BLS WORKING PAPERS

U.S. DEPARTMENT OF LABOR

Bureau of Labor Statistics

 

OFFICE OF PRICES AND LIVING

CONDITIONS

Experimental Poverty Measures Under Alternate Treatments of Medical Out-of-Pocket

Expenditures: An Application of the Consumer Expenditure Survey

Kathleen Short, U.S. Census Bureau

Thesia I. Garner, U.S. Bureau of Labor Statistics

Working Paper 358

May 2002

 

All views expressed in this paper are those of the authors and do not reflect the views or policies of their respective

agencies or the views of other staff therein.
1

Experimental Poverty Measures

Under Alternate Treatments of Medical Out-of-Pocket Expenditures:

An Application of the Consumer Expenditure Survey1

Kathleen Short and Thesia I. Garner

February 27, 2002

For additional information contact:

 

1

 We thank Jessica Banthin, Richard Bavier, David Betson, David Johnson, and Barbara Wolfe for their

input into our research. This paper reports the results of research and analysis undertaken by BLS and

Census Bureau staff. This study is to inform interested parties of research and to encourage discussion. All

views expressed in this paper are those of the authors and do not reflect the views or policies of their

respective agencies or the views of other staff therein. The authors accept responsibility for all errors.

Kathleen Short

Senior Research Economist

HHES Division, Room 1065

U.S. Census Bureau

Washington, D.C. 20233-8500

301-763-8921

kshort@census.gov

Thesia I. Garner

Senior Research Economist

Division of Price and Index Number

Research

Bureau of Labor Statistics (BLS)

U.S. Department of Labor

Postal Square Building, Room 3105

2 Mass. Ave., N.E.

Washington, D.C. 20212

202-691-6576

garner_t@BLS.gov
2

Abstract

This paper presents experimental poverty measures that update those presented

in Current Population Report, P60-216, “Experimental Poverty Measures: 1999”.

Estimates for 2000 are presented and compared with the official measure. In this

paper we emphasize the difference in two of the measures that use Consumer

Expenditure (CE) data to estimate medical out-of-pocket expenses. Poverty

rates, poverty gaps, and income-to-poverty-threshold ratios are computed and

compared across poverty measures for various subgroups, particularly children

and the aged. Results show that alternate methods of measuring medical

expenses affect our perception of the relative incidence of poverty, the depth of

poverty experienced by these groups, and the number of people who are

classified in extreme poverty (those with family income below one-half of the

poverty threshold).

Background

The official measure of poverty in the United States has been in place

since the 1960s and has served to inform many policy debates. However, this

measure itself is often the focus of criticism from scholars and policy makers

alike. In her book, Drawing the Line2

, Patricia Ruggles described alternative

concepts of poverty and methods for measuring poverty; she also proposed

methods to update and revise the current official poverty threshold and resource

definitions. In response to this work, the Joint Economic Committee held

Congressional hearings in the early 1990s. These hearings lead to the formation

of the National Academy of Sciences (NAS) Panel on Poverty and Family
3

Assistance. The goal of the panel was to examine the current official measure of

poverty in the United States. In 1995 this panel of scholars published their

findings in a report titled Measuring Poverty: A New Approach3

.

In general, the NAS panel report proposed eight broad sets of

recommendations which focus on the following: (1) adopting a new poverty

measure; (2) setting and updating the poverty threshold; (3) adjusting the

threshold; (4) defining family resources; (5) identifying needed data; (6)

highlighting other issues related to poverty measurement; (7) relating poverty

measurement to assistance programs; and (8) linking states’ needs to the panel’s

proposed measure. The panel stated that poverty thresholds should represent a

budget for food, clothing, shelter (including utilities) and a small amount for other

needs. Family resources would be defined – consistent with the threshold

concept – as the sum of money income together with the value of near money

benefits minus expenses that cannot be used to buy goods and services in the

threshold budget. The panel also stated that,

The U.S. Office of Management and Budget should adopt a revised

poverty measure as the official measure for use by the federal

government. Appropriate agencies, including the Bureau of the Census

and the Bureau of Labor Statistics, should collaborate to produce the new

thresholds each year and to implement the revised definition of family

resources.4

The basic criteria for developing the poverty measure, according to this NAS

panel, were that it should be understandable and broadly acceptable to the

public, statistically defensible, internally consistent, and operationally feasible.

