Broken Symmetry

Fixed Points in the Publishing Industry

From an interview of Lonely Planet's Gus Balbontin on O'Reilly Radar:

The essence of what the print people have known for 500 years is still the same in the digital world: you still have to publish great content. Yes, the tone may change a little. Yes, the experience might be slightly different. But at the end of the day, the people creating the content are humans. The people consuming it are also humans. The same humans that consume print consume digital. It's not different.

...

In terms of the next 10 or 20 years, the essence of what publishers are doing won't change at all. This is what should make publishers feel comfortable about the future. The reason why you're there and the problems that you can solve for customers won't change. That's what you need to keep focusing on.

Former Apple CEO John Sculley on Steve Jobs, Systems Thinker

From a fantastic interview of Sculley at Cult of Mac:

The iPod is a perfect example of Steve’s methodology of starting with the user and looking at the entire end-to-end system. It was always an end-to-end system with Steve. He was not a designer but a great systems thinker. That is something you don’t see with other companies. They tend to focus on their piece and outsource everything else.

Valuing Patented Features of Complex Systems Using Frequency-Averaged Measures of Demand

[Submitted today in response to this call for papers. -MFM]

ABSTRACT

Thanks to the ubiquity and integration of digital computers, each consumer of a product or service now produces a digital stream of data. Bundled together, these streams of data record how particular products or services, including any patented features, are valued by actual consumers in different geographical regions and in different windows of time. Most relevant to patent royalty calculations are the histories of transactions for a particular product or service. These transactions eventually show up in financial statements, which permit top-down estimates of value, such as revenue or gross margins. But alternative metrics drawn from these streams, such as change in the frequency of transactions before and after the introduction of a patented feature, also permit bottom-up estimates of the value of patented features. Demand can also be estimated using metrics for customer engagement, such as the frequency and length of visits to a particular website or the conversion ratio of number of independent visits per completed transaction. In some cases, analyses of these data permit calculation of a more reliable lower bound for the marginal value of a patented feature to a complex product or service. More generally, time-frequency analyses of data on consumer behavior complement existing methods for calculating lost profits or reasonable royalties, and can help resolve questions about the marginal value a patented feature adds to a complex or highly integrated product or service.

The Damages Apportionment Problem for Complex Systems

Under 35 U.S.C. § 284, “[u]pon finding for the claimant the court shall award the claimant damages adequate to compensate for the infringement but in no event less than a reasonable royalty for the use made of the invention by the infringer, together with interest and costs as fixed by the court.” Famously, the Southern District of New York laid out a “comprehensive list of [fifteen] evidentiary facts  relevant, in general, to the determination of the amount of a reasonable royalty for a patent license” Georgia-Pacific Corp. v. U.S. Plywood Corp., 318 F.Supp. 1116, 1120 (S.D.N.Y.1970). The thirteenth in this list is “[t]he portion of the realizable profit that should be credited to the invention as distinguished from non-patented elements, the manufacturing process, business risks, or significant features or improvements added by the infringer.” Id.

When Georgia-Pacific was decided in 1970, Jimi Hendrix was still performing, the Internet was known only as ARPANET, and access to information about cutting edge research and development usually required national security clearance. Four decades later, instead of secrets about national defense leaking to the press through a former first lieutenant in the Marine Corps with high-level security clearance, an Australian hacker is leaking them to the Internet. Instead of a carefully choreographed ballet of contractors producing a 747, a globally distributed swarm of programmers continuously releases new features and combinations of features in an effort to attract a stable base of users. Consumers depend upon producers – producers who compete vigorously with each other to make the sales necessary for their own survival – to cooperate in the development and adoption of industry standards that are necessary for complex, integrated systems to exist at all. The Federal Circuit put it well in describing one of the most commercially successful productivity software products as “an enormously complex software program comprising hundreds, if not thousands or even more, features.” Lucent Technologies, Inc. v. Gateway, Inc., 580 F. 3d 1301, 1333 (Fed. Cir. 2009). The Federal Circuit found “it inconceivable to conclude, based on the present record, that the use of one small feature … constitutes a substantial portion of the value.” Id.

Most lawyers agree with the Federal Circuit that the base for calculating royalties should be discounted to adjust for the value that other features contribute to a product. Other features may include features themselves covered by other patents (not owned in common with a patent-in-suit), or features not easily protectable through patents (such as the durability of parts, precision of manufacturing tolerances, or the timely availability of the product or service at a requested order volume). Moreover, what feature or features were sufficient or necessary to the completion of a sale may vary from customer to customer, or even for the same customer over time. In most cases, it is indeed inconceivable that any single patented feature could be responsible for the entire revenue (much less profit) generated by a complex or highly integrated product or service.

On the other hand, the very fact that an infringer has chosen to implement a patented feature rather than a non-infringing alternative is strong evidence that the patented feature most likely contributes some finite value to the product or service. That value, in turn, is ultimately reflected in the revenue and profit generated by the sale of the complex product or service that includes the patented feature.

[Discussion of economic case for patents, focusing on the potential social benefit of granting property rights in easily appropriable innovations in markets with high barriers to entry. Exclusionary rights permit supracompetitive prices in proportion to inelasticity of demand for patented innovations. Thus, measuring inelasticity of demand is core problem for patent valuation in general, and for damages apportionment in particular.]

Measuring the Price Elasticity of Demand

The Federal Circuit has acknowledged that price elasticity is at the core of the problem of patent valuation. The opinion in Crystal Semiconductor v. Tritech Microelectronics, 246 F. 3d 1336 (2001) is particularly instructive, although it deals specifically with price erosion. In Crystal Semiconductor, the Federal Circuit explained the economic theory of price elasticity:

For example, if substitution of a product were impossible and the product were a necessity, elasticity of demand would be zero — meaning consumers would purchase the product at identical rates even when the price increases. This very rare type of market is called inelastic. On the other side of the spectrum, if any price increase would eradicate demand, elasticity of demand would be infinite — meaning consumers would decline to purchase another single product if the price increases by any amount. This very rare type of market is called perfectly elastic. Markets typically have an elasticity greater than zero and less than infinity.

Crystal Semiconductor, 246 F.3d at 1359 (italics added). In other words, the market value of a patented feature should be tied to its effect on price elasticity, and price elasticity can be estimated by reference to the relative rate of sales at different price levels. The Federal Circuit went on to rule that the patentee in Crystal Semiconductor had failed to show sufficient evidence of whether or how much the rate of sales would have declined as a result of a price increase. Id. at 1360-1. It is enough for my purposes, however, to note that the Crystal Semiconductor case provides a legal precedent for the use frequency-averaged measures of the value of patented innovations, such as relative rates of sales.

