 2.8 2.7 2.7 2.7

Other relative . . . . . . . . . . . . . . . . . 0.8 0.3 0.4 0.3 0.3 0.4 0.4 0.4 0.4

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 68.5 68.5 68.5 68.8 68.7 68.5 68.7

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 25.8 25.9 25.8 25.5 25.6 26.0 25.7

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 5.7 5.6 5.7 5.8 5.6 5.6 5.6

Hispanic origin1 . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.4 23.4 23.4 23.6 23.5 23.5 23.5

No workers. . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 37.8 36.9 37.6 36.7 35.8 34.9 35.5

One or more workers . . . . . . . . . . . . . . 85.8 61.2 62.2 63.1 62.4 63.3 64.2 65.1 64.5

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . 65.5 31.5 31.5 31.2 31.4 32.4 32.4 32.3 32.5

Male householder . . . . . . . . . . . . . . . 11.6 14.1 14.0 14.0 14.0 14.1 14.1 14.0 14.0

Female householder. . . . . . . . . . . . . 22.9 54.4 54.5 54.8 54.7 53.5 53.6 53.7 53.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 18.0 17.8 17.9 17.7 17.6 17.6 17.5

Midwest. . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 18.5 18.4 18.5 18.4 18.7 18.6 18.7

South. . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 38.7 38.9 38.7 38.8 38.6 38.8 38.8

West . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 24.8 24.9 24.9 25.1 25.1 25.0 25.1

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 42.0 42.0 42.1 42.1 42.2 42.1 42.1

Not central city. . . . . . . . . . . . . . . . . . 50.7 34.5 34.6 34.4 34.6 34.5 34.5 34.4 34.6

Nonmetropolitan area. . . . . . . . . . . . . . 19.5 23.3 23.4 23.5 23.3 23.4 23.3 23.4 23.3

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–13

U.S. Census Bureau
Table A7a. Poverty Rates Taking Account of Taxes in Resources: 1997

[Percent poor]

Official

measure

Includes net capital gains

Social

security

payroll tax

Federal

income

State

income

Federal

and state

Federal

and state

plus EIC All taxes

All persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 14.1 13.3 13.3 13.4 11.9 12.7

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 21.1 19.8 19.9 19.9 16.9 18.3

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . 10.9 11.7 11.0 11.0 11.1 10.0 10.8

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 10.6 10.5 10.5 10.5 10.5 10.5

Unrelated individuals . . . . . . . . . . . . . . . . . . . 21.0 21.0 21.0 21.0 21.0 21.0 21.0

Family members:

Householder or spouse . . . . . . . . . . . . . . . 5.3 5.4 5.3 5.3 5.3 5.2 5.3

Other relative. . . . . . . . . . . . . . . . . . . . . . . . 6.1 6.4 6.1 6.2 6.2 5.7 5.9

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 11.7 11.1 11.1 11.1 9.8 10.6

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 28.1 26.6 26.6 26.7 24.1 25.3

Other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 16.9 16.2 16.1 16.2 15.2 16.0

Hispanic origin1. . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 29.0 27.1 27.1 27.3 23.1 25.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 36.3 36.3 36.3 36.3 36.3 36.3

One or more workers. . . . . . . . . . . . . . . . . . . . . 9.5 10.4 9.5 9.5 9.6 7.8 8.9

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . 6.4 7.0 6.4 6.4 6.4 5.3 6.0

Male householder. . . . . . . . . . . . . . . . . . . . . . 16.1 17.1 16.4 16.2 16.5 15.6 16.6

Female householder . . . . . . . . . . . . . . . . . . . 31.5 32.6 31.5 31.6 31.7 28.7 30.0

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 13.2 12.7 12.6 12.7 11.5 12.2

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 11.2 10.4 10.5 10.6 9.4 10.1

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 15.5 14.6 14.6 14.7 13.0 14.0

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 15.6 14.7 14.7 14.8 13.0 14.1

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 19.8 18.8 18.8 18.9 16.8 18.0

Not central city . . . . . . . . . . . . . . . . . . . . . . . . 9.0 9.6 9.0 9.0 9.1 8.1 8.7

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . 15.9 17.0 15.9 15.9 16.0 14.2 15.2

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–14 APPENDIX A

U.S. Census Bureau
Table A7b. Distribution of the Population Taking Account of Taxes in Resources: 1997

[Percent]

Total

population

Poverty population

Official

measure

Includes net capital gains

Social

security

payroll tax

Federal

income

State

income

Federal

and state

Federal

and state

plus EIC All taxes

All . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 39.6 39.5 39.6 39.5 37.6 38.0

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 61.6 50.8 51.3 51.0 50.9 51.1 51.8 52.1

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 9.0 9.5 9.5 9.4 10.5 9.9

Unrelated individuals . . . . . . . . . . . . . . . 4.0 6.3 5.9 6.3 6.3 6.2 7.0 6.5

Family members:

Householder or spouse . . . . . . . . . . . 7.2 2.9 2.8 2.9 2.9 2.9 3.2 3.0

Other relative . . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.3 0.3 0.4 0.4 0.4 0.3

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 68.6 68.5 68.5 68.5 67.9 68.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 25.6 25.7 25.7 25.7 26.1 25.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 5.8 5.8 5.8 5.8 6.1 6.0

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.5 23.3 23.3 23.3 22.2 23.0

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 36.6 38.7 38.7 38.5 43.3 40.4

One or more workers . . . . . . . . . . . . . . . . . 85.8 61.2 63.4 61.3 61.3 61.5 56.7 59.6

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 65.5 31.5 32.8 31.4 31.5 31.4 29.4 31.0

Male householder . . . . . . . . . . . . . . . . . . 11.6 14.1 14.1 14.3 14.1 14.3 15.2 15.2

Female householder. . . . . . . . . . . . . . . . 22.9 54.4 53.1 54.3 54.4 54.3 55.4 53.9

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 17.8 18.2 18.1 18.1 18.5 18.2

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 18.6 18.3 18.4 18.4 18.4 18.5

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 38.6 38.6 38.6 38.6 38.5 38.4

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 25.0 25.0 24.9 24.9 24.7 24.9

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 42.0 42.3 42.3 42.3 42.3 42.2

Not central city. . . . . . . . . . . . . . . . . . . . . 50.7 34.5 34.4 34.4 34.4 34.4 34.4 34.6

Nonmetropolitan area. . . . . . . . . . . . . . . . . 19.5 23.3 23.6 23.3 23.4 23.4 23.3 23.2

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–15

U.S. Census Bureau
Table A8a. Poverty Rates Including All In-Kind Transfers in Resources, Before and After Tax: 1997

[Percent poor]

Official measure

Before tax income

with all in-kind

benefits

After tax income

with all in-kind

benefits

All persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 11.8 11.1

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 17.5 15.6

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 9.9 9.7

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 8.9 8.9

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.0 16.8 16.8

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 4.9 5.0

Other relative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 5.6 5.5

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 9.9 9.4

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 23.2 21.5

Other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 14.2 14.0

Hispanic origin1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 24.2 22.3

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 32.8 32.9

One or more workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 8.4 7.6

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 5.8 5.3

Male householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 14.6 15.3

Female householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.5 27.6 25.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 10.7 10.2

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 9.4 8.8

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 13.2 12.3

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 13.1 12.4

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 16.4 15.5

Not central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0 8.2 7.8

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 14.2 13.2

1 Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–16 APPENDIX A

U.S. Census Bureau
Table A8b. Distribution of the Population Including All In-Kind Transfers in Resources, Before and

After Tax: 1997

[Percent]

Total population

Poverty population

Official measure

Before tax income

with all in-kind

benefits

After tax income

with all in-kind

benefits

All . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 39.3 37.1

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.6 50.8 51.7 53.4

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 9.0 9.6

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 6.3 5.6 6.0

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 2.9 3.0 3.2

Other relative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.4 0.4

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 69.1 69.3

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 25.2 24.7

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 5.8 6.0

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.4 22.8

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 39.4 41.8

One or more workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.8 61.2 60.6 58.2

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.5 31.5 32.1 31.3

Male householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 14.1 14.4 15.9

Female householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.9 54.4 53.5 52.8

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 17.3 17.5

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 18.5 18.5

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 39.3 38.9

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 25.0 25.2

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 41.5 41.5

Not central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.7 34.5 35.1 35.3

Nonmetropolitan area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 23.3 23.5 23.2

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–17

U.S. Census Bureau
Table A9a. Poverty Rates Taking Account of Medical Care: 1997

[Percent poor]

Official measure

Deducting MOOP from income

Adding public

insurance to

Official threshold income

Experimental

threshold

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 16.3 15.6 12.0

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 22.6 21.7 18.0

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 13.0 12.4 10.1

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 19.3 18.9 9.1

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.0 33.9 28.0 17.9

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 12.3 14.7 4.7

Other relative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 9.3 10.6 5.5

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 14.0 13.4 10.1

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 30.0 28.5 23.7

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 19.2 18.4 14.6

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 31.2 30.2 24.8

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 44.3 42.9 33.3

One or more workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 11.7 11.1 8.5

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 8.6 8.9 5.7

Male householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 19.2 16.4 15.0

Female householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.5 36.9 34.5 28.8

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 15.3 14.5 11.3

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 13.4 12.8 9.5

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 17.8 17.3 13.3

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 17.7 16.8 13.4

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 22.1 20.9 16.9

Not central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0 11.5 11.0 8.2

Nonmetropolitan area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 19.9 19.5 14.6

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–18 APPENDIX A

U.S. Census Bureau
Table A9b. Distribution of the Population Taking Account of Medical Care: 1997

[Percent]

Total population

Poverty population

Official measure

Deducting MOOP from income

Adding public

insurance to

Official threshold income

Experimental

threshold

All. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 36.6 36.8 39.5

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.6 50.8 49.3 48.8 51.5

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 14.1 14.5 9.0

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 6.3 8.2 7.1 5.9

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 2.9 5.5 6.8 2.8

Other relative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.4 0.5 0.3

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 70.8 71.0 68.9

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 23.6 23.4 25.3

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 5.6 5.6 5.8

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 21.8 22.1 23.5

No workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 38.6 38.9 39.2

One or more workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.8 61.2 61.5 61.1 60.8

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.5 31.5 34.6 37.2 30.9

Male householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 14.1 13.7 12.2 14.4

Female householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.9 54.4 51.7 50.6 54.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 17.9 17.7 17.9

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 19.2 19.1 18.3

South. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 38.4 38.9 38.7

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 24.5 24.3 25.2

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 40.5 39.9 41.8

Not central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.7 34.5 35.7 35.7 34.6

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 23.3 23.8 24.4 23.6

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–19

U.S. Census Bureau
Table A10a. Poverty Rates Taking Account of Owner-Occupied Housing: 1997

[Percent poor]

Official measure

Estimated rental

shelter cost in

thresholds

Adding net return

on home equity

to income

Both in a

combined measure

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 12.2 12.1 11.0

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 18.5 18.8 17.6

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 10.0 10.1 9.1

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 9.3 7.4 6.3

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.0 14.6 14.5 9.7

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 6.7 3.7 4.5

Other relative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 6.6 5.3 5.7

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 10.1 9.9 9.0

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 24.6 24.6 22.7

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 15.3 15.2 14.6

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 25.1 25.5 23.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 33.9 32.4 29.9

One or more workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 8.6 8.7 7.9

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 6.3 5.7 5.5

Male householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 13.3 14.7 11.9

Female householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.5 28.5 29.0 26.3

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 11.4 11.7 10.6

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 9.4 9.5 8.5

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 13.7 13.2 12.2

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 13.3 13.3 12.1

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 17.0 17.8 16.1

Not central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0 8.3 7.9 7.3

Nonmetropolitan area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 15.0 14.2 13.0

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–20 APPENDIX A

U.S. Census Bureau
Table A10b. Distribution of the Population Taking Account of Owner-Occupied Housing: 1997

[Percent]

Total population

Poverty population

Official measure

Estimated rental

shelter cost in

thresholds

Adding net return

on home equity

to income

Both in a

combined measure

All . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 40.3 41.2 42.1

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.6 50.8 50.6 51.5 51.0

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 9.1 7.3 6.8

Unrelated individuals . . . . . . . . . . . . . . . . . . . . . . 4.0 6.3 4.8 4.8 3.5

Family members:

Householder or spouse . . . . . . . . . . . . . . . . . . 7.2 2.9 4.0 2.2 3.0

Other relative. . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.4 0.3 0.4

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 68.1 67.8 67.3

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 25.9 26.2 26.4

Other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 6.0 6.0 6.3

Hispanic origin1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.5 24.2 24.4

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 39.5 38.1 38.4

One or more workers. . . . . . . . . . . . . . . . . . . . . . . . 85.8 61.2 60.5 61.9 61.6

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.5 31.5 33.8 30.8 32.9

Male householder. . . . . . . . . . . . . . . . . . . . . . . . . 11.6 14.1 12.6 14.1 12.5

Female householder . . . . . . . . . . . . . . . . . . . . . . 22.9 54.4 53.6 55.1 54.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 17.9 18.5 18.3

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 18.0 18.4 18.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 39.5 38.3 38.9

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 24.6 24.9 24.8

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 41.6 43.9 43.5

Not central city . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.7 34.5 34.4 33.2 33.6

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . 19.5 23.3 24.0 22.9 22.6

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–21

U.S. Census Bureau
Table A11a. Poverty Rates Using Alternative Units of Analysis: 1997

[Percent poor]

Official measure

Cohabiting

couples

...and

housemate/

roommate

...and

roomer/

boarder

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 12.7 11.7 11.5

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 19.1 18.2 18.2

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 10.4 9.1 8.9

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 10.5 10.1 10.0

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 10.5 9.5 9.4

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 25.8 24.5 24.3

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 15.6 14.2 13.9

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 26.4 25.2 25.0

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 34.9 31.7 31.2

One or more workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 9.0 8.3 8.2

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 6.4 6.3 6.3

Male householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 15.5 11.9 11.3

Female householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.5 29.5 26.9 26.6

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 12.1 11.2 11.1

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 9.7 8.9 8.8

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 14.1 13.1 13.0

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 14.1 12.6 12.3

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 18.1 16.8 16.6

Not central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0 8.6 7.7 7.6

Nonmetropolitan area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 15.0 14.1 14.0

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

A–22 APPENDIX A

U.S. Census Bureau
Table A11b. Distribution of the Population Using Alternative Units of Analysis: 1997

[Percent]

Total population

Poverty population

Official measure

Cohabiting

couples

...and

housemate/

roommate

...and

roomer/

boarder

All. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 39.9 41.7 42.0

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.6 50.8 50.3 48.0 47.7

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 9.8 10.3 10.4

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 68.1 67.1 67.0

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 26.1 27.1 27.2

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 5.9 5.8 5.8

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.7 24.7 24.8

No workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 39.0 39.1 38.9

One or more workers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.8 61.2 61.0 60.9 61.1

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.5 31.5 32.8 35.2 35.6

Male householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 14.1 14.2 11.9 11.5

Female householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.9 54.4 53.1 52.9 53.0

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 18.2 18.4 18.4

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 17.9 17.8 17.9

South. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 38.9 39.4 39.5

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 25.1 24.4 24.2

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 42.6 42.9 43.0

Not central city . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.7 34.5 34.4 33.5 33.3

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 23.3 23.0 23.6 23.7

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulation of March 1998 Current Population Survey data.

APPENDIX A A–23

U.S. Census Bureau
Appendix B.

Detailed Tables for Section IV

B1a. Standardized Poverty Rates: 1997.................................................. B–2

B1b. Distribution of the Population: 1997 ................................................. B–3

B2a. Poverty Rates: 1997 ................................................................. B–4

B2b. Distribution of the Population: 1997 ................................................. B–5

B3. Standardized Poverty Rates by Selected Characteristics: 1997 .................. B–6

B4. Poverty Rates by Selected Characteristics: 1997 .................................. B–7

B5. Poverty Rates Standardized to Match the Official Rate for All Persons in 1997

With Experimental Thresholds Based on Consumer Expenditure Survey Data:

1990 to 1997

B5a. Official Poverty Measure .......................................................... B–8

B5b. NAS Measure ..................................................................... B–9

B5c. DCM1 Measure .................................................................... B–10

B5d. DCM2 Measure .................................................................... B–11

B5e. DES-DCM2 Measure .............................................................. B–12

B5f. NGA Measure...................................................................... B–13

B5g. DES-DCM2-NGA Measure ........................................................ B–14

B6. Poverty Rates With Experimental Thresholds Based on Consumer Expenditure

Survey Data: 1990 to 1997

B6a. Official Poverty Measure .......................................................... B–15

B6b. NAS/U Measure.................................................................... B–16

B6c. DCM1/U Measure.................................................................. B–17

B6d. DCM2/U Measure.................................................................. B–18

B6e. DES-DCM2/U Measure............................................................ B–19

B6f. NGA/U Measure ................................................................... B–20

B6g. DES-DCM2-NGA/U Measure ..................................................... B–21

B7. Poverty Rates Standardized to Match Official Rates for All Persons in 1997

With Experimental Thresholds Based on the CPI-U: 1990 to 1997

B7a. Official Poverty Measure .......................................................... B–22

B7b. NAS-CPI Measure ................................................................. B–23

B7c. DCM1-CPI Measure ............................................................... B–24

B7d. DCM2-CPI Measure ............................................................... B–25

B7e. DES-DCM2-CPI Measure ......................................................... B–26

B7f. NGA-CPI Measure................................................................. B–27

B7g. DES-DCM2-NGA-CPI Measure ................................................... B–28

B8. Poverty Rates With Experimental Thresholds Based on the CPI-U: 1990 to

1997

B8a. Official Poverty Measure .......................................................... B–29

B8b. NAS/U-CPI Measure............................................................... B–30

B8c. DCM1/U-CPI Measure............................................................. B–31

B8d. DCM2/U-CPI Measure............................................................. B–32

B8e. DES-DCM2/U-CPI Measure....................................................... B–33

B8f. NGA/U-CPI Measure .............................................................. B–34

B8g. DES-DCM2-NGA/U-CPI Measure ................................................ B–35

APPENDIX B B–1

U.S. Census Bureau
Table B1a. Standardized Poverty Rates: 1997

Official

measure

Experimental measures

(standardized to match the official rate)

NAS DCM1a DCM2b DES-DCM2c NGAd

DES-DCM2-

NGAe

All persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 13.3 13.3 13.3 13.3 13.3 13.3

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 17.6 17.9 17.7 17.3 17.4 17.2

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . 10.9 11.1 11.0 11.0 11.2 11.1 11.2

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 15.0 14.5 14.9 14.9 15.3 15.2

Unrelated individuals . . . . . . . . . . . . . . . . . . . 21.0 20.8 20.2 20.7 22.8 20.9 22.9

Family members:

Householder or spouse . . . . . . . . . . . . . . . 5.3 12.5 12.1 12.4 11.2 13.0 11.6

Other relative. . . . . . . . . . . . . . . . . . . . . . . . 6.1 8.9 8.4 8.9 8.6 8.7 8.6

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 11.5 11.5 11.5 11.5 11.5 11.6

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 23.3 23.5 23.2 23.5 23.2 23.1

Other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 17.0 16.7 16.9 16.9 16.3 15.9

Hispanic origin1. . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 27.0 27.1 26.9 26.5 24.9 24.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 34.4 33.8 34.4 34.5 34.9 34.7

One or more workers. . . . . . . . . . . . . . . . . . . . . 9.5 9.8 9.9 9.8 9.8 9.7 9.7

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . 6.4 7.8 7.7 7.8 7.3 7.8 7.3

Male householder. . . . . . . . . . . . . . . . . . . . . . 16.1 15.6 15.6 15.6 16.6 15.3 16.2

Female householder . . . . . . . . . . . . . . . . . . . 31.5 27.8 28.1 27.8 28.7 28.0 28.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 14.1 14.1 14.0 14.2 12.0 11.8

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 10.0 10.0 10.0 10.0 10.8 10.8

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 13.1 13.3 13.3 13.2 14.8 15.1

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 16.1 15.9 16.0 16.0 14.4 14.2

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 18.5 18.5 18.5 18.4 17.2 17.2

Not central city . . . . . . . . . . . . . . . . . . . . . . . . 9.0 10.2 10.2 10.2 10.3 9.7 9.7

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . 15.9 13.1 13.2 13.2 13.0 16.5 16.4

a Child care method based on SIPP. b Child care method based on AFDC program allowances. c Child care method based on AFDC program allowances and three-parameter equivalence scale.

d NAS measure with no geographic adjustment. e Child care method based on AFDC program allowances, three-parameter equivalence scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March 1998 Current Population Survey data.

B–2 APPENDIX B

U.S. Census Bureau
Table B1b. Distribution of the Population: 1997

Total

population

Poverty population

Official

measure

Experimental measures

NAS DCM1a DCM2b DES-DCM2c NGAd DES-DCM2-NGAe

All . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 35.1 35.8 35.3 34.5 34.8 34.3

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 61.6 50.8 51.4 51.1 51.3 52.0 51.4 52.0

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 13.5 13.1 13.4 13.4 18.8 13.7

Unrelated individuals . . . . . . . . . . . . . . . 4.0 6.3 6.2 6.0 6.2 6.8 6.3 6.9

Family members:

Householder or spouse. . . . . . . . . . . 7.2 2.9 6.8 6.6 6.8 6.1 7.1 6.3

Other relative. . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.5 0.5 0.5 0.5 0.5 0.5

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 71.4 71.2 71.4 71.2 71.7 71.9

Black. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 22.5 22.8 22.5 22.7 22.5 22.3

Other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 6.1 6.0 6.1 6.1 5.9 5.7

Hispanic origin1

. . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.3 23.4 23.1 22.8 21.4 21.2

No workers . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 36.8 36.2 36.8 36.9 37.3 37.1

One or more workers. . . . . . . . . . . . . . . . . 85.8 61.2 63.2 63.9 63.2 63.1 62.7 62.9

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . 65.5 31.5 38.3 37.8 38.4 36.0 38.3 36.3

Male householder. . . . . . . . . . . . . . . . . . 11.6 14.1 13.7 13.6 13.7 14.5 13.4 14.2

Female householder . . . . . . . . . . . . . . . 22.9 54.4 48.0 48.6 48.0 49.6 48.3 49.6

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 20.3 20.2 20.2 20.4 17.3 16.9

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 17.6 17.6 17.5 17.5 18.9 19.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 34.7 35.2 35.1 34.9 39.2 39.9

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 27.4 27.0 27.2 27.2 24.6 24.2

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 41.6 41.6 41.5 41.5 38.8 38.8

Not central city . . . . . . . . . . . . . . . . . . . . 50.7 34.5 39.1 39.1 39.1 39.3 36.9 37.1

Nonmetropolitan area . . . . . . . . . . . . . . . . 19.5 23.3 19.3 19.4 19.4 19.2 24.3 24.2

a Child care method based on SIPP. b Child care method based on AFDC program allowances. c Child care method based on AFDC program allowances and three-parameter equivalence scale.

d NAS measure with no geographic adjustment. e Child care method based on AFDC program allowances, three-parameter equivalence scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March 1998 Current Population Survey data.

APPENDIX B B–3

U.S. Census Bureau
Table B2a. Poverty Rates: 1997

Official

measure

Experimental measures

NAS/U DCM1/Ua DCM2/Ub

DESDCM2/Uc NGA/UdDES-DCM2

NGA/Ue

All persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 15.4 15.9 15.4 16.1 15.8 16.5

Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 20.3 21.4 20.5 20.8 21.0 21.5

Nonelderly adults . . . . . . . . . . . . . . . . . . . . . . . . 10.9 12.8 13.2 12.9 13.6 13.1 13.9

Elderly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 17.4 17.4 17.4 18.4 17.9 18.9

Unrelated individuals . . . . . . . . . . . . . . . . . . . 21.0 23.9 23.9 23.9 28.2 24.5 28.5

Family members:

Householder or spouse . . . . . . . . . . . . . . . 5.3 14.5 14.5 14.5 13.9 15.1 14.4

Other relative. . . . . . . . . . . . . . . . . . . . . . . . 6.1 10.3 10.3 10.3 10.2 10.5 11.0

White. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 13.4 13.8 13.5 14.1 13.8 14.4

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 26.8 27.9 26.8 28.1 27.1 28.9

Other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 18.8 19.2 18.8 19.0 18.5 18.7

Hispanic origin1. . . . . . . . . . . . . . . . . . . . . . . . . . 27.1 31.6 33.0 31.7 32.6 30.2 30.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.3 38.4 38.4 38.4 39.9 39.1 40.6

One or more workers. . . . . . . . . . . . . . . . . . . . . 9.5 11.6 12.2 11.7 12.2 11.9 12.5

Persons in family of type:

Married couple . . . . . . . . . . . . . . . . . . . . . . . . 6.4 9.4 9.7 9.4 9.3 9.8 9.6

Male householder. . . . . . . . . . . . . . . . . . . . . . 16.1 17.5 18.0 17.6 19.6 17.4 19.6

Female householder . . . . . . . . . . . . . . . . . . . 31.5 31.4 32.5 31.5 33.7 32.1 34.6

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 16.2 16.6 16.3 17.1 14.0 14.8

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 11.6 12.0 11.6 12.2 12.9 13.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 15.3 16.0 15.5 16.2 17.6 18.5

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 18.6 19.2 18.6 19.3 17.3 17.7

Metropolitan area:

Central city. . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 21.2 22.1 21.2 22.2 20.5 21.6

Not central city . . . . . . . . . . . . . . . . . . . . . . . . 9.0 11.9 12.4 12.1 12.5 11.4 11.9

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . 15.9 15.4 15.7 15.4 16.0 19.9 20.6

a

Child care method based on SIPP.

b

Child care method based on AFDC program allowances.

c

Child care method based on AFDC program allowances and three-parameter equivalence scale.

d

NAS measure with no geographic adjustment.

e

Child care method based on AFDC program allowances, three-parameter equivalence scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March 1998 Current Population Survey data.

B–4 APPENDIX B

U.S. Census Bureau
Table B2b. Distribution of the Population: 1997

Total

population

Poverty population

Official

measure

Experimental measures

NAS/U DCM1/Ua DCM2/Ub

DESDCM2/Uc NGA/UdDES-DCM2

NGA/Ue

All . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5 39.7 35.1 35.7 35.2 34.2 35.2 34.6

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 61.6 50.8 51.4 51.3 51.4 52.2 51.2 51.8

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 9.5 13.5 13.0 13.4 13.6 13.6 13.7

Unrelated individuals . . . . . . . . . . . . . . . 4.0 6.3 6.2 6.0 6.1 6.9 6.2 6.9

Family members:

Householder or spouse . . . . . . . . . . . 7.2 2.9 6.8 6.6 6.8 6.2 7.0 6.3

Other relative . . . . . . . . . . . . . . . . . . . . 0.8 0.3 0.5 0.5 0.5 0.5 0.5 0.5

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 68.6 71.8 71.7 71.9 71.9 72.3 72.1

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 25.6 22.4 22.6 22.3 22.4 22.1 22.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 5.8 5.8 5.8 5.8 5.6 5.6 5.4

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 11.4 23.4 23.5 23.7 23.4 23.1 21.9 21.2

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 38.8 35.4 34.2 35.2 35.2 35.2 34.9

One or more workers . . . . . . . . . . . . . . . . . 85.8 61.2 64.6 65.8 64.8 64.8 64.8 65.1

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 65.5 31.5 40.0 40.1 40.1 38.0 40.6 38.2

Male householder . . . . . . . . . . . . . . . . . . 11.6 14.1 13.2 13.1 13.2 14.1 12.8 13.8

Female householder. . . . . . . . . . . . . . . . 22.9 54.4 46.8 46.8 46.7 47.9 46.6 48.0

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 18.2 20.1 19.9 20.1 20.3 17.0 17.1

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3 18.3 17.6 17.5 17.5 17.6 19.1 19.3

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 38.7 35.0 35.3 35.2 35.2 39.2 39.4

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 24.9 27.3 27.2 27.2 27.0 24.7 24.2

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 29.8 42.2 41.2 41.4 41.0 41.2 38.8 39.0

Not central city. . . . . . . . . . . . . . . . . . . . . 50.7 34.5 39.3 39.4 39.6 39.4 36.6 36.7

Nonmetropolitan area. . . . . . . . . . . . . . . . . 19.5 23.3 19.5 19.2 19.4 19.4 24.6 24.3

a

Child care method based on SIPP.

b

Child care method based on AFDC program allowances.

c

Child care method based on AFDC program allowances and three-parameter equivalence scale.

d

NAS measure with no geographic adjustment.

e

Child care method based on AFDC program allowances, three-parameter equivalence scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March 1998 Current Population Survey data.

APPENDIX B B–5

U.S. Census Bureau
Table B3. Standardized Poverty Rates by Selected Characteristics: 1997

Number

(1,000)

Official

measure

Experimental measures (standardized to match the official rate)

NAS DCM1a DCM2b DES-DCM2c NGAd DES-DCM2-NGAe

All persons . . . . . . . . . . . . . . . . . . . . . . . . 268,480 13.3 13.3 13.3 13.3 13.3 13.3 13.3

Age groups:

Less than 3 years . . . . . . . . . . . . . . . . 11,546 21.2 20.1 20.6 20.2 19.7 20.0 20.0

3 to 5 years . . . . . . . . . . . . . . . . . . . . . 12,051 22.8 21.4 21.3 21.5 21.0 21.0 21.1

6 to 11 years . . . . . . . . . . . . . . . . . . . . 23,997 20.3 17.4 17.8 17.5 17.1 17.0 16.6

12 to 17 years . . . . . . . . . . . . . . . . . . . 23,475 17.2 14.7 14.9 14.7 14.5 14.7 14.4

18 to 21 years . . . . . . . . . . . . . . . . . . . 14,816 18.2 18.3 18.5 18.2 18.8 18.4 19.0

22 to 44 years . . . . . . . . . . . . . . . . . . . 94,201 11.4 11.4 11.4 11.4 11.6 11.3 11.5

45 to 54 years . . . . . . . . . . . . . . . . . . . 34,057 7.2 7.6 7.4 7.6 7.6 7.5 7.5

55 to 59 years . . . . . . . . . . . . . . . . . . . 12,190 9.0 9.4 9.1 9.3 9.3 9.6 9.5

60 to 64 years . . . . . . . . . . . . . . . . . . . 10,065 11.2 11.1 10.8 11.1 11.1 11.4 11.4

65 to 74 years . . . . . . . . . . . . . . . . . . . 17,874 9.2 12.7 12.3 12.6 12.7 13.0 12.9

75+ years . . . . . . . . . . . . . . . . . . . . . . . 14,209 12.2 17.9 17.3 17.8 17.6 18.2 18.0

Race/origin:

White, not Hispanic ............... 191,859 8.6 9.1 9.1 9.2 9.2 9.5 9.6

White, Hispanic . . . . . . . . . . . . . . . . . . 29,341 26.9 27.0 27.0 26.8 26.4 24.9 24.6

Black, not Hispanic . . . . . . . . . . . . . . . 33,631 26.3 23.1 23.4 23.0 23.3 23.2 23.0

Black, Hispanic . . . . . . . . . . . . . . . . . . 827 32.7 29.8 30.4 29.8 29.3 23.6 24.9

Other, not Hispanic . . . . . . . . . . . . . . . 12,352 15.6 16.6 16.3 16.6 16.6 15.9 15.6

Other, Hispanic1

. . . . . . . . . . . . . . . . . . 469 28.3 26.0 27.5 26.0 26.5 25.6 25.6

Number of persons in family:

1 person . . . . . . . . . . . . . . . . . . . . . . . . 41,672 20.9 18.8 18.4 18.7 20.3 18.7 20.2

2 persons . . . . . . . . . . . . . . . . . . . . . . . 62,073 8.3 11.0 11.2 11.1 10.6 11.3 10.9

3 persons . . . . . . . . . . . . . . . . . . . . . . . 50,433 10.9 11.4 11.4 11.2 11.8 11.4 12.0

4 persons . . . . . . . . . . . . . . . . . . . . . . . 59,408 10.4 10.0 9.9 10.0 9.9 10.1 10.0

5 persons . . . . . . . . . . . . . . . . . . . . . . . 33,347 14.2 13.7 14.1 13.9 13.2 13.6 12.9

6 persons . . . . . . . . . . . . . . . . . . . . . . . 12,623 20.7 18.9 19.0 18.8 17.8 18.8 18.2

7 persons . . . . . . . . . . . . . . . . . . . . . . . 5,055 29.1 23.8 24.3 23.8 21.4 24.5 22.4

8 persons . . . . . . . . . . . . . . . . . . . . . . . 2,160 27.3 23.8 23.8 25.0 22.1 22.7 18.1

9 persons . . . . . . . . . . . . . . . . . . . . . . . 788 35.9 24.6 24.6 22.0 22.0 20.1 20.1

10+ persons . . . . . . . . . . . . . . . . . . . . . 922 45.9 41.1 41.9 41.1 35.4 23.9 19.2

Marital status:

Married, spouse present . . . . . . . . . . 110,619 5.3 7.3 7.2 7.3 6.8 7.4 7.0

Married, spouse absent . . . . . . . . . . . 2,424 20.6 21.2 20.7 21.2 21.4 20.6 21.4

Widowed . . . . . . . . . . . . . . . . . . . . . . . . 13,599 17.6 18.5 18.1 18.4 19.9 18.9 20.1

Divorced . . . . . . . . . . . . . . . . . . . . . . . . 24,346 19.7 17.3 17.4 17.3 18.3 17.6 18.4

Never married . . . . . . . . . . . . . . . . . . . 117,493 18.8 17.2 17.4 17.2 17.3 17.0 17.2

Gender:

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131,376 11.6 11.9 11.9 11.9 11.8 11.9 11.8

Female.......................... 137,105 14.9 14.5 14.5 14.5 14.6 14.6 14.7

Education (25 years of age and over):

No high school diploma . . . . . . . . . . . 29,558 24.5 24.5 24.1 24.4 24.4 25.0 24.8

High school diploma . . . . . . . . . . . . . . 58,174 9.9 11.0 10.9 11.0 11.1 11.1 11.1

Some college . . . . . . . . . . . . . . . . . . . . 42,506 6.5 7.5 7.4 7.5 7.6 7.4 7.6

College degree. . . . . . . . . . . . . . . . . . . 41,974 3.1 4.2 4.1 4.2 4.3 4.0 4.1

Citizenship status:

Native........................... 242,219 12.5 12.2 12.3 12.3 12.3 12.5 12.6

Naturalized citizen. . . . . . . . . . . . . . . . 9,732 11.4 13.4 13.3 13.4 13.4 12.1 12.1

Not a citizen . . . . . . . . . . . . . . . . . . . . . 16,529 25.0 28.0 27.6 27.8 27.5 24.7 24.2

Disability status:

Not disabled ..................... 153,248 9.4 10.1 10.1 10.1 10.2 10.0 10.1

Disabled . . . . . . . . . . . . . . . . . . . . . . . . 20,017 25.3 19.9 19.4 19.9 20.3 20.8 21.1

Severe disability. . . . . . . . . . . . . . . . . . 14,649 29.1 22.1 21.6 22.1 22.7 23.1 23.6

Self-reported health status:

Excellent . . . . . . . . . . . . . . . . . . . . . . . . 91,976 9.7 9.9 10.1 9.9 9.9 9.8 9.9

Very good . . . . . . . . . . . . . . . . . . . . . . . 81,855 11.5 11.7 11.7 11.7 11.7 11.5 11.5

Good . . . . . . . . . . . . . . . . . . . . . . . . . . . 63,804 15.8 15.9 15.8 15.9 15.9 16.0 15.8

Fair. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21,252 21.0 20.8 20.6 20.6 20.7 21.2 21.3

Poor . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9,594 27.7 24.3 23.6 24.2 24.6 25.5 25.9

a

Child care method based on SIPP.

b

Child care method based on AFDC program allowances.

c

Child care method based on AFDC program allowances and three-parameter equivalence scale.

d

NAS measure with no geographic adjustment.

e

Child care method based on AFDC program allowances, three-parameter equivalence scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March 1998 Current Population Survey data.

