INCOME SUFFICIENCY, EXPENDITURES AND SUBJECTIVE POVERTY:

RESULTS FROM THE UNITED STATES AND THE NETHERLANDS

Thesia I. Garner

U. S. Bureau of Labor Statistics

600 E Street NW, Washington, D.C. 20212

and

Klaas de Vos

Erasmus University

P.O.Box 1738, 3000 DR Rotterdam, the Netherlands1

1. Introduction

In recent years there has been a renewed interest among social science researchers and 

policymakers concerning the definition, measurement, and incidence of poverty. With 

government agencies producing statistics for quite sorts time concerning the incidence of 

poverty and the characteristics of poor individuals and households, there have also been 

parallel activities to improve the identification and measurement of poverty. This has been 

particularly true within the United States (U.S.), countries in Europe, Canada and Australia.

Since the early 1980's, research activities in the U.S. have focused primarily upon the 

impact on poverty statistics of using different definitions of income. Recent activities have 

included examinations of alternative methods for valuing selected in-kind transfer benefits and 

their effects upon poverty, and the effect of taxes on poverty (Census 1985, 1988). Researchers 

at the U.S. Bureau of the Census also conducted a study of the sensitivity

__________________________

1The views expressed in this paper are those of the authors and do not reflect the policies of the US. 

Bureau of Labor Statistics. The research of De Vos was partly made possible by a grant from the Dutch 

Foundation for the Advancement of Research in the Economic Sciences (ECOZOER), part of the 

Netherlands Organization for Scientific Research. Thanks to Mary Kokoski, Dennis Fixler, Kimberly D. 

Zieschang, Marshall Reinsdorf, Gordon Fischer, Patricia Ruggles, Connie Sorrentino, and other 

colleagues at the Bureau of Labor Statistics for comments, and to Anna Sanders and Richard Miller for 

assistance in manuscript preparation and research assistance, respectively. Final revisions to the 

manuscript were made when Garner was a visiting Fulbright scholar at the institute of Sociology, Czech 

Academy of Sciences, in Prague.
in the poverty rates of using a different price index to update poverty thresholds than the one 

which is used for the official poverty measure (Census 1989). Research has also included an 

examination of the impact of using different normative consumption standards for measuring 

poverty, for example by changing the market basket and the multiplier upon which the U.S. 

standard is based (Ruggles 1990). In addition to studies on the official poverty measure, research 

has also been conducted using subjective measures (e.g.,. Blaylock and Smallwood 1986; 

Colasanto, Kapteyn and Van der Gaag 1984; Danziger et al. 1984; De Vos and Garner 1991; 

Dubnoff 1982; Vaughan 1991). Recently, Congressional hearings were held by the Joint 

Economic Committee (JEC) to ask questions about the accuracy of the U.S. official measure of 

poverty compared to other measures of poverty (Congress 1990) and effectiveness of the 1960's 

War on Poverty programs (Congress 1991). In response, and under the initial direction of the 

Congress, a distinguished National Academy of Sciences Panel was formed to examine issues 

related to poverty and family assistance.

Activities within Europe have included pilot programs to identify and combat poverty, 

and efforts to more fully understand what is meant by poverty. Unlike in the U.S., where 

official poverty is based upon an absolute standard, in Europe poverty is generally considered 

to be a phenomenon of relative rather than absolute deprivation. On the level of the European 

Community this view is strengthened by the diversity among the Member States. Therefore, 

the European Community has been supporting research to further the development of poverty 

masurement. Attention has focused on determining which resources are to be measured, what 

is the most appropriate unit of observation, and how is the minimum acceptable way of life to 

be defined (e.g., Teekens and Van Praag 1990). Unlike in the U.S., where income is used a the 

resource to determine who is poor, Europeans are considering the use of household 

expenditures as an alternative to household income as an important poverty indicator (e.g., 

Eurostat 1990). Researchers in Europe have also been looking at alternative definitions for 

determining the minimum acceptable way of life as the basis for defining poverty, including 

those based on the notion forwarded by the Leyden school that a measure of poverty can 

possibly be derived from the perception of individuals within a society (see, e.g., Van Praag, 

Hagenaars and Van Weeren 1982; Hagenaars 1986; Kapteyn, Kooreman and Willemse 1988; 

Deleeck 1989).

Activities in Canada to evaluate the extent and nature of poverty have focused mostly 

on data collection and analysis by Statistics Canada. For over 20 years, Statistics
Canada has been publishing a series of "Low Income Cut-Offs" (LICOs), as well as statistics 

on individuals and families whose incomes are below the LICOs. LICOs are based on the 

proportion of expenditures allocated to "necessities". These LICOs are often considered as 

Canada's semi-official poverty lines. More recent efforts include Statistics Canada's conducting 

a series of experiments into two types of subjective income questions based on the Leyden 

approach. One is an income evaluation question and the other is a minimum income type of 

question. Both questions have been asked in supplements to the Survey of Consumer Finances 

(Morisette and Poulin 1991; Poulin 1985, 1988, 1989a, 19896; Wolfson and Evans 1989).