Top-Down Estimates from Time-Averaged Revenues and Profits

The approach to estimating price elasticity described in Crystal Semiconductor requires the use of revenue and profit figures, which would typically be derived from financial statements. Financial statements provide a highly compact summary of the entire history of transactions that occurred among a company and its many stakeholders, from the purchasing of capital equipment and parts from suppliers, to the payment of labor for design and assembly, to the actual payments of cash from customers for delivery of the final product. Thus, financial statements provide a good foundation for what I will call “top-down” estimates of the value of patented features.

[Discussion of the information architecture of financial statements: Income and cash-flow statement record time-integrated flow of revenue and expenses; balance sheet records snapshot in time of assets and liabilities. The information architecture of financial statements lends itself to optimization of time-averaged measures of efficiency in increasing sales, decreasing costs of sales. Trends in sales or costs of sales are visible only after two or more periods have elapsed.]

Top-down estimates of the value of patented innovations are most appropriate for valuation of products or services that are protected by a single patent. Top-down estimates provide only a ceiling on valuation when multiple patents cover each product or service sold in the transactions that ultimately result in the financial statements from which the top-down estimates are drawn.

Frequency-Averaged Measures of Productivity

Every time-averaged measure of profitability has a frequency-averaged counterpart. In practice, experienced investors and managers use both to develop a picture of the health of an organization. For example, in addition to gross margin – a time-averaged ratio of profit to revenue – experienced investors and managers also track inventory turnover – a frequency-averaged ratio of costs of goods sold to average inventory. A company with high gross margins but dropping inventory turnover is unlikely to maintain its margins going forward. Conversely, low margins with increasing inventory turnover signals that higher margins might be available in the future. [Discuss analogy to driving without a tachometer.]

Inside large corporations, managers don’t wait until the end of the quarter to spot trends in supply or demand for a particular good or service. Rather, managers monitor daily reports about order and inventory volume to ensure that the supply of products and services stays synchronized with customer demand.

Bottom-up Estimates from Frequency-Averaged Measures

The stream of data that management uses for frequency-averaged measures of productivity provides the basis for alternative, bottom-up estimates of demand for patented innovations. Bottom-up estimates derived from frequency-averaged measures are useful in valuing patents on innovations introduced as features of an existing product or service, or in valuing patents on products or services that are sold as a bundle with many other products or services. Bottom-up estimates may also be helpful in putting a more reliable floor on the minimum value of a patented innovation. A variety of techniques may be used to produce bottom-up estimates using frequency-averaged measures. I give two as examples: Fourier analysis of a time-series of transactions and A|B testing of a web service.

Sales of a particular product are recorded as a time-series of transactions, each of which is associated with a particular price. Within a particular window of time, one can count up the number of transactions and the total sales. The former is a frequency-integrated measure of sales, the latter the time-integrated measure of revenue. Focussing on the former, we can see how the frequency of sales changes within different same-width and different-width windows of time. Most relevant to patent valuation, we can look at how the frequency of sales changes before and after the introduction of a new patented feature. If frequency increases even as price is held constant or decreased, the patented feature probably increased the demand for the product or service.

Because frequencies change seasonally, many web services rely upon a more direct method for testing demand for a feature, called A|B testing. Using A|B testing, managers can watch how actual consumers interact in real-time with a web service that includes slightly different features. It is conceivable that A|B testing could be used in some cases to demonstrate that a patented feature is less desirable than an existing version of web service, effectively resolving some disputes that cannot be resolved using only top-down estimates of value. [Discussion of A|B testing, Google Analytics, Optimizely, &c.]

Improving on Mean Field Approximations of Consumer Behavior

From Coco Krumme, Manuel Cebrian, and Alex Pentland:

Much of economic theory is built on observations of aggregate, rather than individual, behavior. Here, we present novel findings on human shopping patterns at the resolution of a single purchase. Our results suggest that much of our seemingly elective activity is actually driven by simple routines. While the interleaving of shopping events creates randomness at the small scale, on the whole consumer behavior is largely predictable. We also examine income-dependent differences in how people shop, and find that wealthy individuals are more likely to bundle shopping trips. These results validate previous work on mobility from cell phone data, while describing the unpredictability of behavior at higher resolution.

Traditionally, economic data hasn't had the granularity to distinguish between different groups of consumers. Like the exact solutions to the Ising Model, rational expectations theory is a kind of mean field approximation. Now that we have digital trails for individual consumers, improvements are being made to economic models of consumer behavior.

Note that this kind of theory and data doesn't fit easily within the scope of behavioral economics and finance. This isn't a laboratory study. This isn't a theory of psychology. When it comes to consumer behavior at least, we can now say with some empirical support behind us, that indeed "more is different."

A Genetic Substrate for Shared Intentionality?

From Replicated Typo:

At 14 months of age for example, human children are able to successfully pass an object-choice task. In this task, children are presented with two upside-down buckets, one of which contains a toy, and the experimenter points toward the bucket where the toy is hidden. The child then turns to the right bucket and retrieves the toy. Although this task may appear simple, it is remarkable that chimpanzees fail it. In contrast to children, they fail to see the pointing gesture as a relevant cooperative signal within a shared attentional frame. Instead chimpanzees seem to think something along the lines of: “‘A bucket. So what? Now where’s the food?’ They do not understand that the pointing is intended to be ‘relevant’ to the searching as a shared activity (see Sperber & Wilson, 1986)” (Tomasello & Carpenter 2007: 122).

But this result is reversed in chimpanzees when instead of pointing cooperatively towards the bucket, the experimenter makes a prohibiting gesture by holding her arm out towards the correct container with her palm out, says something like “Don’t take this one” in a firm manner and then leaves the room. In this competitive context chimpanzees can successfully infer where the hidden reward. What is equally interesting is that 24 month old children do not retrieve the hidden toy possibly because they were better at cognitive control than 18 month old children and chimpanzees and were aware of the social and communicative conventions of the prohibiting action (Hermann & Tomasello 2006, see e.g. Miller et al. 2002, Tomasello 2008: 208ff. ).

Utility is Local and Ephemeral

From a commencement address by Ben Bernanke:

Your sense of how well off you are economically depends a great deal on your expectations and aspirations, which in turn are largely formed by the community in which you live.

Via Tyler Cowen. Not new to readers of B.S., but encouraging to see also is the reference to Csikszentmihalyi's theory of flow:

Another factor in happiness, perhaps less obvious, is based on the concept of "flow."12 When you are working, studying, or pursuing a hobby, do you sometimes become so engrossed in what you are doing that you totally lose track of time? That feeling is called flow. If you never have that feeling, you should find some new activities--whether work or hobbies.

