BLS WORKING PAPERS

U.S. DEPARTMENT OF LABOR 

Bureau of Labor Statistics 

OFFICE OF PRICES AND LIVING

CONDITIONS 

 

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

Assessments of Minimum Needs 

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

Kathleen Short, U.S. Census Bureau 

 Working Paper 381

 March 2005 

All views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the U.S. 

Bureau of Labor Statistics.
Economic Well-Being Based on Income, 

Consumer Expenditures and 

 Personal Assessments of Minimum Needs 

Thesia I. Garner 

Division of Price and Index Number Research 

U.S. Department of Labor 

and 

Kathleen S. Short 

Housing and Household Economics Statistics Division 

U.S. Census Bureau 

August 10, 2004 (edited 11-18-04; revised 9-21-06)) 

Citation: 

Garner, Thesia I. and Short, Kathleen. ìEconomic Well-Being Based on Income, Consumer Expenditures 

and Personal Assessments of Minimum Needsî 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, Oxford, UK: Elsevier Science, February 2004, pp. 319-361.(BLS Working Paper 

381).

Presented During the Conference on Inequality, Poverty, and Welfare 

To Honor Professor John Formby 

May 22-24, 2003 

University of Alabama 

Tuscaloosa, Alabama

JEL Classifications: 

D12 Consumer Economics: Empirical Analysis 

I31 General Welfare, Basic Needs, Living Standards, Quality of Life 

I32 Measurement and Analysis of Poverty 

Key Words: well-being, sufficiency, poverty, income, expenditures, Consumer 

Expenditure Survey, Survey of Income and Program Participation 

We extend our appreciation to Ismael Ahamdanech Zarco, the discussant of our paper at the Formby conference, and to others 

attending the meetings, as well as to Pat Ruggles, the discussant of an abbreviated version of the paper when it was presented at the 

Joint Statistical Meetings of the American Statistical Association in San Francisco in August 2003. John Formby, Karel Van den 

Bosch, and Klaas de Vos also provided much appreciated comments and suggestions. We extend our appreciation to Denton Vaughan 

and Dan Weinberg for providing helpful comments and suggestions on earlier versions of this manuscript. Preliminary results from 

the SIPP part of this study were presented at the 2003 ASSA Conference in a session sponsored by the Society of Government 

Economists. We thank Arie Kapteyn, discussant of the ASSA paper, and others attending the session for their comments and 

suggestions. To Susan Poulin we owe special thanks for discussions concerning the Statistics Canada study in which the same basic 

methods as the ones presented in this paper are used. We thank Linda Stinson, Clyde Tucker, and others within the Bureau of Labor 

Statistics for their guidance in exploring the ìwhysî and ìhowsî of minimum income and spending. 

This paper reports the results of research and analysis undertaken by U.S. Bureau of Labor Statistics and U.S. Census Bureau staff. 

This work has gone through limited internal review and is being released to inform interested parties of research to encourage 
1

discussion. All views expressed in this paper are ours and do not reflect the views or policies of our respective agencies or the views 

of other staff therein. We accept responsibility for all errors. 

ABSTRACT 

Responses to minimum income (MIQ) and minimum spending questions (MIQ) are used to 

produce economic well-being thresholds. Thresholds are estimated using a regression framework. 

Regression coefficients are based on U.S. Survey of Income and Program Participation (SIPP) data and 

then applied to U.S. Consumer Expenditure Survey (CE) data. Three different resource measures are 

compared to the estimated thresholds. The first resource measure is total before-tax money income, and the 

other two are expenditure-based. The first of these two refers to expenditure outlays and the second to 

outlays adjusted for the value of the service flow of owner-occupied housing (rental equivalence). The 

income comparison is based on SIPP data while the outlays comparisons are based on CE data. Results 

using official poverty thresholds are shown for comparison. This is among the earliest work in the U.S. in 

which expenditure outlays have been used for economic well-being determinations in combination with 

personal assessments, and the first time rental equivalence has been used in such an exercise. Comparisons 

of expenditures for various bundles of commodities are compared to the CE-derived thresholds to provide 

insight concerning what might be considered minimum or basic. 

Results reveal that CE and SIPP MIQ thresholds are higher than MSQ thresholds, and resulting 

poverty rates are also higher with the MIQ. CE-based MSQ thresholds are not statistically different from 

average expenditure outlays for food, apparel, and shelter and utilities for primary residences. When 

reported rental equivalences for primary residences that are owner-occupied are substituted for out-ofpocket shelter expenditures, single elderly appear to be as badly off as they would be with a strict outlays 

approach in defining resources. 
2

1. INTRODUCTION

 Personal assessments of what is needed financially to provide for oneís minimum level of living 

can be used to produce measures of economic well-being (see Garner and Short 2003a for a list of several 

studies). Household surveys are often sources of these data. The current study incorporates data from two 

U.S. federal household surveys, the Survey of Income and Program Participation (SIPP) and the Consumer 

Expenditure Survey (CE). 

 The potential for collecting personal assessments of economic well-being using federal household 

surveys for the U.S. began about 25 years ago when three major activities were independently undertaken 

by the Census Bureau and the Bureau of Labor Statistics (BLS). First, in 1979, the Census Bureau 

supported the collection of minimum income levels and respondent evaluations of personal income in a 

federal household survey as part of the Census Bureau Research Panel of the Income Survey Development 

Program (ISDP) (see Danziger et al. 1984). 

 Second, at about the same time, the Bureau of Labor Statistics (BLS) contracted with the 

University of Wisconsin-Madison Institute for Research on Poverty and the Center for Social Sciences at 

Columbia University to study the BLS Family Budget Program (Expert Committee on Family Budgets 

1980; Watts 1980). The Expert Committee noted that direct assessments of minimum needs could be used 

to establish a central prevailing norm of levels of living as understood by the population, and that these 

norms could be used to establish new Family Budgets. They recommended that perceptions of consumption 

levels associated with particular standards of living be examined in addition to perceptions of income 

levels. They stated that perceptions of consumption, for example, could be used, ìÖ to determine how 

much people feel it would be necessary for a family to spend on food in order to have a given level of 

living ñ a minimum level, an adequate level, etc.î (Expert Committee on Family Budgets 1980, p. 95). The 

Committee recommended that direct questions concerning minimum needs be asked in household surveys 

and that Family Budgets eventually be based on responses to these questions.1

 A minimum income 

question was included in the CE in 1982 in response to the Expert Committeeís recommendation. 

 

1

 The Expert Committee stated that, ìA program of research and testing should develop methods leading toward eventual replacement 

of the median-type of norm we are currently recommending for the Family Budgets with the norms derived directly from peopleís 

perceptionsî (p.52). 
3

 And third, the Census Bureau included minimum income and minimum spending questions in a 

Survey of Income and Program Participation (SIPP) Topical Module on Basic Needs. The module was 

administered as part of the ninth wave of the 1993 SIPP panel with data collected in the 1995 (see 

Kominski and Short 1996). Questions about income satisfaction were also included in the module along 

with personal assessment questions focused on other aspects of material well-being (for analyses of data 

from these other questions, see Bauman 1998 and Bauman 1999). 

 Personal assessment questions about minimum income and spending support a more populist or 

democratic framework for living standards measurement than to one based strictly on expert judgment, for 

example. Such measures are based on the notion that ordinary people, as opposed to experts, know what 

they need in order to get along or prosper. When minima refer specifically to certain items, a mixed 

measure can result that reflects both the views of experts concerning the items required for basic living and 

ordinary peopleís personal assessments of how to define these items and their level of income or spending 

needs.2

 

 The purposes of this study are to present subjective economic well-being thresholds, based on 

minimum income (MIQ) and minimum spending questions (MSQ), and to compare these to three resource 

measures to calculate the percentage of households whose resources are insufficient relative to their needs 

as implied by these measures. Additional comparisons of thresholds to expenditures for various bundles of 

commodities are made to gain insight regarding what might be included in oneís response to a MSQ, and 

how this can differ by demographic group. The resource measures include before-tax money income, total 

expenditures outlays, and an expenditures outlays measure that accounts for the rental equivalence of 

owner occupants. The latter measure reflects the value of the flow of services from owner-occupied 

housing, and as such, represents consumption needs as opposed to spending needs. No other adjustments 

are made for the consumption of other commodities in the analysis. Before-tax money income focuses on 

oneís ability to attain a level of living. Expenditures focus more on oneís actual level of living. 

 The expenditures based approach is related to a recommendation made by the National Academy 

of Sciences Panel on Poverty and Family Assistance (hereafter referred to as the NAS Panel) that a 

 

2

 The National Academy of Sciences Panel on Poverty and Family Assistance recommended a threshold that is also mixed for poverty

measurement with commodities specified by the Panel to include food, clothing, shelter, utilities, and other basic items. Median 

expenditures for these commodities for a two-adult, two-child family would then be used as an input to produce thresholds for other 

families (Citro and Michael 1995). 
4

consumption or expenditures concept of family resources could be considered in the future for measuring 

poverty (Citro and Michael 1995, p. 13). Comparing expenditures, or some variant of expenditures such as 

a value for consumption, to a threshold that represents some minimum standard of living is in the tradition 

of previous research (e.g., Andress et al. 2001; Andrews et al. 2001; Grootaert and Braithwaite 2000; 

Gundersen and Oliveira 2001; Lanjouw and Lanjouw 2001; Mayer and Jencks 2000; Milanovic 1998; Pan 

2003; Pradhan and Ravallion 2000; Slesnick 1993, 1994, 1998), and is being used increasingly in studies of 

economic well-being in developing countries (see Deaton and Grosh 2000, and ìWelfare in Bosnia...î 2002 

as an example).3

 

 MIQ and MSQ thresholds produced for the U.S. thus far have been compared to income only. To 

our knowledge, this study represents the first time expenditure outlays and an outlays measure adjusted for 

rental equivalence have been used in combination with MIQ and MSQ data to examine economic wellbeing and poverty for the U.S.4

 However, total expenditures, as defined by the BLS for publication, were 

previously compared to official poverty thresholds by Federman et al. (1996). In addition, a recent study 

published by the Census Bureau uses CE expenditure outlays to examine the distribution of consumer 

durables across deciles based on outlays (U.S. Census Bureau 2003) as an approach to study economic 

well-being. 

The current study is an extension of the earlier Garner and Short (2003a, b) research which used 

data from the SIPP. As in the previous studies, personal assessment thresholds are derived using the 

intersection method first introduced by Goedhart et al. (1977), but the current model is simplified compared 

to that used by Garner and Short in their first study (2003a).5

 As before, data from the SIPP Topical 

Module on Basic Needs, 1993 panel-wave nine, are used to estimate regression coefficients that relate 

minimum income or spending and actual before-tax money household income. For the earlier study, 

minimum income (MIQ) and minimum spending (MSQ) thresholds were produced and compared to 

before-tax money income. The current study again compares thresholds to before-tax money income using 

the simplified model specification and, in addition, applies results from the SIPP-based regression to the 

 

3

 Also see Census (2003) for a more detailed discussion of the use of consumption and expenditures in measuring economic wellbeing. 