 2

 Ruggles, 1990.

3

 Citro and Michael, 1995 4

 Citro and Michael, p. 5.
4

In response to the panel’s report and recommendations, research was

undertaken by staff within the Bureau of Labor Statistics (BLS) and the Census

Bureau. Their work has resulted in several papers and conference presentations

that reproduced the panel’s work and examined underlying assumptions and

measurement issues.5

Building on this joint research, the Census Bureau released two reports

that presented several variations of alternative methods of measuring who is

poor based on the recommendations of the NAS panel – July 1999 with results

for the years 1990-97 (Short et al., 1999) and October 2001 with results from

1999 (Short, 2001a). The second Census Bureau report included improved

methods for measuring individual elements of experimental measures and further

refined the concepts outlined in the NAS panel report. In particular, the second

report examined two new methods for handling medical out-of-pocket expenses

(MOOP): accounting for them in experimental thresholds, or subtracting these

expenses from family resources. The treatment of medical out-of-pocket

expenses in a poverty measure proved most controversial in the discussion that

followed the release of both the panel’s and the Census Bureau’s first reports6

.

Since medical spending is the focus of continuing debate over poverty

measurement, this study utilizes the same experimental poverty measure as the

second Census report, but presents results for the year 2000.7

 These measures

and resulting poverty rates are contrasted with the current official poverty

 

5

 Early work includes Johnson, Shipp, Garner, 1997 and Garner et al., 1998. These and other working

papers are available on census poverty measurement website

http://www.census.gov/www/hhes/povmeas.htm. 6 See for example, “Open Letter on Revising the Official Measure of Poverty”, 2000.
5

measure. The official poverty measure indicated that 11.3 percent of all people

had income below the official poverty threshold in 2000. The experimental

measures result in slightly higher rates overall and indicate differences by sociodemographic subgroups.

Medical out-of-pocket spending (MOOP)

Medical out-of-pocket expenditures include those for health insurance

premiums, medical services, drugs, and medical supplies. The method that the

NAS panel used to value these expenses in a poverty measure using survey

data 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 was adjusted to

match benchmarks developed from the Health Care Financing Administration’s

National Health Accounts.8

 The adjusted amounts of MOOP were then

subtracted from income as a necessary expense, before comparing family

resources to poverty thresholds. Note that this step introduced some

inconsistency in a complete poverty measure in that no other component in the

panel’s measure was adjusted to match independent aggregate estimates. That

is, while other elements in the panel’s proposed poverty measure suffer from

non-sampling error, such as the underreporting of income or benefits, they are

nevertheless unadjusted in the poverty measures reported here, as they are in

the official measure. This inconsistent treatment likely resulted in an

 7 See Short, 2001a, for details of methods.

8 See Betson, 1995b.
6

overstatement of the effect of MOOP on poverty rates in the panel’s report and

the first Census Bureau report that mimicked the panel’s approach.

In light of both the conceptual and practical issues raised by this

approach, an alternative was proposed to add out-of-pocket needs to the

thresholds and not to subtract MOOP from income.9

 Thus, the threshold would

include medical out-of-pocket spending along with spending on the commodity

bundle of food, clothing, shelter, and utilities. Thresholds could be calculated for

family types based on health care spending patterns according to size of family,

age of family members, and health insurance coverage status.

The NAS panel did not pursue this alternative because it would require a

much larger number of thresholds to reflect different levels of medical care

need.10 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

expenditure to incorporate medical care needs in the thresholds may

overestimate the costs for many families and underestimate the cost for a few

families due to the distributional properties of these expenditures. 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.”

