Broken Symmetry

Focal Points Constitute Organizations by Synchronizing the Phase of Human Rhythms

What is the source of growth within a society? Cooperation. What is the source of destruction? Conflict.

At this level of generality, you'd be hard-pressed to find anybody who'd disagree. Yet the mechanism for growth within an economy, or even a firm, remains mysterious. I suggest that the mechanism for growth is the phase synchronization of human activities, which occur in cycles. By communicating and reinforcing focal points, leaders and followers synchronize the phase of otherwise independent human cycles. The emergence of different institutions at different times and in different places is explained by comparative advantages to the communication and reinforcement of one focal point over another.

Growth begins at the level of individuals. Each person within an economy consumes and produces goods or services with a temporal and spatial pattern that repeats. When you count up how often each person consumes or produces within a set period of time, you get a frequency. If you look at a large group of people within the same window of time, you get a frequency distribution. This frequency distribution is mathematically equivalent to aggregate demand (for frequency of consumption) or aggregate supply (for frequency of production).

Here's an amazing fact: If, instead of the frequency-averaged picture, you look at a time-averaged picture of consumption or production for the same large group of people within the same time window, you will not usually see much fluctuation. You'd see a constant level of consumption or production with a little bit of noise around the signal. The noise would be within the range of transactions costs. This is because when the group is large enough, the cycles will be randomly distributed in phase. Thus, instead of adding up into one big cycle, many smaller cycles will cancel into a relatively smooth constant function.

Although economists use mental models of supply and demand to forecast market equilibriums, most managers and investors (at least in the United States, Japan is a little different) look only at time-averaged pictures of consumption and production in making marginal decisions. In effect, they look at the current time-averaged costs of production, the current time-averaged price, and order more widgets to be produced until the former exceeds the latter.

But as we ought to have learned by now, looking only at time-averaged measures of supply and demand is dangerous. Time-averaged measures are useful for understanding total costs. But they are terrible for measuring and forecasting changes in supply and demand. Hence, when supply or demand change suddenly (as they are apt to do in a globalized economy), managers and investors who look at time-averaged measures alone are at a disadvantage. What might show up in a time-averaged picture as a sudden decline could easily be forecast from a frequency-averaged picture that shows slowing frequencies of consumption or production.

Frequency-averaged pictures of consumption and production are more useful in measuring and forecasting value because they provide a more direct measurement of cooperation among people within an organization. Given fixed inputs, the shorter the frequency of the cycle from order to delivery, the more cooperation is taking place among workers. To borrow an analogy from chemistry, only bulk characteristics (such as temperature or pressure) can be measured with a time-averaged picture. The measurement of internal structure requires a frequency-averaged picture (such as an absorption or NMR spectrum). Some day we may be able to measure the focal points for an organization by observing the structure of its frequency spectra of activities.

What is a focal point? A focal point is a mental goal, which is shared by an organization. A focal point can be as trivial as the goal of getting a bucket from point A to point B -- a focal point that organizes bucket brigades. A focal point can be as noble and complex as life, liberty, and the pursuit of happiness -- a focal point that organized a representative democracy. A focal point need not be easily understood or articulated: market price signals are a focal point that organizes consumption and production, although nobody has succeeded in understanding or modeling market price signals (at least at a large scale). Like people, focal points are not limited to a single domain of knowledge or experience. Thus, organizations of people, which are constituted by focal points, have not been limited to a single domain of knowledge or experience.

How do focal points organize people? When two people share a focal point, the cycles that characterize each person's pattern of consumption or production will synchronize in phase to realize the focal point. Growth arises from phase synchronization. When the focal point is profit, growth arises from voluntary exchange (i.e., synchronization of consumption and production). When the focal point is happiness, growth arises from voluntary associations (e.g., synchronization of personal activities through the institutions of family or friendship). Over the long haul, particular organizational structures (e.g., outsourcing with market price signals vs. vertical integration) persist because they perform better at synchronizing cycles.

Thus, once we acknowledge that focal points are responsible for the spontaneous emergence of organizations, we can understand how and why some organizations seem to succeed and some to fail. Successful organizations have focal points that promote sustainable cycles and tight phase synchronization. Often, such focal points have many levels of abstraction, which permit for a variety of different people to relate to different facets of the same focal point. Often, such focal points have long-time horizons, which permit for more sustainable cycles of human activity -- the frequency of each person's consumption or production can only be pushed so high.

The flip side to this is that some focal points are very dangerous and destructive. In particular, when the focal point for an organization becomes its distinction from another group of people (i.e., when the focal point is racial, ethnic, or national identity), the organization will become agitated and violent when forced to interact with the group from which it perceives itself distinct. In fact, this has been the basic strategy for most dictators throughout the course of human history.

The Founding Fathers of the United States of America had an implicit understanding of focal points, and the role focal points play in organizing people. Our nation was constituted by a long, drawn-out process whereby nearly every political conflict was resolved through a voluntary agreement among equals. I say nearly because there was one issue left on the table, which wasn't formally resolved until the Civil War (and many would say remains incompletely resolved even today). Part of their genius was in recognizing the comparative advantage of various focal points.

