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Measuring Poverty: A New Approach (1995)


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Suggested Citation:"CONCLUSIONS." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
Page 140
Suggested Citation:"CONCLUSIONS." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
Page 141
Suggested Citation:"CONCLUSIONS." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
Page 142
Suggested Citation:"CONCLUSIONS." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
Page 143
Suggested Citation:"CONCLUSIONS." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
Page 144

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POVERTY THRESHOLDS 140 average weekly amounts (converted to an annual basis) for 1992 and 1993 with Vaughan's poverty numbers for 1947-1989. The sample sizes are small in each year and, at least partly for this reason, the year-to-year changes in the estimated Gallup poverty level (and similarly in the get-along level) show considerable variation. Nonetheless, some clear patterns emerge. Most striking, the estimated poverty level from the Gallup Poll data shows about the same relationship to the official poverty threshold as does one-half the median after-tax four-person family income (compare with Table 2-3). Both of these series were below the official threshold through 1955, about the same as the official threshold through about 1965, and then above the official threshold. It seems clear that subjective poverty thresholds respond to changes in real income or consumption, both up and down. For example, one can see dips in the Gallup get-along and poverty levels in real terms in periods of recession from the data in Table 2-4. One major question for poverty analysts is the time- series elasticity of subjective poverty thresholds with respect to changes in median income or consumption. If the elasticity is 1 or very close to 1 (i.e., if a percentage change in the threshold series is the same as the percentage change in the income series), one could argue for a strictly relative approach to updating poverty thresholds. If the elasticity is somewhat less than 1, one might prefer an updating method somewhere between a completely relative and an absolute approach. Vaughan (1993:42) estimated the elasticity of the Gallup get-along series for 1947-1989 with respect to median after-tax four-person family income as 0.80 (using constant 1967 dollars and only the years for which means rather than medians were available). Not surprisingly, because of generally increasing taxes over the post-World War II period, Vaughan's estimate of the elasticity of the get-along series with respect to median before-tax four-person family income is lower, 0.65. With respect to average family income, Rainwater (1992) estimated the elasticity as 1.0 for the get-along series through 1986.37 Maritato (1992), in a review of get-along responses in Canada over the period 1973-1985 presented in Michalos (1989), estimated the elasticity with respect to family income (whether mean or median) as 0.70. CONCLUSIONS We draw several conclusions from our review of alternative concepts that could be used to derive and update poverty thresholds for the United States. First, it is clear that all approaches involve judgements—whether in choosing a 37 One reason for Rainwater's result may be his use of current dollars. If the elasticity is truly less than 1 and the correct regression is in real terms, then the estimated coefficient will be biased toward 1 if current dollars are used. Maritato also used current dollars.

POVERTY THRESHOLDS 141 particular distribution (e.g., income or expenditures and from which data set) and a particular cutoff point for a relative poverty threshold (it is only by convention that 50% of the median is the common cutoff); in choosing a particular question wording and estimation method (e.g., using the full set or a subset of respondents) for deriving a subjective poverty threshold from survey data; or in deriving the specifications for an expert budget. As a result, poverty thresholds developed by different applications of a particular approach (e.g., by different experts), as well as by different approaches, differ. Second, it is clear that all concepts have large elements of relativity in them. In developing a poverty standard, some reference is invariably made to the living conditions of the particular time and place. Consequently, poverty thresholds constructed at different times tend to reflect real changes in consumption. This is true, by definition, of relative thresholds. And there is strong evidence that survey responses about poverty or minimum income levels are also relative to time and place: the time-series elasticities of subjective responses with respect to median income are high (although not 1.0).38 Finally, on close inspection, it turns out that expert budgets—at the time of their development—are also relative. And while the practice is to update an expert budget for price changes until it is replaced by a new standard, the new standard typically takes account of the real changes in income or consumption since the old standard was set. For example, the post-World War II BLS family budgets, which were revised at about 10-year intervals, each time mirrored median levels of expenditure. Table 2-5, which includes thresholds developed by several approaches, illustrates both of these points. Columns 1 and 2 list thresholds developed around 1980 and 1990, respectively (in 1992 dollars). The thresholds listed in each column vary, indicating the effects of different judgements about concepts, methods, and data. The thresholds also show relativity to time and place: for most thresholds for which comparable estimates are available for around 1980 and around 1990 (excluding the thresholds that are updated simply for price changes), the value (in 1992 dollars) increases from the earlier to the later year. (See also Table 2-1, which shows the large increases in real terms in the value of thresholds developed by the Orshansky multiplier method and those specified as 50 percent of median income over the period 1950 to 1992.) Given the evidence of relativity in the way in which poverty thresholds are commonly derived, we conclude that the key point for consideration is not whether to treat poverty thresholds as absolute or relative, but, rather, 38 In various countries, cross-sectional elasticities of respondents' answers about minimum income with respect to their own income have been estimated at 0.40 to 0.60 (see Maritato, 1992: Table 1), indicating that respondents in better off societies will tend to set a higher poverty line than respondents in less wealthy countries.