4

 See Deaton (1998) for a discussion of the choice of a welfare measure. See Ritakallio (2003) for research on the importance of 

housing costs in welfare comparisons. 

5

 The regression model in the earlier study included interaction terms while the current study focuses on primary effects. The earlier 

study is based on the De Vos and Garner (1991) model.
5

CE to produce a companion set of thresholds as noted. Using data from both sources, a set of comparisons 

is made for the MIQ and MSQ thresholds. The MIQ is compared to SIPP before-tax money income and 

the MSQ to CE expenditure outlays. Other comparisons are presented for illustration. 

 When before-tax money income is compared to a threshold based on minimum income responses, 

it is assumed that income for making ends meet is being considered. What a respondent considers ìto make 

ends meetî can be broad and could possibly include savings (for example, for a childís future college 

education) or it could include payments on previously borrowed funds. Thus comparing income to the 

MIQ-based threshold seems appropriate. In contrast, the MSQ asks respondents to focus specifically on 

spending and basic necessities such as food, shelter, clothing and other essential items for daily living. 

Thus, comparing expenditure outlays is likely the more appropriate resource measure to compare to a MSQ 

threshold. If respondents are thinking of what it costs to meet their consumption versus spending needs, 

say for housing, comparing the MSQ threshold to expenditures that account for the value of their 

consumption might be the preferred approach. Comparing minimum spending-based thresholds with 

expenditure outlays is not possible with the SIPP as only limited expenditure data are collected.6

 For this 

part of the analysis CE expenditure data are used. Estimated SIPP-based coefficients are applied to a 

sample of CE respondents and then weighted to derive population based thresholds. Since the SIPP and CE 

are designed to both represent the same U.S. population, the estimated thresholds should be quite similar. 

 Based on cognitive research, Stinson (1997)7

 reported that respondents can identify minimum 

economic needs, and when faced with changes in their economic situations that lead to reduced income, 

can provide a minimum set of expenditures that they consider necessary. How respondents make a 

distinction between income and spending needs was not examined by Stinson, nevertheless her research 

supports the notion that minimum income used here represents a higher level of living than does minimum 

spending. If this is the case, then one might consider a higher MIQ-based threshold as representing a 

ìsocial minimum standardî while a lower MSQ-based threshold would represent a ìsubsistence minimum 

standard.î Lower thresholds are expected from the MSQ than from the MIQ as the MSQ is more specific in 

 

6

 In the 1993 SIPP Panel, limited expenditure data were collected, for example, for child care expenditures. 

7

 In the early 1990ís the BLS, with support from the Census Bureau, conducted cognitive testing on what respondents think when 

asked subjective well-being questions like the Minimum Income Question (MIQ) and Minimum Spending Question (MSQ). Stinson 

was the lead researcher for the project. 
6

defining basic needs than is the MIQ. This hypothesis is based on Stinsonís work (1997), and earlier 

findings of Morissette and Poulin (1991) for Canada, and Garner and Short for the U.S. (2003a, b). 

Results reveal that MIQ and MSQ thresholds are statistically significantly different in the two 

surveys with the MIQ thresholds being higher. Different resource measures have implications regarding 

oneís ability to meet perceived basic needs, particularly for certain population subgroups such as the 

elderly. Comparisons of thresholds to expenditures for various commodity bundles suggest that 

ìminimumsî differ not only in terms of level but also in terms of the commodity bundle composition for 

demographic subgroups. 

 This research suggests that a closer examination of minimum spending is important. Responses to 

the MIQ and MSQ likely differ because people think ìmaking ends meetî requires more than ìspendingî 

for barely adequate food, shelter, clothing, and other essential items. When a basic living threshold is 

desired for well-being examinations, the MSQ could serve as the basis for such a measure. The MSQ calls 

for a greater specificity of basic needs than does the MIQ and is less likely to be affected by the 

unpredictability of income. 

 The paper is divided into three remaining sections. A brief overview is presented along with a 

description of the data and methods. The results and conclusions follow. 

2. OVERVIEW, DATA and METHODS 

2.1 Overview 

 The minimum income question (MIQ) and minimum spending question (MSQ) asked in the U.S. 

Survey of Income and Program Participation (SIPP), and used in this study, are identical to those asked in 

the Survey of Consumer Finances conducted by Statistics Canada in the 1980ís (Morissette and Poulin 

1991). The MIQ had been asked by previous researchers in Canada, the U.S. and other countries;8

 however 

the Canadians introduced the MSQ as another version of the MIQ. The MSQ refers specifically to barely 

adequate food, shelter, clothing, and other essential items for daily living. Morissette and Poulin (1991) 

reported thresholds based on the MSQ that were lower than those based on the MIQ. Garner and Short 

 

8

 We are aware that the MIQ has been asked in the following countries at least: Australia, Belgium, Czech Republic, Germany, the

Netherlands, Russia, Slovakia, and Switzerland. 
7

(2003a, b) found the same result using SIPP data and concluded that the MIQ and MSQ thresholds are 

conceptually different, unlike the underlying assumption of Morissette and Poulin (1991) and Stinson 

(1997). The only other country, that we have been able to identify, in which questions about the cost to 

maintain a level of minimum (standard) living has been asked is the Peopleís Republic of China.9

 Subjective thresholds and resulting rates of the population below the thresholds are produced 

using two different sets of data, the SIPP and CE. First, MIQ and MSQ thresholds are produced for a 

weighted sample of U.S. households using SIPP data and a regression of the minimums on total before-tax 

household income and other socio-demographic variables. Before-tax money income is included in the 

model for two reasons: first because the MIQ is asked with regard to before-tax money income; and second 

because this income is the same as that used for official poverty statistics although the data source differs.10

Household before-tax money income is compared to the MIQ and MSQ household thresholds to produce 

subjective poverty rates; official poverty thresholds are presented for comparison. 

 Second, relationships between the SIPP MIQ and MSQ data and income, along with other sociodemographic variables, are assumed and then applied to a weighted sample of consumer units (for 

definition, see Data section) participating in the U.S. Consumer Expenditure Survey (CE) to produce 

thresholds. When using the CE, MIQ and MSQ thresholds are compared to total expenditure outlays to 

produce an additional set of subjective poverty rates. MIQ and MSQ thresholds are also compared to 

smaller bundles of expenditures to provide insight regarding what might be considered to be minimally 

necessary. Total expenditure outlays adjusted for the value of the flow of services of owner-occupied 

housing is also compared to the thresholds. Such a comparison is meaningful if answers to the MIQ and 

MSQ reflect ìconsumptionî needs as opposed to ìspendingî needs. Such an interpretation would be 

reflective of a respondent answering the question with reference to people in general, rather than to his or 

her own circumstance. Stinsonís work (1997) suggests that this might be the case, for example, as an 

 

9

 As part of the 1995 Chinese Household Income Projects Survey, urban households in China were asked a minimum-needs based 

question. The question can be referred to as a minimum spending question since the reference ìneedî is ìthe cost of maintaining a 

minimum standard of livingî. The MSQ asked is (translated from Mandarin): ìWhat is the monthly cost of maintaining a minimum 

standard of living for the whole family in 1995?î The Chinese Household Income Projects Survey was conducted as part of a major 

research program of the Chinese Academy of Sciences (Bishop 2003). Also see Bishop, Luo, and Pan (2004) and Pan (2003) for 

analyses of these data; both sets of authors used consumption expenditures rather than income for the regression intersection model. 

Pan (2003) compared the derived minimum thresholds to consumption expenditures to assess poverty while Bishop, Luo, and Pan 

(2004) compared the derived thresholds to income. Gustafsson, Shi, and Sato (2002, forthcoming) used perceived minimum needs 

data collected for 1999 in twelve cities in China. The question for this study is (as translated from Mandarin): ìAccording to your 

actual situation how much are your minimum, household living expenses each month?î Income was used in the regression intersection 

and income was compared to derived thresholds to assess poverty. 

10 Official poverty statistics are based on data from the Current Population Survey, not the SIPP. 
8

owner might refer to less expensive rental housing for his or her shelter needs. Poverty rates based on 

official poverty thresholds and outlays with and without the consumption adjustment for shelter are 

presented. 

2.2 Data 

 The SIPP data were collected from the 1993 panel of households using the Topical Module on 

Basic Needs, the last in a series of nine modules. Data were collected from October 1995 through January 

1996. Household characteristics refer to the data collection period and total before-tax money income is for 

the previous four months. Thus income was reported for the last four months beginning in June 1995 for 

those interviewed in October 1995, and December 1995 for those interviewed in January 1996. The MIQ 

was asked of only half of the SIPP respondents to the Topical Module (Table 1). The other half were asked 

the MSQ. 

 The minimum income question (MIQ) follows: 

To meet the expenses you consider necessary, what do you think is the minimum income, 

BEFORE-TAX, a family like yours needs, on a yearly basis, to make ends meet (If you are 

not living with relatives, what are the minimum income needs, BEFORE-TAX, of a 

individual like you?) 

 The minimum spending question (MSQ) follows: 

In your opinion, how much would you have to SPEND each year in order to provide the 

BASIC necessities for your family? By basic necessities I mean barely adequate food, 

shelter, clothing, and other essential items required for daily living? 

 The reference period for the MIQ and MSQ varied depending upon the preferences of 

respondents. The majority of respondents answered the MIQ and MSQ in annual dollar values: 67.8 

percent for the MIQ and 53.7 percent for the MSQ. Over 38 percent of the MSQ respondents used a 

monthly reference period in contrast to the 26 percent of the MIQ sample (See Table 2). 
9

 Data were collected from households; however, the MIQ and MSQ refer to a family situation. A 

household is defined in the SIPP as all the people who are living in a housing unit. A housing unit is 

defined as a living quarters with its own entrance and cooking facilities. A family, in contrast, is composed 

of all persons who are related by birth, marriage, adoption, or other legal arrangement. 

 The CE sample, for which thresholds are produced, includes consumer units interviewed in the 

last calendar quarter of 1995 and/or first quarter of 1996; data were collected using the Quarterly Interview 

instrument. In the CE Interview, expenditures for the three months prior to the interview are collected 

during a single interview. Thus, the earliest reference period for the entire sample would be the three 

months prior to October 1995 or July 1995. The last set of interviews, conducted in March 1996, refer to 

expenditures beginning in December 1995 and ending in February 1996. These time periods were selected 

as they overlap, although not perfectly, with the reference period for the SIPP Topical Module. For this 

study, as for official publications of expenditures, quarterly reports of expenditures are assumed to be 

independent. As most of the sampleís expenditures refer to 1995, results are assumed to be for 1995, the 

same as for the SIPP. 