For example, the Founding Fathers wanted religious institutions. But they didn't want religious institutions to have access to the military. So they recommended to us an establishment clause. As another example, the Founding Fathers wanted an open public discussion about government, which they knew would benefit representatives (and hence, the represented). So they recommended to us protection of speech and the press. As a final example, the Founding Fathers wanted civilians to respect and relate to the military rather than treating them either with too much or too little respect. So they put a civilian (the President) in charge of the military. They were geniuses at this.

At this moment in history, it is our task to revisit the social contracts that constitute public and private organizations. We have at our fingertips new technology and new understanding sufficient to make great leaps in how well we synchronize our activities. It is up to our generation to decide whether we will use these tools and theories to do good or evil to humanity.

How to Improve Traffic Flow

I was driving on Highway 17 on my way to Santa Cruz today, and I started reflecting on the question of how we could improve traffic flow using principles of synchronized flow.

Often on the highway, one will observe a slow driver in the fast lane, holding up a line of traffic.  This is particularly problematic on two-lane roads.  In physics terms, lane changes increase the viscosity of flow, which in turn slows the average rate of traffic, and increases the probability of accidents.

But because humans are driving, we have the possibility of coordinating behavior through incentives.  Ten years ago, this would have been impossible, because two drivers had no way to communicate efficiently (at least not safely) on the freeway.  Now we do.  Here's a very rough idea of how to solve the problem of highway traffic with incentives and technology:

1. Sell an RF device to drivers that can be installed within easy reach of the steering wheel, with an easily visible and readable display that registers a unique identification whenever another such device is nearby -- say within 100 meters -- for example, by displaying a picture of the make, model, and color of the car.  Make it easy to cycle through the nearby cars on the display.
2. Give each driver who installs the device the option of loading a certain amount of cash into memory, say $100, with a specified "tip unit," which could be decided by the user (say, $1).
3. Whenever a driver with the device installed comes up behind another car with the device installed, the device can prompt the driver behind: "Offer Tip?"
4. The driver may then press a button, which signals the device in the car in front that a tip of $1 is being offered from the car behind.
5. Now if the driver in front pulls over, the driver behind can press a button that says, "Give Tip."
6. The device in the car behind then executes an electronic transfer to the device in the car in front.   People who are not in a hurry can literally earn money for accommodating drivers who are.
7. By keeping each device synced with a mainframe by cell connection, the company selling the device can maintain a rating for each tipper (so that you can't game the system by promising a tip, but then not executing) and other anti-fraud measures.

Now obviously this is somewhat regressive as a "tax" on driving time because some people are going to be able to make much bigger tips than others, &c.  But I think it's still a net benefit to society because it would decrease accidents and road rage, and probably increase the average flow of traffic by a lot.  Right now, it's impossible for anybody to know whether the guy in the car behind them is just a jerk in a hurry or whether they're on their way to the hospital to save another person's life.  Besides, it's also a progressive "tax" in the sense that you don't have to pay anything if you take public transportation instead.

If anybody knows of any startups working on a similar idea, I'd like to know.  Because of the incentives of picking up free money and shorter commutes, I bet it wouldn't be hard to sell these devices.

A Neuroscientific Explanation for the Hypothesis of Periodicity and the Synchronized Flow Theory of the Firm?

Regular readers know that I've been exploring an extension of the traditional economic theory of the firm.  Specifically, I've been exploring the following hypothesis:

A firm will emerge when a single team of people can synchronize the flow of supply to demand at lower costs than two independent teams relying on market price signals alone.

"Flow" here means a unit quantity of goods per unit time.  You can read the original post, in which I place the hypothesis in the context of earlier work by Coase, Alchian & Demsetz, and Williamson, here.

To my surprise and joy, it turns out that there have been some discoveries in biology and neuroscience over the past few decades that have some very interesting affinities with the synchronized flow hypothesis.  Specifically, relatively new work on mitochondria, neuroplasticity, mirror neurons, and collaborative memory seem to fit well with the theory of synchronized flow.

The Connection between Mitochondria and the Hypothesis of Periodicity

First, the synchronized flow hypothesis was inspired by the observation that human consumption and production occur in cycles with a measurable frequency distribution.  Integrated up into cumulative distribution functions, these frequency distributions can be shown to be equivalent to aggregate supply and demand for a population within a window of time.  Over the past few days, I've been reading Nick Lane's recent book about mitochondria (thanks to Tyler Cowen for the recommendation), and have discovered that, over a fairly wide range, a power law applies to the basal metabolic rate of mammals.  In other words, some network topology is responsible for the periodicity in our metabolism.  Since mitochondria are responsible for quite a bit of our metabolism, the hypothesis of biologists is that it is the network topology of mitochondria that determines the rhythms of metabolism, at least for mammals.  In other words, our network of mitochondria provides a biological mechanism for explaining the hypothesis of periodicity.

Mitochondria and Neuroplasticity

As if that weren't enough, it appears that mitochondria are also responsible, at least to some extent, for neuroplasticity.  See here for a description of the function of mitochondria within the brain.  Neuroplasticity is the phenomenon whereby certain neural pathways are reinforced by experience.  I started reading about neuroplasticity in this book by Norman Doidge, in which he describes (among other things) how blind people have been taught to see through the use of cameras hooked up to tactile feedback transducers.

Are you with me?  So far we've got a biological mechanism for explaining why we observe particular rhythms of consumption and production, which happens to be related to the mechanism that permits us to learn by repetition.