POVERTY THRESHOLDS 142 TABLE 2-5 Examples of Poverty Thresholds for Four-Person Families Set by Various Methods for Years Around 1980 and 1990, in Constant 1992 Dollars Type and Source of Thresholds Set for Years Thresholds Set for Years Threshold Around 1980 Around 1990 Expert Budget Thresholds Official (Orshansky 1963 14,228 14,228 threshold indexed by CPI- U) Orshansky 1963 threshold 13,082 13,082 indexed by CPI-U-X1 Orshansky food multiplier 16,163 (1980) 20,659 (1991) developed from CEX data Ruggles housing multiplier 21,331 (1980) 21,640 (1992) Weinberg/Lamas food/ N.A. 20,267 (1989) housing multiplier—25th percentile Weinberg/Lamas food/ N.A. 21,790 (1989) housing multiplier—35th percentile BLS lower level budget 19,587 (1981) N.A. Renwick budgeta N.A. 17,600 (1992) Schwarz and Volgy budget N.A. 18,983 (1990) Relative Thresholds Vaughan one-half median 20,715 (1980) 22,308 (1992) before-tax four-person family income Vaughan one-half median 16,629 (1980) 18,018 (1992) after-tax four-person family income Expert Committee on 15,584 (1979) 19,987 (1991)b Family Budget Revisions social minimum Subjective Thresholds Vaughan "poverty" 15,895 (1980) 17,703 (1989) General Social Survey N.A. 17,228 (1993) "poverty" Colasanto et al. 12,160 (1981) N.A. Danziger et al.c 24,680 (1980) N.A. De Vos and Garnerd 32,530 (1982) N.A. SOURCE: See Tables 2-1, 2-2, 2-3, 2-4, and text. NOTE: All thresholds are after-tax unless otherwise noted; dates in parentheses are the year for which the threshold was developed; all amounts are expressed in constant 1992 dollars using the CPI-U (except the second one, as noted). a Renwick threshold calculated as weighted average of thresholds for two-adult/two-child families with one earner and two earners. (Weighting assumes that 75% of two-adult/two-child families have two earners and that one-third of those pay for day care.) b Calculated as one-half average (rather than median) expenditures of four-person consumer units. c Survey question did not specify whether respondents were to indicate minimum income level before or after-taxes. d Survey question asked respondents to indicate minimum income level before-taxes.

POVERTY THRESHOLDS 143 how often to update them for real changes in living standards. We believe there are advantages to an automatic updating method over an approach that updates the thresholds at sporadic intervals. We also conclude that it is time to reconsider the current U.S. thresholds, which have been maintained in absolute terms for more than 30 years and rest on survey data that are almost 40 years old. We recommend a new concept and procedure for updating the U.S. poverty thresholds; however, given the element of judgement involved, we do not recommend an initial threshold for a two-adult/two-child family. In considering concepts for a poverty threshold, we identified some attractive features of Orshansky's original multiplier method (and that of other expert budgets), in particular, the reference to specific needs (e.g., food). This feature produces poverty thresholds that have a normative cast, which we believe is likely to be more attractive to policy makers and the public than are thresholds developed by a purely relative approach (e.g., one-half median after- tax adjusted family income). But, in practice, the Orshansky multiplier approach is little different from a purely relative approach because the multiplier that is applied to the food budget (and essentially drives the thresholds) includes all spending—on luxuries as well as necessities—by the average family. We believe a preferable approach is one that updates the thresholds in a conservative or quasi-relative manner—one that drives the thresholds by changes in spending on necessities that pertain to a concept of poverty rather than by changes in spending on all kinds of consumption. We also believe the bundle of necessities should include more than just food. However, to try to develop a detailed list seems an exercise in futility and likely to raise needless controversy. A good compromise, we concluded, is to specify a bundle of food, clothing, and shelter (including utilities) and apply a small, fixed multiple for other needed spending, such as personal care, household supplies, and non- work-related transportation. Everyone agrees that food, clothing, and shelter are necessary goods and services (although the level of each that is needed is a matter of debate). These categories are evident in society's thinking about the needs of the poor, as evidenced in homeless shelters, soup kitchens, and winter clothing drives. The food, clothing, and shelter bundle also constitutes a large share of spending for the average family—45 percent in 1991 of total after-tax expenditures by four- person consumer units (Bureau of the Census, 1993d: Table 708). Most important, historically these items have behaved like necessities: that is, their combined elasticity with respect to total expenditures has been less than 1.0 (we estimate that elasticity at about 0.65 over the period 1959-1991).39 39 This estimate is derived from data in the National Income and Product Accounts (NIPA) for 1959–1991, the log of personal consumption expenditures on the sum of food, clothing and shoes, housing, fuel oil and coal, and electricity and gas regressed on the log of total personal

