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IDENTIFYING THE POOR: POVERTY MEASUREMENT FOR THE U.S.

FROM 1996 TO 2005

by Thesia I. Garner*

Bureau of Labor Statistics

and

Kathleen S. Short

U.S. Census Bureau

The poverty measure presented compares spending needs to resources available to meet those needs.

The analysis is for the U.S.; however, lessons from other countries regarding desirable properties of a

poverty measure are considered. A primary focus is internal consistency between thresholds and

resources. This study is among the first for the U.S. to describe an internally consistent poverty

measure, drawing from recommendations of the U.S. National Academy of Sciences (NAS). Thresholds reflect spending needs as “outflows.” Resources measure “inflows” available to meet spending

needs. The U.S. Consumer Expenditure Survey is used for thresholds, and the Current Population

Survey is the basis for resources. Trends are reported with comparisons to the official and a relative

measure. An important finding is that increases in expenditures for shelter, captured in the NAS

thresholds, suggest a greater increase in the number of families not able to meet basic needs than is

reflected by official poverty statistics over this time period.

1. Introduction

Researchers and policymakers in countries around the world strive to develop

procedures and measures that best describe the economic well-being of individuals

and families both within and across countries. There is considerable agreement

that comparably defined relative measures are most relevant for cross-national

comparisons (e.g., Smeeding, 2005; OECD, 2008). However, broader measures

across countries have also been developed. For example, addressing the need for

Note: We thank two anonymous referees and the ROIW editors for their comments and suggestions. Earlier versions of this research were presented during the following: Conference on Consumption, Income, and the Well-being of Families and Children, May 4–5, 2006 in Washington, DC; 2005

Joint Statistical Meetings (JSM) in Minneapolis, Minnesota; and Bureau of Labor Statistics seminars.

The comments of conference discussants, Gary Burtless and Timothy Smeeding, are appreciated.

Ralph Bradley, Rob McClelland, and Uri Kogan in the Bureau of Labor Statistics Division of Price

and Index Number Research, and David Johnson and Charles Nelson in the Housing and Household

Economics Statistics Division from the U.S. Census Bureau also provided useful comments. Appreciation is also extended to Rob Cage, Patrick Falwell, and Mary Lynn Schmidt who provided assistance with the U.S. Consumer Price Index (CPI), and Laura Paszkiewicz, who provided assistance with

the U.S. Consumer Expenditure Interview Survey. All comments greatly improved this research. The

views expressed in this research, including those related to statistical, methodological, technical, or

operational issues, are solely those of the authors and do not necessarily reflect the official positions or

policies of the U.S. Census Bureau or U.S. Bureau of Labor Statistics, or the views of other staff

members within these agencies. The authors accept responsibility for all errors.

*Correspondence to: Thesia I. Garner, Senior Research Economist, Division of Price and Index

Number Research, Bureau of Labor Statistics, U.S. Department of Labor, Washington, DC 20212,

USA (garner.thesia@bls.gov).

Review of Income and Wealth

Series 56, Number 2, June 2010

© 2010 The Authors

Journal compilation © 2010 International Association for Research in Income and Wealth Published

by Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main St, Malden,

MA, 02148, USA.

237
comparability across member countries of the European Union, Atkinson et al.

(2002) developed a set of recommendations for the measurement of social inclusion. The result was a three-tier system of measures, beginning with a measure of

the risk of financial poverty. For this measure, household income would be used to

construct a relative poverty measure set at a percentage of median disposable

income. Also included in the recommendations for the European Union was a vast

array of social indicators, such as non-monetary indicators of deprivation, and

indicators of sufficient housing, health, and education in three levels of indicators

of social inclusion.

The development and use of poverty indicators that are meaningful within

countries has been the focus of recent debates in several countries, for example, in

Australia, Canada, India, the United Kingdom, and the United States. There is no

official measure of poverty for Australia; however, the most commonly used

measures of poverty are the Henderson Poverty Lines (HPLs). Since the inception

of the HPLs in the early 1970s, there has been widespread debate on the appropriateness of these for Australian society, with alternatives proposed and evaluated (McDonald, 1997; Daniels, 2002; Saunders, 2004b). Also in Canada there is

no official measure of poverty; however, both absolute and relative measures have

been used unofficially (Statistics Canada, 1998, 2004, 2006; HRSD-Canada, 2006;

Osberg, 2007). The debate in India has been about which of two definitions of

consumption expenditure poverty results in a better or truer picture of poverty for

that country (see Deaton and Kozel, 2005). In the U.K., there seems to be agreement that the main income poverty indicator should be defined in terms of thresholds which rise or fall as average U.K. incomes rise or fall, a relative poverty

measure, but with a caveat that the use of fixed thresholds combined with relative

ones can help to provide a fuller picture of what is happening to the extent of

income poverty (Palmer et al., 2008). Notten and De Neubourg (2007) make the

case that both absolute and relative poverty should be monitored to determine

incidence and benefit adequacy within countries.

Like other countries debating the most appropriate measure to assess the

poverty status of its population, the U.S., too, has considered alternatives to the

current official measure. Issues of relevance and updating have also been discussed. The current official measure of poverty is now considered to be an absolute

measure and was designed in the 1960s as part of the War on Poverty. Many

people over the years have argued that the official U.S. poverty measure is outdated, given the changes in U.S. society and in government policies (see Ruggles,

1990; Citro and Michael, 1995; Fisher, 1996; Blank, 2008).

In the first half of the 1990s, an extensive evaluation of the current official

measure was conducted by the National Academy of Sciences (NAS) Panel on

Poverty and Family Assistance, under the auspices of the Committee on National

Statistics (CNSTAT). The results of the Panel’s work and recommendations are

presented in the report, Measuring Poverty, A New Approach (Citro and Michael,

1995). In the report, the Panel considered several alternatives to the official

measure: relative versus absolute poverty measures, expert-based budgets, subjective measures, and indexes of deprivation. In the end, this group of experts recommended an approach that a hybrid of the budget and relative approaches be

used for official poverty measurement in the United States. In contrast to the

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current U.S. official thresholds, updated only by price changes each year, the Panel

noted that the poverty threshold be updated in a “. . . conservative or quasirelative manner—one that drives the thresholds by changes in spending on necessities . . .” (p. 143). Properties deemed desirable for a new U.S. poverty measure

include: consistency between thresholds and resources in construction, statistical

defensibility, understandability, broad acceptance by the public, and operational

feasibility (Citro and Michael, 1995, p. 4).

This paper presents a poverty measure that is based largely on the NAS

Panel’s recommendations, with deviations reflecting more recent research. Particular emphasis is on internal consistency between the thresholds and resources. The

Panel noted that “It is important that family resources are defined consistently

with the threshold concept in any poverty measure” (Citro and Michael, 1995,

p. 9). Blank (2008) more recently addressed the issue of consistency in recommending that a poverty definition should be used that produces both a credible and

coherent poverty threshold and a consistent and appropriate resource measure.

The aim of the study is to produce an internally consistent poverty measure

that is based on spending “outflows” and money “inflows.” Spending outflows, or

outlays,1,2 are those for basic needs only: food, clothing, shelter, utilities (FCSU),

medical expenses, and other basic necessary goods and services. Resources include

money income from all sources plus the value of near-money benefits that help the

family meet spending needs, less necessary expenses, like work-related expenses

and taxes that must be paid. A family is designated as poor if its annual money

inflow, including relevant near-cash benefits and net of necessary expenses, falls

below the threshold level of money outflow. A difference in the threshold definition

used here and the one used by the Panel is that mortgage principal repayments and

medical care expenditures are included; neither was included in thresholds by the

Panel. The Panel did not include repayments on mortgage principal for “processing convenience” (see discussion below). Rather than subtract medical care expenditures from resources, as done in the 1995 report, these are added to thresholds.3

Not until the work of Garner (2006) and Short (2006) was an internally

consistent NAS-based poverty measure produced. The current research represents

a culmination of this and other related work (e.g., Johnson et al., 1997; Garner

et al., 1998; Short et al., 1998, 1999; Iceland et al., 2001; Short, 2001). In the latter

studies in particular, the researchers aimed to account for the concerns of the

research and policy communities regarding the desirable properties of a poverty

measure (CNSTAT, 2005; Iceland, 2005).

