Monday, September 1, 2008

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.

Thursday, August 28, 2008

What Does this Site Do, Again?

Now that we have gone through the basic elements of our initial "formula," we can revisit the basic premise of this site and provide something of a wrap-up overview. There are still numerous items to discuss--extensions of the analogy, its limits, etc--but we thought it might be good at this point to restate the idea.

Theorizing in any discipline is about abstraction: you try to penetrate to the essential elements of something so as to understand it. This is what economists do: to get a handle on the complexity of economic activity, they seek the core characteristics (or, sometimes, laws)--supply and demand, marginal utility, revealed preference, etc.


In recent years, economists have expanded their purview beyond what we might see as "purely" economic elements. The book Freakonomics, for example, applied economic analysis to all manner of issues that were not traditionally seen as economic issues. But because economics is basically about human behavior and choice, it makes sense that economists would extend their disciplinary boundaries. I have certainly learned more from Steven Landsburg and Tim Harford than I ever did in a college macroeconomics course.

Our aim here is also abstraction, but hopefully in a more colloquial language: that of baseball. We're not saying that every single moment in a baseball game has its economic analogue, nor that every single economic situation has a parallel in baseball. (And we're happily open to reader suggestions for questions or interesting problems to explore.)

We're saying that when you boil down baseball--the on-field game, not the business of it, another growing topic in the past few years--to its essential elements, you get rules, uncertainty, interaction, and complex and perpetually novel outcomes. The same, we submit, is true of economic activity. Now, those seem rather obvious, especially if you simply think about them for a few minutes. But one thing that has surprised us as we have followed economic and financial discusions in the media and some of the academic literature is how remote those seem to be from what actually goes on in the economy.

Rules, of course, are mentioned all the time, as we constantly muse over economic laws and policies. Pick up any book or article written in the last few years on economic issues and you will undoubtedly find a sentence about an "age of uncertainty" or growing uncertainty as to the direction of the economy. Uncertainty is treated as something discrete, like a comet that passes by occasionally. Interaction is the dominant fact of human life in all facets but, until recently, seemed foreign in the economic literature. The steadily growing field of behavioral economics recognizes the importance of interaction, but still retains a focus on stand-alone individuals. Remember the charts from economics class, the business cycle and the production possibility frontier? Quite abstract, but they didn't really convey the dominant fact of economic activity: complex and perpetually novel outcomes. (One of our future posts will be a greater discussion of this, because it is so important.)

So there you have it: in our casting about for different ways to understand the economy, we hit upon baseball. There are probably a lot more people out there who understand at least the basics of baseball than could say they understand the economy and how it changes and develops. We're not experts, but we hope you share our growing understanding through baseball.

Sunday, August 24, 2008

The Dynamic Composite of Teams and Economies

According to Martin Wolf, nations don't compete, companies do. Nevertheless, "American competitiveness" is much on the tongues of our cosmopolitan elite these days. The fear is that other countries, particularly China and India, are beginning to send the United States into an abyss of economic oblivion. This is quite redolent of the 1980s paranoia over Japan (when, I might add, members of that same Council on Competitiveness advocated American adoption of Japanese-style corporatism.)

Possibly the most frequently (over)used word in today's competitiveness conversations is "ecosystem"--what are the elements of an innovation ecosystem? How do we "architect" one? One of the most notable examples of this is a "Periodic Table of Innovation Elements" devised by ASTRA. It purports to list all of the, well, elements that are necessary to come together to form an economic ecosystem that is perpetually innovative. 

This is doubtlessly an innovative way to address competitiveness and economic policy. Unfortunately, it is also a bit misleading. Why? Well, let's see what baseball tells us!

One of the most fundamentally important questions that arises from our baseball analogy is, what explains the difference among teams and countries? If all baseball teams and national economies operate according to the underlying structure of rules, uncertainty, and interaction, why are some teams better than others and why do some countries grow wealthier than others? The answer lies not not only in the quality of players but also in the composite, the way the elements fit together.

Edmund Phelps, Nobel laureate in economics, has explained that a country's economic performance depends on both the strength of individual factors and its economic dynamism, the interlocking system of the relationships among those factors.

