SOME EXPERIMENTAL RESULTS ON ALTERNATE POVERTY MEASURES

SOME EXPERIMENTAL RESULTS ON ALTERNATE POVERTY MEASURES Daniel H. Weinberg and Enrique J. Lamas U.S. Bureau of the Census, Washington DC 20233-3300 Key words: Poverty, Medical Benefits Formal measurement of poverty in the United States is only about 25 years old. Not since the adoption of official poverty thresholds by the Federal government in the late 1960 s has there been such a.great interest as now in examining and possibly respecifying the thresholds. This paper describes an attempt to investigate the likely impact of those changes on our understandmg of the distribution of poverty. For a description of the origins and basis of the official thresholds and details about some of the more current issues that must be addressed to bring the thresholds up-to-date, see Weinberg and Lamas (1994). The paper attempts to understand the relative importance of several of those key issues by using several alternate measures to estimate poverty. These experiments use data from the March 1990 Current Population Survey (CPS); official poverty estimates are presented for comparison purposes. I. ALTERNATE POVERTY MEASURES On the income measurement side, we have utilized the Census Bureau s estimates of the value of noncash transfer (food, housing, and medical) benefits, capital gains, and employerprovided benefits and their estimates of income and payroll taxes to obtain a measure of household after-tax income that includes those benefits. On the poverty measurement side, we have attempted to update the poverty thresholds and introduce regional variation in costs by adding housing to the minimal consumption bundle, respecifying the multiplier, and choosing a more consistent equivalence scale. Details of the procedure are presented in the Appen&x. Several variations are developed and detailed estimates are available from the authors. Briefly, they are based on two estimates of the cost of minimally adequate housing coupled with the presence of medcal coverage as an independent criterion for poverty (considering also the effect of out-of-pocket medical expenditures). Alternate 1 uses the 25th percentile of regional rent distributions (derived from the American Housing Survey) as an indicator of minimal housing cost, includes all non-cash benefits (except imputed income from owneroccupied dwellings) as income, and excludes income and payroll taxes. Alternate 2 also uses the 25th percentile of the rent distribution, but does not count the value of Medicare. Medicaid, or employer-provided health insurance as income. Further, it counts a person as nonpoor only if their after-tax income was above the appropriate threshold someone in their family had some private or government health insurance coverage. (We were unable to measure the adequacy of such coverage.) In addition, if they were not covered by health insurance, but their income was very hgh (more than 8.5 times the poverty level) we clld not count them as poor. In effect, we assume that these persons are self-insured and could pay for adequate health care if they chose to do so. Alternate 3 is similar to Alternate 2 but subtracts family out-of-pocket expenltures for me&cal benefits from income and reduces the poverty thresholds by average out-of-pocket expenses on medical services. These alternates were also computed using the 35th percentile of the rent distribution. A. Effect of Recional Variation and a New Multiplier In order to examine the effect ot updating the poverty measure and establishmg regional variation in the poverty definition separately from the changes in the income definition, Table 1 presents poverty rates for alternative poverty definitions holding income constant; all rates (except the official rate) are computed using post-tax income including the value of noncash benefits. Counting of noncash

income, holding the poveny definition constant at the official thresholds, reduces poverty for all persons by a substantial amount, from 12.8 to 10.4 percent in 1989, almost a 19 percent reduction. Establishing new thresholds with regional variation using the methodology described above leads to uniformly higher poverty rates, at 15.7 percent for the alternative using the 25th percentile of rent and 17.8 percent for the alternative using the 35th percenti~e.