Negative Feedback in Money Supply, the Chinese Peg, and American Real Estate

More from Chernow's biography of Hamilton, which ought to be required reading for any aspiring minarchist:

For political and legal reasons, Hamilton had to address the loaded question of paper money. The Constitution outlawed the issue of paper money by the states; everybody remembered the worthless Continentals printed by Congress during the Revolution. Should the federal government now issue paper money? Fearing an inflationary peril, Hamilton scotched the idea: "The stamping of paper is an operation so much easier than the laying of taxes that a government in the practice of paper emissions would rarely fail in any such emergency to indulge itself too far." As an alternative, Hamilton touted a central bank that could issue paper currency in the form of banknotes redeemable for coins. This would set in motion a self-correcting system. If the bank issued too much paper, holders would question its value and exchange it for gold and silver; this would then force the bank to curtail its supply of paper, restoring its value.

Hamilton saw clearly that the system needed negative feedback to be what Chernow calls "self-correcting."

What is the source of negative feedback to our currency system now? Since 1971 the dollar has not been redeemable against precious metals.

Some people might answer the Federal Reserve, which indeed can adjust interest rates. But what's to stop the Federal Reserve from doing exactly what Hamilton feared -- i.e., lowering interest rates faster than taxes can be levied? We all know the answer to that question today. Let's not forget it.

A better answer might be currency derivatives, such as credit default swaps. These indeed can slow inflation -- if enough are traded and accurately priced. This hints at a somewhat subtle aspect of the kind of "self-correcting system" envisioned by Hamilton: the holders that are likely to exchange paper for gold and silver early when the currency is overvalued will do much, much better than the people who try to exchange it last. And so it is with derivatives. The effectiveness of derivatives as a correcting force depends on the information available and information processing capacity of the average market participant. So long as valuations are independent, but identically distributed, a central limit theorem will apply, forcing transactions toward a set of "rational" prices. But valuations are neither independent nor identically distributed in a crisis; they're highly correlated and indeterminately distributed.

The best answer is other currencies. The economy is global, and if the dollar gets overvalued relative to the yen or euro, then people will start trading dollars for yen or euros until they're matched. Foreign currencies are to the dollar today what gold and silver were in Hamilton's time. In Hamilton's day, there were planters in the south who exchanged tobacco warehouse bills as a currency. Some even bartered. It's not impossible to imagine that people in the United States might some day be paid in Euros or yen rather than dollars. It partly depends, as Hamilton understood, on how much our government can collect in taxes.

The case of the Chinese yuan is interesting because it is pegged to the dollar. What effect does that have on the negative feedback? The effect seems to be damping -- i.e., if our government's credit improves faster than China's, then the peg will nonetheless slow deflation. Conversely, if our government's credit degrades faster than China's (the scenario that for now seems more likely), then the peg will slow inflation.

"Deflation" and "inflation" here mean deflation and inflation relative to other foreign currencies. Another effect of the peg -- perhaps the most important over the past ten years -- has been the lack of any negative feedback to appreciation in Chinese credit or depreciation in U.S. credit relative to each other. In effect, the dollar is not the dollar anymore, but the dollar/yuan. Whereas without the peg, Chinese would at some point have demanded more currency from American businesses in exchange for their goods, with the peg in place, that point has been delayed while the Chinese government has accumulated larger and larger sums of dollars. Today, China's central bank has a currency reserve of U.S. dollars roughly equal to the excess dollars in circulation in the U.S. banking system ($1 trillion).

Let's say the peg was removed. The immediate consequence would be worldwide scramble to exchange dollars for yuan. The Chinese government, with its huge position, would be a big loser over the short run since it has no practical way to exchange that sum. The United States economy would be an even bigger loser, since runaway inflation would likely put the financial system back into cardiac arrest, destroying the confidence and credibility needed for trade to continue and the economy to function.

But longer term, we'd both recover. The Chinese would take a notional hit to their credit, but they have a solid infrastructure in place now, and could replenish their losses with taxes on their new middle class. The United States, in turn, would take longer to recover since we'd have to go back to making things that we've been importing for over ten years before the government would have revenue to tax.

The Chinese government cannot accumulate dollars indefinitely. The peg must be removed at some point. American real estate looks like a great bet in view of that contingency, despite its ugly state at the moment.

UPDATE: Well I guess I won't have to wait as long as I thought to find out whether any of this is correct. See here.

The Internet Operating System

From Tim O'Reilly:

Might an operating system of the future manage when and how data is collected about individuals, what applications can access it, and how they might use it? Might it not automatically synchronize data between devices and applications? Might it do automatic translation, and automatic format conversion between different media types? Might such an operating system do predictive analytics to collect or locally cache data that it expects an individual user or device to need? Might such an operating system do "garbage collection" not of memory pointers but of outdated data or spam? Might it not perform credit checks before issuing payments and suspend activity for those who violate terms of service?

Tim probably inadvertently sent a lot of traffic my way thanks to link through to a Google search of windows "bag of device drivers" andreessen.

Scalability is ultimately the key determinant to what Internet "operating system" will dominate. Google has the "unfair" advantage at this point. Microsoft also has a big cost disadvantage because of its need to support legacy revenue streams. Apple doesn't seem to have the capabilities now to code scalable server-side apps. iTunes is a nightmare. Cisco's products are complements to the operating system market.

Maybe there is still room for a new competitor to Google. Yahoo has more of an opportunity here than many people realize.

Sherrington on Complexity in Economics

From the Royal Society:

The real world of finance and economics is significantly more complicated than the simplistic MG. However, (i) already one sees several conceptually important aspects that are likely to extend to reality; one is the inadequacy of the doctrine of ‘rational expectations’ in which it is assumed that, given the same information, every agent will make the same deduction and achieve equilibrium —- it has already been pointed out that, even for the MG, there is no representative agent, but only a representative stochastic ensemble —- and another is clear from the recognition that, even if agents could change their strategies, there is no optimal solution in which all have the same strategy, as, by definition, not everyone can be in the minority, (ii) the model could be extended in increments of ‘reality’ or complication, for example, including the accumulation and expenditure/gambling of varying degrees of capital, the effects of market impact, allowing for producers, who must both buy and sell in order to carry out their business, and for consumers,16 or involving limitorder-book bidding, settling and price movement, (iii) the inclusion of some of these effects will result in there never being any ‘equilibrium’, although there might be periods of relative stochastic quasi-steady state, albeit probably also punctuated by catastrophic crises, (iv) many of the drivers of cooperation involve information with no spatial-range restriction, thereby justifying meanfield theory treatment as a good approximation, and (v) one could investigate the introduction of global ‘friction’ and ‘bias’ mechanisms, as, for example, through the imposition of trading taxes and/or other political and legal constraints and incentives.