The second Census Bureau report (Short 2001a) presented two new

methods of accounting for medical needs. The first was an updated model

 

9 See Bavier, 1998, and a summary of Marilyn Moon’s proposal in Citro and Michael, p. 236.

10 Citro and Michael, 1995, pp. 223-237.
7

following the panel’s procedure. This method used the 1996 and 1997 Consumer

Expenditure Survey (CE) to assign values of MOOP to different families11. This

version of the MOOP model differs in some important ways from the earlier NAS

model. These differences were summarized by Betson in a series of

recommendations that are made to guide the estimation of this model. The first

recommendation is that the MOOP amounts predicted by the model should not

be calibrated to aggregate totals, as was done in the earlier version. A third order

log-logistic model was estimated for each of 42 different family types, based on

characteristics such as age, health insurance coverage, family size, race, and

income level. Limits were placed on the maximum MOOP amount that could be

assigned. No family was assigned a value that exceeds the 99th percentile of the

MOOP distribution for their respective family type. Estimates from this model

were then used to assign values of MOOP to individual families in the CPS.

These amounts were estimated for each family and subtracted from family

income before determining poverty status, in the measure referred to as MSI --

MOOP subtracted from income. The elements of this approach are outlined

below.

The MSI measure. The MSI measure is conceptually similar to the

measure described in the NAS panel’s report but with some computational

differences. More generally, this measure is constructed in the following way:

Thresholds:

• Thresholds are based on expenditures on food, clothing, shelter and utilities –

data from 1998, 1999, and 2000 CE12

• The equivalence scale is a three-parameter version13

 

11 See Betson, 2001 for complete details. 12 Garner et al., 1998.
8

• Geographic indexes are calculated using the Department of Housing and

Urban Development (HUD) Fair Market Rents14

Resources:

• Use cash income from the March 2001 Current Population Survey (CPS)

• Include the value of food assistance programs (food stamps and school

lunches)

• Include the value of housing subsidies

• Include the value of energy assistance (only heating assistance)

• Subtract work-related and child care expenses

• Take account of taxes as modeled in the CPS

• Subtract medical out-of-pocket expenses (MOOP) as modeled using CE data.

The threshold for a two-adult two-child reference family is presented in Table 1.

This experimental threshold is slightly higher than the official threshold for this

family type.

Table 1: Poverty Thresholds for a Reference Family of Two Adults and Two 

Children: 2000

Official Measure $17,463

Experimental without medical 17,884

Experimental with medical 19,549

Source: Authors’ calculations of CE data 1998, 1999, and 2000

MOOP in the threshold (MIT measure). The second measure examined in

this study computes MOOP differently. This method adds health care out-ofpocket expenditures, as reported in the CE, in the calculation of poverty

thresholds for the two-adult two-child reference family. Thus, the thresholds,

which typically are based on spending for food, clothing, shelter and utilities, now

also include out-of-pocket spending for an additional commodity, health care.

 13 Johnson et al., 1997.
9

Once the reference family threshold is estimated from CE data, thresholds

for families other than the reference family are produced using what we refer to

as a ‘medical risk index’. These are based on characteristics associated with

variations in medical care utilization and cost. These characteristics include

among others, family size, age, and health status of member, and health

insurance coverage. In the case of the uninsured, an adjustment is made to

reflect the likely underutilization of health care by the uninsured15. These indexes

use median MOOP expenditures from the 1996 Medical Expenditure Panel

Survey (MEPS) to compute ratios of MOOP expenditures for different groups

varied by the set of characteristics listed to those of the reference family. MEPS

data are used since health status data are not collected in the CE.16 This method

is referred to as MIT or MOOP in the threshold. Again, unlike the panel’s original

method, no attempt was made to adjust these dollar amounts to aggregate

spending totals. Once MOOP amounts were calculated, they were included in the

thresholds, rather than subtracted from income, before determining poverty

status. Generally, the MIT measure is calculated as follows;

Thresholds:

• Thresholds are based on estimated expenditures for food, clothing, shelter

and utilities, and MOOP from 1998, 1999, and 2000 CE

• The equivalence scale is a three-parameter version and a medical risk index

for the MOOP portion of the threshold as estimated from 1996 MEPS

• Geographic indexes are calculated using HUD Fair Market Rents

Resources:

• Cash income from the March 2001 CPS

• Include the value of food assistance programs (food stamps and school

lunches)

 14 Short, 2001b.

15 See Banthin et al., 2001 for more details on this method.

16 Other options using the CE are presented in Banthin et al. 2001.
10

• Include the value of housing subsidies

• Include the value of energy assistance (only heating assistance)

• Subtract work-related and child care expenses

• Take account of taxes as modeled in the CPS

The threshold for this measure is also shown in Table 1, with the official poverty

threshold and experimental threshold without medical expenses. As expected,

the threshold that includes MOOP is higher than that without.