B–6 APPENDIX B

U.S. Census Bureau
Table B4. Poverty Rates by Selected Characteristics: 1997

Official

measure

Experimental measures

NAS/U DCM1/Ua DCM2/Ub

DESDCM2/Uc NGA/UdDES-DCM2-

NGA/Ue

All persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 15.4 15.9 15.4 16.1 15.8 16.5

Age groups:

Less than 3 years . . . . . . . . . . . . . . . . . . . . 21.2 23.5 24.9 23.9 24.3 24.2 25.0

3 to 5 years . . . . . . . . . . . . . . . . . . . . . . . . . . 22.8 24.7 25.9 24.9 25.1 25.6 26.4

6 to 11 years . . . . . . . . . . . . . . . . . . . . . . . . . 20.3 20.0 21.3 20.3 20.5 20.6 21.2

12 to 17 years. . . . . . . . . . . . . . . . . . . . . . . . 17.2 16.8 17.5 16.9 17.1 17.3 17.8

18 to 21 years. . . . . . . . . . . . . . . . . . . . . . . . 18.2 20.5 21.1 20.7 22.1 21.0 22.2

22 to 44 years. . . . . . . . . . . . . . . . . . . . . . . . 11.4 13.4 13.9 13.4 14.2 13.6 14.5

45 to 54 years. . . . . . . . . . . . . . . . . . . . . . . . 7.2 8.7 8.9 8.8 9.2 8.8 9.4

55 to 59 years. . . . . . . . . . . . . . . . . . . . . . . . 9.0 10.8 10.9 10.8 11.5 11.2 11.5

60 to 64 years. . . . . . . . . . . . . . . . . . . . . . . . 11.2 12.8 12.9 12.8 13.2 13.3 13.9

65 to 74 years. . . . . . . . . . . . . . . . . . . . . . . . 9.2 14.8 14.8 14.8 15.5 15.4 16.0

75+ years. . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 20.6 20.6 20.6 22.0 21.1 22.5

Race/origin:

White, not Hispanic . . . . . . . . . . . . . . . . . . . 8.6 10.6 10.9 10.7 11.2 11.3 12.0

White, Hispanic. . . . . . . . . . . . . . . . . . . . . . . 26.9 31.5 33.0 31.7 32.5 30.2 30.7

Black, not Hispanic . . . . . . . . . . . . . . . . . . . 26.3 26.6 27.7 26.7 28.0 27.1 28.8

Black, Hispanic . . . . . . . . . . . . . . . . . . . . . . . 32.7 33.9 36.7 33.9 34.4 28.7 29.7

Other, not Hispanic . . . . . . . . . . . . . . . . . . . 15.6 18.4 18.7 18.4 18.4 18.2 18.3

Other, Hispanic1 . . . . . . . . . . . . . . . . . . . . . . 28.3 29.2 30.8 29.2 34.1 28.1 29.8

Number of persons in family:

1 person. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.9 21.2 21.2 21.2 24.0 21.4 24.2

2 persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 12.7 13.2 12.8 12.7 13.3 13.2

3 persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 13.3 14.1 13.4 15.0 13.6 15.3

4 persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 11.7 12.4 11.8 12.2 12.1 12.4

5 persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 16.1 16.7 16.2 15.9 16.9 16.8

6 persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 22.0 22.8 22.3 21.2 22.3 22.0

7 persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.1 27.8 28.9 28.1 26.9 28.2 27.5

8 persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.3 27.2 29.5 28.4 26.7 27.9 29.1

9 persons. . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.9 31.9 33.3 31.9 28.4 26.2 23.6

10+ persons . . . . . . . . . . . . . . . . . . . . . . . . . 45.9 46.0 46.0 46.0 41.5 46.6 37.6

Marital status:

Married, spouse present . . . . . . . . . . . . . . 5.3 8.8 9.1 8.9 8.7 9.2 9.0

Married, spouse absent . . . . . . . . . . . . . . . 20.6 22.8 23.2 22.9 25.4 22.6 24.7

Widowed . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.6 21.4 21.4 21.4 23.9 22.1 24.7

Divorced. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.7 20.0 20.5 20.0 22.0 20.4 22.8

Never married . . . . . . . . . . . . . . . . . . . . . . . . 18.8 19.7 20.6 19.9 20.7 20.1 21.1

Gender:

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 13.9 14.4 14.0 14.5 14.2 14.9

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 16.8 17.3 16.9 17.6 17.2 18.1

Education (25 years of age and over):

No high school diploma . . . . . . . . . . . . . . . 24.5 28.6 29.0 28.6 30.2 29.8 31.2

High school diploma . . . . . . . . . . . . . . . . . . 9.9 13.0 13.3 13.1 13.7 13.2 14.0

Some college . . . . . . . . . . . . . . . . . . . . . . . . 6.5 8.8 9.1 8.8 9.5 9.0 9.6

College degree . . . . . . . . . . . . . . . . . . . . . . . 3.1 4.8 4.9 4.8 5.0 4.5 4.8

Citizenship status:

Native . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 14.2 14.7 14.3 14.9 14.9 15.6

Naturalized citizen . . . . . . . . . . . . . . . . . . . . 11.4 16.1 16.7 16.2 17.1 14.5 15.3

Not a citizen . . . . . . . . . . . . . . . . . . . . . . . . . 25.0 31.7 32.9 31.8 32.7 28.8 29.6

Disability status:

Not disabled . . . . . . . . . . . . . . . . . . . . . . . . . 9.4 11.6 12.1 11.7 12.3 11.8 12.4

Disabled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.3 23.5 23.7 23.5 25.1 24.8 26.2

Severe disability . . . . . . . . . . . . . . . . . . . . . . 29.1 26.4 26.5 26.4 28.4 27.8 29.4

Self-reported health status:

Excellent . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.7 11.5 12.1 11.5 11.9 11.5 12.1

Very good . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.5 13.4 14.0 13.6 14.2 14.0 14.5

Good. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 18.6 19.1 18.7 19.4 18.9 20.0

Fair . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.0 24.1 24.6 24.1 25.4 25.0 26.3

Poor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.7 28.3 28.4 28.2 30.3 30.3 31.7

a

Child care method based on SIPP.

b

Child care method based on AFDC program allowances.

c

Child care method based on AFDC program allowances and three-parameter equivalence scale.

d

NAS measure with no geographic adjustment.

e

Child care method based on AFDC program allowances, three-parameter scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March 1998 Current Population Survey data.

APPENDIX B B–7

U.S. Census Bureau
Table B5. Poverty Rates Standardized to Match the Official Rate for All Persons in 1997 With Experimental

Thresholds Based on Consumer Expenditure Survey Data: 1990 to 1997

Table B5a. Official Poverty Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.5 14.2 14.8 15.1 14.6 13.8 13.7 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 21.8 22.4 22.7 21.8 20.8 20.5 19.9

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 10.8 11.4 11.9 12.4 11.9 11.4 11.4 10.9

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 12.4 12.9 12.2 11.7 10.5 10.8 10.5

Unrelated individuals . . . . . . . . . . . . . . . 24.7 24.9 24.9 24.1 23.1 21.4 20.9 21.0

Family members:

Householder or spouse . . . . . . . . . . . 5.9 5.9 7.1 6.4 5.8 4.7 5.3 5.3

Other relative . . . . . . . . . . . . . . . . . . . . 5.8 7.0 7.6 7.4 8.4 7.9 8.7 6.1

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.7 11.3 11.9 12.2 11.7 11.2 11.2 11.0

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.9 32.7 33.4 33.1 30.6 29.3 28.4 26.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4 17.6 17.4 18.9 21.1 17.8 17.6 16.1

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 28.1 28.7 29.6 30.6 30.7 30.3 29.4 27.1

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 40.2 40.5 42.0 42.4 40.7 38.2 38.1 36.3

One or more workers . . . . . . . . . . . . . . . . . 8.9 9.5 10.0 10.2 9.9 9.6 9.6 9.5

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 6.9 7.2 7.7 8.0 7.4 6.8 6.9 6.4

Male householder . . . . . . . . . . . . . . . . . . 15.5 16.3 17.9 18.0 18.3 16.9 16.2 16.1

Female householder. . . . . . . . . . . . . . . . 33.1 34.8 34.9 34.8 34.2 32.4 32.0 31.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 12.2 12.6 13.3 12.9 12.5 12.7 12.6

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 13.2 13.3 13.4 13.0 11.0 10.7 10.4

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 16.1 17.1 17.2 16.1 15.7 15.1 14.6

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.0 14.3 14.9 15.6 15.3 14.9 15.4 14.6

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 19.0 20.2 20.9 21.5 20.9 20.6 19.6 18.8

Not central city. . . . . . . . . . . . . . . . . . . . . 8.7 9.6 9.9 10.3 10.3 9.1 9.4 9.0

Nonmetropolitan area. . . . . . . . . . . . . . . . . 16.3 16.1 16.9 17.2 16.0 15.6 15.9 15.9

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–8 APPENDIX B

U.S. Census Bureau
Table B5. Poverty Rates Standardized to Match the Official Rate for All Persons in 1997 With Experimental

Thresholds Based on Consumer Expenditure Survey Data: 1990 to 1997—Con.

Table B5b. NAS Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3 14.9 15.6 16.5 15.3 14.3 13.7 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 21.0 21.6 22.5 20.7 19.1 18.0 17.6

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.7 12.2 12.7 13.7 12.7 12.0 11.4 11.1

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3 15.7 16.9 17.6 16.8 15.6 15.8 15.0

Unrelated individuals . . . . . . . . . . . . . . . . . 21.7 21.9 22.5 24.3 22.8 21.5 20.9 20.8

Family members:

Householder or spouse . . . . . . . . . . . 12.3 12.7 14.5 14.8 13.9 12.9 13.2 12.5

Other relative . . . . . . . . . . . . . . . . . . . . 10.2 11.2 12.2 10.5 12.1 10.5 12.5 8.9

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 12.7 13.1 14.0 13.1 12.3 11.9 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.8 29.0 31.1 31.3 27.0 26.0 24.4 23.3

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.3 18.4 18.2 21.4 22.0 18.5 16.8 17.0

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 32.0 33.3 33.0 34.2 32.9 30.8 29.5 27.0

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 36.2 36.8 39.6 40.2 39.0 36.6 36.0 34.4

One or more workers . . . . . . . . . . . . . . . . . 10.4 11.0 11.3 12.2 11.1 10.5 10.0 9.8

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.9 9.2 9.7 10.4 9.3 8.6 8.2 7.8

Male householder . . . . . . . . . . . . . . . . . . 16.2 16.9 18.1 19.4 18.4 17.6 16.0 15.6

Female householder. . . . . . . . . . . . . . . . 30.2 31.5 32.0 33.0 31.9 29.1 28.3 27.8

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 14.1 15.1 16.1 14.9 14.8 14.3 14.1

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.7 12.6 13.2 14.1 12.9 11.1 10.1 10.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.6 16.5 17.0 15.2 14.6 13.9 13.1

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 17.2 17.0 18.7 18.4 16.8 16.6 16.1

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 19.6 20.9 21.8 23.0 21.0 20.8 19.1 18.5

Not central city. . . . . . . . . . . . . . . . . . . . . 10.7 11.3 11.7 12.5 12.2 10.8 10.7 10.2

Nonmetropolitan area. . . . . . . . . . . . . . . . . 14.7 14.6 15.3 16.2 14.7 13.5 13.2 13.1

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–9

U.S. Census Bureau
Table B5. Poverty Rates Standardized to Match the Official Rate for All Persons in 1997 With Experimental

Thresholds Based on Consumer Expenditure Survey Data: 1990 to 1997—Con.

Table B5c. DCM1a Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 14.1 14.8 15.5 16.4 15.2 14.3 13.8 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 21.0 21.7 22.6 20.7 19.3 18.6 17.9

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.5 12.1 12.6 13.6 12.5 12.0 11.5 11.0

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.3 16.5 17.1 16.3 15.1 15.4 14.5

Unrelated individuals . . . . . . . . . . . . . . . . . 21.1 21.4 21.9 23.7 22.1 20.7 20.4 20.2

Family members:

Householder or spouse . . . . . . . . . . . 11.9 12.4 14.0 14.3 13.6 12.5 12.9 12.1

Other relative . . . . . . . . . . . . . . . . . . . . 10.1 11.2 12.0 10.2 11.8 10.0 12.7 8.4

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 12.5 13.0 13.8 13.0 12.2 11.9 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.8 29.1 31.0 31.6 27.1 26.2 25.3 23.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.3 18.1 18.4 21.9 22.0 18.8 16.7 16.7

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 31.8 32.9 33.0 33.8 32.6 30.7 29.6 27.1

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 35.4 36.0 38.6 39.3 38.1 35.7 35.2 33.8

One or more workers . . . . . . . . . . . . . . . . . 10.5 11.0 11.4 12.2 11.1 10.6 10.3 9.9

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.7 9.1 9.7 10.3 9.1 8.5 8.2 7.7

Male householder . . . . . . . . . . . . . . . . . . 16.2 16.6 18.0 19.4 18.2 17.5 16.3 15.6

Female householder. . . . . . . . . . . . . . . . 30.1 31.5 31.9 33.0 31.7 29.2 28.7 28.1

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 13.0 13.9 14.9 16.0 14.9 14.7 14.3 14.1

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 12.6 13.2 13.8 13.0 11.1 10.4 10.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.0 15.5 16.6 16.9 15.0 14.6 14.3 13.3

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.6 17.1 16.8 18.7 18.0 16.8 16.4 15.9

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 19.4 20.7 21.6 22.8 21.0 20.7 19.3 18.5

Not central city. . . . . . . . . . . . . . . . . . . . . 10.5 11.3 11.6 12.6 12.0 10.8 10.8 10.2

Nonmetropolitan area. . . . . . . . . . . . . . . . . 14.8 14.5 15.3 15.9 14.5 13.4 13.3 13.2

a

Child care method based on SIPP.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–10 APPENDIX B

U.S. Census Bureau
Table B5. Poverty Rates Standardized to Match the Official Rate for All Persons in 1997 With Experimental

Thresholds Based on Consumer Expenditure Survey Data: 1990 to 1997—Con.

Table B5d. DCM2b Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 14.9 15.5 16.5 15.3 14.3 13.8 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.8 21.0 21.6 22.5 20.7 19.1 18.3 17.7

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.6 12.2 12.6 13.6 12.7 12.0 11.5 11.0

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 15.6 16.8 17.5 16.6 15.5 15.6 14.9

Unrelated individuals . . . . . . . . . . . . . . . . . 21.6 21.8 22.3 24.2 22.6 21.4 20.7 20.7

Family members:

Householder or spouse . . . . . . . . . . . 12.2 12.6 14.3 14.7 13.8 12.8 13.1 12.4

Other relative . . . . . . . . . . . . . . . . . . . . 10.2 11.2 12.2 10.4 11.6 10.5 12.6 8.9

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.1 12.7 13.0 13.9 13.1 12.3 11.9 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.8 28.8 30.9 31.3 27.1 26.0 24.6 23.2

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 18.5 18.5 21.5 22.0 18.7 16.8 16.9

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 31.8 33.1 32.8 34.0 32.6 31.0 29.6 26.9

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 36.0 36.6 39.4 40.0 38.8 36.4 35.8 34.4

One or more workers . . . . . . . . . . . . . . . . . 10.4 11.0 11.3 12.2 11.1 10.5 10.1 9.8

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.8 9.2 9.7 10.5 9.3 8.6 8.2 7.8

Male householder . . . . . . . . . . . . . . . . . . 16.1 16.8 18.1 19.3 18.3 17.6 16.0 15.6

Female householder. . . . . . . . . . . . . . . . 30.1 31.3 31.9 32.8 31.7 29.2 28.5 27.8

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 13.1 14.1 15.0 16.1 14.9 14.8 14.3 14.0

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.7 12.6 13.2 14.0 12.9 11.1 10.2 10.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.0 15.6 16.6 16.9 15.2 14.7 14.1 13.3

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.7 17.2 16.9 18.7 18.2 16.8 16.6 16.0

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 19.6 20.8 21.7 22.9 20.9 20.8 19.3 18.5

Not central city. . . . . . . . . . . . . . . . . . . . . 10.5 11.3 11.7 12.6 12.2 10.8 10.7 10.2

Nonmetropolitan area. . . . . . . . . . . . . . . . . 14.7 14.6 15.3 16.0 14.8 13.6 13.4 13.2

b

Child care method based on AFDC program allowances.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–11

U.S. Census Bureau
Table B5. Poverty Rates Standardized to Match the Official Rate for All Persons in 1997 With Experimental

Thresholds Based on Consumer Expenditure Survey Data: 1990 to 1997—Con.

Table B5e. DES-DCM2c Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 14.8 15.6 16.4 15.2 14.4 13.8 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.3 20.4 21.3 22.0 20.3 18.7 17.8 17.3

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.7 12.2 12.9 13.8 12.8 12.2 11.6 11.2

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4 15.7 17.0 17.5 16.5 15.9 15.8 14.9

Unrelated individuals . . . . . . . . . . . . . . . 24.0 24.5 25.2 26.8 24.4 24.3 23.1 22.9

Family members:

Householder or spouse . . . . . . . . . . . 11.2 11.4 13.2 13.3 12.6 11.8 12.1 11.2

Other relative . . . . . . . . . . . . . . . . . . . . 9.9 10.5 11.6 10.4 11.3 10.3 12.0 8.6

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.1 12.6 13.1 13.9 13.0 12.3 11.9 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.9 28.7 31.0 31.4 27.3 26.4 24.9 23.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.0 18.1 18.5 21.7 21.8 18.4 16.6 16.9

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 31.7 32.5 32.7 33.7 32.0 30.7 28.9 26.5

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 36.5 36.9 39.5 40.4 38.8 37.1 36.3 34.5

One or more workers . . . . . . . . . . . . . . . . . 10.3 10.9 11.3 12.1 11.1 10.5 10.0 9.8

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.3 8.6 9.3 9.9 8.8 8.1 7.7 7.3

Male householder . . . . . . . . . . . . . . . . . . 17.1 17.9 19.3 20.5 19.3 18.6 17.0 16.6

Female householder. . . . . . . . . . . . . . . . 31.1 32.3 33.1 33.7 32.5 30.4 29.5 28.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 13.0 14.1 15.0 15.9 15.0 15.0 14.3 14.2

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 12.6 13.2 13.9 13.0 11.1 10.1 10.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.5 16.7 17.0 15.1 14.6 14.1 13.2

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 16.7 17.1 18.7 18.1 16.9 16.6 16.0

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 19.7 20.9 21.8 22.9 21.1 21.1 19.3 18.4

Not central city. . . . . . . . . . . . . . . . . . . . . 10.5 11.1 11.8 12.5 12.0 10.8 10.6 10.3

Nonmetropolitan area. . . . . . . . . . . . . . . . . 14.4 14.4 15.3 16.0 14.7 13.4 13.5 13.0

c

Child care method based on AFDC program allowances and three-parameter equivalence scale.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–12 APPENDIX B

U.S. Census Bureau
Table B5. Poverty Rates Standardized to Match the Official Rate for All Persons in 1997 With Experimental

Thresholds Based on Consumer Expenditure Survey Data: 1990 to 1997—Con.

Table B5f. NGAd Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 14.4 15.1 15.7 16.5 15.3 14.5 13.7 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.0 20.9 21.6 22.4 20.8 19.2 18.0 17.4

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.8 12.3 12.8 13.6 12.7 12.1 11.4 11.1

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.5 16.2 17.4 17.7 16.9 15.8 15.7 15.3

Unrelated individuals . . . . . . . . . . . . . . . 22.1 22.6 23.1 24.8 22.8 22.1 20.7 20.9

Family members:

Householder or spouse . . . . . . . . . . . 12.5 13.1 14.9 14.8 14.1 12.9 13.3 13.0

Other relative . . . . . . . . . . . . . . . . . . . . 10.1 11.3 11.7 10.1 12.1 10.4 11.9 8.7

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.3 12.9 13.3 14.0 13.2 12.5 11.9 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.5 28.8 31.1 31.4 27.3 25.9 24.6 23.2

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.4 17.9 17.4 20.4 20.4 17.7 15.3 16.3

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 28.2 29.4 29.6 30.6 29.8 29.6 26.3 24.9

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 35.9 36.6 39.2 40.2 38.5 36.3 35.8 34.9

One or more workers . . . . . . . . . . . . . . . . . 10.7 11.2 11.5 12.1 11.2 10.7 10.0 9.7

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 9.1 9.5 10.1 10.5 9.5 8.8 8.2 7.8

Male householder . . . . . . . . . . . . . . . . . . 16.2 17.1 17.9 18.9 18.0 17.6 15.9 15.3

Female householder. . . . . . . . . . . . . . . . 30.1 31.1 31.9 32.9 31.4 29.0 28.4 28.0

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 11.7 12.5 13.4 12.6 12.6 12.2 12.0

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 13.8 13.8 14.6 15.1 13.9 12.2 11.3 10.8

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.2 17.8 18.7 19.1 17.3 16.5 15.7 14.8

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.9 15.3 15.1 16.5 16.3 15.3 14.4 14.4

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 18.3 19.5 20.4 21.5 19.8 19.5 17.7 17.2

Not central city. . . . . . . . . . . . . . . . . . . . . 9.8 10.7 11.1 11.7 11.5 10.2 10.0 9.7

Nonmetropolitan area. . . . . . . . . . . . . . . . . 18.9 18.6 19.2 19.9 18.5 17.7 17.1 16.5

d

NAS measure with no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–13

U.S. Census Bureau
Table B5. Poverty Rates Standardized to Match the Official Rate for All Persons in 1997 With Experimental

Thresholds Based on Consumer Expenditure Survey Data: 1990 to 1997—Con.

Table B5g. DES-DCM2-NGAe Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3 15.0 15.7 16.4 15.1 14.4 13.6 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.4 20.5 21.1 22.0 20.0 18.8 17.5 17.2

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.9 12.4 12.9 13.7 12.7 12.1 11.5 11.2

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.7 16.2 17.7 17.6 16.9 15.9 15.9 15.2

Unrelated individuals . . . . . . . . . . . . . . . 24.9 24.9 26.1 27.0 25.2 24.5 23.1 22.9

Family members:

Householder or spouse . . . . . . . . . . . 11.3 12.0 13.9 13.4 12.8 11.8 12.4 11.6

Other relative . . . . . . . . . . . . . . . . . . . . 9.5 10.3 11.8 9.9 11.5 9.6 11.2 8.6

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 12.8 13.2 13.9 13.1 12.4 11.8 11.6

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.2 29.1 30.8 31.5 26.9 26.0 24.8 23.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.7 17.2 17.5 20.2 20.1 17.4 15.6 15.9

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 27.8 28.8 29.0 29.6 29.0 28.7 25.7 24.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 36.0 36.6 39.5 40.0 38.5 36.2 35.9 34.7

One or more workers . . . . . . . . . . . . . . . . . 10.6 11.1 11.4 12.1 11.0 10.6 9.9 9.7

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.6 8.9 9.4 9.9 8.8 8.3 7.6 7.3

Male householder . . . . . . . . . . . . . . . . . . 16.9 18.1 19.1 20.0 19.1 18.4 16.8 16.2

Female householder. . . . . . . . . . . . . . . . 31.0 32.0 32.9 33.8 32.1 29.9 29.4 28.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 10.7 11.7 12.4 13.4 12.7 12.4 12.4 11.8

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 13.7 13.9 14.5 15.1 13.8 12.2 11.2 10.8

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.2 17.7 18.8 19.2 16.9 16.5 15.6 15.1

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.9 15.0 15.0 16.2 15.9 15.0 14.2 14.2

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 18.3 19.6 20.2 21.5 19.5 19.6 18.0 17.2

Not central city. . . . . . . . . . . . . . . . . . . . . 9.8 10.6 11.1 11.7 11.3 10.1 9.8 9.7

Nonmetropolitan area. . . . . . . . . . . . . . . . . 18.7 18.1 19.2 19.8 18.2 17.4 16.9 16.4

e

Child care method based on AFDC program allowances, three-parameter equivalence scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–14 APPENDIX B

U.S. Census Bureau
Table B6. Poverty Rates With Experimental Thresholds Based on Consumer Expenditure Survey Data: 1990 to

1997

Table B6a. Official Poverty Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.5 14.2 14.8 15.1 14.6 13.8 13.7 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 21.8 22.4 22.7 21.8 20.8 20.5 19.9

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 10.8 11.4 11.9 12.4 11.9 11.4 11.4 10.9

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 12.4 12.9 12.2 11.7 10.5 10.8 10.5

Unrelated individuals . . . . . . . . . . . . . . . 24.7 24.9 24.9 24.1 23.1 21.4 20.9 21.0

Family members:

Householder or spouse . . . . . . . . . . . 5.9 5.9 7.1 6.4 5.8 4.7 5.3 5.3

Other relative . . . . . . . . . . . . . . . . . . . . 5.8 7.0 7.6 7.4 8.4 7.9 8.7 6.1

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.7 11.3 11.9 12.2 11.7 11.2 11.2 11.0

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.9 32.7 33.4 33.1 30.6 29.3 28.4 26.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4 17.6 17.4 18.9 21.1 17.8 17.6 16.1

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 28.1 28.7 29.6 30.6 30.7 30.3 29.4 27.1

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 40.2 40.5 42.0 42.4 40.7 38.2 38.1 36.3

One or more workers . . . . . . . . . . . . . . . . . 8.9 9.5 10.0 10.2 9.9 9.6 9.6 9.5

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 6.9 7.2 7.7 8.0 7.4 6.8 6.9 6.4

Male householder . . . . . . . . . . . . . . . . . . 15.5 16.3 17.9 18.0 18.3 16.9 16.2 16.1

Female householder. . . . . . . . . . . . . . . . 33.1 34.8 34.9 34.8 34.2 32.4 32.0 31.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 12.2 12.6 13.3 12.9 12.5 12.7 12.6

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 13.2 13.3 13.4 13.0 11.0 10.7 10.4

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 16.1 17.1 17.2 16.1 15.7 15.1 14.6

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.0 14.3 14.9 15.6 15.3 14.9 15.4 14.6

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 19.0 20.2 20.9 21.5 20.9 20.6 19.6 18.8

Not central city. . . . . . . . . . . . . . . . . . . . . 8.7 9.6 9.9 10.3 10.3 9.1 9.4 9.0

Nonmetropolitan area. . . . . . . . . . . . . . . . . 16.3 16.1 16.9 17.2 16.0 15.6 15.9 15.9

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–15

U.S. Census Bureau
Table B6. Poverty Rates With Experimental Thresholds Based on Consumer Expenditure Survey Data: 1990 to

1997−Con.

Table B6b. NAS/U Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 16.8 17.5 18.2 19.1 17.8 16.9 16.2 15.4

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.5 24.6 24.9 25.9 23.8 22.5 21.4 20.3

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 13.7 14.3 14.9 15.8 14.8 14.2 13.5 12.8

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.8 18.6 20.3 20.6 19.5 18.3 18.4 17.4

Unrelated individuals . . . . . . . . . . . . . . . 25.3 25.9 26.8 28.4 25.9 25.6 24.3 23.9

Family members:

Householder or spouse . . . . . . . . . . . 14.4 15.1 17.3 17.2 16.4 14.8 15.7 14.5

Other relative . . . . . . . . . . . . . . . . . . . . 11.2 13.2 14.7 13.9 14.5 13.3 13.7 10.3

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 14.9 15.4 16.2 15.3 14.6 14.1 13.4

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.2 34.1 35.0 35.8 31.2 30.3 28.8 26.8

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.4 21.5 22.4 25.0 25.2 21.5 19.5 18.8

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 37.0 38.4 38.3 39.5 37.3 36.9 34.7 31.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 41.0 41.5 44.0 44.7 43.1 41.0 40.4 38.4

One or more workers . . . . . . . . . . . . . . . . . 12.6 13.2 13.6 14.4 13.3 12.8 12.1 11.6

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.7 11.1 12.0 12.4 11.3 10.7 10.1 9.4

Male householder . . . . . . . . . . . . . . . . . . 18.5 19.5 20.7 21.7 20.9 19.8 18.4 17.5

Female householder. . . . . . . . . . . . . . . . 34.9 36.2 35.8 37.3 35.5 33.4 32.6 31.4

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 15.5 16.5 17.6 18.6 17.5 17.6 17.1 16.2

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 14.7 14.9 15.6 16.1 14.8 12.9 12.4 11.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.8 18.5 19.3 19.6 17.9 17.2 16.3 15.3

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.6 19.9 19.8 21.8 21.0 20.0 19.3 18.6

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 23.0 24.1 25.2 26.2 24.3 24.1 22.5 21.2

Not central city. . . . . . . . . . . . . . . . . . . . . 12.4 13.4 13.7 14.7 14.2 12.9 12.7 11.9

Nonmetropolitan area. . . . . . . . . . . . . . . . . 17.7 17.5 18.1 18.8 17.2 16.2 15.6 15.4

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–16 APPENDIX B

U.S. Census Bureau
Table B6. Poverty Rates With Experimental Thresholds Based on Consumer Expenditure Survey Data: 1990 to

1997−Con.