The paper begins with a brief overview of the current official measure, followed by a description of the spending-based threshold and the elements that make

up the resource side of the experimental poverty measure proposed in this research.

Data from the U.S. Consumer Expenditure Survey (CE) are used to produce the

1

For the BLS definition of expenditure outlays, see Rogers and Gray (1994).

2

Throughout this study, spending, expenditures, and outlays are used interchangeably. The

implicit cash value of food stamps is included in out-of-pocket spending for food. The cash values of

other in-kind programs are not included. 3

The original recommendation of the NAS Panel was that medical out-of-pocket expenses would

be subtracted from income as a necessary expense. For earlier research with medical care included in the

thresholds, see Short (2001), Short and Garner (2002), and Banthin (2004).

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threshold. The primary data source for the resource measure is the U.S. Current

Population Survey Annual Social and Economic supplement (CPS). Results for

1996 through 2005 are presented. The NAS-based thresholds are compared to the

current official thresholds and to relative thresholds based on one-half median

resources. The thresholds are examined with regard to underlying concepts and

changes over time. Poverty rates are calculated that compare the measure presented here with the current official measure and a comparable relative poverty

measure to illustrate differences in trends. Poverty rates are presented for the total

population and for specific subgroups of the population that have historically been

most susceptible to hardship in the U.S.

2. The Current Official Poverty Measure and Concerns

The current official measure was developed in the early 1960s as an indicator

of the number of people with inadequate income to cover the costs of a minimum

food diet and to allow for other needed expenses (see Orshansky, 1965; Citro and

Michael, 1995). The official thresholds are based on the share of food spending in

after-tax money income using data from the 1955 Household Food Consumption

Survey, and a food adequacy standard, the U.S. Department of Agriculture

(USDA) Economy Food Plan. Food was found to be one-third of a family budget,

and thus, food costs were multiplied by three. The food plan was issued by the

USDA for “temporary or emergency use when funds are low” (Orshansky, 1965,

p. 20). The food plan did not allow for meals eaten out or other food eaten away

from home, and it was assumed that “the homemaker is a good manager and has

the time and skill to shop wisely, and she must prepare nutritious, palatable meals

on a budget” for herself and her family (Orshansky, 1965, p. 24).

Since the first official thresholds were released, they have been updated for

changes in prices, holding the multiplier constant at three and the food adequacy

standard constant as the Economy Food Plan. In 1969, the Bureau of the Budget

gave “official” status to the following change in the poverty thresholds: to use the

overall Consumer Price Index to update the thresholds for price changes instead of

changes in the value of the Economy Food Plan that had been used earlier. Office

of Management and Budget Policy Directive No. 14 (OMB, 1978) specifically

states that “The official poverty thresholds do not vary geographically, but they

are updated for inflation using [the] Consumer Price Index (CPI-U).”4

The measure of income used in the official poverty measure is before-tax

money income, although the threshold is based on the share of after-tax income

available for food spending. Non-cash benefits (such as food stamps) are not

included in before-tax money income, nor are capital gains or losses. If a person

4

The CPI-U represents the change in prices of a fixed market basket of goods and services, with

relative prices changing while utility remains constant. In addition to regular changes in the CPI market

basket, other changes have been made in the production of the index over the years (see BLS, 2009 for

references). The updating mechanism for the official poverty measure is based on the relative change in

prices of goods and services purchased by an average consumer unit using plutocratic, not democratic,

weights (see Eatwell et al., 1987, pp. 774–5). The official thresholds are never revised for earlier periods

so improvements in the CPI are only reflected when new methods are incorporated in the official index.

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lives with family members, the family members’ incomes are added together and

compared to thresholds that reflect this person’s family size and composition.

Concerns have been raised regarding the use of the current official poverty

measure to describe the economic situation of individuals and families in need.

Such concerns include: (1) the appropriateness of using before-tax income for

official poverty measurement when thresholds are based on after-tax income and

resulting measurement inconsistencies; and (2) out-of-date thresholds (e.g., Citro

and Michael, 1995; Hill and Michael, 2001).

3. Concepts, Methods, and Data

The basic concepts, methods, and data for this study are based on those

proposed by the National Academy of Sciences (NAS) Panel on Poverty and

Family Assistance in their report, Measuring Poverty, A New Approach (Citro and

Michael, 1995). However, since the report was completed, additional work has

been conducted to further explore issues originally raised by the Panel. Findings

and conclusions from this additional work are reflected in the thresholds and

resource measures produced here. For example, in the CNSTAT Workshop in

2004 it was agreed that medical care be accounted for in the thresholds rather than

in resources (Iceland, 2005; see also, Short, 2001; Banthin, 2004). Another primary

difference from earlier work is that mortgage principal repayments are included in

outlays.5 The National Academy of Sciences Panel recommended that the unit of

analysis should be broadened for purposes of measuring poverty to include cohabiting couples (Citro and Michael, 1995, p. 13). Internationally, the unit of analysis

is the household. Short et al. (1999) compared different units of analysis and

showed that the more inclusive the unit the lower the resulting poverty rates. For

comparison to the official measure, the traditional definition of family is employed

here.

3.1. NAS-Based Poverty Thresholds

Poverty is most often defined in terms of one’s ability to meet his/her basic or

minimum needs for survival or participation in society. For this study, expenditures

for a prescribed set of goods and services are used to construct a spending-based

poverty threshold for a reference family. Equivalence scales are then applied to this

initial threshold to derive thresholds for other family types. A crucial part of this

measure is that thresholds are automatically updated over time by the growth in

5

The Panel used the CE publication definitions of food, clothing, shelter, and utilities, as did the

Census Bureau reports on experimental poverty measures (Short et al., 1999; Short, 2001). For this

study, the authors refined the definition to reflect the spending outflows of reference families. Shelter

expenditures include mortgage principal repayments of owners. Such payments are not included in the

CE publication definition of expenditures because the BLS considers these allocations to savings.

However, mortgage principal repayments are not discretionary, and cannot be used to meet other basic

needs of the family. Other differences from the Panel calculations include: expenditures for home equity

loans and lines of credit are not included in the study threshold, nor is spending on utilities for vacation

homes or food and rent as pay. Differences from the Census Bureau experimental thresholds include

adjustments for premiums paid for Medicare Part B and for shelter expenditures of families who both

owned and rented during the reference period.

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spending for basic goods and services that pertain to a specific concept of poverty

rather than solely by price changes.6 Such a procedure allows for improvements in

societal levels of spending for a basic bundle of goods and services.

Producing the threshold has several steps. These include: (1) selecting a reference family; (2) identifying the goods and services to be included in the threshold;

(3) choosing an appropriate equivalence scale; (4) choosing an updating mechanism; and (5) adjusting for geographic differences across areas.

The reference family includes two related adults and children.7 This family

type falls near the center of the family size distribution rather than at one of the

extremes; and it accounts for a relatively large proportion of the population (Citro

and Michael, 1995). Using the data that underlie the 2005 thresholds for this study,

this type of family represents 8.6 percent of household types. Of families with

children, those with two adults and two children are the largest group; people in

these families account for approximately 14 percent of the U.S. population. Since

children have historically made up a large portion of the poverty population, it is

reasonable that the selected reference family would represent spending patterns for

families with children.

Once the reference family is chosen, median expenditures for a set of goods

and services are estimated. As noted earlier, this set includes food, clothing,

shelter, utilities, and medical care. The threshold is referred to as the “FCSUM”

threshold or “experimental” threshold. The thresholds are based on out-of-pocket

spending for:

• Food, at home and away from home

• Clothing

• Utilities (including telephone)

• Medical care

• For renters, shelter expenditures

• For homeowners, non-vacation shelter expenditures that include:

– mortgage interest payments

– repayments of mortgage principal

– mortgage prepayment penalties

– property taxes

– maintenance, repairs, insurance, and other related expenditures.

