Thought of the day

I was reading this statement (via a link from Felix Salmon):

Emergers also have a better chance of being part of the coveted 1% who control 40% of wealth in America someday.

It got me thinking again about precisely why we have low marginal tax rates on those who make above (for example) 500 thousand per year. Now, by low I mean low in comparison with other rates in the post-WWII era.

There seem to be two explanations: 1) competition for key talent and 2) incentive for performance.

The first seems unlikely. All US executives pay taxes in the same country so it just resets the baseline. Americans seem to be the best compensated class of business executives and stock traders so international competition can only matter so much.

The second is much clearer if we (following Linda McQuaig and Neil Brooks) look at sports stars. Did Babe Ruth or Lou Gehrig under-perform relative to Micheal Jordan due to low compensation? Do we really think that the overall quality of play would decline in some massive sense?

Now we might get fewer people wasting their lives trying to become a sports superstar if they paid more in marginal taxes, but is that really a shame?

Meanwhile, infrastructure, education and the rule of law all make economic activity possible. Is it not possible that these areas are under-invested in and could use some transfer of cash?

I do not know for sure, but it is worth thinking about.

Tax Policy

Mark has been discussing the concerns about the hardship that tax increases would inflict on those with an income exceeding $250,000 per year. In part I think that this line of discussion began with Greg Mankiw trying to use himself as an example of a person who might do less labor if the marginal tax rate increased. There were a number of great points brought up as to why this example had issues: see here, here, and here.

There was a second economics professor who also made similar claims although I found them a bit harder to evaluate as the example was not as clear. This argument seemed to be more about how hard this person would find it to make cutbacks rather than a specific example of how he would become less productive.

Yesterday,Noahpinion linked to a great article by Karl Smith that went to the heart of this discussion. The argument was whether tax increases (at the sort of marginal rates we currently have) really depress productivity. Karl Smith made a number of arguments that were worth considering, including:

Third, high income people don’t seem to be working that much more than low income people despite the fact that a natural propensity towards work can make one high income.

Indeed, the data show us that low income folks used to work a little more, but now they work a little less than high income folks. Yet, if the income and substitution effects were balanced for each person we would still expect higher income people to work more.

That’s because working hard can lead to more education, more experience and more promotions. Being hard working is also associated with having a conscientious personality type which is itself more valuable.

So if someone was simply born with a stronger propensity to work, we would expect that person to earn more income per hour. Thus we when look at the data we should see that all these high income people are working lots of hours.

Yet, we actually don’t see that. We see only a mild effect and even then that effect is not robust over time. Sometimes, high income folks are working less.

But the piece is a must read in the entirety. The key argument here, though, is whether the extremely small tax increases that are under discussion (a raise in the marginal tax rate for the highest income bracket from 36% to 39.6%) is really likely to make high income Americans less productive. Because if these tax increases don't disincent work and we accept that government finances really are a mess then the tax hikes seem to be a logical way to "share the cost of these increases".

But I also think that these points don't necessarily go far enough. Are we really convinced that a small decrease in productivity among the wealthy will be that devastating? What is the source of productivity in the American economy? Is it highly paid CEOs, hedge fund managers, lawyers and medical doctors, or is it the majority of workers who drive productivity?

I think it is essential to get this correct. A top down model of an economy (where the people at the top make the key decisions and are responsible for the output) did poorly in Soviet Russia. A bottom up theory of economic gains seems to make a lot more sense and that suggests that small productivity losses among the wealthy are not a serious concern.

It is worth emphasizing that, at this time, I am aware of two proposals to increase the tax rates of the wealthy: increasing the amount of wages on which FICA can be charged and returning to Clinton-era tax rates. Neither of these increases is a vast change in the marginal tax rate of this group. Clearly there are tax increases that would cause issues, but we can handle those when they show up and not now when all of the possible rates under discussion are sane.

The last example that people tend to bring up is innovation and how important it is to reward innovators. Now, as part of a first principle I would like to point out that the innovator is not always the person who profits the most from an invention (consider Nikola Tesla). But it is also worth noting, as Mark points out, that copyright law already provides enormous rewards for intellectual property holders.