So that's obvious, right? We all know that Ernie Banks alone couldn't carry the Cubs to a championship. And isn't the Periodic Table of Innovation a way to express the elements together? Sort of. First, the analogy of the periodic table may be somewhat misleading; second, this reminds me of the Texas Rangers.

I already linked to this article, and I hate to confuse analogies, but we should be aware that the modern elements that make up the Periodic Table did not all appear at once. In fact, it seems that in the beginning there were only three. Trying to list all of the "elements" that make up an "innovation ecosystem" makes it seem like an organization (usually the government--ASTRA is a proponent of big-push federal initiatives) can simply step in and create de novo all these elements.

In 2000, the European Union announced its Lisbon Strategy, whereby it would spur innovation and entrepreneurship through heavy amounts of government-coordinated research and development. Obviously, R&D is critical to innovation. Economic dynamism, however, arises not necessarily from R&D or the generation of innovation, but from how a country makes innovation stick and build on itself.

In this way, the EU might be seen as the Texas Rangers of the international economy. For the past dozen years or so, the Rangers have poured nearly $100 million into big-name signings that translated into only four winning seasons. They haven't been able to put a consistently victorious team together, something that transcends individual players.

No one would argue that the New York Yankees' run of three consecutive World Series titles from 1998-2000 owed nothing to stellar players. But it remains disputed as to how to build such a dominant and consistent team, how to put the pieces together. The same applies to economic growth, and we shouldn't pretend that it is somehow akin to chemistry or physics (or what we think those disciplines are like), that we can simply build or "architect" growth.

Ha Ha Ha, Uncertainty, That's a Good One


Evidently, it is a long-standing joke among economists that uncertainty is a known unknown in economic models. At least early psychologists and modern neuroscientists recognize its importance: "It is, in short, the reinstatement of the vague to its proper place in our mental life which I am so anxious to press on the attention."

That is somewhat reminiscent of my earlier-expressed view that uncertainty is sort of like the dark matter of the economic universe. (Or, I guess more accurately today, dark energy.) And that, I admit, should have prompted me to recall the famous Donald Rumsfeld "poetry" about "unknown unknowns."


Saturday, August 23, 2008

Correction

I stand corrected: thank you to reader skmurphy for pointing out my erroneous attribution of the Game of Life to von Neumann, when it was actually developed (on the back, admittedly, of Neumann's work) by John Conway. I had cited Warsh's cite, and also recalled from Waldrop's book, that Neumann was involved. Error duly noted and corrected. Thanks.

Thursday, August 21, 2008

What are Complex and Perpetually Novel Outcomes?


















So, at long last, we come to the product of our initial formula. As a refresher, let's recall that formula:

Rules x Action in the face of Uncertainty x Interaction = Complex and Perpetually Novel Outcomes

(It should be apparent to most readers by now that this "formula" is slightly tongue-in-cheek. We'll explore that in a future post.)

What do we mean by "complex and perpetually novel"? Let's start with complex, and let me first say what I don't mean by complex. I don't mean the increasing complexity of, say, tying a shoelace knot. You start out with simplicity, you do a loop, you do another loop, more loops at random, until you're left with a knot of such Gordian proportions that you simply take off the shoe. I don't mean that type of complexity. 

I also don't mean the complexity of Calvinball, the game made up and continuously changed by Calvin and Hobbes. With no fixed rules, and the unpredictability of a new rule at any time, the game was immediately complex--impenetrable to even Calvin and Hobbes, generating plenty of frustration and fisticuffs.

What I mean by complexity is that, in any system with a finite and (relatively) immutable set of rules and actions, the number of possible outcomes far exceeds that which you would expect from the seemingly simple starting point. A light bulb flickered on for Peter Albin, an economic pioneer in the field of complexity, when he ran across the "game of Life" created by the brilliant John von Neumann to illustrate cellular automata theory. Here's Albin, as quoted by David Warsh: "What struck me was that in working with automata that derived from 'Life,' a very few operating principles generated model behavior which seemed to be as interesting as those produced by quite massive constructions." (Emphasis added.)

That appears to be quite an apt description of baseball in its essence. In baseball, there's really a limited number of actions you can take in any given situation. The pitcher delivers; the batter can swing or take; the fielders either make the play or it's a hit; the runners go or stay. There are always three outs. Runs score. Games end. (I'll obligingly note the worn but ever-insightful observation that, theoretically, a baseball game could never end: it's not necessarily temporally confined like other sports.)