POVERTY THRESHOLDS 144 More broadly, the basic concept—food, clothing, and shelter plus a little more—is as easy to understand as the original concept of food times a multiplier. On the basis of the historical evidence, to update the poverty thresholds for real changes in expenditures on food, clothing, and shelter times a small, fixed multiple means that they will track real changes in total consumption but in a conservative manner. That is, the percentage changes in the thresholds will lag somewhat behind the percentage changes in total expenditures and so will lag somewhat behind the change in a purely relative measure, such as one-half median income (or the Orshansky approach). We find justification for a conservative approach to updating the thresholds from the behavior of subjective thresholds over time, which clearly move with real growth in living standards (hence, outstripping inflation), but on a less than 1-for-1 basis (most estimates range from 0.65 to 0.80). This conservative approach may also be more acceptable to policy makers and the public than making a complete switch from the absolute procedure used to update the official thresholds over the past 30 years to a purely relative procedure. Although we propose to relate the U.S. poverty thresholds to specific goods (food, clothing, and shelter), we do not propose to have the budget levels for these goods set on the basis of expert standards (e.g., for a certain type of diet or dwelling). We believe it is preferable to turn directly to actual expenditure data as the basis for setting the levels. This approach makes explicit both the judgement and the relativity that are inherent in all of the methods for deriving poverty thresholds that we have reviewed (including expert budgets). Also, with this approach it is more feasible to implement changes on an annual basis than would be an approach of having experts review the budget levels every year. Finally, we conclude that important socioeconomic changes, such as the increase in the number of mothers who work outside the home, make it imperative to address an issue that has received relatively little attention in the debate over poverty thresholds: how to adjust them for differences in family circumstances. Poverty analysts have given considerable attention to how to adjust the thresholds for family size and composition differences and some attention to how to adjust them for cost-of-living differences among geographic areas (see Chapter 3). Almost universally, it is agreed that poverty thresholds should be specified in after-tax terms, recognizing that families differ in tax burdens and hence in their disposable income (although the current U.S. poverty measure does not correspondingly define family income consumption expenditures minus expenditures for medical care, with all amounts in constant 1987 dollars (see Council of Economic Advisers, 1992: Table B-12). The reason for subtracting medical care expenditures is that the NIPA includes payments by insurance as well as out-of-pocket expenditures. A similarly derived estimate of the elasticity of food with respect to total expenditures minus medical care is 0.33.

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Each year's poverty figures are anxiously awaited by policymakers, analysts, and the media. Yet questions are increasing about the 30-year-old measure as social and economic conditions change.

In Measuring Poverty a distinguished panel provides policymakers with an up-to-date evaluation of:

  • Concepts and procedures for deriving the poverty threshold, including adjustments for different family circumstances.
  • Definitions of family resources.
  • Procedures for annual updates of poverty measures.

The volume explores specific issues underlying the poverty measure, analyzes the likely effects of any changes on poverty rates, and discusses the impact on eligibility for public benefits. In supporting its recommendations the panel provides insightful recognition of the political and social dimensions of this key economic indicator.

Measuring Poverty will be important to government officials, policy analysts, statisticians, economists, researchers, and others involved in virtually all poverty and social welfare issues.

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