~ We believe that the level of poverty is essentially arbitrary as long as consistent measurements can be made over time or across demographc groups. While we only present data for one year, 1989, we can determine the distribution of poverty in order to make demographic comparisons. To analyze the effect of regional variation, we compare each of the alternatives to the estlmates based on the official thresholds when noncash benefits are included as income. If the new measures change our perception of who is poor, then further investigation of these alternatives is probably warranted? Table 2 shows the effect on the distribution of poverty of establishmg regional variation holding income constant for selected demographc characteristics of persons and families. The choice of the 25th or 35th percentile leads to a decrease in the proportion of the poor who are Black with a comparable increase in the proportion who are White. (The proportion of the poor in the "Other Race" category did not change significantly.) The proportion of the poor who are of Hispanic origin increased from 17.4 to 18.4 and 18.2 percent using the 25th and 35th percentile, respectively. The measures based on the 25th and the 35th percentile also lead to a small increase in the proportion who are elderly from 10.0 percent to 11.1 and 11.3 percent respectively (these result in comparable decreases in the proportion who are chldren). One important attribute of the alternatives tested in this paper is the regional variation introduced. Consequently, the distribution of poverty is expected to be different, that is, relatively lower in the South and Midwest and relatively higher in the Northeast and West mirroring rental housing price differences. These expectations are borne out by our estimates. The proportions of the poor in the South and the Midwest under the alternative definitions are lower than the proportion using the official definition. The poverty proportions in the Northeast and the West &e higher, as expected. When examining the effect of regional variation on family characteristics, we find some changes in the distribution of poverty. Because the measures based on the 25th and 35th percentiles of rent result in higher thresholds, family characteristics which are associated with incomes just above the official thresholds will comprise a higher proportion of the poor when regional variations are taken into account. A higher proportion of the poor are married couples and a lower proportion are in female householder families when regional variations are taken into account. The alternate measures also result in a lower propomon of householders not workmg whose families are in poverty and a higher proportion working year-round full-time in poverty as compared to the official definition. When examining educational characteristics, regional variation leads to a higher proportion of families in poverty whose householders had been to college or who did not complete high school and a lower proportion who did not complete high school. B. Effect of Medical Benefits We examine the effect of medical benefits using two alternatives-first, by excluding the value of Medicare, Medicaid, and employer-provided benefits from the post-cash measure of income; and second by also excluding out-of-pocket medical expendmres from income and adjusting the poverty definition to exclude average out-of-pocket expenses. These are then coupled with an assessment of whether the family has adequate health insurance. Table 3 presents poverty estimates based on alternative income definitions but holding the poverty definition constant. Not counting medm1 transfers but considering insurance coverage leads to higher poverty rates than the official thresholds when all noncash income (including medical benefits) is counted (14.7 versus 10.4 percent); poverty is also higher than the official poverty rate (12.8 percent). Excluding out-of-pocket medical expenditures 2

results in a further large increase in the poverty rate (to 20.1 percent). Table 3 also presents the effect of excludmg medical transfers and assessing insurance coverage when the poverty definition is changed. Establishmg regional variation using an income definition that excludes medical transfers results in higher poverty rates at the 25th and 35th percentile (21.3 and 23.6 percent) when compared to the official definition (14.7 percent). When out-of-pocket medical expenses are excluded from income the poverty rates based on regional variations (26.5 to 28.8 percent) are substantially hisher than under the official definition (20.1 percent). Excluding medical transfers also affects the proportion of the poor with selected characteristics. Table 4 presents the effect on the distribution of poverty of excluding medical benefits from income when the poverty definition is held constant (in this case at the official thresholds). Excluding mebcal transfers and requiring insurance coverage results in a decrease in the proportion of the poor who are Black from 29.5 to 25.3 percent; this decreases further to percent when out-of-pocket expenses are subtracted. Similarly, the proportion of the poor who are Hispanic declines from 17.2 to 16.9 and 16.8 percent, respectively. Not counting mebcal benefits has interesting effects on the bstribution of the poor by age. Excluding medical benefits decreases the proporuon of elderly poor from 10.7 to 8.1 percent of the total and increases the proportion of workmg age poor. Th~s reflects both the effect of Medicare coverage for the elderly and employer-provided health insurance for the working age population. Subtracting out-ofpocket medical expenditures, however, has the opposite effect. The proportion of the poor who are elderly increases (from 8.1 to 12.8 percent), whle the proportion of working age poor