OK, that's the "complex" part of the product. What about "perpetually novel"? This one is easier. Many of you are likely familiar with Tim Kurkjian's regular feature on "Baseball Tonight," in which he gleefully notes all the things that happened in baseball over the past week that had never, ever happened before. On first impression, it may be surprising that new outcomes could consistently happen in a game with a finite number of rules and possible actions. But if you think about all the elements that go into creating an outcome--the rules, the uncertainty, the interactions--it's not so surprising, after all.

What we find, furthermore, is a close connection between complexity (in our sense here) and perpetually novel outcomes. Here, for example, is Warsh, on his view of economic complexity: "My own sense of the meaning of the word had derived from the use of the word complexity in a famous paper by the economist Allyn Young (“Increasing Returns and Economic Progress”) to describe the growing variety of goods and services, their apparently ever-increasing specialization and differentiation, what we mean today by the supremely hazy term “development."'

Some perceptive readers will at this point likely notice the debt that this site owes to complexity theory (or chaos theory or whatever you want to label it). And while it's true that the ideas behind Box Score were semi-inspired by complexity and ideas related to it (including some of the books listed on this site), that's only part of the story.

Let's face it: complexity theory is sometimes really hard to understand. Most of us, if we're seeking different ways to understand the economy or if we're just trying to get a grasp on basic concepts, are not going to learn all the terminology of a new branch of science. So we at Box Score searched for a simpler way to understand things: a system that generated complexity but that most people could understand. Voila: baseball.

Saturday, August 16, 2008

Formula Elaboration # 3: Interaction



So now we come to perhaps the most important of the three elements: interaction. Think back to our hypothetical encounter between Albert Pujols and Carlos Zambrano

The outcome of this at-bat does not depend solely on their respective individual abilities, or even on the contact between Zambrano's pitch and Pujols' bat. It turns instead on how each of them interprets what they perceive to be the other's thoughts and likely behavior. Likewise with Pujols' expectations of the fielders: what do they think that I'm thinking about what they will do?

The manner in which this interactive dynamic plays itself out becomes ever more complex depending on the situation. With two outs and nobody on base in an early inning, the dynamic is relatively simple. With each addition to the situation, however, the complexity increases and so does the importance of all those myriad interactions: between pitcher and batter, between batter and fielders, between fielders and runners, between runners and base coaches, between the managers, etc.

This is probably pretty elementary to baseball fans, and probably not very surprising to non-fans. How can we use this notion of interaction to think about the economy?

Conventional ways of talking about the economy frequently ignored the effects of interaction. For decades, economists analyzed things almost exclusively in terms of stand-alone individuals with given, even unchanging, abilities and preferences. Yet just as growing research in fields like genetics and neuroscience has demonstrated that interaction can give rise to both personality (nature and nurture) and consciousness (the interactions among neurons), so too has economics recently discovered the importance of interaction.

The magnitude of this realization in economics is well documented in David Warsh's Knowledge and the Wealth of Nations: he chronicles the growing awareness among economists, over a period of twenty years, that things like learning, technological progress, and even economic growth all come down to interaction. Here, for example, is Nobel laureate in economics Robert Lucas, who pioneered the "rational expectations" turn in economic thought: "But we know from ordinary experience that there are group interactions that are central to individual productivity and that involve groups larger than the immediate family and smaller than the human race as a whole. Most of what we know we learn from other people. . . . We know this kind of external effect is common to all the arts and sciences--the 'creative professions.' All of intellectual history is the history of such effects. But, as [Jane] Jacobs has rightly emphasized and illustrated with hundreds of concrete examples, much of economic life is creative in much the same way as is art and science."

In this essay and others, Lucas exemplifies the belated academic recognition of "the influences people have on the productivity of others." Indeed, we've probably intuitively known this for all of human history, except in economic analysis. I would submit that this has stunted everyone else's understanding of economic change.