Researchers and statistical agencies in other countries have also been focusing on 

poverty as well as other masures of economic well-being of their populations. For example, 

Saunders and Bradbury (1989) have produced a study of the consensual approach to poverty 

measurement for Australia, while Whiteford (1985) focused on the relationship between 

poverty and social security.

The result of all of these activities has ban the production of numerous articles and the 

convening of conferences to advance our knowledge and understanding of poverty, both 

nationally and internationally (e.g., Institute for Research on Poverty 1992; Teekens and Van 

Pmag 1990, Polish Statistical Association 1992).

Poverty can be defined generally in a variety of ways: absolutely, relatively, and 

subjectively. An absolute definition reflects a standard below which basic needs cannot be met. 

Relative definitions consider one's relative position in a distribution (e.g., with respect to 

income or expenditures) as crucial. Subjective definitions are based upon the opinions of 

people about their own situation (e.g., about the income Level minimally necessary to make 

ends meet).

Absolute and relive definitions have been used for producing poverty statistics most

often. Subjective definitions arc a fairly new development. Subjective definitions are based on 

the idea that the opinions of people concerning their own situation should ultimately be the 

decisive factor in defining poverty. In this paper we primarily concentrate on a subjective 

definition, defined in terms of income sufficiency, as introduced by Goedhart et al. (1977), 

where income sufficiency is defined in terns of answers to the so-called Minimum Income 

Question (MIQ), which asks for the monetary amounts that
people consider to be minimally necessary to make ends meet for their households. These 

minimum income values err used to produce income sufficiency or subjective poverty 

thresholds. These thresholds are calculated as the income Level at which perceived minimum 

income equals reported actual income, given the result of estimating a logarithmic linear 

relationship between these two variables.

Apart from being related to their actual income, perceived minimum income may also 

be related to various sociodemographic characteristics of the households and, e.g., to their 

expenditure patterns. Hence, income sufficiency thresholds may be differentiated according to 

these variables. So far, the literature on subjective poverty lines in the U.S. (Colasanto, 

Kapteyn, and Van den Gaag 1984; Danziger et al. 1984) has concentrated on family size 

differences and on the factors which differentiate the official poverty lines. Early European 

studies also concentrated upon family size (Goedhart et al. 1977; Van Praag, Hageaaars, and 

Van Weeren 1982), but lately the possible role of a number of other household characteristics 

(e.g., age, education, occupation, urbanization, income fluctuations, number of working 

members) has also been acknowledged (Hagenaars 1986). Kapteyn, Kooreman, and Willemse 

(1988) stress the influence of reference groups.

Previously we have estimated the relationship between perceived minimal income and 

actual income differentiated by a series of sociodemographic variables (De Vos and Garner 

1991). We have presented the average subjective thresholds for the U.S. and the Netherlands 

differentiated by family size and for one and two person households with reference persons 

older and younger than age 65. A comparison of mean official and subjective thresholds 

revealed that the official poverty thresholds were significantly lower than the thresholds based 

upon income sufficiency. A greater percentage of households in the U.S. (42.2 percent) 

compared to the Netherlands (17.1 percent), had incomes below their income sufficiency 

thresholds. In this paper, we continue our attempt to isolate what is minimally necessary in 

different sociodemographic groups by considering separate sets of subjective thresholds. Our 

interest here is the relationship between minimally necessary income and household 

expenditures. The composition of expenditures may be important for poverty analysis since it 

allows one to consider the satisfaction derived from different components in meeting household 

needs. In a study by Homan, Hagenaars, and Van Praag (1986), housing and other fixed 

expenditures were identified as influencing the answers of respondents to the Income 

Evaluation Question and resulting subjective poverty thresholds.
In our previous analysis of the U.S. and Dutch data, we examined the relationship between 

aggregate fixed expenditures and responses to the MIQ. We found that these expenditures 

were significantly related to the perceived minimum incomes which were used to produce the 

income sufficiency thresholds. This earlier U.S.-Dutch research reflects the first attempt by 

researchers to examine the MIQ and subjective thresholds relative to expenditures. In this 

paper we will consider several components of expenditures, in order to identify whether 

certain expenditure categories are more related to perceived minimal income than are others.

The effect of taxation on answers to the MIQ is also examined. For the U.S., the MIQ 

was to be answered by respondents in terns of income before any deductions. In contrast, the 

Dutch respondents were to answer in terms of their after tax income. Thus, for the U.S., we 

include taxes as an additional explanatory variable in the minimum income estimation 

equation.

The paper proceeds as follows. In section two we describe the method and the data. In 

section three we compare U.S. and Dutch results with respect to perceived minimum income 

and discuss the influence of expenditures and taxes. Also included is a contrast of the 

percentages below the resulting income sufficiency thresholds with the official poverty rates, 

which can be considered absolute, and with relative poverty rates based on poverty lines drawn 

at one-half the median income of the respective populations. Section four presents some 

conclusions and some recommendations for further research.