decreases, reflecting the iugher out-of-pocket expenses for the elderly. We find that excluding medical benefits also has a significant effect on the geographical distribution of the poor even when the official thresholds are used. The proportion of the poor in the South decreases while the proportion of the poor in the West increases. The proportion in central cities also decreases. from 42.0 to 40.1 percent, when out-of-pocket expenses are subtracted. Excluding medical benefits and accounting for health insurance results in an increase in the proportion of the poor in marriedcouple families and a complementary decrease in the proportion in female householder families. In addition, the proportion of poor family householders who did not work decreased and the proportion who worked year-round full-time increased when medical benefits are not counted, reflecting the effect of employer-provided health insurance. 11. CONCLUSIONS The issues central to poverty measurement are many and are not easily resolved. The empirical investigation of several experimental alternatives reported in th~s paper leaves us with some lessons. The development of updated poverty thresholds based on food and housing needs results in significantly higher poverty thresholds and poverty estimates than under the official definition. Also important is proper measurement of the contribution of noncash benefits to well-being, especially that of medm1 benefits. We recommend that future investigations of poverty focus particularly on the role of medcal programs, including an examination of the adequacy of insurance coverage. Characteristics of health insurance are not collected by the CPS (nor by the more detailed Survey of Income and Program Participation-- SIPP). Possible approaches include workmg with health surveys directly (e.g., the Health Interview Survey or the National Medical Expenditures Survey), adding questions to the CPS or the SIPP (SIPP has a "variable topical module" specifically oriented toward special data collection needs), or matching survey data with administrative data such as employer records.

APPENDIX DEVELOPMENT OF ALTERNATIVE POVERTY THRESHOLDS 1. Minimal Food Budget Table 22 in U.S. Bureau of the Census (1991b) gives the distribution of chldren and adults in three-person families. Using those statistics and the U.S. Department of Agriculture Thrifty Food Plan for 1989 yields a weighted average minimal annual food cost for a family of three of $2,970. 2. Minimal Housing Budget The monthly housing cost (rent plus utilities) distribution of all nonsubsidized rented units in the U.S. in 1989 was computed from the American Housing Survey separately for central cities, suburbs, and nonmetropolitan areas within each of the four Census regions. Arbitrarily, the 25th percentile in each region was chosen as the indlcator of a minimal housing budget (as roughly one-eighth of all persons are poor, this allows some choice). The 35th percentile was also chosen for analysis. 3. Multiplier U.S. Department of Housing and Urban Development regulations state that no subsidized household is to pay more than 30 percent of its net income for rent. Recent Consumer Expenditure Survey data shows that the typical family spends roughly 20 percent of its disposable income on food. If food and housing are assumed to account for half the family s budget, then the relevant multiplier is 2.0, yielding three-person poverty thresholds ranging from $11,052 in Southern nonmetropolitan areas ( 111.8 percent of the official three-person threshold) to $16,740 in Western suburbs (169.3 percent). Using the 35th percentile of rent instead of the 25th yields three-person thresholds ranging from $1 1.916 in Southern nonmetropolitan areas ( 120.5 percent) to $18,108 in Western suburbs (183.2 percent). 4. Equivalence Scale As stated in the text, determining the appropriate equivalence scale and family types is difficult. For illustration we have chosen the constant elasticity scale presented by Ruggles (1990, Table 4.4), with no distinction made between elderly and non-elderly persons. This scale ranges from a one-person threshold 57.8 percent of the three-person threshold up to the nine or more person threshold being 174.0 percent of the three-person threshold. 5. Health Insurance As mentioned in the text, there is concern that health insurance coverage is not valued correctly. An alternative measure that has been proposed to supplement the income-based measure is to use an indicator--whether or not the person has adequate health insurance coverage. The data are insufficient to determine insurance adequacy, so for this alternative, if someone in the family is covered at all by Medicare, Medicaid, military, or private insurance all family members are considered adequately covered.6 6. Out-of-Pocket Medical Expenditures Out-of-pocket medical expenditures were estimated from Lefkowitz and Monheit (1991) using data from the 1987 National Medical Expenditure Survey (NMES). These estimates include payments by the family for hospital stays, emergency room