Indeed, one can imagine many other social-science problems involving many individuals, often grouped into intermediate local, political or national groups, where the interest is in collective behaviour under the influence of both heterogeneous inherent/cultural inclinations and national and international laws. Clearly, anticipated reactions to variation of the laws are of crucial importance in trying to anticipate the resultant ‘health’ of the whole. Minimal models and their incremental complication play an important role in separating the essential from the peripheral, in anticipating the likelihood of catrastrophes and trying to devise ‘dampers’ to avoid or minimize them. Disorder, in the guise of different inherited and culturally nurtured inclinations, such as risk aversion, honesty and emotionality, as well as mental and physical abilities, is part of the natural make-up of individuals, while frustration is a feature of their collective coexistence requiring a degree of compromise to better the whole.

Read the whole thing. See earlier post on applications of the Ising Model to Keynes.

Via Stefan at the Backreaction blog.

How Persuasive Are You?

When you recommend a new product to your friend and she tries it out, is it because you've persuaded her, or because she shares your preferences? If you're like me, you don't generally bother recommending things to people unless you know they happen to share your tastes along some dimension. Yet in principle there are some people out there whose opinions are "influential" -- coaxing otherwise disinterested people to try new things despite having different tastes. In principle, that's part of why professional athletes and celebrities are paid to endorse products. But teasing out exactly how much of the adoption of a new product is due to influence and how much is due to shared characteristics (i.e., "homophily") in the network can be difficult.

One cut at this question is forthcoming in PNAS in an article titled, "Distinguishing Influence Based Contagion from Homophily Driven Diffusion in Dynamic Networks" by Sinan Aral, Lev Muchnik,and Arun Sundararajan (as noted on the OrgTheory blog) (try emailing Aral for a copy):

In the context of product adoption, peer influence is associated with the presence of adopters in one‟s local network... However, identification of causal peer influence effects is complicated by the unobservability problem. Each user either has adopter friends or not, making it impossible to observe whether those with adopter friends ... would have adopted had they not had adopter friends. Homophily in this case creates a selection bias because treatments are not randomly assigned: adopters are more likely to be treated due to similarity with their neighbors. Thus, frequently used methods such as regression analysis, which can only establish correlation, are insufficient. Causal treatment effects can on the other hand be estimated via matched sampling, which controls for confounding factors and overcomes selection bias by comparing observations that have the same likelihood of treatment.

Toward this end we adapt matched sample estimation for use in dynamic networked settings. Conditioning matches on a vector of observable characteristics, behaviors and attributes yields influence estimates that account for the homophily that may make product adoption decisions cluster in the network even if no influence exists. This procedure establishes upper bounds on the degree to which influence (rather than homophily) explains assortative mixing and temporal clustering in networks. Since influence can vary over time, our framework provides estimates of its evolution. We can also assess the marginal influence of having an additional adopter friend for any arbitrary number of friends.

The upshot of this work is that shared characteristics among individuals accounts for almost all of the "viral" spread of new product adoption -- i.e., that preferences are largely fixed within the time-scale of weeks or months after a new product is introduced. There exists, nonetheless, a small group of people who are "influenced" into adopting a new product -- i.e., whom adopt the product through social interactions with other adopters with whom few characteristics are shared.

At least on its face, the work seems to affirm the use of fixed preferences as an approximation in this context. This validates the use of this approximation by economists. It also demonstrates, however, that the approximation is not without exception. Also of interest to economists.

One question I had on considering the work is whether it would be possible to single out the "influenced" and "influencers" in this survey, and determine whether or not such people occupy a position as bridges or "weak-tie" links within the social networks. Along the lines of Granovetter, the idea is that influence here is largely a function of whether or how often individuals come into contact with others with characteristics far different from their own. It would be interesting to know whether these individuals could be identified using this approach, which isolates "influence" from homophily.

Rolfe Winkler Looks Like a Major New Blogging Talent

From his post "Markets need rules":

Anyone in business knows how much trust matters on both sides of any transaction. When trust disappears, transactions stop. The market breaks down and individuals are forced to rely on themselves. In a perfectly free market, where economic Darwinism means competition always trumps cooperation, trade quickly grinds to a halt.

No one wants this. As economist Russell Roberts has argued, “self-sufficiency is the road to poverty.”

Laws align incentives so that cooperation can be more profitable than competition. So that individuals in the free market don’t have to worry about the market eating them alive.

Winkler's take is slightly different than mine. What I would (and did) say is this:

What Adam Smith taught us is that cooperation is the source of endogenous growth within an economy. Voluntary exchanges and divisions of labor literally create wealth within society. When it's money rather than goods or services that are exchanged, residual income (i.e., profit) is an excellent proxy for cooperation and endogenous growth. In fact, it's the best the world has ever known.

Crucially, the argument is that cooperation creates wealth, and that laws (or social norms) promote wealth creation to the extent that they facilitate and encourage cooperation. This claim may be quite counterintuitive to competition regulatory authorities, in particular, because much of competition regulatory theory is premised on the notion that competition is the engine of growth, with a few recognizing exceptions for temporary and otherwise limited monopolies (for example, for intellectual property). Winkler falls into the same trap by treating cooperation and competition as dichotomous. Competitions are simply one way to get people to cooperate.

Consider the facts of the American Needle case, for example. An unfettered market for NFL souvenirs is one form of private cooperation. The NFL IP licensing group is another. Both are procompetitive and anti-competitive, but among different stakeholders. NFL IP Licensing group promotes competition among professional leagues (MLB, NHL, etc.). A free market among manufacturers and distributors promotes competition among NFL teams, and probably lower prices and lower average quality in souvenirs overall. The question, which I think the Seventh Circuit got right, is what kind of cooperation/competiton we want to promote. The institution of market competition merely pushes people to differentiate or operate with more efficiency. When the market is already operating at peak technological efficiency and peak diversity, competition will be degrading and wasteful.

More fundamentally, the divisons of labor and voluntary exchanges that create wealth are acts of cooperation. In some cases, competiton is necessary to close the gap between bids and asks. In others, there are enough levers on the transaction such that competition isn't necessary to get overlap. In cases where transactions are occurring despite lack of competition, government should be careful not to destroy social capital -- often hard won over generations. That was Ellickson's central insight.

Ecological and Constructivist Rationality

Vernon Smith has articulated a distinction between "constructivist" and "ecological" rationality in economics:

We have become accustomed to the idea that a natural system like the human body or an ecosystem regulates itself. To explain the regulation, we look for feedback loops rather than a central planning and directing body. But somehow our intuitions about self-regulation do not carry over to the artificial systems of human society...

"[C]onstructivist rationality (or ‘constructivism’) ... stems particularly from Descartes (also Bacon and Hobbes), who believed and argued that all worthwhile social institutions were and should be created by conscious deductive processes of human reason...In summary, constructivism uses reason to deliberately create rules of action, and create human socioeconomic institutions that yield outcomes deemed preferable, given particular circumstances, to those produced by alternative arrangements...

Since our theories and thought processes about social systems involve the conscious and deliberate use of reason, it is necessary to constantly remind ourselves that human activity is diffused and dominated by unconscious, autonomic, neuropsychological systems that enable people to function effectively without always calling upon the brain’s scarcest resource– attentional and reasoning circuitry...