Neuroplasticity and Mirror Neurons

Another result we've gotten recently from neuroscience is that there are certain neurons in the brain that will fire both when we do things and when we see another person do the same thing.  If you pair that up with neuroplasticity and the mitochondria, what you've got is a mechanism for us to teach and learn from one-another, including a mechanism for indirectly influencing one-another's rhythms of consumption or production at a biological level.

Consider this: if I perform zen meditation in front of you, because of mirror neurons, your brain is going to start firing along similar pathways to the ones that my brain is firing along while I'm in meditation.  The result is that you are going to be more likely to want to do zen meditation and in fact, you may get some of the benefits even just from watching me do it.  Zen meditation, of course, is a pretty benign example of the power here.  Investors should see immediately how much this means.

Collaborative Memory

Has anybody looked empirically to see whether any of this neurophysiology is borne out at the level of psychology -- much less at the level of economic hypotheses (such as rationality)?  In fact, yes.  Here is a summary of work done on "collaborative memory."  The surprising results of this work are the following: certain cognitive tasks are negatively affected by collaboration, including group brainstorming for word-list retrieval.

In an earlier post, I explored a theory of why that might be, based on the results of other neuroscience research reported in Daniel Goleman's new book, Social Intelligence.  My thought is that the synchronized flow theory can be explained on a neursocientific basis as the result of comparative institutional advantages in how and what information is communicated in order to synchronize supply and demand.  In particular, the thought is that integration of firms will be favored when mirror neurons and plasticity will lead to better flow synchronization.

Obviously, this is all speculation at this point.  But it's really fascinating stuff, and I couldn't help throwing it out there to see whether there was anybody else who would be similarly interested in it.  I realize that the connection between these various steps is fairly tenuous.  Yet lots of research has been done at each step.  If you simply connect the dots, you've got a fairly solid biological explanation for why groups of people choose to work together on one set of tasks, but not another.

The Ensemble of Parametric Oscillators Model of the Economy

Markets can be modeled as ensembles of parametric oscillators.  The parametric oscillator model is the simplest model that is useful in understanding dynamic market prices.  For non-physicist readers, you've made a parametric oscillator whenever you've pumped your legs on a swing to change your frequency of oscillation.  If you've ever had somebody push you, then you've made an amplified parametric oscillator, which is equivalent to a market hooked up to a time-varying external money supply.

Supply can be modeled as an ensemble of oscillators, one for each person.  The cumulative frequency distribution of the supply ensemble is equivalent to the aggregate supply available to a market within a window of time.  Demand can be modeled as an ensemble of oscillators, one for each person.  The cumulative frequency distribution of the demand ensemble is equivalent to the aggregate demand available to a market within a window of time.  See here.  Elasticity is a function of the fatness of the frequency distributions at the half-maximum to their peaks.  The distributions will be poissonian in shape.

Both cumulative distribution functions can be parametrized in terms of the opportunity cost of any scarce resource within an economy, or in terms of a currency that does not vary fast with respect to other currencies within the size of the time window.  (Doesn't that explain why we use currency rather than bartering?)

The "temperature" of these ensembles (i.e., the shape of the distribution for a given amount of capital when scarcity and size of the ensemble are fixed) will be a function of the capital available.  Similarly, other changes in the cumulative frequency distributions of supply and demand will be a function of capital (energy), scarcity (volume), and the size of the ensemble (pressure).  If the changes are made slowly with respect to the time windows within which the distributions are measured, then convexities in the function of frequency with respect to increasing capital, decreasing scarcity, and increasing ensemble size may be observed.  Certain ranges of capital, scarcity, and size of the population will be characterized by certain types of structures.  In other words, as capital, scarcity, and size of population are tuned through different ranges, spontaneously ordered structures for the allocation of capital and resources throughout the ensembles will emerge.  Thus, the parametric oscillator model is consistent with a thermodynamics of institutional design.

Thermodynamics gives us no insight into how and when change will occur.  But the parametric amplifier model also permits an insight into market dynamics.  According to this model, the ensemble of supply oscillators  couples nonlinearly to the ensemble of demand oscillators.  Mathematically, the mechanism for coupling is analogous to a damping force on each ensemble that is, in part, a function of the frequency distribution for the other ensemble.  In other words, the oscillations of the two ensembles don't simply add or subtract from one-another.  They can multiply or divide one-another.

In practice, the coupling mechanism might be provided by anything that causes the frequencies of the ensembles to multiply rather than add, such as transactions costs or liquidity constraints that do not vary linearly with the quantity of goods exchanged.  Study of models of the coupling mechanism will be one of the most fruitful areas of research for econometricians.  For the coupling mechanism is not simply a function of the frequency of the supply and demand ensembles of the market in question.  Rather, it is a function of the frequency distribution for any supply or demand ensemble with non-trivial cross-elasticity with the supply and demand ensembles for the market in question.  The coupling mechanism, including the phenomenon of cross-elasticity, is the dynamic mechanism that describes how and when phase transitions will occur.

Note that variations in external money supply would be a source of capital to the supply or demand ensembles that should be considered separate from the coupling mechanism.  Thus, an increase in external money supply might give rise to parametric amplification.  Variations in external money supply add many complications to understanding the dynamics of parametric oscillators.  Having a Taylor rule that describes how the external money supply varies in time makes the model easier to solve.

