In the Long Run

In its nearly one-month existence, this site has mostly focused on elaborating on the basic ideas underlying the 'formula': Rules x Uncertainty x Interaction = Complex and Perpetually Novel Outcomes.

Necessarily, the first wave of posts offered brief overviews of the elements contained here, and probably gave short shrift to some key ideas. Thus, before moving on to more specific and no less important aspects of baseball's economic explanatory power, I just wanted to flesh out what I consider to be key ideas in economic affairs that we haven't adequately addressed. And here we see Uncertainty and Complex and Perpetually Novel Outcomes come together.

The notion that uncertainty plays a huge role in baseball and the economy (we've analogized this further to dark energy in the universe) is pretty straightforward, and it should be said that we don't really mean uncertainty in the basic sense that no one knows what will happen in the future. That's pretty obvious and not very insightful. (Again, though, I'm consistently surprised by economic writings that attempt to move, with little success, from description to prediction.)

We mean uncertainty in the sense that because so many things go into determining the outcome of one pitch or one play in baseball, our predictive power is limited no matter the statistical tools we have at our disposal. A new National Bureau of Economic Research working paper puts this succinctly: "Behavioral outcomes are influenced by hundreds of variables and a near-infinity of circumstances, happenstances, and coincidences." (Via Odd Numbers.) Because, at bottom, both baseball and economic activity involve human behavior, and because humans are (gloriously) imperfect, there is an endless array of things that will affect an outcome. The relatively new field of "neuroeconomics" takes this even a step further than behavioral economics.

Some readers might claim to find here somewhat of an inconsistency: we list Moneyball, after all, as one of our top book choices and isn't that all about greater statistical rigor in player evaluation? Surely we're not casting our lot with Joe Morgan and his anti-Moneyball crusade?

When I critique the utility (pun intended) of statistical models in economics, I am saying that because of the nearly infinite variety of factors that go into determining one individual decision let alone the course of a $13-trillion economy of 300 million people connected to the rest of the world, how can we hope to predict or manage anything? The approach of Moneyball, often distorted to on-base percentage and much-maligned as purely numerical, revolves around going beyond the traditional statistics used to measure player performance (like batting average) and trying to get a more complete picture of what players do that adds value to a team's effort. Simply sizing up a player's abilities (five tools, etc) or looking at batting average were seen to be insufficient. This won't be news to many readers.

But I would bet that Billy Beane and Bill James don't pretend that they can predict or micro-manage the on-field performance of teams and players. They try to raise the probability of certain outcomes and, ultimately, victory, but they know there are plenty of things (dark energy) out of their control. In this sense, all the noise in the financial press over the last two years about the Federal Reserve "engineering a soft landing" for the U.S. economy and the potential impact of the economic policies of the next president likely overstates things.

As an example, let's look at developments over the long-term, and this is where we see uncertainty working on a much larger scale of complex and perpetually novel outcomes. Let's take the entire course of a 162-game baseball season, and the American economy in the twentieth-century. (Disproportionate time scales, perhaps, but a useful way to think about it--you'll see.)

If you reran, as it were, an entire baseball season, it is highly unlikely that you would get the same result as before. The events as they actually turned out were only one possible pathway, not the only possible outcome. Anyone who has played Strat-O-Matic or Statis-Pro can tell you this and won't be particularly surprised by this observation. The developments during the 2008 season are not deterministic: the bounce of one batted ball, a close call at home, a quarter-inch difference in a pitch, a slight change in wind conditions. Any of these could alter a discrete outcome--compounded over 162 games, they could change the character of everything. We often here this expressed during a player's chase or .400. A few years ago wasn't it the case that with something like 16 more hits Barry Bonds would have hit .400? Put aside the steroids accusations and all the walks: sixteen more hits could easily have been attained with a few of the changes just mentioned--a different bounce, a fielder's position, etc.

Baseball is not Calvinistic: there is no predestination. Economic change, too, is not Calvinistic. If you reran the economic history of the twentieth century, nothing guarantees an exact replay of what happened in real life. Sure, we probably still would have ended up with mass production of automobiles, cell phones, and the Internet. But the dynamics of everything would likely be different. Detroit was not the foreordained geographic center of the auto industry. Other states and other countries were vying for that as well. 

Long-term economic change is often illustrated in economics textbooks by the Production Possibility Frontier, a curve that expands outward as outputs grow. This is a convenient way to depict aggregate economic growth, but doesn't really capture the developmental intricacies of how economic growth feels. Obviously, the point is to represent long-term change in an abstract manner free of potentially-distorting details. But that's like saying at the beginning of a baseball season: some teams will lose, some will win, there will be hits and strikeouts, and at the end there will be one champion. Well, yes that is what happens, but it doesn't really tell us anything about how. Here, in one sense, is an illustration of this. Look at the variety of developmental pathways and niches. Uncertainty and Complex and Perpetually Novel Outcomes are functions of each other.

OK, does this amount to anything more than an observation that contingency plays a large role in baseball and economics? The real payoff is in the implications. We should be careful about applying past lessons to future problems. I would be the first to say let's learn from history, but there's a difference between appealing directly to a past situation and looking instead at the general contours of what has gone before. In this sense, the contemporary debates about whether "Obamanomics" will be like "Clintonomics" or what JFK's tax cuts say about John McCain's economic policies really don't amount to anything meaningful.

We should be more appreciative, in the Popperian sense, of our ignorance: it opens up many more opportunities than a deterministic approach. This is one of the great lessons, for me at least, of David Halberstam's baseball history books: I am consistently surprised in reading them at the unexpected developments, the twists and turns that determined a crucial game or series in 1949 or 1964.

In the next set of posts, we'll begin to take on more specific aspects of baseball and the economy, including entrepreneurship, specialization, long-term dependency effects, and the element of time.