The Effect of the Affordable Care Act Medicaid Expansion on Migration

 I have a new paper out in JPAM: "The Effect of the Affordable Care Act Medicaid Expansion on Migration."

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.

Is the new Health Inequality paper in JAMA driven by the exclusion of zero earners? Probably not.

A new paper in JAMA by Chetty, et al., is getting a lot of press, and rightly so. Using tax and Social Security data, the authors are able to calculate life expectancy, separately by income level and geography. One particularly interesting set of results is the geographic distribution of life expectancy of low earners.

What's most wrong with the corporate tax?

The corporate tax is the tax that economists most love to hate. It discourages capital formation, repels profitable investment, and causes untold dead weight loss in the form of tax lawyers' labor. And while the U.S. is generally a low-tax country, its (statutory) corporate tax rate is anomalously the highest in the developed world. Thus, unsurprisingly, corporate tax reform is always on the forefront of tax economists in Washington, DC.

Some Simple Economics of PrEP

There's a new strategy in the fight against HIV, especially among men who have sex with men (MSM): a drug called Truvada, also referred to as PrEP (for pre-exposure prophylaxis). Early reports suggest that taking Truvada can nearly eliminate the risk of an HIV-negative individual acquiring HIV. PrEP has been somewhat controversial, since one might reasonably conjecture that reducing the risk of unprotected sex will increase the prevalence of unprotected sex.

More on Miller & Sanjurjo

Edit: Jonathan Miller was nice enough to explain my error in interpreting their claim. See below. 

I wrote last week about Miller & Sanjurjo (2015), a working paper which shows how taking unweighted averages of ratios of conditional proportions of success (conditional on previous success) can lead to a biased estimate of the true conditional probability. I then claimed that this result does not extend meaningfuly to the context that they're trying to extend it to: the "hot hand" in basketball, particularly Gilovich, et al. (1985).

Various people smarter than me, notably Andrew Gelman, disagree. They think that the Sanjurjo & Miller critique matters even for the sample sizes considered by Gilovich et al.

Are coin flips memoryless?

There's a working paper going around by Miller and Sanjurjo, cited in a New York Times article, that seems to be arguing the impossible: that, in a sequence of flips of a fair coin, the probability of flipping heads is smaller than 1/2 if the previous flip was heads.

The working paper argues that this is relevant to the "hot hand" debate. E.g., is a basketball player more likely to hit his next shot if he hit his previous shot? The seminal paper in this literature, Gilovich, Vallone, and Tversky (1985), found that the conditional probability of success given previous success was close to the unconditional probability of success, concluding that each shot was roughly independent. But if the laws of probability as we know them are wrong, and independence would somehow imply a decline in the conditional probability of success given previous success, then a finding of conditional probability equal to unconditional would actually be evidence in favor of the hot hand hypothesis.

This claim, for lack of a better word, appears to be wrong.

Edit: See my most recent entry for why I was misunderstanding Miller & Sanjurjo's claim with respect to the Gilovich, et al. study. Basically, I was looking at the wrong part of the Gilovich paper! My exposition of the Miller & Sanjurjo result is still valid, though.

"Would a significant increase in the top income tax rate substantially alter income inequality?"

Here's a Brookings piece by Gale, Kearney, and Orszag --- with some research assistance from yours truly --- which tries to perform the following accounting exercise: If we increased tax rates on the wealthy, and there were no behavioral effects, how much would the after-tax Gini decrease? The answer is "not very much at all."

Under current tax provisions, the after-tax Gini coefficient is .574. This compares to a Gini of .610 calculated over pre-tax income. Raising the top income tax rate to 45 percent reduces the Gini coefficient only from .575 to .573. Raising it to 50 percent brings the Gini to .571.

Some explicit redistribution from the rich to the bottom 20% reduces inequality a bit further, but still not much.

Why? Mostly, because we were considering changes just to the top bracket, which doesn't start until taxable income of $464,850 (for married filing jointly), which corresponds to gross income even higher. Changing the top bracket effects only the very top --- the top 0.5 percent or so --- while 90/10 inequality would be untouched.