Parametric oscillators exhibit many interesting dynamics.  One is the phenomenon of parametric resonance, whereby the ensembles may become synchronized in phase.  Phase synchronization is an implicit or explicit characteristic observable in all markets.  Another is the phenomenon of parametric instability.  Price bubbles can form when the resonance peak (or peaks) are too high-frequency to be sustainable.

For the Hayekians out there, given constant resources and population, as capital is removed from the system, spontaneous symmetry breaking will result in new spontaneous ordering of capital, resources, and population within the market.  In other words, holding two out of three of capital, resources, or population fixed, and minimizing the other variable will lead to more spontaneous order within society.

As an end note, the wave equation necessary to the parametic oscillator model will not apply over longer time scales.  Wave equations are second-order in time.  For very large time windows, dissipative forces will have more noticeable effects, and a heat equation (like the Schrodinger equation) will provide a better approximation of dynamics.  The difference in observable dynamics at different time-scales is part of why microeconomics and macroeconomics are not readily joined in econometric theory.

The Neuroscience of Synchronization

Today I got my hands on a copy of the newest Daniel Goleman (author of Emotional Intelligence) book, titled Social Intelligence.

Goleman summarizes research showing that there are "high road" and "low road" channels of communication operating most of the time in social interactions.  The high road corresponds roughly to processing of ideas.  The low road to emotional signals, which are exchanged through facial expressions, tone of voice, and language including body language.

Interestingly, the low road can function smoothly even as the high road is disrupted, but the converse is not true.  In other words, most people, if distracted with math questions while playing chess, won't play chess as well; but the same people will usually be able to detect whether the voice asking the math questions sounded happy or sad.  By contrast, the high road gets disrupted when the low road is disrupted -- if I shout angrily or sob while I'm asking you complicated questions, you'll most likely show less accuracy in answering them.

Assuming I'm understanding the summary of research correctly, this has fascinating implications for the synchronized flow theory of the firm.

• When low road information is likely to be disruptive (e.g., in buying and selling securities because of the powerful herd instincts triggered by mirror neurons), market signals may be the best means for synchronizing the flow of supply and demand.
• When low road information is likely to be important (e.g., in supplying specialized services, such as legal advice or psychiatry), market signals may be a poor means for synchronizing the flow of supply and demand.

Another finding summarized in the book is that low road communication tends to improve through repeated cooperative interactions.  A firm that has success with internal flow synchronization will thus tend to build on its strength, whereas a firm that tries and fails may disintegrate -- even when a second or third try might be successful.

Why do dairy farmers complain about daylight savings time?

Despite what the usually reliable Cecil over at the Straight Dope has to say, dairy farmers are not stupid or stubborn to complain about daylight savings time.  Daylight savings time causes a phase shift in demand cycles, which disrupts the synchronization of supply and demand cycles established immediately prior to every change due to daylight savings time.

For those who haven't been keeping abreast of the debate, since daylight savings time was introduced decades ago, dairy farmers have been complaining about the problems it causes their cows.

Cecil, like many thoughtful people, has observed that what humans name an hour does not matter to a cow.  On these grounds, he denies that dairy farmers have any legitimate reason to complain.  Just milk the cows at the same time, regardless of whether it's labeled 5 a.m. or 6 a.m., and the cows won't have to adjust to being milked an hour later.

The flaw in this reasoning is that it does not take account of the relative timing between supply and demand.  Suppose it is spring and the clock has moved an hour ahead, but the dairy farmer ignores the time change, and milks 24 hours after the last milking (not 23 hours after, as daylight savings would otherwise require).  Now the cows are happy because they don't have to wake up earlier.  But the distribution truck drivers are unhappy because like everybody else in the world they showed up an hour earlier, and now are late in delivering milk to the local supermarket.  The same problem happens in reverse in the fall, when the truck shows up an hour after the milk has been sitting out, ready for pickup.

The only way for the farmer to avoid disturbing the cows is to convince the whole rest of the world not to pretend like it's an hour later in the spring and an hour earlier in the winter.  Which is exactly what the farmers are trying to do.

Neurophysiological Explanation for Mimetic Desire?

"Mirror neurons"

There are some neurons in our brains that fire both when we do something and when we see somebody else do the same thing.

Among other things, malfunctioning mirror neurons have been postulated to be part of the physiological mechanism behind autism.

Found the link via reading tip from Tyler Cowen.

IP is not an Asset: Patents and Inventors Need to Stick Close

Earlier this week, Peter J. Wallison argued that conventions in fair value accounting may in part be the cause for the recent bubble markets.  Specifically, Wallison pointed to the convention (implemented under FASB 157) that requires assets to be carried at "market" values, even when those assets are not being held for trading purposes.

Almost any scientist or engineer would immediately have recognized the truth of this argument.  Our understanding of any system -- chemical, electrical, mechanical, or financial -- will be limited in part by the accuracy of our tools of measurement.  When one considers how FASB 157 required banks to report the values of MBSs, CDOs, and CDO^2s on their balance sheets far above what the banks would themselves have been willing to give away for the same assets, one understands how the financial markets quickly lost track of the intrinsic value backing the securities traded.

This wisdom has direct relevance to the secondary markets for IP.  Most of the firms now in the secondary markets for IP have taken the view -- and are conducting their businesses -- as if IP were an asset.  This is because IP does bear some characteristics of an asset.  Namely, like real and personal property, IP can be protected through exclusive rights.  The analogy to property has thus come to dominate our understanding of the nature of IP.