Percentages of median expenditures, based on their relationship to predetermined percentile values, drive the poverty thresholds. The Panel recommended a

percentage of median expenditures, rather than a percentile point or range of the

distribution, in order that changes that affect the distribution of expenditures

below the median can increase or decrease the poverty rate (Citro and Michael,

1995, p. 147). The Panel used 78 percent and 83 percent of the median. The 78th

and 83rd percentages correspond to the reference family’s expenditures at the 30th

and 35th percentiles of the distribution of the sum of FCSU expenditures. The

6

The Panel recommended that the thresholds be updated for real growth in the consumption of

basic goods and services (Citro and Michael, 1995, p. 103); the Panel used changes in consumer

spending for updating. 7

A related adult is either the spouse of the reference person or an adult who is related by blood or

other legal arrangement.

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Panel selected the 30th and 35th percentile range to represent the spending of

people at a particular level of basic spending needs. Identifying percentages of

median expenditures that related to the 30th to the 35th percentiles of the spending

distribution was a matter of expert judgment on the part of the Panel members. In

this study, the midpoint of the Panel recommended percentages is used to set the

value of the reference family threshold.

Once the percentages of median expenditures have been determined, multipliers are applied to add a small additional amount to allow for other needs. The

multipliers account for expenditures for personal care, non-work related transportation (estimated at one-half of total transportation expenditures), education, and

reading materials.8 Multipliers of 1.15 and 1.25 are applied; these are based on the

relationship between the sum of FCSU expenditures and expenditures for smaller

and larger other bundles of other needed goods and services (see Citro and

Michael, 1995).

The general formula for deriving the reference family threshold, using food,

clothing, shelter, utilities, and medical care is as follows:

Threshold s Z PM Z P Ms

P M medical

LL HH

medical

t = − ( )( ) ∗ ∗ + ∗∗ ( ) + ( )( ∗ 1

2

) + ∗ ( ) P M H

2

(1)

where:

smedical = medical share of the threshold value

ZL = multiplier representing a smaller basic needs bundle

ZH = multiplier representing a larger basic needs bundle

PL = lower percentage of median expenditures

PH = higher percentage of median expenditures

M = median expenditures for reference family.

An equivalence scale is applied to the reference family threshold to obtain

thresholds for families of other sizes and compositions. We use a threeparameter scale that allows for a different adjustment for single parents (see

Betson, 1996, 2004). The three-parameter scale has been used in several BLS

and Census Bureau studies (Johnson et al., 1997; Short et al., 1999; Short, 2001).

The three-parameter equivalence scale is applied to the non-medical part of the

threshold only. This is because the medical care needs of children are not

expected to be less than those of adults and because there are few inherent scale

economies in medical care spending with increasing family size. Medical risk

indexes are created to account for variations in family expenditures related to

these differences; the indexes are applied to the medical part of the threshold

only.9 The three-parameter scale is as follows:

8

See BLS (2007b, Glossary of Terms) for definitions of transportation, personal care, education,

and reading material expenditures. 9

The medical risk indexes are calculated, using CE data, as the ratio of median medical out-ofpocket expenditures for different groups compared to the median medical expenditures of the reference

family. See Short and Garner (2002) in which the medical risk indexes were based on Medical Expenditure Panel Survey data.

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Single individual scale = 1 00 . , (2a)

Childless couple scale = 1 41 . , (2b)

Multiple adults no children scale adults ( ) = ( )0 7. (2c)

Single adult with children scale adults firstchild

ot

= +∗ + (

∗

0 8

0 5

.

. herchildren)

0 7.

,

(2d)

All other families scale adults children = +∗ ( ) 0 5 0 7 . . . (2e)

The procedure to calculate the experimental thresholds is repeated each year

using the three most recent years of quarterly Interview CE data. Quarterly expenditures are updated to threshold-year dollars using the All Items All City Consumer Price Index (CPI-U). Next, the median of the distribution of the sum of

food, clothing, shelter, utilities, and medical care expenditures, in threshold-year

dollars, is calculated. By design, the resulting experimental thresholds are more

reflective of current needs than are the official thresholds.

The procedure for updating the thresholds is referred to as “quasi-relative.”

Under this procedure, the thresholds rise in real terms as the general standard of

living rises, unlike price-adjusted thresholds, but they do not rise as rapidly as total

(real) consumption or income. In other words, the income elasticity of such a

poverty line (see Fisher, 1996; Kilpatrick, 1973) is between zero and 1.0. The

income elasticity of the FCSUM threshold with respect to reference family median

resources was 0.66 over the 1996–2005 period when thresholds and resources are in

constant dollars. This means that the FCSUM threshold rose by 0.66 percent for

every 1.0 percent increase in the resources of the reference family during that

period. By comparison, the income elasticity of the official poverty line with

respect to before-tax money income is (by definition) zero; and, the income elasticity of the relative threshold based on reference family resources is one.

As a final step, the thresholds are adjusted for cost-of-living differences by

geographic areas within the U.S. The adjustments reflect only inter-area rent

differences by county within each state. The county-level rents are produced

annually by the U.S. Department of Housing and Urban Development to administer its program of rental subsidies. Inter-regional price indexes that adjust for a

larger market basket of goods are not currently available (see Short, 2001).

This study adds to the literature of expenditure-based poverty thresholds.

Other studies that focus on expenditure-based thresholds include, for example, the

work of Allegretto (2005), Bernstein et al. (2000), Bradshaw (1991, 1993; see also

Bradshaw et al., 1987), Braithwaite et al. (1999), Garner and Short (2003, 2004),

Gustafsson et al. (2004), HRSD–Canada (2006), Middleton (2000), Morissette

and Poulin (1991), Pearce (2005), Pradhan and Ravallion (2000), Renwick and

Bergmann (1993), and Saunders (2004a, 2004c). Spending- and/or budget-based

thresholds also have been developed and used in many countries, for example,

Australia, Britain, Canada, Czech Republic, Germany, Hong Kong, Hungary,

Ireland, Malaysia, the Netherlands, Norway, Poland, Sweden, the U.S. (Fisher,

2007) and India (see Deaton and Kozel, 2005; Sen and Himanshu, 2005).

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3.2. NAS-Based Family Resources

The next step in constructing the experimental poverty measure is to calculate

the resources that families possess to meet the needs specified in the thresholds.

The main theme in this section is that, while the selection of a poverty threshold is

a choice (see Ruggles, 1990), once that selection is made, the measure of resources

employed for comparison should be consistent (Citro and Michael, 1995).

When the U.S. official poverty measure was first adopted, the Current Population Survey (CPS) was identified as the source of the income data to be compared

to the poverty thresholds. When Orshansky was developing the poverty thresholds, the CPS was the only good source of nationally representative income data

and only before-tax money income was available (Fisher, 1997). Thus, from the

start, the resource measure has not been consistent with the official thresholds that

are based on spending relative to after-tax income. Orshansky was aware of the

inconsistency of applying after-tax thresholds to before-tax income data. According to Fisher (1997), Orshansky decided she had no other alternative; she reasoned

that the result would yield “a conservative underestimate” of poverty.10

Family resources are defined as the sum of money income from all sources

plus the value of near-money benefits that help the family meet spending needs, less

necessary expenses that must be paid. This alternative concept of family income

can be referred to as “discretionary income”—income that can be used to meet a

family’s basic needs (specifically for food, clothing, shelter, utilities, and medical

care, plus a little bit more) after subtracting necessary expenses such as taxes

and work-related expenses. This resource measure is similar to the net disposable

income (DPI) measure used by researchers conducting international comparisons

of poverty that are based on Luxembourg Income Study (LIS) data (e.g., Gornick

and Jäntti, 2009); the main difference is that only taxes are subtracted for the LIS

measure (LIS, 2009).

The criterion of consistency with the thresholds dictates that near-money

benefits included in the expenditure thresholds are included in resources. The only

near-cash benefits available in the CE data are for food stamps. Expenditures for

food are based on all food purchases, regardless of whether the payment was from

federal assistance or not. Given that thresholds include all food spending, it is

appropriate to include food stamps in the measure of resources. The decision to not

include the value of other government-benefit programs, for example, in-kind

school-based nutrition programs and housing subsidies11 and utilities assistance, in

resources is due to the fact that the thresholds are based on spending needs net of

subsidy receipt, not consumption needs. If the thresholds were to reflect consumption needs, the implicit value of such programs would be included in the thresholds

and resources.