 Expenditure data are collected from consumer units (see U.S. BLS 1997b). Consumer units are 

defined slightly differently from households and families. A consumer unit comprises: (1) all members of a 

particular household who are related by blood, marriage, adoption, or other legal arrangement; (2) a person 

living alone or sharing a household with others or living as a roomer in a private home or lodging house or 

in permanent living quarters in a hotel or motel, but who is financially independent; or (3) two or more 

persons living together who use their income to make joint expenditure decisions. Financial independence 

is determined by the three major expense categories: housing, food, and other living expenses. To be 

considered financially independent, at least two of the three major expense categories have to be provided 

entirely, or in part, by the respondent. For the time period under study, 96 percent of all consumer units 

(CU population weighted) were also households with no other consumer units present. 

2.3 Estimating the Subjective Threshold: The Intersection Method 

The intersection method of producing subjective minimum thresholds was first introduced by 

Goedhart et al. (1977) and was based on the relationship between reported minimum income and actual 

income. The assumption in the current study is that the relationship between minimum spending and actual 
10

income is similar to the relationship between minimum income and actual income. The subjective 

threshold (X*) is calculated as the intersection of the relationship: 

min 0 1 2 2 3 3 ln( ) ln( ) ... X a a Y az az azn n = + + + ++ + ε (1) 

with the line X Y min = for different characteristics, zn. The error term, ε , is assumed to satisfy the 

classical assumptions for simplicity. For this study, we assume that Xmin represents the answer to questions 

about the minimum income or spending dollar amount that the respondent thinks is needed for the family to 

make ends meet. And Y is total household before-tax money income. This approach assumes that 

minimum income or spending, denoted by Xmin, is equal to actual income: X Y min = ; however, minimum 

income and minimum spending are not assumed to be equal. 

We assume a linear relationship between the minimum reported, either income or spending, and 

actual income. A plot of minimum income and minimum spending by total before-tax money income 

indicates that a log-linear model fits the data when Xmin represents the answer to a question about minimum 

income or spending fairly well and this finding is consistent with the work of others (e.g., De Vos and 

Garner 1991; Garner and De Vos 1995; Kapteyn et al. 1988; Van den Bosch 2001). 

The coefficient 1 a has been referred to as preference drift (Van Praag 1971), as it depicts the trend 

that preferences drift upward with income. The notion here is that respondents accustomed to a higher 

standard of living, everything else being the same, will have higher aspirations and therefore will report 

higher estimates of their minimum income or spending requirements. As the model is specified in a 

double-log formulation, the coefficients will lie between zero and one. When the preference drift equals 

zero, the subjective threshold becomes an absolute threshold. When the coefficient equals one, the 

threshold becomes fully relative; in this case, every increase in actual income results in the same percentage 

increase in what is perceived to be the subjective threshold. When the coefficient is between zero and one, 

the interpretation is that as people get richer they set the necessary minimum higher, but do not raise it (in 

percentage terms) as much as their income goes up (see Milanovic and Jovanovic 1999 for a recent 

discussion concerning preference drift). 

Based on earlier work using U.S. data (e.g., De Vos and Garner 1991; Garner and De Vos 1995; 

Garner and Short 2003a), we hypothesize that the coefficient on income will be closer to zero than to one 
11

for the MIQ model. Given that the MSQ refers to a specific set of commodities, we further hypothesize 

that the income coefficient in the MSQ model will be less than the income coefficient in the MIQ model; 

thereby resulting in thresholds that are more absolute than relative. 

An underlying assumption for the intersection approach to estimate minimum income and 

spending-based thresholds is that only those who have income that is at the minimum know what the ìtrueî 

minimum is. This relationship is presented in Figure 1. Since that minimum is not known for a society a 

priori, data are collected from a sample representing the whole population. The predicted threshold based 

on equation (1) and the intersection of X Y min = is: 

0 22

2

1

... *( ... ) exp 1

n n

n

a a z az Xzz

a

  + ++ =     − . (2) 

Different thresholds are possible for given values of zn. Note: income does not enter the prediction 

equation; only the coefficient of income, a1, enters. Alternative thresholds for different family types and for 

different regions of the country, for example, could be derived using the same intersection approach (see 

Figure 2 for an example). 

450

Xmin Xmin=Y

X*min Y

Xmin=f(Y)

Figure 1. The Subjective Threshold Based on the Regression Intersection 

ApproachReported minimum

Actual total income
12

450

X1

*

Xmin

Y

I

II

III

X2

* X3*

Xmin=Y

I One adult

II Two adults

III Two adults, 

one child

Figure 2. Subjective Thresholds for Different Family Types Reported minimum

Actual total income

There are different possible choices regarding the error term, ε , as it is not observable. The choice 

here is not to include an error term when producing the threshold with the result being a median prediction 

(see Garner and Short 2003a for a discussion of this issue). Kapteyn et al. (1988) used the median 

prediction equation (2) as did other researchers using U.S. data (Colasanto et al. 1984; Danziger et al. 1984; 

De Vos and Garner 1991; Garner and De Vos 1995; Garner and Short 2003a, b). The median is chosen as 

the measure of central tendency for the subjective threshold because it is more robust to outliers than the 

mean and because the median is the midpoint of the distribution, thus making it perhaps more relevant for 

poverty discussions than the mean. 

Although most minimum income and spending data to date are for cross-sections, this approach 

was originally designed for use with panel data (Kapteyn et al. 1988). By using panel data, it would be 

possible to test whether people gravitate toward some true minimum over time. It is expected that 

respondents who are above the true minimum would find that over time they have a better idea of what 

their true minimum is and would respond accordingly. For those below the true minimum, over time they 

would realize that they are actually underestimating their true income or spending needs. 
13

Another assumption underlying the intersection approach is that every respondent gives the same 

meaning to the wording used in the MIQ and MSQ. In other words, the expressions ìnecessary to make 

ends meetî and ìbasic necessities,î for example, are assumed to have the same welfare connotation for all 

respondents. Variations in responses would be expected when households have differing needs, for 

example, a family of two adults would be expected to report lower minimum income or spending needs 

than a family of three adults. Differences in responses could also result when they face different prices, for 

example, if prices for necessary commodities were lower in the South than in the Northeast. The regression 

intersection approach allows one to control for differences in responses due to reference group effects. 

Differences due to differing needs and prices would remain. Basing thresholds on these remaining 

differences would be desirable. 

The approach followed in this study is only one among others that has been used by researchers 

when estimating thresholds based on personal assessments of individuals in households or families. 

Another often used approach is to estimate a threshold directly, without controlling for any other 

characteristics than the one for which the thresholds are being derived (e.g., number of persons in the 

household), using the arithmetic average or median. Such approaches have been employed by Gordon et 

al. (2000), Saunders and Matheson (1992), Townsend and Gordon (1991, 1996), and Townsend et al. 

(1997). The Gallup Organization has collected data for ìget-alongî amounts and poverty lines for a family 

of four (husband, wife, and two children) for the U.S.; means and medians have been produced using these 

data (see Vaughan 2004).11

In many of the earliest models using the intersection approach, family size was the only other 

explanatory variable included in the model. However, since the work of Hagenaars (1986), additional 

explanatory variables have been included in the model and hence could be used to further differentiate the 

subjective thresholds. Family size has entered the regression models as the log(family size), log(number of 

adults) plus the log(number of children), dummy variables representing the numbers of adults and children 

in combination with their ages and/or their rank in the family,12 or as a series of dummy variables 

 

11 The Gallup poverty question is: ìPeople who have income below a certain level can be considered poor. That level is called the 

ìpoverty line.î What amount of weekly income would you use as a poverty line for a family of four (husband, wife, and two children) 

in this community?î The Gallup get-along question is: ìWhat is the smallest amount of money a family of four (husband, wife and

two children) needs each week to get along in this community?î The get-along question was asked in Gallup Polls from 1947-89 and 

again in 1992. The Gallup poverty question was asked in 1989 and 1992 (Vaughan 1993, 2004; Citro and Michael 1995). 

12 See Van den Bosch (2001) for an example with the ranks of the children entering the model.
14

representing more differentiated household compositions. Additional variables have included reference 

person characteristics as well as variables that reflect geographic variations. The model used in the current 

study differs from the earlier ones of De Vos and Garner (1991), Garner and De Vos (1995) and Garner and 

Short (2003a) in that primary effects, without interaction terms, are examined. The result is a simpler model 

specification with the potential problems associated with multicollinearity present in earlier models 

lessened. 

The primary household characteristic expected to influence responses to the MIQ and MSQ is 

family size and is most often considered a cost variable. Family size enters the model as log(adults+1) plus 

the log(number of children+1). In addition to needs represented by the presence of adults and children, 

needs also differ for households based on age and when someone is disabled or self-employed. These 

differences are accounted for in the model using the characteristics of the reference person as a proxy for 

the needs of the household as a whole. Other variables could also affect responses, but not necessarily 

reflect differences in needs or costs. Race, ethnicity, and education enter the model to account for potential 

differences in responses due to culture, habits, and reference groups. Differences in the financial needs of 

households can result depending on whether they own their home or not. Homeowners may consider their 

out-of-pocket expenses as greater than those of renters and also potentially more volatile. Differences in 

cost of living may be expected between different geographic regions and between different areas based on 

degree of urbanization. Dummy variables are included in the model to allow for these differences.

In constructing the model it is useful to consider a distinction between cost variables and reference 

group variables. While it is not possible to determine without question if a variable is strictly a cost or 

reference variable, in general, a cost variable is one that influences the costs that a household faces when 

maximizing its standard of living while reference variables influence oneís aspirations (Van den Bosch 

2001). This distinction is important in the production of poverty thresholds from these estimates. 

2.4 Production of Thresholds 

For this study, we produce thresholds based on two approaches. First we produce the threshold for 

each household and then average the thresholds using population weights. Thresholds are then 

differentiated by family size and age of the reference person, household composition according to the 
15

number of adults and children and the age of the reference person, housing tenure, region, and degree of 

urbanization. In this way we average out reference group effects such as those based on education, race, 

ethnicity, etc. We focus on family size as the thresholds have most often been used to compare differences 

across family compositions.13 Housing tenure is of interest since we examine the impact of defining 

housing costs with the value of the flow of owned housing services by rental equivalence for owners. 