Table B6c. DCM1/Ua Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 17.1 17.9 18.6 19.5 18.3 17.4 16.8 15.9

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.2 25.3 25.8 26.7 24.8 23.6 22.6 21.4

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 14.0 14.6 15.2 16.1 15.2 14.6 13.9 13.2

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.8 18.6 20.3 20.6 19.5 18.3 18.5 17.4

Unrelated individuals . . . . . . . . . . . . . . . 25.3 25.9 26.8 28.4 25.9 25.6 24.3 23.9

Family members:

Householder or spouse . . . . . . . . . . . 14.4 15.1 17.3 17.2 16.4 14.8 15.7 14.5

Other relative . . . . . . . . . . . . . . . . . . . . 11.2 13.3 15.0 13.9 14.6 13.4 14.0 10.3

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.5 15.2 15.8 16.5 15.7 15.1 14.4 13.8

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.7 34.9 35.8 37.0 32.2 31.1 30.4 27.9

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.6 22.2 22.7 25.3 25.8 22.3 20.5 19.2

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 37.7 39.1 39.2 40.1 38.2 38.1 35.9 33.0

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 41.0 41.5 44.0 44.7 43.1 41.0 40.4 38.4

One or more workers . . . . . . . . . . . . . . . . . 13.0 13.7 14.1 14.8 13.9 13.4 12.8 12.2

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.9 11.4 12.2 12.7 11.7 11.0 10.4 9.7

Male householder . . . . . . . . . . . . . . . . . . 18.6 19.4 20.9 22.0 21.2 20.2 18.9 18.0

Female householder. . . . . . . . . . . . . . . . 35.7 37.0 36.9 38.3 36.5 34.6 33.9 32.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 16.7 17.9 18.9 18.0 18.2 17.6 16.6

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.4 16.1 16.5 15.4 13.3 12.7 12.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.4 18.9 19.7 20.2 18.4 17.8 17.1 16.0

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 20.2 20.3 22.0 21.3 20.7 19.7 19.2

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 23.4 24.4 25.7 26.7 24.8 24.7 23.4 22.1

Not central city. . . . . . . . . . . . . . . . . . . . . 12.7 13.7 14.1 15.0 14.6 13.4 13.1 12.4

Nonmetropolitan area. . . . . . . . . . . . . . . . . 18.0 17.9 18.6 19.2 17.8 16.7 16.2 15.7

a

Child care method based on SIPP.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–17

U.S. Census Bureau
Table B6. Poverty Rates With Experimental Thresholds Based on Consumer Expenditure Survey Data: 1990 to

1997−Con.

Table B6d. DCM2/Ub Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 16.8 17.6 18.3 19.1 17.9 17.0 16.3 15.4

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.5 24.7 25.1 26.1 24.0 22.8 21.6 20.5

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 13.7 14.4 14.9 15.8 14.9 14.3 13.6 12.9

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.8 18.6 20.3 20.6 19.5 18.3 18.4 17.4

Unrelated individuals . . . . . . . . . . . . . . . 25.3 25.9 26.8 28.4 25.9 25.6 24.3 23.9

Family members:

Householder or spouse . . . . . . . . . . . 14.4 15.1 17.3 17.1 16.4 14.8 15.7 14.5

Other relative . . . . . . . . . . . . . . . . . . . . 11.3 13.3 14.7 13.9 14.5 13.3 13.7 10.3

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 14.9 15.5 16.3 15.4 14.7 14.1 13.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.1 34.2 35.2 35.9 31.4 30.5 28.9 26.8

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.4 21.6 22.5 25.1 25.4 21.7 19.4 18.8

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 37.1 38.3 38.3 39.4 37.4 37.1 34.9 31.7

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 41.0 41.5 44.0 44.7 43.1 41.0 40.4 38.4

One or more workers . . . . . . . . . . . . . . . . . 12.6 13.3 13.7 14.5 13.4 12.9 12.2 11.7

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.8 11.2 12.0 12.5 11.4 10.7 10.1 9.4

Male householder . . . . . . . . . . . . . . . . . . 18.4 19.3 20.8 21.8 20.8 20.0 18.5 17.6

Female householder. . . . . . . . . . . . . . . . 34.8 36.2 36.1 37.4 35.7 33.7 32.8 31.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 15.5 16.5 17.6 18.7 17.7 17.8 17.1 16.3

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 14.7 15.0 15.6 16.1 15.0 13.0 12.5 11.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.8 18.6 19.3 19.7 17.9 17.4 16.4 15.5

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.6 20.0 20.0 21.9 21.1 20.0 19.4 18.6

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 23.0 24.1 25.2 26.2 24.4 24.2 22.6 21.2

Not central city. . . . . . . . . . . . . . . . . . . . . 12.4 13.5 13.8 14.8 14.3 13.0 12.7 12.1

Nonmetropolitan area. . . . . . . . . . . . . . . . . 17.7 17.6 18.2 18.9 17.3 16.5 15.7 15.4

b

Child care method based on AFDC program allowances.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–18 APPENDIX B

U.S. Census Bureau
Table B6. Poverty Rates With Experimental Thresholds Based on Consumer Expenditure Survey Data: 1990 to

1997−Con.

Table B6e. DES-DCM2/Uc Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 17.5 18.2 19.0 19.9 18.5 17.7 17.0 16.1

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.9 25.1 25.6 26.6 24.3 23.2 22.1 20.8

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 14.5 15.0 15.7 16.7 15.5 14.9 14.4 13.6

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.9 19.7 21.0 21.6 20.2 19.3 19.3 18.4

Unrelated individuals . . . . . . . . . . . . . . . 29.7 30.5 31.3 32.9 30.2 30.0 28.5 28.2

Family members:

Householder or spouse . . . . . . . . . . . 13.6 14.3 16.1 16.3 15.3 14.1 14.7 13.9

Other relative . . . . . . . . . . . . . . . . . . . . 12.6 13.3 15.3 14.6 14.3 12.5 14.0 10.2

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.5 16.1 17.0 15.9 15.3 14.8 14.1

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34.2 35.4 36.8 37.4 32.5 31.7 30.3 28.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.3 22.1 23.2 25.4 25.9 22.0 20.4 19.0

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 38.0 39.1 39.3 40.6 38.7 37.9 35.7 32.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 42.7 43.0 45.5 46.1 44.4 42.6 42.0 39.9

One or more workers . . . . . . . . . . . . . . . . . 13.1 13.8 14.3 15.1 13.9 13.4 12.8 12.2

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.7 11.1 11.9 12.5 11.2 10.6 10.0 9.3

Male householder . . . . . . . . . . . . . . . . . . 20.3 21.6 22.8 23.8 23.0 21.8 20.6 19.6

Female householder. . . . . . . . . . . . . . . . 37.3 38.5 38.7 39.9 38.0 36.0 35.2 33.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 16.3 17.2 18.3 19.4 18.3 18.3 18.0 17.1

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4 15.8 16.3 16.9 15.5 13.5 13.0 12.2

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.5 19.1 20.2 20.7 18.4 18.1 17.1 16.2

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.3 20.5 20.7 22.4 21.8 20.8 20.2 19.3

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 24.1 25.1 26.3 27.4 25.2 25.1 23.8 22.2

Not central city. . . . . . . . . . . . . . . . . . . . . 12.8 14.0 14.4 15.4 14.7 13.5 13.3 12.5

Nonmetropolitan area. . . . . . . . . . . . . . . . . 18.4 17.9 18.9 19.7 17.8 17.2 16.4 16.0

c

Child care method based on AFDC program allowances and three-parameter equivalence scale.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–19

U.S. Census Bureau
Table B6. Poverty Rates With Experimental Thresholds Based on Consumer Expenditure Survey Data: 1990 to

1997−Con.

Table B6f. NGA/Ud Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 17.4 17.9 18.7 19.4 18.1 17.3 16.4 15.8

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.3 24.9 25.7 26.3 24.4 23.0 21.6 21.0

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 14.2 14.6 15.2 16.0 15.0 14.4 13.7 13.1

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.9 19.2 21.1 21.2 20.0 19.4 19.0 17.9

Unrelated individuals . . . . . . . . . . . . . . . 26.7 26.7 28.2 29.0 26.9 26.4 24.8 24.5

Family members:

Householder or spouse . . . . . . . . . . . 15.3 15.7 17.8 17.9 16.7 16.0 16.3 15.1

Other relative . . . . . . . . . . . . . . . . . . . . 11.7 13.3 15.4 13.2 13.9 14.3 13.3 10.5

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.3 15.9 16.7 15.8 15.1 14.4 13.8

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.9 34.1 36.1 35.5 31.4 30.4 29.2 27.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.6 20.5 21.6 23.2 24.1 20.7 18.4 18.5

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 34.3 34.7 35.0 36.1 35.1 34.8 32.1 30.2

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 41.5 41.5 44.5 45.1 43.1 41.7 40.8 39.1

One or more workers . . . . . . . . . . . . . . . . . 13.2 13.6 14.1 14.7 13.7 13.1 12.4 11.9

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 11.5 11.7 12.5 13.0 11.9 11.1 10.4 9.8

Male householder . . . . . . . . . . . . . . . . . . 18.6 19.2 20.9 21.4 20.8 20.1 18.4 17.4

Female householder. . . . . . . . . . . . . . . . 35.3 36.0 36.6 37.4 35.5 33.6 32.8 32.1

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 13.2 13.9 15.1 15.8 15.0 15.0 14.2 14.0

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 16.6 16.6 17.4 17.9 16.6 14.5 13.7 12.9

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 21.1 22.1 22.5 20.3 19.9 18.8 17.6

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.1 17.9 18.1 19.5 19.1 18.2 17.5 17.3

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 22.0 23.0 24.1 25.1 23.2 23.1 21.3 20.5

Not central city. . . . . . . . . . . . . . . . . . . . . 12.0 12.7 13.2 13.8 13.5 12.2 11.9 11.4

Nonmetropolitan area. . . . . . . . . . . . . . . . . 22.8 22.1 23.2 24.0 22.3 21.5 20.8 19.9

d

NAS measure with no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–20 APPENDIX B

U.S. Census Bureau
Table B6. Poverty Rates With Experimental Thresholds Based on Consumer Expenditure Survey Data: 1990 to

1997−Con.

Table B6g. DES-DCM2-NGA/Ue Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 18.0 18.7 19.5 20.3 18.9 18.0 17.3 16.5

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.6 25.6 26.3 27.1 25.0 23.5 22.5 21.5

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 14.9 15.4 16.1 16.9 15.8 15.2 14.6 13.9

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 20.3 21.8 22.2 20.9 20.1 19.8 18.9

Unrelated individuals . . . . . . . . . . . . . . . 31.2 31.3 32.4 33.7 30.9 30.8 29.5 28.5

Family members:

Householder or spouse . . . . . . . . . . . 14.4 14.9 16.8 16.9 16.1 14.8 15.0 14.4

Other relative . . . . . . . . . . . . . . . . . . . . 12.9 13.4 16.0 13.4 14.0 14.2 13.8 11.0

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.5 16.1 16.6 17.4 16.3 15.7 15.1 14.4

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.0 35.3 37.3 37.9 33.2 31.7 31.0 28.9

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.6 21.6 21.9 24.0 24.8 21.7 19.4 18.7

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 35.1 36.1 36.0 37.5 36.0 35.5 33.2 30.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 42.9 43.2 46.1 46.5 44.6 43.1 42.4 40.6

One or more workers . . . . . . . . . . . . . . . . . 13.7 14.3 14.7 15.5 14.3 13.7 13.1 12.5

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 11.4 11.7 12.4 13.0 11.8 10.9 10.4 9.6

Male householder . . . . . . . . . . . . . . . . . . 20.7 21.3 23.1 23.7 22.9 22.1 20.5 19.6

Female householder. . . . . . . . . . . . . . . . 37.7 38.9 39.2 40.2 38.0 36.3 35.7 34.6

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 14.0 14.9 15.8 16.7 15.8 15.7 15.1 14.8

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 17.1 17.4 18.2 18.6 17.2 15.2 14.4 13.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.4 21.9 22.9 23.5 21.2 20.5 19.9 18.5

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.5 18.5 18.6 20.2 19.8 18.9 18.4 17.7

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 22.9 24.0 25.2 26.3 24.2 24.1 22.6 21.6

Not central city. . . . . . . . . . . . . . . . . . . . . 12.4 13.3 13.7 14.4 14.1 12.7 12.5 11.9

Nonmetropolitan area. . . . . . . . . . . . . . . . . 23.4 22.9 24.0 24.8 23.0 22.2 21.7 20.6

e

Child care method based on AFDC program allowances, three-parameter equivalence scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–21

U.S. Census Bureau
Table B7. Poverty Rates Standardized to Match Offical Rates for All Persons in 1997 With Experimental

Thresholds Based on the CPI-U: 1990 to 1997

Table B7a. Official Poverty Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.5 14.2 14.8 15.1 14.6 13.8 13.7 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 21.8 22.4 22.7 21.8 20.8 20.5 19.9

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 10.8 11.4 11.9 12.4 11.9 11.4 11.4 10.9

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 12.4 12.9 12.2 11.7 10.5 10.8 10.5

Unrelated individuals . . . . . . . . . . . . . . . 24.7 24.9 24.9 24.1 23.1 21.4 20.9 21.0

Family members:

Householder or spouse . . . . . . . . . . . 5.9 5.9 7.1 6.4 5.8 4.7 5.3 5.3

Other relative . . . . . . . . . . . . . . . . . . . . 5.8 7.0 7.6 7.4 8.4 7.9 8.7 6.1

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.7 11.3 11.9 12.2 11.7 11.2 11.2 11.0

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.9 32.7 33.4 33.1 30.6 29.3 28.4 26.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4 17.6 17.4 18.9 21.1 17.8 17.6 16.1

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 28.1 28.7 29.6 30.6 30.7 30.3 29.4 27.1

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 40.2 40.5 42.0 42.4 40.7 38.2 38.1 36.3

One or more workers . . . . . . . . . . . . . . . . . 8.9 9.5 10.0 10.2 9.9 9.6 9.6 9.5

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 6.9 7.2 7.7 8.0 7.4 6.8 6.9 6.4

Male householder . . . . . . . . . . . . . . . . . . 15.5 16.3 17.9 18.0 18.3 16.9 16.2 16.1

Female householder. . . . . . . . . . . . . . . . 33.1 34.8 34.9 34.8 34.2 32.4 32.0 31.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 12.2 12.6 13.3 12.9 12.5 12.7 12.6

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 13.2 13.3 13.4 13.0 11.0 10.7 10.4

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 16.1 17.1 17.2 16.1 15.7 15.1 14.6

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.0 14.3 14.9 15.6 15.3 14.9 15.4 14.6

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 19.0 20.2 20.9 21.5 20.9 20.6 19.6 18.8

Not central city. . . . . . . . . . . . . . . . . . . . . 8.7 9.6 9.9 10.3 10.3 9.1 9.4 9.0

Nonmetropolitan area. . . . . . . . . . . . . . . . . 16.3 16.1 16.9 17.2 16.0 15.6 15.9 15.9

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–22 APPENDIX B

U.S. Census Bureau
Table B7. Poverty Rates Standardized to Match Offical Rates for All Persons in 1997 With Experimental

Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B7b. NAS-CPI Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.7 14.5 15.1 15.8 14.6 13.8 13.6 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.0 20.3 21.0 21.7 19.7 18.4 17.8 17.6

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.2 11.8 12.3 13.1 12.1 11.6 11.1 11.1

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.8 15.2 16.4 16.8 16.1 14.9 15.6 15.0

Unrelated individuals . . . . . . . . . . . . . . . 20.9 21.2 21.9 23.4 21.8 20.5 20.5 20.8

Family members:

Householder or spouse . . . . . . . . . . . 11.9 12.4 14.0 14.0 13.4 12.4 13.1 12.5

Other relative . . . . . . . . . . . . . . . . . . . . 10.0 10.8 11.8 9.7 11.5 9.5 12.5 8.9

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 12.3 12.7 13.4 12.5 11.8 11.7 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.7 28.1 30.3 30.1 25.9 25.1 24.2 23.3

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.6 17.7 17.9 21.0 21.1 17.8 16.7 17.0

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 30.9 32.2 32.1 32.9 31.4 29.5 29.2 27.0

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 35.2 35.9 38.5 38.8 37.8 35.4 35.5 34.4

One or more workers . . . . . . . . . . . . . . . . . 9.9 10.6 10.9 11.6 10.5 10.1 9.9 9.8

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.4 8.9 9.4 9.9 8.8 8.2 8.1 7.8

Male householder . . . . . . . . . . . . . . . . . . 15.8 16.4 17.7 18.8 17.8 17.0 15.9 15.6

Female householder. . . . . . . . . . . . . . . . 29.0 30.6 31.1 31.8 30.6 28.3 28.0 27.8

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 13.5 14.6 15.3 14.2 14.2 14.1 14.1

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 12.3 12.8 13.5 12.3 10.8 10.0 10.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3 15.2 16.1 16.3 14.6 14.1 13.8 13.1

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 16.6 16.6 18.2 17.5 16.2 16.4 16.1

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 18.8 20.3 21.2 22.2 20.1 20.1 18.8 18.5

Not central city. . . . . . . . . . . . . . . . . . . . . 10.2 11.0 11.4 12.1 11.6 10.4 10.6 10.2

Nonmetropolitan area. . . . . . . . . . . . . . . . . 14.1 14.0 14.9 15.4 14.1 13.0 13.1 13.1

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–23

U.S. Census Bureau
Table B7. Poverty Rates Standardized to Match Offical Rates for All Persons in 1997 With Experimental

Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B7c. DCM1-CPIa Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.6 14.3 15.0 15.7 14.5 13.8 13.7 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.2 20.2 21.0 21.6 19.7 18.6 18.4 17.9

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.1 11.7 12.2 13.0 12.0 11.5 11.4 11.0

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.4 14.7 16.0 16.4 15.6 14.5 15.2 14.5

Unrelated individuals . . . . . . . . . . . . . . . 20.3 20.5 21.3 22.9 21.2 19.9 20.1 20.2

Family members:

Householder or spouse . . . . . . . . . . . 11.6 11.9 13.6 13.6 12.9 12.0 12.7 12.1

Other relative . . . . . . . . . . . . . . . . . . . . 9.9 10.7 11.9 9.5 11.2 9.6 12.5 8.4

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.5 12.1 12.6 13.1 12.4 11.8 13.9 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.9 27.9 29.8 30.5 25.6 25.2 28.4 23.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.0 17.6 17.9 21.4 21.0 17.9 19.2 16.7

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 30.6 31.8 32.2 32.3 31.3 29.5 29.3 27.1

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 34.5 35.0 37.7 38.0 36.8 34.6 34.9 33.8

One or more workers . . . . . . . . . . . . . . . . . 10.0 10.6 11.0 11.6 10.6 10.2 10.2 9.9

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.4 8.7 9.4 9.7 8.8 8.1 8.1 7.7

Male householder . . . . . . . . . . . . . . . . . . 15.6 16.2 17.6 18.8 17.4 17.0 16.1 15.6

Female householder. . . . . . . . . . . . . . . . 29.1 30.6 30.9 31.9 30.2 28.3 28.5 28.1

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 13.3 14.3 15.2 14.1 14.1 14.1 14.1

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 12.1 12.7 13.3 12.4 10.8 10.3 10.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.5 14.9 16.1 16.2 14.4 14.2 14.2 13.3

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.0 16.6 16.5 17.9 17.2 16.1 16.1 15.9

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 18.8 20.0 20.9 22.0 20.0 20.1 19.2 18.5

Not central city. . . . . . . . . . . . . . . . . . . . . 10.1 10.8 11.4 12.0 11.4 10.4 10.7 10.2

Nonmetropolitan area. . . . . . . . . . . . . . . . . 14.2 13.9 14.8 15.1 14.1 12.8 13.2 13.2

a

Child care method based on SIPP.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–24 APPENDIX B

U.S. Census Bureau
Table B7. Poverty Rates Standardized to Match Offical Rates for All Persons in 1997 With Experimental

Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B7d. DCM2-CPIb Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.6 14.4 15.1 15.8 14.6 13.8 13.6 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.0 20.2 21.0 21.6 19.7 18.4 18.0 17.7

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.1 11.7 12.3 13.0 12.1 11.5 11.3 11.0

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.7 15.1 16.3 16.7 16.0 14.8 15.5 14.9

Unrelated individuals . . . . . . . . . . . . . . . 20.7 21.0 21.8 23.3 21.6 20.3 20.4 20.7

Family members:

Householder or spouse . . . . . . . . . . . 11.8 12.3 13.9 13.9 13.3 12.3 13.0 12.4

Other relative . . . . . . . . . . . . . . . . . . . . 10.0 10.6 11.9 9.5 11.5 9.4 12.6 8.9

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 12.2 12.6 13.3 12.5 11.8 11.7 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.6 27.7 30.2 30.0 25.8 25.1 24.4 23.2

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.6 17.8 18.1 21.1 20.9 17.8 16.7 16.9

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 30.8 32.0 31.9 32.8 31.1 29.5 29.1 26.9

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 35.1 35.7 38.3 38.6 37.5 35.1 35.3 34.4

One or more workers . . . . . . . . . . . . . . . . . 9.9 10.6 10.9 11.6 10.5 10.1 9.9 9.8

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.4 8.8 9.4 9.9 8.8 8.2 8.1 7.8

Male householder . . . . . . . . . . . . . . . . . . 15.6 16.3 17.6 18.7 17.6 17.0 15.9 15.6

Female householder. . . . . . . . . . . . . . . . 29.0 30.4 31.0 31.6 30.3 28.2 28.1 27.8

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 13.5 14.4 15.3 14.2 14.1 14.1 14.0

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 12.2 12.9 13.3 12.3 10.7 10.1 10.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.4 15.1 16.1 16.2 14.5 14.1 13.9 13.3

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 16.5 16.5 18.2 17.3 16.2 16.3 16.0

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 18.8 20.3 21.0 22.0 20.0 20.1 19.0 18.5

Not central city. . . . . . . . . . . . . . . . . . . . . 10.1 10.9 11.4 12.1 11.6 10.3 10.5 10.2

Nonmetropolitan area. . . . . . . . . . . . . . . . . 14.2 13.9 14.9 15.3 14.1 12.9 13.2 13.2

b

Child care method based on AFDC program allowances.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–25

U.S. Census Bureau
Table B7. Poverty Rates Standardized to Match Offical Rates for All Persons in 1997 With Experimental

Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B7e. DES-DCM2-CPIc Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.5 14.3 15.1 15.7 14.5 13.8 13.6 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.4 19.7 20.6 21.2 19.2 18.0 17.6 17.3

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.2 11.9 12.4 13.2 12.2 11.7 11.5 11.2

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.8 15.3 16.6 16.6 15.7 15.2 15.6 14.9

Unrelated individuals . . . . . . . . . . . . . . . 23.0 23.7 24.4 25.4 23.6 23.4 22.7 22.8

Family members:

Householder or spouse . . . . . . . . . . . 10.8 11.2 13.0 12.6 11.9 11.4 12.0 11.2

Other relative . . . . . . . . . . . . . . . . . . . . 9.6 10.4 11.2 9.7 10.7 9.6 11.6 8.6

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.5 12.2 12.7 13.3 12.4 11.9 11.7 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.3 27.8 30.2 30.0 25.9 25.2 24.7 23.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.6 17.9 18.1 21.1 20.7 18.1 16.5 16.9

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 30.5 31.2 31.4 32.5 30.8 29.5 28.6 26.5

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 35.3 36.0 38.6 39.0 37.1 35.8 36.0 34.5

One or more workers . . . . . . . . . . . . . . . . . 9.7 10.5 10.9 11.5 10.5 10.1 9.8 9.8

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 7.9 8.2 8.9 9.4 8.3 7.7 7.6 7.3

Male householder . . . . . . . . . . . . . . . . . . 16.5 17.5 18.7 19.9 18.5 18.1 16.8 16.6

Female householder. . . . . . . . . . . . . . . . 29.8 31.5 32.2 32.5 31.1 29.3 29.2 28.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 13.6 14.5 15.1 14.2 14.6 14.1 14.2

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 12.3 12.7 13.4 12.3 10.7 10.1 10.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 15.0 16.2 16.2 14.5 14.0 13.8 13.2

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 16.2 16.5 18.0 17.2 16.3 16.4 16.0

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 18.8 20.3 21.0 22.1 20.0 20.3 19.0 18.4

Not central city. . . . . . . . . . . . . . . . . . . . . 10.0 10.8 11.4 11.9 11.5 10.4 10.5 10.3

Nonmetropolitan area. . . . . . . . . . . . . . . . . 13.8 13.8 14.9 15.3 14.0 12.9 13.2 13.0

c

Child care method based on AFDC program allowances and three-parameter equivalence scale.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–26 APPENDIX B

U.S. Census Bureau
Table B7. Poverty Rates Standardized to Match Offical Rates for All Persons in 1997 With Experimental

Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B7f. NGA-CPId Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.8 14.6 15.2 15.8 14.6 13.9 13.5 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 20.3 21.0 21.5 19.7 18.4 17.8 17.4

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.3 11.9 12.4 13.0 12.1 11.7 11.3 11.1

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.6 16.9 17.0 16.2 15.1 15.4 15.3

Unrelated individuals . . . . . . . . . . . . . . . 21.3 21.8 22.3 23.7 21.8 21.1 20.4 20.9

Family members:

Householder or spouse . . . . . . . . . . . 12.0 12.7 14.6 14.2 13.5 12.4 13.1 13.0

Other relative . . . . . . . . . . . . . . . . . . . . 9.4 10.4 11.1 9.8 11.4 10.1 11.8 8.7

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.8 12.4 12.9 13.3 12.6 12.0 11.7 11.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.3 28.0 30.3 30.3 26.3 25.1 24.3 23.2

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.9 17.3 16.9 19.6 19.5 17.0 15.1 16.3

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 26.8 28.5 28.7 29.2 28.3 28.6 26.0 24.9

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 34.8 35.7 38.4 38.9 37.5 35.2 35.4 34.9

One or more workers . . . . . . . . . . . . . . . . . 10.1 10.8 11.1 11.6 10.6 10.2 9.8 9.7

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.6 9.1 9.7 9.9 8.9 8.4 8.0 7.8

Male householder . . . . . . . . . . . . . . . . . . 15.7 16.6 17.4 18.3 17.3 17.0 15.7 15.3

Female householder. . . . . . . . . . . . . . . . 29.0 30.3 31.1 31.8 30.3 28.1 28.0 28.0

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 11.3 12.1 12.9 12.0 12.0 12.0 12.0

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 13.3 14.0 14.4 13.2 11.7 11.1 10.8

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.4 17.3 18.2 18.2 16.5 15.8 15.4 14.8

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 14.8 14.7 15.9 15.5 14.8 14.3 14.4

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 17.5 18.9 19.8 20.6 18.9 18.9 17.5 17.2

Not central city. . . . . . . . . . . . . . . . . . . . . 9.4 10.3 10.8 11.3 10.9 9.8 9.8 9.4

Nonmetropolitan area. . . . . . . . . . . . . . . . . 18.0 18.0 18.6 19.0 17.5 16.8 16.9 16.5

d

NAS measure with no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–27

U.S. Census Bureau
Table B7. Poverty Rates Standardized to Match Offical Rates for All Persons in 1997 With Experimental

Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B7g. DES-DCM2-NGA-CPIe Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.7 14.4 15.2 15.7 14.5 13.8 13.4 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.6 19.6 20.5 21.0 19.1 18.0 17.2 17.2

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 11.4 12.0 12.5 13.2 12.1 11.7 11.3 11.2

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.0 15.6 17.1 16.9 16.1 15.5 15.8 15.2

Unrelated individuals . . . . . . . . . . . . . . . 23.7 24.1 25.1 25.9 24.3 23.7 22.9 22.9

Family members:

Householder or spouse . . . . . . . . . . . 10.8 11.6 13.4 13.0 12.1 11.6 12.3 11.6

Other relative . . . . . . . . . . . . . . . . . . . . 8.9 9.9 11.2 9.1 11.0 9.3 11.2 8.6

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.7 12.3 12.8 13.3 12.5 11.9 11.6 11.6

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.0 27.9 30.0 30.2 25.8 25.2 24.3 23.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.0 16.7 17.0 19.3 19.3 16.6 15.2 15.9

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 26.7 27.6 28.2 28.1 27.8 27.8 25.3 24.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 34.9 35.4 38.5 38.6 37.3 35.4 35.6 34.7

One or more workers . . . . . . . . . . . . . . . . . 10.0 10.7 11.0 11.5 10.4 10.1 9.7 9.7

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 8.2 8.5 9.1 9.4 8.3 7.9 7.4 7.3

Male householder . . . . . . . . . . . . . . . . . . 16.4 17.5 18.6 19.5 18.3 17.8 16.7 16.2

Female householder. . . . . . . . . . . . . . . . 29.8 31.0 31.9 32.5 30.9 29.0 29.0 28.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 11.3 12.0 12.9 12.0 11.8 12.2 11.8

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2 13.2 14.0 14.4 13.1 11.8 11.0 10.8

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.4 17.1 18.2 18.3 16.2 15.9 15.3 15.1

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 14.4 14.5 15.5 15.3 14.5 14.0 14.2

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 17.5 18.8 19.6 20.6 18.8 19.0 17.7 17.2

Not central city. . . . . . . . . . . . . . . . . . . . . 9.3 10.2 10.7 11.2 10.8 9.7 9.7 9.7

Nonmetropolitan area. . . . . . . . . . . . . . . . . 17.8 17.6 18.6 18.9 17.3 16.7 16.6 16.4

e

Child care method based on AFDC program allowances, three-parameter equivalence scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–28 APPENDIX B

U.S. Census Bureau
Table B8. Poverty Rates With Experimental Thresholds Based on the CPI-U: 1990 to 1997

Table B8a. Official Poverty Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 13.5 14.2 14.8 15.1 14.6 13.8 13.7 13.3

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 21.8 22.4 22.7 21.8 20.8 20.5 19.9

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 10.8 11.4 11.9 12.4 11.9 11.4 11.4 10.9

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 12.4 12.9 12.2 11.7 10.5 10.8 10.5

Unrelated individuals . . . . . . . . . . . . . . . 24.7 24.9 24.9 24.1 23.1 21.4 20.9 21.0

Family members:

Householder or spouse . . . . . . . . . . . 5.9 5.9 7.1 6.4 5.8 4.7 5.3 5.3

Other relative . . . . . . . . . . . . . . . . . . . . 5.8 7.0 7.6 7.4 8.4 7.9 8.7 6.1

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.7 11.3 11.9 12.2 11.7 11.2 11.2 11.0

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.9 32.7 33.4 33.1 30.6 29.3 28.4 26.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4 17.6 17.4 18.9 21.1 17.8 17.6 16.1

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 28.1 28.7 29.6 30.6 30.7 30.3 29.4 27.1

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 40.2 40.5 42.0 42.4 40.7 38.2 38.1 36.3

One or more workers . . . . . . . . . . . . . . . . . 8.9 9.5 10.0 10.2 9.9 9.6 9.6 9.5

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 6.9 7.2 7.7 8.0 7.4 6.8 6.9 6.4

Male householder . . . . . . . . . . . . . . . . . . 15.5 16.3 17.9 18.0 18.3 16.9 16.2 16.1

Female householder. . . . . . . . . . . . . . . . 33.1 34.8 34.9 34.8 34.2 32.4 32.0 31.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 12.2 12.6 13.3 12.9 12.5 12.7 12.6

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 13.2 13.3 13.4 13.0 11.0 10.7 10.4

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 16.1 17.1 17.2 16.1 15.7 15.1 14.6

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.0 14.3 14.9 15.6 15.3 14.9 15.4 14.6

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 19.0 20.2 20.9 21.5 20.9 20.6 19.6 18.8

Not central city. . . . . . . . . . . . . . . . . . . . . 8.7 9.6 9.9 10.3 10.3 9.1 9.4 9.0

Nonmetropolitan area. . . . . . . . . . . . . . . . . 16.3 16.1 16.9 17.2 16.0 15.6 15.9 15.9

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–29

U.S. Census Bureau
Table B8. Poverty Rates With Experimental Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B8b. NAS/U-CPI Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 16.9 17.6 18.3 17.0 16.3 16.0 15.4

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.5 23.8 24.3 24.8 22.8 21.7 21.1 20.3

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 13.1 13.8 14.4 15.2 14.1 13.6 13.4 12.8

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.1 17.9 19.4 19.7 18.5 17.7 18.3 17.4