Necessary expenses are subtracted from income to determine how much

discretionary income, or inflow, is available to purchase goods and services

10See Fisher (1997, footnote 57).

11Using CE Interview data from 2003 quarter two through 2006 quarter one, the data used to

estimate the 2005 threshold, approximately 1.8 percent of all reference families were renters living in

subsidized or government housing. Rozaklis and Garner (1999) reported that a threshold which

accounted for the consumption of subsidized or government rental housing would only be about $1.00

higher than a spending based threshold.

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represented by the threshold.12 Necessary expenses include taxes and expenses

related to work. Taxes are defined to include federal and state income taxes and all

payroll taxes paid. Earning a wage entails incurring expenses, such as travel to

work and the purchase of uniforms or tools as well as care provided for children

while parents are at work. These expenses are viewed as necessary and are paid by

families before expenditures are made on other goods and services. The remaining

discretionary income or resources represent the ability of the family to purchase,

on an annual basis, what they need to spend for basic goods and services, given

that they may already be receiving various non-cash benefits.

3.3. Data

This paper uses several surveys to construct the experimental poverty

measure. First, the Consumer Expenditure Survey (CE) quarterly Interview data,

collected from 1994 quarter two through 2006 quarter one (BLS, 2007a), are used

to construct thresholds for 1996 through 2005. Each quarterly data collection

refers to expenditures made during the three months prior to the interview month.

It is assumed that data from each reference quarter are independent of the data

from other quarters; this same assumption is made for official publications of CE

data and was also made by the Panel in their report. Quarterly expenditures are

annualized by multiplying them by four. Three years of quarterly data are used to

produce each annual reference family threshold.

Second, to measure family income or, as more broadly defined, family

resources, the analysis uses the Current Population Survey Annual Social and

Economic Supplement (CPS ASEC) for the income years 1996 to 2005 with data

collected in March each year from 1997 through 2006 (Census Bureau, 2007b). The

Panel recommended using the Survey of Income and Program Participation (SIPP)

to measure family resources, but found general agreement that the timeliness and

complexity of the survey were important shortcomings (CNSTAT, 2005). However,

information from the SIPP is used to value work-related expenses.

The calculation of resources for an experimental poverty measure starts with

current money income as defined and measured in the CPS ASEC; this income is

also used to calculate official poverty statistics. Current money income includes

cash income received on a regular basis, such as income from earnings, any cash

transfers, and property income. The reference period for money income is that

received in the previous calendar year by the family residing together as of

February, March, or April of the interview year. Before-tax income, regularly

received, does not include net realized capital gains, gifts, lump sum inheritances,

or insurance payments. The CPS collects no information on taxes paid, so a tax

calculator is employed. As part of the tax calculator, net realized capital gains are

simulated and added to income.

12One important necessary expense is child support paid to another household. The amount of

child support paid by one household to another is not collected in the CPS and is not used for official

income statistics by the Census Bureau; child support transfers are doubly counted in household

income and official poverty statistics.

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4. Results and Discussion

4.1. Thresholds

Experimental and official poverty thresholds for a family with two adults and

two children are shown in Figure 1. Spending-based thresholds are estimated using

out-of-pocket expenditures for food, clothing, shelter, utilities, and medical care;

these thresholds are referred to as FCSUM in the figure. To place the U.S.

experimental results in an international context, four-person relative thresholds are

also presented. Population-based relative thresholds are set at 50 percent of median

equivalized household resources; resources are equivalized using a single parameter

scale, the square root of family size. This scale implies that the needs of a household

composed of four people are twice as large as those of a single person household.

There is considerable agreement that the appropriate poverty measure for crossnational comparisons is a relative measure (for example, see Atkinson et al., 2002;

Smeeding, 2005; OECD, 2008). It is of interest to note the similarity between the

FCSUM and the relative thresholds. However, there are slight differences: from

1997 to 2001, relative thresholds are higher; after 2004 the opposite is true. Importantly, the official poverty thresholds are always lower than the other thresholds

presented (see Appendix Table A1 for levels, rates of change, and confidence

intervals). It should be noted that, while the FCSUM threshold is calculated as a

three-year moving average, the relative threshold is based on a single year. When a

moving-average relative threshold, based on resources, is produced using two years

of data, the differences between the relative and FCSUM threshold are even smaller

for the earlier part of the series (results not shown). This finding suggests a strong

relationship between spending and resources at the median, averaged over a

number of years, for the reference family. Also, one might conclude that a movingaverage relative threshold may better reflect the minimal level of resources required

to function normally within society than one based on single year data. (See Corak,

2006, for a discussion of these concepts.)

$0

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Relative

FCSUM

Official

Figure 1. Official, Relative, and Experimental Poverty Thresholds for the Reference Family1 in the

United States: 1996–2005

Note: 1 Official and experimental poverty thresholds are for 2-adult, 2-child families; relative

poverty thresholds are for 4-person families.

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To compare how the thresholds move relative to other household economic

series, income data from the Census Bureau (2007b) and expenditure data from the

Bureau of Labor Statistics (2007b) are examined. These data reveal that from 1996

to 2001, before-tax money income for all households increased more rapidly than

did total expenditures for all consumer units; however, after 2001, expenditures

rose more quickly. FCSUM thresholds increased at about the same rate as did

total expenditures. In contrast, relative thresholds moved more slowly than

income, expenditures, and FCSUM thresholds.

In order to understand better why the new thresholds differ in trends from the

official threshold, we examine assumptions regarding movements over time and by

examining what is included in the thresholds. FCSUM thresholds are based on

reference family spending over the three most recent years of expenditure data,

including the threshold year. The threshold for each year is based on a moving

average of the median sum of FCSUM expenditures over the 12 quarters of data.

Although quarterly expenditure data are price-adjusted to the threshold year using

the All Item CPI-U, movements in the experimental thresholds primarily reflect

changes in expenditures for food, clothing, shelter, utilities, and medical care.

By design, the experimental thresholds are comprised of basic necessities. In

contrast, the official threshold is based on the assumption that one-third of total

spending is allocated to food; the remainder is for all other goods and services.

However, changes in the official thresholds are affected by changes in the CPI-U

which are affected by changes in expenditure patterns over time and associated

price movements of all items for all consumers living in urban areas.13 CE expenditure data are used to produce expenditure shares for use in the production of the

CPI-U; weight-base periods are selected for index construction.14 For example,

1996 price indexes are based on expenditure shares of the average consumer unit

during the 1982–84 period; 2004 and 2005 price indexes are based on expenditure

shares during 2001–02 period.

The shares of the FCSUM threshold components over the 1996 to 2005 time

period were fairly constant, with food and shelter expenditures combined account13The CPI-U measures the average change in prices paid by urban consumers for a fixed market

basket of goods and services (see BLS, 2009). Unlike the thresholds, the CPI-U is based on the spending

and prices faced by consumers living in metropolitan statistical areas (MSAs) and urban places of 2500

inhabitants or more. Non-farm consumers living in rural areas within MSAs are also included. Military

consumer units living off base with 50 percent or more of their total family income coming from the

armed forces are not included in the CPI-U population. 14The CPI-U expenditures shares were produced for low level aggregations by Cage, Falwell, and

Schmidt (Cage et al., 2008), in the Division of Consumer Prices and Price Indexes at the BLS, using

internal CE data. These weights are identified as biennial weights, chapter 10, by this division. Two

years of CE (Diary and Interview combined) are used. For the CPI-U index years of 1996 and 1997,

the base weights are from 1982–84 CE data; expenditure groups are based on the 1987 CPI Item

Structure. For the 1998–2001 indexes, weights were based on 1993–95 data and the 1998 CPI Item

Structure. For the 2002–03 indexes, the weights were based on 1999–2000 data, also the 1998 structure. For the 2004–05 indexes, weights were based on data from 2001–02 and the 1998 item structure.