These considerations lead to the second concept of a rational order, as an undesigned ecological system that emerges out of cultural and biological evolutionary processes: home grown principles of action, norms, traditions, and ‘morality’.

An analogy may be helpful in understanding and remembering the difference between these two concepts of rationality. In a dance performance, the choreographer may exercise constructivist rationality by designing and explaining the moves to the individual performers. But it is ecological rationality that takes over as the individual performers together -- though practice and attention to their neighbors -- execute the performance:

Both forms of rationality are necessary to the pleasing result.

Here's an interesting question to consider: By what mechanism does constructivist order become embedded in ecological order? By reference to the analogy we can make this question more concrete: By what mechanism does the choreography influence the performance of the dancers?

In considering the dance analogy, the answers are not so difficult to see, although the details are surely interesting and important. The choreographer communcates her design with verbal or written instructions to the dancers, who then practice under the choreographer's direction until the design is reproduced. But when we drop the analogy and consider the question more broadly in the context of markets and market-based institutions, the answers seem fuzzier and more difficult to envision.

Perhaps one slice at the answer is provided in a paper by Barbara Drossel reviewed earlier here on Broken Symmetry:

These systems essentially have three states which are called quiescent, excited, and refractory. If there is an excitation, it spreads to the quiescent neighbors. After excitation, a region is refractory to further stimulation and needs some time to recover its quiescent state. The model discussed in this paper describes an excitable medium in the limit where excitation spreads fast on the scale of the refractory time, and where spontaneous excitation is rare. In cases where this limit can be realized experimentally, such a system should show either synchronization or SOC, depending on whether the transition from the refractory to the quiescent state and from the quiescent to the excited state are deterministic or stochastic.

Within Drossel's terminology, sync is acheived through excitation from a quiescent to a refractory state. When in a refractory state, any additional excitation will be passed onto neighboring states. In this regard, Drossel's model seems to have fundamental links to models of population inversions, which produce the coherent radiation of masers and lasers.

Given the right circumstances, even a weak coupling between the neural networks of individuals might be enough to induce a group of people into a state of sync or self-organized criticality.

Spectral Analysis of Different Economic Groups

The NYT yesterday ran a very cool infographic: How Different Groups Spend Their Day.

Be sure to click on the various groups in the top right and watch how the chart shifts. These shifts vividly show that different socioeconomic groups have different frequency spectra for a given activity of consumption or production. From the chart, all we can infer is the difference in mean among the distributions for various groups. But from the data that made up the chart, we might also be able to see the shape of the distributions -- i.e., how much variance there is within the group in time spent on a given activity each day.

Can you see how tracking the frequency of consumption and production for a given individual or group would be a quantitative way to classify different groups, or even organizations? Notice how people with college and advanced degrees spend many more hours working than people with high school degrees. Notice how people over 65 years spend more than twice as much time watching television as adolescents and young adults.

Oh, and guess what most people without children do with the time that people with children spend on family care? T.V. What a waste.

Thoughts on High-Frequency Trading

I've been thinking about doing a longer post on this topic for a while since it fits so well with the idea of applying Fourier analysis to market regulation. Tyler Cowen blogs about it today:

The correct judgment of efficiency occurs at the system-wide level, not at the level of the individual trading strategy. The short-run story is that private profits exceed social returns but in the longer run the trading activity and liquidity brings increasing social returns and better communication of information.

Especially interesting was the comment from Matt Belcher:

I'm a high-frequency trader so take my comments on that basis. Prior to high-frequency trading and fully-electronic markets, the most trading profits went to the physically largest and most charismatic traders on the trading floors. By being large or gregarious they were more easily able to get the attention of brokers and get filled on their orders first, effectively front-running the other traders on the floor. On the NYSE, the specialist in charge of the book also could also extract profits at will. Since the advent of HFT, profits have moved from these traders to the ones with the best computer scientists. You can argue whether the new market is more efficient or fair, but you can't claim that the old one was somehow perfect and impossible to manipulate.

Putting aside fraud like churning and front-running (i.e., assuming the government is monitoring it!), from a social perspective HFT simply turns the fastest firms into the market makers by giving them a competitive advantage over other market makers in profiting on the spread. One could make a good argument, then, that the investments in HFT are a waste from a social perspective. Given the fact that the frequency of new information about public company stock, for example, becomes available on a time-scale much, much longer than the difference in time-scale between the last generation of market makers and the new generation of HFT market makers, this looks like a classic case of the croupiers on Wall Street taking another cut from the public.

But the argument is not so simple. A key empirical question is whether, in fact, the bid-ask spread has narrowed as a result of HFT. If so, then over a long-enough period of time, it may be that the social benefits of a narrower spread make up for the costs of investing in HFT.

A big picture issue is that the frequency of trading is dependent upon what sorts of information and analysis are done by the trader. If you're going to be day trading, then you ought to have access to HFT technology. If you're buying on fundamentals, then from an IRR perspective, whether you have HFT technology at your disposal will matter only when you're moving around a significant number of the total outstanding shares in a company.

Conor Clarke Interviews Thomas Schelling

At his Atlantic Correspondents blog:

I think rational expectations can lead to several alternative equilibrium situations, depending on what people choose to expect. If people expect the price of coffee to go up, they will make it go up. And if people expect the price of coffee to go down, it will go down. And the rational expectations model doesn't necessarily tell you what external ingredient beings to sway opinion in one direction or another.

Last year I wrote up a discussion of Schelling's classic explanation of how rationality is only a special case of symmetries in expectations here: Bounded Rationality or Broken Symmetry?

"Computational Social Science"

From David Lazer, Alex Pentland, Lada Adamic, Sinan Aral, Albert-László Barabási, Devon Brewer, Nicholas Christakis, Noshir Contractor, James Fowler, Myron Gutmann, Tony Jebara, Gary King, Michael Macy, Deb Roy, Marshall Van Alstyne:

To date, research on human interactions has relied mainly on one-time, self-reported data on relationships. New technologies, such as video surveillance (1), e-mail, and “smart” name badges, offer a moment-by-moment picture of interactions over extended periods of time, providing information about both the structure and content of relationships. For example, group interactions could be examined through e-mail data, and questions about the temporal dynamics of human communications could be addressed: Do work groups reach a stasis with little change, or do they dramatically change over time (2)? What interaction patterns predict highly productive groups and individuals? Can the diversity of news and content we receive predict our power or performance (3)? Face-to-face group interactions could be assessed over time with “sociometers.” Such electronic devices could be worn to capture physical proximity, location, movement, and other facets of individual behavior and collective interactions.