Geography is of interest as differences in costs of living could be reflected in the thresholds but so also 

could other differences in the composition of the geographic areas in terms of households. This approach 

has been followed previously by various researchers (e.g., De Vos and Garner 1991; Garner and De Vos 

1995; Garner and Short 2003a; Gustafsson, Shi, and Sato 2002, forthcoming; Milanovic and Jovanovic 

1999). 

The second approach entails producing a set of thresholds differentiated by the same variables but 

holding the values of the other socio-demographic variables at their weighted national averages or some 

other set of values. Hagenaars (1986) and Van den Bosch (2001) used weighted national averages for the 

non-differentiated variables in the production of subjective thresholds, while Kapteyn et al. (1985) 

produced thresholds for a ìpoorî reference group and for a ìmedianî reference group.14 Van den Bosch 

(2001) notes that the distinction between cost and reference variables is fairly clear theoretically but that 

theory ìdoes not provide straightforward guidance on the problem of which variables used in the models Ö 

are to be regarded as cost variables and which ones as reference variablesî ( p. 222). He acknowledges that 

many empirical variables can have both cost and reference effects. 

As noted by Hagenaars (1986), which subjective line should be used depends on the political 

choice of differentiating characteristics that a society makes. She noted that when averaging over certain 

characteristics, errors will be made. ìÖpeople who feel poor according to the poverty [subjective]15 line 

differentiated for their type may be defined as non-poor according to the average poverty [subjective] line 

(type II error), and people who were not poor according to their type specific poverty line may be defined 

as poor (type I error)î (Hagenaars 1986, p. 108). She further notes that, (paraphrased), ìIf in a democratic 

process, the majority of the population has characteristics that are the same as those at the national mean, 

 

13 Equivalence scales implicit in subjective thresholds have been produced often and, in some cases, compared to those based on other 

approaches (e.g., Garner and De Vos 1995; Garner and Short 2003a; Pan 2003; Bishop, Luo, and Pan 2004; Van den Bosch 2001). 

14 Reported by Van den Bosch (2001). 

15 We refer to the lines as ìsubjectiveî rather than ìpovertyî lines. 
16

the decision may be made to average all over characteristics to produce the threshold. Minorities that have 

characteristics different from the national mean may as a result either benefit from a resulting type II error, 

or suffer from a type I errorî (p. 108). 

2.5 Application to U.S. Consumer Expenditure Survey Data 

SIPP data are used to estimate two relationships: (1) minimum income with total before-tax 

money income; and (2) minimum spending with total before-tax household income. The SIPP estimated 

coefficients from equation (1) are inputs into equation (2), along with the demographic characteristics data 

from the CE, to produce CE based MIQ and MSQ thresholds. Due to the intersection of X Y min = , only 

the coefficient of income enters the prediction equation and not income (see equation 2). 

 Two assumptions underlie the approach of applying the SIPP-estimated coefficients to the CE 

sample to derive MIQ and MSQ thresholds for the CE population. First, the SIPP and CE samples are 

drawn from the same U.S. population and there is no bias resulting from systematic attrition in SIPP (see 

Garner and Short 2003a for a discussion concerning this issue, and McArthur and Short 1985). Second, the 

relationships between minimum income and minimum spending and each of the explanatory variables in 

the MIQ and MSQ models are the same in both samples.

 Total expenditures outlays are examined against the MIQ and MSQ thresholds and the official 

poverty thresholds. We start with the definition of total expenditure outlays used by the Bureau of Labor 

Statistics and edit it to not include expenditures that are only included in the fifth interview. These include 

those for finance charges (excluding those on mortgages and financed vehicles), occupational expenses, 

and cash contributions to organizations and non-CU members. This was done in order that all consumer 

units would have the opportunity to have the same expenditures as every other consumer unit each quarter. 

Included in total expenditure outlays are those for the following: food and beverages at home and away 

from home including meals as pay; housing including shelter, utilities, household operations and household 

furnishings and equipment, and rent as pay; apparel and services; transportation; health; entertainment; 

personal care; reading; education; tobacco; miscellaneous such as legal fees and banking services; life and 

other personal insurance; and contributions for retirement and pension plans including Social Security. 

Total expenditure outlays differ from the BLS publication definition in that the outlays for mortgage 
17

principle payments for housing and other property are included in outlays, along with out-of-pocket 

payments for vehicles and entertainment items.16

 An additional measure of total expenditures is used to compare to the MIQ and MSQ thresholds, 

one based on the value of the flow of services from owner-occupied housing. Such a measure enables us to 

examine the impact of housing needs based on the value of the flow of services from owned housing, 

defined as rental equivalence, as compared to actual spending outlays. Out-of-pocket expenditures for 

shelter that is the primary residence and owned by the consumer unit were replaced by the value of the flow 

of services from this housing.17 This value was provided by consumer units in the CE and defined as rental 

equivalence by the BLS. The rental equivalence question from the CE interview follows: 

If someone were to rent your home today, how much do you think it would rent for 

monthly, unfurnished and without utilities? 

This question was asked of all consumer units who lived in their own house at the time of the interview or 

those who lived in such housing earlier during the quarterly interview period. For this study, consumer 

units who were living in housing that they owned at the time of the interview are assumed to have lived in 

that housing for the entire quarter; and the quarterly rental equivalence is assumed to reflect their shelter 

costs for the entire period. The sum of paid rent and an estimate of rental equivalence are assumed to be 

the shelter costs of consumer units who were renters at the time of the interview, but who lived in housing 

that they owned during an earlier period.18 Using rental equivalence, rather than out-of-pocket 

expenditures or outlays, suggests that when people answer the MSQ they are thinking about the cost of 

shelter consumption, in other words, how much they would need to rent their own home rather than what 

they would actually have to spend for the housing they current live in and own. Assuming rental 

 

16 The total expenditure outlays definition can be reproduced using the CE internal data base. In this study, ETOTAL is the same as in 

the BLS data base with two exceptions: it does not include expenditures that are only collected in the fifth interview like those for 

some miscellaneous items (zmisceL2) or for cash contributions (zcashctb). For this study, ETOTAL is defined as the sum of 

zfoodhom, zfoodxmp, zalcbevs, ehousing, zapparel, etranprt, zhealth, eentrmnt, zpercare, zreading, zeducatn, ztobacco, zmiscel1, 

emiscmrt, zfoodmap, zrentrap, and zperlins.

17 The BLS internal MTAB data file variable UCC ì910050î represents rental equivalence. The file values need to be multiplied by 4 

to obtain a monthly value and by 12 to obtain a quarterly value. 

18 Renters with positive rental expenditures (CE variable ZRENTXRP>) and who also reported positive owned housing expenditures 

(ZOWNDWLL>0) represented only 0.5 percent of the sample. There were no renters with zero rental expenditures but positive owner

expenditures. Owners with positive rental and owner expenditures represented about 0.4 percent of the sample. Thus the impact of 

assigning rental equivalence to renters for only one month is likely to not affect the results significantly. However, for current renters 

living in their owned housing for more than one month prior to becoming a renter, their shelter costs will be underestimated in the 

outlays with rental equivalence comparisons. For owners who lived in rental housing prior to becoming a homeowner, their shelter 

costs may be overestimated. Given the way that the CE rental equivalence data is recorded in the data base, we were not able to make 

any finer distinctions than these. 
18

equivalence for the shelter costs of owner occupants in a poverty threshold is consistent with the National 

Academy of Sciences (NAS) Panel on Poverty and Family Assistanceís recommendation.19

 While all items that one purchases could be considered ìessential,î we compared actual spending 

on selected commodities to the CE based derived MSQ thresholds. Each bundle is presented in the table 

below. The smallest bundle refers to the majority of items listed in the MSQ with: food, clothing, and 

shelter for primary residence. We include utilities as part of shelter for this exercise. These commodities are 

the same as those recommended by the NAS Panel upon which a new poverty threshold would be based 

(Citro and Michael 1995, p.6)20. 

Bundle One Outlays for food and non-alcoholic beverages at 

home and away from home, shelter and utilities outof-pocket expenses for primary residence, and 

apparel (food and rent as pay are not included) 

Bundle One plus Health Bundle One plus health care. 

Bundle Two Bundle One plus half of out-of-pocket 

transportation expenses and personal care 

Bundle Three Bundle Two plus expenditures for education and 

reading materials 

Bundle Four Bundle Three plus expenditures for household 

operations and household furnishings and 

equipment 

 The second bundle includes health care as a basic necessity. This follows the procedure followed 

by Short and Garner (2002) and Banthin et al. (2001). In contrast, the NAS Panel subtracted health care 

expenses from the resource side rather than including these in the basic bundle that served as the basis of 

the recommended poverty threshold. 

 The commodities identified for inclusion in bundles two and three are those used by the NAS 

Panel for the estimation of lower and higher multipliers used to derive the recommended threshold (Citro 

and Michael, 1995, Table 2-6, footnotes a and b; see Garner et al. 1998 for a replication). These bundles 

were selected by the NAS Panel as examples of what might be included in smaller and larger bundles, not 

what specifically would be included. Bundle two includes all those in bundle one plus one half of out-ofpocket transportation expenses and personal care. Transportation includes the purchase of vehicles, fuel, 

 

19 For example, see Garner et al. (1998) who produced experimental poverty thresholds that incorporated rental equivalence. 

20 For the NAS Panel report, the BLS publication definitions were used to define the bundles, not the out-of-pocket approach. In

addition, food and rent as pay were included in the bundles in food and shelter respectively. Short and Garner (2002) have not 

included food and rent as pay in their estimations of the experimental poverty thresholds since these could not be accounted for on the 

resource side. 
19

finance charges, maintenance and repairs, vehicle insurance, vehicle rental licenses, and public 

transportation. Personal care includes personal care services and appliances. Bundle three includes all of 

bundle two plus education and reading materials. Education includes school books, supplies, equipment, 

tuition and other school expenses including rentals. Reading includes newspapers, magazines, books, 

encyclopedias and other reference books. As a more expanded bundle for this study, the fourth includes 

those in bundle three plus those for household operations and household furnishings and equipment. 

Included are domestic services, babysitting and day care, and household furnishings and equipment. 

Household furnishings and equipment includes household textiles, furniture, floor coverings, appliances, 

house wares, and other household equipment. For the consumption expenditure-based comparisons, rental 

equivalence replaces the shelter out-of-pocket expenditures for owner occupants for the comparison to the 

thresholds. 

3. RESULTS 

Sample statistics, regression results, thresholds, and poverty rates are presented in this section. All 

results are assumed to be for 1995 although data are from the last half of the year. Table 3 reveals that the 

SIPP and CE weighted samples are quite similar according to the distributions of households and consumer 

units by the selected characteristics. However there are a few differences. The CE sample is slightly older, 

has fewer units with reference persons who have more than a high school education, has fewer units with 

self-employed reference persons, has slightly fewer adults on average, and has more units living in rural 

areas. The differences are not large but they are statistically significantly different.21 Insofar as the SIPP 

and CE samples are different in terms of their population representativeness, the assumption that the 

relationships implied by the MIQ and MSQ regression models are similar may be wrong. The results in 

Table 3 suggest, however, that applying the SIPP-based model coefficients to the CE is a useful exercise. 