visits, outpatient clinic visits, physician visits, dental visits, prescription medicines, home health care, and medical equipment and supplies. Overall for 1987, approximately 85.3 percent of persons used some health services with average cost per person of $1,865 and average out-of-pocket expenditures of $452. Using data from Lefkowitz and Monheit (1991) on the percent of persons using any service and mean cost per user, we calculated average cost per person by age and type of health insurance coverage. In order to obtain estimates for 1989, we adjusted the averages by the change in the Consumer Price Index (CPI) for medical care. The estimates above exclude payments for health insurance premiums. In order to estimate total out-of-pocket expenditures, we used annual out-ofpocket health insurance premiums by income and type of coverage from the 1987 NMES in Vistnes (1992) and adjusted them by the 1987-89 change in the CPI for medtcal costs. These were then added to out-of-pocket expenditures above. For policyholders 65 years and older with private coverage, we obtained unpublished preliminary data from the 1987 NMES whch estimated annual out-ofpocket expenditures of $485. n

When out-of-pocket medical expenditures are subtracted from income, we also reduce the poverty thresholds by 3.6 percent, the ratio of 1987 per capita out-of-pocket expendtures from Lefkowitz and Monheit (1991) to 1987 per capita income (U.S. Bureau of the Census, 1991a). NOTES 1. Use of a thxd equivalence scale, the Canadm scale used for their proposed low-income lines (see Wolfson, 1993), affected the level but not the distribution of poverty (increasing the level by about 0.5 percentage points). 2. Obviously, this cutoff is arbitrary; modest changes do not affect the poverty calculations much if at all. 3. The poverty estimates presented in previous versions of ths paper were revised because of an error in the rent distributions used in the earlier work. The estimates presented in this paper use revised rent levels are significantly higher than those used previously and result in htgher poverty estimates. 4. Comparisons of the effects of noncash income itself on the distribution using the official definition will not be discussed. (See U.S. Bureau of the Census, 1990, for a discussion of those differences.) 5. Jacobs and Shipp (1991) indicate that food was 17.0 percent of current expenditures in 1988-89. 6. Various methods could be used to determine the adequacy of medical coverage. For example, an alternative method to determine the adequacy of medical coverage for family poverty would be to have family members covered. This is pmcularly important when a family member has only one member covered by insurance, and that person is an elderly person covered by Medicare. Such alternatives should be considered in future research. REFERENCES Jacobs, Eva and Stephanie Shipp. 1991. "A History of the U.S. Consumer Expendmre Survey: 1935 to 1988." Mimeo, U.S. Bureau of Labor Statistics. Lefkowitz, D. and A. Monheit. 1991. Health Insurance. Use of Health Services, and Health Care ExDenditures. (AHCPR Pub. No. 92-0017). National Medical Expenditure Survey Research Findings 12, Agency for Health Care Policy and Research: Public Health Service. Ruggles, Patricia. 1990. Drawing the Line. Washlngton, D.C.: Urban Institute Press. US. Bureau of the Census. 1990. "Measuring the Effects of Noncash Benefits on Income and Poverty: 1989." Series P-60 No. 169-RD, September. U.S. Bureau of the Census. 1991a. "Money Income of Households, Families, and Persons in the United States: 1988 and 1989." Series P-60 No. 172, July. U.S. Bureau of the Census. 1991b. "Poverty in the United States: 1988 and 1989." Series P-60 No. 171, July. Vistnes, J. 1992. Private Health Insurance Premiums in 1987: Policyholders Under Age 65. (AHCPR Pub. No. 92-0061 ). National Medical Expenditure Survey Data Summary 5, Agency for Health Care Policy and Research: Public Health Service. Weinberg, Daniel H. and Enrique J. Lamas. 1994. "Measurement of Need: The U.S. Poverty Line." Proceedings of the American Statistical Association, Social Statistics Section. Wolfson, Michael. 1993. "Current Developments in Poverty Measurement in Canada." Paper prepared for meetings of the American Statistical Association, Fort Lauderdale, Florida, January 1993. ACKNOWLEDGEMENTS The authors are Chief, and Special Assistant for SPP, respectively, of the Housing and Household Economic Statistics Division, U.S. Bureau of the Census, U.S. Department of Commerce. We wish to thank Judy Eargle for her indispensable computer programming assistance. None of the conclusions should be considered her responsibility, however. Similarly, the views do not necessarily reflect those of the Census Bureau or the Department of Commerce. Earlier versions of this paper was presented at the conference on Poverty Measurement for Economies in Transition in Eastern European Countries, Warsaw, Poland. October 1991 and at the Winter Meetings of the American Lauderdale, Florida, 5? Statistical Association, Ft. January 1993.