It's not just interactions among individuals that matter, of course: firms interact with one another and with government regulators, and everyone interacts in one way or another with the rules and the ever-present dark matter (uncertainty). The upshot is that any economic prediction you read that is based on past behavior (which is all of them) bears this fatal flaw: it simply cannot account for the various actions and interactions that determine the dynamic aggregate we call "the economy." Expand that to a global scale and, well, you can see why Alan Greenspan basically thinks the Federal Reserve doesn't matter much anymore.

(Last year in the Wall Street Journal there was a very revealing graphic: they compared the GDP growth predictions of economists with actual GDP growth. Guess what? The economists were nowhere close. Read Taleb if you are looking for harsh words on economists.)

Even if you're not a baseball fan, even if you're not a sports fan in general, you've probably heard the aphorism, "That's why they play the games." The team that looks the best "on paper" is not always (and perhaps only sometimes) the champion at the end of a season. The ultimate result turns on interactions and the unpredictable chains of development they initiate.

We could call those, say, complex and perpetually novel outcomes. Hey! That turns out to be the product of our 'formula," the subject of our next post.

Friday, August 15, 2008

Klosterman Comes Close to Getting It

Since my expository post on Uncertainty, you can see that I have come across a few things relevant to that general theme. One was the Taleb quotation. And now comes this from Chuck Klosterman, one of my favorite writers, in the September issue of Esquire (he is a columnist there). I don't think it's available online yet, so I'll post a few selections here:

"Baseball has--by far--the best scoring system in all of sport. It makes uninteresting contests exciting, because it a) doesn't have a concept of time and b) distributes runs in unorthodox increments. . . . Imagine a 3-0 game in the bottom of the ninth inning: The leading team is clearly in control. But if the leadoff hitter gets a bloop single, the pressure immediately reverts to the pitcher--now, if the next guy gets on base, the game has the potential to be reinvented with one swing. The fact that you can instantly score a variable number of runs (in a game in which scoring is rare) keeps baseball fascinating."

(Admittedly, Klosterman begins this sidebar by saying baseball is a "turgid game that no longer reflects society." Obviously, given the existential premise of this website, I think he's wrong.)

There are multiple levels we could explore here, but I want to initially focus on the one that jumped out at me: a direct link to Mandelbrot's concept of "trading time," a key part of his ideas around fractals in finance. Klosterman points out that in baseball, scoring often occurs in bunches: this not only perpetuates uncertainty but also distorts a "normal" sense of time.

I wonder if a worthwhile statistical analysis would be to chart the distribution of scoring in baseball? Does it occur in bunches? It might make sense given the way a run-scoring rally can build on itself, but I wonder if this might be tied to home run frequency.

Anyway, if run scoring in baseball did occur in bunches, I suppose this might be analogous to the economic phenomenon of innovations often appearing in waves or clusters.

If anyone out there knows if such a statistical analysis has been done, please let me know.

Thursday, August 14, 2008

Our Favorite Curmudgeon on Uncertainty


Nassim Nicholas Taleb, in an interview with Portfolio today:

"The structure of uncertainty in the world is vastly greater than we think."

Dark matter . . . See post of a few days ago.

(I use "curmudgeon" in a friendly sense, of course. I am a huge fan of his.)


Tuesday, August 12, 2008

Baseball as a Teaching Tool

Hmmm . . . on deck, baseball used to teach children about the economy, perhaps?

Baseball Used to Teach Kids About Math and Science


Monday, August 11, 2008

Inequality in Sports

I already mentioned this in a post over at Growthology, where I have the privilege of serving as a guest blogger this week, but I thought it totally pertinent to our project here.

Mark J. Perry at Carpe Diem had this very enlightening post yesterday on home run inequality and team income inequality. He intriguingly notes how the unequal distribution of home run production in any given year matches the unequal distribution of income as documented by the IRS. Perry also had a similar post about the 80-20 rule in NBA scoring.

His point, of course, is that inequality in any human activity, including the economy, is inevitable. Our purview here at Box Score won't always include normative judgments, though I would refer readers to the Friedrich Hayek quotation I posted in the aforementioned Growthology post, as well the Kurt Vonnegut short story.

At some point in the near future we may have a post from Derek applying the insights of Hayek (one of the greatest overall thinkers of the 20th century) to our baseball analogy.

On a final note, the MLB historical stats that Perry used are likely a gold mine for future analysis on this site.