 Regression coefficients are presented in Table 4 for the MIQ and MSQ using the SIPP data.22

These results reveal that the model fits the MIQ data better than the MSQ data. The adjusted R2

s are 0.326 

 

21 Standard errors of the means were produced to account for the complex sample design. For the SIPP, SAS PROC 

SURVEYMEANS with a stratum and cluster variable and household weights was used to produce the standard errors. Standard errors 

of the means were produced for the CE using a method of balanced half sampling. In this method, a number of replicate subsamples 

were formed from the set of sampled consumer units. Each replicate subsample is approximately half the size of the original sample 

and was constructed to reflect the stratification and clustering used in the survey sampling. Then the standard error of the mean was 

estimated based on the means of the subsamples (see BLS Handbook of Methods (BLS 1997a, p.165 for details). 22 Ordinary least squares regression is used for the estimation. 
20

and 0.234 respectively. This simpler model fits the data as well as the earlier model (Garner and Short 

2003a) with a more complex specification of characteristics (MIQ R2

=0.325 and the MSQ R2=0.235). 

 Responses to the MIQ are more sensitive to difference in income than are responses to the MSQ as 

revealed by the Ln(Y) coefficient: 0.273 and 0.201. Minimum spending increases less with actual income 

than does minimum income. The coefficients from the Garner and Short (2003a) models reveal similar 

results: 0.267 and 0.205. As noted earlier, the closer the value of the income coefficient to zero, the more 

absolute the resulting threshold would be. As hypothesized, a MSQ-based threshold is more absolute than 

one based on the MIQ. The earlier work of De Vos and Garner (1991), using CE data and responses to the 

MIQ in 1982, produced an income coefficient of 0.43 indicating that the subjective threshold, based on 

1982 CE data, was less absolute than the threshold based on the 1995 SIPP data. De Vos and Garner (1991) 

reported an income coefficient of 0.552 for the Netherlands in 1983 which is in the range of the value, 0.54, 

reported by Hagenaars and Van Praag (1985, p. 151) for a set of Western European countries. In contrast, 

Milanovic and Jovanovic (1999) reported preference drift of 0.14 to 0.23 for 1993 to 1996 Russia 

depending on the MIQ model specification. Lower levels of preference drift have also been reported for 

China. Gustafsson, Shi, and Sato (2002, forthcoming) reported preference drift coefficients ranging from 

0.27 to 0.40 using income and responses to a MSQ for 1999 China. These results are similar to those 

reported by Pan (2003) and Bishop, Luo, and Pan (2004) for 1995 China, but using consumption 

expenditures rather than income, and another version of the MSQ rather than the MIQ with coefficients 

from 0.21 to 0.27. 

 As expected, needs are greater as the number of children increases. They are also greater with 

increases in the number of adults in the household, age of the reference person, for owners, and for 

households living in what are considered higher costs areas (the Northeast and West). Higher education of 

the reference person and whether the reference person is a man also contribute to greater needs being 

reported, perhaps reflecting reference groups effects as noted by Hagenaars (1986). When the reference 

person is not working due to a disability, the income and spending needs are less based on these MIS and 

MSQ results. Being self-employed significantly increases oneís spending needs but not income needs. 

 Average total before-tax money incomes for the MIQ and MSQ weighted household samples are 

presented in Table 5, along with official poverty thresholds and the estimated MIQ and MSQ thresholds. 
21

Households were assigned official thresholds based on the age of the reference person in single and couple 

families, and the numbers of people and children for other households. The SIPP-based MIQ and MSQ 

thresholds are midway between average before-tax money income and the official poverty thresholds. 

 Table 6 includes average expenditure outlays with and without the adjustment for rental 

equivalence, and predicted MIQ and MSQ thresholds based on the SIPP coefficients. Note that the 

expenditures with rental equivalence are only slightly higher with the adjustment as compared to without 

the adjustment. 

 The MSQ thresholds, for both surveys, are about 69-70 percent of the MIQ thresholds using the 

two approaches for producing the thresholds. These are slightly higher than the ratios found in the work of 

Morissette and Poulin (1991) for Canada (58-65 percent for household sizes of one to six people). Vaughan 

(1993, 2004) reports that the average Gallup poverty threshold was 71.8 percent of the Gallup get-along 

threshold in 1989. The MIQ thresholds are about 90 percent higher than the official poverty threshold 

while the MSQ are only about 30 percent higher. 

 Official thresholds for the SIPP and CE weighted samples are produced for comparison in Tables 

5 and 6. As each household in the SIPP and each consumer unit in the CE are assigned their own 

thresholds, average thresholds across the populations differ from the thresholds published by the Census 

Bureau. The average official thresholds are quite similar for the CE and SIPP reflecting that the number of 

children and adults in the two weighted samples are very similar. This is not surprising as the CE and SIPP 

use the CPS as control totals. Differences are likely due to the fact that the data are collected from 

consumer units rather than households in the CE.23 For this study also all students living away from home 

are not included in the CE weighted sample but these students are included in the SIPP weighted sample as 

part of the parentís household. The ratios of the CE MIQ to SIPP MIQ thresholds and of the CE MSQ to 

SIPP MSQ threshold are 1.03, again reflections of the slight differences in the samples. 

 CE total expenditure outlays are on average 72 percent of before-tax money income from the 

SIPP. This suggests, on average, a difference of about $12,000 annually over and above what is already 

included in total expenditures. Bundle one (food, clothing, and shelter and utilities for primary residence) 

expenditures represent about half of all CE expenditure outlays and about one-third of SIPP before-tax 

 

23 About 96 percent of all consumer units were also households with no other consumer units present.
22

money income. The share of total expenditure outlays increases to about 55 percent when health care is 

added to bundle one, and the share of income to approximately 40 percent. Adjusting expenditure outlays 

by rental equivalence for owner occupants increases the percentage share of total outlays to just about 50 

percent and to 74 percent of SIPP before-tax money income. 

 The CE MSQ threshold looks like bundle one and the CE MIQ threshold looks like bundle four 

with the rental equivalence adjustment. The CE MSQ threshold is not statistically significantly different 

from expenditure outlays for bundle one at the 0.05 level, and the MIQ threshold is not significantly 

different from bundle four expenditures with the adjustment.24 

 The overall estimates presented in Table 6 may be misleading, however, for some demographic 

subgroups. Table 7 includes quarterly medians of CE based MIQ and MSQ thresholds and mean 

expenditure outlays for all items and for the various bundles for selected demographic groups. Table 8 

includes the means based on outlays adjusted for rental equivalence. These results indicate that certain 

subgroups have expenditures that are lower than the MSQ thresholds for their groups. This means, that on 

average, their spending is less than what they need based on their personal assessments of minimum 

financial needs. Relating this to Figure 1, these consumer units would be to the left of the intersection point 

of household before-tax money income and the minimums reported. Bundle one expenditure outlays are 

less than the MSQ thresholds for one-person consumer units aged 65 or younger, one- and two-person 

elderly consumer units, consumer units with seven or more people, single parents, renters, and for 

consumer units living in the Northeast, and very slightly in the South. 

 With increases in expenditures relative to the MSQ thresholds, consumers are considered to be 

better off with their spending greater than their assumed needs. When health care is added to the basic 

bundle of food, clothing, shelter, and utilities, we find that spending now exceeds the MSQ thresholds for 

most consumer units except people living alone, single parents, and renters. 

 Additional movements above the thresholds are seen with bundle two expenditures which include 

transportation and personal care along with food, clothing, shelter and utilities. Nearly all consumer units 

move above the MSQ threshold with bundle two expenditures. 

 

24 Standard errors of the predicted thresholds were produced using the same procedures used to produce the standard errors of the

sample means, accounting for the complex sample design of the SIPP. But the sampling variance in the regression coefficients was 

not accounted for in the estimation of the standard errors of the thresholds. 
23

 Two subgroups appear to have particularly high spending needs as reflected by their MSQ 

thresholds and out-of-pocket expenditures. This means that even with larger bundles of commodities, these 

consumers have greater needs than are reflected by the earlier bundles that might be considered sufficient. 

Consumer units composed of one adult with two children do not move above their MSQ threshold until 

expenditures for bundle four are considered. The group of consumer units who appear the worse off, 

relative to their personal assessments and derived MSQ thresholds are single-person consumer units aged 

65 and over. For none of the commodity bundles do their out-of-pocket expenditures exceed their MSQ 

threshold. 

 Replacing out-of-pocket shelter expenditures by the rental equivalence for owner-occupants 

improves the relative well-being position of most consumer unit subgroups. Of particular interest are 

single-person consumer units with the reference person greater than or equal to age 65 who now have 

adjusted expenditures only a couple of dollars short of the first MSQ threshold (with all characteristics 

allowed to vary) with bundle one expenditures. These results reveal the importance of owner- occupied 

housing particularly for elderly consumer units. 

 When deriving poverty thresholds, the NAS Panel (Citro and Michael 1995) recommended that 

rather than estimating thresholds for different family and household types directly that a reference family 

be used and other thresholds would be derived from the expenditures of this family. The NAS Panel 

recommended that the reference family be composed of two adults with two children, with the reference 

person less than age 65, and the children less than 18. For a consumer unit with two adults and two 

children,25 official thresholds and NAS Panel thresholds are about 85 percent of the MSQ threshold (when 

the characteristics are allowed to vary) for 1995 (results not shown). The MSQ threshold is 98 percent of 

the threshold (in 1995 dollars) that was produced by Renwick using a basic needs budget for the 

comparable family type with one working parent26 (1998; also see Renwick and Bergmann 1993), 90 

percent of the ìsyntheticî Gallup poverty threshold for four person families,27 and 80 percent of the 

 

25 See Table 7, MIQ and MSQ thresholds compared are those for consumer units with two adults with two children when the 

characteristics are allowed to vary. Unlike the NAS measure, there is no reference person age restriction for the MIQ and MSQ 

thresholds for this comparison and the two adults do not need to be married. However, like the NAS measure, children are less than 18 

years of age. 

26 Renwick and Bergmann (1993) used a categorical approach to define a poverty budget which they referred to as a basic needs 

budget (BNB) and produced these for 1989. Renwick (1998) updated the BNBs to 1996. The BNBs are based on adequacy standards. 

