National Academies Press: OpenBook

Measuring Poverty: A New Approach (1995)

Chapter: Adding Health Insurance Benefits to Income

« Previous: Current Poverty Measure
Suggested Citation:"Adding Health Insurance Benefits to Income." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
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Suggested Citation:"Adding Health Insurance Benefits to Income." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
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Page 228
Suggested Citation:"Adding Health Insurance Benefits to Income." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
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Page 229
Suggested Citation:"Adding Health Insurance Benefits to Income." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
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Page 230

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DEFINING RESOURCES 227 Adding Health Insurance Benefits to Income Work by the Census Bureau and others on valuing health insurance benefits was stimulated by the expansion of health insurance coverage in the public and private sectors. The work began on the assumption that health care benefits could be added to income just like other in-kind benefits (e.g., food stamps), without adjusting the

DEFINING RESOURCES 228 poverty thresholds. Analysts quickly moved from trying to add to income the actual benefits received by a particular individual because this approach had the perverse effect of making sicker people look richer than healthier people. However, as Moon (1993) points out, the preferred strategy of adding average insurance values for groups is hardly better, because it has the effect of making sicker groups (e.g., the elderly or disabled) look richer than healthier groups. Over the years, the Census Bureau has tried several approaches to valuing Medicare and Medicaid benefits, including a market value approach, a recipient value approach, the poverty budget shares approach, and the current method, called the "fungible value" approach. (See Chiswick, 1985, for a critique of the first three approaches.) The agency has also assigned values to employer- provided health insurance. In all of this work, the Census Bureau has compared estimates of income including values for health insurance benefits to the official thresholds without adjustments. In brief, the fungible value approach for valuing Medicare and Medicaid benefits starts with the market insurance value but includes only the portion that is determined to be fungible in the sense that it frees up resources that could have been spent on medical care (see Bureau of the Census, 1993a:B-1–B-3). The determination of the fungible portion of Medicare or Medicaid is made by comparing a family's income to a poverty threshold consisting only of food (based on the USDA Thrifty Food Plan) and housing (based on fair market rents determined by HUD). Then for each family, the value of the mean Medicare or Medicaid benefits (or both) for families in the same risk class is added to income to the extent that the family has any income that exceeds the new, lower threshold.19 The effects of adding Medicare and Medicaid benefits to income without adjusting the thresholds are dramatic; see Table 4-2.20 In 1986 (the last year for which estimates are available to compare across valuation methods), the fungible value approach reduced the poverty rate by 1.1 percentage points (or 8%) for the total population and by 2.5 percentage points (20%) for the 19 The risk classes for Medicare are people age 65 and over and the blind and disabled by state. The risk classes for Medicaid are people age 65 and over, the blind and disabled, nondisabled people age 21-64, and nondisabled people under age 21, by state. As an example of the calculation, if a family's risk class had average Medicare benefits of $2,500 per year and $1,000 of income that exceeded its food and housing needs, then only $1,000 of the Medicare benefits would be added to income. 20 These and other estimates derived from the Census Bureau's experimental poverty series should be viewed as approximate. In most instances, one cannot determine from the published tables the purely marginal effects of a particular change because the tables generally show the cumulative effects of more than one change. For example, one definition might add food stamps and the next might also add Medicare. An estimate of the effects of Medicare obtained by comparing poverty rates between the two definitions will thus be affected by interactions between the effects of food stamps and Medicare.

DEFINING RESOURCES 229 TABLE 4-2 Poverty Rates with and without Insurance Values for Public and Private Medical Care Benefits Under Different Valuation Approaches, Selected Age Groups, 1986, in Percent Population Group and Fungible Valuea Market Valueb Recipient Valueb Medical Care Benefit Total Population Official definition 13.6 13.6 13.6 Including Medicare only 13.1 N.A. N.A. Including Medicaid only 13.1 N.A. N.A. Including Medicare and 12.5 10.3 12.3 Medicaid Also including employer- 12.0 provided insurance People under Age 18 Official definition 20.5 20.5 20.5 Including Medicare only 20.3 N.A. N.A. Including Medicaid only 19.4 N.A. N.A. Including Medicare and 19.2 16.1 19.0 Medicaid Also including employer- 18.4 provided insurance People Aged 25–44 Official definition 10.2 10.2 10.2 Including Medicare only 10.0 N.A. N.A. Including Medicaid only 9.8 N.A. N.A. Including Medicare and 9.6 8.4 9.6 Medicaid Also including employer- 9.1 provided insurance People Aged 65 and Over Official definition 12.4 12.4 12.4 Including Medicare only 10.0 N.A. N.A. Including Medicaid only 12.3 N.A. N.A. Including Medicare and 9.9 4.1 8.2 Medicaid Also including employer- 9.8 provided insurance NOTE: The Census Bureau uses a single market value approach to estimate the value of employer- provided health insurance benefits; the effects are shown in the fungible value column because the latter is the current preferred approach for valuing public health insurance benefits. N.A., not available. a Calculated from Bureau of the Census (1988b: Tables F, H). b Calculated from Bureau of the Census (1988a: Tables C, 1).

DEFINING RESOURCES 230 elderly. The reductions in the poverty rate under the recipient value approach were somewhat larger: 1.3 percentage points (10%) for all people and 4.2 percentage points (34%) for the elderly. The reductions in the poverty rate under the market value approach were quite large: 3.3 percentage points (24%) for the total and 8.3 percentage points (67%) for the elderly.21 Adding in the value of employer-provided health insurance further reduces poverty (see Table 4-2), although not to a marked extent.22 In 1986, the effects were greatest for working-age people 25-44 (reducing their poverty rate by 0.5 percentage point, or 5%) and least for those aged 65 and over (reducing their rate by only 0.1 percentage point, or 1%). Moon (1993:6-7) terms the current Census Bureau fungible value method for valuing government medical insurance benefits an improvement over previous approaches but still flawed: By allowing the value of benefits to fully fill in the gap between food and housing costs and the poverty line, the formula effectively assumes that all resources beyond food and housing would be devoted to medical expenses up to the poverty line. This is an improvement over counting the full value of medical benefits as part of resources, but it still has the essential problem of treating as fungible benefits that can be used for only one purpose. For the elderly, it effectively establishes a new—and lower—poverty threshold equivalent to the food and housing minimum budgets. If the expansion of health insurance benefits that began in the 1960s had served to offset the out-of-pocket expenses component of the poverty thresholds, then it might have been appropriate to add insurance values to resources in some way without adjusting the thresholds. However, what happened is that demand for medical care increased dramatically: per capita medical care spending more than doubled over the 1970-1990 period, rising from $1,166 to $2,566 (in 1990 dollars). Individuals' out-of-pocket share declined, but the real dollar average of out-of-pocket expenditures increased by 25 percent—from $478 in 1963 to $597 in 1990, both figures representing about 4 percent of per capita median income (Moon, 1993:23). In other words, health insurance paid for increased use of medical services, but it did not reduce average out-of-pocket expenses. One reason is that many forms of insurance require individuals to pay part of their expenses, so that the higher demand for medical 21 The poverty budget shares approach reduced the poverty rate in 1985 (the last year in which this approach was used) by 1 percentage point (7%) for the total population and by 3.1 percentage points (25%) for the elderly, similar to the effect of the fungible value approach (Bureau of the Census, 1986: Tables C, D). 22 The Census Bureau estimates employer contributions through a model developed from a statistical match of the March CPS and the 1977 National Medical Care Expenditure Survey. The Census Bureau hopes soon to update its model by using data from the 1987 NMES—see Bureau of the Census (1993a:B-3–B-4).

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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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