For the 1987 structure only, apparel services and sewing machines were included in apparel, and

telephone services, community antennae and cable television services were included in utilities; they

were not for the 1998 structure. Adult day care center expenditures were included in the 1998 item

structure but not in the 1987 structure. For the share tabulations, food did not include expenditures

for alcoholic beverages.

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ing for over 50 percent of the threshold;15 these account for about 45 percent of

CPI-U base expenditures during the same time period. Utilities account for about

13–14 percent of the thresholds but only 5 to 8 percent of the CPI-U defined

expenditures (depending upon whether telephone services were included or not).

The largest shares of expenditures in the CPI-U were for goods and services not

included in food, clothing, shelter, utilities, and medical care (around 39 percent).

Other goods and services account for about 16 percent of the FCSUM thresholds.

Movements in the FCSUM thresholds and in the official threshold reveal that

food prices, as measured by the CPI-U for food, and food expenditures in the

threshold increased at about the same rate, approximately 25 percent over the 1996

to 2005 time period. Prices and threshold expenditures for utilities and medical care

increased by about 40 to 42 percent. Clothing prices and threshold expenditures

decreased about 9 percent. The largest increase in implicit threshold expenditures is

for shelter (55.6 percent); the increase in shelter prices was only 31.2 percent.

A major difference in the experimental thresholds and the CPI-U, and consequently in movements of the official poverty thresholds, is related to the treatment of shelter. Recall that out-of-pocket shelter expenditures of the reference

family consist of such items as mortgage interest, mortgage principal repayments,

property taxes and insurance for homeowners, rent and tenants insurance for

renters, and maintenance and repairs for both. The CPI-U for shelter reflects

changes in space rents for primary residences of renters and owners along with

appropriate expenditure weights.16 The thresholds represent the spending patterns

of and prices faced by four-person families with two children, a group with a high

rate of homeownership while the CPI-U is based on the urban population with

lower rates of homeownership than the reference family population.

An examination of the CE data used in this study reveals that about 75

percent of reference families in 1996 owned their homes; an additional 5 percent

were homeowners by 2005. Of all reference family homeowners, 85 percent had

mortgages in 1996. Those with mortgages increased to 89 percent by 2005. For

owners with mortgages, median out-of-pocket expenditures for mortgage principal repayments and mortgage interest increased 45 percent over this time period.

Median property taxes increased 58 percent for all owners but 67 percent for those

with mortgages. Home market values rose approximately 80 percent for reference

family homeowners with and without mortgages from 1996 to 2005 (authors’ own

calculations using the CE data).

Examining expenditure and demographic data that underlie the CPI-U reveals

that approximately 60 percent of urban consumer units were owners for the 1996

15Following the Panel’s estimation procedure (see Citro and Michael, 1995, p. 198, footnote 14),

the shares of expenditures in the threshold reflect the expenditures for the threshold components at the

30th and 35th percentiles of the distribution of the sum of expenditures for food, clothing, shelter,

utilities, and medical care (FCSUM) for two adult-two child families. Average expenditures for each

component of the threshold are calculated using expenditures between the 27.5 and 32.5 percentiles and

the 32.5 and 37.5 percentiles (representing the 30th and 35th vingtiles) of the sum of FCSUM expenditures. These shares are converted to share fractions of the FCSUM thresholds using multipliers of

1.15 and 1.25. 16Reported rents for primary residences are adjusted by the BLS to omit the cost of utilities in

reported rents and thus are made comparable to owners’ reported rental equivalence. The change in

space rents for non-rent-controlled and non-subsidized or public rental housing is applied to owneroccupied housing in the same location as the rental units.

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index; for the 2005 index the rate increased to 64 percent. Shelter expenditures in the

CPI-U are based on rental equivalence only and thus mortgage information is not

relevant to the production of the CPI-U. For the 1996 index, owners’ equivalent

rents accounted for about 20 percent of total expenditures; this share increased to 23

percent by 2005 (authors’ own calculations using the CE data: BLS, 2007b).

These differences in shares and movements in shelter expenditures and prices

are consistent with our finding that the FCSUM thresholds increased more rapidly

over the 1996 to 2005 period than did the official poverty threshold, based on the

CPI-U. Such an outcome would result from a market where mortgaged home

prices are increasing at a faster rate than owners’ rents, a phenomenon that

occurred over the 1996 to 2005 period.

4.2. Family Resources

Changes in poverty thresholds would be expected to change trends in poverty

statistics over time. However, these statistics are also affected by changes in income

and other tax and transfer policies. Besides before-tax money income, changes in

food stamp benefits, taxes, and work-related expenses may change trends in

poverty rates. An examination of the elements in the family resource measure

sheds light on changes in overall family resources from 1996 to 2005.

Table 1 shows the aggregate dollar amounts added to or subtracted from

before-tax money income for the period 1996 to 2005 to calculate family resources

for the experimental poverty measure. Overall, these additions and subtractions

result in relatively large net subtractions from income. For example, in 1996,

additions of food stamps, net realized capital gains, and the earned income tax

credit (EITC) sum to total additions of $215.2 billion.17 For that same year,

subtractions of all taxes and work expenses totaled $1178 billion, five times as large

as additions to income. By 2005, subtractions totaled seven times additions to

income. Note that while aggregate income taxes fell in 2002 and 2003, payroll taxes

and work expenses continued to increase substantially across the period. Since over

time we are subtracting larger and larger amounts relative to additions, the experimental measures may result in higher poverty rates due in part to these calculations.

4.3. Experimental Poverty Rates

To determine poverty status, total family resources are compared to the

spending-needs thresholds. If the “inflow” to family resources is below the

“outflow” amount needed, then all individuals within the family are classified as

poor. Taking account of spending on basic goods and resources available to

families for spending provides information about families who, while not poor

using the official measure, may have difficulty meeting basic needs because necessary outflows exceed inflows.

Table 2 and Figure 2 show poverty rates, based on the official, relative, and

experimental poverty measure, for the years 1996 to 2005. The results show that

the official poverty rate fell from 1996 to 2000 (13.7 to 11.3 percent). After 2000,

17Note that a large part of additions to income are made up of net realized capital gains and that

these values vary depending on changes in imputation methodology at the Census Bureau.

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TABLE 1

Aggregate

Additions and Subtractions to

Family

Resources ($ billion) for the

Total Population: 1996 to 2005

Additions Subtractions

Year

Food

Stamps1

Net Capital

Gains2

Earned Income

Tax Credit3

Federal

Income Tax3

State

Income Tax3

Payroll

Taxes3

Work

Expenses4 Childcare4

1996 14.2 179.4 21.6 627.0 163.2 266.0 98.0 19.51997 12.3 239.6 21.7 703.0 180.4 285.0 102.0 21.01998 10.8 339.9 22.5 757.0 200.6 304.0 106.0 22.11999 9.6 457.7 23.5 858.0 224.6 328.0 106.0 18.52000 8.7 468.8 22.5 907.5 237.0 343.0 105.0 19.12001 9.7 483.8 23.7 923.0 248.7 357.0 120.0 19.82002 11.2 58.3 25.7 744.0 179.3 386.0 128.0 19.22003 12.9 78.0 26.1 745.0 188.4 396.0 128.0 19.12004 14.7 185.0 27.0 968.0 198.2 409.0 134.0 20.02005 16.2 179.8 29.3 864.0 207.8 431.0 152.0 22.2

Notes: 1Reported face value of food stamps received over the year in CPS ASEC.2Capital gains and losses are imputed to the CPS ASEC at the Census Bureau using the IRS Statistics of Income (SOI) file.3Tax figures are simulated based on reported income amounts and imputed capital gains and losses.4Work expenses and child care expenses while parents work are based on data collected in the CPS and the SIPP. A percentage of median expenses reported in

the SIPP are assigned to individuals and are computed based on the number of weeks worked reported in the CPS. After 1998 a question in the CPS regarding paymentfor childcare was used. Prior to that, whether or not families paid for childcare was modeled using SIPP data and applied to CPS families.