So I think we should look to balance harms. Recent events have included layoffs of government workers into a economy with an extremely high unemployment rate. Are we sure that the consequences of a large body of long term unemployed workers will be better than that of small increases in tax rates?

Tax increases as landscape perturbation?

Over at Felix Salmon's site, Justin Fox presents an interesting counter-argument to Greg Mankiw:

[T]here’s a really fascinating tale in [Sam Howe Verhovek’s Jet Age: The Comet, the 707, and the Race to Shrink the World] involving tax incentives. During the Korean War, Congress enacted an excess profits tax meant to keep military contractors from, well, profiteering. In its infinite wisdom, Congress defined excess profits as anything above what a company had been making during the peacetime years 1946-1949.

Boeing was mostly a military contractor in those days (Lockheed and Douglas dominated the passenger-plane business), and had made hardly any money at all from 1946 to 1949. So pretty much any profits it earned during the Korean conflict were by definition excess, and its effective tax rate in 1951 was going to be 82%. This was unfair and anti-business. If similar legislation were enacted today, you could expect U.S. Chamber of Commerce members to march on Washington and overturn cars on the streets.

It being 1951, Boeing instead sucked it up and let the tax incentives inadvertently devised by Congress steer it toward a bold and fateful decision. CEO Bill Allen decided, and was able to persuade Boeing’s board, to plow all those profits and more into developing what became the 707, a company-defining and world-changing innovation. Writes Verhovek:

Yes, it was a huge gamble, but for every dollar of the dice roll, only eighteen cents of it would have been Boeing’s to keep anyway. For Douglas and Lockheed, both in a much lower tax bracket, that was not so easy a call.

So that’s it! High tax rates—confiscatory tax rates—spur innovation! Well, at least once in a blue moon they do. Which is an indication that there might be some important stuff missing from the classic economists’ view of taxation, as summed up by Greg Mankiw a few weeks ago:

Economists understand that, absent externalities, the undistorted situation reflects an optimal allocation of resources. It is crucial to know how far we are from that optimum. To be somewhat nerdy about it, the deadweight loss of a tax rises with the square of the tax rate.

Somehow I don’t think that formula held true in Boeing’s case.

This leads me to wonder if this reminds anyone else of algorithms that locate superior optima by slightly perturbing fitness landscapes (processes closely related to simulated annealing). Mankiw complains that certain taxes distort the economic landscape, but if local optimization is an issue (as was apparently the case with Boeing), then mild distortion from time to time is likely to lead to a better performing economy.

For background, here's an excerpt from a post on landscapes. The subject was lab animals but the general principles remain the same:

And there you have the two great curses of the gradient searcher, numerous small local optima and long, circuitous paths. This particular combination -- multiple maxima and a single minimum associated with indirect search paths -- is typical of fluvial geomorphology and isn't something you'd generally expect to see in other areas, but the general problems of local optima and slow convergence show up all the time.

There are, fortunately, a few things we can do that might make the situation better (not what you'd call realistic things but we aren't exactly going for verisimilitude here). We could tilt the landscape a little or slightly bend or stretch or twist it, maybe add some ridges to some patches to give it that stylish corduroy look. (in other words, we could perturb the landscape.)

Hopefully, these changes shouldn't have much effect on the size and position of the of the major optima,* but they could have a big effect on the search behavior, changing the likelihood of ending up on a particular optima and the average time to optimize. That's the reason we perturb landscapes; we're hoping for something that will give us a better optima in a reasonable time. Of course, we have no way of knowing if our bending and twisting will make things better (it could just as easily make them worse), but if we do get good results from our search of the new landscape, we should get similar results from the corresponding point on the old landscape.


* I showed this post to an engineer who strongly suggested I add two caveats here. First, we are working under the assumption that the major optima are large relative to the changes produced by the perturbation. Second our interest in each optima is based on its size, not whether it is global. Going back to our original example, let's say that the largest peak on our original landscape was 1,005 feet tall and the second largest was 1,000 feet even but after perturbation their heights were reversed. If we were interested in finding the global max, this would be be a big deal, but to us the difference between the two landscapes is trivial.