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.

On Borjas (2015), The Wage Impact of the Marielitos : A Reappraisal

Influential labor economist George Borjas is out with a new working paper revisiting the famous Card (1990) result on the Mariel Boatlift. The Boatlift was a huge, plausibly exogenous immigration shock felt by Miami in 1980. Card had originally found that the Miami labor market had seemed to absorb the immigrants without an impact on native wages. Borjas' working paper challenges that result.

Is Tax Avoidance Socially Costly?

Yesterday, I was reading Gorry, Hassett, Hubbard, and Mathur (2015) in this week's NBER release. Their paper is about how taxes affect the structure of executive compensation (e.g., between cash, stock grants, and stock options). This motivated me to try to think carefully about the extent to which tax avoidance is socially costly.

A Toy Model of Repatriation of Foreign Earnings of U.S. Corporations (or, How Congress Keeps Shooting Itself in the Foot)

Frequently, we hear reports out of Washington that, while "tax reform is dead", the parts of the corporate tax involving foreign earnings are so self-evidently horrible that we might see a small-scale reform to this part of the tax code.

This stylized fact seems relatively true: the most recent estimates suggest that U.S. corporations are holding over $2 trillion in "profits" overseas; these profits, if repatriated, would be subject to a tax equal to the difference between the U.S. corporate rate (35%) and whatever was paid initially to the foreign country [omitting some details]. Members of Congress would love to see this cash brought home, even if the benefits only accrue to shareholders and executives, as the recent literature has suggested. (Of course, the profits need not actually be "held" overseas; we just mean that some controlled foreign corporation has yet to pay its U.S. parent corporation a big fat dividend of those profits.)

A Simple Model Challenging Gruber & Saez-type Estimates of the Elasticity of Taxable Income

One of the most obvious ways to reduce income inequality is to increase the marginal tax rates on high earnings (and use the revenue to redistribute to the poor or to provide public services). But, of course, this comes at the cost of further distorting the decision-making of those facing the higher tax rates. The elasticity of taxable income (ETI) with respect to the net of tax rate, (1-t), is a key parameter in quantifying these distortions. A higher ETI means that the welfare costs of increasing taxes is larger.

Sallee, West, and Fan (2015): Do Consumers Recognize the value of fuel economy? Evidence from used car prices and gasoline price fluctuations.

From this week's NBER release is a great paper showing how to isolate variation you care about while holding a lot of things constant. Abstract:

Debate about the appropriate design of energy policy hinges critically on whether consumers might undervalue energy efficiency, due to myopia or some other manifestation of limited rationality. We contribute to this debate by measuring consumers' willingness to pay for fuel economy using a novel identification strategy and high quality microdata from wholesale used car auctions. We leverage differences in future fuel costs across otherwise identical vehicles that have different current mileage, and therefore different remaining lifetimes. By seeing how price differences across high and low mileage vehicles of different fuel economies change in response to shocks to the price of gasoline, we estimate the relationship between vehicle prices and future fuel costs. Our data suggest that used automobile prices move one for one with changes in present discounted future fuel costs, which implies that consumers fully value fuel economy. 

The most well-known market failure in the market for carbon-producing goods is the negative externality of pollution: consumers rationally do not internalize the harm that their carbon emissions will place on others. The Econ 101 solution for this is a Pigouvian carbon tax or, equivalently (in terms of efficiency) a cap-and-trade system.

But some argue that consumer inattention causes a second market failure: consumers undervalue their own savings from energy efficiency. This failure would cause the level of carbon emissions to be too high even under the optimal Econ 101 Pigouvian tax. As a result, there is a long literature (with which I'm not too familiar) that tries to estimate consumers' valuation of fuel efficiency.

At a first glance, the simplest way of answering this question in the context of automobiles would be cross-sectional: compare the sales prices of cars with varying fuel efficiency, while richly controlling for observable characteristics. Of course, the price of a given car is substantially determined by unobservable characteristics which are correlated with fuel economy, so this strategy is not credible.

A slightly more sophisticated strategy would exploit changes in the price of gasoline, and compare the change in price for high-efficiency and low-efficiency vehicles. An increase in the price of gasoline should cause the price for a Hummer to fall by more than the price of a Camry. For this to measure consumer valuation of energy efficiency, there can't be anything else differentially occurring for high- and low-efficiency vehicles correlated with energy prices. But if more fuel-efficient models are introduced in response to a fuel price increase---increasing competition in that segment---we could see a fall in the price of high-efficiency vehicles that isn't caused by consumer valuation (see Langer and Miller (2013)).

Enter Sallee, West, and Fan (2015). Their strategy makes use of more subtle variation. They use variation in the odometer readings, interacted with variation in fuel prices. Intuitively, fuel prices should matter less for car prices if the car has a shorter expected life---i.e., the change in the present discounted cost of fuel will be smaller if the life is shorter. The beauty of this strategy is that you can look within vehicle-month cells.

This is, in some sense, analogous to a triple difference.

The first difference is within a single vehicle type sold in a given month; say, two 2007 Honda Civics sold in May 2013, where the only variation is the odometer reading. We can essentially estimate the slope of the mileage-price curve, which will presumably be negative (lower mileage cars are more valuable).

The second difference is across vehicle types: between 2007 Honda Civics and 2007 Ford F-150s. We compare the mileage-price curve of both types of vehicles. Holding all else constant, we'd expect the 2007 Ford F-150 to have a flatter mileage-price curve, since higher mileage means the expected life of the vehicle --- and thus the life during which its driver will "suffer" from its relative fuel inefficiency --- is smaller.

Of course, not all else is constant: it's possible that trucks have better longevity, or vice versa, which would contaminate the mileage-price curve. So, enter the third difference: when fuel prices are higher and lower. Intuitively, the extent to which the F-150 mileage-price curve is flatter than that of the Honda Civic mileage-price curve should be increasing in the fuel price. In practice, this triple difference is estimated by using vehicle type X month fixed effects.

What do they find? Putting aside the caveats that their fuel-cost variables are constructed with many assumptions (to which the results may not be fully robust), they find that an increase in the PDV of fuel costs---variation in which comes solely from variation in mileage---is passed through as a 1-to-1 reduction in the wholesale purchase price.

This, to me at least, was a somewhat surprising result. Their calculation of the PDV of the fuel cost is non-trivial, and I highly doubt that consumers are literally making that calculation. Instead, some combination of rules-of-thumb and other market forces are combining to set the market price of these cars "correctly." It is a very interesting question why the rules-of-thumb and market forces provide the "correct" price in this market, but not in other markets that suffer from similar complexities, e.g., health care, retirement savings, etc. This, to me, seems a central question at the intersection of neo-classical and behavioral economics, to which I don't think a satisfying answer has been provided.