it does not seem inconceivable to construct an ex post index, much like the SPM, which could be used to assess different programs, such as the Supplemental Nutrition Assistance Program and Temporary Assistance for Needy Families.

Clarification is needed on what is of most interest: a measure that indicates the policy’s effectiveness contemporaneously or one that indicates the risk of individuals facing a large out-of-pocket expense or medical emergency in the future. The latter is more the intellectual exercise that one associates with risk, insuring against uncertain events.

Short mentioned in her presentation that one of the problems with the SPM is that, if one assigns the uninsured to be insured, it makes them look worse off economically because the SPM records just spending. She said that what is needed is an MCER measure to show that the insured are better off.

If these measures are constructed as separate indices, there is no obvious way to capture that any one individual is better off or, in some aggregate sense, that all are better off. He said he actually likes the idea of two separate indices.

Ziliak pointed out the literature on multidimensional measures of poverty and deprivation. The United Kingdom has a measure of deprivation with something like 70 different items, and they are added up into a single index. So surely in the United States it is possible to add two measures together to come up with some index. There is recent work on multidimensional measures of well-being that could be aggregated into a single index (i.e., Alkire and Foster, 2011; Bourguignon and Chakravarty, 2003).

He commented that measuring poverty appears a lot easier, perhaps because it has been going on for a lot longer. One draws a line based on some measure of needs and then counts resources and compares one with the other. It seems straightforward.

But with the concept of MCER, the notion of the thresholds is still not well defined at this point in time, because what people need has not been well defined. But if one were to use different thresholds, he said he thought that it would be important to capture employment status. Part of the reason is that a lot of money is spent in this country on work-related injuries and illness. He noted that coverage and type of coverage seem critical in thinking about thresholds. Geographic adjustment is also important, as indicated by cross-state variation.

Finally, in terms of data, Ziliak said he leans heavily toward moving forward using the CPS ASEC as the data set of choice, in part because of the need to go forward; there is a mandate in the ACA about constructing measures reflecting state differences and medical need. The CPS ASEC has large sample sizes, and it has introduced medical out-of-pocket spending,

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