Source: Authors’ own calculations using the 1997–2006 CPS ASEC (Census Bureau, 2007a).

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the official rate begins to increase, reaching 12.7 percent by 2004 and remaining

stable at about the same rate in 2005. The experimental poverty measure displays

a similar pattern. Differences in trends are due to increases in the experimental

thresholds as well as increased payroll taxes and work expenses that families faced.

While the official rate is lower in 2005 than in 1996, the spending need-based rate

is highest in 2005. The increase in taxes and work expenses, and the experimental

thresholds after 2000, bring the experimental rate back to the 1996 level and

beyond, to 17.7 percent by 2005.

The relative threshold and resource measure result in an average poverty rate

of 17.3 percent for the period. From 1996 to 2005, poverty rates using the relative

measure range from a low of 16.7 percent in 2005 to a high of 17.7 percent in 1999.

Recent estimates of relative poverty (e.g., Smeeding, 2005; OECD, 2008) reveal

higher relative poverty rates for the United States than for many other countries.

Using a disposable income poverty measure, Smeeding (2005) reported a poverty

rate for the U.S. population to be about 17 percent in 2000. The OECD published

relative poverty rates for 2004, ranging from a low of 5 percent for Denmark and

TABLE 2

Official and Experimental Population Poverty Rates Using

Income-Based Resources: 1996–2005

Year Official Experimental Relative

1996 13.7 17.1 17.5

1997 13.3 16.2 17.4

1998 12.7 15.8 17.7

1999 11.9 15.2 17.7

2000 11.3 15.3 17.2

2001 11.7 16.1 17.1

2002 12.1 17.1 17.1

2003 12.5 17.0 17.3

2004 12.7 17.2 17.0

2005 12.6 17.7 16.7

Source: Authors’ own calculations using the 1997–2006 CPS

ASEC (Census Bureau, 2007a) and thresholds based on CE Interview

data (BLS, 2007a).

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Relative

Experimental

Official

Figure 2. Official, Relative, and Experimental Poverty Rates for the U.S. Population: 1996–2005

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Sweden to a high of 18 percent for Mexico and Turkey, followed by the U.S. at 17

percent for 2005. For these two cross-country studies, resources were countryspecific household disposable income with taxes subtracted and cash and nearcash transfers added to money income; work-related expenses were not subtracted

from income.

Figure 2 shows the differences in trends in poverty rates over this time period

for the three poverty measures. While the experimental poverty rates are more like

the relative measure in terms of level, there is a tendency to follow the trends

apparent in the official poverty measure, falling in the first half of the period, and

then increasing to 2005. Unlike the relative measure, the official poverty rates fall

and then rise with the recession that occurred between March and November of

2001, as do the rates based on the experimental measure.

Finally, in Table 3 we focus specifically on official and experimental poverty

rates for demographic groups. These groups are identified in terms of age and race.

Children and families identified as black are of particular interest as these groups

have had historically high poverty rates. For both groups, poverty rates based on

the official and experimental measures are lower in 2005 than in 1996. Among the

groups considered, poverty is highest among blacks over this time period regardless of the measure used. Official child poverty rates are also high. The child

poverty rate, based on the experimental measure, is higher than the elderly rate in

1996; however, by 2005, elderly poverty surpasses child poverty by 0.4 percentage

points. Poverty rates for children and blacks are lowest from 1999 to 2001 for both

poverty measures, while official poverty is lowest for the elderly in 1999 and

experimental poverty is lowest in 1997 to 1999.

5. Summary and Conclusions

The new poverty measure in this study follows recommendations presented

in the report, Measuring Poverty: A New Approach (Citro and Michael, 1995)

TABLE 3

Official and Experimental Poverty Rates for Specific Demographic Groups: 1996 to 2005

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Children

Official 20.5 19.9 18.9 17.1 16.1 16.3 16.7 17.6 17.8 17.6

Experimental 22.8 21.8 21.2 19.8 19.6 19.9 21.1 20.7 20.5 21.1

Non-elderly adults

Official 11.4 10.9 10.5 10.1 9.4 10.1 10.6 10.8 11.3 11.1

Experimental 14.4 13.7 13.3 13.1 12.8 13.9 14.8 14.8 15.3 15.5

Elderly

Official 10.8 10.5 10.5 9.7 10.2 10.1 10.5 10.3 9.8 10.2

Experimental 18.0 16.6 16.4 16.4 18.5 19.2 20.9 20.8 20.2 21.5

White

Official 11.2 11.0 10.5 9.8 9.4 9.9 10.2 10.5 10.8 10.6

Experimental 14.3 13.8 13.3 13.1 13.2 14.0 15.0 14.8 15.0 15.2

Black

Official 28.4 26.5 26.1 23.6 22.0 22.7 23.9 24.3 24.8 24.9

Experimental 32.8 30.1 30.3 27.5 26.8 28.0 29.7 29.5 30.1 31.9

Source: Authors’ own calculations using the 1997–2006 CPS ASEC (Census Bureau, 2007a) and

thresholds based on CE Interview data (BLS, 2007a).

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and subsequent research. Using the same methods over time, poverty rates were

produced that reflect the spending-need outflows and income inflows of families

in the United States. Poverty rates based on the experimental measure were compared to rates based on the official measure and a relative measure for 1996

through 2005. This is among the first studies to produce a NAS-based poverty

measure for the U.S. that emphasizes the consistency property deemed desirable

for poverty measurement.

The experimental thresholds reflect recent spending levels and patterns, and

changes in living standards over time, unlike the official poverty thresholds.

Reflecting increased spending needs of families for basic goods and services from

1996 to 2005, the FCSUM thresholds rose more rapidly than the official poverty

thresholds and the CPI-U, the updating mechanism for the official measure.

Differences in the experimental threshold and CPI-U were highlighted to provide

insight regarding why the official and experimental thresholds move differently.

One of the more pronounced findings was that the largest shares of expenditures

that are accounted for in the CPI-U are for goods and services that are not

included in the basic needs bundle. Thus, the U.S. official poverty threshold is

influenced more by expenditures for and prices of goods and services that primarily do not include food, clothing, shelter, utilities, and medical care. Another

striking result is that implicit shelter expenditures in the thresholds rose almost

twice as fast as the shelter expenditures underlying the CPI-U. This difference is

due to the treatment of owner-occupied shelter. Reference family spending for

property taxes, mortgage interest, and mortgage principal repayments increased

more rapidly than rents of homeowners in the CPI-U from 1996 to 2005. Relative

thresholds were shown to be very similar in level to the experimental FCSUM

thresholds, both higher than the official thresholds.

The resource measure was constructed to represent the ability of families to

meet the needs implicit in the FCSUM threshold. Income inflows, net of taxes and

work-related expenses, were compared to spending need- or outflow-based thresholds. Unlike in the Measuring Poverty report, the only government near-cash

benefits included in resources was for food assistance. The cash value of government

food stamps was included in resources as purchases using food stamps were

included in food expenditures in the threshold measure. All other spending in the

thresholds is reported net of subsidy or transfer receipt; thus any in-kind subsidies

or transfers for shelter, food, utilities, clothing, and medical care are already

accounted for in the spending measure. The receipt of a subsidy or transfer means

that the family has lower spending needs; and subsequently lower resource needs.

The experimental poverty measure, calculated over the ten-year period,

showed trends and levels of poverty that differed from the official measure for the

overall population and for specific demographic groups. An important finding of

this work is that increases in the amount needed to pay for basic goods and

services, particularly increased shelter expenditures, resulted in a greater increase

in the number of families not able to meet basic needs than is reflected by the

official poverty statistics.

A relative measure of poverty was shown to be more like the experimental

measure in terms of levels, but it did not follow the same trends as the experimental

or official measures. These latter two measures reflected changes in economic

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conditions over the period, falling from 1996 to 2000 and then increasing afterwards, reflecting the recession of 2001. In terms of poverty rates, official poverty

was lowest over this period, followed by the rates based on the experimental

measure. Relative resource poverty was comparable to that reported in international comparisons for the 2000s.