2. Method and Data

2.1 The Interaction Method

As introduced by Goedhart et al. (1977), subjective poverty lines or income sufficiency 

thresholds are calculated as tie income level where Ymin equals Y given the relationship
Here Ymin represents the answer to questions like "What income do you consider to be 

minimally necessary. for your household to make ends meet" (the MIQ), and Y represents 

current household income. The idea behind the choice of the intersection of the relationship (1) 

with the line Ymin = Y is that only people whose income is close to their minimally necessary 

income have a realistic picture of this minimum income level. Respondents with more income 

tend to overestimate their minimally necessary income, while people with less income tend to 

underestimate it. When they would be awarded their reported minimally necessary incomes 

they would, after a while, find out that they actually could get by with a lower, respectively 

would need a higher minimum income. Figure 1 illustrates this approach.

As noted in section 1, the answer to the MIQ depends not only on income but also on 

household characteristics: families with different characteristics require different amounts of 

money to make ends meet. By adding family size and other household characteristics to 

regressions of equation (1), separate intersections for diverse household types may be 

calculated, resulting in associated household equivalence scales.

A basic assumption for the calculation of the income sufficiency thresholds is that 

every respondent adheres the sawn meaning to the wording used in the MIQ: the expression 

"minimally necessary to make ends meet" is supposed to have the same welfare connotation for 

all respondents. Even if one accepts the possibility of interpersonal comparisons of welfare, a 

careful formulation of the questions is needed. This is especially true for
international comparisons, where language differences may hamper the phrasing of terms with 

the same meaning. Obviously, when comparing U.S. and Dutch data we must reckon with the 

possibility of differences in the interpretation of the MIQ, particularly since the questions in 

the surveys we use were not designed for international comparisons.

2.2 Data

The U.S. data we use are from the Consumer Expenditure Survey (CEX) for 1982. The 

CEX is sponsored by the Bureau of Labor Statistics (BLS), U.S. Department of Labor, data are 

collected by the Bureau of the Census. Detailed household characteristics and income data are 

collected as well as data on approximately 90 to 95 percent of total family expenditures. Data 

are collected from a national probability sample of households designed to represent the 

civilian noninstitutional population and a portion of the institutional population, living in 

selected types of group quarters; however, in 1982 households living in rural areas outside 

Standard Metropolitan Statistical Areas (SMSA's) were not surveyed due to budgetary 

constraints. Data are collected from consumer units within households. A consumer unit is an 

individual, family, or group of persons who pool their incomes to make joint expenditure 

decisions. The consumer unit is often identified by the characteristics of its reference person. 

The reference person is the first member of the consumer unit mentioned by the respondent 

when asked to "Start with the name of the person or one of the persons who owns or rents the 

home." The sample, targeted at approximately 5,000 consumer units per quarter, is selected on 

a rotating panel basis; each quarter, one-fifth of the sample is new to the survey. For more 

information about the CEX, see U.S. Department of Labor (1986).

The MIQ was included in the quarterly CEX questionnaire only during the period from 

January 1, 1982 through January 31, 1983. The question was included in the last section of the 

questionnaire and was asked only during the fifth interview. The resulting sample includes 

4,830 consumer units. In the CEX, the MIQ was asked after a series of detailed questions about 

expenditures and income. It was introduced by the statements: "In previous interviews we have 

asked a number of questions about how you spend your money and about your income. Now 

we have some questions regarding how you feel about
some of these things." Then respondents were asked to answer, for their consumer units, the 

MIQ as follows: "Living where you do now and meeting the expenses you consider necessary, 

what would be the smallest income (before any deductions) you and your family would need 

to make ends meet?" Following this question, respondents were asked about the time period 

for which this income was needed. We used this information to produce annual perceived 

minimum incomes. Since tire question referred to "income (before any deductions)", we 

assume that the income reported as minimum is before taxes.

The Dutch data are from a 1983 newspaper survey. In cooperation with Bernard van 

Praag and Aldi Hagenaars of the Center for Research in Public Economics of Leyden 

University, ten regional Dutch newspapers associated with the joint Press Service (GPD) 

included a two-page questionnaire with a set of 67 questions in their editions of Saturday, 

September 10, 1983. Questionnaires were returned by some 20,000 households. For this 

research a nationally representative subset of 13,730 households is used. The questions 

referred to household characteristics, income, expenditures, and a series of related subjects. 

For this data set, a household is defined as a group of people, living together, whose 

expenditures are made from common pooled resources. The main breadwinner in the 

household is the person who contributes the most money. For more information on the survey, 

we refer to De Vos and Hagenaars (1986) and Van Duin and Hagenaars (198!) who conclude 

that after reweighting the representativity of the data is comparable to that of surveys 

conducted in a more traditional manner.

In the Dutch questionnaire the MIQ was part of a series of questions concerning one's 

opinion about a possible new system of social security with a "basic income" to which every 

household without a source of income should be entitled. After asking whether one would be in 

favor or against such a system,- the question we use as the MIQ is stated as follows: "The 

previous question was about the basic income ("needs minimum"). How high should that be 

for your household, according to you?" Respondents were directed to report minimum income 

after taxes were deducted.