The data could raise interesting questions about, for example, patterns of proximity and communication within an organization, and flow patterns associated with high individual and group performance (4). We can also learn what a “macro” social network of society looks like (5), and how it evolves over time. Phone companies have records of call patterns among their customers extending over multiple years, and e- Commerce portals such as Google and Yahoo collect instant messaging data on global communication. Do these data paint a comprehensive picture of societal-level communication patterns? In what ways do these interactions affect economic productivity or public health? It is also increasingly easy to track the movements of people (6). Mobile phones allow the large-scale tracing of people’s movements and physical proximities over time (7). Such data may provide useful epidemiological insights: How might a pathogen, such as influenza, driven by physical proximity, spread through a population?

Available here. To model that data, you need a theory of highly integrated, complex dynamical systems. That set of theory is what I refer to as "systems theory" on this blog.

Computational social science is actually not new. Csikszentmihalyi started collecting such data with pagers decades ago using his "Experience Sampling Method" (ESM).

Via Dan Katz at the Computational Legal Studies blog.

Bleg for Economists: Empirical Tests of the Rational Hypothesis

Folks, aside from the lab experiments (which I know produced mixed results), what empirical evidence do we have of the validity of the rational hypothesis? As best I can tell, the last work done in this regard were the nonparametric tests of WARP by Varian and Bronars in the 1980s.

Those studies, of course, were of aggregates of household consumption over long time periods. Has anybody tested the rational hypothesis against revealed preferences outside a laboratory by tracking individual consumer behavior?

The question comes to this: Is there a data set for a large population that tracks the time-series of acts of consumption for each individual in the population over some period of time?

If the rational hypothesis is applied to predict how individuals will behave, then it should be based on empirical data about individual behavior, should it not? Where is that data?

Entropy in Highly Correlated Systems: Market Equilibrium as Stable Synchronized Flow

The review article linked to the post on Tsallis entropy provides an excellent introduction to this generalization of Boltzmann-Gibb (BG) statistics. In particular, section 2.2 explains how BG statistics obtain at certain limits of the generalized q-statistics (a/k/a Tsallis entropy). What are these limits?

First, BG statistics apply at the limit of independence. So, for example, in a series of N binary events, Tsallis entropy is approximately 2^[N(1-q)]-1/(1-q), and if the events are independent, q = 1 and this reduces to the BG entropy 2^N. This limit is not all that surprising.

Second, BG statistics also apply at the limit of perfect correlation. So, for example, if events are correlated at all scales in accordance with some power law N^r, then the Tsallis entropy is approximately N^[r(1-q)]-1/(1-q). If and when q takes on the value q* = 1 - 1/r, then again BG statistics obtain, albeit to a different set (of rescaled) microscopic variables.

That is really surprising. What that means is that we might see normal (i.e., gaussian statistics) apply even to highly correlated "equilibrium" states. One can't help wondering whether, in fact, that is exactly what we are calling a market equilibrium.

Statistics are all well and good, but what is going on at the micro level to produce these statistics? Tsallis talks in very general terms about "multi-fractal" states. What's that mean? Sounds cool at least, doesn't it?

The paper from Zanette and Kuperman I posted on Friday provides some interesting clues about how microscopic dynamics go from uncorrelated to correlated through a phase transition. The figure posted shows how the number of clusters with different phase characteristics is maximized during phase transitions, and that the process of going from uncorrelated to correlated states involves "cross sync" of spatially dispersed clusters during the phase transition.

Read in conjunction with the papers on Tsallis entropy, I think a picture of how the micro dynamics change with the macro statistics starts to emerge. In particular, we should see Levy statistics during phase transitions, and Gaussian statistics in periods of relatively good syncrhonization/high correlation.

It's a new way to model markets, but the math is all there, folks. Look at the statistics for price shifts within a window to see if they're gaussian or levy distributed. If gaussian, then buyers and sellers are either acting completely independently of one-another (possible, but unlikely) or counterparties are acting synchronously in accordance with share perfectly antisymmetric expectations of future value/revenue (more likely). If levy, then the perfectly antisymmetric synchronized flow among buyers and sellers has broken out into multiple cross-synced clusters.

Is there a way to prevent the market from crashing precipitously at unpredictable intervals? I don't know, but I would think that keeping the market constantly in a phase transition would be a more stable mode of operation -- less susceptible to systemic failures -- than a mode of perfectly correlated expectations.

The Problem with the Principle of Revealed Preferences and a Suggested Solution

In Chapter 5 of the Foundations of Economic Analysis, Paul Samuelson sets forth what he calls "The Pure Theory of Consumer's Behavior," which he identifies with the analysis of utility. According to Samuelson, many economists "separate economics from sociology upon the basis of rational or irrational behavior, where these terms are defined in the penumbra of utility theory. It would seem extremely important, therefore, to know clearly what is contained in the conventional utility analysis, if only to understand the consequences of denying its validity." (at 90)

What is utility? It is not happiness in Bentham's sense, or welfare in some general sense. Nor is it a physiological or psychological. "Originally great importance was attached to the ability of goods to fill basic biological needs," writes Samuleson, "but in almost every case this view has undergone extreme modification."

Why? Because of "the recognition that a cardinal measure of utility is in any case unnecessary; that only an ordinal preference, involving 'more' or 'less' but not 'how much,' is required for the analysis of consumer's behavior."

This is a weak explanation for why consumer behavior should be considered independent of psychology or biology. Why would biology or psychology demand that preferences be cardinal rather than ordinal when a measure of consumer behavior does not? Samuelson does not say. This makes the fact that evolutionary biology, social psychology, and sociology have made a come back recently less surprising, does it not?

But how does this utility analysis of consumer behavior work then? Starting from the assumption of ordinal preferences, Samuelson postulates the existence of a utility function. To help the reader in visualizing his argument, assume for now that there are only two types of goods or activities, A and B, that a consumer can choose. If we assign the quantity of good or activity A to the x-axis and the quantity of good or activity B to the y-axis, then the utility function would be a set of lines in the x-y plane. None of these lines cross; each represents a set of x,y pairs (or bundles of A and B) which produce the same amount of utility for the consumer. The lines are called "indifference curves."

How does this get us to a theory of consumer behavior? We get there with just two additional assumptions:

The utility analysis rests on the fundamental assumption that the individual confronted with given prices and confined to a given total expenditure selects that combination of goods which is highest on his preference scale.

(at 97) In other words, given a budget, a consumer behaves so as to maximize her utility by selecting the bundle of goods that includes as many of the goods that she ranks highly as possible.

There are two assumptions here. First, that the consumer maximizes utility. Second, that the particular bundle of goods selected reveals that the consumer prefers that bundle over any other.

As one might guess from the title of this post, I see problems with one of these assumptions, and it is not the assumption of maximization. As Richard Feynman has noted, for example, the behavior of many systems (human and non-human) can be described as a constrained extremization. It would be more surprising to find out that consumer behavior does not maximize or minimize some quantity.

