The American Apparel board of directors has ousted the company’s founder. The company stock jumped up nearly 20% on the announcement. Contrary to what we see in the movies, being a successful founder of a big company does not entitle one to kick back, smoke cigars, and let the profits roll in. Dov Charney had some innovative ideas about clothing and about turning a small enterprise into a global chain, but his personal failings became damaging, so he had to go.
An interesting question to ask is “who works for whom?” A week ago we might have thought that American Apparel worked for Charney, and not the other way around, but we would have been wrong. The board that fired him is itself beholden to the shareholders; the old share price (before the 20% jump) was the result of investors restricting their investments in the company because its bad CEO made it less appealing than some alternative investments. And who are the shareholders beholden to? Continue reading American Apparel Demonstrates a Fundamental Principle of Capitalism→
Today I will be dispensing life advice. There’s a certain type of person who will tell you that you should follow your passion regardless of money concerns; to do otherwise would be “selling out.” This is pretty terrible advice. If eating, sleeping, and going to the bathroom are not my passions, should I never do these things? What is it about money (or rather, all the things that exchange for money) that makes it unacceptable to include among one’s goals?
The big problem with this advice is that it is often given to young people. Young people have passions, but they can only be passionate about the things they have experienced at their young age. When I was young, I was passionate about painting. Now I am passionate about economics. If I had taken the oft-repeated advice to “follow my passion,” I would be struggling to make a living as an oil painter. Only by not following my passion was I able to discover a different (and much more remunerative) passion.
I have some problems with the rational expectations hypothesis. To hear some macro economists talk about it, you’d think that it was a wonderful scientific innovation for economists to start assuming that the agents in their models know the structure of the economy and only make random errors in forecasting. Such sentiments are entirely misguided.
Is it really the case that the market behaves as if the people in the market do not make systematic errors? If so, this is a highly interesting feature of the market economy, one that economists should explain rather than simply asserting.
It is entirely possible to construct a theory of markets without presupposing the specific types of errors (systematic or random) that people make. In doing so, we should ask ourselves what would happen to an entrepreneur who repeatedly and systematically failed in forecasting the future state of prices. Such a person would repeatedly earn losses. Faced with these losses, he would be forced either to revise his forecasting method such that his predictions would improve, or face continual losses and eventual bankruptcy. Thus, the market process tends, in the limit, towards something like rational expectations. Continue reading What’s the Big Deal with Rational Expectations?→
Under the common law, lawyers are not allowed to ask witnesses “leading questions,” as witnesses can be influenced by the way questions are asked. A leading question is one that suggests a particular answer, for instance, “Were you at the country club on Saturday night?” is a leading question, while, “Where were you on Saturday night?” is not.
Econometricians should be as careful as lawyers when questioning the most unreliable of all witnesses: economic data. Most statistical software will automatically spit out t-tests for whether the coefficients in regression models equal zero. This is equivalent to asking the data, “Data, given these modelling assumptions, can you deny with 95% certainty that this coefficient equals zero?” That’s a leading question, and the econometrician shouldn’t ask it unless he has special reason to suspect that the coefficient is zero. Continue reading Significance Tests as Leading Questions→
When calico printed cloth was introduced to Europe, the French government banned it. They employed gestapo-style tactics to stamp out the new innovation. Here’s Murray Rothbard’s summary of the fiasco, from his excellent An Austrian Perspective on the History of Economic Thought (vol. 1, p. 219):
The new cloth, printed calicoes, began to be imported from India in the 1660s, and became highly popular, useful for an inexpensive mass market, as well as for high fashion. As a result, calico printing was launched in France. By the 1680s, the indignant woollen, cloth, silk and linen industries all complained to the state of ‘unfair competition’ by the highly popular upstart. The printed colours were readily outcompeting the older cloths. And so the French state responded in 1686 by total prohibition of printed calicoes: their import or their domestic production. In 1700, the French government went all the way: an absolute ban on every aspect of calicoes including their use in consumption. Government spies had a hysterical field day: ‘peering into coaches and private houses and reporting that the governess of the Marquis de Cormoy had been seen at her window clothed in calico of a white background with big red flowers, almost new, or that the wife of a lemonade-seller had been seen in her shop in a casquin of calico’. Literally thousands of Frenchmen died in the calico struggles, either being executed for wearing calicoes or in armed raids against calico-users.
Class probability means: We know or assume to know, with regard to the problem concerned, everything about the behavior of a whole class of events or phenomena; but about the actual singular events or phenomena we know nothing but that they are elements of this class.
This is the ordinary sort of probability. We reach into an urn containing seven red balls and two white balls, so the probability of choosing a red ball is 7:2. We can say this because we have knowledge about the class of balls in the urn. Mises distinguishes this from case probability:
Case probability means: We know, with regard to a particular event, some of the factors which determine its outcome; but there are other determining factors about which we know nothing.
Goldman Sachs, Barclays, Deutsche Bank, JP Morgan and Morgan Stanley together made an estimated £2.2 billion from speculating on food including wheat, maize and soy between 2010 and 2012. Speculation increases price volatility and has been a major factor in the sharp spikes in global food prices of the last six years.
The solution is to create a bitcoin-style, decentralized prediction market that can’t easily be shut down. The prediction market could take bets denominated in bitcoin or another cryptocurrency. As with these cryptocurrencies, this prediction market would have a public ledger keeping track of bets, with many computers processing bets and updating the ledger. Continue reading We Need a Bitcoin-Style Prediction Market→
Garrett M. Petersen's blog about markets, institutions, and ideas.