The Efficacy of Groups, Group Selection, and an Ecology of Plans

Richard Wagner posits that the macroeconomy is made up of an ecology of plans; I am sympathetic to his views because this allows for a framework of the economy to be seen as more than just the sum of its parts. This is because macroeconomic action is not just an aggregate of microeconomic action. The exception to this is at the very first encounters where the macro level interactions have yet to be formed (there are no institutions, formal or informal, that dictate behavior). After these are established, the micro transactions rely on the macro economy to enable them while the macro economy can only be perpetuated by the continuance of micro-level human action. One cannot exist without the other once the cycle has been initiated. Though, it is very possible that either one of these may wane in presence of the other.

The mediator between micro and macro action is that of the meso-level. Agents form themselves into groups; in fact, many agents will self-select or be selected into several groups. Families are one such type of these groups, while political parties, friendships, civic organizations, and religious congregations are all examples of groups in which any one agent can simultaneously take part. In both the public and private sphere, what causes these groups to survive throughout more than just one generation? What about an even smaller time scale, like more than a few meetings? What about Black Swan groups like the Bolsheviks? What are the behavioral mechanisms that ensure their continued survival? How does this compare to those who do not propagate for more than one life cycle?

I do believe that in the case of many of these sets, there exists a form of group selection similar to that in the evo-bio literature. Groups evolve a specific set of geno/phenotypic traits that occur at the group level instead of at the individual level. There is some argument in the evo-bio literature, but given that social systems can exhibit increasing returns to scale because of institutions or technology, I intend to sidestep their disagreements until another time. This means that a social system (a collection of groups into a very large group) is able to evolve certain traits that are different from those of another social system. I’ve argued in short essays that these traits may be readily copied by another group because knowledge is non-excludable and nonrival in nature. It has been pointed out to me that this means very little because it depends not on transference of knowledge but on the use of knowledge. I can’t agree more given that most people today have access to the entirety of human knowledge via a device in their pockets, but instead of using it for the advancement of our species, many play video games or feed a dopamine addiction. (This is pot calling the kettle black; I guilty of both of these.)

What I propose is an extension of Dr. Wagner’s hypothesis: the ecology of plans matters at the meso-level as well. Groups have plans. They are a way to lower the transaction costs of many people into a singular goal. Some of these groups seek domination of an entire economic system, others simply want to enjoy the fellowship of their members. I think I’ve mentioned Ostrom’s rules on common pool resources; these extend to efficacy of groups. In future posts, I hope to work out some agent based modelling of this.

Sidebar for myself: Demand will eventually create a supply through a variety of mechanisms and processes that necessitate the actions of entrepreneurial agents, but the converse is not true.

Ostrom, CPRs, and the Efficacy of Groups

Elinor Ostrom’s work in her study of common pool resources is paramount to my ideas. Ostrom defined the conditions in the form of eight core design principles:

  1. Clearly defined boundaries
  2. Proportional equivalence between benefits and costs
  3. Collective choice arrangements
  4. Monitoring
  5. Graduated sanctions
  6. Fast and fair conflict resolution
  7. Local autonomy
  8. Appropriate relations with other tiers of rule-making authority

These design principles are what is necessary for group survival and success to take place. Ostrom also defines success, for institutions: institutions are successful when they enable agents within the system to engage in productive outcomes despite the ever-present temptations of shirking and free-riding. I think this focus on “productive outcomes” could lay the basis of future system effectiveness/ efficiency, but that still leaves and immense amount of gray area to be resolved.

Using the CPR framework, the Soviet Union was destined to fail because its scores on conditions 2, 3, 6,7, and 8 were subpar. I would further claim that the USSR was doomed to failure (by productive outcomes) because it failed to meet certain criteria applied to socio-ecological systems. Namely, it failed to create a coherent system that allowed for interaction in a resilient and sustained manner. Furthermore, it failed to allow for a dynamic economy that allowed for continuous adaptation. Central planning and mono-centricity are anathema to adaptivity at the micro and meso levels.

[1] Wilson, Ostrom, and Cox. “Generalizing the core design principles for the efficacy of groups.” Journal of Economic Behavior & Organization, 90S (2013) S21–S32. 2012.

[2] Ostrom, Elinor. Governing the Commons. Cambridge, 2018.

Krugman (gasp!) talks on evolutionary economics and biology

Okay, okay, okay… It was at the European Association for Evolutionary Political Economy in November of 1996 (which is before the blogging Krugman we all know and love). In this talk, Krugman offers some bridges in between the two fields, finds common ground, and even suggests that we use the same methodologies to accomplish our studies. Which I think is appropriate given that the variables studied in both of our fields are not as concrete as physics but can be infinitely more complex (and thus, according to Michael Shermer, more difficult).