Unrelated individuals . . . . . . . . . . . . . . . 24.3 24.9 25.9 27.0 24.7 24.6 24.0 23.9

Family members:

Householder or spouse . . . . . . . . . . . 13.7 14.5 16.5 16.5 15.6 14.4 15.6 14.5

Other relative . . . . . . . . . . . . . . . . . . . . 10.8 12.7 14.0 13.2 13.9 12.7 13.7 10.3

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.7 14.4 14.9 15.5 14.6 14.0 13.9 13.4

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.5 33.1 34.0 34.5 30.1 29.4 28.4 26.8

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.7 20.2 21.5 24.0 23.9 20.8 19.2 18.8

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 35.7 37.2 37.2 37.9 36.1 35.4 34.2 31.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 39.8 40.4 42.9 43.4 41.8 40.0 40.0 38.4

One or more workers . . . . . . . . . . . . . . . . . 12.0 12.7 13.1 13.7 12.6 12.2 12.0 11.6

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.2 10.7 11.5 11.8 10.6 10.1 9.9 9.4

Male householder . . . . . . . . . . . . . . . . . . 17.7 18.9 20.1 21.1 20.2 19.2 18.3 17.5

Female householder. . . . . . . . . . . . . . . . 33.7 35.2 35.0 36.0 34.5 32.5 32.3 31.4

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.9 17.0 17.8 16.7 17.0 16.9 16.2

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 14.1 14.4 15.0 15.5 14.2 12.5 12.2 11.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.0 17.8 18.7 18.9 17.0 16.7 16.1 15.3

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.9 19.3 19.4 20.8 20.2 19.1 19.0 18.6

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 22.2 23.4 24.5 25.3 23.3 23.4 22.3 21.2

Not central city. . . . . . . . . . . . . . . . . . . . . 11.9 12.9 13.3 14.1 13.6 12.3 12.6 11.9

Nonmetropolitan area. . . . . . . . . . . . . . . . . 16.7 16.9 17.4 18.0 16.2 15.6 15.3 15.4

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–30 APPENDIX B

U.S. Census Bureau
Table B8. Poverty Rates With Experimental Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B8c. DCM1/U-CPIa Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 16.4 17.3 18.0 18.8 17.5 16.8 16.6 15.9

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.2 24.5 25.1 25.8 23.9 22.7 22.4 21.4

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 13.4 14.1 14.7 15.5 14.5 14.0 13.8 13.2

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.1 17.9 19.4 19.7 18.5 17.7 18.3 17.4

Unrelated individuals . . . . . . . . . . . . . . . 24.3 24.9 25.9 27.0 24.7 24.6 24.0 23.9

Family members:

Householder or spouse . . . . . . . . . . . 13.7 14.5 16.5 16.5 15.6 14.4 15.6 14.5

Other relative . . . . . . . . . . . . . . . . . . . . 10.9 13.0 14.2 13.3 13.9 12.6 13.9 10.3

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.0 14.6 15.3 15.8 15.0 14.4 14.3 13.8

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.4 34.0 34.8 36.0 31.0 30.3 30.2 27.9

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.9 20.7 21.6 24.7 24.6 21.7 20.2 19.2

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 36.4 37.8 38.1 38.8 37.0 36.5 35.5 33.0

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 39.8 40.4 42.9 43.4 41.8 40.0 40.0 38.4

One or more workers . . . . . . . . . . . . . . . . . 12.4 13.2 13.6 14.2 13.2 12.8 12.7 12.2

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.4 10.9 11.7 12.1 11.0 10.4 10.3 9.7

Male householder . . . . . . . . . . . . . . . . . . 17.9 18.9 20.3 21.5 20.5 19.5 18.8 18.0

Female householder. . . . . . . . . . . . . . . . 34.5 36.0 36.0 37.1 35.4 33.6 33.6 32.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 16.0 17.4 18.2 17.3 17.5 17.4 16.6

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3 14.9 15.4 15.9 14.8 12.8 12.6 12.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.6 18.3 19.1 19.5 17.5 17.1 17.0 16.0

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.1 19.5 19.7 21.2 20.5 19.8 19.6 19.2

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 22.6 23.8 25.0 25.9 23.9 23.9 23.2 22.1

Not central city. . . . . . . . . . . . . . . . . . . . . 12.2 13.3 13.6 14.4 14.0 12.8 13.0 12.4

Nonmetropolitan area. . . . . . . . . . . . . . . . . 17.2 17.2 17.8 18.4 16.8 16.0 15.9 15.7

a

Child care method based on SIPP.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–31

U.S. Census Bureau
Table B8. Poverty Rates With Experimental Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B8d. DCM2/U-CPIb Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 17.0 17.7 18.4 17.1 16.4 16.1 15.4

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 23.9 24.4 25.0 23.1 22.0 21.4 20.5

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 13.2 13.9 14.4 15.2 14.2 13.7 13.4 12.9

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.1 17.9 19.4 19.7 18.5 17.7 18.3 17.4

Unrelated individuals . . . . . . . . . . . . . . . 24.3 24.9 25.9 27.0 24.7 24.6 24.0 23.9

Family members:

Householder or spouse . . . . . . . . . . . 13.7 14.5 16.5 16.5 15.6 14.4 15.6 14.5

Other relative . . . . . . . . . . . . . . . . . . . . 10.8 12.9 13.9 13.2 14.0 12.7 13.7 10.3

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.7 14.4 15.0 15.6 14.7 14.1 14.0 13.5

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.8 33.2 34.0 34.6 30.3 29.6 28.7 26.8

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.6 20.2 21.7 24.1 24.2 21.1 19.2 18.8

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 35.9 37.2 37.2 37.9 36.0 35.6 34.4 31.7

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 39.8 40.4 42.9 43.4 41.8 40.0 40.0 38.4

One or more workers . . . . . . . . . . . . . . . . . 12.0 12.8 13.2 13.8 12.7 12.4 12.1 11.7

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.3 10.8 11.5 11.9 10.7 10.2 10.0 9.4

Male householder . . . . . . . . . . . . . . . . . . 17.6 18.7 20.2 21.1 20.0 19.4 18.3 17.6

Female householder. . . . . . . . . . . . . . . . 33.7 35.3 35.2 36.1 34.7 32.8 32.5 31.5

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.9 17.1 17.9 16.8 17.0 16.9 16.3

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 14.6 15.0 15.6 14.4 12.6 12.4 11.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.1 17.9 18.7 18.9 17.0 16.8 16.2 15.5

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.9 19.3 19.4 20.9 20.3 19.2 19.2 18.6

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 22.2 23.4 24.4 25.3 23.4 23.4 22.4 21.2

Not central city. . . . . . . . . . . . . . . . . . . . . 11.9 13.0 13.4 14.1 13.6 12.5 12.6 12.1

Nonmetropolitan area. . . . . . . . . . . . . . . . . 16.8 16.9 17.5 18.1 16.3 15.8 15.5 15.4

b

Child care method based on AFDC program allowances.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–32 APPENDIX B

U.S. Census Bureau
Table B8. Poverty Rates With Experimental Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B8e. DES-DCM2/U-CPIc Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 16.8 17.7 18.4 19.1 17.6 17.0 16.8 16.1

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.0 24.3 24.9 25.6 23.3 22.3 21.9 20.8

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 13.9 14.6 15.2 16.0 14.8 14.3 14.2 13.6

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.1 18.9 20.3 20.7 19.4 18.5 19.0 18.4

Unrelated individuals . . . . . . . . . . . . . . . 28.4 29.4 30.2 31.5 28.8 28.8 28.0 28.2

Family members:

Householder or spouse . . . . . . . . . . . 13.0 13.8 15.6 15.7 14.7 13.5 14.5 13.9

Other relative . . . . . . . . . . . . . . . . . . . . 12.2 12.7 14.9 13.2 13.7 12.4 14.0 10.2

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3 15.0 15.6 16.3 15.2 14.6 14.5 14.1

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.8 34.2 35.5 35.8 31.0 30.8 30.1 28.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.4 21.7 22.4 24.2 25.1 21.5 20.3 19.0

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 36.4 37.8 38.3 39.2 37.0 36.3 35.1 32.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 41.3 42.0 44.5 44.9 43.2 41.5 41.6 39.9

One or more workers . . . . . . . . . . . . . . . . . 12.5 13.3 13.7 14.4 13.1 12.7 12.6 12.2

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.2 10.7 11.5 11.9 10.5 10.1 9.9 9.3

Male householder . . . . . . . . . . . . . . . . . . 19.5 21.0 22.1 22.9 22.3 20.9 20.3 19.6

Female householder. . . . . . . . . . . . . . . . 36.1 37.4 37.6 38.6 36.7 34.9 34.8 33.7

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 15.6 16.7 17.8 18.5 17.4 17.6 17.8 17.1

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 14.8 15.1 15.8 16.2 14.8 13.1 12.7 12.2

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.7 18.6 19.5 19.8 17.6 17.4 17.0 16.2

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.6 20.0 20.1 21.7 21.0 19.9 19.9 19.3

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 23.2 24.3 25.4 26.3 24.1 24.3 23.5 22.2

Not central city. . . . . . . . . . . . . . . . . . . . . 12.4 13.6 13.9 14.7 14.1 12.9 13.1 12.5

Nonmetropolitan area. . . . . . . . . . . . . . . . . 17.5 17.4 18.3 18.9 17.0 16.3 16.2 16.0

c

Child care method based on AFDC program allowances and three-parameter equivalence scale.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–33

U.S. Census Bureau
Table B8. Poverty Rates With Experimental Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B8f. NGA/U-CPId Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 16.6 17.3 18.2 18.6 17.3 16.6 16.2 15.8

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.1 24.2 24.9 25.3 23.4 22.1 21.3 21.0

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 13.5 14.1 14.8 15.4 14.4 13.8 13.5 13.1

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.9 18.6 20.4 20.2 19.2 18.5 18.7 17.9

Unrelated individuals . . . . . . . . . . . . . . . 25.5 26.0 22.3 27.8 25.8 25.2 24.6 24.5

Family members:

Householder or spouse . . . . . . . . . . . 14.5 15.1 14.6 16.9 16.1 15.3 16.1 15.1

Other relative . . . . . . . . . . . . . . . . . . . . 11.0 13.0 11.1 12.2 13.2 13.9 13.3 10.5

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 14.8 15.5 15.9 15.0 14.5 14.1 13.8

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.6 33.0 35.0 34.5 30.4 29.2 28.9 27.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.6 19.9 20.9 22.6 23.1 19.9 18.1 18.5

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 32.7 33.8 34.0 34.6 33.6 33.5 31.7 30.2

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 40.1 40.6 43.6 43.8 41.9 40.4 40.4 39.1

One or more workers . . . . . . . . . . . . . . . . . 12.5 13.1 13.6 14.0 13.0 12.5 12.2 11.9

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.8 11.3 12.0 12.2 11.2 10.5 10.2 9.8

Male householder . . . . . . . . . . . . . . . . . . 18.0 18.8 20.2 20.8 20.0 19.6 18.3 17.4

Female householder. . . . . . . . . . . . . . . . 33.9 35.1 35.7 36.3 34.3 32.5 32.4 32.1

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 13.5 14.5 15.1 14.4 14.4 14.0 14.0

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 16.1 16.9 17.0 15.9 13.9 13.4 12.9

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.7 20.4 21.4 21.6 19.4 19.1 18.6 17.6

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.2 17.4 17.6 18.7 18.2 17.5 17.3 17.3

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 21.0 22.3 23.5 24.2 22.3 22.1 21.0 20.5

Not central city. . . . . . . . . . . . . . . . . . . . . 11.3 12.3 12.8 13.2 12.9 11.7 11.7 11.4

Nonmetropolitan area. . . . . . . . . . . . . . . . . 21.8 21.3 22.3 22.7 21.2 20.6 20.4 19.9

d

NAS measure with no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

B–34 APPENDIX B

U.S. Census Bureau
Table B8. Poverty Rates With Experimental Thresholds Based on the CPI-U: 1990 to 1997−Con.

Table B8g. DES-DCM2-NGA/U-CPIe Measure

1990 1991 1992 1993 1994 1995 1996 1997

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . 17.3 18.1 18.9 19.4 18.1 17.2 17.1 16.5

Children. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.6 24.9 25.6 25.9 24.0 22.5 22.3 21.5

Nonelderly adults . . . . . . . . . . . . . . . . . . . . 14.3 14.9 15.6 16.2 15.2 14.5 14.4 13.9

Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.0 19.5 21.0 21.1 20.1 19.1 19.6 18.9

Unrelated individuals . . . . . . . . . . . . . . . 29.8 30.1 31.3 32.2 29.9 29.6 29.0 28.5

Family members:

Householder or spouse . . . . . . . . . . . 13.7 14.4 16.2 16.0 15.3 13.9 14.9 14.4

Other relative . . . . . . . . . . . . . . . . . . . . 12.1 12.7 15.1 12.5 13.5 12.6 13.6 11.0

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 15.6 16.1 16.6 15.7 15.0 14.9 14.4

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34.0 34.5 36.5 36.2 31.9 30.3 30.7 28.9

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.9 20.7 21.3 23.0 23.9 20.8 19.2 18.7

Hispanic origin1 . . . . . . . . . . . . . . . . . . . . . . 33.6 34.9 35.0 35.8 34.4 34.2 32.9 30.6

No workers . . . . . . . . . . . . . . . . . . . . . . . . . . 41.6 42.2 45.1 45.1 43.3 41.5 41.9 40.6

One or more workers . . . . . . . . . . . . . . . . . 13.1 13.8 14.2 14.7 13.7 13.0 13.0 12.5

Persons in family of type:

Married couple. . . . . . . . . . . . . . . . . . . . . 10.8 11.3 11.9 12.3 11.2 10.4 10.2 9.6

Male householder . . . . . . . . . . . . . . . . . . 19.7 20.6 22.6 22.7 22.2 21.2 20.4 19.6

Female householder. . . . . . . . . . . . . . . . 36.6 37.9 38.4 38.7 36.7 34.8 35.3 34.6

Geographic regions:

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 14.4 15.2 15.8 15.0 15.0 14.9 14.8

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . 16.5 16.9 17.8 17.6 16.5 14.4 14.2 13.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 21.2 22.3 22.5 20.3 19.7 19.7 18.5

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.7 18.1 18.1 19.4 19.0 18.1 18.1 17.7

Metropolitan area:

Central city . . . . . . . . . . . . . . . . . . . . . . . . 22.0 23.4 24.5 25.1 23.3 23.0 22.4 21.6

Not central city. . . . . . . . . . . . . . . . . . . . . 11.9 12.9 13.3 13.9 13.6 12.2 12.4 11.9

Nonmetropolitan area. . . . . . . . . . . . . . . . . 22.5 22.2 23.2 23.6 21.9 21.3 21.4 20.6

e

Child care method based on AFDC program allowances, three-parameter equivalence scale, and no geographic adjustment.

1

Persons of Hispanic origin may be of any race.

Source: U.S. Census Bureau tabulations of March Current Population Survey data.

APPENDIX B B–35

U.S. Census Bureau
Appendix C.

Definitions of Elements in the Experimental

Poverty Measures

DEFINING THE THRESHOLDS

In this study, as in the study by the National Academy

of Science Panel on Poverty Measurement and Family

Assistance (hereafter the panel) and in previous work (Garner et al., 1998 and Short et al., May 1998), the thresholds

are calculated by following several steps. First, median

expenditures (adjusted to current dollars) for reference

units are obtained from the Consumer Expenditure Survey

(CEX) using their food, clothing, shelter, and utilities

(FCSU) expenditures.1 Second, percentages of median

expenditures are selected which reflect the 30th and 35th

percentiles of the distribution of FCSU expenditures. These

percentiles translate to approximately 78 and 83 percent

of the median. The panel concluded in their study that

these percentiles seem to represent a reasonable range for

the FCSU component of the reference family’s threshold.2

Third, expenses for their other needs (e.g., household

supplies, personal care, and nonwork-related expenses)

are accounted for through the use of a small multiplier.

The panel recommended a lower and upper value for the

multiplier of 1.15 and 1.25, respectively. They stated that

this range of multipliers compared favorably to estimates

from other studies3 that range from 1.14 to 1.30. In this

study, as in the panel’s work, the base-year threshold is

computed by taking the average of these upper and lower

values for both the percentages and multipliers (i.e.,

Threshold = 0.5 * (1.15 * .78 + 1.25 * .83) * median),

with the result being that the threshold equals 0.96725 *

median expenditures for the basic bundle. Hence, the

resulting threshold of $15,998 is almost equal to median

expenditures on FCSU of $16,540 for 1997.

Fourth, adjustments are made to reflect geographic differences in costs. Following the panel, we use interarea

housing cost indexes calculated from the 1990 census

data on gross rent (not including utilities) for apartments

with specified characteristics, adjusted for the share of

housing (including utilities) in the proposed poverty budget.4 5 These indexes are produced for five population size

categories within each of the nine geographic census divisions. In our application, we normalize the indexes based

on the geographic distribution of the weighted sample.

The area indexes are produced relative to the U.S. average

index, which is equal to 1.0. For example, the threshold

for the reference unit in a large metropolitan area in New

England is 27 percent higher than the national average,

while it is 15 percent lower than the national average if

this family lives in a nonmetropolitan area in the West

South Central region (as shown in Table C3).

Fifth, an equivalence scale adjusts the reference unit’s

threshold to produce thresholds for family units with different characteristics from those of the reference unit. The

panel recommended a two-parameter equivalence scale

that accounts for the differing needs of adults and children and the economies of scale of living in a larger

household. This scale is (A+pK)f

, where A and K represent

the number of adults and children, p represents the adultequivalent of one child and f represents the scale

economy factor. Since the choice of equivalence scale can

have substantial effects on the distribution of poverty,6 we

examine other equivalence scales using the 1997 CPS and

the official resource definition.

Sixth, the base year thresholds are updated over time

using a price adjustment factor. While the panel recommended updating by the change in median expenditures

on FCSU each year (a quasi-relative adjustment7), they also

recommended that an alternative set of thresholds be produced during the first several years after the new poverty

measure is implemented which are updated for price

change only.8 In this report we present two alternative

choices for updating the thresholds.

There are also some slight differences in the calculation

of the thresholds in this report from previous work. The

thresholds presented here do not include rent as pay or 1

The panel assumed that the quarterly interviews are independent and produced annual expenditures by multiplying each reference unit’s expenditures by four. All expenditures were converted to

1992 constant dollars. For example, if the collection quarter of the

data occurred sometime during 1989, the 1989 expenditures were

updated using the change in overall prices between 1989 and 1992.

An alternative to the all-items CPI-U could have been used for this

purpose. For example, a weighted average of the CPIs for the items

included in the threshold could have been used. 2

Citro and Michael, 1995, p. 149.

3

For example, see Renwick, 1993, pp. 573-582; Bureau of Labor

Statistics, 1982; Schwarz and Volgy, 1992.

4

The panel set this share at 44 percent.

5

Johnson et al., 1997 found that these indexes produced similar

results to those using interarea price indexes that account for more

expenditure categories than housing. 6

See Citro and Michael, 1995 and Johnson et al., 1997.

7

An explicitly relative adjustment would tie poverty thresholds

directly to changes in levels of living, such as median income or

expenditures on all goods. Updating with changes in consumption

of basic goods is a more conservative approach. 8

Citro and Michael, 1995, p. 7.

APPENDIX C C–1

U.S. Census Bureau
interest on home equity loans in the calculation of shelter

costs. They exclude expenditures on utilities for vacation

homes. They also do not include food as pay in the calculation of food expenditures.

Table C1 presents the official thresholds and the experimental thresholds used in this report for 1990 through

1997. The thresholds presented in column (2) are based

on estimates of median expenditures using 3-year averages of CEX data and those in column (3) are CPI-U

adjusted backward from 1997. From 1990 to 1997, the

CPI-U adjusted thresholds increased by 22.8 percent while

the median expenditure adjusted thresholds increased by

19.9 percent. In contrast, the panel found that the median

expenditures increased more than the CPI-U between 1980

and 1992. However, the panel noted that such a relationship may not hold for the year-to-year changes.9 We found

that for the longer period between 1982 and 1997, the

median expenditures for the basic bundle also increased

more than the CPI-U.10 Changes in the estimated median

expenditures are more volatile than changes in the CPI-U,

due in part to the relatively small sample sizes (approximately 5,000 consumer units are interviewed each quarter

but only about 9.5 percent of the consumer units are families with two adults and two children) in the CEX.

9

Citro and Michael, 1995, p. 158.

10Johnson et al., 1997.

Table C1. Thresholds for a Reference Family of Two Adults With Two Children

[Dollars]

Year

Official

FCSU1

CEX CPI-U

1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13,254 13,342 13,028

1991 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13,812 13,843 13,576

1992 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14,228 14,253 13,985

1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14,654 14,791 14,403

1994 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,029 15,166 14,772

1995 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,455 15,545 15,191

1996 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,911 15,744 15,639

1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16,276 15,998 15,998

Percent change 1990 to 1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.8 19.9 22.8

1

Food, clothing, shelter, and utilities.

Note: Columns adjusted backward from 1997 estimates; see text for details.

Source: Bureau of Labor Statistics tabulations of Consumer Expenditure Survey data.

Table C2. Alternative Equivalence Scales

Family type

Official

Two-parameter scales1

Threeparameter

scale2 Canadian3

f=0.65;

p=0.7

f=0.75;

p=0.7

f=0.65;

p=0.85

f=0.5;

p=1.0

Single adult ............................. 4

0.513 0.451 0.399 0.427 0.500 0.463 0.500

Two adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

0.660 0.708 0.672 0.700 0.707 0.653 0.670

Three adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.771 0.922 0.910 0.873 0.866 1.000 0.900

Two adults, one child. . . . . . . . . . . . . . . . . . . . . 0.794 0.861 0.841 0.844 0.866 0.880 0.850

Two adults, two children . . . . . . . . . . . . . . . . . . 1.000 1.000 1.000 1.000 1.000 1.000 1.000

Two adults, three children. . . . . . . . . . . . . . . . . 1.177 1.129 1.151 1.144 1.118 1.114 1.150

One adult, one child. . . . . . . . . . . . . . . . . . . . . . 0.680 0.637 0.595 0.637 0.707 0.699 0.700

One adult, two children . . . . . . . . . . . . . . . . . . . 0.794 0.797 0.770 0.815 0.866 0.830 0.850

Ratios of Scale

Single adult to two adults . . . . . . . . . . . . . . . . . 0.777 0.637 0.595 0.637 0.707 0.714 0.709

Single parent with two children to two adults

with one child . . . . . . . . . . . . . . . . . . . . . . . . . . 1.000 0.926 0.915 0.965 1.000 1.000 0.943

1

Two-parameter scale = (adults + p * children)f

2

Three-parameter scale = (ratio of the scale for two adults to one adult is 1.41

For single parents (adults + .8 + .5 * children -1).7

All other families (adults + .5 * children).7) 3

Canadian scale = (1 + .4 * (adults - 1) + .4 * (first child) + .3 * (children -1))

4

Nonelderly adults.

Source: Johnson et al., 1997.

C–2 APPENDIX C

U.S. Census Bureau
EQUIVALENCE SCALES

To examine the sensitivity of the poverty rate to the

equivalence scale, we consider several different equivalence scales here. These scales include three different twoparameter scales, a one-parameter scale (the square root

of family size), the scales from the Canadian low-income

cutoffs and an alternative three-parameter scale. Table C2

presents the scales, normalized so that the scale for the

reference unit is 1.0.

The two-parameter scales are given by the following

parameter values: p=0.7 and f=0.65 (the panel’s lower

bound), p=0.7 and f=0.75 (the panel’s upper bound), and

p=0.85 and f=0.65. The one-parameter scale is basically a

two-parameter scale that treats adults and children similarly (i.e., p=1.0). These are also called constant-elasticity

scales. This scale was suggested by Watts11 and Ruggles12

and is given by the square root of family size (A+K)0.5.

The Canadian scale is determined by using 1.0 for the

first adult, 0.4 for each additional adult, and 0.3 for each

child.13 In single-parent families, the first child increased

the scale by 0.4 and each additional child by 0.3. The final

scale, proposed by Betson, is a three-parameter scale14

which allows for the first child in a single-adult family to

increase the scale more than the first child in a two-adult

family. In addition, the three-parameter scale15 restricts

the relationship between two-adult and one-adult families

so that the scale for the two-adult family is 41 percent

higher than the scale for the single-adult family.16 As

noted in the report, compared with the panel’s recommendation, the three-parameter scale provides more economies of scale between singles and childless couples and

more similarity between the scales for families of one parent with two children and two parents with one child.

To illustrate these latter two issues the last two rows in

Table C2 present the ratios of the scales for these family

types. The two-parameter scale assumes smaller economies of scale between one- and two-person families than

the other scales shown, and the two scales suggested by

the panel assume that single-parent families require less

than two-parent families of a similar size.

The other main difference between all these scales and

the official scales is the treatment of the elderly. None of

the experimental scales distinguish between elderly and

nonelderly families, while the official scales assign a single

elderly person a scale of 0.473 and an elderly couple a

scale of 0.597 (versus 0.513 and 0.660 for nonelderly

adults, respectively). In all cases, the scale (and respective

threshold) increases for elderly couples, and in all but two

cases, falls for single elderly individuals.

The main effect of these different scales is in the composition of the poor. The different thresholds for the elderly greatly affect their poverty rates. Table A2b in Appendix A shows that the elderly range from comprising 8.3

percent of the poverty population to 11.4 percent, compared with the current official proportion, 9.5 percent in

1997. The percentage composition for children ranges

from 38.0 percent to 41.0 percent. The various scales also

affect the composition for married couples and female

householder families; however, they do not change the

composition of the poverty population for regions or

race/ethnicity categories.

The final rows in Table A2a and Table A2b show that

the scales have a large impact on the poverty rates for

families of different sizes. The poverty rate for singles

ranges from 15.1 for the panel’s upper bound (f=0.75 and

p=0.7) to 21.4 percent for the square root of family size

(and also the Canadian scale). The poverty rate for twoperson families using these scales is 8.4 percent and 9.2

percent, representing the lower and upper bounds, respectively.

The significant effect on elderly poverty is again highlighted in Table A2a. Under the official poverty measure,

elderly unrelated individuals are almost four times more

likely than elderly couples (householder or spouse) to be

poor, while using the panel’s upper bound causes the likelihood to fall to only 1.5 times. In fact, all of the experimental scales yield a more equal likelihood of poverty

between singles and couples, with the three-parameter

scale yielding the largest differential between the two.

GEOGRAPHIC ADJUSTMENTS

As noted by the panel, ‘‘There is wide agreement that it

is desirable to adjust poverty thresholds for differences in

prices... [however] ...There are no geographic area cost-ofliving indexes that correspond to the Consumer Price

Index for Urban Consumers (CPI-U).’’17 Various approaches

have been proposed to estimate interarea price differences. In this section, the panel’s method for accounting

for differences in prices by geographic area is explained

first. This is followed by a method that uses interarea consumer price indexes developed by a team of researchers

at the Bureau of Labor Statistics.18

The NAS Panel’s Method

The panel developed an interarea price index for housing.19 They focused on housing because housing expenditures are the largest component of the poverty budget and

because variations in housing costs are significant by

11Suggested by Watts in conversation with the panel, see Citro

and Michael, 1995, p. 181, footnote b. 12Ruggles, 1990. 13Wolfson and Evans, 1989. 14See Betson, 1996. 15See Johnson et al., 1997 for applications of this scale. 16The three-parameter scale is given by 1.41 for two-adult only

households, (A + C + p(K-1))f for single-parent households and (A +

pK)f for other households, where p=.5, f=.7 and C=.8.

17Citro and Michael, 1995, pp. 182-183. 18Kokoski et al., 1994 (KCM). For alternative indexes, see Malpezzi et al., 1980 and 1998. 19Citro and Michael, 1995, pp. 194-197.

APPENDIX C C–3

U.S. Census Bureau
region and population size. They used a modified version

of a method developed by the Department of Housing and

Urban Development (HUD) for the administration of Section 8 rental housing subsidies. Using a combination of

data from the American Housing Survey, the latest decennial census, and a random-digit dialing survey, HUD develops a set of Fair Market Rents that vary by geographic

location. The panel used census data only and computed

index values for each of the 341 metropolitan areas (setting the U.S. average equal to 1.0). The index values were

based on the cost of two-bedroom rental units (not including utilities) with specific characteristics at the 45th percentile of the value of the distribution for each area. The

data were then grouped into six population size categories within each of the nine census divisions. The nonmetropolitan areas were aggregated by region and new index

values computed, which produced a final set of 41 index

values.

The index values were further adjusted for the estimated fraction of the poverty budget accounted for by

housing (including utilities), that was set at 44 percent.

This effectively created a fixed-weight interarea price

index with two components: housing, and all other goods

and services, where the price of other goods and services

was assumed not to vary. This narrowed the range of

index values. As the panel pointed out, the proposed procedure should not be viewed as the last word on the issue

of adjusting poverty thresholds for the area differences in

prices. Their procedure only accounts for differences in

housing costs. It also does not account for differences

within an area, differences in quality of a unit, or significantly higher housing costs in Alaska or Hawaii. The

resulting indexes are shown in Table C3. For this report,

the indexes are adjusted for each year of the CPS sample

so that the average of the indexes across all persons is

1.00. For example, for 1997 the indexes were divided by a

factor of 1.0252 to yield an average of 1.00 using the

March 1998 CPS.

BLS Experimental Interarea Price Indexes

In an earlier study,20 adjustments in expenditures for

interarea price differences were based on experimental

price index research performed at the Bureau of Labor

Statisticis (BLS) by Kokoski, Cardiff, and Moulton.21 These

researchers used a hedonic methodology and monthly

CPI-U price data for July 1988 through June 1989 to produce experimental interarea price indexes; indexes were

computed for the 44 CPI publication geographic areas.22

These experimental interarea price indexes were created

at the lowest level of CPI price data available and were

aggregated to form index factors for 11 major expenditure categories. This was accomplished by weighting

lower level indexes using expenditure shares from CEX

data. The resulting 11 expenditure categories comprise

about 85 percent of total consumer spending. In order to

account for the remaining 15 percent of expenditures, a

residual category vector was approximated by taking the

average of the 11 existing factors for each area. Although

the interarea price indexes are experimental, there are no

other suitable data currently available that can be utilized

to estimate interarea price differences.

To obtain the price indexes for each of the 45

region/size areas used in the panel’s report, Johnson et al.

(1997) used the 12 region/size averages from the procedure in Kokoski et al. for each of the three smaller areas in

each of the nine divisions. That is, the indexes for the

small, medium, and large size metro areas in the Western

region were used for areas with less than 250,000 people,

250,000-500,000 people, and 500,000-1,000,000 people

in both the Mountain and Pacific divisions. Indexes for the

larger areas (with 1,000,000-2,500,000 people and over

2,500,000 people) were obtained by taking the weighted

average of the metropolitan areas located in each division

that were represented in the interarea indices.

To compare the two methods, both sets of indexes

were adjusted so that the weighted average for the 45

region/size areas was 1.0 and were designed to measure

differences in prices between areas relative to the average

of all other areas. The work by Johnson et al. compared

the interarea consumer price indexes used by the panel

with the BLS interarea price indexes by division and population size. The indexes were applied by division and

population size to the thresholds calculated in an earlier

paper. Although the BLS interarea price indexes include

more expenditure categories than the panel’s housing

indexes, both methods produced similar indexes, with a

correlation coefficient of 0.78.

Table C4 shows the different thresholds using these different adjustments. This table illustrates the main differences between the BLS interarea approach and the panel’s

housing index approach. Since the BLS approach is based

on the Primary Sampling Unit (PSU) for the CEX, some metropolitan areas of similar size (e.g., Greater Los Angeles

and San Diego) within the same region have different

thresholds, while the housing index assigns the same

threshold. In addition, since there are only four regions in

the BLS approach, different regions of similar size (e.g.,

medium-sized cities in the Mid-Atlantic and New England

regions) receive similar thresholds under the BLS

approach, but different thresholds under the panel’s

approach. Finally, both adjustments cause the thresholds

in nonmetropolitan areas to be less than the national average.

FOOD STAMPS AND SCHOOL LUNCH SUBSIDIES

Both receipt of food stamps and the amount received

are reported in the Current Population Survey (CPS).

20Johnson et al., 1997. 21Kokoski et al., 1994. 22The KCM research is currently on hold. They are not official BLS

published data.

