Economics

Book review: The Law Market by Erin A. O’Hara and Larry E. Ribstein.

This book describes why it has become easier for parties to a contract to choose which legal system will be applied to their contract, both in terms of the political forces that enabled choice and why it’s good that choice is possible.

The political forces include the ability of some parties to physically leave a jurisdiction if they have inadequate choices about what law will be applied to them. Often enough those parties are employers that legislators want to remain in their jurisdiction.

The benefits include simple things like predictability of contract interpretation when the contract covers things that involve physical locations associated with multiple jurisdictions where there otherwise would be no reliable way to predict which court would assert jurisdiction over disputes. They also include less direct effects of providing incentives for legal systems to improve so as to attract more customers.

The book mostly deals with contracts between corporations, and is much more tentative about advocating choice of law for individuals.

The book provides examples showing that as with most markets, competition for law produces better law. But is also mentions more questionable results, such as competition for most effective tax shelters or the easiest terms for divorce (for divorce, the book suggests those who want divorce to be hard should try to arrange contracts that allocate assets in a way that discourages divorce; it would be harder for easy-divorce states to justify ignoring those contracts). There’s also a risk that the competition will sometimes benefit lawyers rather than their clients, as clients often rely on lawyers to decide which legal system to use without having a practical way to check who benefits from some of those choices.

The book is often dull reading because it often describes case law to explain quirks of current law that will be of interest to few non-lawyers.

One part that disappointed me was the assumption that the choice of jurisdiction should dictate the physical location in which plaintiffs must argue their case (the travel costs can make some lawsuits unpractical to a consumer suing a company if the company decides the location at which a suit is argued). Why are we trapped in a set of rules that requires travel to a possibly distant court when we have technology that provides reasonable remote communications?

I just noticed some confused arguments between Jeremy Siegel and Standard and Poors over how to aggregate earnings for companies in a stock index to produce a meaningful report of what the companies in the index earned.
See here and here.

Siegel provides an example involving percent changes in Exxon-Mobil and Jones Apparel. But that has a weak resemblance to what S&P is doing. A more accurate analogy to what S&P is doing would use changes to market cap rather than percent changes. If Jones Apparel declined in market cap by $10 billion, it would hurt the index just as badly as a $10 billion decline in Exxon-Mobil’s market cap. Looked at that way, S&P’s approach looks sensible.

But since Jones Apparel has a market cap of less than $1 billion, the current bankruptcy laws make it far-fetched that Jones Apparel could lose more than $1 billion in market cap.

If you’re using earnings as a proxy for the health of the economy, S&P’s method doesn’t create a problem – the bankruptcy laws affect who loses money, but the money is still lost. But for an investor, Siegel has a point which is half right.

Siegel’s solution of weighting earnings by market cap may work well under any realistic conditions, but has no sensible theory behind it, and can fail badly under some far-fetched conditions. Imagine that Jones Apparel reports an unexpected one-time windfall of $1 trillion, which ought to raise the market cap of Jones Apparel by about $1 trillion. The way S&P computes S&P 500 earnings, an investor looking at S&P 500 earnings would see a strong hint that the value of the S&P 500 ought to rise by about $1 trillion. But under Siegel’s method, the initial effect on S&P 500 earnings would suggest a barely noticeable rise in the value of the S&P 500 of under $1 billion. Then at some point the Jones Apparel market cap would soar and the S&P 500 earnings would be recomputed with much different weights and investors would see a much different picture. So Siegel has proposed something which could result in a potentially large change in reported S&P 500 earnings without any change in the what shares someone who invests in the S&P 500 holds and without any changes in reported earnings.

Morningstar has a method (PDF) designed for evaluating portfolios that uses a harmonic weighted average and ignores companies with negative earnings. That has advantages, but the magnitude of losses provides some hints about how far a company is from profitability, so an ideal method should pay some attention to losses.

Siegel mentions comments by Shiller that suggest Shiller has better (but possibly impractical) ideas. I doubt Shiller’s analysis provides as much support for Siegel’s argument as Siegel claims.

Any sensible investor looks at a multi-year average of earnings along the lines suggested by Shiller, which minimizes the problems associated with faulty weighting of earnings.

