National Academies Press: OpenBook

Measuring Poverty: A New Approach (1995)

Chapter: Accuracy of Medical Care Expense Imputations

« Previous: Equivalence Scale Effects
Suggested Citation:"Accuracy of Medical Care Expense Imputations." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
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Page 271
Suggested Citation:"Accuracy of Medical Care Expense Imputations." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
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Page 272
Suggested Citation:"Accuracy of Medical Care Expense Imputations." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
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Page 273

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EFFECTS OF THE PROPOSED POVERTY MEASURE 271 smaller and larger families, but, with one exception, the effects are small. The exception is the category of one-person families, for which the 0.75 factor reduces their poverty rate by almost 4 percentage points (on a standardized basis) compared with the official rate. One can see why this occurs by looking at Figure 3-5 (in Chapter 3): the equivalence scale value for one-person families with the 0.75 factor is lower than the current scale value, while the scale values for other family types are very similar. The difference in the scale values for one-person families stems from the fact that the current measure assumes that unrelated individuals need almost 80 percent as much as two-adult families, but the proposed equivalence scale with the 0.75 scale economy factor assumes that unrelated individuals need only about 60 percent as much as two-adult families. (Expressed another way, the current measure assumes that two-adult families need only 29% more than one-adult families, while the proposed scale with the 0.75 factor assumes that they need 68% more. These relationships are not quite the same when the second person in a family is a child; see Chapter 3.) The scale economy factor of 0.65 affects poverty rates to a moderate extent for people in almost all family size categories, although the net effect for the total population balances out to almost zero. The 0.65 factor reduces poverty for unrelated individuals (although not as much as the 0.75 factor) and also for people in families of five, six, and seven or more persons. In contrast, it increases poverty for people in two-person and three-person families. The reason for these results is that the 0.65 factor assumes greater economies of scale than either the measure with the 0.75 factor or (in most instances) the current measure. Hence, the 0.65 factor generally produces higher scale values than the other two measures for two- and three-person families and lower scale values for families of five or more persons. (The scale value for unrelated individuals with the 0.65 factor is between the other two values for this group; see Figure 3-5.) In sum, the scale with the 0.75 factor has little effect on poverty for most family size categories but a large (negative) effect on unrelated individuals; the scale with the 0.65 factor has moderate effects on every category. Neither scale affects poverty among children to any degree because almost 80 percent of children are in families of 3-5 persons, for which the effects tend to balance out. In contrast, because 85 percent of the elderly are in families of one or two persons (with 54% in the latter category), the scale with the 0.75 factor lowers the poverty rate for the elderly by a significant amount, while the scale with the 0.65 factor has the opposite effect (see Table 5-9). Accuracy of Medical Care Expense Imputations The imputation of out-of-pocket medical care expenses is the component with the biggest single effect on the overall poverty rate under the proposed

