Here's the abstract:
The expansion of Medicaid to low-income nondisabled adults is a key component of the Affordable Care Act's strategy to increase health insurance coverage, but many states have chosen not to take up the expansion. As a result, for many low-income adults, there has been stark variation across states in access to Medicaid since the expansions took effect in 2014. This study investigates whether individuals migrate in order to gain access to these benefits. Using an empirical model in the spirit of a difference-in-differences, this study finds that migration from non-expansion states to expansion states did not increase in 2014 relative to migration in the reverse direction. The estimates are sufficiently precise to rule out a migration effect that would meaningfully affect the number of enrollees in expansion states, which suggests that Medicaid expansion decisions do not impose a meaningful fiscal externality on other states.This paper gets at the heart of a classic topic in economics: the optimal division of roles between federal, state, and local governments -- known as fiscal federalism. On the one hand, assigning greater responsibility at the state or local level can help better align policy with local preferences. On the other hand, when one locality can exert an externality on another locality, decentralization can create inefficiency. Migration--especially migration in response to state-level means-tested benefits--can be a major source of externalities in this context: if a cut in means-tested welfare benefits in one state leads to migration of beneficiaries from that state to another, states might tend to engage in a “race to the bottom” which would not be optimal when viewed nationally.
The 2014 Medicaid expansion in the ACA is a highly unique setting to study “welfare migration” (also known as “welfare magnetism”). From a methodological perspective, the expansion of Medicaid to roughly half the country but not the other half creates very large variation in access to health care -- much larger variation than is typically studied in this literature. From an immediate policy perspective, migration responses were often cited by non-expanding states as a reason why they should not expand. Even if the state expenditures on newly eligible beneficiaries were small (due to the 90% long-run federal match), policymakers often argued that an influx of Medicaid-eligible individuals would cause expenses on other programs, such as education, to grow in excess of the associated growth of the tax base. Is the feared migration response evident in the data?
To get at this question, I use public use data from the American Community Survey (ACS) through 2014. The large sample size of the ACS allows me to examine a subgroup of low-income individuals -- in particular, those whose reported income places them below the cutoff for Medicaid eligibility in most expansion states (138% of poverty). This data set isn't perfect, of course. I'd prefer if ACS interviews were performed all at once -- ideally toward the end of the year -- rather than on a rolling basis. Furthermore, income can be endogenous to migration decisions. Read the paper for how I handle these issues.
Given this sample, I perform a difference-in-differences analysis, with a subtle twist. One dimension of the difference-in-differences is time, with 2014 as the "post" period. The other dimension is direction of migration flow: migration from non-expansion states to expansion states, versus migration in the opposite direction. In other words, I examine whether non-expansion-to-expansion migration increases in 2014, relative to the analogous increase in expansion-to-non-expansion migration in 2014. Here's the twist: In this difference-in-differences, non-expansion-to-expansion migration is playing the role of treated and expansion-to-non-expansion plays the role of control. However, both directions are plausibly "treated." Most obviously, the Medicaid expansion could increase non-expansion-to-expansion migration as people migrate in order to gain eligibility. But the expansion could also reduce migration in the opposite direction; e.g., individuals who would otherwise have migrated from an expansion state to a non-expansion state decide not to out of fear of losing coverage. Both of these effects push the estimates I get in the same direction. So, this empirical strategy is a test for whether at least one of these effects exists.
Spoiler: neither effect appears to exist.
Figure 2 from the paper, reproduced below, shows the results in graph form. The blue dotted line shows the migration rate from expansion states to non-expansion states, expressed as the percent of migrants relative to the size of the initial subgroup population. The green solid line shows the migration rate from non-expansion states to expansion states -- this is the flow we would expect to see grow in 2014 (relative to the opposite flow) if Medicaid caused migration. Since about 2008 (when I start my estimation sample), the trends in migration in these two directions were fairly parallel, which is reassuring. And, in 2014, these parallel trends appear to continue. This, visually at least, this strategy finds no effect of the expansion on migration. The regression estimates, which you can read about in the paper, confirm this null estimate. In fact, I show that the null estimate is sufficiently precise to rule out a 2% migration-induced increase in the Medicaid eligible population in expansion states, even under very aggressive assumptions. This suggests that the fiscal externality from expanding Medicaid is quite small. Additionally, in the paper, I restrict the sample to individuals who live close to the border of an expansion state and a non-expansion state; the estimates get noisier but remain consistent with a null effect.
So, why aren't people migrating? There are several possible explanations. Most obviously, moving might be quite costly relative to the perceived benefit of Medicaid. This would be consistent with the work of Finkelstein, Hendren, and Luttmer (2015), based on the Oregon Health Insurance Experiment. This could also be because individuals don't expect to stay on Medicaid for an extended period of time, and thus the cumulative value of Medicaid coverage is fairly small.
Another explanation could be that the time horizon of the 2014 ACS is too short; it might take time for individuals to learn about expanded coverage in other states, and it may take time for individuals to actually move. In the paper, I punt on this, since the 2014 ACS is the latest data I had.
Fortunately, the 2015 ACS has recently been released. The following figure is a version of Figure 2, extended to 2015. (Some states expanded Medicaid between 2014 and 2015. This figure drops those states, and disregards moves made into those states, so the graph through 2014 will look a bit different than Figure 2.) This figure shows that, if anything, non-expansion-to-expansion migration fell somewhat in 2015 relative to migration in the opposite direction -- an effect which has the opposite sign than one would expect if Medicaid expansions caused a delayed migration effect in 2015. Note that I have spent significantly less time analyzing the 2015 ACS relative to the analyses that made the actual paper, so take this result with a grain of salt. Nevertheless, the 2015 ACS appears to confirm the results obtained using the 2014 ACS: the ACA Medicaid expansions did not seem to induce migration.
earlier post I made on JPAM's website.