Book review: The Invisible Hook: The Hidden Economics of Pirates by Peter Leeson.

This is an interesting history of early eighteenth century pirates with an economist’s insights into what influenced them to have institutions such as democracy and to be in many ways pleasanter to serve on than commercial or military ships of the same time.

He has a fairly open bias toward portraying pirates favorably. I sometimes wondered whether there’s enough evidence to support his sometimes surprising conclusions. He makes plausible claims to be getting his historical information from the relevant experts, but without careful checking I can’t tell whether he has slanted his story to make it more entertaining.

He describes some good reasons why “workers’ democracy” doesn’t work as well in modern corporations as it did on pirate ships. But he is too willing to accept the observed absence of corporate democracy as evidence of its inefficiency. I can easily imagine that managers grab more power than is good for the company, and that principal-agent problems let them get away with it (pirates’ relations with the law made it easier for them to remedy this via mutiny). Also, he overstates the claim that “workers don’t have the finances required” for worker ownership of corporations. There are plenty of companies with low enough capital requirements for this to be unimportant. The big difference I see between modern corporations and pirate ships is that pirates had strong reasons to stick together until their venture got enough loot for them to all retire at once and divide the results. Employees in modern corporations want much more flexibility in when they leave the company, which creates complications for workers’ democracy or for the employee who wants to leave however it is handled.

One analysis whose absence disappointed me was whether the long-term benefits to joining a pirate ship were better than those of commercial or military ships. What fraction of pirates retired wealthy? How many of them were fooled by a temporary shortage of law enforcement into adopting a career with an abnormally high death rate once governments increased law enforcement?

He occasionally digresses into standard economics rants that have no relevance to pirates, such as the two pages on lobbyist rent-seeking.

Book review: Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals, by David Aronson.

This is by far the best book I’ve seen that is written for professional stock market traders. That says more about the wishful thinking that went into other books that attempt to analyze trading rules than it does about this author’s brilliance. There are probably books about general data mining that would provide more rigorous descriptions of the relevant ideas, but they would require more effort to find the ideas that matter most to traders.

There hasn’t been much demand for rigorous analysis of trading systems because people who understand how hard it is to do it well typically pick a different career, leaving the field populated with people who overestimate their ability to develop trading systems. That means many traders won’t like the message this book sends because it doesn’t come close to fitting their preconceptions about how to make money. It is mostly devoted to explaining how to avoid popular and tempting mistakes.

Although the book only talks specifically about technical analysis, the ideas in it can be applied with little change to a wide variety of financial and political forecasting problems.

He is occasionally careless. For example: “All other things being equal, a TA rule that is successful 52 percent of the time is less valuable than one that works 70 percent of the time.” There might be a way of interpreting this that is true, but it’s easy for people to mistake this for a useful metric, when it has little correlation with good returns on investment. It’s quite common for a system’s returns to be dominated by a few large gains or losses rather than the frequency of success.

The book manages to spell Occam three different ways!

Book review: Hollywood Economics: How extreme uncertainty shapes the film industry, by Arthur De Vany.

This rather dense and scholarly book that contains some good insights into how markets for information differ from markets for physical goods. But few people will want to read the whole book. Much of the book was originally published as papers in economics journals. It’s better organized than that suggests, but the style is mostly oriented toward professional economists.

Much of the book can be summed up by the conclusion that nobody knows anything about how successful a movie will be. The typical film loses money, and the expected returns are heavily dominated by rare films that are huge successes.

He says through much of the book that returns on investment in movies have infinite variance, and only at the very end admits that that’s not literaly true, and then provides a more credible description of the variance as unstable and generally increasing over time.

His argument that Hollywood makes too many R-rated films takes a good deal of effort to follow. Table 5.3 is confusing, because it shows a mean return on R-rated films as much higher for the returns on PG13 films. This sounds like the opposite of his conclusion. It took 13 more pages before I figured out that that was due to some high rates of return on low budget R-rated films that had little effect on aggregate profits. It appears that his conclusion ought to have been that Hollywood makes too many high-budget R-rated films, and too few low-budget R-rated films.

His description of the antitrust cases that transformed the movie industry provides convincing evidence that the courts were confused and didn’t help the independent exhibitors that the lawsuits were allegedly designed to help. The arguments about how they affected consumers are less clear.