C–4 APPENDIX C

U.S. Census Bureau
Table C3. Geographic Adjustments for Housing Costs in Experimental Poverty Thresholds*

Area and population size Index value

Northeast

New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont)

Nonmetropolitan areas and metropolitan areas under 250,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.128

Metropolitan areas 250,000-500,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.128

Metropolitan areas 500,000-1,000,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.148

Metropolitan areas 1,000,000-2,500,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.141

Metropolitan areas 2,500,000 or more. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.209

Middle Atlantic (New Jersey, New York, Pennsylvania)

Nonmetropolitan areas and metropolitan areas under 250,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.908

Metropolitan areas 250,000-500,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.997

Metropolitan areas 500,000-1,000,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.020

Metropolitan areas 1,000,000-2,500,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.975

Metropolitan areas 2,500,000 or more. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.187

Midwest

East North Central (Illinois, Indiana, Michigan, Ohio, Wisconsin)

Nonmetropolitan areas and metropolitan areas under 250,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.896

Metropolitan areas 250,000-500,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.959

Metropolitan areas 500,000-1,000,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.987

Metropolitan areas 1,000,000-2,500,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.995

Metropolitan areas 2,500,000 or more. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.059

West North Central (Iowa Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota)

Nonmetropolitan areas and metropolitan areas under 250,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.861

Metropolitan areas 250,000-500,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.962

Metropolitan areas 500,000-1,000,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.981

Metropolitan areas 1,000,000-2,500,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.028

Metropolitan areas 2,500,000 or more (use areas 1-2.5 million) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NA

South

South Atlantic (Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina,

Virginia, West Virginia)

Nonmetropolitan areas and metropolitan areas under 250,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.899

Metropolitan areas 250,000-500,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.961

Metropolitan areas 500,000-1,000,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.007

Metropolitan areas 1,000,000-2,500,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.043

Metropolitan areas 2,500,000 or more. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.119

East South Central (Alabama, Kentucky, Mississippi, Tennessee)

Nonmetropolitan areas and metropolitan areas under 250,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.827

Metropolitan areas 250,000-500,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.935

Metropolitan areas 500,000-1,000,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.947

Metropolitan areas 1,000,000-2,500,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NA

Metropolitan areas 2,500,000 or more. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NA

West South Central (Arkansas, Louisiana, Oklahoma, Texas)

Nonmetropolitan areas and metropolitan areas under 250,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.858

Metropolitan areas 250,000-500,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.911

Metropolitan areas 500,000-1,000,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.942

Metropolitan areas 1,000,000-2,500,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.962

Metropolitan areas 2,500,000 or more. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.005

West

Mountain (Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming)

Nonmetropolitan areas and metropolitan areas under 250,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.888

Metropolitan areas 250,000-500,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.976

Metropolitan areas 500,000-1,000,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.039

Metropolitan areas 1,000,000-2,500,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.003

Metropolitan areas 2,500,000 or more. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NA

Pacific (Alaska, California, Hawaii, Oregon, Washington)

Nonmetropolitan areas and metropolitan areas under 250,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.969

Metropolitan areas 250,000-500,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.018

Metropolitan areas 500,000-1,000,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.028

Metropolitan areas 1,000,000-2,500,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.104

Metropolitan areas 2,500,000 or more. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.217

NA Not applicable.

* Table copied from Table 5-3, page 252: Constance F. Citro and Robert T. Michael (eds.) Measuring Poverty: A New Approach, Washington, DC:

National Academy Press, 1995.

APPENDIX C C–5

U.S. Census Bureau
Receipt and amount of food stamps are also collected in

the Survey of Income and Program Participation (SIPP).

This benefit is reported similarly in both surveys. However, in the CPS, respondents are asked if they ever

received food stamps in the previous calendar year. If they

answer that they did, then they are asked to report the

total amount received in that year. Respondents to the SIPP

are asked to report receipt of food stamps on a monthly

basis every 4 months for the entire panel length. If they

report receipt of food stamps, then they report the

monthly face value amounts.

In the CPS, we recorded that 10 percent of all people

were in a family in which someone reported food stamp

receipt sometime during the year 1991. In that same year,

12 percent of SIPP respondents reported receiving food

stamps. The estimated average amount of food stamps

received for each family is similar in the two surveys:

$1,951 in SIPP and $1,909 in CPS. This average is comparable to administrative program data from the Food and

Nutrition Service of the Department of Agriculture, where

the average annual benefit per household equaled $1,983

for 1991.

If we sum the value of total food stamp receipts across

all families in the surveys, we record a total of $12.4 billion in the CPS and $14.8 billion in the SIPP for 1991.

These figures, when compared to unpublished program

spending totals of $18.3 billion for the year 1991, suggest, perhaps not surprisingly, underreporting of food

stamp receipt in both surveys. The aggregate value in the

CPS for 1997 is $12.3 billion. Figures from the CPS for

1997 show a slightly lower percentage of people receiving

food stamps, 8 percent, with average amounts of those

receiving benefits equaling $2,087 per year.

School lunches, whether free, reduced price, or regular

price, are reported differently in the two surveys. In the

CPS respondents report the number of children who usually ate a school lunch in the previous calendar year, and

they indicate if that lunch was free or reduced price. Obviously, responses to this question depend on the respondents interpretation of the word usually. In the SIPP, the

question is asked, ‘‘How many school lunches were eaten

by the children per week?’’ This different question elicits

different responses on school lunch participation. In 1991,

we estimate that in the CPS only 32 percent of respondents reported that children in the family usually ate a

school lunch, as compared to 40 percent in the SIPP.

The income value for the school lunch program for each

participant family is calculated using this information and

data on the annual subsidy for free, reduced, and fullpriced meals. Information on the dollar amount of subsidies per meal is obtained from the Department of Agriculture (unpublished data). Again, however, the treatment

differs in each survey. In the CPS, since no additional information is available, we must assume that all reported children ate a school lunch of the reported price scheme all

year. In the SIPP, with subannual reports, we can more correctly apply the correct amounts of in-kind benefit to each

family. The lack of information in the CPS results in an

overestimation of amounts received. We calculate an average family lunch subsidy of $302 in the CPS versus only

$232 in the SIPP.

Since fewer households reported receiving school

lunches in the CPS, but we are imputing larger dollar

amounts, the aggregate subsidies across all families are

virtually identical in both surveys, $5.3 billion for calendar

year 1991. Total dollars spent by the school lunch program for that year were reported to be $4.1 billion, suggesting that our estimates are overvaluing these amounts.

For 1997, our estimates in the CPS show that 30.2 percent

of all persons are in families with some children eating a

hot school lunch and 45.3 percent of all persons in poor

families. An aggregate amount valued from this program

is $5.8 billion in that year (see Table C5).

Table C4. Comparison of Thresholds Using the BLS and NAS Geographic Adjustments: Various Areas

[Dollars]

Geographic area

1995 thresholds

BLS experimental interarea NAS housing index

Reference threshold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,561 15,561

Washington, DC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18,378 17,273

Greater Los Angeles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18,984 18,782

San Diego. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17,973 18,782

Mid Atlantic

Medium size metropolitan area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16,355 15,748

New England

Medium size metropolitan area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16,355 17,724

East South Central

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12,791 12,776

West South Central

Nonmetropolitan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12,791 13,242

Source: Johnson et al., 1997.

C–6 APPENDIX C

U.S. Census Bureau
HOUSING SUBSIDY VALUATION

Rent subsidies for renters receiving subsidies and for

those living in public housing, one of the noncash benefits

valued in the March supplement to the CPS, are estimated

as part of normal Census Bureau processing of the CPS

microdata file. These values are currently estimated with a

regression model that uses American Housing Survey

(AHS) data from 1985, updated using the CPI Residential

Rent Index. This section describes the current model, illustrates the results of applying this model to the original

data, and compares the effects of using current updating

procedures with the results of using more recent AHS data

from 1993 (future work will examine 1997 data).

Current Method

The current model provides estimates of monthly housing costs for renters as a function of four variables. In

essence, this is a very simple hedonic housing cost model.

Monthly housing costs, the dependent variable, include

both rent and utility costs. The four independent variables

are:

1. The number of full baths.

2. The presence or absence of all of three kitchen appliances: refrigerator, dishwasher, and garbage disposal.

3. The presence of any of four problems: hole(s) in

wall(s), hole(s) in floor, peeling paint, or rats.

Table C5. Percent of Persons With Positive Family Amounts and Mean Annual Amounts, CPS: 1997

All persons Poor persons

Percent of

people

Mean annual

family amounts

(dollars)

Percent of

people

Mean annual

family amounts

(dollars)

Food Stamps

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 1,012

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 2,087 42.4 2,389

School Lunches

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 315

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30.2 336 45.3 695

Housing Subsidies

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 513

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 2,149 19.2 2,675

Energy Assistance

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 24

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 210 11.5 207

Child Care - Model

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 239

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 2,944 10.0 2,383

Child Care - SIPP Medians

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 679 431

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.3 2,315 24.4 1,763

Child Care - AFDC

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415 287

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.7 3,260 10.1 2,828

Work-Related Expenses

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,138 404

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.4 1,333 59.0 685

Medical Out-of-Pocket Expenses

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,677 1,630

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94.0 2,847 79.8 2,042

Federal Income Taxes

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7,273 11

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76.1 9,554 3.4 334

Social Security Taxes

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,996 373

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.9 3,614 58.3 640

Earned Income Tax Credit

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314 997

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.0 1,656 47.2 2,112

Net Return on Home Equity

All persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,089 932

With positive amounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57.5 3,917 30.8 3,204

Source: U.S. Census Bureau tabulations of March 1998 Current Population Survey data.

APPENDIX C C–7

U.S. Census Bureau
4. An index of satisfaction with community services:

police, hospital, public transportation, and shopping.23

To get estimates of the effect of these independent variables on the rental cost, this model is estimated only for

unsubsidized renters in two-bedroom units, the most

prevalent type of rental unit. Unsubsidized renters are

renters who report that they do not live in public housing,

do not receive state or local assistance with housing costs

and do not report their income for purposes of setting

rent. Separate regressions were estimated for each of four

Census Bureau geographic regions: Northeast, Midwest,

South, and West. Subsidized renters are those who either

live in public housing or receive state or local assistance

with housing costs.24 The regression coefficients are then

applied to the housing characteristics of subsidized renters in the relevant region25 to obtain an estimate of what

the predicted monthly housing cost would have been in

the absence of the subsidy. The difference between the

mean predicted monthly housing cost and the mean outof-pocket housing costs of subsidized renters in the designated region is the mean subsidy for a two-bedroom unit

in that region.

This subsidy is then adjusted for family income and

number of bedrooms. Renters were divided into three

income categories. The categories and their adjustment

factors are:

Family income Adjustment factor

Less than $6,000 1.25

$6,000-9,999 1.15

$10,000 or more .48

The current model makes adjustments for the number

of bedrooms. Units are divided into three categories: units

with less than two bedrooms, units with two bedrooms,

and units with more than two bedrooms. The adjustment

factors for bedrooms are two region-specific ratios generated from the costs of nonsubsidized renters in the 1985

AHS data (see Table C6). The adjustment factor is the

region-specific ratio of median monthly costs for the

group divided by the median monthly cost for a twobedroom unit.

Updated Estimates

Having provided a description of the current measurement technique, we turn our attention to a comparison of

estimated subsidies using AHS data from 1985 and 1993.

Table C7 shows estimated 1993 subsidies for the entire

United States using the 1985 AHS updated with the price

index and 1993 AHS data for renters in two-bedroom units

with family incomes between $6,000 and $9,999.26

Results for other income groups and/or number of bedrooms can be computed using the adjustment factors

given above.

For the United States as a whole, subsidized households with incomes between $6,000 and $9,999 who lived

in two-bedroom units would have an estimated average

subsidy of $221 in 1993 if 1985 data are used and

updated with CPI-U residential rent indices. However, if

1993 AHS data are used, similarly situated families in

1993 had an estimated subsidy of $324. The CPI-U

updated subsidy is $103 less than the subsidy computed

with current data. In relative terms, using the CPI-U rent

indices to update the subsidy for 1993 underestimates the

average subsidy for specified households (viz., two bedrooms, income between $6,000- $9,999) by 35 percent.

Regional Differences

Estimated subsidies are updated for 1993 using CPI-U

ratios to provide comparisons between CPI-U indexupdated subsidies and subsidies modeled on 1993 data.

Differences between 1985 AHS index-updated and 1993

AHS subsidies range from $78 (South) to $135 (West).

23One service, public schools, is not included in the index. 24Renters who report their income for purposes of setting rent

are included among subsidized renters, but renters who do not

report their income for purposes of setting rent are included among

nonsubsidized renters. Respondents with missing data in each of

the four housing subsidy questions are not included in the original

model. 25Specifically, the monthly housing cost of each subsidized

renter was computed by applying an equation where the estimated

regression coefficients for nonsubsidized renters in two-bedroom

units were applied to the characteristics reported by the subsidized

renters in two-bedroom units.

26In order to simplify the discussion and make the presentation

clearer, in this appendix we show results only for this middle

income category (i.e., $6000-$9,999). Recall that the adjustment

factor for this group is 1.15. Results for other income categories

and number of bedrooms are consistent with these results.

Table C6. Monthly Housing Costs (Rent and Utilities)

by Number of Bedrooms and Region: 1985

[Dollars]

1 bedroom2 bedrooms3 bedrooms

All renters

Northeast. . . . . . . . . . . . . . . . . . . . . . . 356 422 454

Midwest . . . . . . . . . . . . . . . . . . . . . . . . 271 364 405

South . . . . . . . . . . . . . . . . . . . . . . . . . . 297 369 449

West . . . . . . . . . . . . . . . . . . . . . . . . . . . 368 468 599

Nonsubsidized renters

Northeast. . . . . . . . . . . . . . . . . . . . . . . 391 455 503

Midwest . . . . . . . . . . . . . . . . . . . . . . . . 300 380 428

South . . . . . . . . . . . . . . . . . . . . . . . . . . 321 388 485

West . . . . . . . . . . . . . . . . . . . . . . . . . . . 386 486 629

Source: U.S. Census Bureau tabulations of 1985 American Housing

Survey data.

C–8 APPENDIX C

U.S. Census Bureau
These results suggest that index-updated average subsidies underestimate average subsidies for specified households by 24 percent to 40 percent. These differences are

substantial.

Most of the difference is reflected in the higher rents of

nonsubsidized renters in 1993 than in 1985. For the South

and Midwest, the average predicted rent for two-bedroom

units was approximately $100 more in 1993 than it was in

1985. For the West and Northeast, it was approximately

$150 and $180, respectively. The secondary factor is a

lower average monthly cost in 1993 compared to 1985 for

subsidized renters in 3 of the 4 regions: Midwest, ($30),

South ($10), and West ($20). In the Northeast, average

Table C7. Estimated Housing Subsidies for the United States and Regions: Two-Bedroom Units and Income

$6,000 to $9,999

[Dollars]

United States Northeast Midwest South West

1985 AHS1

Sample size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 568 166 131 168 103

Subsidy amount (1993 dollars) . . . . . . . . . . . . . . . . . . . . . . 221 279 185 198 247

1993 AHS

Sample size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 646 192 153 200 101

Subsidy amount (dollars) . . . . . . . . . . . . . . . . . . . . . . . . . . . 324 368 290 276 382

1

Updated using CPI-U residential rent indices.

Source: U.S. Census Bureau tabulations of 1985 and 1993 American Housing Survey data.

Table C8. Mean Monthly Housing Subsidies for Families by Selected Characteristics: 1993

Sample size

Current subsidy1

(dollars)

Updated subsidy2

(dollars)

State level FMR3

(dollars)

Overall. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3,332 161 250 300

Family income less than 6,000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,133 231 354 484

Family income 6,000 to 9,999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,958 216 333 418

Family income 10,000 + . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3,179 92 144 179

Married couple. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547 122 191 195

Male householder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 587 137 216 230

Female householder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,198 176 273 342

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,023 196 286 376

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 820 129 224 252

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 917 156 232 252

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 572 164 270 338

Less than 2 bedrooms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,991 137 218 232

2 bedrooms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,194 159 244 283

More than 2 bedrooms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3,085 195 298 444

Less than 2 bedrooms

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 175 259 298

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 103 189 180

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 129 198 179

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362 141 231 296

2 bedrooms

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 628 197 277 352

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 535 136 229 252

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 644 150 222 235

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387 163 266 341

More than 2 bedrooms

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 911 223 330 558

Midwest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 609 167 276 408

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,011 190 275 368

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 200 332 487

1

Method currently used based on 1985 American Housing Survey data.

2

Method based on 1993 American Housing Survey data.

3

Fair market rents (FMR) based on Urban Institute research.

Source: U.S. Census Bureau tabulations of March 1994 Current Population Survey data.

APPENDIX C C–9

U.S. Census Bureau
rent of subsidized households increased $40,27 which offset the effect of higher average rents among nonsubsidized renters. The initial conclusion that we draw from

these data is that it is important to use current data rather

than updating older data with Residential Rent Indices

because the index-updating approach appears to underestimate subsidies.28

The housing subsidies that are on the March CPS

supplement file are based on subsidies estimated from the

1985 AHS, updated for inflation. As noted, the subsidies

vary by region, number of bedrooms, and income of the

family. We use the 1993 AHS and examine the effect of

using these more recent data on poverty rates and aggregate expenditure. For example, the mean monthly family

subsidy currently on the published file is $161. The minimum subsidy is $55, and the maximum subsidy is $336.

Using updated subsidies, the mean monthly family subsidy is $250, while the minimum subsidy is $99, and the

maximum subsidy is $556.

Alternatively, Fair Market Rents (FMRs) are available

from HUD at a very detailed geographic level. Using a

population-weighted average of the FMRs by state for

1993,29 we estimate housing subsidies as follows. We

assume the respondent’s rent is the appropriate state-level

average FMR. These FMRs vary by the number of bedrooms assigned to the respondent.30 Then, the respondent’s rent is assumed to be 30 percent of the households

gross income, excluding the earned income of household

members under age 18.31 The difference between the FMR

and the respondent’s rent is the subsidy estimate in this

scheme. When we use FMRs at the state level to calculate

subsidies, the mean monthly subsidy is $300. Table C8

shows mean monthly subsidies at the family level, by

selected characteristics, using the three methods.32

Aggregate Expenditure

Updating alternative data sources for estimating rent

subsidies has a dramatic effect on aggregate expenditures

as shown in Table C9. Using data from 1993, we estimate

that $16.6 billion were spent on housing subsidies in

1993, as opposed to the $10.7 billion estimated using the

price-adjusted data. Public housing subsidies account for

$10.9 billion (66 percent) of aggregate expenditures,

while rental assistance accounts for $5.7 billion (34 percent) of program spending.33 The FMR scheme shows

$19.9 billion in aggregate expenditures; $12.8 billion for

public assistance housing and $7.1 billion for rentassisted housing. The new estimates of aggregate expenditures compare more favorably with an independent estimate of $17.7 billion in rental assistance.34 Allocation

between public housing and rental assistance is difficult,

although the Urban Institute argues that the CPS underestimates rental assistance.35 Aggregate expenditures are broken down in Table C9 to show variation according to various schemes.

27This $40 approximates the difference between the 1993 and

1985 coefficients for the presence of specified problems. In 1993,

the coefficient is positive. Although it does not meet the criterion

for statistical significance, it does contribute to the subsidy estimates. It is not plausible that households in the Northeast pay an

extra $10 every month for the presence of rats, peeling paint or

holes in the walls or floors. Obviously the variable is correlated with

some omitted variable, and the model is misspecified. 28Note that the residences in the 1985 national sample remained

in the sample for the 1993 survey unless demolished or converted

to nonresidential use. However, there were additional residential

units in the 1993 AHS sample due to new construction. 29Unpublished Urban Institute memoranda. 30The CPS does not collect information on the number of bedrooms the family has directly. Rather, we estimate the number of

bedrooms using the age, sex, and marital status of family members

as specified by HUD occupancy rules. The Urban Institute, in the

process of incorporating housing subsidies into their TRIM model,

criticized our bedroom number assignment on several grounds.

This appendix does not address the shortcomings of the Census

Bureau’s bedroom estimation, but takes the number of bedrooms

given on the file. 31The income measure used in this comparison is a very rough

approximation of the appropriate income to use in determining

rent. HUD program rules allow various deductions to income, only

some of which could be modeled in the CPS. Thus, the results for

the state level FMR subsidy scheme are very preliminary.

32This analysis is performed at the family level because official

poverty is a family concept. There are valid arguments for estimating housing subsidies at the household level, but such estimates

would be difficult to allocate among families in multifamily households. Such an allocation would be necessary to look at the effect of

housing subsidies on poverty. 33Using the old subsidy data, $7.7 billion (65 percent) was

estimated as public housing expenditure, while $3.6 billion (35

percent) was estimated for rental assistance. 34The independent estimate from HUD includes outlays for

Section 8, Rent Supplements; Section 236, Rental Housing Development Grants; and Public Housing programs. Public Housing expenditures include an operating and a modernization budget, neither of

which is related to market rent. 35Various Urban Institute internal memoranda. Analysis of CPS

data for calendar years 1991 through 1993 show a generally stable

estimate of 1.7 - 1.9 percent of families (as defined by presence of

family records in the CPS) having rental assistance. The percentage

of families reporting public housing is more variable, from 2.7

percent in 1991 to 3.5 percent in 1993.

Table C9. Aggregate Housing Program Expenditures

[Billion dollars]

Overall Public Rental

Current subsidy1

. . . . . . . . . . . . . . . . . 10.7 7.0 3.6

Updated subsidy2

. . . . . . . . . . . . . . . . 16.6 10.9 5.7

State level FMR3 . . . . . . . . . . . . . . . . 19.9 12.8 7.1

Independent estimate4 . . . . . . . . . . . 17.7 NA NA

NA Not applicable.

1

Method currently used based on 1985 American Housing Survey

data. 2

Method based on 1993 American Housing Survey data.

3

Fair market rents (FMR) based on Urban Institute research.

4

Figure from HUD includes outlays for Section 8, Rent Supplements, Section 236, Rental Housing Development Grants, and Public

Housing Programs.

Source: U.S. Census Bureau tabulations of March 1994 Current

Population Survey data.

C–10 APPENDIX C

U.S. Census Bureau
ENERGY ASSISTANCE FOR HEATING

The CPS collects information on whether households

receive benefits from the government’s energy assistance

program and the amount received over the last 6 months.

Given that this information is only reported for the winter

months suggests that we are only collecting the heating

portion of this program. The CPS reports that 2.5 percent

of all people in 1997 were in a family where this benefit

was received. Of all people classified as poor under the

official measure, 11.5 percent of individuals reported

receiving this benefit.

The SIPP, however, collects information on receipt of

energy assistance in every month of the year. Asking the

questions year round captures individuals who received

help with cooling as well as heating bills. Respondents

report if help was received and the monthly amounts

received. From the SIPP, we estimate that 6 percent of all

people were in a family where someone reported receipt

of energy assistance; 28 percent of all people classified as

officially poor reported this benefit. These percentages are

considerably higher than those reported in the CPS, but,

as noted, also include individuals who reported assistance

with cooling bills. The average amount that families

received across people in families with this benefit in

1991 was $278 based on SIPP data.

For this application in the CPS, we use the amount of

energy assistance reported by respondents for heating

benefits only. When reported amounts are used in this way

in the CPS, we estimate that the average amount received

was $210 in 1997. Aggregate reported figures for heating

assistance in the CPS, summed across all families, equals

$0.5 billion in 1997, more than half of the $0.88 billion

dollars reported as the total heating benefits spent for the

program in 1995.36 Aggregate figures in the SIPP sum to

$1.5 billion in 1991, for both heating and cooling. This

number is actually higher than published program information of a total of $1.1 billion for heating benefits and

$27 million in cooling benefits in that year.

WORK-RELATED EXPENSES

Under the experimental measure of poverty two types

of work-related expenses are subtracted from a family’s

resources: 1) child care expenditures, and 2) other workrelated expenses. In this section we present three methods of valuing child care costs and one method of valuing

other work-related expenses.

Child Care Expenditures

The first method of valuing child care expenditures

involves using topical module data from the 1991 SIPP to

estimate child care expenses for CPS families (the March

CPS contains no questions on child care expenses). In the

SIPP, parents or guardians of children less than 15 years of

age who were in the labor force or attended school during

the reference period were asked about their child care

arrangements and costs during the last month. The panel

proposed that we deduct out-of-pocket child care costs

from the income of families where both parents, or the

only resident parent, reported being in the work force.

They also recommended that expenses be limited to the

earnings of the parent with the lower earnings, or to the

cap on the dependent care tax credit (which is $2,400 for

one child or $4,800 for two or more children – whichever

is lower). While the panel suggested that we impute child

care expenses to parents of children under 15 years of

age, we impute such expenses only to parents of children

under 12 years old because children age 12 and over are

less likely to require child care arrangements outside of

school.

We use a two-step procedure for estimating the

expenses for each of two separate groups of families: twoparent families where both parents worked, and families

with a single working parent. First, we estimate logistic

regressions for the two groups to estimate the probabilities of incurring child care expenses based on the

race/ethnicity of the head, the number of children of various ages, region, and family income. The two-parent equation also included a variable for the proportion of the

family’s earnings earned by the mother. Second, weekly

expenses of working parents who paid for child care are

regressed on the same set of explanatory variables using

an Ordinary Least Squares (OLS) technique. The panel estimated such a model using data from the 1990 SIPP panel.

We reestimated this same model using the 1991 and the

1992 SIPP panels (see Tables C10 and C11).

The logistic regression results from SIPP 1992 are used

to establish the probability that a family in the CPS had

incurred child care expenses. Based on this probability, the

family is randomly selected to either have or have not

incurred expenses. If the family is selected to have

incurred expenses, the OLS regressions are then used to

impute the amount of child care expenses of the CPS family, based on the family’s characteristics. As mentioned

above, imputed expenditures are limited to the earnings

of the parent with the lower earnings, or to the cap on the

dependent care tax credit — whichever is lower.

The second method for valuing child care expenses

involves estimating logistic regressions described above

to determine who incurs child care costs. Then we subtract dollar amounts from resources based on Aid to Families With Dependent Children (AFDC) and food stamps program child care deduction guidelines which take into

account the number and age of children in the family. In

particular, these programs have permitted parents to

deduct from countable income some out-of-pocket spending for child care necessary for the parent to work or participate in training. In 1989, the maximum amount of this

deduction was $175 per month for each minor child aged 36U.S. Department of Health and Human Services, 1997, p. 9.

APPENDIX C C–11

U.S. Census Bureau
2 or older, and $200 per month for children younger than

2. We base child care valuations on these figures because

these program deductions for child care are the clearest

normative statement of what the Federal government

regards as a ceiling on the cost of child care necessary for

employment. To take account of changing costs over time,

we update them for inflation using the CPI-U.

Specifically, using this method we deduct child care

expenses in the following way: 1) We impute who incurred

child care costs via the logistic regression described in

method 1; 2) For the first child under the age of 2 in a

family, we subtract the weekly AFDC deduction amount

($200/4.348) for each week worked by the parent who

worked the fewest weeks in the previous year. A smaller

amount is subtracted for each additional child under 2 in

the family because data from the 1993 SIPP indicates that

expenses for additional children are smaller than for the

first. The ratio we use is 0.486 because families paying for

care of one child averaged $74 in costs per week, and

those paying for more than one averaged $110. For each

child from 2 to 11 years old, from family resources we

subtract the weekly AFDC deduction amount ($175/4.348)

Table C10. Logit Coefficients Predicting Whether a Family Incurred Child Care Expenses: 1990-1992

Single-parent family Married-couple family

1990 1991 1992 1990 1991 1992

Intercept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –4.832 –4.082 –2.523 –10.012 –10.937 –8.672

Black family head . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.048 –0.403 –0.137 0.218 0.079 –0.289

Hispanic family head. . . . . . . . . . . . . . . . . . . . . . . . . . –0.081 –0.184 –0.207 0.460 0.152 –0.170

Number of children

0-5 years old . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.017 1.187 1.074 1.028 0.874 1.127

6-11 years old . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.055 0.214 0.116 –0.051 –0.244 –0.107

12-15 years old . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –1.062 –1.310 –1.018 –1.160 –1.076 –1.211

16-18 years old . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.993 –0.381 –0.128 –0.603 –0.867 –0.259

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.111 –0.256 0.040 0.307 0.757 0.630

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.083 0.097 0.078 0.332 0.826 0.853

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.236 0.210 0.648 0.309 0.495 0.693

Log of family income. . . . . . . . . . . . . . . . . . . . . . . . . . 0.431 0.320 0.150 0.766 0.848 0.640

Percent of family’s income earned by the mother – – – –1.771 –1.410 –1.167

Chi square .................................. 305.7 172.5 183.8 865.7 576.3 796.2

Number of observations . . . . . . . . . . . . . . . . . . . . . . . 1,223 675 902 2,978 2,106 2,533

– Represents zero.

Source: U.S. Census Bureau, Survey of Income and Program Participation, 1990-1992 panels.

Table C11. Ordinary Least Squares Regression Coefficients for Child Care Expenses: 1990-1992

Single-parent family Married-couple family

1990 1991 1992 1990 1991 1992

Intercept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –52.220 –105.122 –105.406 –221.396 –136.950 –332.173

Black family head . . . . . . . . . . . . . . . . . . . . . . . . . . . . –6.875 –4.427 7.960 0.121 –9.531 –4.250

Hispanic family head. . . . . . . . . . . . . . . . . . . . . . . . . . –6.223 –5.653 –3.343 –4.399 –4.602 –9.975

Number of children

0-5 years old . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.492 38.446 40.590 23.637 29.497 59.364

6-11 years old . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.308 16.885 18.602 1.469 7.060 23.809

12-15 years old . . . . . . . . . . . . . . . . . . . . . . . . . . . . –3.546 14.556 19.539 –2.223 9.139 –9.965

16-18 years old . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.523 11.443 –16.055 –5.931 1.670 18.428

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –11.676 0.123 –16.501 –6.713 –45.457 –7.558

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –11.187 0.455 1.526 –2.940 –40.525 3.140

West. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –8.728 11.315 1.707 6.662 –34.251 3.537

Log of family income. . . . . . . . . . . . . . . . . . . . . . . . . . 9.986 11.601 12.432 22.855 17.333 29.584

Percent of family’s income earned by the mother. – – – 29.864 43.572 54.660

R2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1403 0.3014 0.1408 0.2422 0.1469 0.1388

Number of observations . . . . . . . . . . . . . . . . . . . . . . . 455 237 306 1,071 702 826

Root MSE from unweighted regressions . . . . . . . . 32.588 35.166 68.033 34.579 65.998 93.247

– Represents zero.

Source: U.S. Census Bureau, Survey of Income and Program Participation, 1990-1992 panels.

C–12 APPENDIX C

U.S. Census Bureau
for such children for each week worked by the parent who

worked the fewest weeks in the previous year. Again, a

smaller amount is subtracted for each additional child

aged 2 through 11 equal to 0.486 of the dollar amount of

the initial child. In families with children in both the under

2 and 2 through 11 age ranges, we subtract ($200/4.348)

for the first child, and either ($200/4.348)*0.486 or

($175/4.348)*0.486 for each subsequent child— depending on the age of the child; 3) finally, total child care

expenses are adjusted for inflation. See Table C5 for mean

values of child care expenses for this method.

The third method for valuing child care expenses

involves simply subtracting a fixed amount from the earnings of families with no nonworking parents and with children under the age of 12, and to limit this deduction to

the earnings of the lower earner. We subtract fixed

amounts equal to 85 percent of median annual expenses

as reported in SIPP from these families. We use estimates

from the 1993 SIPP panel updated to 1997 using the CPI

for child care and nursery school. We calculate six separate medians depending on the number and age of children (see Table C12). This method imputes child care

costs for all families with working parents and children. It

follows the method used to impute other work-related

expenses to families, described below.

Other Work-Related Expenses

The panel proposed subtracting a flat amount for other

work-related expenses, to be updated annually for inflation. They recommended subtracting flat amounts rather

than reported expenses because of the trade-off that

people often make between housing and commuting

costs. For example, a family may choose a less expensive

home farther away from work (and thus incur greater

work-related expenses) rather than a more expensive

home closer to work. It makes little sense to subtract

other work-related expenses for the former family but not

the latter.

Following the panel’s recommendations, the flat amount

we deduct is 85 percent of the median amount spent on

other work-related expenses, as reported by SIPP respondents (no questions on other work-related expenses are

asked in the CPS). This amount is restricted to not exceed

the person’s earnings. The panel used data from the

1987 SIPP, the most recent data available.37 More specifically, the 1987 SIPP collected information on work-related

expenses from people who had at least one employer in

the reference period. Three types of expenses were identified:

1. Annual expenses— annual work-related expenses

such as union dues, licenses, permits, special tools, or

uniforms.