Although accountants often treat IP as an asset, IP is not a commodity.  IP is more like equity, although it is not like other equity.  IP is a limited exclusive right to human capital (namely, to inventors' time solving a technological problem).

Maybe part of the reason that Abraham Lincoln understood the importance of patent law is because he understood that human capital cannot be owned.  The photograph shows the Emancipation Proclamation, whereby Lincoln did more for the cause of freeing human capital than many other men together have done in the course of human history.  Lincoln loved the patent system because he understood that it too could lead to more freedom.  Scientists and engineers work best free from the immediate demands of business people and customers.  The idea of a patent system carries within itself the promise of more innovation and more freedom.

POSTSCRIPT: Please note that I do not believe that inventors are literally enslaved right now.  There are obviously huge differences between the enslavement of millions of black Americans and the metaphorical enslavement of inventors who are now forced to do work other than inventing because of the broken patent system.  I do, however, believe that making people more free leads always to a multiplicity of unanticipated social benefits.

What the Founding Fathers knew about R&D that we have forgotten

As evidenced by his lecture on discoveries and inventions, Abraham Lincoln had a deep understanding of the patent system.  It is amazing how his lecture, which is now well over 150 years old, can seem so fresh today.  He and Charlie Munger have inspired me to undertake a historical review of other important lessons of the imminent dead.  Today the lesson is from Scottish enlightenment thinker Adam Smith, famous for his authorship of The Wealth of Nations. I must shamefully admit that I have thus far been unable to make it through the entirety of his treatise.  I have nonetheless been the beneficiary of the wisdom of Adam Smith through the help of editors, from whom we have the following excerpt:

To take an example, therefore, from a very trifling manufacture; but one in which the division of labour has been very often taken notice of, the trade of the pin-maker; a workman not educated to this business . . . nor acquainted with the use of the machinery employed in it (to the invention of which the same division of labour has probably given occasion), could scarce, perhaps, with his utmost industry, make one pin in a day, and certainly could not make twenty. But in the way in which this business is now carried on, not only the whole work is a peculiar trade, but it is divided into a number of branches, of which the greater part are likewise peculiar trades. One man draws out the wire, another straights it, a third cuts it, a fourth points it, a fifth grinds it at the top for receiving the head; to make the head requires two or three distinct operations; to put it on, is a peculiar business, to whiten the pins is another; it is even a trade by itself to put them into the paper; and the important business of making a pin is, in this manner, divided into about eighteen distinct operations, which, in some manufactories, are all performed by distinct hands, though in others the same man will sometimes perform two or three of them.

Adam Smith goes on and on from here about the many benefits of the "division of labour."  Although controversial in his day, the benefits of "the division of labour" are in our day a fact so well-accepted by the majority that many people seem unaware of the history of this idea.  We seem to assume it a logical consequence of any business. That it is not.  In each case in which a division of labor is successfully implemented in business, there was first an entrepreneur who saw the benefit of separating one task into two.  Henry Ford brought the magic of divisions of labor to the production of cars through the assembly line.   Most people can't imagine this, but before him others probably scoffed at the idea that something as complex as a car could ever be assembled without a single person overseeing the entire process.

Are we not still scoffers?  In the United States, we now live in an age in which most lawyers, business people, and researchers believe that R&D and early-stage product development are incapable of being done by two teams.  The fact remains, however, that the best inventors and the best startup CEOs are not often the same person.  And the best R&D and the best product development tend to occur in different environments.  We have strained for the past twenty-years in the United States to force inventors into the role of entrepreneurs, and entrepreneurs into the role of inventors.  Being a hardworking nation, we have not been entirely unsuccessful.  But how much more successful might we be were we to accept once and for all that there is an efficient division of labor between R&D and commercialization (yes, even the "commercialization" done by startups)?

The patent system is the most sophisticated and efficient means for implementing a division of labor between R&D and commercialization ever conceived by humans.  It is by cutting back at patent rights in the United States that we have inadvertently forced inventors to become entrepreneurs and entrepreneurs to become inventors.  Let us not further disintegrate the division of labor between R&D and commercialization by weakening our patent laws in 2008.  Let us recognize that good inventors and good startup CEOs are not always (or often!) the same person.  Let us "promote the progress of science and the useful arts" in the ways our Founding Fathers intended, by a division of labour between R&D and industry.

Stable Market Design with Control Theory

Earlier this week, I had a vision of how analog circuit design theory could have provided some useful insights into how to avoid bubble markets.  I haven't found too much on this from googling, although this paper looks pretty close from the abstract (I don't have a subscription so can't verify whether they're actually thinking the same way).

The field that physicists and applied mathematicians call Control and Dynamical Systems has basically developed to aid engineers in building systems that use feedback to stabilize the state of any system that goes through cycles.  There are lots of things that machines (like the stealth fighter) do that humans would not be able to do because of the magic of feedback-stabilized oscillation.

The implications that this has for business cycles in public and private markets is so obvious that I'm quite certain that somebody already knows how to do this.   Alas, they're probably making boat loads of money on it as we speak.  Another problem worth solving is how to give incentives to such people to share their insights through something other than bidding or asking price.  (Actually, granting patents on financial engineering innovations isn't a bad way to do this.  But a two-decade term would be overkill in most cases.)