Mean values of MOOP assigned by the two different methods are shown

in an appendix table for different family types. While the two methods assign

different amounts to different families, the key difference between the two

methods is that MSI models health expenditures (MOOP) based on individual

family characteristics, while MIT fixes the level for all families with certain specific

characteristics.

Finally, we note that the second Census Bureau report included a third

method. This approach to valuing medical expenses combined the two

approaches described above into a single measure. This combined approach

included the addition of a MOOP value in the thresholds but also subtracted a net

MOOP amount from family income. The discussion here focuses only on the two

separately estimated methods in order to establish more clearly the differences in

the two methods.

Experimental poverty rates

Poverty rates based on these measures are presented in Table 2 along

with the official poverty rate. The estimated poverty rate using the MSI measure

was 12.2 percent in 2000. The MIT measure yields a poverty rate of 12.7
11

percent. While both of the new experimental measures result in similar poverty

rates for all people that are slightly higher than the official rates, including MOOP

in a poverty measure and the method by which that is done have important

effects on the poverty rates of different population subgroups.

Table 2: Poverty Estimates for All People Using Official and Experimental

Poverty Measures 2000

Number (1,000) Percent

Official Measure 31,054 11.3

MSI 33,739 12.2

MIT 34,960 12.7

Source: March 2001 Current Population Survey

Demographic subgroups. Using the poverty measures described above, this

section examines the differential incidence of poverty for various socio-economic

and demographic subgroups. Table 3 shows poverty rates under the official and

the two experimental poverty measures for various demographic groups.

Poverty rates by age group show higher rates for adults using the

experimental measures, especially for the elderly (see Figure 1). Child poverty

rates, 16.1 percent under the official measure, are about the same under the MIT

measure, 15.9 percent, but considerably lower under the MSI measure, 14.6

percent. The non-elderly adult poverty rate increases modestly from 9.4 with the

official measure to 10.4 under the MSI measure and 11.0 percent with the MIT

measure. The poverty rate for people 65 years and over is higher, 10.2 under the

official measure, compared with 14.2 and 16.6 percent under the MIT and the

MSI measures respectively.
12

Differences in poverty rates between the official and the experimental

measures are explained by all of the elements included in an experimental

measure. Average family amounts added and subtracted from income to move

from the official to the experimental measures are shown in Figure 2 for selected

subgroups. In that figure one sees the higher average benefits received,

including tax credits (EITC), and the lower MOOP amounts for children relative to

the elderly. The combination of these results in increased poverty rates for the

elderly using the experimental measures relative to the official measure.

Table 3. Poverty Rates by Selected Characteristics, 2000

Official Measure MSI MIT

All Persons 11.3 12.2 12.7

Age

 Children (<18) 16.1 14.6 15.9

 Adults, 18-64 9.4 10.4 11.0

 Elderly, 65+ 10.2 16.6 14.2

Race/Ethnicity

 Non-Hispanic White 7.5 8.5 8.6

 Black 22.0 20.6 21.3

 Hispanic 21.2 24.2 26.3

Family Type

 Married-couple 5.6 6.9 7.2

 Male-headed (no spouse present) 14.8 17.3 17.6

 Female-headed (no spouse present) 25.7 25.1 25.8

Number of workers

 No workers 33.2 35.4 33.8

 One or more workers 8.0 8.7 9.5

Region

 Northeast 10.3 12.9 13.2

 Midwest 9.5 9.0 9.3

 South 12.5 12.2 12.5

 West 11.9 14.9 15.8

Metropolitan Area

 Central city 16.1 17.6 18.4

 In metro, not central city 7.8 9.8 10.2

 Nonmetropolitan area 13.4 10.8 10.8

Source: March 2001 Current Population Survey
13

Figure 2: Mean Transfer Benefits and Expenses 

-$10,000

-$8,000

-$6,000

-$4,000

-$2,000

$0

$2,000

$4,000

Foodstamps

Housing

School Lunch

Heating

Federal Income Tax

FICA Tax

EITC

Work Expenses

Child Care

MOOP (MSI)