2. Mileage expenses— the number of miles usually

driven to and from work in a typical week, for people

who do some driving to work. An estimate of 22.5

cents per mile was used to convert mileage to

expenses.

3. Other expenses— other expenses incurred in getting

to and from work, such as bus fares or parking fees,

in a typical week.

Tabulations from the 1987 SIPP panel indicate median

weekly amounts of $17 (in 1992 dollars) for these

expenses; 85 percent of the median is $14.42. The combined deduction of child care and other work-related

expenses for working families with children under 12

years of age is capped to not exceed the earnings of the

parent with lower earnings when using imputed child care

expenses from methods 1 and 3, but not capped when

using expenses estimated with method 2.

In order to evaluate the validity of our imputed workrelated expenditures (for both child care and other workrelated expenses), we compare our CPS estimates with

expenses reported by SIPP families. We find that imputed

values from the CPS data tend to be higher than SIPP numbers. The discrepancy results mainly from the fact that we

assign these expenses to a higher percentage of people in

the CPS than in the SIPP. This, in turn, is a function of the

way we assign working status to survey individuals and

their families. Recall that child care expenses are calculated only for families with no nonworking parents (i.e.,

where both parents work in dual-headed family or where

the head of a single-headed family works). In the SIPP, if

both parents (or the parent in a single-headed family)

worked at least 1 week in the month when the child care

topical module was administered, then that family is

assigned to the no nonworking parent category. In contrast, using the CPS, we assign families no nonworking

parent status if both parents (or the parent of a singleheaded family) reported working at least 1 week in the

37The 1996 SIPP panel includes an annual module on workrelated expenses, thus allowing yearly updates in the future.

Table C12. Median Child Care Costs by Number and

Age of Children: 1991-1993

[Dollars]

1991

panel

1992

panel

1993

panel

One child under 12 years old

No children under 5 years old . . . 1,820 1,560 1,820

One child under 5 years old . . . . 2,600 3,120 3,120

Two or more children under 12

years old

No children under 5 years old . . . 1,560 2,080 2,548

One child under 5 years old . . . . 3,380 3,640 3,380

Two children under 5 years old. . 4,160 4,680 4,836

Three children under 5 years

old. . . . . . . . . . . . . . . . . . . . . . . . . . 4,940 7,150 5,200

Source: U.S. Census Bureau, Survey of Income and Program Participation, 1991-1993 panels.

APPENDIX C C–13

U.S. Census Bureau
previous year. Clearly, the probability that parents will

report having worked is greater if the accounting period is

a year (as in the CPS) rather than a month (as in the SIPP).

Thus, more people are assigned child care expenses in the

CPS than the SIPP.

TAXES—FEDERAL AND STATE INCOME TAXES AND

SOCIAL SECURITY PAYROLL TAXES

This section describes the methodology and procedures

which were developed to estimate taxes associated with

the income information on the March CPS microdata file.

In all, four types of taxes were simulated: 1) Federal individual income taxes, 2) state individual income taxes, 3)

property taxes on owner-occupied housing, and 4) social

security payroll taxes.

A major element in the simulation system are statistical

summaries of individual income tax returns compiled by

the Internal Revenue Service (IRS). These statistics are

made available in the IRS publication series, Statistics of

Income (SOI). Some unpublished statistical summaries

from the IRS were also used to develop these procedures.

A third element was the AHS microdata file. This element

was used to assign property taxes paid to the March CPS

sample households residing in owner-occupied housing.

Federal Income Taxes

Simulation of Federal income taxes requires up to four

separate operations. First is the formation and classification of tax filing units using household relationship, marital status, and dependency rules. Second, is the calculation of adjusted gross income for each of those units.

Third is the simulation of amount of Federal income taxes

paid. Finally, calculation of the earned income tax credit

(EIC) is made, when applicable.

A Federal tax filing ‘‘unit’’ is defined as any individual

(or married couple) with a certain amount received in selfemployment income, in wages or salary, interest, dividends, rents and royalties, estates and trusts, or pension

income in the previous year. The qualifying income levels

were chosen because they either corresponded to tax laws

or helped bring the estimated number of filing units on

the CPS in line with SOI data.

The next step in the formation of Federal tax filing

units is the assignment of dependency status. The algorithm for assigning dependency for each tax unit uses the

following rules.

• All filing primary family householders and spouses are

included as exemptions on their own tax returns.

• All children under age 15 who are members of the primary family are counted as dependents on the return of

the family householder.

• Children aged 15 and over (except related subfamily

members) with a total taxable income below a given

amount are assigned dependency to the tax return of

the primary family householder.

• Children aged 15 and over who are students are

assigned dependency to the primary family householder

regardless of income level.

• All other primary family members (except related subfamily members) within a given level of taxable income

are assigned as dependents on the tax return of the primary family householder.

• Related subfamilies having at least one Federal tax filing

unit are treated separately in the same manner as primary families.

• Members of a related subfamily containing no Federal

tax filing unit are assigned dependency to the tax return

of the primary family householder.

• All unrelated subfamilies are treated in the same manner as primary families.

• Primary and secondary unrelated individuals aged 15

and over are treated as exemptions only on their own

tax returns.

All simulated filing units are classified into 1 of 3 return

types. Married couples and persons whose marital status

is ‘‘married, spouse absent in Armed Forces’’ are assumed

to file joint returns. Unmarried family householders with

dependents are assumed to file head of household

returns. All other persons classified as Federal tax filing

units are assumed to file as single individuals.

Computation of Adjusted Gross Income and

Capital Gains

Adjusted gross income (AGI) for each simulated tax filing unit is calculated by summing the income amounts

from all taxable sources plus an imputed amount for capital gains. The sources of CPS income included in AGI are

wages and salaries, net farm and nonfarm selfemployment income, net rental and royalty income, dividends, interest, estates and trusts, income from private

and government pensions, unemployment compensation,

and alimony.

Capital gains are imputed to tax filing units based on

data obtained from a SOI public use file and reports summarizing information reported on Federal tax returns.

These data provide estimates of the probability that a filing unit with given characteristics reported capital gains,

and the mean amount of capital gains for that type of unit.

The characteristics in this probability matrix are: level of

AGI, type of return, and age of tax filer. We randomly

assign capital gains: a random number (between 0 and 1)

is generated for each filing unit; if that number is less than

or equal to the probability of filing units in that matrix cell

reporting capital gains, the mean amount of capital gains,

as computed above, is added to that unit’s AGI. This procedure does not control on other characteristics that

might affect the allocation of this source of income. As a

C–14 APPENDIX C

U.S. Census Bureau
result of the fact that capital losses can be greater than

capital gains for some groups, the net effect of capital

gains on income for any particular group can be negative.

To simulate tax laws, a portion of social security

income is included in AGI if the sum of AGI and half of the

total social security amount exceed a given level. In these

cases, the lesser of 1) one-half of the social security payments or 2) one-half of the difference between the modified AGI and the income limit is included in AGI.

Payments to individual retirement accounts (IRAs) are

also simulated for the tax model. The May CPS pension

supplement (updated to reflect changes in IRA regulations)

is used to estimate probabilities of tax-filing units contributing to IRAs, and the average amounts contributed. Average IRA contributions are updated annually based on SOI

data. These probabilities are then used to assign IRA contributions to individual tax-filing units on the CPS file. The

IRA contributions are deducted from the total income

received by the tax-filing units in order to compute AGI.

Computation of Taxable Income and Taxes Paid

Taxable income is computed by subtracting the estimated allowable deductions from AGI. The first step in

this process consists of predicting which filing units itemized deductions. Homeownership is determined to be the

most important variable available from the CPS for assigning itemization status to tax filers. First, a statistical match

is made of between the March CPS and most recent AHS in

order to assign a monthly mortgage amount and a property tax amount to each owner-occupied unit on the March

CPS. Probabilities of itemizing for homeowner, tax-filing

units are computed by size of monthly mortgage payment

from the 1979 Income Survey Development Program

(ISDP) test panel.38 Probabilities for renters are computed

by AGI level. These probabilities described are used to

randomly assign itemization status within monthly mortgage (or AGI) intervals using a similar technique as used in

the assignment of capital gains. The amount of itemized

deductions for tax filing units is computed using a matrix

showing the ratio of itemized deductions to AGI for all

units by AGI interval, type of tax return, and presence of a

home mortgage. The ratios of itemized deductions to AGI

are computed using an SOI public use file and SOI data.

Next, a standard deduction is estimated for each tax filing

unit by multiplying the number of exemptions by a given

dollar amount. Taxable income is then estimated by subtracting the itemized and standard deductions from AGI.

Tax liability is then computed using the appropriate tax

schedule for that simulated return type.

The dependent child care credit is simulated for the

Federal tax model and subtracted from the total tax liability. This credit allows tax filers to deduct a portion of child

care expenses while they work or look for work. Data

from the June 1982 CPS supplement are used to estimate

probabilities of tax filers paying for child care. These estimates are updated annually from SOI data.

The earned income credit (EIC) is simulated for the tax

model. These tax credits are used in the calculation of net

Federal tax liability and computation of after-tax household income for filing units with one or more dependent

children, less than a certain level in AGI, and earnings in a

given range. Since the earned income tax credit can be

larger than Federal tax liability, the net effect of Federal

income taxes on certain groups in this report can be negative.

The simulation procedures do not capture variations in

proportions of income paid in taxes within AGI intervals.

The proportion of income paid in taxes for households

with similar AGI amounts may differ relative to factors,

such as race, age of household members, number of

household members, and marital status. The extent to

which these variations exist has not been measured;

therefore, caution should be used when interpreting relatively small differences between the after-tax incomes of

various subgroups of the population.

The lack of variation in proportions of income paid in

taxes within AGI intervals is due in large part to the use of

aggregate-level IRS data in the simulation process, as

described previously in the appendix. The use of

aggregate-level IRS data was necessary because the

detailed information needed to simulate tax liability was

not available on an individual-level basis to the Census

Bureau. Published IRS estimates play a significant role in

the simulation of Federal income taxes. Proportions of tax

filers claiming capital gains, average capital gains, itemized deductions as a percentage of AGI, and average IRA

and child care credit amounts are the major IRS-based

components in the CPS Federal tax simulation procedure.

State Individual Income Taxes

For the purpose of this model, the definitions of tax filing units and AGI used for the estimation of Federal

income taxes are also used for the simulation of state

income taxes. The amounts of state individual income

taxes paid are computed by developing a model of each

state’s income tax regulations. Information on the state

tax systems was obtained from a publication entitled,

State Tax Handbook. State tax rates and brackets are

updated annually to reflect changes in state tax regulations. While every detail of each state’s income tax system

is not simulated, most of the important aspects are

accounted for.

Property Taxes on Owner-Occupied Housing

Simulated property taxes are only used in the computation of net return on home equity in this report. Property

taxes are already included in the out-of-pocket expenditures of owner-occupants so they are in the panel’s thresholds. In order to simulate property taxes for owneroccupied housing units, the March CPS simulation file was 38The ISDP was the precursor of SIPP.

APPENDIX C C–15

U.S. Census Bureau
statistically matched to a file from the AHS. Since the AHS

file contained responses to questions on annual property

tax expenses, the statistical match allowed the transfer of

property tax amounts to CPS records when a CPS and AHS

household were found to have similar matching criteria.

The characteristics used to match the two files were: age

of householder, state, metropolitan and central-city status

of the household, household income, household size,

number of living quarters, and the race, sex, and educational attainment of the householder. If there was no AHS

household with the exact combination of characteristics as

a particular CPS household, a match was then attempted

at a new level that did not have quite as much detail. This

was repeated until a match was found for every CPS

household.

Households on the AHS file that did not answer the

question dealing with property tax expenses were ineligible for the match. Since monthly mortgage expenses,

which were used to simulate itemization status for Federal

taxpayers, were also assigned to CPS households using

this match, households that did not answer the AHS questions on that subject were similarly excluded from the

match. Thus, any one AHS household could have been

used more than once to impute data to CPS households.

Property taxes paid on secondary residences, such as

vacation homes, could not be simulated. Also, the proportion of rent that pays the property taxes on renteroccupied housing units was not estimated. The estimation

procedures for property taxes paid by homeowners produce estimates that do not correspond precisely with

those available from the AHS. These differences are mainly

the result of differing universes and use of the statistical

matching procedure. Note that property taxes are considered a consumption item and are not deducted from

income. They do play a role in determining the income

value of owner-occupied homes, however.

Payroll Taxes

The social security payroll tax (FICA) was simulated

using occupation of longest job and earnings data

reported on the CPS. Social security payroll taxes were calculated directly from the reported CPS earnings using the

social security payroll tax formula for 1997. Not all workers were assigned coverage under social security and,

therefore, a small number were not subject to social security taxes. Since the late 1980s, we have assigned some

Federal workers as FICA-covered and some as covered

under the older noncovered Federal retirement system

based on the age of the Federal worker. Unpublished

aggregate statistics supplied by the Social Security Administration were used to make assignments for these workers.

MEDICAL CARE

In this report, we follow the panel’s approach concerning the treatment of medical care in the poverty measure.

For this approach, we analyze the impact of deducting

household obligations for the cost of medical care and

health insurance out-of-pocket (MOOP) expenses from

resources as the panel did. In this approach the treatment

of MOOP is consistent on both sides of the poverty equation: the threshold and the resource sides. In general, this

approach compares income less MOOP expenses to a

threshold reflecting the costs of the basic bundle (FCSU),

$15,998 for the reference family in 1997 (see the FCSU

threshold in Table C1). One additional approach, the addition of insurance values as resources where insurance coverage was subsidized by the government (i.e., medicare

and medicaid) is also described below.

Medical Out-of-Pocket Expenses

Deducted From Resources

In accordance with the panel’s recommendations, we

analyze the impact of medical expenditures in the determination of economic poverty by comparing resources

less MOOP expenses to a threshold that does not include

needs for medical care or health insurance. Also, like the

NAS panel, we impute MOOP expenses in the CPS. A

description of the imputation process follows.

To compensate for the lack of information on medical

expenditures in the CPS, we use the same basic approach

as the panel. However, we use a revised imputation model

developed subsequent to the release of the panel’s

report.39 For that model, the expenditure data (covering all

components of MOOP expenses except individuals’ premium payments for part B medicare) were obtained from

the 1987 National Medical Expenditure Survey (NMES),

aged to 1991. The imputation procedure assigned a predicted expenditure to each family based on the characteristics of that family and adjusted the imputed amount to

ensure that, in the aggregate, total imputed out-of-pocket

expenditures agree with aggregates expenditures estimated from an independent source.40

The imputation model consists of three components.

The first component of the model is the determination of

whether or not a family incurred any MOOP expenses in

the course of the year. A set of probabilities for different

families was determined using NMES data that take

account of insurance status, family size and income, race,

and age of elderly householder. Whether a particular family would incur MOOP expenses is determined by drawing

a random number from a uniform distribution. If that random number exceeds the probability of not incurring

MOOP, the family is imputed positive MOOP expenses (see

Table C13).

The second component of the model is to assign actual

values of MOOP expenses to those who incur such

39Betson, 1997a. The new method corrects for an error discovered subsequent to the report’s publication. 40Note that we do not adjust any other income source to meet a

benchmark amount.

C–16 APPENDIX C

U.S. Census Bureau
expenses. The panel assumed that the cumulative distribution of medical expenses could be described by a logistic function. They estimated the parameters based on the

following equation:

Ln(c/(1-c)) = a + bX (h) + g ln(moop) + d X (h) * ln(moop) + e

where ln(moop) = natural log of MOOP spending and c is

the percentile in the cumulative distribution of MOOP in

the NMES data. The description of variables and the estimated regression results are shown in Tables C14 to Table

C16. This information is then used to assign a value of

MOOP to each family. The value of the expense is determined from the distribution of expenditures in NMES using

a stochastic approach based on the following formula:

M = exp{(ln(rn2/(1-rn2)) - a- b X(h))/g}

Where:

M = MOOP

rn2 = random number drawn from a uniform distribution

X (h) = a vector of family characteristics (age, race,

Table C13. Probabilities of NOT Incurring Medical Out-of-Pocket Expenses by Characteristics of Householder

Insurance

Characteristics

Nonelderly

Family size Income Race probabilities

Private health insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 person Not low income White or other 0.065

Black 0.041

Low income White or other 0.075

Black 0.143

2 or 3 persons Not low income White or other 0.061

Black 0.083

Low income White or other 0.012

Black 0.012

4 persons or more Not low income White or other 0.031

Black 0.024

Low income White or other 0.003

Black 0.006

Public health insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 person Not low income White or other 0.397

Black 0.606

Low income White or other 0.219

Black 0.628

2 or 3 persons Not low income White or other 0.371

Black 0.408

Low income White or other 0.212

Black 0.279

4 persons or more Not low income White or other 0.237

Black 0.507

Low income White or other 0.256

Black 0.345

No insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 person Not low income White or other 0.378

Black 0.482

Low income White or other 0.248

Black 0.420

2 or 3 persons Not low income White or other 0.151

Black 0.194

Low income White or other 0.103

Black 0.128

4 persons or more Not low income White or other 0.043

Black 0.126

Low income White or other 0.036

Black 0.213

Age Family size Income

Elderly

probabilities

under 75 1 person Not low income 0.167

Low income 0.023

2 persons or more Not low income 0.101

Low income 0.016

75 or over 1 person Not low income 0.087

Low income 0.022

2 persons or more Not low income 0.054

Low income 0.017

Source: Betson, 1997a.

APPENDIX C C–17

U.S. Census Bureau
income, and insurance coverage) that varies

by elderly or nonelderly status

a, b, g = parameters estimated from the equation as

noted above.

The most straightforward component is the assignment

of medicare part B premiums to families with elderly members in the CPS. This is necessary because the expenditure

data from NMES that formed the bases of the imputation

model did not capture these out-of-pocket costs. For each

elderly person in the family who was not covered under

medicaid, we assign a fixed amount of money to the family equal to the legislated part B premium amounts for

each year.41 People with medicaid coverage are assumed

not to incur the costs of the part B premiums because that

program (by and large) covers that obligation.

The final value of MOOP expenses is computed as the

sum of the medicare part B premiums and the imputed

value M, adjusted for price changes and calibrated to the

independent control totals. The aggregate totals used

were developed from a variety of sources. Overall they

pertain to the aggregate total for 1992 used by the panel,

adjusted to other years according to changes in the CPI-U

41Social Security Administration, 1997, Table 2C1, p. 107.

Table C14. Description of Independent Variables Used in Medical Out-of-Pocket Expenditure Equations

Lnmoop Log of medical out-of-pocket expenses

Public Equal to 1 if insured by medicare or medicaid only, 0 otherwise

Unins Equal to 1 if uninsured, 0 otherwise

Fs23 Equal to 1 if family size is 2 or 3

Fs4m Equal to 1 if family size is 4 or more

Fs2m Equal to 1 if family size is 2 or more

Age75 Equal to 1 if reference person is 75 years or older

Nonpoor Equal to 1 if the ratio of the family money income to poverty line exceeds 1.5

Black Equal to 1 if race of head is Black

Publmp Lnmoop * Public

Unlmp Lnmoop * Unins

Nplnp Lnmoop * Nonpoor

F23lmp Lnmoop * Fs23

F4mlmp Lnmoop * Fs4m

F2mlmp Lnmoop * Fs2m

A75lmp Lnmoop * Age75

Source: Betson, 1997a.

Table C15. Regression Coefficients for Nonelderly Population

Coefficient t statistic

Constant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.9028 37.595

Lnmoop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2549 89.848

Publmp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.4039 –28.007

Unlmp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.1304 –9.467

Nplnp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.0644 5.441

F23lmp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.0921 8.338

F4mlmp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1491 11.912

Blklmp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.0692 –6.290

Public. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2560 45.142

Unins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.0070 44.449

Fs23. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.8702 –45.427

Fs4m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –1.1897 –58.434

Nonpoor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.1913 –9.533

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.3866 20.215

R2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.9227

Source: Betson, 1997a.

C–18 APPENDIX C

U.S. Census Bureau
for medical care.42 These totals were disaggregated into

three components (out-of-pocket medical costs toward

medicare part B premiums, other MOOP expenses incurred

by families with an elderly reference person, and MOOP

expenses incurred by families not containing an elderly

reference person). In our calculation, the totals for elderly

and nonelderly were calibrated separately. Generally, the

model tends to underestimate the out-of-pocket spending

of the nonelderly and overestimate the spending of the

elderly compared with the aggregates we used. For

example, to match the aggregate values for 1997, we multiplied nonelderly expenditures by a factor of 1.179 and

elderly expenditures by a factor of .8257. Furthermore,

this is the only component of the poverty measure that is

calibrated to an administrative control total, and thus

adjusted for errors in reporting and sampling.

With this method, we estimate that 94 percent of all

people in the CPS were in a family with at least some

MOOP expenses. The average assigned amount spent in

1997 in the CPS was $2,847. Further, 80 percent of poor

people were allocated these expenses, which averaged

$2,042 (see Table C5). Since all amounts were calibrated

to aggregate totals (see below) the aggregate-spending

total was calculated to be $271 billion for 1997 (see Table

C17). It is important to note that these amounts are large

and have a significant effect on poverty rates.

Including the Value of Health Insurance in the

Measure of Resources

The procedure published annually since the late 1980s

by the Census Bureau43 applies a fungible cash value to

medicare and medicaid benefits. The March supplement

collects information on the number of persons who were

covered by medicare and/or medicaid at any time during

the previous calendar year. For the purpose of preparing

these estimates, it is assumed that anyone who was covered at any time during the year was covered for the

entire year. The income value of benefits from these programs is defined as the fungible value of the benefits; that

is, these benefits are counted as income to the extent that

they free up resources that could have been spent on

medical care.

To make this calculation, a separate amount representing basic food and housing requirements is determined

based on the cost of the Department of Agriculture’s

Thrifty Food Plan and a cost of housing based on the

HUDs FMRs. The implicit standard used here is different

from those used either in the official thresholds or the

panel’s proposed thresholds. The value of benefits from

these programs is based on mean program outlays by

state and risk class, such as the elderly and blind or disabled individuals.

42Betson, 1995b. 43U.S. Census Bureau, 1993 and 1998.

Table C16. Regression Coefficients for Elderly Population

Coefficient t statistic

Constant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5079 25.777

Lnmoop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2170 94.459

Fs2m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.4655 30.387

Age75 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.2682 –3.837

Nonpoor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.6364 –12.750

Nplnp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.4410 –14.151

F2mlmp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.1610 –23.768

A75lmp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.0515 –31.019

R2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.9458

Source: Betson, 1997a.

Table C17. Aggregate Control Total for Medical Out-of-Pocket Expenses Deducted From Resources

[Billion dollars]

Year Aggregate Medicare part B Elderly MOOP Nonelderly MOOP

1990..................................................... 187.89 8.56 42.13 137.19

1991..................................................... 204.28 9.31 45.81 149.16

1992..................................................... 219.40 10.00 49.20 160.20

1993..................................................... 232.44 10.59 52.12 169.72

1994..................................................... 243.52 11.10 54.61 177.81

1995..................................................... 254.49 11.60 57.07 185.82

1996..................................................... 263.37 12.00 59.06 192.31

1997..................................................... 270.76 12.34 60.72 197.70

Source: U.S. Census Bureau calculations and Betson, 1995b.

APPENDIX C C–19

U.S. Census Bureau
The fungible value of public insurance benefits is then

estimated by comparing a family resource measure that

includes in-kind benefits, such as food stamps and housing subsidies, with the cost of basic food and housing

requirements. If family resources do not cover these basic

needs, then no addition is made. Otherwise, the insurance

benefit is valued as the amount by which the family’s

resources exceed the cost of basic food and housing

requirements up to the full amount of the benefit.

In order to include these values in a poverty measure,

we add the fungible value of public health insurance to

income and compare that value of resources to the official

poverty thresholds. These estimates are shown in Table

A9.

OWNER-OCCUPIED HOUSING

The panel’s treatment of shelter (not including utilities)

is the same for owners and renters. For the thresholds,

only out-of-pocket expenditures are included.44 Thus,

although the treatment of owners and renters is the same

in terms of using out-of-pocket expenditures for the

thresholds, homeowners with low or no mortgages are not

being treated in a comparable way as homeowners with

mortgages or as renters in terms of their shelter consumption.45 While homeowners with low or no mortgages have

relatively low out-of-pocket shelter expenses, their consumption is expected to be more like that of other homeowners and renters. For such low mortgage households,

their needs are being met through the implicit cost of the

equity investment in their owned housing units. If reference families were primarily composed of homeowners

with low or no mortgages, the out-of-pocket shelter

expenditures used in the production of the thresholds

would be relatively low compared to their expected consumption. This would result in an underestimate of their

shelter consumption costs because it ignores the implicit

cost of homeowners equity from ownership of the housing

unit.

If the reference family were primarily composed of

homeowners with newer mortgages, their out-of-pocket

shelter expenditures would be relatively high as compared

to the expenditures of other owners and renters. If this

were the case, an overestimate of the cost of shelter consumption could result. Using the out-of-pocket expenditures for owners with mortgages could also result in an

overestimate of shelter costs because owners with mortgages are allowed to take a tax deduction for mortgage

interest paid, thus reducing their true costs for shelter.

Finally, the implicit benefit of house price appreciation,

which is one of the primary advantages of homeownership, is ignored.

For resources, the value of the flow of services that

owners obtain from their homes is not accounted for in

the panel’s estimates. Thus, owners with low or no mortgages have more of their incomes available for the consumption of other items. As noted by the panel,46 excluding some value for this implicit income is to underestimate

these homeowner’s resources relative to their poverty

thresholds. Such an approach has interesting implications

for elderly households who own their homes and do not

have mortgages or have very low mortgage interest payments. This treatment of the elderly means that households living in expensive houses with substantial wealth,

and hence implicit income in the form of owner’s equity,

are just as likely to be classified as poor as those in small

inexpensive units (ceteris paribus). If we assume that elderly households can transform their home equity into a

flow of guaranteed income using a reverse annuity mortgage, this equity could be used to increase their

resources.

Following this approach, we assume that this implicit

income could be used to meet one’s basic needs. As noted

by the panel,47 some analysts48 think that it may not be

appropriate to add the full net imputed rent to resources,

especially for the elderly. The panel stated that a downward adjustment to the value for a larger-than-needed

home would be appropriate, but there appears to be little

agreement concerning what the adjustment would be. One

approach suggested is to cap the amount of the implicit

income at the level of the shelter component in the poverty thresholds.49

In this section, we describe two additional approaches

for estimating shelter costs for the thresholds, and one

approach for estimating a value for the flow of services

from owner-occupied housing. For the thresholds, we

compare out-of-pocket shelter expenditures with estimated shelter costs based on a hedonic regression equation and shelter costs based on reported rental equivalence by homeowners. The flow of services for resources

is estimated as the net return to home equity. Each of

these methods was briefly reviewed and supported in

theory by the panel in their report. However, the panel

produced no estimates based on these approaches. Participants at a 1998 Brookings workshop on Housing and Geographic Issues in the Measurement of Poverty supported

our exploration of these approaches for poverty measurement.

44For renters, shelter expenditures include those for rent paid,

repairs and maintenance, and tenants insurance. For homeowners,

shelter expenditures include those for mortgage interest, property

taxes, maintenance, repairs, and homeowners insurance; mortgage

principal payments are not included. 45Citro and Michael, 1995, p. 148.

46Citro and Michael, 1995, p. 245. 47Citro and Michael, 1995, p. 246. 48For example, Ruggles, 1990. 49Citro and Michael, 1995, p.246.

C–20 APPENDIX C

U.S. Census Bureau
Valuing Shelter for Homeowners in the Thresholds

As noted earlier, for owners, whether the family has a

mortgage or not greatly affects out-of-pocket shelter

expenditures, as does the mix of homeowners and renters

among the reference families. Using 1993-1997 CEX quarterly Interview data, we find that approximately 75 percent of the reference families live in owner-occupied housing.50 About 64 percent of the reference families live in

owner-occupied housing and have a mortgage. Mortgage

interest payments account for about 69 percent of the outof-pocket expenditures of owners with mortgages. Other

expenditures include property taxes (20 percent), maintenance, repairs, and related goods and services, such as

homeowners insurance (11 percent). Since mortgage interest is a substantial portion of the out-of-pocket expenditures paid by many owners, thresholds will tend to rise

and fall with the movement of mortgage interest rates. In

addition, larger mortgage interest payments are associated with families living in newer, larger housing units

located in high amenity neighborhoods. This means that

thresholds will tend to be quite high when reference families have higher interest payments and live in such neighborhoods.

The panel acknowledged some of the problems associated with using actual out-of-pocket shelter expenditures

as reported in the CEX; however, they used these expenditures for processing convenience. They stated that a preferable definition would include actual outlays for mortgage payments, taxes, insurance, and maintenance and

repairs, together with an imputed amount for the estimated rental value of the home net of such outlays. Such a

definition would treat homeowners with low or no mortgage payments in a comparable manner with other homeowners and renters.51 By following such an approach, one

could expect that the implicit cost of housing consumption of owners with low or no mortgages would more

appropriately be accounted for.

In this section, we describe two methods that we used

to value the shelter consumption of reference families:

rental equivalence and estimated shelter costs (not including utilities) based on a hedonic regression model. Both

methods have been previously presented52 and used by a

BLS/Census Bureau research team,53 but refinements to

the hedonic method have been introduced for this report.

The rental equivalence of owner-occupied housing is

based on the responses of owners to a specific question,

‘‘If someone were to rent your home today, how much do

you think it would rent for monthly, unfurnished and without utilities?’’ For homeowners, this value replaces their

reported out-of-pocket expenditures. In an earlier study,54

rental equivalence values reported in the 1995 CEX and

the 1995 Consumer Price Index Housing Survey were compared and found to result in similar average values for like

families. We are unaware of other Federally sponsored surveys in which the rental equivalence question has been

asked. Whether owner-occupants are accurate evaluators

of the rental values of their units has not been examined

based on our search of the literature.55

For hedonic regression-pricing models, observed

expenditures (e.g., rental costs) for shelter are regressed

on explanatory variables representing the individual characteristics of the housing, and the regression coefficients

are estimates relating to the implicit marginal prices of

these characteristics. For our study, the resulting coefficients from the renter regression are used in combination

with the characteristics of the owner units to estimate

owner costs for shelter. Thus, this approach results in an

estimate of owner’s shelter costs in an average community

using the characteristics and rent paid by renters with like

housing characteristics. Defining shelter costs this way for

owner-occupants contrasts with the panel’s recommendation that defined owner shelter costs as the sum of the

actual outlays for mortgage payments, taxes, insurance,

and maintenance and repairs, plus an imputed amount for

the estimated rental value of the home net of such outlays. We decided to model owner shelter costs so that

owner and renter shelter costs would be comparable,

rather than to allow owners with high mortgage interest

payments and other large expenditures to be different

from other homeowners and renters living in similar types

of dwellings and in the same areas. In addition, basing

owner shelter costs on the actual outlays when the estimated shelter costs are lower could mean that some owners could quite easily be considered poorer than renters

only because these families own their homes and their

out-of-pocket expenditures are higher. We thought it was

counterintuitive that owners would be more likely to be

poor than would renters, given the same amount of housing and other expenses. Furthermore, our approach makes

thresholds less sensitive to fluctuations in interest rates

and decisions to refinance.

The shelter expenditures paid by renters are the basis

for the dependent variable in the model. Shelter expenditures for renters include rent paid and expenditures for

maintenance, repairs, and tenants insurance. For this

model, owners’ estimated shelter costs are based on a

50 semilog regression of renters’ shelter expenditures on The homeownership rate for all consumer units in the CEX is

63.4 percent. Thus, the reference family is more likely to own its

home than families on average. Data from the quarterly Housing

Vacancy Survey indicates that the National homeownership rate is

64.8 percent for 1993-1997, comparable to the rate produced using

the CEX. 51Citro and Michael, 1995, p. 148. 52Johnson et al., 1997. 53Short et al., May 1998.

54Johnson et al., 1997. 55On a related topic, Follain and Malpezzi, 1981, examined the

accuracy of owner-occupants concerning the market value of their

homes using hedonic methods and the Annual Housing Survey.

They found that the average over-occupant downwardly biases its

estimate of the market value by about 2 percent.