Mike Linksvayer describes a good perspective on why it’s important to have most information in a commons rather than restricted by copyright.
Most economists have a strong bias toward assuming transaction costs are unimportant. Coase has fought this. It sure looks to me like the Coase Theorem ought to be understood as demonstrating that one of the most important tasks for economists is to improve our understanding of how to reduce transaction costs. Economists have invested too much in models which depend on transaction costs being insignificant to easily be persuaded to adopt such a different focus.

Lessig’s book The Future of Ideas: The Fate of the Commons in a Connected World describes why having some commons can be as valuable as having some resources protected by secure property rights, and why it matters for science and technology. But his argument style is designed for ordinary political debates, and doesn’t provide the breadth or power that a good economist would produce when attempting to reform economics.

I have little idea whether Creative Commons will put additional money to good use, but the value of its goals should not be overlooked.

Book review: The Soulful Science: What Economists Really Do and Why It Matters by Diane Coyle.
This book provides a nice overview of economic theory, with an emphasis on how it has been changing recently. The style is eloquent, but the author is too nerdy to appeal to as wide an audience as she hopes. How many critics of economics will put up with quips such as “my Hamiltonian is bigger than yours!”?

The most thought-provoking part of the book, where she argues that economics has a soul, convinced me she convinced me she’s rather confused about why economics makes people uncomfortable.
One of her few good analogies mentions the similarities between critics of evolution and critics of economics. I wished she had learned more about the motives of her critics from this. Both sciences disturb people because their soulless autistic features destroy cherished illusions.
Evolutionary theory tells us that the world is crueler than we want it to be, and weakens beliefs about humans having something special and immaterial that makes us noble.
Likewise, economics tells us that people aren’t as altruistic as we want them to be, and encourages a mechanistic view of people that interferes with attempts to see mystical virtues in humans.

Some of her defenses of mainstream economics from “post-autistic” criticism deals with archaic uses of the word autistic (abnormal subjectivity, acceptance of fantasy). These disputes seem to be a disorganized mix of good and bad criticisms of mainstream economics that don’t suggest any wholesale rejection of mainstream economics. It’s the uses of autistic that resemble modern medical uses of the term that generate important debates.

She repeats the misleading claim that Malthusian gloom caused Carlyle to call economics the dismal science. This suggests she hasn’t studied critics of economics as well as she thinks. Carlyle’s real reason (defending racism from an assault by economists) shows the benefits of economists’ autistic tendencies. Economists’ mechanistic models and lack of empathy for slaveowners foster a worldview in which having different rules for slaves seemed unnatural (even to economists who viewed slaves as subhuman).

I just happened to run across this thought from an economist describing his autistic child: “his utter inability to comprehend why Jackie Robinson wasn’t welcomed by every major league team”.

She tries to address specific complaints about what economists teach without seeing a broad enough picture to see when those are just symptoms of a broader pattern of discomfort. Hardly anyone criticizes physics courses that teach Newtonian mechanics for their less-accurate-than-Einstein simplifications. When people criticize economics for simplifications in ways that resemble creationists’ complaints about simplifications made in teaching evolution, it seems unwise (and autistic) to avoid modeling deeper reasons that would explain the broad pattern of complaints.
She points to all the effort that economists devote to analyzing empirical data as evidence that economists are in touch with the real world. I’ll bet that analyzing people as numbers confirms critics’ suspicions about how cold and mechanistic economists are.

She seems overconfident about the influence economists have had on monetary and antitrust policies. Anyone familiar with public choice economics would look harder for signs that the agencies in question aren’t following economists’ advice as carefully as they want economists to think.

I’m puzzled by this claim:

The straightforward policy implication [of happiness research] is that to increase national well-being, more people need to have more sex. This doesn’t sound like a reasonable economic policy prescription

She provides no explanation of why we shouldn’t conclude that sex should replace some other leisure activities. It’s not obvious that there are policies which would accomplish this goal, but it sure looks like economists aren’t paying as much attention to this issue as they ought to.