MOOP (MIT)

Note: EIT C is Earned Income T ax Credit

Source: T able 4

Children

Elderly

Figure 1: Poverty Rates by Age

16.1

9.4

10.2

14.6

10.4

16.6

15.9

11.0

14.2

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

 Children (<18) Adults, 18-64 Elderly, 65+

Source: March 2001 CPS

Official

MSI

MIT
14

Differences in poverty rates between the two experimental measures are

only explained by different treatments of MOOP. While average values for MOOP

are lower for most subgroups that we examine under the MIT method, this

method likely errs by assigning the same values to all in a given group. This

results in the imputation of too large a value to too many families, and too small a

value to the few families who actually face large MOOP expenses.

Experimental poverty rates also differ by race and ethnicity. Experimental

poverty rates are higher than official poverty rates for Non-Hispanic Whites and

Hispanics, though slightly lower for Blacks. The rates tend to be lower for Blacks

due to a combination of factors, including higher receipt of some near-cash

transfers and slightly lower work-related expenses and taxes paid. Differences in

average amounts of these elements are shown in Table 4 by race and Hispanic

origin.

Accounting for non-cash transfers also affects the incidence of poverty by

family type. When poverty rates by family type are examined, one sees increases

moving from the official to the experimental measures among persons in marriedcouple and male-householder (unmarried) families, and little change among

female-householder families. Married-couples tend to receive less near-cash

transfer income and have higher work-related and medical expenses than the

other family types (see Table 4 for average amounts).

As expected, the experimental measures (which include geographic

adjustments) result in poverty rates that differ by region and by metropolitan/nonmetropolitan status. As highlighted by the change in the poverty rates between
15

Table 4: Mean Family Amounts across Individuals, 2000 (dollars)

All Official Poor Near Poor Children Adults Elderly White Black Hispanic No

Workers

1+

Workers

Foodstamps 117 750 248 252 76 33 83 314 231 264 95Housing 142 978 346 270 93 116 85 473 293 460 94School Lunch 103 322 256 229 68 9 87 190 254 65 109Heating 6 28 25 10 5 6 5 11 5 15 5Federal Income Tax -9,075 -20 -101 -9,159 -10,031 -3,936 -9,711 -4,496 -3,887 -1,144 -10,271FICA Tax -3,475 -438 -979 -3,807 -3,827 -931 -3,611 -2,379 -2,770 0 -4,000EITC 319 1,147 1,257 624 245 41 276 559 795 0 368Work Expenses -1,230 -460 -771 -1,312 -1,361 -374 1,242 -1,096 -1,364 0 -1,416Child Care -377 -162 -305 -746 -292 -8 -367 -468 -429 0 -434MOOP (MSI)a -1,762 -551 -753 -1,563 -1,643 -2,818 -1,824 -1,419 -1,281 -1,987 -1,729MOOP (MIT)b 1,323 851 1,102 1,256 1,210 2,053 1,340 1,201 1,203 1,443 1304

Married

Couple

Female

Householder

Northeast Midwest South West Central

City

Suburbs Non-metro

Territory

Foodstamps 62 309 117 92 120 136 198 64 138Housing 48 439 239 98 100 171 287 82 88School Lunch 98 154 89 86 106 126 135 81 115Heating 4 14 11 9 3 4 8 4 10Federal Income Tax -11,933 -2,621 -10,651 8,709 -8,414 -9,151 -7,647 -11,235 -5,254FICA Tax -4,333 -1,607 -3,736 3,668 -3,184 -3,513 -3,002 -3,985 -2,787EITC 238 627 284 252 337 389 410 263 335Work Expenses -1,455 -787 -1,240 -1,281 -1,184 -1,242 -1,155 -1,299 -1,154Child Care -415 -369 -434 -346 -352 -398 -372 -410 -292MOOP (MSI)a -2,042 -1,313 -1,883 -1,824 -1,715 -1,674 -1,533 -1,894 -1,753MOOP (MIT)b 1,476 1,090 1,345 1,341 1,318 1,293 1,235 1,365 1,341aAverage out-of-pocket expenditure subtracted from resources. bAverage out-of-pocket expenditures included in threshold.c People classified as “near poor” are those with family income below 125 percent of the poverty threshold.