The poverty measure produced for this study reflects assumptions, which like

other poverty measures, involve subjective judgment. For example, expert judgment guided the selection of food, clothing, shelter, utilities, and medical care as

the basis of the threshold. Identifying percentages of median expenditures that

related to the 30th to the 35th percentiles of the spending distribution was also a

matter of judgment. A goal of this study was to produce a poverty measure based

on an inflows and outflows concept as one option in the production of an internally consistent poverty measure. When relative measures of poverty are used,

consistency is implicit in the design; however, when other types of measures are

used, researchers need to pay particular attention to consistency. Otherwise,

poverty could be reduced by simply adding the value of in-kind transfers of goods

and services to resources without accounting for the benefit in the thresholds, and

thereby biasing downward poverty rates and gaps.

Our constant guides, while producing and describing the measure presented in

this research, were the properties that the Panel deemed desirable for a revised

poverty measure for the U.S.: consistency in the construction of thresholds and

resources; statistical defensibility; understandability; broad acceptance by the

public; and operational feasibility. In producing outflows-based thresholds and

inflows-based resources, and explaining the procedures that underlie these, we

hope to have produced a measure that has these important properties.

Appendix

TABLE A1

Official, Relative,

1 and NAS-Based2 Poverty Thresholds for the Reference Family:

1996–2005

Year Official Relative FCUSM

Confidence Interval:

FCSUM

1996 $15,911 $18,034 $18,096 $17,428 $18,763

1997 $16,276 $18,894 $18,424 $17,912 $18,935

1998 $16,530 $20,060 $18,994 $18,465 $19,523

1999 $16,895 $20,934 $19,648 $19,149 $20,147

2000 $17,463 $21,722 $20,731 $20,169 $21,293

2001 $17,960 $22,174 $21,640 $21,140 $22,141

2002 $18,244 $22,370 $22,600 $22,076 $23,125

2003 $18,660 $22,964 $23,109 $22,578 $23,640

2004 $19,157 $23,314 $23,738 $23,167 $24,310

2005 $19,806 $23,742 $24,784 $24,300 $25,269

1996 to 2005 percentage change 24.5% 31.7% 37.0%

Notes: 1

Relative threshold is based on the median before-tax money income of adult equivalized income.

That median is multiplied by 2 to obtain the 4-person threshold. 2

Based on out-of-pocket expenditures (including repayment of mortgage principal for owned

housing).

Source: Census Bureau and authors’ own calculations using U.S. Consumer Expenditure Survey

data (BLS, 2007a).

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References

Allegretto, Sylvia, Basic Family Budgets: Working Families’ Incomes Often Fail to Meet Living Expenses

Around the U.S., Briefing Paper #165, Economic Policy Institute, Washington, DC (http://

www.epi.org/content.cfm/bp165), September 2005.

Atkinson, Tony, Bea Cantillon, Eric Marlier, and Brian Nolan, Social Indicators: The EU and Social

Inclusion, Oxford University Press, New York, 2002.

Banthin, Jessica, “Where Do We Stand in Measuring Medical Care Needs for Poverty Definitions?”

(http://www7.nationalacademies.org/cnstat/Workshop_on_Experimental_Poverty_Measures.

html), August 2004.

Bernstein, Jared, Chauna Brocht, and Maggie Spade-Aguilar, How Much Is Enough? Basic Family

Budgets for Working Families, Economic Policy Institute, Washington, DC, 2000.

Betson, David, “Is Everything Relative? The Role of Equivalence Scales in Poverty Measurement,”

University of Notre Dame, UNPUBLISHED Manuscript, 1996.

———, “Poverty Equivalence Scales: Adjustment for Demographic Differences Across Families,”

Committee on National Statistics, National Academy of Sciences, Workshop to Assess the

Current Status of Actions Taken in Response to “Measuring Poverty: A New Approach,”

2004.

Blank, Rebecca M., “How to Improve Poverty Measurement in the United States,” Journal of Policy

Analysis and Management, 27(2), 233–54, 2008.

Bradshaw, Jonathan, “Rescuing Budget Standards from the Scrapheap of History,” The New Review

[of the Low Pay Unit], No. 12, 6–8, 1991.

——— (ed.), Budget Standards for the United Kingdom, Avebury, Aldershot, 1993.

Bradshaw, Jonathan, Deborah Mitchell, and Jane Morgan, “Evaluating Adequacy: The Potential of

Budget Standards,” Journal of Social Policy, 16(Part 2), 165–81, 1987.

Braithwaite, Jeanine, Christiaan Grootaert, and Branko Milanovic, Poverty and Social Assistance in

Transition Countries, St Martin’s Press, New York, 1999.

BLS (Bureau of Labor Statistics), Consumer Expenditure Interview Survey Internal Data, Washington,

DC, 2007a.

———, http://stats.bls.gov/cex/home.htm, 2007b.

———, http://stats.bls.gov/cpi/cpifaq.htm, 2009.

Cage, Robert, Patrick Falwell, and Mary Lynn Schmidt, BLS, U.S. Department of Labor, personal

communications regarding the CPI and expenditure weights, 2008.

Census Bureau, Current Population Survey Annual Social and Economic Supplement (CPS ASEC)

internal data for the income years from 1996 to 2005 with data collected in 1997 through 2006, 2007a.

———, http://www.census.gov/hhes/www/income/income.htm, 2007b.

Citro, Constance F. and Robert T. Michael (eds), Measuring Poverty: A New Approach, National

Academy Press, Washington, DC, 1995.

CNSTAT (Committee on National Statistics), Planning Group for the Workshop to Assess the Current

Status of Actions Taken in Response to “Measuring Poverty: A New Approach,” John Iceland,

Rapporteur, Experimental Poverty Measures: Summary of a Workshop, National Academies

Press, Washington, DC, 2005.

Corak, Miles, “Principles and Practicalities for Measuring Child Poverty,” International Social Security

Review, 59(2), 3–35, 2006.

Daniels, Dale, “The Poor in Australia: Who Are They and How Many Are There?” Analysis and

Policy, Social Policy Group, Parliamentary Library, Parliament of Australia (http://

www.aph.gov.au/library/INTGUIDES/SP/poverty.htm), 2002.

Deaton, Angus and Valerie Kozel, “Data and Dogma: The Great Indian Poverty Debate,” World Bank

Research Observer, 20(2), 177–99, 2005.

Eatwell, John, Murray Milgate, and Peter Newman (eds), The New Palgrave: A Dictionary of Economics, Volume 2, E to J (New Palgrave), Macmillan, London and Basingstoke, 774–5, 1987.

Fisher, Gordon, “Relative or Absolute—A New Light on the Behavior of Poverty Lines Over Time,”

Newsletter of the Government Statistics, Section and the Social Statistics Section of the American

Statistical Association, 10–12, 1996.

———, “The Development of the Orshansky Poverty Thresholds and Their Subsequent History

as the Official U.S. Poverty Measure” (http://www.census.gov/hhes/www/povmeas/papers/

orshansky.html), 1992, revised 1997.

———, “An Overview of Recent Work on Standard Budgets in the United States and Other Anglophone Countries” (http://aspe.hhs.gov/POVERTY/papers/std-budgets/report.pdf), 2007.

Garner, Thesia I., “Developing Poverty Thresholds,” 2005 Proceedings of the American Statistical

Association, Social Statistics Section [CD-ROM], American Statistical Association, Alexandria,

VA, 2006.

Review of Income and Wealth, Series 56, Number 2, June 2010

© 2010 The Authors

Journal compilation © International Association for Research in Income and Wealth 2010

256
Garner, Thesia I. and Kathleen S. Short, “Personal Assessments of Minimum Income and Expenses:

What Do They Tell Us about ‘Minimum Living’ Thresholds and Equivalence Scales?” in

John A. Bishop and Yoram Amiel (eds), Inequality, Welfare and Poverty: Theory and Measurement, Vol. 9 of the Series Research on Economic Inequality, Elsevier Science, Oxford, 191–243,

2003.