Sunday, August 10, 2008

Formula Elaboration # 2: Uncertainty

Let's say Carlos Zambrano, anchor of the Chicago Cubs rotation, faces St. Louis Cardinals superstar Albert Pujols, in a tight pennant race game. Each player has studied the other: pitch type, pitch sequence, hot and cold hitting zones, direction the ball is usually hit in, etc. When the bases are empty, Pujols has an informed guess of the likelihood that Zambrano will start him off on a fastball low and away. On any given count--1-0, 2-0, 2-1--Zambrano knows that Pujols swings X% of the time. The infield positions itself according to Pujols' directional probabilities, and the outfield will usually play Pujols deep.

Always a game conducive to statistical analysis, the last twenty years have seen a veritable explosion in the statistics used to analyze any possible outcome during a baseball game. Part of this goes under the name sabermetrics (a site we like is Baseball Prospectus), but you can see less mathematical derivations of it during any television broadcast: average with runners on second and third with two out, average with a 3-1 count, ERA during day games, etc.

But no matter how many formulae you throw into a particular situation, like one between Zambrano and Pujols, the outcome always remains indeterminate. It's often said that baseball is a game of inches, and slight differences in the trajectory or spin of the ball, the planar path of the swing, the angle at which the ball and bat meet can have enormous differences. (The "butterfly effect" in a different context.) Pertaining to another sport, David Foster Wallace has written excellently on all the different things that can affect the path of a racquet-launched tennis ball.

All of that is not surprising, but it just goes to show how much uncertainty remains even in a statistical-heavy endeavor like baseball. Moreover, the participants in a baseball game are only human, prone to mistakes and irrational decisions. The beautiful unpredictability of homo sapiens will always create copious amounts of uncertainty.

It also shouldn't surprise anyone that uncertainty is a major factor in the economy. Go back one year to the beginning of what is usually referred to as the "credit crisis." Canvass any news article in the subsequent year and you will continually find expressions of shock at how much we don't know and how murky the future directions of the U.S. and world economies are. It's as if it never occurred to them that uncertainty still lurked. (There are, of course, some hope-inspiring exceptions.)

But what does uncertainty mean? The idea that uncertainty plays a large role in economic affairs has come back into some form of fashion in recent years, mostly due to the fabulous work of Nassim Nicholas Taleb and his books, The Black Swan (the more popular one) and Fooled by Randomness (the better one). Still, Taleb would probably be the first to point out that economists and commentators appear to be consistently surprised at not only the impact of uncertainty but also the mere existence of uncertainty.

I say uncertainty is "back" in fashion because it has been recognized before in economic analysis. Two famous economists in particular, Frank Knight and Joseph Schumpeter, saw uncertainty as a critical element in the economic universe--the dark matter, we might say.

Here is Knight writing in 1921 in Risk, Uncertainty and Profit:

"It is a world of change in which we live, and a world ofuncertainty. We live only by knowing something about the future; while the problems of life, or of conduct at least, arise from the fact that we know so little. This is as true of business as of other spheres of activity. . . . If we are to understand the workings of the economic system we must examine the meaning and significance of uncertainty; and to this end some inquiry into the nature and function of knowledge itself is necessary."

We'll leave the epistemology for the future, or for others (a favorite is Karl Popper). For now it is sufficient to note that Knight insightfully distinguished between two types of uncertainty. Risk, which could be quantitatively measured and thus known and accounted for; and "true" uncertainty, which is non-quantitative and "not susceptible to measurement and hence to elimination." It is this "true" uncertainty--the dark matter--that accounts for the existence of profit and entrepreneurship. (We'll return to entrepreneurship in a future post when we sort out its baseball analogue.)

Speaking of entrepreneurship, Schumpeter was the economist of the entrepreneur--we'll dwell more on this great thinker in the future. Here we'll simply note that Schumpeter placed a great deal of emphasis on "indeterminateness" in economic activity, a line of thought that is well covered in Thomas McCraw's recent biography of Schumpeter, Prophet of Innovation.

OK, so you get the point. Uncertainty rules in baseball and the economy because of the number of things that can affect possible outcomes. If a single play in baseball cannot be worked out or predicted in advance, how much harder is it for businesses and governments in their more complicated environments? This redounds back to the importance of rules, particularly those set forth by governments. Individuals and firms face enough uncertainty as it is--they don't need additional uncertainty created by arbitrary government action.