EFFECTS OF THE PROPOSED POVERTY MEASURE 272 measure, increasing the rate by 2.1 percentage points in standardized terms. Clearly, a question is the adequacy of the imputation procedures. One way to assess their adequacy is to inspect the results for reasonableness. Thus, the results we obtained meet such obvious tests as that the amounts imputed, in total and by characteristics, match the dollar totals obtained from the NMES data. Also, the imputed amounts make sense in relation to families' income levels: for families with gross money incomes around the median, we imputed an average of about $2,150 for out-of-pocket medical care expenses; for families with incomes around the 10th percentile, we imputed an average of only $450 for such expenses. (Table 5-4 shows the combined amount of deductions for out-of-pocket medical care, child care, and other work-related expenses that were imputed to families at different points in the income distribution.) Some recent research studies provide information to evaluate alternative imputation procedures for out-of-pocket medical care expenditures, including ours. Weinberg and Lamas (1993) estimated poverty rates for 1989 under several measures, including some that took account of out-of-pocket medical care costs that they imputed to the March 1990 CPS by using 1987 NMES data. Specifically, they imputed mean 1987 expenditures, updated to 1989 with the Consumer Price Index (CPI) for medical care, to people under age 65 categorized by age group (under 5, 6-17, 18-44, 45-64) and health insurance coverage (any private insurance, public insurance only, uninsured) and to people aged 65 and older categorized by health insurance coverage (Medicare only, Medicare and other public coverage, Medicare and private coverage, uninsured). Because they also made some other changes to the poverty definition, it is not possible to estimate precisely the marginal effect on poverty rates of subtracting their imputed values for out-of-pocket medical care costs. Roughly, it appears that the effect would be to increase the 1989 poverty rate of 12.8 percent by 5.4 percentage points (Weinberg and Lamas, 1993: Table A-2); this increase is 6.1 percentage points standardized to the 1992 poverty rate of 14.5 percent. Doyle, Beauregard, and Lamas (1993) used the 1987 NMES itself, projected forward to income year 1991 and calibrated to the March 1992 CPS, to estimate poverty rates with the current definition and measures that excluded out-of-pocket medical care costs. (They also estimated poverty rates with variations of a two-index approach.) For one measure, they calculated out-of- pocket expenses in the same manner as Weinberg and Lamas (1993) (i.e., by using subgroup means); for another measure, they used the actual out-of-pocket expenditures reported in the NMES for each family unit. With subgroup means, they estimated that the subtraction of out-of-pocket medical care costs would increase the 1991 poverty rate of 14.2 percent by 1.9 percentage points; with the use of actual NMES expenditure data, they estimated

EFFECTS OF THE PROPOSED POVERTY MEASURE 273 that the increase would be 1.1 percentage points (Doyle, Beauregard, and Lamas, 1993: Table 2a).14 Hence, there are four estimates, including the panel's, of the effect on poverty of subtracting out-of-pocket medical care costs (including health insurance premiums) from income (standardized to 1992): • 6.1 percentage points, with group means imputed to the March 1990 CPS (Weinberg and Lamas, 1993); • 2.1 percentage points, with the more elaborate imputation procedure that we carried out on the March 1993 CPS; • 1.9 percentage points, with group means imputed to a 1987 NMES file calibrated to the March 1992 CPS (Doyle, Beauregard, and Lamas, 1993); and • 1.1 percentage points, with actual expenditure data from a 1987 NMES file calibrated to the March 1992 CPS (Doyle, Beauregard, and Lamas, 1993). Clearly, the effect on the poverty rate of subtracting out-of-pocket medical care costs from income is less with the use of actual data than with imputed data. Also, a more elaborate imputation (e.g., that conducted by the panel) produces less of an effect than a simpler imputation. These findings are as expected because the distribution of out-of-pocket medical care costs is highly skewed: many people have relatively low-costs, while some people have high costs that raise the average, even within subgroups. Hence, an imputation procedure (particularly a simple one) is likely to overstate the expenses of enough people so as to overstate the increase in the poverty rate. Finally, there is an unexplained difference attributable to the use of a different survey file: namely, estimates of the effect on the poverty rate of subtracting out-of-pocket medical care costs with the NMES are lower than those with the March CPS, even when the same procedure of imputed subgroup means is used.15 Overall, it is not possible to draw a definitive conclusion about our approach because of the differences in the data and procedures used to calculate each of the estimates. However, it appears that our estimate is roughly consistent with all the available work, although it may somewhat overstate the 14 Again, these are rough estimates because Doyle, Beauregard, and Lamas also made other changes to the poverty measure, specifically, excluding taxes from income and reducing the official poverty thresholds by 3.6 percent to account for average out-of-pocket medical care expenses for the total population. A tabulation run for the panel, which provides a better estimate of the marginal effect, estimated an increase in the poverty rate of 0.8 percentage point with the approach of using actual expenditure data from the NMES. (This tabulation kept taxes in the income definition and lowered the official thresholds.) 15 One factor that may contribute to the difference is that Doyle, Beauregard, and Lamas (1993) updated the 1987 NMES expenditure data by changes in the national health accounts rather than by the change in the medical care component of the CPI.

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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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