Adding Health Care Spending to the Poverty Equation

I discussed the challenges of measuring poverty in the United States in a three part series on this blog last year. The official poverty line is based on pre-tax income adjusted for household size. The main alternative to the official poverty measure is the Census Bureau’s Supplemental Poverty Measure (SPM), which adjusts for many more factors such as receipt of public benefits and cost of living variations across regions. One significant aspect of the SPM is that it deducts out-of-pocket health care spending from a family’s income. In other words, if a family spent $2,000 on medical care last year, that amount will be fully subtracted from their income, making them appear $2,000 poorer. Is this a good idea?

Bruce Meyers and James Sullivan argue in a recent paper that it is not. They perform a head-to-head comparison of the SPM with the official poverty line and find that, holding the size of the population fixed, adopting the SPM will tend to skew the population “in poverty” toward families that spend more on health care, and that these families are less disadvantaged than those that are now classified as non-poor. Here’s what they say, which is worth quoting at length:

“On the one hand, large out-of-pocket medical expenses resulting from poor health can drain family resources. On the other hand, these expenses can arise because families choose to allocate resources towards health, purchasing expensive health insurance or electing to have procedures that are not fully covered by insurance. It is difficult a priori to determine whether most out- of-pocket medical spending reflects those with lower health status or those who have greater resources and make choices to spend more on out-of-pocket health care costs. While our analysis does not directly address the connection between health status and health spending, our findings point out that when out-of-pocket medical expenses are subtracted from income to calculate poverty, those identified as “poor” have higher consumption, more education, more rooms in their home and are more likely to be covered by health insurance. This pattern is consistent with a belief that many families with large medical out-of-pocket expenses have the resources to support such spending, and they are making a choice to spend as much as they do on medical care. The importance of this issue, and its substantial impact on who is defined as poor, suggests a need for more research on the relationship between health spending and health status.” 

Let’s take a step back. We know from the health economics literature that medical care is a normal good, meaning that people consume more of it as their incomes increase. There could be many reasons for this. In the short run, many people postpone seeing a doctor when their budgets are tight. As the income constraint is relaxed, they will seek more care that improves their immediate quality of life such as back surgery and dental treatment. People may also be more willing to undertake investments in their future health, such as taking statins for high cholesterol, when their incomes increase because they expect they will live longer and happier lives. Without placing a judgment on whether this spending is worth it from a societal perspective, there is clearly some component of health care that reflects people’s tastes and desires. The same can be said about food: as people’s income increases, they will eat better tasting, (and we hope) better quality foods. Fully deducting for these kinds of expenses may therefore tend to understate the resources of families that utilize a lot of health care.

Of course, income is not the only factor that drives out-of-pocket spending on health care, so too does access to subsidized health care and health conditions. A person who earns twice the poverty level, but spends half their take home income on medical expenses stemming from a chronic condition has the same effective amount of resources as a health person living on the poverty line – money that is spent managing an urgent or persistent health condition is money that cannot be used to plug other holes in the budget. Although Sullivan and Meyer do not dwell on the point, the population that is counted as poor under the SPM is older and less likely to receive public health insurance. In some of my own work, I have looked at this population with the same data and I find that they are disproportionately households headed by adults in their late forties and early fifties. My hunch is that many of these families are the working poor as they near retirement. They are families that have amassed more material possessions, but they are also beginning to experience the burden of chronic health problems. By comparison, families that fall under the official poverty line are much more likely to participate in public insurance because they are often poor enough on an income basis to make Medicaid eligibility in their states, and they tend to be younger with children.

This is the problem that a measurement of poverty has to address. We need to compare the circumstances of two very different kinds of households, the older family with more resources and more needs on the one hand, and the younger family that can use public health insurance when they need it, but who are also more susceptible to material deprivations. To make these apples-to-apples comparisons we should make some adjustment for insurance status and health conditions. One way to do this is to try to monetize the value of public insurance for low-income people (see my post from last month) or to subtract from budgets the expected cost of having a different kind of health condition. This kind of nuanced adjustment could be done by combining several different datasets such as the Medical Expenditure Panel Survey and the Survey of Income and Program Participation.