27 Information from Vaughan (1993, 2004) is used to used produce "synthetic" Gallup get along and poverty thresholds for 1995. This 

approach is the same as that followed by Vaughan in his production of synthetic Gallup poverty thresholds for the period 1947-1989 
24

Renwick threshold (in 1995 dollars) for the family with two working parents and two children. The MIQ 

threshold is 96 percent of the ìsyntheticî Gallup get-along threshold for the four person family. The MIQ 

threshold is 70 percent of the Prevailing Family Standard,28 based on the Expert Committee on Family 

Budgets recommendations (Watts 1980), and reported by Johnson et al. (2001) in 1995 dollars. The MIQ is 

79 percent of the mean of several market basket based budgets across the U.S. reported by Bernstein et al. 

(2000) in 1995 dollars. 29

 Above results are presented for the thresholds and expenditures to help us understand what the 

MIQ and MSQ might mean to respondents. Next we focus on the use of the thresholds in identifying 

households and consumer units who are below the thresholds and who thus would be considered worse off 

than those at or above the thresholds. In this section we refer to these rates as ìpovertyî rates. Percentages 

of consumers units from the CE and households from the SIPP below various thresholds are presented in 

Tables 9, 10, and 11. These results are based on the thresholds derived from the approach allowing all the 

characteristics to vary in the prediction of the thresholds. Table 9 includes percentages for the total 

populations and consumer unit or household size. A further distinction for one and two person units by age 

of the reference person (less than 65 years or greater than or equal to 65 years) is also presented in Tables 9 

and 10. It is important to note that the measures of family resources used for these comparisons are not 

necessarily consistent with the thresholds and should be interpreted as illustrations only. 

The before-tax income measure of resources, compared to the different thresholds, results in lower 

rates than obtained using the CE data. This is not surprising as the money income measure accounts for 

savings and income taxes that are not included in the CE expenditures outlays measures. As noted earlier, 

quarterly data were used for the analysis and thus expenditure outlays not counted in the CE measure used 

here are those for cash contributions for people outside the consumer unit, occupational expenses, and those 

 as described in Citro and Michael (1995). The ratio of average Gallup poverty to Gallup get along responses in 1989 (the 1989 data 

are considered more reliable than the 1992 data according to Citro and Michael (1995)) is 71.8 percent. The average Gallup get along 

response to median after tax money income for four person families is 69.6 percent over the 1961-1989 period. In order to produce a 

"synthetic" Gallup get along threshold for 1995, 69.6 percent is multiplied by the 1995 median after-tax money income for four person 

families ($40,917). The "synthetic" Gallup poverty threshold is derived by multiplying the 1995 get along threshold by 71.8 percent. 

The "synthetic" get along threshold for 1995 is $28,478 and the synthetic poverty threshold is $20,447. Vaughan (2004) reports a 

value of $20,458; the difference is due to rounding percentages. 

28 The Prevailing Family Standard would be the median expenditures of married couple families with two children less than 18. 

Johnson et al. (2001) produced these using an expenditures outlays definition. The budget did not include the payment of income taxes 

or allocations for savings. The median expenditure for this family in 1995 dollars is $38,789. 

29 These authors identified items that they deemed necessary for a working family to maintain ìa safe and decent standard of livingî 

(p.4) and produced a budget for a two-parent two-child family living in Baltimore. Family budgets were also presented for various 

states, and regions. The simple average of the budgets presented for two-parent two-child families is $34,470 in 1995 dollars.
25

associated with miscellaneous expenses like finance charges. Expenditures for these items are only 

collected in the fifth interview. Using an outlays measure that could be used with quarterly data, results in 

totals that are lower than what they would have been if a full accounting of all expenditures were included. 

 The official SIPP-based poverty rate for households is 9.8 percent when based on the MIQ 

weighted sample using income. The percentage of households below the SIPP MIQ threshold is 26 percent. 

Higher rates result when quarterly expenditure outlays are used. When the official poverty thresholds are 

compared to expenditure outlays, consumer unit poverty is 12.4 percent. MSQ thresholds result in lower 

poverty for the CE with 19.3 percent of all consumer units having total expenditure outlays below the MSQ 

threshold. Rental equivalence results in a poverty rate for consumer units in the CE of 13.8 percent for the 

CE based MSQ thresholds. 

 The highest rates using the personal assessment based thresholds are for the single elderly in the 

SIPP (Tables 9). MIQ poverty rate for this group is 41.6 percent and 35.4 for the MSQ. Rates are higher 

for the CE expenditures outlays measure as compared to the SIPP measure: 57.2 for the MIQ and 45.5 for 

the MSQ. In contrast, the highest rates when the official poverty thresholds are used are for six-person or 

seven or more person households in the SIPP and CE weighted samples. SIPP before-tax money income 

official threshold based rates range from 21.2 percent to 28.3 percent. The CE expenditures outlays 

official threshold rates are about 46 percent for consumer units with seven or more people. 

 The presence of a second adult in an elderly household or consumer unit makes an enormous 

difference in poverty rates (Table 10). Moving from households or consumer units with one elderly person 

to couple units, with the reference person greater or equal to 65 years of age, reduces poverty using the 

official poverty threshold from 16-19 percent to about 5 percent. CE expenditure-based official threshold 

poverty falls from 26 percent to about 9 percent when total expenditure outlays are used, and from 14.2 

percent to 3.2 percent with rental equivalence. SIPP MIQ and MSQ poverty rates using before-tax money 

income fall from 42 percent and 35 percent to 14 and 9 percent, respectively. The CE expenditure outlays 

poverty rate using the MIQ falls from 57 percent to 30 percent and the MSQ-based rate falls from 46 

percent to 18 percent. As with the official thresholds, rental equivalence makes a substantial difference for 

elder consumer units. The MSQ-based poverty rate, using the CE, drops from 46 percent to 26 percent for 

one person elderly consumer units, and from 18 to 6 percent for couple elderly consumer units. These 
26

results suggest that a resource measure based more on consumption (e.g., the value of the flow of services 

from owner-occupied housing) as opposed to spending needs would result in lower subjective poverty 

rates. 

 Implicitly the MIQ and MSQ thresholds are adjusted for differences in the costs of living by 

region. This is because consumer units would be expected to respond to the MIQ and MSQ-based on the 

costs of living they face in their immediate geographic areas. In contrast, official poverty thresholds are not 

adjusted for geographic differences in prices. Regions can differ in other ways in addition to costs as well 

with the impact of these differences reflected in the thresholds and resulting poverty rates. 

 To show the effect of accounting for differences in region and the use of personal assessment 

questions for threshold estimation, percentages of consumer units from the CE and households from the 

SIPP are presented by region in Table 11 and are compared to official threshold based rates. The first panel 

in Table 11 reveals the greatest percentage of consumer units and households who are worse off, according 

to official thresholds, using either income or expenditure outlays, live in the South. Those in the West are 

marginally worse off than those in the South when rental equivalence is used in the resource measure. In 

contrast, consumer units and households living in the Northeast are worse off relative to those living in 

other regions when the MIQ and MSQ thresholds are assumed. 

Results by region that reflect differences in cost of living are of particular interest for the 

development of experimental poverty measures (see Short 2001a, b). Results from this study suggest 

reasonable outcomes for poverty thresholds that are adjusted to take account of differences in thresholds by 

geographic area. Higher thresholds are indicated for the Northeast and West based on the results from the 

CE (Table 7) and SIPP (not shown) using both approaches (i.e., allowing the other model characteristics to 

vary or holding their values at the national means) to produce the thresholds, and are also reflected in the 

published experimental measures that have been accordingly adjusted (see Short 2001a). 

4. CONCLUSION 

 

 Differences in economic well-being result if one uses expenditure outlays as opposed to income, 

and also when different well-being thresholds are assumed. Replacing out-of-pocket expenditures with 

rental equivalence for owner-occupants can also change their economic well-being status. Higher well-
27

being results with SIPP income as opposed to CE expenditure outlays regardless of the threshold: the MIQ, 

MSQ, or official thresholds. Accounting for the value of housing consumption, rather than housing out-ofpocket expenditures, also increases well-being. 

 Caution needs to be applied when a consumption-based resource measure such as the one used in 

this study is compared to income or spending needs thresholds however. Consistency between the threshold 

and resource measure should be a basic requirement for any well-being or poverty measure. Comparing a 

consumption-based resource measure, like outlays with the rental equivalence adjustment, to an income or 

spending needs based measure may not result in a consistent measure of poverty or well-being, depending 

upon respondentsí interpretations of the MIQ and MSQ. If a consumption-based measure is consistent with 

official poverty thresholds depends on what one considers as the underlying needs concept in official 

poverty. 

 Which resource measure is more appropriate to use with the MIQ as opposed to the MSQ is also a 

question, although results were presented for income and outlays both for illustration purposes. If, as with 

the MIQ, the focus is on income and the level of income necessary to make ends meet, then income is the 

more appropriate resource measure. If spending is the focus, then expenditure outlays would be the better 

measure. 

 In determining which of the personal assessment questions is best for determining well-being or 

poverty status, again, the researcherís or policymakerís goal must be clear. Is the goal to produce a 

threshold that reflects some social minimum standard as might be reflected in a MIQ-based threshold? Is 

the goal to produce a threshold based on a very specific set of commodities and what is spent on these as 

reflected in a MSQ threshold? Each threshold will provide information about the well-being of a society, 

but each tells us something different; the two thresholds are not substitutes for each other, just as 

expenditures are not a substitute for income as a resource measure. 

 Results in this study clearly support the notion that the MIQ and MSQ reflect different needs, with 

the MIQ referring to a broader set of needs than the MSQ. The MIQ allows respondents to formulate more 

freely what is needed to make ends meet while the MSQ directs respondents to think of a certain set of 

commodities. However, respondents have discretion in defining what they understand constitutes barely 

adequate food, clothing, shelter, and other necessities along with the level. In comparing expenditure 
28

outlays with the MSQ thresholds, we find that on average, consumer units actually spend for food, clothing, 

shelter, and utilities an amount that differs very little from the median MSQ threshold. Differences by 

consumer unit characteristics arise, however, with the most dramatic results for the elderly. 

 The highest well-being results for the U.S. population when official poverty thresholds are 

assumed. However, the current official thresholds have been criticized as inadequate for the U.S. today 

(e.g., Citro and Michael 1995). This criticism may be warranted based on the analysis of personal 

assessments of economic needs presented in this study. These results reveal that minimum spending needs 

appear to reflect, on average, what consumers actually spend on the four basic commodities noted, and this 

spending, and reported needs, are greater than the official poverty thresholds. 