In the interest of aiding translation between physicists and economists (and hopefully help avoid yet another major bubble in our financial markets), I'm going to identify the simplifying assumptions that I think are most useful in modeling markets with control theory, and then offer a few extremely crude observations about the potential benefits of applying this theory.  I'll use electrical engineering terminology to show the relationship between the variables.

* Price can be modeled as a two-dimensional current signal in time and demand P = P(t, d)
* Price changes will be amplified by bundling supply and demand (e.g., through securitisation) so that P = A*P where A is either less than 1 (supply bundling) or greater than 1 (demand bundling) depending on whether buyers or sellers are being aggregated by a particular security.
* Transactions cost can be modeled as resistance (and Price * Transactions Cost will approximate Demand)
* External money supply can be modeled as capacitance (which will introduce a phase lag into price)
* Liquidity can be modeled as inductance (which also introduces a phase lag into the price)
* Demand can be modeled as voltage

For purposes of this model, I'm assuming that the external money supply obeys some predictable rules (like Taylor's Rules).  The system is going to be extremely indeterminate if the external money supply doesn't behave in predictable ways.  (There's a useful result right there!  Let's implement Taylor's Rules.)

From my very crude understanding of theory, this kind of model would permit the following predictions to be worked out from the nonlinear differential equations that govern such a system:

* Systems that include both inductance and capacitance (i.e., external money supplies and liquidity) are going to oscillate at a characteristic frequency.  That frequency is the "resonance peak," and it's amplitude will vary depending on the amplifiers.  If they're too strong, the circuit blows up.

* Systems that include large inductance but low capacitance (i.e., liquidity but no external money supply) are going to decay exponentially to zero price

* Systems that include mostly positive feedback (i.e., amplify demand without inverting or phase shifting the input signal) are going to increase exponentially (until they blow up).  (This was Monday's insight.)

* Systems that are tuned to include just the right amount of positive and negative feedback are going to oscillate stably within a limit cycle for long-periods of time.  In fact, such systems will "magically" self-correct price to demand.   Actually, this is most markets, most of the time.  We just haven't been paying enough attention to the bigger picture.

Somebody out there must have done some graduate school research on this topic.  We should send them to Bernanke and hope for the best.

UPDATE: Thanks Google.  Here's Steve Fairfax of MTechnology making a similar point.  And here's Donald D. Hester and D.L. Brito making a similar point... in 1974!  Do we ever learn?  (Don't answer that.)

UPDATE2: Here's a book on "Economic Dynamics" with a whole section working out a version of control theory applied to a more complicated model.

UPDATE3: I've worked out a numerical example with estimates for the subprime mortgage market here.

Modeling the Subprime Mortgage Market as a Closed Loop Oscillator with only Positive Feedback

Electrical engineers who design analog circuits learn an important rule of thumb: closed loop systems that provide only positive feedback to their inputs can become unstable.  In the diagram at right, when A and B are relatively good amplifiers, the multiplication of their amplifying effect at the input Vin can cause the system to blow up.

The closed loop oscillator with only positive feedback is actually also a useful way to understand what caused the subprime mortgage market bubble, and what could have been done to prevent it.

According to the newspaper accounts, something like this was happening: home buyers were bidding for price (Vin), which was being approved by assessors. Banks were then offering loans based on the assessments to the buyers, and selling the loans to loan-buyers.  Loan-buyers were then bundling the loans into CDOs (amplifier A), and then selling them to bigger loan-buyers, who were then bundling CDOs into CDO^2s (amplifier B).  The bundling permitted for larger-scale buyers of loans to get into the market, which has a multiplying effect on demand for loans, which in turn gave the banks and assessors an incentive to offer loans at higher assessed values regardless of the underlying value of the property.  There was no mechanism for negative feedback on price to enter the closed loop that buyers, assessors, banks, and institutional investors formed.  And when A*B approaches 1, as it will eventually in a system with powerful amplifiers and no negative feedback, the system blows up.

Electrical engineers avoid these kinds of instabilities (usually!) by building negative feedback into the loop -- i.e., by introducing some circuit element that inverts or phase shifts the signal fed back into the input of the circuit so that the signal doesn't just keep growing and growing until it blows up the circuit.

Lee Fennell at the University of Chicago law school has a great suggestion for how we could have built negative feedback into the system: bifurcate on-site and off-site risks associated with homeownership, and make buyers pay separately for these two types of risk.  So for example, a home buyer might be required to buy an insurance contract at the same time they purchase their home, the premium for which is large enough to permit the insurer to pay the home buyer off for a loss in home value should the value of her home later decrease precipitously because of off-site problems in her community (such as factory closings, pollution, or crime).

Now imagine how the same cycle would have worked: the home buyer makes a bid on both the home and the insurance for off-site risk -- the law has to require her to buy both, otherwise this doesn't work.  The home assessor approves an inflated price.  That's still the assessor's incentive because of the demand for mortgages.  But the insurer then raises insurance prices in response to the assessment to offset the larger risk associated with the inflated price.  If the home buyer can pay the increased premium, it's a deal.  If not, the deal falls through, and prices tend to fall back to a level that more accurately reflects the underlying value of the property.

UPDATE: Upon reflection, I realize that the government actually does not have to require homebuyers to buy both the home and the insurance.  In fact, only the insurance-provider and mortgage-provider would have to agree.  This raises other complications (what happens when they're owned by the same entity, e.g.?), but it's useful to see at least that new legislation might not be required.