Although context and wording of the U.S. and Dutch MIQ's are dearly different, we 

nevertheless felt confident that comparisons could be made legitimately, since both questions 

try to assess the income level which the respondents consider to be minimally necessary for 

their households. However, differences in the formulation of the questions are taken into 

account in the analysis and discussion of the results.
Furthermore, given the wording of the questions, one may argue that the income levels 

computed as the intersection of equation (1) with the relationship Ymin - Y, corresponding to a 

level of living associated with "making ends meet", cannot really be seen to represent poverty. 

This is especially true to the extent that the answers to the MIQ reflect short run expectations 

and would be different when people would have experienced more income levels. In view of 

this, we refer to the interaction levels as "income sufficiency levels", in addition to the more 

frequently used "subjective poverty lines":

2.3 Explanatory Variables for Ymin Added in Earlier Studies

As from the early days of the subjective minimum approach (Goedhart et al. 1977), 

family size differentiated subjective thresholds have been computed by adding log(family size) 

to equation (1). Since then, other authors, especially Hagenaars (1986), have extended the 

number of explanatory variables to be included in equations like (1), and hence as 

differentiating factors for the subjective poverty lines. It can be argued that even if a variable 

causing a significant effect in (1) is not accepted as a differentiating factor for the poverty line 

(e.g., due to political objections, and/or because it is assumed that the underlying cause of the 

significant effect is not differences in costs but differences in taste), such a variable should still 

be taken into account to obtain unbiased estimates of other differentiating effects.

If, for instance sex of the reference person has a differentiating effect in addition to 

household size, it can be expected that the household size effect is biased if the sex of the 

reference person is not included as a differentiating variable, because small households are 

more likely to have a female reference person. If households with female reference persons 

would report higher minimum sufficient incomes but that effect is ignored in the regression it 

can be expected that the income sufficiency thresholds of small households will be 

overestimated relative to large households. On average, this will be correct since small 

households will more often have female headed reference persons, but it can be shown that the 

income sufficiency thresholds of small households with male reference persons will be 

overestimated whereas those of large households with female headed reference persons will be 

underestimated. Implicitly the higher thresholds for females are taken into account,
because they affect the other coefficients. If one would insist upon sex-neutral thresholds, it 

would probably be more correct to include sex as a differentiating variable in the regression, 

and to compute the thresholds using the 'average sex' in the sample. In that case the fact that, 

e.g., small households more often have female reference persons is fully compensated for. The 

same effect would only be reached when the sex of the reference person was not included in 

the regression if it would not be correlated with any of the other explanatory variables. 

Likewise, if one would want to bar reference group effects in determining the thresholds, it 

would be correct to include variables for reference groups in the regression, and then compute 

the thresholds for households with 'average' reference groups.

Thus, it appears that all variables having a differential effect on the answer to the MIQ 

should be included in the regression, even if they are not allowed to differentiate the income 

sufficiency thresholds. The decision which variables to include should therefore be made on 

empirical rather than theoretical grounds.

In De Vos and Garner (1991) we added a series of variables to log(Y) in equation (1). 

These variables pertained to household composition and employment status, sex, age, 

education, and corrections for neglected income components and selectivity bias, and 

additionally for the U.S. data: rice, region, degree of urbanization, and marital status of female 

reference persons. Person characteristics refer to the main breadwinner or to the reference 

person in the Dutch and American surveys respectively. These two terms ate used 

synonymously throughout the remainder of the paper.

In this paper we take the inclusion of these variables in equation (1) as a starting point. 

For an elaborate discussion of their motivation, we refer to our previously mentioned paper. 

Here, we will only summarize the corrections for neglected income components and selectivity 

bias. One variable, the log of anchor income (log(Yanc)), is included in the regressions to 

correct for the fact that people tend to neglect parts of their income when answering the MIQ 

(see, for example Kapteyn, Kooreman, and Willemse 1988). The Yanc is an estimate of the 

picture of the household's income that the respondent has in mind when answering the MIQ. It 

is a weighted sum of income components (e.g., income of the main breadwinner, income of the 

partner, income of the children, income of other consumer unit members (U.S. only), and 

family income not associated with any specific individual member such as family allowances) 

with weights between zero and one.
In our operationalization, the income of the train breadwinner receives a weight of one, while 

most other income components obtain a lower weight. However, contrary to the Netherlands, 

the income of the partner of the reference person in the U.S. obtains a weight of one in the 

anchor income. When it is supposed that the respondents underestimate their minimally 

necessary income and their actual income by the same percentage, it can be shown that 

log(Yanc) enters in equation (1) with coefficient one, while a, should be estimated by adding 

one to the coefficient of log(Y) (see Homan 1988).

To correct for possible bias in the estimates of the coefficients due to selective 

nonresponse, a correction factor is included based on a Probit equation explaining response. 