Table 1. Povertv Rates for Alternate Povertv Definitions, 1989 Poverty Rate (percent of persons) income Measure: Official (Cash, pre-tax) Poverty Definition: official 12.8% Expanded (Non-cash, post-tax) o Poverty Definition: Official 10.4 o Poverty Definition: Regional - 25th housing percentile 15.7-35th housinc percentile 17.8 SOURCE: Calculations by the authors from the March 1990 Current Population Survey. Table 3. Povertv Rates for Medical Alternatives, 1989 (all persons) Povenv Rate Poverty Definition: Official 10.4% noncash, post-tax post-tax 14.7 noncash, post-tax, adjusted" 20.1 Povenv Definition: RegionaU25th percentile noncash, post-tax 15.7 noncash, post-tax 21.3 noncash, post-tax, adjusteda 26.5 Poverty Definition: RegionaY35th percentile 17.8 noncash, post-tax noncash, post-tax 23.6 noncash, post-tax, adjusteda 28.8 NOTE a. Poverty thresholds when this income measure is used are adjusted downward by 3.6 percent (see Appendix); estimated out-of-pocket medical costs are subtracted from income. SOURCE: Calculations by the authors from the March 1990 Current Population Survey. Table 2. Distribution of Povenv Using Alternate Definitions: 1989 Povenv Definition Official Official ReeionalR5 RecionaV35 Income Measure Cash. pre-tax noncash, (official) post-tax post-tax post-tax (1) (2) (3) (4) DEMOGRAPHIC GROUP ALLPERSONS RaceNispanic Oriein 67.2 70.5 White 65.9 71.2 28.4 Black 24.9 29.5 24.3 1.4 4.6 Other race 4.5 4.6 17.4 Hispanic origin 18.4 18.2 17.2 81.6 82.6 Non-Hispanic 81.9 82.8 & Under 18 18-44 45-64 65 or older 39.9 12.5 10.7 38.1 38.9 13.0 10.0 36.6 39.3 13.0 11.1 36.4 39.4 13.0 11.3 Location Metropolitan Central city Suburbs Nonmetropolitan South region Northeast region Midwest region West region 72.7 43.1 29.6 27.3 41.1 16.1 22.3 20.6 71.7 42.0 29.7 28.3 43.4 14.4 22.5 19.9 78.7 41.5 37.2 21.3 38.7 16.9 19.6 24.8 78.8 40.8 38.0 21.2 38.3 17.7 19.1 24.8 76.3 73.5 75.3 75.9 35.9 34.8 39.1 40.9 37.0 21.4 35.2 24.2 32.5 24.7 31.4 43.2 43.8 48.9 50.8 5 1.7 50.7 45.5 43.6 5.1 5.5 5.6 5.6 Work status of householder Worked year-round full-time 17.3 29.4 Worked 1-49 weeks Did not work 53.3 17.6 29.2 53.2 28.6 47.3 26.8 28.2 45.0 Family Status In families In marriedcouple families In families with female householder. Unrelated individuals ALLFAMILIES Type of family Married couple Female householder. Male householder. Education of householder Completed 1 or more years of college 15.0 15.4 17.3 Graduated high school, no years 35.6 of college 35.8 36.8 Did not complete hiph school 49.2 49.0 45.9 SOURCE: Calculations by the authors from the March Current Population Survey. 17.7 37.2 45.1 1990