 To better understand the relationship between spending needs and actual spending, it would be 

desirable for the MSQ to be collected in the same survey as total expenditures and subsets of these 

expenditures. Then the relationship between minimum spending and actual reported spending might be 

tested. 
29

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33

Table 1. SIPP Sample Distribution by Assignment (total sample n=17,572) 

 

Minimum

Income Sample

Minimum

Spending Sample

Half Samplea 8853 8713

Observations for regression-intersection modelb 6332 6292

a Six households assigned to the Basic Needs Module did not answer the MIQ or MSQ. 

b Positive minimum values reported and full set of regressors. 

 

Table 2. Distribution of Paritcipating SIPP Sample by Reference Period 

Time Period 

Minimum

Income Sample

Minimum 

Spending Sample

Week 6.0 7.6

Bi-weekly 0.4 0.4

Monthly 25.8 38.3

Yearly 67.8 53.7
Table 3. Weighted Sample Means and Standard Errors of Variables Included in SIPP Regressions of Ln (Xmin) and in Prediction Equation for the CE 

U.S. MIQ 1995 U.S. MSQ 1995 U.S. CE 1995Q4-1996Q1 CE and CE and

(n=6332) (n=6292) (n=9397) SIPP MIQ SIPP MSQ

Weighted Weighted

Mean Standard Mean Standard Mean Standard Samples Samples

 Error of Mean Error of Mean Error of Mean Differ Differ

Annualized Reported Minimum Income $28,938 $289 na na na naAnnualized Reported Minimum Spending na na $21,066 $192 na naAnnualized Total Expenditure Outlays na na na na $30,417 $449Annualized Total Expenditures with Rental Equivalence1 na na na na $31,537 $425Annualized Before Tax Money Income $42,344 $730 $43,932 $1,224 na naQuarterly Reported Minimum Income $7,234 $72 na na na na Quarterly Reported Minimum Spending na na $5,267 $48 na na Quarterly Total Expenditure Outlays na na na na $7,604 $112 Quarterly Total Expenditures with Rental Equivalence1 na na na na $7,884 $106 Quarterly Before Tax Money Income $10,586 $182 $10,983 $306 na na Reference Person 

Age 48.082 0.281 47.735 0.233 48.248 0.205 bAge2 2599.0 29.818 2558.9 23.997 2632.560 21.141 aMale 0.628 0.007 0.638 0.007 0.622 0.013 Black 0.117 0.005 0.113 0.005 0.116 0.004 Hispanic 0.092 0.005 0.083 0.006 0.078 0.007 High School Grad 0.327 0.006 0.336 0.006 0.332 0.008 > High School 0.499 0.008 0.497 0.007 0.458 0.010 a aWork Disabled 0.051 0.003 0.051 0.003 0.051 0.003 Self-employed 0.073 0.003 0.077 0.003 0.056 0.003 a a

Ln(1+Number of adults) 1.012 0.004 1.019 0.004 1.008 0.004 b Number of adults 1.848 0.011 1.866 0.011 1.842 0.013 Ln(1+Number of children <18) 0.381 0.008 0.391 0.008 0.375 0.007 Number of children <18 0.720 0.016 0.741 0.018 0.704 0.015 Own home 0.640 0.008 0.638 0.008 0.646 0.006 Northeast 0.201 0.008 0.199 0.007 0.197 0.006 Midwest 0.242 0.008 0.249 0.008 0.247 0.006 West 0.224 0.009 0.206 0.008 0.209 0.008 City 0.389 0.011 0.381 0.011 0.382 0.013 Rural 0.238 0.013 0.242 0.010 0.266 0.011 b1 Rental equivalence of primary residence replaced for outlays for owners; 

outlay expenditures for other properties. 

a Statistically significant at the p=0.05 level 
1

b Statistically significant at the p=0.10 level 

SIPP standard errors produced using SAS Proc Surveymeans. 

CE standard errors produced using the balanced repeated replication method of variance estimation. Consumer units living in college or university housing excluded from CE sample; represented 1.7% of original sample or 164 cases. 

Source: 1993 SIPP-9th wave and Consumer Expenditure Survey data 1995Q4 and 1996Q1. 
2

Table 4. Coefficients and Standard Errors from SIPP Minimum Income and Spending Regressions (unweighted regressions) 

U.S. MIQ 1995 (n=6332) U.S. MSQ 1995 (n=6292) MIQ and MSQ

Coefficient Standard Coefficient Standard Coefficients

 Error Error Differ

Intercept 6.359 a 0.121 6.767 a 0.123 aLn(Y) 0.273 a 0.012 0.201 a 0.012 a

Reference Person 

Age note 0.228 a 0.031 0.202 a 0.031 

Age2 note -0.003 a 0.000 -0.002 a 0.000 Male 0.107 a 0.018 0.078 a 0.018 Black 0.035 0.029 -0.047 0.029 a

Hispanic 0.001 0.032 -0.011 0.033 High School Grad 0.101 a 0.025 0.056 a 0.026 

> High School 0.281 a 0.026 0.193 a 0.026 a

Work Disabled -0.157 a 0.040 -0.094 a 0.040 

Self-employed 0.015 0.031 0.080 a 0.030 

Ln(1+Number of adults) 0.075 a 0.037 0.126 a 0.038 Ln(1+Number of children <18) 0.114 a 0.017 0.171 a 0.017 a

Own Home 0.121 a 0.020 0.127 a 0.020 

Northeast 0.172 a 0.023 0.165 a 0.023 Midwest -0.030 0.021 -0.013 0.021 West 0.044 a 0.023 0.046 a 0.023 City 0.025 0.018 0.013 0.019 Rural -0.077 a 0.021 -0.111 a 0.021 Adjusted R2 0.326 0.234 

a Statistically significant at the p=0.05 level b Statistically significant at the p=0.10 level 

Note: Coefficent and standard error for Age have been multiplied by 10 for presentation;  coefficient and standard error for Age2 have been multiplied by 10 for presentation 

Source: 1993 Survey of Income and Program Participation (SIPP), 9th wave, and calculations by Garner and Short (2003b). 
3

Table 5. Mean Quarterly and Annualized SIPP Before Tax Money Income, and Estimated Median Minimum Value Thresholds (SIPP Population Weighted Households ) 

Quarterly 

Annual 

Estimate

 Before Tax Money Income-MIQ Sample $10,586 $42,344 Before Tax Money Income-MSQ Sample 10,983 43,932

Allowing all characteristics to vary 

 MIQ Theshold $5,451 $21,804 MSQ Theshold 3,755 15,018

Characteristics set at national means 

 MIQ Theshold $5,139 $20,556 MSQ Theshold 3,617 14,469 Official based on MIQ Weighted Samplea $2,839 $11,355

 Official based on MSQ Weighted Samplea 2,865 11,460

aOfficial poverty thresholds are for families but are applied to SIPP households. Source: 1993 SIPP-9th wave and Consumer Expenditure Survey data 1995Q4 and 1996Q1. 
4

Table 6. Mean Quarterly and Annualized CE Outlays, and Estimated Median Minimum Value Thresholds (CE Population Weighted Consumer Units) 

Quarterly Annual Estimate

Total Expenditure Outlays $7,604 $30,417Bundle One 3,733 14,930Bundle One plus Health 4,150 16,599Bundle Two 4,457 17,827Bundle Three 4,624 18,496Bundle Four 5,043 20,174Total Expenditure Outlays Adjusted for Rental Equivalence $7,884 $31,537Bundle One 4,013 16,050Bundle One plus Health 4,430 17,719Bundle Two 4,737 18,946Bundle Three 4,904 19,616Bundle Four 5,323 21,294

Allowing all characteristics to vary 

 MIQ Thresholds Using SIPP Coefficients $5,287 $21,147 MSQ Thresholds Using SIPP Coefficients 3,649 14,595

Characteristics set at national means 

 MIQ Thresholds Using SIPP Coefficients $4,991 $19,965 MSQ Thresholds Using SIPP Coefficients 3,521 14,085

 Officiala $2,882 $11,527

aOfficial poverty thresholds are for families but are applied to SIPP households. Bundle One: outlays for food at home and away from home, shelter expenses for primary residence, utilities, apparel. Bundle One plus Health: outlays for food at home and away from home, shelter expenses for primary residence, utilities, apparel, and health care. Bundle Two: Bundle One plus half of transportation expenses, personal care. Bundle Three: Bundle Two plus expenditures for education and reading materials. Bundle Four: Bundle Three plus expenditures for household operations and household furnishings and equipment. Source: Consumer Expenditure Survey data 1995Q4 and 1996Q1. 
5

Table 7. Quarterly Estimated Median Minimum Thresholds and Mean Consumer Expenditure Outlays (CE Population Weighted Consumer Units) 

Characteristics Allowed 

to Vary 

Other Characteristics Set 

to Means 

 Median Median Median Median Total BundleConsumer Unit Size MIQ MSQ MIQ MSQ Expenditure Bundle One plus Bundle Bundle Bundle

Threshold Threshold Threshold Threshold Outlays One Health Two Three Four

1 person $4,321 $2,966 $4,555 $3,092 $4,618 $2,399 $2,686 $2,783 $2,884 $3,097

 one person, <65 5,007 3,183 4,917 3,184 5,352 2,697 2,890 3,162 3,297 3,552 one person, >=65 3,029 2,558 3,438 2,775 3,236 1,838 2,300 2,070 2,107 2,239

2 persons 4,922 3,432 4,779 3,322 7,732 3,602 4,112 4,374 4,517 4,961

 2 people, ref. <65 5,378 3,560 5,171 3,432 8,424 3,930 4,302 4,772 4,945 5,399 2 people, ref. >=65 3,891 3,143 3,587 2,960 6,168 2,861 3,681 3,473 3,549 3,969

3 people 5,728 3,880 5,193 3,725 8,937 4,389 4,816 5,267 5,482 5,9814 people 6,498 4,430 5,544 4,075 10,084 4,958 5,436 5,864 6,123 6,7605 people 6,587 4,603 5,819 4,355 10,035 5,033 5,450 6,099 6,324 6,8086 people 6,688 4,764 6,024 4,570 9,457 5,087 5,440 6,033 6,269 6,6867 people or more 6,473 4,936 6,345 4,927 8,629 4,561 4,869 5,440 5,570 6,015