Perhaps we're consistently surprised by uncertainty because it often masquerades as certainty, or at least predictability, in the form of short-term patterns, for example. The course of a baseball season is often shaped by slumps and streaks. For apparently no reason, a player will suddenly lose the ability to get on base, or will go on a two-week tear. The same happens to teams, and we similar effects in the economy. Stock markets go through stretches of incredible gains or mounting losses; firms can stagnate for extended periods of time.

These short-term patterns can yield a small degree of predictability, and economic models allows us to predict with some confidence the short-term consequences of an action. Yet despite the fact that such patterns are regular economic phenomena and can have identifiable causes, one common trait is that they are usually unforeseen, and sometimes inexplicable.

But we're only human after all: we grasp for any measure of certainty in a world full of the dark matter of uncertainty. As we'll discuss in greater depth later, however, this uncertainty is what creates the opportunities exploited by entrepreneurs in the economic context and what we'll for now call "game-changers" in baseball. In short, uncertainty is a prime source of wealth creation and economic growth.

Or, as Lewis Lapham has written, paraphrasing an Arab proverb: "we have less reason to fear what might happen tomorrow than to beware of what happened yesterday." That's as true in baseball as in the economy.

Saturday, August 9, 2008

Formula Elaboration # 1: Rules

In our introductory post, we set forth the basic formula that expresses the idea of this website:

Rules x Action in the Face of Uncertainty x Interactions of Individuals = Complex and Perpetually Novel Outcomes

Today we begin a brief series of elaboration designed to explain just what we mean by the elements in this formula. Let's start with Rules, or (R) for short. 

(As will become clear, the elements--and anything additional we will later include--are arranged not in chronological order, but in order of what we perceive to be importance in their contribution to the product. That is, we don't think that, when a market economy begins, a council of elders sits down and designs a given set of rules, just as the evolution of baseball doesn't trace itself to a single inventive point in time when someone sat down and made up rules for a never-before-seen game. This is a chicken-and-egg issue and really isn't relevant here.)

Rules are relatively straightforward. Clear rules, both formal and informal, govern a baseball game. Formal rules include foul lines, base paths, the strike zone, the pitching rubber, etc. These provide the basic playing template for the game and are for the most part unchanging. (Critics of the possibly-shrinking strike zone would disagree.) 

The formal rules provide a measure of certainty and are undergirded by informal rules: when a pitcher can knock down a batter, discouragement of stealing bases in late innings when ahead by so many runs, how hard to take out the shortstop during a double play, etc. Tacit and unwritten, informal rules nonetheless help shape the contours of the game.

Market economies are to a great extent self-generating and self-regulating, yet no market economy can function without clear rules and standards. As Financial Times commentator Martin Wolf has written: "Good markets need good governments." Government regulation is, by nature, reactive, but plays a crucial role in structuring economic processes. 

Rules promulgated by government, however, by no means exhaust the rules that provide structure in a market economy. Any type of human behavior occurs in a structure of formal and informal rules. Statutory laws, municipal codes, and accounting standards (often non-governmental) are examples of formal rules. Informal rules can be identified for almost any type of situation: table manners, linguistic conventions, behavioral norms, etc. These can often be unconscious, but still influence our actions. The emphasis within many corporations on "tacit knowledge" is another good example.

Nobel laureate in economics Douglass North is perhaps the most famous name associated with this distinction between different types of rules: he pioneered much of the work, known as new institutional economics, in illuminating the rule structure in which market behavior occurs. Likewise, for a slightly unorthodox but enlightening take on different levels of behavior in the context of economic change, see the work of Geoffrey Hodgson.

No baseball game could be played and no economy could function without rules. But even if you memorized the entire rule book for Major League Baseball, you would have only the dimmest idea of what actually goes on during a game and what determines the outcome of each game. The same goes for the economy: laws and regulations and informal behavioral norms shape economic behavior, but don't really tell you what goes on or how things change.

I suppose this is slightly analogous to the idea that "creativity loves constraints," and you can already see this adumbrating the product (complex and perpetually novel outcomes), but be patient. We next explore the other parts of the formula.