Source: March 2001 Current Population Survey
16

the official and the experimental measures, poverty estimates increase in the

Northeast and West and decrease in the Midwest and South. Likewise, measures

that include geographic adjustments (as the MSI and MIT do) yield higher poverty

rates in central cities, and to a less extent in the suburbs, while lower poverty rates

result for nonmetropolitan areas.

Poverty gaps

The previous section reports the prevalence of poverty under different poverty

measures. While the poverty rate tells us the proportion of a population that is poor,

it does not give us information about the depth of poverty in that population. The

mean income deficit, or average poverty gap, tells us something about the shortfall

of income relative to the poverty threshold, and thus the depth of poverty for various

people.

Table 5 lists mean income deficits, or poverty gaps, under the official

measure and under the two experimental measures, the MSI and the MIT measures.

These income deficits are calculated by determining who is poor under the given

measure, and for those individuals, subtracting their family income from their

relevant poverty threshold. When incomes are negative, the deficit is set equal to the

poverty threshold, suggesting that no deficit exceeds the measure of need for the

basic bundle of goods.

In official Census Bureau publications, income deficits are calculated

separately for families and for unrelated individuals. The first two lines of Table 5

show these calculations for these two groups under the three measures. The third

line combines family heads and individuals for simplicity, and the remaining
17

averages for subgroups are based on this combined group, by characteristic of the

family head or the unrelated individual (in effect, unrelated individuals are treated

like families consisting of one person). Also see Figure 3.

Table 5: Mean Income Deficits: 2000 (dollars)

Official MSI MIT

Families $6,821 $4,333 $4,787

Unrelated Individuals 4,388 3,731 3,869

Families and Unrelated Individuals 5,414 4,013 4,296

Age of head

 18 to 64 5,986 4,249 4,831

 65+ 2,868 3,173 2,573

White 5,248 3,931 4,184

Black 5,773 4,078 4,438

Hispanic origin 6,258 4,847 5,366

No workers 5,486 4,701 4,701

One or more workers 5,335 3,434 3,951

In family of type:

 Married couple 6,612 4,153 4,578

 Male householder 4,968 4,129 4,445

 Female householder 5,243 3,889 4,091

Geographic regions:

 Northeast 5,344 4,286 4,607

 Midwest 5,398 3,666 3,843

 South 5,214 3,718 3,929

 West 5,841 4,459 4,893

Metropolitan Area:

 Central city 5,588 4,292 4,638

 Not central city 5,496 4,150 4,470

Nonmetropolitan Area 4,972 3,113 3,176

Source: March 2001 Current Population Survey

While the prevalence of poverty may be higher under the experimental

measures relative to the official measure, this table indicates that average poverty

gaps are much lower for both experimental measures than the official measure. This

result holds for all groups shown here, except one (discussed
18

below). While the differences between the income deficits are larger or smaller for

different groups, in general, the family incomes of poor individuals are closer to the

poverty line under the experimental measures than under the official measure. Thus,

while subtracting taxes and other necessary expenses from income does move

people across the poverty line and into poverty, on average, they are not being

moved as far below that line as they would be below the office threshold. Also,

including noncash benefits raises the income of many poor families, even if they are

not sufficient to raise them out of poverty.

Figure 3: Mean Income Deficits 2000

6,821

4,388

5,414

4,333

3,731

4,013

4,787

3,869

4,296

$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

Primary Families Unrelated Individuals Families and UI’s

Official

MSI

MIT
19

There is one exception -- the elderly. As shown in Table 5, the elderly

demonstrate higher mean income deficits under the MSI experimental measure

relative to the official measure. While the large MOOP expenses attributed to the

elderly contribute greatly to these higher figures, there is an additional factor that

explains this difference. The official poverty thresholds are specified to be lower for

the elderly than for the non-elderly, while the experimental poverty thresholds make

no distinction for age of householder. On the other hand, due to the lower values of

MOOP assigned using the MIT measure, the poverty gap for the elderly under that

measure is lower than the official measure gap.