Consumer Unit Compositiona One adult, no children, ref. <65 $5,007 $3,183 $4,917 $3,184 $5,352 $2,697 $2,890 $3,162 $3,297 $3,552 One adult, no child, ref.>=65 3,029 2,558 3,438 2,775 3,236 1,838 2,300 2,070 2,107 2,239 Two adults, no children, ref.<65 5,429 3,592 5,126 3,394 8,886 4,073 4,467 4,976 5,167 5,637 Two adults, no children, ref.>=65 3,894 3,144 3,585 2,958 6,186 2,864 3,687 3,479 3,556 3,979 Three adults, no children 5,332 3,738 4,892 3,449 9,863 4,601 5,203 5,630 5,950 6,378 One adult, one child 4,980 3,328 5,080 3,587 5,180 2,916 3,151 3,331 3,386 3,715 One adult, two children 5,176 3,524 5,415 3,913 4,815 2,944 3,103 3,316 3,354 3,667 Two adults, one child 6,077 4,045 5,296 3,824 9,482 4,639 5,041 5,565 5,768 6,353 Two adults, two children 6,810 4,589 5,646 4,171 10,014 4,959 5,424 5,808 6,013 6,747 Two adults, three children 6,816 4,700 5,907 4,436 10,103 4,993 5,434 6,059 6,186 6,752Housing Tenure  Own $5,593 $3,900 $5,296 $3,725 $8,833 $4,199 $4,728 $5,054 $5,250 $5,761 Rent 4,728 3,191 4,481 3,179 5,364 2,882 3,097 3,368 3,483 3,736Region of Residence  Northeast $6,242 $4,224 $6,019 $4,126 $8,108 $4,194 $4,606 $4,899 $5,138 $5,575 Midwest 4,834 3,422 4,558 3,299 7,596 3,576 3,995 4,340 4,510 4,938 South 4,886 3,364 4,753 3,354 6,978 3,320 3,765 4,017 4,165 4,558 West 5,588 3,848 5,053 3,551 8,180 4,170 4,543 4,908 5,037 5,475
6

Degree of Urbanization  City $5,417 $3,679 $5,246 $3,692 $7,186 $3,694 $4,033 $4,353 $4,525 $4,888 Suburb 5,473 3,839 5,065 3,630 8,258 4,017 4,468 4,768 4,960 5,477 Rural 4,852 3,353 4,558 3,160 7,336 3,410 3,896 4,191 4,320 4,690a These categories represent 88.7 percent of all 

consumer units. 

Source: Consumer Expenditure Survey data are from 1995Q4 and 1996Q1. Coefficients used for CE thresholds are based on data from the 1993 SIPP-9th wave. 
7

Table 8. Quarterly Estimated Median Minimum Thresholds and Mean Consumer Expenditure Outlays with Rental Equivalence Adjustment (CE Population Weighted Consumer Units) 

Characteristics Allowed 

to Vary 

Other Characteristics Set 

to Means 

 Median Median Median Median BundleConsumer Unit Size MIQ MSQ MIQ MSQ Total Bundle One plus Bundle Bundle Bundle 

Threshold Threshold Threshold Threshold Expenditures One Health Two Three Four

1 person $4,321 $2,966 $4,555 $3,092 $4,950 $2,731 $3,018 $3,115 $3,216 $3,429

 one person, <65 5,007 3,183 4,917 3,184 5,479 2,823 3,017 3,289 3,424 3,679 one person, >=65 3,029 2,558 3,438 2,775 3,955 2,556 3,018 2,788 2,825 2,958

2 persons 4,922 3,432 4,779 3,322 8,254 4,124 4,634 4,896 5,039 5,483

 2 people, ref. <65 5,378 3,560 5,171 3,432 8,755 4,261 4,633 5,103 5,276 5,730 2 people, ref. >=65 3,891 3,143 3,587 2,960 7,122 3,815 4,635 4,427 4,503 4,923

3 people 5,728 3,880 5,193 3,725 9,014 4,466 4,893 5,344 5,558 6,0584 people 6,498 4,430 5,544 4,075 10,046 4,920 5,398 5,826 6,085 6,7225 people 6,587 4,603 5,819 4,355 10,215 5,214 5,631 6,280 6,505 6,9896 people 6,688 4,764 6,024 4,570 9,606 5,237 5,589 6,182 6,419 6,8367 people or more 6,473 4,936 6,345 4,927 8,941 4,872 5,181 5,752 5,882 6,327

Consumer Unit Compositiona One adult, no children, ref. <65 $5,007 $3,183 $4,917 $3,184 $5,479 $2,823 $3,017 $3,289 $3,424 $3,679 One adult, no child, ref.>=65 3,029 2,558 3,438 2,775 3,955 2,556 3,018 2,788 2,825 2,958 Two adults, no children, ref.<65 5,429 3,592 5,126 3,394 9,235 4,423 4,816 5,326 5,516 5,987 Two adults, no children, ref.>=65 3,894 3,144 3,585 2,958 7,146 3,824 4,647 4,439 4,516 4,938 Three adults, no children 5,332 3,738 4,892 3,449 10,109 4,847 5,448 5,875 6,195 6,623 One adult, one child 4,980 3,328 5,080 3,587 5,390 3,126 3,361 3,541 3,596 3,925 One adult, two children 5,176 3,524 5,415 3,913 5,001 3,130 3,290 3,502 3,541 3,853 Two adults, one child 6,077 4,045 5,296 3,824 9,442 4,599 5,001 5,525 5,728 6,313 Two adults, two children 6,810 4,589 5,646 4,171 9,921 4,866 5,331 5,714 5,919 6,654 Two adults, three children 6,816 4,700 5,907 4,436 10,310 5,200 5,641 6,266 6,392 6,958Housing Tenure  Own $5,593 $3,900 $5,296 $3,725 $9,276 $4,642 $5,170 $5,497 $5,693 $6,204 Rent 4,728 3,191 4,481 3,179 5,348 2,866 3,080 3,352 3,467 3,719Region of Residence  Northeast $6,242 $4,224 $6,019 $4,126 $8,345 $4,431 $4,843 $5,136 $5,375 $5,812 Midwest 4,834 3,422 4,558 3,299 7,833 3,812 4,232 4,577 4,747 5,174 South 4,886 3,364 4,753 3,354 7,335 3,677 4,122 4,374 4,522 4,914 West 5,588 3,848 5,053 3,551 8,424 4,414 4,787 5,152 5,281 5,719
8

Degree of Urbanization  City $5,417 $3,679 $5,246 $3,692 $7,378 $3,886 $4,225 $4,546 $4,717 $5,081 Suburb 5,473 3,839 5,065 3,630 8,559 4,318 4,768 5,069 5,260 5,777 Rural 4,852 3,353 4,558 3,160 7,715 3,788 4,274 4,569 4,698 5,069a These categories represent 88.7 percent of all 

consumer units. 

Source: Consumer Expenditure Survey data are from 1995Q4 and 1996Q1. Coefficients used for CE thresholds are based on data from the 1993 SIPP-9th wave. 
9

Table 9. Percentage of CUs or Households Below Various Thresholds by CU/Household Size: 1995 (CE CU Population Weighted; SIPP Sample Household Population Weighted) 

CE Expenditure Outlays CE Expenditures with 

Minimum Income Rental Equivalence 

 Adjustment 

CU/Household Size MIQ Official MIQ Official MIQ Official1 person 0.407 0.146 0.581 0.169 0.496 0.114 one person, <65 0.402 0.138 0.586 0.122 0.564 0.099 one person, >=65 0.416 0.161 0.572 0.257 0.369 0.1422 people 0.188 0.062 0.296 0.074 0.209 0.045 2 people, ref. <65 0.206 0.069 0.293 0.066 0.234 0.049 2 people, ref. >=65 0.141 0.045 0.303 0.093 0.152 0.0363 people 0.215 0.062 0.298 0.088 0.259 0.0724 people 0.204 0.084 0.290 0.110 0.272 0.0975 people 0.220 0.123 0.277 0.166 0.261 0.1496 people 0.330 0.236 0.347 0.271 0.318 0.2647 people or more 0.218 0.212 0.420 0.458 0.371 0.412 Total 0.260 0.098 0.377 0.124 0.315 0.093Minimum Spending CU/Household Size MSQ Official MSQ Official MSQ Official1 person 0.265 0.146 0.352 0.169 0.255 0.114 one person, <65 0.217 0.124 0.297 0.122 0.253 0.099 one person, >=65 0.354 0.188 0.455 0.257 0.257 0.1422 people 0.098 0.063 0.141 0.074 0.074 0.045 2 people, ref. <65 0.101 0.069 0.121 0.066 0.081 0.049 2 people, ref. >=65 0.090 0.049 0.186 0.093 0.058 0.0363 people 0.125 0.100 0.123 0.088 0.096 0.0724 people 0.112 0.099 0.107 0.110 0.097 0.0975 people 0.091 0.109 0.114 0.166 0.098 0.1496 people 0.189 0.222 0.202 0.271 0.188 0.2647 people or more 0.183 0.283 0.241 0.458 0.205 0.412 Total 0.150 0.106 0.193 0.124 0.138 0.093Source: 1993 SIPP-9th wave and Consumer Expenditure Survey data 1995Q4 and 1996Q1. Allowing characteristics to vary in prediction model. 
10

Table 10. Percentage of Single and Couple CUs or Households Below Various Thresholds by Age of Reference Person: 1995 

(CE CU Population Weighted; SIPP Sample Household Population Weighted)  SIPP Total Before Tax Money Income CE Expenditure Outlays CE Expenditures with 

 Rental Equivalence  Adjustment CU/Household Size MIQ 

Official 

(MIQ sample) MSQ

Official 

(MSQ 

sample) MIQ MSQ Official MIQ MSQ Official 

1 person  one person, <65 0.402 0.138 0.217 0.124 0.586 0.297 0.122 0.564 0.253 0.099 one person, >=65 0.416 0.161 0.354 0.188 0.572 0.455 0.257 0.369 0.257 0.142two adults, no children  2 people, ref. <65 0.149 0.045 0.067 0.038 0.254 0.098 0.047 0.193 0.058 0.030 2 people, ref. >=65 0.140 0.045 0.087 0.046 0.301 0.184 0.089 0.147 0.055 0.032Allowing characteristics to vary in prediction model. 
11

Table 11. Percentage of CUs or Households Below Various Thresholds by Region: 1995 (SIPP Sample Household Population Weighted; CE CU Population Weighted)  SIPP Total Before Tax Money Income CE Expenditure Outlays CE Expenditures with 

Rental Equivalence 

 Adjustment Region MIQ 

Official 

(MIQ 

sample) MSQ 

Official 

(MSQ 

sample) MIQ MSQ Official MIQ MSQ Official 

Northeast 0.318 0.103 0.179 0.096 0.459 0.249 0.106 0.399 0.186 0.081Midwest 0.197 0.078 0.117 0.087 0.306 0.147 0.100 0.245 0.098 0.078South 0.270 0.118 0.157 0.130 0.379 0.200 0.147 0.311 0.142 0.104West 0.261 0.088 0.152 0.100 0.381 0.184 0.132 0.324 0.131 0.105 Total 0.260 0.098 0.150 0.106 0.377 0.193 0.124 0.315 0.138 0.093Allowing characteristics to vary in prediction model.