Beyond getting the empirical measurement right, there are deep conceptual puzzles to be resolved. Before we can say whether a poverty measurement is adequate or inadequate, we need to be very clear about what the purpose of measuring poverty should be. The population of people that gets lumped together as “poor” is amorphous and shifting across time and space. Our differing measurements of poverty each reflect a particular aspect of social concern, ranging from what people can realistically obtain with their bundle of resources to how much what the government does for different populations changes the wellbeing of those groups. This latter point is critical for whether we keep or drop out-of-pocket costs – depending on how you look at it, the Affordable Care Act will be expected to lift millions of low-income adults out of poverty in the next three years.

About Brendan Saloner

I am a postdoctoral fellow at the University of Pennsylvania in the Robert Wood Johnson Health and Society Scholars Program. I completed a PhD in health policy at Harvard in 2012. My current research focuses on children's health, public programs, racial/ethnic disparities, and mental health. I am also interested in justice and health care.
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8 Responses to Adding Health Care Spending to the Poverty Equation

  1. Brad F says:

    Uwe Reihnardt’s take on the same from last month, well worth reading:

    His example of rising physician pay, and how the benefit imputes to Medicaid beneficiaries illustrates the problem you cite. In spades.


  2. Thank you, Brad! It’s always impressive to see how someone like Reinhardt can really bring this issue to life. He explains several things that I tried to allude to, but more clearly.

    Here’s what he said about the issue I was grappling with a few weeks ago:

    “At the theoretical level, economists use one of two approaches to valuing benefits in kind from the recipient’s perspective.

    The standard approach is to define the value of a benefit in kind to recipients as the maximum they would pay for it out of their own money income. That imputed value, of course, would depend in part on the recipient’s money income. As I remarked in an earlier post, most economists have no problem with that, but the public might.

    An alternative is to use an approach I explored in a related post, here amplified by my lecture notes to students. Suppose we gave a hypothetical recipient not the benefit in kind but the cash it costs taxpayers to provide the benefit. How much of that cash would that recipient then spend on the benefit? Perhaps even more, in case of insurance? Whatever the case may be, we would use that amount as the value imputed to the benefit. That imputed value, of course, would partly depend on the recipient’s money income as well.”

  3. “Although Sullivan and Meyer do not dwell on the point, the population that is counted as poor under the SPM is older and less likely to receive public health insurance. In some of my own work, I have looked at this population with the same data and I find that they are disproportionately households headed by adults in their late forties and early fifties.”

    One point to note here is that the big increase in income poverty using the SPM is among the over-65 group. (Although I imagine there is also some increase among the near-elderly.)

    Also, Sanders Korenman and Dahlia Remler have a new paper on the inclusion of health care expenditures in the SPM, it’s at: They conclude: “Subtracting MOOP expenditures from resources worsens a poverty measure’s predictive validity and excluding assets exacerbates this bias, since assets fund MOOP expenditures. Health shocks do not result in reported material hardship for the elderly but do for the near-elderly.” Instead of just subtracting health care spending (without including medical benefits on the income side), they argue for a “health-inclusive” measure.

    • Hi Shawn,

      Nice to hear from you.

      Thank you so much for the Korenman and Remer citation. Reading their paper — which is long but worthwhile — hits home some of the important conceptual and measurement issues. I won’t comment much on their paper here, other than to say that I thought that the idea of a Health Inclusive Poverty Measure (HIPM) was plausible under the conditions they described. I still think we should keep working on the problem of identifying the fungible value of public programs like Medicaid, since we have to, on some margin decide whether to plow more money into health care or other benefits for low-income populations.



  4. Thanks for every other magnificent post. Where else may just anybody
    get that type of information in such a perfect means of writing?

    I have a presentation next week, and I am on the search for such information.

  5. Dahlia Remler here. Sandy Korenman and I have released an updated version of our paper. It has significant new content that our APPAM conference paper did not, including illustrative HIPM calculations and analysis showing that elderly individuals who become poor due to the SPM’s unlimited MOOP deduction do not appear poor based on many other indicators.

  6. Thanks Dahlia! I’ll give it a read, and hopefully I can find some time to blog more about this important issue. Best wishes, Brendan

  7. Simone Bailey says:

    Medical care likewise long term care are really expensive nowadays. Since the demand is greater because people are living much longer, then access to healthcare and long term care will be more expensive. The one who will surely suffer from these are people are the unfortunate ones. It’s hard for them to make their ends meet and much more when they need to seek medical attention. The cost of long-term care insurance and health insurance is pricey as you can see here:, and the only way poverty-stricken people can afford this is through government programs. I really hope the Affordable Care Act will pan out as beneficial to the people and can give them the proper care they need.

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