The problem is with the principle of revealed preference. What the principle suggests is that the preferences (and hence utility) of a consumer can be measured indirectly (i.e., revealed) by observing what bundle of goods is preferred. The problem is that, by construction, a preference is revealed only when a transaction occurs. Although everybody has experienced an increase and decrease in preferences for particular goods over time (such as hunger and thirst), the principle of revealed preferences gives us no way to measure how preferences evolve in time between transactions. Relatedly and in addition, to make a complete "measurement" of consumer preferences for an entire set of goods, one must assume that the ranking of preferences does not change over time (or at least that it changes in deterministic ways). Otherwise there is no logically coherent way to rank the entire set of preferences.

Why do economists make these assumptions? They assume revealed preferences because there are few obvious alternative methods for measuring preferences. They assume time-independence of preferences because there is no other way to measure the entire preference function. Ultimately, they make both of these assumptions because with them, one can make reasonable forward-looking forecasts about how an economy will change as a result of shifts in supply or demand for a particular good. Reasonable, but not perfect!

There are alternatives for measuring preferences. On this blog a year ago I started writing about one. Consider as an alternative to the ordinal ranking of preferences a cardinal measurement of preferences. The preferences of a consumer for a particular good could be measured by counting how often the consumer consumed the particular good within a specific window of time. This measurement of consumer preference would take units of frequency. So if a consumer ate 5 apples in a day, we would say that the consumer had preference 5 apples per day. If the consumer ate only 1 orange per week, then we would say that the consumer had preference 1/7 oranges per day.

Notice how this alternative method of measuring preferences is consistent with the principle of revealed preferences in the sense that within a particular window of time we can rank preferences for each consumer. Within the window of the one week observed, the consumer preferred apples to oranges. If the preferences of this particular consumer are stable over many weeks, then the preference function observed through revealed preferences will be either almost or exactly the same as the preference function measured directly through frequency of consumption and then ranked. This condition of stability is called "ergodicity" by physicists.

But notice also how this method of measuring preferences provides additional flexibility. In particular, the model permits for us to treat preferences as varying with the time-scale of observation. Over the course of a month, consumers might not have much interest in oranges. But over the course of a year, there may be a more substantial preference for oranges.

In addition, the alternative method of measuring preferences permits us to get more information out of the fact of exchange. Whereas before an exchange was our only source of information about the preferences of the parties to the exchange, now with our independent measurement of preferences we can use the fact of exchange as an additional source of information.

Let's say Charlie sells A to Warren for B. If we know that Charlie uses an A / week and B / day, then we can infer that Charlie probably has either some inventory of B or expects to get access to more B within the next day. The fact of exchange tells us about the model that Charlie and Warren have in mind in forecasting their future needs based on their memory of the history of their preferences. In other words, the fact of exchange in view of measured frequencies of preferences still tells us something about their subjective valuation, but it tells us something more subtle than that Charlie prefers B to A and Warren vice-versa. It tells us how often Charlie and Warren expect to use A and B given their current inventory and history of consumption.

For earlier Broken Symmetry posts on related topics see here and here.

In a nutshell, my suggestion is to replace the principle of revealed preferences with a hypothesis of periodicity. The principle of revealed preferences would still obtain in the limit of ergodicity.

Revisiting Robert Ellickson's Critique of Functionalism

An excerpt from Order Without Law:

[E]arly functionalists had a tendencey to consider a human group as a single organizm whose "health" could be examined. It was then easy for them to surmise that Darwinian evolutionary processes would help favor the survival of socially adaptive norms. In the following passage the libertarian scholar Friedrich Hayek lapsed into this sort of analysis:

It is not only in his knowledge, but also in his aims and values, that man is the creature of civilization: in the last resort, it is the relevance of these individual wishes to the perpetuation of the group or the species that will determine whether they will persist or change. It is, of course, a mistake to believe that we can draw conclusions about what our values ought to be simply because we realized that they are a product of evolution. But we cannot reasonably doubt that these values are created and altered by the same evolutionary forces that have produced our intelligence. All that we can know is that the ultimate decision about what is good or bad will be made not by individual human wisdom, but by the decline of the groups that have adhered to the "wrong" beliefs. [The Constitution of Liberty at 36]

(Before nonlibertarian scholars dismiss these thoughts, they should be aware that both Lon Fuller and Thomas Schelling have also harbored suspiciously functionalist sentiments.) [Citing Fuller's "Human Interaction and the Law," and Schelling's Micromotives and Macrobehavior at 124-133].

The difficulty with this sort of organic analysis is that evolutionary processes, as most biologists understand them, select either genes or individual organisms, not groups, for survival. [Citing Dawkins's Selfish Gene and E.O. Wilson's Sociobiology at 106-129; and noting V.C. Wynne-Edwards's dissent.] Assume, for example, that honesty is a functional norm in the sense that, if all the members of a group were consistently honest, they would each be better off than if everyone were consistently dishonest. Would the Darwinian struggle favor the survival of the groups of honest persons? Not necessarily. A dishonest individual living in an environment surrounded by honest people might especially prosper, surrounded by easy marks. As a result, the Darwinian process would tend to select dishonest people for survival. In short, to support a Panglossian scenario of group evolutionary progress, functionalists could not rely simply on the biological theory of natural selection. Instead, they had to develop theories to explain how social-control systems would evolve within groups to prevent successful invasions by deviants who would subvert group welfare.

The punchline is that group selection theory is now enjoying a resurgence among some evolutionary biologists, notably including E.O. Wilson, whom Ellickson cites in support of the proposition that the theory has been rejected by evolutionary biologists. Wilson and Holldobler recently published, The Superorganism, which lays out a group selection theory for how cooperation evolved among insects.

The other objections to functionalism raised by Ellickson are also moot now in view of the improved theoretical tools for being more quantitative about functionalism. In particular, associating a group with a network, and individuals with nodes therein, permits evolution of group behavior to be modeled using mathematical models for network growth and decay. Such models help to eliminate much of the conceptual circularity to which Ellickson objects in this passage.

Market Prices Synchronize Flows

Suppose for a moment that you had never heard of economics or the rational hypothesis but nonetheless had to explain the phenomena of market prices with reference to neither. Where might you start?

I would start by observing what is exchanged. Price is only a measure in some currency of what is exchanged. Let's make it concrete: if someone pays $1 to someone else for a peanut butter and jelly sandwich, then the price is either $1 or 1 PB&J. The definition of buyer and seller is arbitrary, thus so is the unit of price.

Why is there an exchange? Because at the moment in time of the exchange, each party wants something that their counterparty has more than something else currently owned. Alice is hungry and Bob wants the $1 more than the PB&J.