———, “Economic Well-Being Based on Income, Consumer Expenditures and Personal Assessments

of Minimum Needs,” in John A. Bishop and Yoram Amiel (eds), Studies on Economic Well-being:

Essays in the Honor of John P. Formby, Vol. 12 of the Series Research on Economic Inequality,

Elsevier Science, Oxford, 319–61, 2004.

Garner, Thesia I., Stephanie Shipp, Geoffrey Paulin, Kathleen S. Short, and Charles Nelson, “Poverty

Measurement in the 1990s,” Monthly Labor Review, 121(3), 39–68, 1998.

Gornick, Janet and Markus Jäntti, “Child Poverty in Upper-Income Countries: Lessons from the

Luxembourg Income Study,” Luxembourg Income Study Working Paper No. 509 (http://

www.lisproject.org/publications/liswps/509.pdf), 2009.

Gustafsson, Björn, Li Shi, and Hiroshi Sato, “Can a Subjective Poverty Line Be Applied to China?

Assessing Poverty Among Urban Residents,” Journal of International Development, 16(8), 1089–

107, 2004.

Hill, Carolyn J. and Robert T. Michael, “Measuring Poverty in the NLSY97,” The Journal of Human

Resources, Special Issue on Early Results from the National Longitudinal Survey of Youth, 1997

Cohort, 36(4), 727–61, 2001.

HRSD–Canada (Human Resources and Social Development Canada), Low Income in Canada: 2000–

2002 Using the Market Basket Measure (www.hrsdc.gc.ca/en/cs/sp/sdc/pkrf/publications/research/

2002-000662/page00.shtml), June 2006.

Iceland, John, “The CNSTAT Workshop on Experimental Poverty Measures, June 2004,” Focus,

23(3), 26–30, 2005.

Iceland, John, Kathleen Short, Thesia Garner, and David Johnson, “Are Children Worse Off? Evaluating Well-Being Using the New (and Improved) Measure of Poverty,” Journal of Human

Resources, 36(2), 398–412, 2001.

Johnson, David, Stephanie Shipp, and Thesia I. Garner, “Developing Poverty Thresholds Using

Expenditure Data,” 1997 Proceedings of the American Statistical Association, Government and

Social Statistics Section, Anaheim, California, American Statistical Association, Alexandria, VA,

28–37, 1997.

Kilpatrick, Robert W., “The Income Elasticity of the Poverty Line,” Review of Economics and Statistics, 55(3), 327–32, 1973.

LIS (Luxembourg Income Study), Information on LIS Data Sets, LIS Variable Definition List

(http://www.lisproject.org/techdoc/variable.xls), 2009.

McDonald, Maureen K., “Poverty Measurement and Poverty Statistics in Australia,” paper presented

at the Seminar on Poverty Statistics, Santiago, May 7–9 (http://www.ibge.gov.br/poverty/pdf/

australia1.pdf), 1997.

Middleton, Sue, “Agreeing Poverty Lines: The Development of Consensual Budget Standards

Methodology,” in Jonathan Bradshaw and Roy Sainsbury (eds), Researching Poverty, Ashgate,

Aldershot, 59–76, 2000.

Morissette, R. and Susan Poulin, Income Satisfaction Supplement: Summary of Four Survey Years, Staff

Reports, Labour and Household Surveys Analysis Division, Statistics Canada, Ottawa, Canada,

1991.

Notten, Geranda and Chris de Neubourg, The Policy Relevance of Absolute and Relative Poverty

Headcounts: What’s in a Number? Maastricht Graduate School of Governance, MRPA Paper No.

4668, August 2007.

OECD (Organization for Economic Co-operation and Development), Growing Unequal? Income Distribution and Poverty in OECD Countries, October 2008.

OMB (Office of Management and Budget), Statistical Policy Directive No. 14, Definition of Poverty for

Statistical Purposes, May 1978.

Orshansky, Mollie, “Counting the Poor: Another Look at the Poverty Profile,” Social Security Bulletin,

28(1), 3–29, 1965.

Osberg, Lars, “The Evolution of Poverty Measurement—with Special Reference to Canada,” Unpublished Manuscript, available from the author at osberg@dal.ca, 2007.

Palmer, Guy, Tom MacInnes, and Peter Kenway, Monitoring Poverty and Social Exclusion 2008,

Joseph Rowntree Foundation, York, December 2008.

Pearce, Diana, The Self-Sufficiency Standard for the Washington, D.C. Metropolitan Area 2005, prepared for the Wider Opportunities for Women, in conjunction with Wider Opportunities

for Women’s Family Economic Self-Sufficiency Project (http://www.sixstrategies.org/states/

states.cfm), 2005.

Review of Income and Wealth, Series 56, Number 2, June 2010

© 2010 The Authors

Journal compilation © International Association for Research in Income and Wealth 2010

257
Pradhan, Menno and Martin Ravallion, “Measuring Poverty Using Qualitative Perceptions of Consumption Adequacy,” The Review of Economics and Statistics, 82(3), 462–71, 2000.

Renwick, Trudi J. and Barbara R. Bergmann, “A Budget-Based Definition of Poverty with an Application to Single-Parent Families,” Journal of Human Resources, 28(1), 1–24, 1993.

Rogers, John M. and Maureen B. Gray, “CE Data: Quintiles of Income vs. Quintiles of Outlays,”

Monthly Labor Review, 117(2), 32–7, 1994.

Rozaklis, Patricia and Thesia I. Garner, “Subsidized Renters: Thresholds,” presentation at the Bureau

of Labor Statistics, May 5, 1999.

Ruggles, Patricia, Drawing the Line: Alternative Poverty Measures and Their Implications for Public

Policy, The Urban Institute Press, Washington, DC, 1990.

Saunders, Peter, “Budget Standards Alive and Well!” Social Policy Research Centre Newsletter, 87,

(http://www.sprc.unsw.edu.au/nl/NL87.pdf), 2004a.

———, “Towards a Credible Poverty Framework: From Income Poverty to Deprivation,” SPRC

Discussion Paper No. 131 (http://www.sprc.unsw.edu.au/dp/DP131.pdf), January 2004b.

———, “Updated Budget Standard Estimates for Australian Working Families in September 2003,”

SPRC Report 1/04, Sydney, New South Wales, Australia, Social Policy Research Centre, University of New South Wales (www.sprc.unsw.edu.au/reports/ACTU_BS.pdf), February 2004c.

Sen, Abhijit and Himanshu, “Poverty and Inequality in India: Getting Closer to the Truth,” in Angus

Deaton and Valerie Kozel (eds), The Great Indian Poverty Debate, Macmillan India, 2005.

Short, Kathleen, Experimental Poverty Measures: 1999, U.S. Census Bureau, Current Population

Reports, Consumer Income, P60-216, U.S. Government Printing Office, Washington, DC, 2001.

———, “Estimating Resources for Poverty Measurement: 1993–2003,” 2005 Proceedings of the American Statistical Association, Social Statistics Section [CD-ROM], American Statistical Association,

Alexandria, VA, 2006.

Short, Kathleen and Thesia I. Garner, “Experimental Poverty Measures: Accounting for Medical

Expenditures,” Monthly Labor Review, 125(8), 3–13, 2002.

Short, Kathleen, Martina Shea, David Johnson, and Thesia Garner, “Poverty-Measurement Research

Using the Consumer Expenditure Survey and the Survey of Income and Program,” American

Economic Review, 88(2), 352–6, 1998.

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.

Smeeding, Timothy, “Causes and Conditions of Social Vulnerability in Comparative Perspective:

Asian Evidence from the LIS Dataset,” Luxembourg Income Study Working Paper Series,

No. 417, August 2005.

Statistics Canada, Low Income Measures (LIMs) 1996, Household Surveys Division, 1998.

———, Low Income Cutoffs from 1994 to 2003 and Low Income Measures from 1992 to 2001, Income

Research Paper Series, Income Statistics Division, 2004.

———, Low Income Cut-offs for 2005 and Low Income Measures for 2004, Income Research Paper

Series, Income Statistics Division, 2006.

Review of Income and Wealth, Series 56, Number 2, June 2010

© 2010 The Authors

Journal compilation © International Association for Research in Income and Wealth 2010

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