Fermi and Founders

"There are two possible outcomes: if the result confirms the hypothesis, then you've made a measurement. If the result is contrary to the hypothesis, then you've made a discovery."

- Enrico Fermi

Around Silicon Valley, early-stage venture capitalists tend to agree: invest in teams and markets, not business plans.  Why not business plans?  Because plans have to change, and sometimes drastically, in order for a new business to succeed.

In this sense, the character of a company's founders is much more important than a particular business plan.  The process of thinking through, writing out, and pitching a business plan causes founders to become more committed to their ideas psychologically.  It takes founders of extraordinary character to have both the courage to ignore criticism that is not well-founded, and the humility to listen and learn from criticism that is.  Not coincidentally, it is the same characteristics that make for the best businesses.  Good businesses have the courage to ignore the customers who will never find value in their product or service, but listen and adapt to the needs of the customers who do and will.

Enrico Fermi was one of the last great physicists to do both theory and experiment.  There's pretty much a division of labor between these in physics now.  According to legend, Fermi would wake very early in the morning and work out on paper the expected results of his experiments.  Then he'd go into the lab and produce data until he'd satisfied himself that he had done his calculations correctly.

Is it any wonder that he seemed to have more insights?

Stranded R&D

In 1980, Congress passed the Bayh-Dole Act.  Overnight with its passage, universities and government-funded R&D labs gained a comparative advantage in funding R&D.  Universities and government labs have a cost advantage in that many had already spent tens of billions of dollars setting up research labs for non-commercial purposes, including teaching and curious exploration.  Many scientists and engineers found the prestige of academia, and the increase in professional freedom it promises, a compelling offer.  The result has been a gradual shutting down of corporate R&D labs, and an expansion of industry collaboration with scientists and engineers now employed by universities and government labs.

Many people think of the Bayh-Dole Act as an unmitigated success story.  Several multi-billion dollar technology companies that are now household names (such as Genentech and Google) started in graduate school research labs.  Many inventors are happier in the more collaborative environment that academia offers.  Collaboration is an under-appreciated driver of innovation.

Unfortunately, so far universities have underperformed private benchmarks for the successful transfer of technology.  Despite spending almost an order of magnitude more on R&D (about $50 billion), the AUTM reports only about a factor of two more revenue from R&D (about $2 billion) than does IBM (about $1 billion on about $5 billion in R&D) over an overlapping period from the mid-nineties to the mid-zeroes of the present decade.  Although it is tempting to attribute the difference in returns entirely to the diversion of R&D funding into pure science (an attribution that ought to silence the Bayh-Dole critics who favor pure science), it is important to remember that there was a net inflow of the most productive researchers from industry into academia over the same period of time.  This concentration of the brightest minds of science and engineering within academia would probably have led to a faster increase in returns from R&D if there weren't something else going on.

And there is something else going on.  The costs of licensing and litigation of patents has skyrocketed over the same period of time.  The biggest reason for increasing costs has been the inelastic supply of patent lawyers relative to the exploding demand for their services.  Unlike patent prosecution, which can be done by non-lawyer patent agents and examiners, patent licensing and litigation are services that require a state bar license (and the three years of ABA-accredited law school that this usually requires).  Law firms are struggling to meet demand by increasing starting associate salaries (patent boutiques started the chain reaction in both instances over the past ten years), but the corresponding increase in associate to partner ratios at most law firms (necessary to keep profits-per-partner high and retain top partners) has led to a decline in the quality of services overall.

It is worth noting that many technology transfer offices are staffed by non-lawyer scientists and engineers with formal or informal business training.  Many of these employees are probably undervalued by the legal services market because of their lack of state bar credentials.  Seeing the value, university tech-transfer offices and other government and private firms not constrained by state bar requirements are scooping these types of employees up.  Non-lawyers will probably play a growing role in R&D funding and technology-transfer going forward, even in providing "legal" services.  The investment banks (such as Altitude Capital) and venture capital funds (such as Intellectual Ventures) that have recently entered the secondary market for patents are early signs of this trend.

The result of these macroeconomic trends in R&D is a market in which many startups and smaller companies are realizing only a fraction of the intrinsic value of their R&D.  Technology is stranded in later-stage startups and other small private companies that are not eligible for further venture capital financing, acquisition, or IPO.  Problems in the credit markets and the passage of the Sarbanes-Oxley Act have further exacerbated the problem for these companies in the acquisition and IPO arena.  In effect, the United States is piling up a vast, invisible junkyard of stranded R&D that could be socially valuable if placed into the hands of the right owners.

As the returns to investment in R&D decline, so too do the number of jobs available for researchers outside academia.  This is a problem that is vital to the health of the U.S. economy within its global environment.  If current trends continue, there will be more Ph.D. engineers living in China than in the U.S. by 2010.  The number of U.S. patents issuing to foreign entities is already nearly equal to the number of patents issuing to the U.S.  If the U.S. were to strengthen its patent system, we would be far better positioned than any other nation in the world to bring the power of market-based incentives to bear on the problem of attracting the most talented human capital -- the single most important problem we face in our long-term prospects for economic growth.