APPENDIX C C–21

U.S. Census Bureau
selected housing and location characteristic variables. Malpezzi and colleagues56 and others57 have found that a

semilog regression fits the hedonic price-characteristics

relationship for housing fairly well. To be included in the

regression sample, renters are identified as consumer

units in the CEX database if they report positive out-ofpocket shelter expenditures, do not receive rent as pay,

and do not live in government subsidized or public housing. Owners are identified as those owning their dwelling

and having a positive value for out-of-pocket shelter

expenditures (as defined for the basic threshold definition), or a positive expenditure for rental equivalence. The

requirement of some positive owner expenditure is added

to ensure that the owner sample is actually composed of

owners.

The housing unit characteristics selected for the sample

are based primarily on those used previously in the literature.58 The general hedonic regression specification

includes variables representing: structural characteristics

of the dwelling, location characteristics, contract characteristics, a neighborhood characteristic, and an interview

characteristic. Among the structural characteristics are age

of the dwelling, type of dwelling,59 number of bedrooms,

number of complete baths, number of rooms other than

bedrooms and baths, type of heating,60 and other amenities.61 Squared and interaction terms for some of these

variables are also included in the model. Location is represented by geographic sampling areas or primary sampling

units. The contract characteristics that we include are

whether utilities were included in the rent, whether the

consumer units dwelling has a swimming pool, tennis

court, barn or stable, guesthouse, greenhouse, or offstreet parking. According to Messe and Wallace,62 the age

of the dwelling typically proxies for neighborhood effects

(established community, older trees, etc.) as well.63 64 In

most other hedonic models of housing, dwelling quality

variables are also included;65 such data are not currently

collected in the CEX.

A variance components model was used to estimate the

hedonic equation for eight regions of the country and for

two time periods. This model was used because we

wanted to account for the correlation of reports when a

consumer unit was in the data file more than once and we

wished to use all of the interviews. Because this last

requirement meant that we had an unbalanced design, we

needed a procedure that would account for this.66 In the

CEX, consumer units can be in the data file from one to

four times, depending upon when and how often they participate in the Interview Survey. Since ultimately we

wanted to produce the thresholds for 1995, 1996, and

1997, although only the 1997 threshold is used in the

main part of this report, we needed data from 1993

through 1997. To conduct the regression analysis we used

all the reports, regardless of family type, in order to maximize our sample size.

The rent regression sample included data from 31,122

interviews. This sample was divided into two samples representing: (1) 1993 Quarter 1 through 1996 Quarter 1,

and (2) 1996 Quarter 2 through 1997 Quarter 4. These

two samples were used because in 1996 Quarter 2 a new

sample design for the CEX was fully implemented.67 The

eight regions were based on dividing the four Census

Bureau regions of Midwest, Northeast, South, and West

into large and other primary unit subsamples. Our regression results reveal that accounting for the fact that consumer units are in the data file more than once is significant (Pr>Z is 0.0001 for all models). Conducting the

analysis for the regional subgroups was also important

based on the results that some of the significant regression coefficients are positive for some regional subgroups

and negative for others.68

To evaluate how well the model estimated the actual

shelter expenditures of renters, we used the predicted values from the regression and adjusted this amount to

account for the functional form of the model.69 The correlation between the regression renters’ estimated and their

actual expenditures is 0.93. The correlation coefficient for

reference family regression renters is 0.94.

Means and medians of quarterly shelter expenditures,

out-of-pocket, rental equivalence, and estimated shelter

costs based on regression analysis have been produced

for consumer units with two adults and two children for

both owners and renters.70 These were produced so that

we could better understand how the mix of renters and

owners with and without mortgages in our sample could

influence shelter costs and ultimately the experimental

56Malpezzi et al., 1998. 57See Gillingham, 1975; Moulton, 1995; Ozanne and Malpezzi,

1985; and Thibodeau, 1995. 58See, for example, Follain and Malpezzi, 1981; Malpezzi et al.,

1998; Meese and Wallace, 1997; Ozanne and Malpezzi, 1985;

Moulton, 1995; and Thibodeau, 1995. 59Dummy variables for type of dwelling include: detached, row

house, end unit townhouse, duplex, numplex, garden apartment,

high rise apartment, flat, or mobile home. 60Dummy variables for type of heating include: gas, electric, oil,

or other. 61Dummy variables for amenities include: has swimming pool,

tennis court, barn or stable, guesthouse, porch, terrace, patio,

apartment, off-street parking, window air-conditioning, or central

air-conditioning. 62Meese and Wallace, 1997, p. 54. 63Malpezzi et al., 1998, used race as a proxy for measuring

neighborhood effects. 64A complete list of variables for each time and subregion

sample is available upon request. 65See Thibodeau, 1995, for variables that have been used to

proxy housing quality using the American Housing Survey data.

66The SAS procedure Proc Mixed was the most appropriate

procedure for this application. 67The new design was introduced in 1996 Quarter 1, but no data

were collected under the new design in January of that year. 68Results from the regression models are available upon request. 69See Greene, 1990, p. 168 and Thibodeau, 1995, p. 442 for a

description of the adjustment. Thanks are extended to Ralph Bradley and Anthony Yezer for discussions concerning this issue. 70Tables with the means and medians are available upon request.

C–22 APPENDIX C

U.S. Census Bureau
poverty thresholds. For both means and medians, shelter

out-of-pocket expenditures are lower for renters than are

those for all owners combined (including both owneroccupants with and without mortgages). Mean renter quarterly expenditures from 1993 through 1997 for the reference family are $1,473. The lowest mean out-of-pocket

shelter expenditures are for owners without mortgages—

$623. This is in sharp contrast to the mean for owners

with mortgages—$2,203. Renters’ mean quarterly out-ofpocket expenditures are about 74 percent of mean owner

expenditures (medians are about 85 percent). Owners

without mortgages have out-of-pocket shelter expenditures that are 28 percent of that of owners with mortgages.

The next highest values for owners are those based on

the regression analysis estimates and the highest are

those based on rental equivalence responses. Again, differences between owners with and without mortgages

emerge. The reported rental equivalence of owners without mortgages is 72 percent of the mean value reported

by owners with mortgages. Model-based estimates for

shelter costs for owners without mortgages are 76 percent

of expenditures for renters. For all owners, the out-ofpocket shelter expenditures are about 78 percent of the

average rental equivalence while the estimated shelter

costs are lower at 66 percent of rental equivalence. The

closer relationship between out-of-pocket expenditures

and reported rental equivalence is not surprising if, as

might be expected, respondents answer the rental equivalence question with respect to their neighborhoods and

current shelter costs. Houses with higher mortgages are

likely to be in neighborhoods with more amenities.

Poverty thresholds using each of the three methods to

determine shelter costs are presented in Table C18. As

expected, given that the estimated shelter costs for

owner-occupants with mortgages are lower than are their

out-of-pocket expenditures and the fact that the a sizable

majority of the reference families have mortgages, the

thresholds with the estimated owner shelter costs are

lower. For 1997, the threshold based on estimated shelter

costs for the reference family is $15,809. The next highest

thresholds are those based on out-of-pocket expenditures;

for 1997 the threshold is $15,998. The highest thresholds

are those based on the rental equivalence reported by

owners; for 1997 the threshold is $18,162. The same pattern holds in 1995 and 1996.

Net Return to Home Equity Added to Resources

Homeowners with a positive amount of home equity

receive a benefit in the form of housing services that is

not generally counted as income. In this report, we apply

a rate of return to the estimated amount of home equity;

that is, we treat equity in owned home as an asset from

which the owner receives implicit interest income.

The March CPS supplement collects information on

whether the housing unit is owned or rented, but does not

collect information on home equity. The rate of return

approach is implemented by using the statistical match to

the AHS based on age of the householder, state, SMSA,

central city status, income, household size, number of living quarters, race-sex-education of the householder, and

presence of own children. Data taken from the AHS

include: monthly mortgage amount, annual property

taxes, market value of residence, market value of land if

the dwelling was a mobile home and they own the land

upon which the home sits, balance remaining on mortgage, and an indicator of whether this unit is part of a

condominium or cooperative. The return to home equity

value of the house was determined by multiplying the

market value of the home (plus the market value of the

land if the dwelling was a mobile home) by a rate of

return.The estimate of the amount of income derived from

home equity is dependent on the rate of return that is chosen. The rate chosen is the average rate of return on highgrade municipal bonds from the Standard and Poors

series. Because homeowners pay property taxes, the final

estimate of the amount of income derived from home

equity is made equal to the imputed return less the

amount of property taxes paid.

THE UNIT OF ANALYSIS

The current demographic unit of analysis used by the

Census Bureau in the CPS for measuring poverty is the

family. The official poverty thresholds also assume that

the family is the primary economic unit for poverty classification. Defining this unit relies on specific definitions of

family and nonfamily relationships within a household.

The Census Bureau defines a household as all the persons

who occupy a housing unit, where a housing unit is a

house, an apartment, a mobile home, a group of rooms, or

a single room in which the occupants: (1) live separately

from any other persons in the building, and (2) have direct

Table C18. Reference Family Thresholds Based on Different Approaches to Estimate Shelter Costs

[Dollars]

FCEstU estimated

shelter costs

FCSU out-of-pocket

expenditures

FCReqU reported rental

equivalence

1995 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,214.35 15,544.58 17,211.81

1996 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,557.25 15,743.76 17,670.69

1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,808.69 15,998.32 18,162.22

Source: Bureau of Labor Statistics tabulations of Consumer Expenditure Survey data.

APPENDIX C C–23

U.S. Census Bureau
access from the outside of the building or through a common hall. One person in each household is designated as

the householder, and this is usually the person, or one of

the persons, in whose name the home is owned, being

bought, or rented. Other household members are characterized according to their relationship to this householder,

or reference person, by asking the ‘‘relationship to reference person’’ question. A family is defined as a group of

two or more persons related by birth, marriage, or adoption who reside together; such persons are usually considered members of one family. A household may consist of

one family, one person living alone, two or more families

living together, or any other group of related or unrelated

persons who share living arrangements.

The current official poverty measure uses three distinguishable units of analysis: (1) primary families, (2) unrelated subfamilies, and (3) unrelated individuals aged 15 or

older. The primary family in a household includes everyone in the household related to the householder. An unrelated subfamily includes persons who are not related to

the primary family but who are related to each other as (1)

husband and wife or (2) parent(s) and never-married child(ren) under age 18. An unrelated individual is a person

aged 15 and over in a household who is not a member of

a primary family or an unrelated subfamily, whether living

alone or with others in the household.71 The poverty status of an individual is ascertained by comparing the sum

of the incomes of all members of that person’s primary or

unrelated subfamily to the appropriate poverty threshold,

or by comparing the income of an unrelated individual to

the appropriate poverty threshold. The current use of family as the unit of analysis has a normative basis also

reflected in some Federal law and program rules. Family

members are expected to share resources to a degree that

unrelated persons are not.

Persons Not Officially Related to the Householder

Cohabiting couples. The category unmarried partner

was implemented in the relationship to reference person

question by the Census Bureau to identify cohabiting

couples beginning in the 1990 Census of Population and

Housing, the 1995 CPS, and the 1996 SIPP. An unmarried

partner is defined as a person who is not related to the

householder, but who shares living quarters and has a

close personal relationship to the householder. Unmarriedpartner couples are identified in these data collection systems only if one of the partners is the householder. A

review of these data suggests that this direct measure of

cohabitation in the CPS yields relatively low estimates of

the prevalence of cohabitation. For example, in 1995, estimates from the National Survey of Family Growth suggested that 22 percent of unmarried women aged 30 to

39 were cohabiting. This compares with 9 percent estimated from the CPS direct questions.72

In view of the relationship of many of these couples,

the panel recommended that cohabiting couples be

treated as families. Therefore, to reflect the pooling of

income and sharing of expenditures of these couples and

their families, estimates presented in section three of this

report include within a single unit of analysis the householder and unmarried partner of the householder, as well

as all the relatives of the householder and any children of

the unmarried partner who are present in the household.

The official measure excludes children of an unmarried

partner from the unrelated subfamily of the unmarried

partner if these children have ever been married or if they

are age 18 or over, classifying them instead as unrelated

individuals, that is, as separate units of analysis for

assessing poverty. The more inclusive cohabiting-couple

unit of analysis implemented here includes all children of

an unmarried partner within the income pooling unit of

the unmarried partner and the householder, regardless of

the marital status or age of these children. Children who

are the biological children of both the householder and the

unmarried partner are included in the official poverty unit

of analysis of only one of these parents, but the cohabiting unit of analysis links these children with both of their

biological parents.

Housemates, roommates, foster children, and other

nonrelatives. The units of analysis currently used in the

official poverty measure also do not combine the incomes

of various additional categories of nonrelatives in the

household with the incomes of the householder and relatives of the householder. A housemate or roommate is

defined by the Census Bureau as a person who is not

related to the householder, but who shares living quarters

primarily in order to share expenses.

In addition, even if they have a parent in the household,

but have ever been married or are age 18 or over, housemates and roommates are excluded by the official poverty

measure from the unrelated subfamily that includes their

parents; instead they are classified as unrelated individuals with their poverty status based on their own income

only. Housemates and roommates who are children under

age 15 are not included in any official poverty unit and

their poverty status is neither calculated nor reported if

they do not have a parent in the household, despite the

fact that they are sharing in the housing and other

resources available in the household. Children who are not

related to the householder but who live with both biological parents are included in the unit of analysis of no more

than one of these parents if the parents are not currently

married to each other.

Foster children are placed by the local welfare department in homes of persons (foster parents) who provide

care to the children in return for money paid by a state or 71Note that these rules imply that unrelated children under age

15 (such as foster children) are not included in the universe of

people for whom poverty status is calculated. 72See Bumpass and Lu, 1998, and Casper et al., 1999.

C–24 APPENDIX C

U.S. Census Bureau
local welfare office. Foster children share in the housing

and meals of the household, and no doubt other important aspects of the level of living afforded by the family

income available to foster parents. Yet, if they are under

age 15, foster children are excluded from all official units

of analysis and their poverty status is neither calculated

nor reported, while, if they are age 15 or older, they are

each treated as an independent unit of analysis based on

only their own personal income. Other nonrelatives of the

householder who are not members of unrelated subfamilies are treated in a fashion similar to foster children.

These persons include friends and guests who are living in

the home and sharing in the accommodations and perhaps

other aspects of the household level of living, yet they are

excluded from the official poverty universe if they are

under age 15, and they are treated as an independent

unrelated individual with access to only their own income

if they are age 15 or older.

Roomers and boarders. Roomers and boarders pay

money to the householder in return for lodging or meals.

Hence, the rent they pay offsets at least a portion of the

costs of maintaining the housing unit (permitting economies of scale in housing for both the householder and the

roomer), and they may pay for food which may permit the

householder (and boarder) to benefit from economies of

scale in purchasing these commodities. In other words,

roomers and boarders are sharing their income with the

householder, through a formal economic transaction, in

order to contribute to payments for housing and, at least

sometimes, to food costs that maintain the household.

Despite their financial contribution to maintaining the

household, roomers and boarders who are members of

unrelated subfamilies are treated by the official poverty

measure as a unit of analysis separate from other household members, and among roomers and boarders who are

not members of unrelated subfamilies (including those

who have a parent in the home but have ever been married or are age 18 or over), poverty status is based only on

their own income if they are age 15 or older, or if they are

under age 15 they are excluded from the official poverty

universe and their poverty status is neither calculated nor

reported.

Defining Four Alternative Units of Analysis

In accordance with recommendations of the panel, new

poverty estimates are derived here based on four alternative units of analysis that are defined more inclusively

than those in the official poverty measure.

1. First, the cohabiting-couple unit of analysis is defined

for households with an unmarried partner as including

(1) the householder, (2) all the relatives of the householder, (3) the unmarried partner, and (4) regardless of

their marital status or age, the children of the unmarried partner. One purpose of including all persons

identified as children of the unmarried partner is to

insure the identical treatment of persons identified as

children of the householder and those identified as

children of the unmarried partner. Because the Census

Bureau explicitly identifies no more than one parent

for each person in a household, an unknown but

potentially sizeable number of persons identified as

children of the householder are also biological children of the unmarried partner, and an unknown but

potentially sizeable number of persons identified as

children of the unmarried partner are also biological

children of the householder. In other words, in an

unknown but potentially large number of households,

the householder and the unmarried partner are actually the biological parents of the children identified by

the Census Bureau as the child of only one of them.

All persons in the household who are not included in

this ‘‘cohabiting couple’’ unit of analysis are instead

classified according to the procedures of the official

measure.

2. Second, the housemate-roommate unit of analysis is

defined for households with one or more housemates,

roommates, or other nonrelatives of the householder

who were not included in the unmarried-partner unit

of analysis. For these households the unit of analysis

includes (1) the householder, (2) all the relatives of the

householder, (3) the housemates, roommates, foster

children, or other nonrelatives of the householder who

were not included in the unmarried-partner unit of

analysis, and (4) regardless of their marital status or

age, the children of the housemates, roommates, or

other nonrelatives of the householder who were not

included in the unmarried-partner unit of analysis. All

persons in the household who are not included in this

unit of analysis, that is, those included in the unmarried partner unit of analysis, or roomers and boarders,

are instead classified according to the procedures of

the official measure. In results that combine the

unmarried-partner and housemate-roommate units of

analysis, all the nonrelatives included in both units of

analysis with the householder and householder’s relatives are treated as a single unit of analysis.

3. Third, the roomer-boarder unit of analysis is defined

for households with one or more roomers or boarders

who were not included in the unmarried-partner or

housemate-roommate units of analysis. For these

households, the unit of analysis includes (1) the

householder, (2) all the relatives of the householder,

and (3) roomers and boarders of the householder who

were not included in the unmarried-partner or

housemate-roommate units of analysis. All persons in

the household who are not included in this unit of

analysis, that is, those included in the unmarried partner and housemate-roommate units of analysis, are

APPENDIX C C–25

U.S. Census Bureau
instead classified according to the procedures of the

official measure.

4. Fourth, the household unit of analysis is defined as

including all persons in the household.

C–26 APPENDIX C

U.S. Census Bureau
Appendix D.

Summary of NAS Panel Recommendations

This appendix summarizes pages 4 through 15 of Measuring Poverty: A New Approach, Constance F. Citro and

Robert T. Michael, editors, National Academy Press, 1995.

Recommendation 1.1. The official U.S. measure of poverty should be revised to reflect more nearly the circumstances of the nation’s families and changes in them over

time. The revised measure should comprise a set of poverty thresholds and a definition of family resources (for

comparison with the thresholds to determine who is in or

out of poverty) that are consistent with each other and

otherwise statistically defensible. The concepts underlying

both the thresholds and definition of family resources

should be broadly acceptable and understandable and

operationally feasible.

Recommendation 1.2. On the basis of the criteria in

Recommendation 1.1, the poverty measure should have

the following characteristics:

• The poverty thresholds should represent a budget for

food, clothing, shelter (including utilities), and a small

additional amount to allow for other needs (e.g., household supplies, personal care, nonwork-related transportation).

• A threshold for a reference family type should be developed using actual Consumer Expenditure Survey data

and updated annually to reflect changes in expenditures

in food, clothing, and shelter over the previous 3 years.

• The reference family threshold should be adjusted to

reflect the needs of different family types and to reflect

geographic differences in housing costs.

• Family resources should be defined—consistent with the

threshold concept—as the sum of money income from

all sources together with the value of near-money benefits (e.g., food stamps) that are available to buy goods

and services in the budget, minus expenses that cannot

be used to buy these goods and services. Such

expenses include income and payroll taxes, child care

and other work-related expenses, child support payments to another household, and out-of-pocket medical

care costs, including health insurance premiums.

Recommendation 2.1. A poverty threshold with which

to initiate a new series of official U.S. poverty statistics

should be derived from Consumer Expenditure Survey

data for a reference family of four persons (two adults and

two children). The procedure should be to specify a percentage of median annual expenditures for such families

on the sum of three basic goods and services (food, clothing, and shelter, including utilities) and apply a specified

multiplier to the corresponding dollar level so as to add a

small amount for other needs.

Recommendation 2.2. The new poverty threshold

should be updated each year to reflect changes in consumption of the basic goods and services contained in the

poverty budget: determine the dollar value that represents

the designated percentage of the median level of expenditures on the sum of food, clothing, and shelter for twoadult/two-child families and apply the designated multiplier. To smooth out year-to-year fluctuations and to lag

the adjustment to some extent, perform the calculations

for each year by averaging the most recent 3 years’ worth

of data from the Consumer Expenditure Survey, with the

data for each of those years brought forward to the current period by using the change in the Consumer Price

Index.

Recommendation 2.3. When the new poverty threshold

concept is first implemented and for several years thereafter, the Census Bureau should produce a second set of

poverty rates for evaluation purposes by using the new

thresholds updated only for price changes (rather than for

changes in consumption of the basic goods and services

in the poverty budget).

Recommendation 2.4. As part of implementing a new

official U.S. poverty measure, the current threshold level

for the reference family of two adults and two children

($14,228 in 1992 dollars) should be reevaluated and a

new threshold level established with which to initiate a

new series of poverty statistics. That reevaluation should

take account of both the new threshold concept and the

real growth in consumption that has occurred since the

official threshold was first set 30 years ago.

Recommendation 3.1. The four-person (two-adult/twochild) poverty threshold should be adjusted for other family types by means of an equivalence scale that reflects

differences in consumption by adults and children under

18 and economies of scale for larger families. A scale that

meets these criteria is the following: children under 18 are

treated as consuming 70 percent as much as adults on

average; economies of scale are computed by taking the

number of adult equivalents in a family (i.e., the number

APPENDIX D D–1

U.S. Census Bureau
of adults plus 0.70 times the number of children), and

then by raising this number to a power of from 0.65 to

0.75.

Recommendation 3.2. The poverty thresholds should

be adjusted for differences in the cost of housing across

geographic areas of the country. Available data from the

decennial census permit the development of a reasonable

cost-of-housing index for nine regions and, within each

region, for several population size categories of metropolitan areas. The index should be applied to the housing portion of the poverty thresholds.

Recommendation 3.3. Appropriate agencies should

conduct research to determine methods that could be

used to update the geographic housing cost component of

the poverty thresholds between the decennial censuses.

Recommendation 3.4. Appropriate agencies should

conduct research to improve the estimation of geographic

cost-of-living differences in housing as well as other components of the poverty budget. Agencies should consider

improvements to data series, such as the BLS area price

indexes, that have the potential to support improved estimates of cost-of-living differences.

Recommendation 4.1. In developing poverty statistics,

any significant change in the definition of family resources

should be accompanied by a consistent adjustment of the

poverty thresholds.

Recommendation 4.2. The definition of family

resources for comparison with the appropriate poverty

threshold should be disposable money and near-money

income. Specifically, resources should be calculated as follows:

• Estimate gross money income from all public and private sources for a family or unrelated individual (which

is income as defined in the current measure);

• Add the value of near-money nonmedical in-kind benefits, such as food stamps, subsidized housing, school

lunches, and home energy assistance;

• Deduct out-of-pocket medical care expenditures, including health insurance premiums;

• Deduct income taxes and social security payroll taxes;

• For families in which there is no nonworking parent,

deduct actual child care costs, per week worked, not to

exceed the earnings of the parent with the lower earnings or a cap that is adjusted annually for inflation;

• For each working adult, deduct a flat amount per week

worked (adjusted annually for inflation and not to

exceed earnings) to account for work-related transportation and miscellaneous expenses; and

• Deduct child support payments from the income of the

payer.

Recommendation 4.3. Appropriate agencies should

work to develop one or more ‘‘medical care-risk’’ indexes

that measure the economic risk to families and individuals

of having no or inadequate health insurance coverage.

However, such indexes should be kept separate from the

measure of economic poverty.

Recommendation 5.1. The Survey of Income and Program Participation (SIPP) should become the basis of official U.S. income and poverty statistics in place of the

March income supplement to the Current Population Survey (CPS). Decisions about the SIPP design and questionnaire should take account of the data requirements for

producing reliable time series of poverty statistics using

the proposed definition of family resources (money and

near-money income minus certain expenditures). Priority

should be accorded to methodological research for SIPP

that is relevant for improved poverty measurement. A particularly important problem to address is population undercoverage, particularly of low-income minority groups.

Recommendation 5.2. To facilitate the transition to SIPP,

the Census Bureau should produce concurrent time series

of poverty rates from both SIPP and the March CPS by

using the proposed revised threshold concept and updating procedure and the proposed definition of family

resources as disposable income. The current series should

be developed starting with 1984, when SIPP was first

introduced.

Recommendation 5.3. The Census Bureau should routinely issue public-use files from both SIPP and the March

CPS that include the Bureau’s best estimate of disposable

income and its components (taxes, in-kind benefits, child

care expenses, etc.) so that researchers can obtain poverty

rates consistent with the new threshold concept from

either survey.

Recommendation 5.4. Appropriate agencies should

conduct research on methods to develop poverty estimates from household surveys with limited income information that are comparable to the estimates that would be

obtained from a fully implemented disposable income

definition of family resources.

Recommendation 5.5. Appropriate agencies should

conduct research on methods to construct small-area poverty estimates from the limited information in the decennial census that are comparable with the estimates that

would be obtained under a fully implemented disposable

income concept. In addition, serious consideration should

be given to adding one or two questions to the decennial

census to assist in the development of comparable estimates.

D–2 APPENDIX D

U.S. Census Bureau
Recommendation 5.6. The Bureau of Labor Statistics

should undertake a comprehensive review of the Consumer Expenditure Survey to assess the costs and benefits

of changes to the survey design, questionnaire, sample

size, and other features that could improve the quality and

usefulness of the data. The review should consider ways

to improve the CEX for the purpose of developing poverty

thresholds, for making it possible at a future date to measure poverty on the basis of a consumption or expenditure

concept of family resources, and for other analytic purposes related to the measurement of consumption,

income, and savings.

Recommendation 6.1. The official poverty measure

should continue to be derived on an annual basis. Appropriate agencies should develop poverty measures for periods that are shorter and longer than a year, with data from

SIPP and the Panel Study of Income Dynamics, for such

purposes as program evaluation. Such measures may

require the inclusion of asset values in the family

resources definition.

Recommendation 6.2. The official measure of poverty

should continue to use families and unrelated individuals

as the units of analysis for which thresholds are defined

and a resources aggregated. The definition of ‘‘family’’

should be broadened for purposes of poverty measurement to include cohabiting couples.

Recommendation 6.3. Appropriate agencies should

conduct research on the extent of resource sharing among

roommates and other household and family members to

determine if the definition of the unit of analysis for the

poverty measure should be modified in the future.

Recommendation 6.4. In addition to the basic poverty

counts and ratios for the total population and groups (the

number and proportion of poor people) the official poverty

series should provide statistics on the average income and

distribution of income for the poor. The count and other

statistics should also be published for poverty measures

in which family resources are defined net of government

taxes and transfers, such as a measure that defines

income in before-tax terms, a measure that excludes

means-tested government benefits from income, and a

measure that excludes all government benefits from

income. Such measures can help assess the effects of government taxes and transfers on poverty.

Recommendation 7.1. Agencies responsible for Federal

assistance programs that use the poverty guidelines

derived from the official poverty thresholds (or a multiple)

to determine eligibility for benefits and services should

consider the use of the panel’s proposed measure. In their

assessment, agencies should determine whether it may be

necessary to modify the measure (for example, through a

simpler definition of family resources or by linking eligibility less closely to the poverty thresholds because of possible budgetary constraints) to better serve program

objectives.

Recommendation 8.1. The states should consider linking their need standard for the Aid to Families With Dependent Children program to the panel’s proposed poverty

measure and whether it may be necessary to modify this

measure to better serve program objectives.

APPENDIX D D–3

U.S. Census Bureau
Elements of the Current and Proposed Poverty Measures1

Element Current Measure Proposed Measure

Threshold Concept ........................... Food times a large multiplier for all other expenses Food, clothing, and shelter, plus a little bit more

1992 level (two-adult/two-child family) .......... $14,228 Suggest within range of $13,700-$15,900

Updating method ............................. Update 1963 level each year for price changes Update each year by change in spending on food,

clothing, and shelter over previous 3 years by

two-adult/two-child families

Threshold Adjustments

By family type.............................. Separately developed thresholds by family type;

lower thresholds for elderly singles and couples

Reference family threshold adjusted by use of

equivalence scale, which assumes children need

less than adults and economies of scale for larger

families

By geographic area. . . . . . . . . . . . . . . . . . . . . . . . . No adjustments Adjust for housing cost by regions and size of

metropolitan area

Family Resource Definition (to compare with

threshold to determine poverty status) .......... Gross (before-tax) money income from all sources Gross money income, plus value of near-money

in-kind benefits (e.g. food stamps), minus income

and payroll taxes and other nondiscretionary

expenses (e.g., child care and other work-related

expenses; child support payments to another household; out-of-pocket medical care expenses, including health insurance premiums)

Data Source (for estimating income)............ March Current Population Survey Survey of Income and Program Participation

Time Period of Measurement ................. Annual Annual, supplemented by shorter term and longer

term measures

Economic Unit of Analysis ..................... Families and unrelated individuals Families (including cohabiting couples) and

unrelated individuals

1

Table copied from Table 1-1, page 41: Constance F. Citro and Robert T. Michael (eds.), Measuring Poverty: A New Approach, Washington, DC:

National Academy Press, 1995.

D–4 APPENDIX D

U.S. Census Bureau
Appendix E.

Source and Accuracy of Estimates

SOURCES OF DATA

Most estimates in this report come from data obtained

in March of the years 1991 through 1998 in the Current

Population Survey (CPS). The Census Bureau conducts the

survey every month, although this report uses only March

data for its estimates. The March survey uses two sets of

questions: the basic CPS and the supplement.

The Census Bureau used data from various sources in

developing alternative measures of income and poverty

for 1997. Specifically, we combined data from the American Housing Survey (AHS), the Consumer Expenditure Survey (CEX), the Survey of Income and Program Participation

(SIPP), the National Medical Expenditure Survey (NMES), the

Income Survey Development Program (ISDP), and the Internal Revenue Service (IRS) with CPS data.

In addition, this report uses the State Tax Handbook

from the Commerce Clearing House as another information source of tax data. For some noncash valuation estimates, this report uses data from the U.S. Department of

Agriculture (UDSA), the Health Care Financing Administration (HCFA), and the Department of Housing and Urban

Development (HUD).

A description of the sources of data we used to derive

these estimates follows. Except for the CPS, these descriptions are brief. See Current Population Reports, Series P60-

186RD, Measuring the Effect of Benefits and Taxes on

Income and Poverty: 1992, and publications on the appropriate surveys for more details.

American Housing Survey. The Census Bureau collects

housing data for the Department of Housing and Urban

Development. The population covered by the sample for

the AHS (called the Annual Housing Survey before 1984)

includes all housing units in the United States. For a more

detailed description of the sample design, see the report

Current Housing Reports, Series H150-89, The American

Housing Survey for the United States in 1989, U.S. Department of Commerce.

The AHS is no longer conducted in even numbered

years, so we based the property tax estimates in this

report on the 1993 AHS. Also, for the noncash estimates,

we used the 1985 AHS data in a model to estimate the

value of public housing. For more details on the AHS

model used to estimate public and subsidized housing values, please see Appendix B of Current Population Reports,

Series P60-186RD, Measuring the Effect of Benefits and

Taxes on Income and Poverty: 1992.

Consumer Expenditure Survey. There are two components to the Consumer Expenditure Survey: the Quarterly

Interview Survey and the Diary Survey.

The Quarterly Interview Survey obtains data on large

expenditures and those which occur on a fairly regular

basis; that is, the type of expenditures that we expect

respondents to recall accurately over a 3-month period

and for which records are likely to be available. The Diary

Survey provides data on items not covered in detail in the

Quarterly Survey by asking respondents to keep two

1-week diaries to record all purchases made during the

period.

Survey of Income and Program Participation. The

Survey of Income and Program Participation (SIPP) is a continuing panel survey, begun in 1983, that is sponsored

and conducted by the U.S. Census Bureau. The design in

effect until 1994 introduced a new sample panel each February. In 1994 and 1995, there were no panels introduced.

In 1996, a nonoverlapping design was implemented. Each

sample household is interviewed every 4 months. The

sample covers the U.S. civilian noninstitutionalized population and members of the Armed Forces living off post or

with their families on post. Sample size has varied from

12,500 to 23,500 households per panel; the 1996 panel is

composed of 36,700 households. The reporting unit is the

household, with unrelated individuals and families also

identified.