Inclusion of this correction factor (the inverse Mills' ratio) causes the estimates of the standard 

errors of the OLS estimates to be incorrect (see, e.g., Heckman 1979; Greene 1981). 

Nevertheless, we have chosen to present these estimates and to refrain from attempts to come 

up with the correct values. For details and discussion of the results of the Probit equation we 

again refer to De Vos and Garner (1991).

2.4 Expenditure Variables Added to Equation (1)

In answering the question concerning which income they would minimally need for 

their households, it is conceivable that respondents consider the expenditures they have and 

expect to have in the future. Many kinds of expenditures can be adapted at any moment to 

different circumstances (for example to a lower income), but some expenditures do not allow 

such adaptation at will. This may be because these expenditures are fixed due to long term 

contracts and can only be changed at heavy costs. An example is formed by housing 

expenditures, which in many cases may only be changed by moving into another house. 

Hence, it could be expected that in answering the MIQ respondents with high fixed 

expenditures would report relatively high minimum incomes. In our previous paper we 

reported results which confirmed this expectation. The effect is not necessarily limited to 

expenditures which can be considered as fixed, however. Respondents might also want to 

maintain high expenditures in categories which one initially would consider more easily 

adaptable, and would report higher minimum incomes than would households with lower 

expenditures in these categories. Hence, in order to examine the relationship between
perceived minimum income and expenditures, in this paper we do not only consider fixed 

expenditures such as housing, but extend the analysis to several expenditure categories. One 

way to do so would be to include the logarithms of several expenditure variables (or, e.g., the 

expenditure shares) as additional explanatory variables in equation (1). However, this would 

introduce considerable multicollinearity since expenditures can be expected to depend heavily 

upon income, and also to be significantly related to sociodemographic variables included in 

equation (1). Hence, in order to avoid multicollinearity and to obtain the net effects of 

expenditures, we have chosen to estimate expenditure share equations with log(Y) and the 

sociodemographic variables included in equation (1) as explanatory variables, and to use the 

resulting residuals as additional explanatory variables in equation (1). These residuals can be 

interpreted as indicative of relatively high or low expenditures, all other things being equal. For 

both the U.S. and the Netherlands, we include residuals from the share regressions of food 

(including alcoholic beverages), clothing and services, housing, utilities, education, insurance, 

leisure, and transportation. For the U.S. alone, the residual of the share for taxes and Social 

Security and Railroad Retirement payments is in addition included

The Dutch expenditures were obtained by asking estimates of the amounts spent on 

global categories of goods and services (e.g., insurances). Expenditures for the U.S. were 

obtained by asking detailed questions about expenditures (e.g., homeowner's insurance, tenant's 

insurance, commercial health insurance, life insurance). To make expenditures as comparable 

as possible for the two data sets, we grouped the detailed U.S. expenditure data. A listing of 

these detailed expenditure variables and their groupings is available from the authors upon 

request. For the U.S. analysis, quarterly expenditure data were used to produce annualized 

expenditure values. For consumer units participating in less than four quarterly interviews (7 

percent of the sample participated in only one interview, 8 percent in two, and 10 percent in 

three), expenditures were averaged over the quarters in which the consumer unit did participate 

and the resulting expenditure values were annualized. This procedure was necessary to have a 

study sample which, when weighted, would be the most representative for the U.S. population. 

Yet, we are aware that for certain consumer units these "annualized" expenditures arc an overor underestimate of their actual expenditures. Likewise, the Dutch expenditure data, annualized 

from estimates of the expenditures for different time periods, may also have a fairly broad error 

margin. For reference, results of
the expenditure share regressions for both countries are included in the appendix in Tables A1 

and A2. Means and standard deviations of the variables included in equation (1) are presented 

in Table 1.

2.5 The Relative Poverty Threshold

As announced in the introduction, in this paper we compare the subjective income 

sufficiency thresholds (with and without taking account of expenditures) with the official 

poverty line, which may be regarded as more or less absolute, and with a relative poverty line 

for each country. This relative poverty line is defined as one-half the median income per 

equivalent adult. The equivalence scale used for the calculation of this poverty line assigns 1.0 

to the first adult, 0.7 to each additional adult, and 0.5 to each child in the household; this scale 

has been recommended by the Organization for Economic Co-operation and Development (see 

OECD 1982 and O'Higgins and Jenkins 1989). Income per equivalent adult is computed by 

dividing total household income by the equivalence scale. Then we construct a distribution of 

income per equivalent adult in which every household is weighted by its number of equivalent 

adults. In this distribution the median is located. The relative poverty line for a particular 

household is then computed by multiplying one-half of this median equivalent income by the 

equivalence scale relevant for the household

3. Results

3.1 Regressions

In this section we present regression results of estimating equation (1) with the 

explanatory variables discussed in the previous section (Table 3). For comparison, we have 

also added the regression results without the expenditures (Table 2). For an elaborate 

discussion of the latter results we refer to De Vos and Garner (1991). In general, we concluded 

there that the coefficient of log(Y) in the regression of log(Ymin) is somewhat smaller and that 

the coefficients of most other differentiating factors are somewhat larger



in the U.S. than in the Netherlands. This holds both for factors objectively leading to 

differences in minimal needs, like household composition, and for social characteristics 

like education. Nevertheless the regression results arc quite comparable. Most 

importantly, there appeared to be no clear indications of basic differences in views 

concerning minimum necessary income, despite differences in the official policy with 

respect to poverty and government transfer programs in the two countries.