Table 4. Distribution of Povertv Using Alternate Definitions Excludine Medical Benefits: 1989 Poverty Definition: Income Measure Official Cash. pre-tax Official noncash, post-tax Official post-tax. adjusted' 13.) ReplionalR5 post-tax ReeionalR5 Rreionali35 noncash, p0st-m post-tax, adiusted (5.) 16.) ReeionaU35 post-tax. adjusted (7.) ( I.) (2.) 65.9 29.5 4.6 17.2 82.8 70.0 25.3 4.7 16.9 83.1 71.4 4.5 16.8 83.3 72.6 22.9 4.5 16.9 83.1 74.0 21.6 4.4 16.1 83.9 73.4 22.2 4.4 16.6 83.4 74.5 21.2 4.4 15.6 84.4 Under 18 18-44 45-64 65 or older 39.9 12.5 10.7 32.0 14.2 15.6 8.1 33.0 40.1 14.1 12.8 31.7 40.8 14.2 13.2 32.0 38.6 13.5 15.9 31.8 40.3 14.0 13.8 32.1 38.6 13.4 15.9 Location,Metropolitan Central city Suburbs Nonmetropolitan Souh region Northeast region Midwest region West region 72.7 43.1 29.6 27.3 41.1 16.1 22.3 20.6 73.3 12.0 31.4 26.7 10.7 15.3 22.1 21.9 72.2 40.1 32.1 27.8 40.5 15.8 21.4 22.2 78.8 40.8 38.0 21.2 18.5 19.9 24.7 76.2 38.8 23.8 18.2 20.6 23.9 78.7 40.0 38.7 21.3 36.8 18.8 19.9 24.6 76.4 38.3 38.1 23.6 18.4 20.3 23.9 76.3 In married-couple families 35.9 In families with female householder. no swuse present 37.0 Unrelated individuals 21.4 ALL FAMILIES Type of familv 43.2 Married couple Female householder. 51.7 Male householder. 5.1 70.1 36.8 74.2 42.2 73.0 40.7 76.2 46.2 73.9 42.7 76.9 47.5 29.4 27.9 28.1 28.5 7.9 26.2 6.5 27.5 7.4 25.7 6.2 50.7 55.1 54.1 58.9 55.8 59.8 42.7 39.0 39.9 35.6 38.3 34.7 6.5 5.9 5.9 5.6 5.9 5.5 24.2 27.3 18.1 25.2 25.4 47.1 27.0 25.5 42.7 28.8 23.5 42.9 28.8 24.9 43.3 30.7 23.2 42.6 DEMOGRAPHIC GROUP ALL PERSONS RaceMspanic Oriein White Black Other race Hispanic origin Non-Hiaponic & Family Status In families Work status of householder Worked vex-round full-time 17.3 Worked 1-49 weeks 29.4 Did not work 53.3 14.) Education of householder Completed 1 or more years of college 15.0 17.2 16.6 18.1 18.2 18.4 Graduated high school. no years of college 35.8 36.6 35.8 37.0 37.5 Did not complete hieh school 49.2 46.3 47.6 45.0 44.8 44.1 NOTE: a. Poverty thresholds when this income measure is used are adjusted downward by 3.6 percent (see Appendix): pocket medical costs are subtracted from income. SOURCE: Calculations by the authors from the March 1990 Current Population Survey. 7 18.6 44.0 estimated out-of-