Income-to-poverty-threshold ratios

Another gauge of the relative distance of the poor from the poverty level is the

proportion below specified fractions of their respective poverty thresholds. This

section examines income-to-poverty-threshold ratios under the various measures

and does so across the entire income distribution. This exercise illustrates not only

the difference in distribution below the poverty line, but across all income levels as

the definition of family resources changes.

Table 6 shows estimates of the percent of people by family income-topoverty-threshold ratios under the three measures discussed, the official, MSI, and

MIT measures. It can be seen that accounting for taxes and transfers in the income

measure results in greater percentages of individuals in the middle-income ranges.

This is the result of the re-distributional effect of taxes and transfers that are included

in the experimental measures.
20

Table 6: Percent of People by Income-to-Poverty Ratios, 2000

All persons White

Official MSI MIT Official MSI MIT

Less than 0.5 4.4 3.8 3.6 Less than 0.5 3.5 3.4 3.2

0.5 to 0.99 6.9 8.4 9.1 0.5 to 0.99 5.9 7.3 7.9

1.0 to 1.99 17.9 27.8 29.6 1.0 to 1.99 17.0 26.1 27.9

2.0 to 3.99 32.5 37.8 38.7 2.0 to 3.99 32.7 39.0 40.3

4 or more 38.3 22.2 19.0 4 or more 40.9 24.1 20.7

Children Black

Official MSI MIT Official MSI MIT

Less than 0.5 6.4 3.9 3.8 Less than 0.5 9.3 6.1 5.7

0.5 to 0.99 9.6 10.7 12.0 0.5 to 0.99 12.7 14.5 15.6

1.0 to 1.99 21.3 33.3 34.1 1.0 to 1.99 24.4 37.8 39.6

2.0 to 3.99 33.3 36.7 36.8 2.0 to 3.99 32.0 30.7 30.1

4 or more 29.3 15.4 13.2 4 or more 21.7 11.0 9.0

Nonelderly Adults Hispanic

Official MSI MIT Official MSI MIT

Less than 0.5 3.9 3.6 3.6 Less than 0.5 7.3 6.3 6.1

0.5 to 0.99 5.5 6.8 7.4 0.5 to 0.99 13.9 17.9 20.2

1.0 to 1.99 14.7 24.6 25.9 1.0 to 1.99 30.1 44.1 44.3

2.0 to 3.99 31.6 39.0 40.4 2.0 to 3.99 32.6 25.7 24.4

4 or more 44.3 26.0 22.6 4 or more 16.1 6.0 5.1

Elderly Female Householder

Official MSI MIT Official MSI MIT

Less than 0.5 2.2 4.6 2.7 Less than 0.5 10.9 8.6 8.0

0.5 to 0.99 8.0 12.0 11.5 0.5 to 0.99 14.8 16.5 17.9

1.0 to 1.99 27.1 32.5 38.8 1.0 to 1.99 27.2 38.6 40.1

2.0 to 3.99 35.7 33.5 34.0 2.0 to 3.99 29.2 26.6 26.2

4 or more 27.0 17.4 13.1 4 or more 17.9 9.7 7.9

Source: March 2001 Current Population Survey

Comparing the official versus the MSI measure shows that a slightly higher

percentage of all people – 4.4 versus 3.8 percent – are in extreme poverty (below

one-half of the relevant poverty threshold) using the official measure (also see

Figure 4). Further, while the MSI measure yields a slightly higher percentage of

people below the poverty line than the official measure yields, more of those
21

individuals are above one-half the relevant poverty threshold than are found using

the official measure – 8.4 percent using MSI versus 6.9 percent using the official

measure. This is as expected from the calculation of poverty gaps and results from

the addition of in-kind transfers to family incomes in the experimental measures. The

results are similar, though even more pronounced, for the MIT measures relative to

the official measure.