People are starting to recognize these problems.  Recently, the Brookings Institute has called for the government to setup a National Innovation Foundation.  But aren't the market-based incentives of a strong patent system a better way for the government to encourage R&D funding?  Although a handful of firms, including Intellectual Ventures, Ocean Tomo, and other new entrants are struggling to meet immediate needs, the inventors and startups most in need cannot afford to hire anyone to answer the lobbyists hired by the large corporations that are net payers of patent licenses (when forced to pay at the end of protracted litigation).

Although the big picture of innovation is so large and complex that it is difficult for most people to understand, the solutions are actually simpler and easier than most would imagine.  First, the patent laws should be reformed in ways that would promote private settlements of disputes over patent infringement rather than litigation.  Some recent changes to the patent law have been beneficial in this regard, and some detrimental.  Unfortunately, the Supreme Court's recent holding in Medimmune makes it harder than ever for inventors to get to the table with large corporations without ending up in litigation.  And after Mercexchange, startups and independent inventors do not have the threat of an injunction to keep licensees at the bargaining table when those startups and inventors have failed to find funding to themselves commercialize the technology.  Neither of these by themselves is fatal.  The threat of injunction was no doubt abused by opportunistic speculators from time to time over the past few decades.  But not in decades has it been more difficult for investors in R&D to see a return through patent licensing.

Second, if the government is going to provide funding to solve these problems, that funding might best be used to lower the barriers to entry for the practice of patent law.  For scientists and engineers, especially those who understand business, the opportunity costs of wages are probably much higher than the costs of a law school education.  Public funding of scholarships for scientists and engineers who intend to study law would over time decrease the transactions costs associated with patent licensing, and gradually decrease the amount spent on litigation as it becomes easier and easier for opposite parties to reach agreement on differing valuations of a technology.

Third, institutional investors should consider allocating a larger share of their funding to hiring more employees for their technology transfer offices now, and later for investing in private equity funds that specialize in R&D investment.  The technology transfer offices are now overwhelmed by the demands on their time in many cases.  As a result, they tend to focus on the biotech and pharmaceutical inventions that are likely to provide the largest payouts, ignoring the many other areas of R&D that could nevertheless have a transformative impact on our society.  In terms of private equity investments, over the short-term the lack of licensing revenue is going to impede the returns for these funds.  But restarting the R&D engine of economic growth is going to require the public and private sectors to work together.

These are complex problems that it will take teamwork to solve.

Update: Silicon Valley never fails to disappoint in its farsightedness.  Jaisen Mathai, Michael Arrington, and Stu Phillips are all groping around the edges of the problem.

Update 2: I was recently asked whether the figures for IBM and AUTM include capital gains from equity.  The answer is no, neither do.  I have seen no evidence and have no reason to believe, however, that the AUTM should be seeing larger returns from equity on its R&D than IBM.  So the larger point about relative efficiency in technology transfer seems still to be sound.

How did the United States get stuck on the peak of a Sombrero?

Consider a ball resting at the center of the sombrero pictured at right.  Poised at the very center of the sombrero and at rest, the ball will not move.  It is in an (unstable) equilibrium.  Nonetheless, if nudged, the ball will roll down into the ring of the sombrero.  The lowest ring around the peak of the sombrero is a stable equilibrium.  Any further nudges will push the ball around the ring a bit; but the ball will end up rolling around the ring from then on.

In this example, physicists would call the direction in which the ball gets nudged an "order parameter."  And here's what makes the order parameter interesting: Starting from the peak of the sombrero, the ball will roll in any direction easily.  But starting from the ring of the sombrero, the ball will tend to roll only along tangents to the ring.  The symmetry of the order parameter is broken as it moves into a new equilibrium.  Thus, broken symmetry signals a new equilibrium.

People, firms, and even whole markets can persist in unstable equilibriums, like the peak of the sombrero.  If it's a big enough sombrero, even relatively big nudges won't move us off the peak.  In addition, from the peak of the sombrero, every direction looks about the same.  So for a long time we might get nudged one way and then nudged back again without ever leaving the peak.

Look at what happens, however, when a group of people start seeing the sombrero rather than its peak alone. That group will start rolling the ball in the same direction.  And note that it doesn't much matter what direction that is.  Any direction will do in getting us off the peak of the sombrero (so long as there isn't another group just as big trying to roll it back the other way).  Once off the peak, things will look very different to everyone, not just the people who can see the whole sombrero.  We might even be able to reach a new consensus: "We'll either go left or right around the ring.  But any other direction doesn't make sense."

When it comes to patent law in the United States, we're at the peak of a sombrero right now.  Here's what I see: We're spending tens of billions of dollars every year on new R&D.  But some of that money is spent redundantly (in ignorance of the prior art), and some of it is completely lost (to patent infringement) because ideas, once disclosed, are impossible to take back.  Trade secret torts and contracts just aren't as good a way to solve these problems.  Turning a blind-eye to patent infringement is bad long-term policy for the United States.  There are already a few other countries that are watching and hoping that we'll drop the ball on this one.  (Or I guess not push the ball far enough in the right direction.)

With the big sombrero in mind, it shouldn't be so hard for everyone to see how strong patent rights are a smart way "to promote the progress of science and the useful arts" through market-based incentives.  Both the Venetians in the 15th Century and our Founding Fathers in 1787 saw the value of patents.  Where did we go astray?

I also gave a brief explanation for the name "Broken Symmetry" in my first post to this blog, but I wanted to revisit the metaphor because it has been so fruitful for me in understanding the organic evolution of markets and firms.