She appears wrong when she claims that it’s reasonable to assume prediction market traders are risk neutral, and that that is sufficient to make prediction market prices reflect probabilities. Anyone interested in this should instead follow her reference to Manski’s discussion and see the response by Justin Wolfers and Eric Zitzewitz.

There are lots of small Chinese companies trading on U.S. stock exchanges that look at first glance to be ridiculously underpriced. One reason for the low prices are that it’s harder than you might expect to enforce U.S. law on Chinese companies that have few or no assets in the U.S.

The most blatant example I’ve seen is Eternal Technologies Group Inc, which has ignored a judgment in a lawsuit that seems minor compared to the cash the company reports having, with the result that a receiver has been appointed who is likely to collect some money in ways that badly hurt stockholders who bought before the lawsuit.
Another hint at how little the company cares about stockholders (at least those in the U.S.) is the careless way their press releases are written: “5. Radification of the elecrion of the auditors” (they managed to spell election correctly on the prior line, so it’s not simple ignorance).

I’ve noticed problems with other U.S. traded Chinese companies that leave me uncertain which of them can be trusted. I’ve been trading stocks listed on the Hong Kong Stock Exchange a fair amount, and haven’t noticed any similar problems there. I presume the stronger cultural and/or legal ties are more effective than anything that can be accomplished by U.S. law.

A number of people have compared the final forecasts for the election (e.g. this), but I’m more interested in longer term forecasting, so I’m comparing the state-by-state predictions of Intrade and FiveThirtyEight on the dates for which I saved FiveThirtyEight data a month or more before the election.

Here is a table of states where Intrade disagreed with FiveThirtyEight on one of the first four dates for which I saved FiveThirtyEight data or where they were both wrong on July 24. The numbers are probability of a Democrat winning the state’s electoral votes, with the Intrade forecast first and the FiveThirtyEight forecast second.

State 2008-07-24 2008-08-22 2008-09-14 2008-10-01
CO 71/68 60/53 54.5/46 67.5/84
FL 42/29 34.5/28 30/14 55.2/70
IN 38/26 34.1/15 20/11 38/51
MO 50/26 32.9/13 22.1/11 42.5/48
NC 30/22 25/21 14/7 51/50
NV 51.2/49 49/45 44.9/32 55/66
OH 65/53 50/38 40/29 53.5/68
VA 60.5/50 52.3/36 42/22 59/79

On July 24, both sites predicted Florida, Indiana, and North Carolina wrong. FiveThirtyEight got Indiana right on Oct 1 when Intrade was still wrong, but Intrade got North Carolina right on that date (just barely) while FiveThirtyEight rated it a toss-up.
Intrade got Nevada right on July 24 (just barely) while FiveThirtyEight got it wrong (just barely).
For Virginia, Intrade was right in July and August while FiveThirtyEight was undecided and then wrong.
FiveThirtyEight got Colorado wrong on September 14, but Intrade didn’t.
FiveThirtyEight got Ohio wrong on August 22, while Intrade got it right.
Intrade rated Missouri a toss-up on July 24, while FiveThirtyEight got it right.

On September 14, FiveThirtyEight was fooled by McCain’s post convention bounce by a larger margin than Intrade, but by Oct 1 FiveThirtyEight was more confident about correcting those errors.
For states that were not closely contested, there were numerous examples where Intrade prices where closer to 50 than FiveThirtyEight. It’s likely that this represents long-shot bias on Intrade.

In sum, Intrade made slightly better forecasts for the closely contested states through at least mid September, but after that FiveThirtyEight was at least as good and more decisive. Except for Intrade’s Missouri forecast on July 24, the errors seem largely due to underestimating the effects of economic problems – errors which were also widespread in most forecasts for other things affected by the recession.

In the senate races, I didn’t save FiveThirtyEight forecasts from before November 1. It looks like both Intrade and FiveThirtyEight made similar errors on the Alaska and Minnesota races.
[Update on 2009-01-13: contrary to initial reports, they apparently got the Alaska and Minnesota races right, although there’s still some doubt about Minnesota.]

On the other hand, Intrade had been fairly consistently (but not confidently) saying since early July that California’s Proposition 8 (banning same-sex marriage) would be defeated. Pollsters as a group did a somewhat better job there by issuing conflicting reports.