As could be exacted, adding the expenditure residuals (Table 3) to the regression 

hardly alters the coefficients of the ether explanatory variables. Only the correction 

factor for nonresponse, which was not included in the explanatory variables of tire 

expenditure regressions, now obtains a significant coefficient in the Dutch regression. As 

to the coefficients of the residuals, we see that they are significantly positive in a 

majority of the cases. Relatively high expenditure shams are associated with relatively 

high reported minimally necessary incomes; this is true under the condition that all else 

is equal, i.e., compared to others with the same characteristics. For both countries 

positive significant coefficients are found for food, housing, and utilities. In addition, 

insurance is positively related to minimally necessary income in the Netherlands, while 

leisure is negatively related. For consumers in the US., high shares of education and 

transportation expenditures are positively related to perceived minimum income. In 

contrast to the results for the Netherlands, expenditures for leisure are also positively 

related to subjective minimum income. Thus, in the U.S. we find much smaller 

differences between the coefficients of the respective residuals, a compared to the 

Netherlands where we find clear differences between the high coefficients for fixed 

expenditures, like housing and utilities, and the negative coefficient for leisure.

Hence, it would appear that in answering the MIQ, respondents in the 

Netherlands more clearly distinguished between (fixed) expenditures which they would 

want to continue and luxury expenditures which could be reduced. This may not be the 

case in the U.S. where relatively high expenditures have the same effect on reported 

minimum income in almost all expenditure categories. This different resale for the two 

countries is expected to be related to what respondents consider necessary, as alluded to 

previously, and to their interpretation of the MIQ. For example, in the U.S. transportation 

accounts for a greater share of expenditures than in the Netherlands. The fact that the 

U.S. transportation coefficient is significant and larger than the one for the Netherlands is 

likely to be related
to the fact that there are fewer available substitutes for private transportation in many 

parts of the U.S. An implication is that respondents in the U.S. would consider 

transportation expenditures to be more fixed than in the Netherlands.

An alternative explanation is that respondents in the two countries interpreted the 

MIQ somewhat differently. It may be that the question was understood in the U.S. as 

asking for the minimum income needed to "continue your present living pattern." This 

interpretation is not unlikely given that respondents just previously had been asked to 

provide detailed expenditure and income information. It is clear that this makes the 

interpretation of the resulting thresholds as poverty lines rather doubtful. in contrast, for 

the Netherlands, the MIQ was included in a survey focused on social polity issues, one of 

which was the possible introduction of a new system of social security with a "basic 

income" to which households without income would be entitled. Thus, it is likely chat 

Dutch respondents were more predisposed to provide a necessities based minimum 

income for their households. If this is the case, interpreting the resulting thresholds as 

poverty lines is more appropriate in the Netherlands than it is in the U.S.

The residuals of the tax share estimation also obtain a significant positive 

coefficient in the U.S., but it is clearly lower than that of the expenditure residuals. This 

is probably mused by the fact that the tax share residuals are relatively large in absolute 

terms, among others, as a result of the very small part of the variance in the tax shares 

equation explained.

3.2 Threshold: and Percentages

We are aware of the fact that the legitimacy of some of the variables included in 

the regressions as differentiating factors for a poverty line may be subject to discussion 

(although they are rightly included in the regression). We also have noted that the 

interpretation of the resulting thresholds as poverty lines may be doubtful. Nevertheless, 

we present some results pertaining to the income sufficiency thresholds associated with 

the above regressions in this section. We will not try to give a complete picture of the 

thresholds lines for all possible combinations of differentiating factors, but limit 

ourselves to the means of the thresholds computed for the individual households on the 

basis of their characteristics. We only present the averages differentiated according to 

family size.
However, it should be noted that all differentiating factors have been taken into account. 

As we mentioned in section 2, the subjective income sufficiency thresholds are

computed as the intersections of the estimated relationship

Table 4 provides the means of the resulting thresholds with and without the 

expenditures included in the regressions, according to family size. For comparison, we have 

also armed the means of the actual income levels in our surveys, the official poverty lines in 

the U.S., the official social minimums relevant for the Netherlands, and the relative poverty 

thresholds basal on one-half the median of equivalent income as discussed in section 2.

It can be concluded that the levels of the subjective income sufficiency thresholds in 

the U.S. are considerably above the official poverty lines. For most household size groups, the 

mean subjective poverty line is more than twice the official poverty threshold. In the 

Netherlands the subjective poverty fines are also about the official minimum, but in general the 

difference is clearly smaller and amounts to about 20 percent. Compared to the mean income 

levels, the differences in the subjective poverty lines are much smaller; in both countries the 

mean poverty lines lie in the range of 60 to 75 percent of the man incomes in most family size 

groups. Taking account of the expenditures raises the average income sufficiency thresholds. 