National Medical Expenditure Survey. The 1987

National Medical Expenditure Survey is a nationally representative survey of the civilian noninstitutionalized population in the United States. The survey was designed to

provide estimates of insurance coverage and the use of

services, expenditures, and sources of payment. The

household component involved four rounds of personal

and telephone interviews at 4-month intervals, with a

short telephone interview constituting a supplementary

fifth round. Ninety-four percent of those completing the

first interview, or about 37,000 persons in approximately

15,000 households, participated in all four rounds of interviewing.

Income Survey Development Program. The ISDP was

the research and development phase for the Survey of

Income and Program Participation (SIPP). The Census

Bureau used the ISDP to examine and resolve design,

operational, and technical issues for the SIPP. The household sample for the 1979 ISDP was a nationwide multiple

APPENDIX E E–1

U.S. Census Bureau
frame sample. The majority of sample households in the

ISDP came from addresses contacted in the 1976 Survey

of Income and Education.

Statisticians selected the remainder of sample households from a reserve file of sample cases maintained by

the Census Bureau. For a more detailed description of this

sample design, see the report Wage and Salary Data From

the Income Survey Development Program: 1979 (Preliminary Data From Interview Period One), Current Population

Reports, Special Studies, Series P-23, No. 118.

Internal Revenue Service data. Much of the IRS data in

this report come from the Statistics of Income (SOI) series,

in particular the SOI Bulletin Individual Income Tax

Returns, Preliminary Data: 1996, Spring 1998. This

report, based on a sample drawn from all tax returns filed

in 1997, presents information on taxpayers’ incomes,

exemptions, deductions, credits, and taxes.

Data from other sources. The State Tax Handbook,

October 1, 1991, from the Commerce Clearing House,

includes information on state tax systems. We updated

these data to reflect changes in state income tax rates.

Much of the data on cash and noncash benefits are

from administrative records. Values of school lunches and

food stamps are from USDA unpublished data. Medicaid

and medicare data come from HCFA unpublished records.

Also, USDA and HUD data are used to compute medicaid

and medicare values. For more details, see Appendix B of

Current Population Reports, Series P60-186RD, Measuring

the Effect of Benefits and Taxes on Income and Poverty:

1992.

Basic CPS. The basic CPS collects primarily labor force

data about the civilian noninstitutional population. Field

representatives ask questions concerning labor force participation of each member 15 years old and over in every

sample household.

The CPS sample includes coverage in all 50 states and

the District of Columbia. The Census Bureau continually

updates the sample to account for new residential construction. The Census Bureau divides the United States

into 2,007 geographic areas. In most states, a geographic

area consists of a county or several contiguous counties.

In some areas of New England and Hawaii, the Census

Bureau uses minor civil divisions instead of counties. We

select a total of 754 geographic areas for the sample.

About 50,000 occupied households are eligible for interview every month. Field representatives are unable to

obtain interviews at about 3,200 of these units. This

occurs when the occupants are not found at home after

repeated calls or are unavailable for some other reason.

Since the introduction of the CPS, the Census Bureau

has redesigned the CPS sample several times. These redesigns have improved the quality and accuracy of the data

and have satisfied changing data needs. The Census

Bureau completely implemented the most recent changes

in July 1995.

Table E-1 summarizes changes in the CPS designs for

the years 1960 to 1998.

CPS March supplement. In addition to the basic CPS

questions, field representatives ask supplementary questions in March about money income received the previous

calendar year.

To obtain more reliable data for the Hispanic population, the Census Bureau increased the March CPS sample

by about 2,500 eligible housing units, interviewed the previous November, that contained at least one sample person of Hispanic origin.1 In addition, the sample includes

people in the Armed Forces living off post or with their

families on post.

CPS estimation procedure. This survey’s estimation

procedure inflates weighted sample results to independent

estimates of the civilian noninstitutional population of the

United States by age, gender, race, Hispanic/non-Hispanic

origin, and state of residence. The independent estimates

are based on:

• The 1990 Decennial Census of Population and Housing.

• An adjustment for undercoverage in the 1990 census.

• Statistics on births, deaths, immigration, and emigration.

• Statistics on the size of the Armed Forces.

1

This report shows information on the Hispanic population

collected in the 50 states and the District of Columbia, and therefore

does not include residents of Puerto Rico.

Table E-1. Description of the March Current

Population Survey

Time period Number of

sample

areas

Housing units eligible1

Interviewed

Not

interviewed

1996 to 1998 . . . . . . 754 46,800 3,200

1995 . . . . . . . . . . . . . 792 56,700 3,300

1990 to 1994 . . . . . 729 57,400 2,600

1989 . . . . . . . . . . . . . 729 53,600 2,500

1988 . . . . . . . . . . . . . 729 53,200 2,600

1986 to 1987 . . . . . . 729 57,000 2,500

1985 ............. 2

629/729 57,000 2,500

1982 to 1984 . . . . . . 629 59,000 2,500

1980 to 1981 . . . . . . 629 65,500 3,000

1977 to 1979 . . . . . . 614 55,000 3,000

1973 to 1976 . . . . . . 461 46,500 2,500

1972 . . . . . . . . . . . . . 449 45,000 2,000

1967 to 1971 . . . . . 449 48,000 2,000

1963 to 1966 . . . . . . 357 33,500 1,500

1960 to 1962 . . . . . 333 33,500 1,500

1

Excludes about 2,500 Hispanic households added from the previous November sample. (See ‘‘CPS March Supplement.’’) 2

The Census Bureau redesigned the CPS following the 1980 Decennial Census of Population and Housing. During the phase-in of the new design, housing

units from the new and old designs were in sample.

E–2 APPENDIX E

U.S. Census Bureau
The independent population estimates used for 1994

and later are based on updates to controls established by

the 1990 decennial census. Data previous to 1994 are

based on independent population estimates from the latest available decennial census data. For more details on

the change in independent estimates, see the section

entitled ‘‘Introduction of 1990 Census Population Controls’’ in an earlier report (Series P-60, No. 188). The estimation procedure for the March supplement included a

further adjustment so that the husband and wife of a

household received the same weight.

ACCURACY OF THE ESTIMATES

Since the CPS estimates come from a sample, they may

differ from figures from a complete census using the same

questionnaires, instructions, and enumerators. A sample

survey estimate has two possible types of error: sampling

and nonsampling. The accuracy of an estimate depends

on both types of error, but the full extent of the nonsampling error is unknown. Consequently, one should be particularly careful when interpreting results based on a relatively small number of cases or on small differences

between estimates. The standard errors for CPS estimates

primarily indicate the magnitude of sampling error. They

also partially measure the effect of some nonsampling

errors in responses and enumeration, but do not measure

systematic biases in the data. Bias is the average, over all

possible samples, of the differences between the sample

estimates and the true value.

Nonsampling variability. We can attribute nonsampling

errors to several sources including the following:

• Inability to obtain information about all cases in the

sample.

• Definitional difficulties.

• Differences in the interpretation of questions.

• Respondents’ inability or unwillingness to provide correct information.

• Respondents’ inability to recall information.

• Errors made in data collection, such as recording and

coding the data.

• Errors made in processing the data.

• Errors made in estimating values for missing data.

• Failure to represent all units with the sample (undercoverage).

CPS undercoverage results from missed housing units

and missed people within sample households. Compared

with the level of the 1990 decennial census, overall CPS

undercoverage is about 8 percent. Undercoverage varies

with age, gender, and race. Generally, undercoverage is

larger for males than for females and larger for Blacks and

other races combined than for Whites. As described previously, ratio estimation to independent age-gender-raceHispanic population controls partially corrects for bias due

to undercoverage. However, biases exist in the estimates

to the extent that missed people in missed households or

missed people in interviewed households have different

characteristics from those of interviewed people in the

same age-gender-race-Hispanic origin group.

A common measure of survey coverage is the coverage

ratio, the estimated population before post-stratification

divided by the independent population control. Table E-2

shows CPS coverage ratios for age-gender-race groups for

a typical month. The CPS coverage ratios can exhibit some

variability from month to month, but these are a typical

set of coverage ratios.

Answers to questions about money income often

depend on the memory of one person in the household.

Recall problems can cause underestimates of income in

survey data because it is easy to forget minor or irregular

sources of income. Respondents may also misunderstand

Table E-2. March CPS Coverage Ratios

Age

Non-Black Black All persons

Male Female Male Female Male Female Total

0 to 14 years ............................ 0.942 0.951 0.880 0.904 0.932 0.943 0.937

15 to 19 years........................... 0.864 0.910 0.885 0.751 0.867 0.884 0.876

20 to 24 years........................... 0.823 0.877 0.707 0.757 0.808 0.859 0.834

25 to 29 years........................... 0.863 0.919 0.755 0.810 0.850 0.903 0.877

30 to 34 years........................... 0.880 0.950 0.671 0.833 0.855 0.934 0.895

35 to 44 years........................... 0.899 0.940 0.684 0.863 0.875 0.930 0.903

45 to 54 years........................... 0.938 0.961 0.778 0.953 0.923 0.960 0.942

55 to 64 years........................... 0.932 0.953 0.834 0.929 0.923 0.951 0.938

65 to 74 years........................... 0.932 0.977 0.939 0.958 0.932 0.975 0.956

75 years and older....................... 1.019 1.008 0.910 0.961 1.011 1.004 1.007

15 years and older....................... 0.902 0.945 0.767 0.858 0.887 0.934 0.912

0 years and older ........................ 0.911 0.946 0.802 0.871 0.898 0.936 0.917

APPENDIX E E–3

U.S. Census Bureau
what the Census Bureau considers money income or may

simply be unwilling to answer these questions correctly

because the questions are considered too personal. See

Appendix C, Current Population Reports, Series P60-184,

Money Income of Households, Families, and Persons in the

United States: 1992 for more details.

For additional information on nonsampling error, see

Appendix F of this report. Also, see Statistical Policy Working Paper 3, An Error Profile: Employment as Measured by

the Current Population Survey, Office of Federal Statistical

Policy and Standards, U.S. Department of Commerce, 1978

and Technical Paper 40, The Current Population Survey:

Design and Methodology, Bureau of the Census, U.S.

Department of Commerce.

Comparability of data. Data obtained from the CPS and

other sources are not entirely comparable. This results

from differences in interviewer training and experience

and in differing survey processes. This is an example of

nonsampling variability not reflected in the standard

errors. Use caution when comparing results from different

sources.

A number of changes were made in data collection and

estimation procedures beginning with the January 1994

CPS. The major change was the use of a new

questionnaire. The Bureau of Labor Statistics redesigned

the questionnaire to measure the official laborforce concepts more precisely, to expand the amount of data available, to implement several definitional changes, and to

adapt to a computer-assisted interviewing environment.

The Census Bureau modified the March supplemental

income questions for adaptation to computer-assisted

interviewing, but did not change definitions and concepts.

Because of these and other changes, one should use caution when comparing estimates from data collected in

1994 and later years with estimates from earlier years.

Data users should also use caution when comparing

estimates in this report (which reflect 1990 census-based

population controls) with estimates from the March 1993

CPS and earlier years (which reflect 1980 census-based

population controls). This change in population controls

had relatively little impact on summary measures, such as

means, medians, and percent distributions. It did have a

significant impact on levels. For example, 1990-based

population controls caused a 1-percent increase in the

civilian noninstitutional population and in the number of

families and households. Thus, estimates of levels for data

collected in 1994 and later years will differ from those for

earlier years by more than what could be attributed to

actual changes in the population. These differences could

be disproportionately greater for certain subpopulation

groups than for the total population.

Since the Census Bureau did not use independent population control totals for people of Hispanic origin before

1983, compare Hispanic estimates over time cautiously.

Based on the results of each decennial census, the Census Bureau gradually introduces a new sample design for

the CPS. During this phase-in period, the Census Bureau

collects CPS data from sample designs based on different

censuses. While most CPS estimates have been unaffected

by this mixed sample, geographic estimates are subject to

greater error and variability. Users should exercise caution

when comparing estimates across years for metropolitan/

nonmetropolitan categories. For more information, see

Appendix C, Current Population Reports, Series P60-193,

Money Income in the United States: 1995 (With Separate

Data on Valuation of Noncash Benefits).

Note when using small estimates. The Census Bureau

shows summary measures (such as medians and percentage distributions) only when the base is 75,000 or greater.

Because of the large standard errors involved, summary

measures would probably not reveal useful information

when computed on a smaller base. However, we display

estimated numbers even though the relative standard

errors of these numbers are larger than those for corresponding percentages. These smaller estimates permit

combinations of the categories to suit data users’ needs.

Take care in the interpretation of small differences. For

instance, even a small amount of nonsampling error can

cause a borderline difference to appear significant or not,

thus distorting a seemingly valid hypothesis test.

Sampling variability. Sampling variability is variation

that occurred by chance because a sample was surveyed

rather than the entire population. Standard errors, as calculated by methods described below in Standard errors

and their use, are primarily measures of sampling variability, but they may include some nonsampling error.

Standard errors and their use. Data users must use a

number of approximations to derive, at a moderate cost,

standard errors applicable to the estimates in this report.

Instead of providing an individual standard error for each

estimate, we have provided two parameters, a and b, to

calculate standard errors for each type of characteristic.

Table E-3 provides standard error parameters for various types of characteristics. Table E-4 provides factors to

approximate CPS standard errors for estimates prior to

1997. Table E-5 has the year-to-year correlation coefficients for income characteristics.

The sample estimate and its standard error enable one

to construct a confidence interval, a range that would

include the average result of all possible samples with a

known probability. For example, if all possible samples

were surveyed under essentially the same general conditions and using the same sample design, and if an estimate and its standard error were calculated from each

sample, then approximately 90 percent of the intervals

from 1.645 standard errors below the estimate to 1.645

standard errors above the estimate would include the

average result of all possible samples.

A particular confidence interval may or may not contain

the average estimate derived from all possible samples.

E–4 APPENDIX E

U.S. Census Bureau
However, one can say with specified confidence that the

interval includes the average estimate calculated from all

possible samples.

Some statements in the report may contain estimates

followed by a number in parentheses. This number can be

added to and subtracted from the estimate to calculate

upper and lower bounds of the 90-percent confidence

interval. For example, if a statement contains the phrase

Table E-3. CPS Standard Error Parameters for Poverty, Income, and Nonincome Characteristics: 1997

Characteristics

Total or White Black Hispanic

ababa b

BELOW POVERTY LEVEL

Persons

Total ....................................... -0.000039 10,380 -0.000301 10,380 -0.000338 10,380

Male ....................................... -0.000079 10,380 -0.000647 10,380 -0.000641 10,380

Female ..................................... -0.000076 10,380 -0.000563 10,380 -0.000666 10,380

Age

Under 15 ................................... -0.000134 8,002 -0.000834 8,002 -0.000857 8,002

Under 18 ................................... -0.000112 8,002 -0.000698 8,002 -0.000664 8,002

15 and over ................................. -0.000050 10,380 -0.000417 10,380 -0.000486 10,380

15 to 24 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -0.000106 3,927 -0.000703 3,927 -0.000487 3,927

25 to 44 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -0.000047 3,927 -0.000366 3,927 -0.000276 3,927

45 to 64 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -0.000070 3,927 -0.000666 3,927 -0.000295 3,927

65 and over ................................. -0.000122 3,927 -0.001403 3,927 -0.000885 3,927

Households, Families, and Unrelated

Individuals

Total ....................................... +0.000102 2,442 +0.000102 2,442 +0.000102 2,442

ALL INCOME LEVELS

Persons

Total ....................................... -0.000012 2,454 -0.000116 2,810 -0.000135 2,810

Male ....................................... -0.000025 2,454 -0.000258 2,810 -0.000264 2,810

Female ..................................... -0.000023 2,454 -0.000210 2,810 -0.000275 2,810

Age

15 to 24 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -0.000066 2,454 -0.000503 2,810 -0.000349 2,810

25 to 44 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -0.000030 2,454 -0.000262 2,810 -0.000197 2,810

45 to 64 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -0.000044 2,454 -0.000477 2,810 -0.000211 2,810

65 and over ................................. -0.000076 2,454 -0.001047 2,810 -0.000633 2,810

Households, Families, and Unrelated

Individuals

Total ....................................... -0.000013 2,241 -0.000119 2,247 -0.000210 2,247

Households with children under 18 ............ -0.000013 2,241 -0.000119 2,247 -0.000210 2,247

NONINCOME CHARACTERISTICS

Persons

Employment status .......................... -0.000018 2,985 -0.000125 3,139 -0.000151 3,139

Educational attainment ....................... -0.000012 2,757 -0.000139 2,680 -0.000163 3,051

Health insurance ............................ -0.000024 6,332 -0.000320 11,039 -0.000359 11,039

Total, Marital Status, Other

Some household members ................... -0.000019 5,211 -0.000217 7,486 -0.000244 7,486

All household members ...................... -0.000024 6,332 -0.000320 11,039 -0.000359 11,039

Households, Families, and Unrelated

Individuals

Total ....................................... -0.000012 2,068 -0.000077 1,871 -0.000155 1,871

Note: To determine parameters prior to 1997, multiply by the appropriate factor in Table E-4. For nonmetropolitan residence categories, multiply

the a and b parameters by 1.5. For foreign-born characteristics, multiply the a and b parameters for Total and White by 1.3. No adjustment is necessary for Blacks and Hispanics.

APPENDIX E E–5

U.S. Census Bureau
‘‘grew by 1.7 (±1.0) percent,’’ the 90-percent confidence

interval for the estimate, 1.7 percent, is 0.7 percent to 2.7

percent.

Data users may also use standard errors to perform

hypothesis testing. This is a procedure for distinguishing

between population parameters using sample estimates.

One common type of hypothesis appearing in this report

is that two population parameters are different.

One can perform tests at various levels of significance.

The significance level of a test is the probability of concluding that the characteristics are different when, in fact,

they are the same. All statements of comparison in the

text were tested at the 0.10 level of significance or better.

This means that the absolute value of the estimated difference between characteristics is greater than or equal to

1.645 times the standard error of the difference.

The Census Bureau uses 90-percent confidence intervals and 0.10 levels of significance to determine statistical

validity. Consult standard statistical textbooks for alternative criteria.

Standard errors of estimated numbers. One can

obtain the approximate standard error, sx, of an estimated

number shown in this report by using the formula:

sx 5 =ax 2 1 bx (1)

Here x is the size of the estimate and a and b are the

parameters in Table E-3 associated with the particular type

of characteristic. When calculating standard errors from

cross-tabulations involving different characteristics, use

the set of parameters for the characteristic which will give

the largest standard error.

Illustration. Suppose that there were 35,574,000 people

below the poverty level in 1997. Use the appropriate

parameters from Table E-3 and formula (1) to get

Number, x 35,574,000

a parameter -0.000039

b parameter 10,380

Standard error 566,000

90% conf. int. 34,644,000 to 36,504,000

The standard error is calculated as

sx 5 =20.000039 x 35,574,0002 1 10,380 x 35,574,000 5 566,000

The 90-percent confidence interval is calculated as

35,574,000 ± 1.645 x 566,000.

A conclusion that the average estimate derived from all

possible samples lies within a range computed in this way

would be correct for roughly 90 percent of all possible

samples.

Standard errors of estimated percentages. The reliability of an estimated percentage, computed using

Table E-4. CPS Factors to Apply to a and b

Parameters for Estimates Prior to 1997

Characteristics Factor

NON-HISPANIC

1996 ......................................... 1.00

1989 to 1995 ................................. 0.92

1988 ......................................... 1.02

1981 to 1987 ................................. 0.86

1967 to 1980 ................................. 0.75

HISPANIC

1996 ......................................... 1.00

1989 to 1995 ................................. 0.92

1988 ......................................... 1.19

1984 to 1987 ................................. 0.86

Table E-5. CPS Year-to-Year Correlation Coefficients for Poverty and Income Estimates

Characteristics

Below poverty level All income levels

1972-1983 or

1984-1997 1983 - 1984 1971 - 1972 1970 - 1971 1960 - 1997

People Families People Families People Families People Families People

Families,

households,

and unrelated

individuals

Total ............ 0.45 0.35 0.39 0.30 0.15 0.14 0.31 0.28 0.30 0.35

White.............. 0.35 0.30 0.30 0.26 0.14 0.13 0.28 0.25 0.30 0.35

Black .............. 0.45 0.35 0.39 0.30 0.17 0.16 0.35 0.32 0.30 0.35

Other races ........ 0.45 0.35 0.30 0.30 0.17 0.16 0.35 0.32 0.30 0.35

Hispanic1 .......... 0.65 0.55 0.56 0.47 0.17 0.16 0.35 0.32 0.45 0.55

1

People of Hispanic origin may be of any race.

Note: These correlations are for comparisons of consecutive years. For comparisons of nonconsecutive years, assume the correlations are zero.

For Asians and Pacific Islanders, use the correlation coefficient for total. Correlation coefficients for 1983-84 are lower than those for 1982-83 or

1984-85 because of the phase-in of the new sample design.

E–6 APPENDIX E

U.S. Census Bureau
sample data from both numerator and denominator,

depends on both the size of the percentage and its base.

Estimated percentages are relatively more reliable than the

corresponding estimates of the numerators of the percentages, particularly if the percentages are 50 percent or

more. When the numerator and denominator of the percentage are in different categories, use the parameter

from Table E-3 indicated by the numerator. One can obtain

the approximate standard error, sx,p, of an estimated percentage by using the formula

sx,p 5 Î b

x p~100 2p! (2)

Here x is the total number of people, families, households,

or unrelated individuals in the base of the percentage, p is

the percentage (0 ≤ p ≤ 100), and b is the parameter in

Table E-3 associated with the characteristic in the numerator of the percentage.

Illustration. Suppose that of the 35,574,000 people below

the poverty level in 1997, 24,396,000, or 68.6 percent,

were White. Use the appropriate parameter from Table E-3

and formula (2) to get

Percentage, p 68.6

Base, x 35,574,000

b parameter 10,380

Standard error 0.8

90% conf. int. 67.3 to 69.9

The standard error is calculated as

ss,p 5 Î 10,380

35,574,000 x 68.6 x ~100 2 68.6! 5 0.8

The 90-percent confidence interval is calculated as 68.6

± 1.645x0.8.

Standard error of a difference. The standard error of

the difference between two sample estimates is approximately equal to

sx2y 5 =sx

2 1 sy2 2 2rsxsy (3)

where sx and sy are the standard errors of the estimates, x

and y. The estimates can be numbers, percentages, ratios,

etc. Table E-5 contains the correlation coefficient, r, for

year-to-year comparisons for CPS income estimates of

numbers and proportions. For other comparisons, assume

that r equals zero. Making this assumption will result in

accurate estimates of standard errors for the difference

between two estimates of the same characteristic in two

different areas, or for the difference between separate and

uncorrelated characteristics in the same area. However, if

there is a high positive (or negative) correlation between

the two characteristics, the formula will overestimate (or

underestimate) the true standard error.

Illustration. Suppose that the number of people below the

poverty level in 1997 was 35,574,000 and in 1996 was

36,529,000. The apparent difference is -955,000. Use the

appropriate parameters and factors from Table E-3 and

Table D-4 and formulas (1) and (3) to get

x y difference

Estimate, x 35,574,000 36,529,000 -955,000

a parameter -0.000039 -0.000039 -

b parameter 10,380 10,380 -

r - - 0.45

Standard error 566,000 572,000 597,000

90% conf. int. 34,644,000 to

36,504,000

35,588,000 to

37,470,000

-1,937,000

to

27,000

The standard error of the difference is calculated as

sx2y 5 =566,0002 1 572,0002 2 2x0.45 x 566,000 x 571,000 5 597,000

The 90-percent confidence interval for the estimated difference between the number of people in poverty for

1997 and 1996 is calculated as -955,000 ± 1.645 x

597,000. Because this interval contains zero, we cannot

conclude with 90-percent confidence that the number of

people below the poverty level in 1997 was lower than the

number of people below the poverty level in 1996.

Standard error of a ratio. Certain estimates may be

calculated as the ratio of two numbers. The standard error

of a ratio, x/y, may be computed using

sx/y 5 x

y Î(

sx

x )

2

1 (

sy

y )

2

2 2r

sxsy

xy (4)

The standard error of the numerator, sx, and that of the

denominator, sy , may be calculated using formulas

described earlier. In formula (4), r represents the correlation between the numerator and the denominator of the

estimate.

For one type of ratio, the denominator is a count of

families or households and the numerator is a count of

people in those families or households with a certain characteristic. If there is at least one person with the characteristic in every family or household, use 0.7 as an estimate

of r. An example of this type is the mean number of children per family with children.

For all other types of ratios, r is assumed to be zero. If r

is actually positive (or negative), then this procedure will

provide an overestimate (or underestimate) of the standard error of the ratio. Examples of this type are the mean

number of children per family and the family poverty rate.

Note: For estimates expressed as the ratio of x per

100 y or x per 1,000 y, multiply formula (4) by 100 or

1,000, respectively, to obtain the standard error.

Illustration. Suppose the number of families below the

poverty level, x, was 7,324,000 and the total number of

families, y , was 70,884,000. The ratio of families below

APPENDIX E E–7

U.S. Census Bureau
the poverty level to the total number of families would be

0.103 or 10.3 percent. Use the appropriate parameters

from Table E-3 and formulas (1) and (4) with r=0 to get

x y ratio

Estimate 7,324,000 70,884,000 0.103

a parameter +0.000102 -0.000012

b parameter 2,442 2,068 -

Standard error 153,000 294,000 0.002

90% conf. int. 7,073,000 to

7,575,000

70,401,000

to

71,367,000

0.099 to

0.107

Using formula (8) with r = 0, the estimate of the standard

error is

sx/y 5 7,324,000

70,884,000 Î[ 153,0007,324,000]

2

1 [ 294,000

70,884,000]

2

5 0.002

The 90-percent confidence interval is calculated as 0.103

± 1.645 x 0.002.

E–8 APPENDIX E

U.S. Census Bureau
Appendix F.

Data Quality: Current Population Survey

The quality of income data derived from surveys is

affected by two main sources of error: sampling error and

nonsampling error. Sampling error is fairly easily quantified and is discussed in Appendix E. Nonsampling error,

which is addressed in this section, can have many

sources, such as:

1. Failure of the sample frame to include all units for

which the survey was intended to represent.

2. Failure to contact all sample units.

3. Poor quality of responses.

4. Missing data problems.

Most of the analysis of nonsampling error is made at

the aggregate level since the kind of data needed to make

those types of analysis are more readily available.

Over the years, evaluations of the quality of the March

CPS income estimates have revealed downward biases

when survey estimates are compared to independent estimates derived from administrative sources. Deriving independent estimates for the purpose of evaluating the quality of survey data can be difficult and results in some

uncertainties. The survey and administrative sources use

different definitions, cover different universes, and are

based on different concepts. Therefore, adjustments to the

administrative sources must be attempted. These adjustments attempt to remove income that is received by the

institutional population, deceased people, and people not

living the United States. Also, the adjustments should

remove any components of income that are received as

in-kind payments or benefits and remove lump-sum or

one-time payments or withdrawls.

In spite of the uncertainties regarding the development

of independent estimates, it is important to attempt to

monitor the quality of survey data using these sources. An

evaluation of March 1997 CPS income data follows.

Table F1 presents income aggregates for 17 different

income sources. Five of those sources are well reported in

the March CPS with their aggregate incomes exceeding 90

percent of benchmark estimates: wages and salary, social

security, supplemental security income, veterans’ payments, and private pensions. The reporting of these

income sources has remained about the same or improved

over time (see Table F2). The reporting for three other

income sources has shown a steady trend of improved

reporting though they are not at the same high levels relative to benchmarks. Property income, both interest and

dividends, improved from the low to mid 50 percent levels

in 1984 to over 70 percent in 1996. Unemployment compensation showed a moderate improvement with aggregate income, relative to benchmarks, going from 75 percent to 83 percent. In total, these eight sources of income

with improved reporting accounted for roughly 90 percent

of all the income collected in the CPS in 1996.

The reporting for the remaining income sources has not

fared so well. CPS aggregate income estimates have

declined, relative to benchmarks, steadily over time for

the remaining income sources with the exception of workers’ compensation. The reporting of workers’ compensation is up from its 1984 levels, though down slightly from

1990. Some of the declines for the other income sources

are relatively minor as in the case of Federal employee

pensions where the percent went down only a few points

(from 85 percent to 81 percent). Others, however, are

more severe, such as military retirement (dropping nearly

40 percentage points) and rents and royalties (dropping

35 percentage points). Though it is not encouraging to see

a drop in the reporting of any income source, the sources

showing a decline in their aggregate income, relative to

benchmarks, are minor and accounted for only 7 percent

of all CPS income in 1996.1

This section does not report on nonsampling error for

noncash items, such as food stamps, that are used in this

report. Nevertheless, it is important to note that many of

the elements of the poverty estimates presented in this

report suffer from underreporting, as we have shown in

Appendix C. Each element is subject to underreporting

problems to differing degrees. In contrast, the imputation

for medical out-of-pocket expenses is controlled to a

benchmark which is not underreported. Corrections for

these underreporting problems would result in different

estimates of the prevalence of poverty and, therefore, this

is an additional subject for research.

1

The remaining 3 percent of aggregate CPS income in 1996 is

from sources where we do not have independent benchmarks at

this time.

APPENDIX F F–1

U.S. Census Bureau
Table F1. CPS Aggregates as a Percent of

Benchmark: 1996

Benchmark

(preliminary)Aggregate

(millions) 1996

Wages and salary . . . . . . . . . . . . . . . 3,585,238 3,668,060 102.3

Self-employment ................ 471,624 239,367 50.8

Interest. . . . . . . . . . . . . . . . . . . . . . . . . 198,784 156,114 78.5

Dividends....................... 108,186 76,658 70.9

Rents and royalties . . . . . . . . . . . . . . 75,332 44,515 59.1

Social security .................. 323,274 298,819 92.4

Railroad retirement . . . . . . . . . . . . . . 7,660 3,405 44.5

Supplemental security income. . . . . 27,270 22,261 81.6

Aid to families with dependent

children . . . . . . . . . . . . . . . . . . . . . . . 21,574 13,368 62.0

Other cash welfare . . . . . . . . . . . . . . 3,375 2,720 80.6

Unemployment compensation . . . . . 21,163 17,624 83.3

Worker compensation . . . . . . . . . . . . 16,704 12,954 77.6

Veterans payments . . . . . . . . . . . . . . 18,318 15,854 86.5

Private pensions. . . . . . . . . . . . . . . . . 99,421 106,993 107.6

Federal employee pensions. . . . . . . 38,715 31,111 80.4

Military retirement . . . . . . . . . . . . . . . 28,201 16,388 58.1

State and local employee

pensions . . . . . . . . . . . . . . . . . . . . . . 65,835 37,649 57.2

Total (where benchmark exists) . . . 5,110,676 4,763,857 93.2

Source: Preliminary Census Bureau tabulations of March 1997 CPS

data.

Table F2. CPS Aggregates as a Percent of

Benchmark: 1984-1996

1984 1990 1996

Wages and salary . . . . . . . . . . . . . . . 97.3 97.0 102.3

Self-employment . . . . . . . . . . . . . . . . 70.2 66.8 50.8

Interest. . . . . . . . . . . . . . . . . . . . . . . . . 56.7 61.1 78.5

Dividends. . . . . . . . . . . . . . . . . . . . . . . 51.8 31.3 70.9

Rents and royalties . . . . . . . . . . . . . . 95.4 87.8 59.1

Social security . . . . . . . . . . . . . . . . . . 91.9 93.0 92.4

Railroad retirement . . . . . . . . . . . . . . 71.4 66.7 44.5

Supplemental security income. . . . . 84.8 89.0 81.6

Aid to families with dependent

children . . . . . . . . . . . . . . . . . . . . . . . 78.4 71.6 62.0

Other cash welfare .............. 120.0 86.2 80.6

Unemployment compensation . . . . . 74.8 80.2 83.3

Worker compensation . . . . . . . . . . . . 48.2 94.5 77.6

Veterans payments . . . . . . . . . . . . . . 59.7 77.5 86.5

Private pensions. . . . . . . . . . . . . . . . . 57.2 110.8 107.6

Federal employee pensions. . . . . . . 84.7 82.6 80.4

Military retirement . . . . . . . . . . . . . . . 98.1 89.2 58.1

State and local employee

pensions . . . . . . . . . . . . . . . . . . . . . . 71.7 80.1 57.2

Total (where benchmark exists) . . . 88.3 89.0 93.2

Source: Data for 1984 from Vaughan (1989), for 1990 from Coder

and Scoon-Rogers (1996), and for 1996 from preliminary Census

Bureau tabulations of March 1997 CPS data.

F–2 APPENDIX F

U.S. Census Bureau
Issue

Report Title

Experimental Poverty Measures Current Population Reports Consumer Income 1990 to 1997 P60-205