National Academies Press: OpenBook

Measuring Poverty: A New Approach (1995)

Chapter: Medical Care Needs and Resources

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Suggested Citation:"Medical Care Needs and Resources." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
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Page 223
Suggested Citation:"Medical Care Needs and Resources." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
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Page 224

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DEFINING RESOURCES 223 having no value to the recipients and that it assumed the same demand for subsidized goods and services among program participants as among near- poverty nonparticipants. Needed Research and Development We agree with the Census Bureau's use of market values for food stamps and other nonmedical in-kind benefits, primarily on the ground of operational feasibility. The major problem area concerns public housing, for which it is most likely that recipients would not value the benefit as much as an equivalent amount of cash and for which there are difficulties in accurately ascertaining the market value or the recipient value. The Census Bureau has changed its procedure for estimating rental subsidies several times over the decade to strive for greater accuracy. Yet there is evidence that problems remain. Thus, the Census Bureau's aggregate estimates of housing subsidies are considerably below the subsidy amounts reported as outlays by the U.S. Department of Housing and Urban Development (HUD). For example, Steffick (1993) cites 1990 total outlays of $13 billion but the Census Bureau estimates $9 billion in total subsidies for that year. The distribution of subsidy amounts among families may also be problematic. As an example, although housing costs vary considerably by geographic area, the Census Bureau's estimates distinguish only the four major regions (see Steffick, 1993, on this point). Finally, the Census Bureau is still using data from the 1985 American Housing Survey, which are now quite old. At a minimum, the Census Bureau should reestimate its model with later AHS data. Ideally, more research should be conducted on methods for valuing housing subsidies. We note that SIPP affords the opportunity to improve the valuation of nonmedical in-kind benefits. SIPP includes more benefits (specifically, LIHEAP, WIC, and School Breakfast) than does the March CPS and provides more accurate reporting because of more frequent interviews. SIPP also ascertains housing costs (rent and utilities) for people in subsidized as well as unsubsidized housing and so provides a much better basis for imputing rental subsidies than does the March CPS, which lacks housing cost data. The Census Bureau is currently developing an in-kind benefit valuation program for SIPP, and we urge that this work move forward. Medical Care Needs and Resources The issue of how best to treat medical care needs and resources in the poverty measure has bedeviled analysts since the mid-1970s, when rapid growth in the Medicare and Medicaid programs (and in private health insurance) led to a concern that the official measure was overstating the extent of poverty among

DEFINING RESOURCES 224 beneficiaries because it did not value their medical insurance benefits. Yet after almost two decades of experimentation, there is still no agreement on the best approach to use. (See Moon, 1993, for a review of past approaches and suggested alternatives.) Two problems make it very difficult to arrive at a solution that both achieves the necessary consistency between the threshold concept and the resource definition and is feasible to implement. The first problem is that medical care benefits are not very fungible—they may free up resources to some extent, but they by no means have the fungibility of, say, food stamps. There are two reasons that food stamps are essentially interchangeable with money: (1) virtually all households spend at least some money for food, so the receipt of food stamps frees up money income for consumption of other goods and services; (2) the maximum food stamp allowance is low enough that it is unlikely households would receive more benefits than the amount they would otherwise choose to spend on food. Neither of these conditions holds for medical care benefits: not all families have medical care needs during a year, and, although medical care benefits for low-cost services (e.g., a prescription drug or a doctor visit) may free up money income for other consumption, the "extra" benefits received from insurance (or free care) to cover expensive services (e.g., surgery) are not likely to free up money income to the same degree. Hence, approaches that add the value of medical insurance benefits to income without also increasing the thresholds have the perverse effect that sick people look better off than healthy people even though their extra "income" cannot be used to support consumption. In the more common practice of assigning average benefits for groups (i.e., valuing medical benefits at the assumed insurance premium amount), the result is similar—to make sicker groups, such as the elderly or disabled, look better off than healthier groups. However, any attempt to develop thresholds that appropriately recognize needs for medical care runs into the second problem: that such needs are highly variable across the population, much more variable than needs for such items as food and housing. Everyone has a need to eat and be sheltered throughout the year, but some people may need no medical care at all while others may need very expensive treatments. One would have to develop a large number of thresholds to reflect different levels of medical care need, thereby complicating the poverty measure. Moreover, the predictor variables used to develop the thresholds (e.g., age, or self-reported health status) may not properly reflect an individual's medical care needs during any one year: some people in a generally sicker group may not be sick that year and vice versa for people in a generally healthier group. The result would be that it would be very easy to make an erroneous poverty classification. A related issue is that, until very recently, hardly any research on this topic considered the question of out-of-pocket medical care costs. Even groups with good medical insurance coverage, such as the elderly, pay some of their

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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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