This is probably caused by the convex shape of the antilog function; the logarithm of the 

poverty lines may be expected to remain constant on average by adding factors with zero 

means.
Table 5 presents the average equivalence scales resulting from the figure of Table 4, 

and compares them to earlier studies using the subjective threshold computed answers to a 

MIQ. For the US. this includes Danziger et al. (1984), who use the 1979 Income Survey 

Development Program (ISDP) panel due, and Colasanto, Kapteyn, and Van der Gaag (1984), 

who employ data from the 1981 Wisconsin Basic Needs Study (BNS). For the Netherlands we 

include results of Kapteyn, Kooreman, and Willemse (1988), whoa data are from the 1982 

Labour Mobility Survey (LMS), and Berghman et al. (1988), who used data from the 1985 

Central Bureau of Statistics Social-Economic Panel (CBS).
It can be seen that in the U.S. the official poverty lines increase much faster with 

household size than in the Netherlands. Disregarding the anomalous fault for households 

with six or more persons in the U.S., we see that the differences in the average 

equivalence scales implied by the subjective thresholds are, in general, much smaller. 

The relative poverty lines show the highest increase with family size in both countries. It 

may be that this equivalence scale, originally devised by the OECD as noted earlier, is 

more appropriate for countries where expenditures with relatively low scale economies, 

like food, compose a larger part of the total budget.
Compared to earlier studies with subjective thresholds, we see that the U.S. results 

from this study are fairly close to the Wisconsin results of Colasanto, Kapteyn, and Van der 

Gaag (1984), but are clearly steeper than those of Danziger et al. (1988). Compared to the 

Dutch results of Kapteyn, Kooreman, and Willemse (1988), who also correct for nonresponse 

and neglected income components, our subjective thresholds rise less fast for households up to 

four members, but faster for larger households. Berghman et al. (1988), who do not correct for 

possible biases, find clearly flatter equivalence scales. Finally, the average equivalence scales 

of the expenditure based subjective thresholds in the Netherlands are fairly dose to the original 

values, while they show a rather implausible course in the U.S. Further research is required to 

shed lot on the doses of this result.

The percentages of households or consumer units below the subjective thresholds, the 

official poverty fines, and the relative poverty lines are presented in Table 6. Again, we limit 

ourselves to the general picture, which shows that according to all measures the percentages 

are clearly higher in the U.S. than in the Netherlands. 'this is indicative of the fact that the 

lower tail of the income distribution in the U.S. is clearly thicker than in the Netherlands, 

among others as a consequence of the elaborate system of income transfers in the latter 

country. It should be added, however, that the presented percentages of poor according to the 

official minimum in the Netherlands am an underestimation of the real percentages, and that 

revisions in the system after 1983 have forced more households to the social minimum.

Given the differences between the subjective thresholds and the official poverty lines, it 

is self-evident that the percentages of households below the subjective thresholds am much 

larger than the percentages below the official poverty line, especially in the U.S. The 

percentages in the different family size groups show that in both countries single persons above 

65 are especially at risk of being in poverty when the sufficient income approach is assumed 

Given the respective poverty lines, the percentage in this group for the Netherlands should not 

be taken too seriously, being based on rather few observations. However, the poverty among 

elderly one person households in the U.S. seems a serious problem indeed. Apart from this 

group, poverty percentages are also above the average for younger singles and for elderly 

couples. According to the official and the relative thresholds, poverty is also widespread 

among large households. In the Netherlands subjective income
insufficiency is highest with the singles and large households; singles are also overrepresented 

among the officially poor, while large households am most often poor according to the relative 

poverty threshold. Taking account of the expenditures in the answers to the MIQ increases the 

extent of income insufficiency in the Netherlands, but causes a decrease in the U.S. Further 

analysis of the distribution of the expenditure residuals would be necessary to find out the 

cause of this difference.
4. Discussion and Conclusion

In this paper we have performed regressions of log(Ymin) on log(Y) and a series of 

differentiating factors, and we have compared the resulting thresholds and percentages of 

households below these thresholds to official and relative poverty in the U.S. and the 

Netherlands. We find that on average, the income sufficiency thresholds am considerably 

above the official poverty fines, but more so is the U.S. than in the Netherlands. The 

percentages below the thresholds are also considerably higher in the U.S. than in the 

Netherlands, whether we look at the official poverty definition, the computed subjective 

thresholds (with or without accounting for expenditures), or to a relative poverty line.

Perhaps the most important contributions of this paper are: (1) to have distinguished 

specific expenditures that appear to be correlated with the minimum incomes that individuals 

think they seed to make ends meet; and (2) to have introduced more questions concerning the 

respondents' interpretations of the MIQ and concerning the uses of the resulting thresholds. 