Sunday, August 3, 2008

Welcome to Box Score

Last week, the Bureau of Economic Analysis announced its most recent estimates for Gross Domestic Product (GDP) in the United States. (For a helpful chart over time, see here.) This is the most prominent of the many gauges used to assess the health of the nation's economy, yet its worth is notoriously disputed. The government will be revising these estimates for months, and even years. Nevertheless, it is used by most everyone to make decisions about future actions, whether investments, new businesses, or savings. But what does it really tell us? What does any economic statistic tell us?

Welcome to Box Score, the website devoted to exploring the manifold ways in which the game of baseball can help explain the economy and how it works. The problem of the meaning of statistics is familiar in baseball, and is the source of the name of this site. Like most baseball fans, we peruse the daily box scores in the sports section to learn about what happened in any particular game the previous night. (We also watch the highlights on Baseball Tonight, a subject we return to below.)

From the box score, we gather the basics of the game: inning-by-inning scoring, an individual players' performance, their totals for the season, attendance, etc. Obviously, however, these numbers, no matter how comprehensive, cannot convey the true events of the game and how that particular game relates to other games during the season, whether already played or those yet to be played. What was the pitch sequence to Alex Rodriguez in his first at-bat with runners on base? What was the pitch sequence in his third at-bat, with bases empty? What was the defensive alignment? How did that affect the decisions of the battery (pitcher and catcher) in their approach to A-Rod or his approach to the at-bat? How did his appearance against Roy Halladay relate to a previous confrontation? Watching television highlights certainly adds to a more comprehensive understanding, but inevitably runs up against an inherent limitation of television itself: it is a medium focused on the present, and its ability to convey a narrative over time, especially one as intricate as baseball, is constrained.

Such questions have risen to the fore of baseball in recent years, thanks in large part to the so-called Moneyball approach and the untold contributions of Bill James. General managers and scouts and statisticians have searched for different ways to measure the impact of things like defensive alignment.

Our premise is that the limitations of the baseball game box score have a parallel in economics. So GDP grew by 1.9% last quarter: is that good in relative or historical terms? What exactly happened during the second quarter of the year that produced that number? How have events in the last 6 months or the the last 6 quarters or the last 6 years affected what is occurring in the economy today?

Let's look at this in a larger frame: from 1908 to 2008, the American economy grew at about 3% per year. In economics, that is accepted as a pretty good performance, especially when compared to other countries over the same century. We could flesh that out by saying that per capita personal income grew by X%, or that business investment grew by X%. These numbers would certainly tell us that our economy has performed well at an aggregate level.

But what do those numbers even mean? Saying we enjoyed 3% per annum growth really doesn't tell you anything about how daily life in the United States changed. Without even thinking about it, any of us could rattle off a dozen things that are available today that didn't exist in 1908 (cell phones, personal computers, microwaves), or that are immeasurably better today (drinking water, automobiles, vaccinations). Economic growth (3% per year) obviously is tied up in these advances, and there has been fantastic research done in recent years on alternative ways to measure economic growth and change.

For "ordinary people" (those without Ph.Ds in economics), discussions of the economy can quickly enter the realm of abstraction and argot and lose meaning in mazes of numbers, policies, and arguments. We propose here to use baseball as a vehicle to explore and (hopefully) explain how the economy works, the process of economic change, and, well, the magic of economic growth. The basic "formula" at the core of this website (with many permutations, to be sure) is:

Rules x Action in the Face of Uncertainty x Interactions of Individuals = Complex and Perpetually Novel Outcomes

This applies to both baseball and the economy and is not intended to be all-encompassing--indeed, many of the entries on this site will be devoted to tinkering with, adding to, and changing this formula.

This idea grew out of an essay Dane drafted last summer. After responses both tepid and enthusiastic, I shelved it for a year. With the economic turmoil of the last few months, I decided to revisit and rewrite it. Dave, Derek, and Charles all expressed interest in the analogy, and we decided to establish this site as a way to communicate it and, just as importantly, continue learning ourselves. We do not presume to be experts (at either economics or baseball analysis), but we are keenly interested in the economic future of this country and how we can all better understand it so that we can hopefully generate faster growth for everyone.

Enjoy.