Alan Blinder had a good column yesterday, summarized and discussed by Mark Thoma.  The current movement, supported by Greg Mankiw I might add, is trying to raise the rate of taxation on private equity income so that Warren Buffet is not paying a lower tax rate than someone poorer than me.  More generally, it seems to many people that the rate of taxation on capital gains should be the same as the rate of taxation on ordinary income.

It’s hard to go against the weight of that opinion, but I would like to refocus the debate on the difference between stated and real rates of capital taxation, most of all with regard to loss offsets.  I haven’t seen this discussed in the very recent debates, though it is an old theme in public finance.

My uninformed-by-ever-having-been-a-tax-lawyer sense is that loss offsets for the capital gains tax are worth a great deal to some investors.  Sell your winners to coincide with selling some losers and claim a net gains income of zero or very low.  Let the asset winners ride and they will end up in your bequest and have their taxable values reset upon your death.  If your option values line up the right way, you have enough diversification, and you are not liquidity constrained, it seems that for many people the de facto rate of capital gains taxation is not 15 percent but rather close to zero.  (Maybe not quite zero in expected value terms; it’s tricky because if the losses exceed the gains you can deduct only $3000 of the losses from regular income but on the upside you’re taxed all the way.  On the other hand, you can offset with charitable deductions.)

Let’s say we raised the book rate of tax on capital gains to forty percent.  For some people the net real rate of tax on capital gains could still be zero.  For other people it would be forty percent.

Let’s say we raised the book rate of tax on capital gains to eighty percent.  For some people the net real rate of tax on capital gains could still be zero.  For other people it would be eighty percent.

Under which of these scenarios have we equalized the tax rates on capital gains and labor income?

For any published capital gains rate, it seems there are two or more (and possibly wildly disparate) real rates de facto.  Again, I’m no tax lawyer, but it seems any capital gains tax hike falls disproportionately on the non-diversified (if you hold only one asset and it is a huge winner, where can you get a loss offset from?  The quality of your tax accountant probably matters too.  Any other factors?).

No matter what, capital gains rates for some investors are too high and for others the rates are too low.  And don’t be shocked if many of those "too low" rates are enjoyed by the wealthy.  There will be unfairnesses when compared with income taxation as well.  It is a question of choosing your unfairness, not being able to eliminate unfairness or differential treatment.  So the mere fact that one apparently unjustified unfairness has been pointed out…well…I’m not yet ready to cry uncle.

One reason why the Clinton tax hikes weren’t so bad for capital formation is because capital gains taxes can be avoided in various ways.  The Bush defenders should recognize that and admit that K gains tax hikes are not always a disaster.  On the other hand, the notion of equalizing income and capital gains rates is a myth, and always will be.  There simply isn’t a single capital rate that ends up applied to everyone, no matter what it says on paper.

You might go down another path and talk about eliminating the loss offset.  I wonder if that can be done feasibly.  For instance it would mean that assets A and B, held together in a mutual fund are worth more than assets A and B held separately.  You can think of other problems with this in your spare time.

Yet another (and better) path is to institute a consumption tax, but in the meantime these other kinds of unfairness are not going to disappear.  See also Martin Feldstein on other costs of capital income taxation.

It makes perfect sense to say: "we’ve already spent the money, taxes somewhere have to go up."  But the Buffet example, taken alone, doesn’t convince me much.  Let’s start by taxing negative externalities at a higher level, not by focusing on major creators of wealth.

Some states ban the use of credit scores to price auto insurance in part because African-Americans and Hispanics tend to have lower (worse) credit scores and thus pay higher auto insurance rates.  The brute facts, however, are that credit scores are good predictors of auto claims. Luke Froeb at Management R&D summarizes a recent FTC study on the issue.

1. Credit scores effectively predict … the total cost of [auto insurance] claims.
2. Credit scores permit insurers to evaluate risk with greater accuracy, which may make them more willing to offer insurance to higher-risk consumers … . [note: this is why you can call up GEICO, let them look at your credit report, and get an auto insurance quote over the phone].
3. ..as a group, African-Americans and Hispanics tend to have lower scores than non-Hispanic whites and Asians.
4. …scores effectively predict risk of claims within racial and ethnic groups.
5. The Commission could not develop an alternative scoring model that would continue to predict risk effectively, yet decrease the differences in scores among racial and ethnic groups.

Thus banning the use of credit scores would at best force good drivers (of all races) to subsidize bad drivers.  At worst, if insurance companies cannot price according to risk an adverse selection problem could be created in which good drivers purchase less insurance (to avoid having to pay the subsidy to bad drivers) thus pushing rates even higher and perhaps unraveling the market.

Today I will pick E. Glen Weyl, a mere Youngling, who is studying at Princeton University.  Here is his paper on neural networks, and the abstract:

I consider a potential neural basis of overconfidence, the well-documented tendency of individuals to overestimate the precision of their predictions. I present a simple, classic connectionist model for predicting a binary variable. I show that while the network initially makes weak predictions (in the middle of the probability range) regardless of input, after observing randomly generated data it learns to be overconfident in the sense that when presented with other, unrelated random data it makes strong predictions. The model matches behavioral data in that it shows overconfidence growing with experience and then, eventually, declining. The model shows how overconfidence, far from being a surprising fallacy, can be seen as a natural outgrowth of statistical over-fitting in the brain.

Glen probably won’t be underappreciated for long.  Here is his seminal paper on two-sided markets (e.g., Match.com).  There is already talk he will be a leading economist of the next generation.

Here is Glen’s home page, and his other papers.

Here is Dave Warsh on Weyl.  Here is an article full of praise.  (He’s already looking non-underappreciated; note the CV, A.B. 2007, Ph.d. expected 2008.)  Here is Glen’s commencement address.  Here is Glen’s fight against protectionism.  Here are Glen’s film reviews.  Here is Glen’s dining guide for Princeton cuisine (hmm…).

I very much liked Glen’s paper on Simon Kuznets: Economist of the Russian Jewish Diaspora.

Here is Glen’s muse, Alisha Holland.  Here is Glen’s path to Unitarianism.

Let us all be grateful for people like Glen Weyl.