The table also shows that this pattern of fewer people in extreme poverty

when using the experimental measures holds for most demographic groups

including children, Blacks, and Hispanics. The percent of children in extreme poverty

as reported with the official poverty measure is 6.4 percent. Under the experimental

measures that falls to 3.9 and 3.8 percent.

Figure 4: Percent of Persons by Income to Poverty Threshold 

Ratio 2000

4.4 3.8 3.6

6.9 8.4 9.1

17.9

27.8 29.6

32.5

37.8

38.7

38.3

22.2 19.0

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Official MSI MIT

4.0 or more

2.0 to 4.0

1.0 to 2.0

0.5 to 1.0

under 0.5
22

The one exception is the elderly. Notably, 2.2 percent of the elderly are in

extreme poverty under the official measure. Under the MSI measure this rises to 4.6

percent. This result follows from the method used in that measure to value MOOP

expenses. However, the MIT measure is much closer to the official measure in this

regard.

Summary and conclusions

This paper describes and compares the size and composition of the poverty

population under the official poverty measure and two experimental measures of

poverty. The major focus is a discussion of methods and data used to estimate

medical out-of-pocket expenses.

Results indicate that, while many groups are somewhat more likely to be

classified as poor under the experimental measures, the depth of their poverty is

less than is generally found under the official measure. Further, income-to-poverty

threshold ratios reveal that for several groups, such as children, Blacks, and

Hispanics, the percent in extreme poverty is lower under the experimental measures

than the official measure.

A few elements in the experimental measures have a particularly important

role in changing our perception of who is poor. For one, accounting for health care

costs considerably increases the number of people who appear to be struggling to

get by. Particularly, it increases the number of elderly who are perceived to be poor,

while only slightly affecting the number of poor children and Blacks. Choice of

method to account for health care costs has an effect on these estimates. All
23

statistics shown here, poverty rates, poverty gaps, and income-to-poverty thresholds

ratios, are affected by the method chosen to include medical expenses.

A final but important conclusion from this study is that there is much to be

learned from a poverty measure that is carefully and explicitly constructed. It allows

us to understand more precisely the economic situation of families and individuals.

Including government benefits aimed at the most needy within the experimental

measures also helps gauge the effectiveness of these programs in improving the

lives of low-income families and individuals. With such a procedure one can more

carefully ascertain the situation of particular population subgroups that are often

specifically targeted for aid. Finally, the experimental measures allow us to more

thoroughly understand the costs and economic hardship that individuals and families

face and to examine where and how difficulties arise.
24

Appendix Table. Medical Risk Factors (with adjustment for uninsured) and

Mean Values of MOOP for MSI and MIT Measures

Characteristics Medical Risk

Factors

MSI

Mean Amount

MIT

Mean Amount

Reference family 1.00 $1,853 $1,349

Families with no elderly members

Private, 1 person

Good health 0.42 868 571

Fair/poor health 0.77 933 1,044

Private, 2 people

Good health 0.89 1,991 1,196

Fair/poor health 1.13 2,143 1,520

Private, 3+ people

Good health 1.00 1,946 1,352

Fair/poor health 1.26 1,913 1,695

Public, 1 person

Good health 0.02 438 24

Fair/poor health 0.07 487 93

Public, 2+ people

Good health 0.03 322 45

Fair/poor health 0.09 403 124

Uninsured, 1 person

Good health 0.48 235 649

Fair/poor health 0.90 278 1,217

Uninsured, 2+ people

Good health 1.02 556 1,370

Fair/poor health 1.08 460 1,462

Families with elderly members

Private, 1 person

Good health 1.19 2,043 1,606

Fair/poor health 1.31 2,059 1,765

Private, 2+ people

Good health 1.92 3,045 2,593

Fair/poor health 2.30 3,025 3,096

Public, 1 person

Good health 0.49 1,978 659

Fair/poor health 0.45 1,841 605

Public, 2+ people

Good health 0.91 2,845 1,220

Fair/poor health 1.01 2,734 1,367

Source: 1998- 2001 Consumer Expenditure Survey, 2001 Current Population Survey, 1996 Medical

Expenditure Panel Survey and Banthin et al., 2001.
25

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