Although it sums reasonable that individuals would consider the expenditures they need to 

make when answering the MIQ, only one previous study (De Vos and Garner 1991) explicitly 

included expenditures (fixed) in an analysis of this question. For the current study, we 

examined the relationship between responses to the minimum income question and 

expenditures for various categories of goods and services. For both countries, housing and 

utilities expenditures were clearly considered to be necessary in making coda meet. Food 

expenditures were also related to minimum income, although not as strongly as the two 

categories just noted. In contrast, clothing expenditures were not related to minimum income 

by respondents in either country, is the coefficient for food smaller than for the first two 

categories, because within the category of food there are expenditures which families cart more 

easily do without? Does the result for clothing give us any indication of a "presumed" 

durability of items in this category or of clothing purchase patterns? Do we consider the 

clothing goods and services that we think of as necessities only a small share of the total 

clothing budget?

Statistics Canada (1988) recently surveyed respondents in a supplement to the Survey 

of Consumer Finances, in an attempt to snore directly address the issue of meeting the basic 

spending nerds of the family. Respondents were asked the following question: "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." Unlike in our study, basic necessities were 

more or less defined. Further research needs to be conducted to gin a greater understanding of 

what respondents actually consider to be necessary when meeting their needs, versus what 

survey questionnaire designers and policymakers consider to be necessary.

We initially began our research feeling fairly confident that we could interpret the MIQ 

comparably for the U.S. and the Netherlands, and that the income sufficiency thresholds could 

be interpreted as perhaps some type of poverty line. However, now, after obtaining these 

results, we are less sure. The significant negative coefficient for leisure expenditures in the 

Netherlands versus the positive coefficient in the U.S. has led us to question whether 

respondents in the two countries were both thinking about "basic" needs. As noted previously, 

it is likely that the U.S. respondents were thinking about their current expenditure patterns, 

since they had just been asked derailed questions about expenditures. Thus, the assumption 

underlying the computation of the income sufficiency threshold as a poverty line, that 

everyone adheres the same welfare connotation to a "minimally necessary income", may not 

be valid across the two surveys and between and within populations. When in reality higher 

educated people or people with higher expenditures tend to relate a different lifestyle to their 

minimally necessary income than do lower educated people or people with lower expenditures 

(all other things, like income, being equal), the question arises whether we still have a 

legitimate poverty definition. As long as they reflect real cost differences, differences in the 

poverty lines do not seem unreasonable. When they spar to be related to different welfare 

levels, we have a problem.

Moreover, the results of this research support the proposition that context and question 

wording do matter, as cognitive psychology wild suggest. Over approximately the last 20 

years, MIQs have been asked in one survey or another and in different countries, most often 

with different wording and in different contexts. Questions are asked about "you and your 

family", "a family like yours", and hypothetical families. Needs have only been defined in one 

survey (Statistics Canada 1988). Nods have beat most often described in terms of "necessary" 

to make ends meet. Does this tan the same as when "absolutely" precedes the phrase? Does it 

mean the same as "barely adequate"? Minimum income has been presented as "smallest 

income", "very smallest income", and "basic income". Can we
assume that all of these terms mean the same to respondents? Deductions and taxes are 

most frequently not to be considered when answering the MIQ. To which deductions and 

what taxes are we referring? Many MIQs allow respondents to select the time period for 

which their minimum income refers. For those questions which do rest, a year is the 

preferred reference period. For spending-oriented questions, perhaps a shorter time 

period than a year would provide respondents with a more reasonable time frame for 

remembering (this option is available in the Statistics Canada (1988) spend question). 

And last, questions often ask respondents to estimate a minimum income keeping in 

mind "living where you live now." One type of question states "in this community" 

(O'Hare et al. 1990). Would the first phrase man that respondents are not to make 

changes in their housing arrangements and other activities? Would the second phrase 

allow respondents to move, but only within their current communities? A question 

referring to "adequate shelter" is likely to elicit a very different response than either of 

the other two phrases. When we ask individuals and families to answer the MIQ with 

respect to their current living arrangements, perhaps the measures are better indicators of 

the overall economic well-being of households within a society than they are of poverty.

Homelessness, poverty, and deprivation appear to be growing in our societies, 

particularly among certain groups, such at single parent families. Among many other 

issues, two important questions pertain to cumber of persons involved and the accent of 

their problems. To answer these questions it is necessary to assess what individuals and 

families must have to live. Conducting surveys with questions on perceived income 

sufficiency and spending requirements could be one of the means to do so. However, as 

the results of this paper clearly show, these questions need to be further explored and 

compared with alternative methodologies. Thus far, Statistic Canada appears to be one of 

the most active actors engaged in testing different MIQs in the field. In contrast, we 

suggest that a thorough examination of minimum income and related questions in a 

cognitive laboratory would probably be even most worthwhile. After this work, field 

testing would ensue. When we understand better the meanings of our questions, we will 

be in better positions to provide data cad conduct analyses, using such subjective 

measures, which focus on economic wellbeing, in general, and poverty, specifically.
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