Does this make Alice and Bob rational? No. All it means is that Alice was hungry and Bob was not! Suppose Alice and Bob don't complete their transaction at this moment in time, but rather at an earlier or later moment in time. Suppose it's breakfast rather than lunch time. Will Alice pay $1 for the PB&J? No. She just had breakfast, and anyway she doesn't like peanut butter for breakfast. Now suppose it's dinner rather than lunch. Yes. Alice is hungry because she skipped lunch. She prefers steak, of course. But she's famished so PB&J will do. Bob, on the other hand, might decide at dinner time that $1 is no longer a fair price. Now he's hungry too, and maybe he can't afford to buy or make himself dinner with only $1 from Alice.

This all may seem like a silly exercise to you, but really it's not. What it shows is that price varies in time as preferences vary in time. Preferences are not static, although they may appear to be so if we look at a large enough group over a long enough time.

What are Alice and Bob doing then? They are cooperating. Alice happens to have an extra dollar left over from her sale of a sweater she knitted. Bob has an extra PB&J because he bought too many ingredients. Alice and Bob are meeting each others' needs -- creating wealth in Smith's parlance.

Let's try to generalize from Alice and Bob. Let's say later Charlie shows up and wants a PB&J for a $1. He saw Alice eating hers and wanted one too. Will Bob sell him a PB&J for a $1? That depends. Does Bob have another PB&J to sell? Obviously, Charlie is out of luck if the answer is no. But maybe Charlie is willing to pay more than $1. If so, then Bob might be able to buy more ingredients (if necessary) or spend more time making another PB&J for Charlie.

Why did the price go up? The answer is not scarcity alone! It was not the existing supply and demand alone that determined whether a transaction took place, or if so, at what price. It was scarcity AND the time required for Bob to make the sandwich. If the sandwich wasn't already prepared, then there might be no deal if Bob didn't have the time to make a sandwich right then, or if Charlie couldn't or wouldn't wait for the sandwich to be made.

Asymmetries in both time and goods on both sides of the trade determine whether a transaction will occur, and at what price. But over time periods much longer than the average period of time between transactions, it is the asymmetries in time that matter most in determining price -- money and goods equilibrate because cycles of consumption or production eventually synchronize.

It is in this sense that market prices synchronize the activities of market actors, whose rhythms are otherwise set by hard wired biological needs.

But if price is a function of the frequency and synchronization of complementary activities, then what need is there to add to our theory a hypothesis that market actors seek always to maximize their share of the value of a transaction?

For an earlier post on this topic, see here.

Best Four Sentence Summary of the Crisis and How to Fix It

From Shiller and Akerlof in today's WSJ:

Commercial and savings banks used to have reason to be careful initiating mortgages -- they would most likely hold the debt for years. But banks would increasingly sell the mortgages they initiated to others. And regulation did not adapt to reflect this change in the financial structure. The regulatory failure led to a profound systemic instability in our economy, which accounts for the severity of our economic crisis. Devising new regulatory structures that will allow financial innovation to proceed and yet prevent new such systemic problems is the major challenge to our creative capitalism today.

Tjalling Koopmans on Milton Friedman on Profit Maximization

Here's Milton Friedman:

Let the apparent immediate determinant of business behavior be anything at all -- habitual reaction, random chance, or what not. Whenever this determinant happens to lead to behavior consistent with rational and informed maximization of returns, the business will prosper and acquire resources with which to expand; whenever it does not the business will tend to lose resources and can be kept in existence only by the addtion of resources from outside. The process of natural selection helps to validate the hypothesis [of profit maximization]-- or, rather, given natural selection, acceptance of the hypothesis can be based largely on the judgment that it summarizes appropriately the conditions for survival.

Here's Tjalling Koopmans picking that apart:

Here a postulate about individual behavior is made more plausible by reference to the adverse effects of, and hence the penalty for, departures from the postulated behavior. The reality of the penalty is documented by technological and institutional facts, such as the reproducibility of production processes and the operation of accounting procedures in bankrputcy laws. . . But if this is the basis for our belief in profit maximization, then we should posulate that basis itself and not the profit maximization which it implies in certain circumstances.

Friedman's argument is incomplete for at least two reasons. First, we need an additional explanation as to how or why profit maximization is the relevant selection criterion. There is no a priori reason for this to be true of any institution. Second, we need to know at what level the selection criterion is applied -- i.e., to individual or group performance. The level at which competitive pressure applies will determine the amount of in-group coopearation below that level.

Where does thirst for knowledge fit within our preference functions?

Via Peter Klein at Organizations and Markets I found the recent paper by Paul A. David on the emergence of norms of openness among scientists during the Renaissance, along with an accompanying comment by Kenneth Arrow, which includes these extraordinary passages:

It seems to me that that there is a motive for action not taken account of in standard economic models. It is a motive that operates in a social context and cannot fully be discussed in the terms standard in “methodological individualism.” I refer to what appears to me to be a tendency for individuals to exchange information, to engage in gossip at all levels. There is some form of satisfaction not only in receiving information but also in conveying it. Currently, this is exemplified by the curious phenomenon of Wikepedia, where individuals spend time and effort to convey information without pay and without fame. Probably, there is even an evolutionary basis for this phenomenon, though explanations of social traits (other than those involving kin) on the basis of natural selection have proved to be difficult.

* * * snip * * *

No doubt, consumer demand in the form of practical implications played some role in the acceptance of mathematicians. We all recall the story of Archimedes’ determination of density by weighing in water, and its use in detecting fraud in the making of a royal crown. I have heard no such stories about Euclid or Apollonius of Perga. A major accomplishment of Renaissance mathematicians was the solution of algebraic equations of the third and fourth degree--that is, expressing the solution in terms of repeated taking of roots. But this is and was not a practical way of solving these equations. It was of purely theoretical and, if I may put it so, aesthetic interest, only appreciated by cognoscenti.

Like any modern follower of William of Occam, I hate to multiply causes. The desires for economic success and for reputation are important and basic for the understanding of the growth of scientific knowledge. But I find it hard to understand the developments without the additional desires to acquire and to distribute information, above and beyond the values of economic reward and fame.

What do we consume when we learn new mathematical truths? How might such a good fit within preference function that includes traditional goods? Should we call it a violation of the rational hypothesis if certain groups will forebear traditional goods in order to satiate a thirst for knowledge?

Surowiecki on Positive Feedback Loops

Back in May I blogged a bit about how subprime mortgage securities could be modeled as a positive feedback loop. James Surowiecki picks up the same theme in the latest Financial Page for the New Yorker:

Explanations for the crash often focussed on the hysteria and panic that periodically seem to seize investors. But the madness of crowds wasn’t the whole story. In a healthy market, there are countercyclical forces—mechanisms and institutions that go against the general market trend and encourage diversity of thinking—that make it harder for feedback loops and vicious cycles to take hold. Lately, though, many of these institutions and mechanisms have become procyclical: instead of countering trends, they amplify them.