Does Your Forecast Consider The Punchbowl?

Here is David Merkel:

Unless revenue growth kicks in, that means the profit margin, already at record highs, will soar to an astounding record. But won’t revenue growth begin again? That’s hard to say, but if revenue growth starts in earnest, the Fed will start removing policy accommodation, because ban lending will be perking up. At that point, it is anyone’s guess as to what will happen.

In other words, never forget that the central bank moves last.

Let’s say you have a forecast for what the economy/stock market will do in the medium term. Your forecast almost certainly assumes current fed policy stays in place, which, depending who you ask is somewhere between mildly accommodative and crazy-time loose. Bernanke is on my TV right now warning against prematurely tightening, so your assumption is probably good, right?

David, of course, is smarter than that; he knows that fed accommodation is a function of the consensus of a relatively small group of very fallible humans. Right now, for example, the market thinks fed accommodation is really important and that the fed is doing a good job of laying out the punchbowl. Rewind a few years and the market had a similar hope but the opposite evaluation.

Now David happens to not like the current monetary policy stance but his view (like that of anyone that thinks about this for a while) is rather complex. My view is that I believe some version of EMH and believe that aggregate stock market value is something of a proxy for the general economy (stock market goes up, economy is good). This means the market represents the most intelligent possible evaluation of monetary policy and it’s thumbs up right now.

But how might policy change when the recovery picks up? This is THE critical macro question and any analysis that ignores it should be thrown in the trash.

Now We’re Getting Revolutionary

Georgia Tech throws the first stone:

The Georgia Institute of Technology plans to offer a $7,000 online master’s degree to 10,000 new students over the next three years without hiring much more than a handful of new instructors.

Georgia Tech will work with AT&T and Udacity, the 15-month-old Silicon Valley-based company, to offer a new online master’s degree in computer science to students across the world at a sixth of the price of its current degree. The deal, announced Tuesday, is portrayed as a revolutionary attempt by a respected university, an education technology startup and a major corporate employer to drive down costs and expand higher education capacity.

Very exciting.

Udacity will receive 40 percent of the revenue from the new degree program, according to Georgia Tech, which will receive the rest. AT&T is subsidizing the effort financially to ensure that it will break even in its first year and is lending its name to the project

There will several kinds of students:

1. 6,000 students who meet the minimum standards will be admitted.
2. 2,000 students will take the courses but not be interested in the degree. Not clear whether these meet any standards.
3. 2,000 studnets who do not meet the minimum standards (GRE) who “do well in two core classes”. How do they take those core classes if they aren’t admitted? Well, they’re drawn from…
4. the unlimited number of students who can take the MOOC-version of the course with no instructor support and no real degree at the end.

Students will be assisted by instructors from Georgia Tech and Udacity employees who handle more run-of-the-mill questions:

Galil and Thrun both said that Udacity-paid staffers could answer most of the questions students in the courses come up with.

“In many cases, the questions are simple. In many cases these questions can be found in FAQs, even though students don’t find them in FAQs,” Galil said.

Thrun said there’s no reason to make a professor answer the same question 200 times for 200 students. He said his staff will free up Georgia Tech instructors to do more difficult work.

Oh, and everyone is getting paid. Welcome to the future!

Agency Cost Apologists

…it seems that strong families tend to be good for people individually, but bad for the world as a whole. Family clans tend to bring personal benefits, but social harms, such as less sorting, specialization, agglomeration, innovation, trust, fairness, and rule of law.

That’s Robin Hanson.

In his post there are many quotes with interesting perspectives on this idea. I focused on this one:

Risk taking …in family firms … is positively associated with proactiveness and innovation. .. Even if family firms do take risks while engaged in entrepreneurial activities, they take risk to a lesser extent than nonfamily firms. … Risk taking in family firms is negatively related to performance. (more)

Interesting.

The essence of agency costs is that somebody else pays when something goes wrong. This encourages risky behavior.

Is risk really so great? Just hire some managers to bet the farm more often and everyone wins? What is “risk”, anyway? After a bit of digging I was able to find this definition of risk taking:

Thus, firms with an entrepreneurial orientation are often typified by risk-taking behavior, such as incurring heavy debt or making large resource commitments, in the interest of obtaining high returns by seizing opportunities in the marketplace…

Presently, however, there is a well accepted and widely used scale based on Miller’s (1983) approach to EO, which measures risk taking at the firm level by asking managers about the firm’s proclivity to engage in risky projects and managers’ preferences for bold versus cautious acts to achieve firm objectives.

Ok, so it’s survey data (ie watch out for bias!). Large, agent-run companies, remember, have their own risk-killing system which shrugs off survey results: bureaucracy. One can imagine a situation in which agents raise their status by boldly proclaiming a desire for risk with no hope of having to actually act.

These papers should say “professed desire for risk taking is associated with inferior results” for family-run companies. It’s my own view that real corporate strategy involves making lots and lots of small, decent bets.

Never swing for the fences. Never bet the firm. Big risks are unconscionably stupid business.

Calling The Central Banking Bottom

Here is a report by a UK equities research firm:

Changes are afoot inside the world‟s major central banks… After more than a decade of inflation targeting, monetary authorities are, it seems, increasingly minded to go for growth, as the problem is no longer rising prices, but unemployment.

The long-term consequences of this shift – which my colleague Jim Leaviss has termed “central bank regime change‟ – remain uncertain… With its incoming governor recognised as having one of the most informed understandings of the new regime, the Bank of England looks set to play an increasingly important role in the global monetary policy revolution. UK shares could stand to benefit.

I agree. When the central bankers get their act together, which they are doing, nominal incomes will rise, whipping up a tailwind for the recovery.

Now consider the price of of gold which, according to my view, should drop when the markets get comfortable with the bankers’ strategy. It has.

We Throw Alone

Humans are good at throwing things. In fact, we’re great at it; no other animal can throw stuff like we can.

Hm. How important is throwing? I wonder if Aliens, should they exist, throw? More here.

-=-=-

edit: the Randall Monroe post links us to this abstract (among others), which opens with this:

It has been proposed that the hominid lineage began when a group of chimpanzee-like apes began to throw rocks and swing clubs at adversaries, and that this behaviour yielded reproductive advantages for millions of years, driving natural selection for improved throwing and clubbing prowess.

Loving Ugly, Stupid Models

But simple, beautiful mathematical explanations can make us greedy. While we wish for all explanations of the world around us to be elegant, science often involves “the slaying of a beautiful hypothesis by an ugly fact,”

…“there is growing empirical evidence that people use a common source for evaluations of both beauty and truth.” The source he refers to is processing fluency, the state of being able to easily parse and understand a situation. Essentially, the more easily we can get a handle on a situation (because it’s mathematically simple, we’ve seen it many times before, it’s symmetrical, etc.), the more likely it is to seem right.

That’s from this article by Sam Arbesman. I’ll bang my actuarial drum again here: we are trained to use a series of very elegant models of random processes which often involve some clever math but in reality the models only become convincing once you have enough historical data to… well, throw the model away.

There is nothing elegant about social/economic interaction. Go crude and go ugly.

Trusting Statistics

Wolfers and Stevenson with a checklist for evaluating statistics. Here is the most important one, to me:

If the author can’t explain what they’re doing in terms you can understand, then you shouldn’t be convinced.

It’s the biggest problem I have with what I do for a living. I often don’t understand what I’m measuring, be it weather phenomena or auto accidents. They systems that produce Hurricanes and car crashes are too complex for anyone to understand.

Yet we fit statistical parameters to them and cross our fingers.