Here are some notes:

Krugman offers a four-part approach to economics:

  1. Economics is about what individuals do.
  2. Individuals are self-interested.
  3. The individuals are intelligent.
  4. The primary focus of these individuals is their interactions.

The primary difference between evo-bios and econs is that evo-bios don’t assume requirement number (3). Agents in evo-bios can be myopic. My own interjection here is that agents need not seem rational to the outside observer, only that they are rational insofar as their rationality is bounded.

Reading John Maynard Smith’s (not Keynes’) “Evolutionary Genetics” is probably a good start to recognizing the parallels between the fields.

The differences between evo-econs and neoclassicals is that evo-econs want to get away from maximization and equilibria. I think the latter is a recurring theme in heterodox economics, especially that of Austrian which lends some bias into my formal training. Nonetheless, I often argue that the economy is always trending towards an ever-changing equilibrium; therefore, it is always in disequilibrium. If we ever reached equilibrium, either communism has succeeded or the human race is extinct… possibly both.

Krugman points to Leslie Orgel’s Second Law: “Evolution is smarter than you are.” Maybe so, if only in that evolution is an organic process and there is no way that any one person can predict the eventual outcomes of these marginal changes over time. We can’t necessarily know a priori what is and is not efficient. Often we assume whatever outcome is reached is inherently efficient. Also, evo-bios look at evolution from a stationary perspective, and not in a dynamic shift that is presently occurring. This is not so much unlike certain models in economic growth theory.

The most useful concept in this talk is that of “Evolutionary Stable Strategies.” These are the strategies that any one agent should follow given the strategies everyone else is following. Krugman points to equilibrium, but I think more towards game theory (both have equilibria, but game theory allows for probability of repeated games).

In conclusion, Krugman offers sage advice on what econs can learn from evo-bios: “that models are metaphors, and that we should use them, not the other way around.” Many economists fully believe in their mechanisms versus acknowledging them for what they are, merely useful fictions that allow us to simplify the complexity that is human action.

 

Towards a new kind of macroeconomics

For much of my undergraduate and early graduate career, I considered macroeconomics to be an imaginary field of study. After all, macro is just a scaled up version of micro economic action, right? In fact, this is often remarked as truth by many of my peers and professors. Macro is make-believe. How could it not be after the 2007-09 financial crisis? Everything we had learned prior to that point seemed to go out the window.

Since that time, there has been a resurgence in the study of graduate level economics. I think this is probably a net positive, more eyes to acres as Wendell Berry would say. But with growth in economists also comes more variety in ideas. While studying for my macro qualifying exams last summer, I began early and devoted 20+ hours each week to studying. The macro portion was by far the more difficult of our exams. During this time, two things happened: 1) I saw how the models and ideas of macro theory met at various intersections and 2) I read Richard Wagner’s pieces on macro as an ecology of plans and Viennese Kaleidics. I wont reiterate these papers here, but it gave me a perspective on macroeconomics which I had yet to see.

Macro is more than the sum of its parts. It is not simply an aggregation of micro actions, but those micro actions affect the macro environment which in turn affects the micro actions. This is a self-perpetuating feedback loop. Unlike all of the early growth models, everything in the macro economy is endogenous (except for the a priori system parameters).

We’re on the cusp of a brave new world of macro theory. Where this goes depends much on the current generation of economists. I am looking to follow a system theoretic and make use of agent modelling. My colleagues have suggested OEE and other forms of advanced techniques; I haven’t settled on one yet, but I’ve spent some time looking into the various programs and software.

In closing, I’ll leave you with this quote from Andrew G. Haldane at his 2016 GLS Shackle address:

“Although (the recent) crisis in economics is a threat for some, for others it is an opportunity — an opportunity to make a great leap forward, as Keynes did in the 1930s. For the students in this room, there is the chance to rethink economics with as clean a sheet of paper as you are ever likely to find. That is perhaps why the numbers of students applying to study economics has shot up over recent years. This is one of the silver linings of the crisis. No discipline could ask for a better endowment. But seizing this opportunity requires a re-examination of the contours of economics and an exploration of some new pathways.”

Laws of Demand and Diminishing Marginal Returns Outside Economics

Yesterday, I posted on a synthesis between economics and the other sciences. In this blog post, I provide a couple examples of such theoretical crossover. This is from a current working paper of mine on the endogeneity of social systems.

The laws governing the physical universe are constant through time and space; however, they must be discovered by someone to be brought into the set of scientific theory and knowledge recognized by humanity. Likewise, economic laws are constant throughout society, but it takes observations from people to draw these theories out from the interactions of others. Economic laws are inherent to the universe; they are de facto a priori synthetic. The laws of demand are known to be constant and everywhere existent, much like the laws of the positive sciences. It does not take transactions amongst people for the laws of economic to become evident, notably the first law of demand can be seen in biology, chemistry, and physics.

For instance, the law of demand has been seen throughout the biological systems as animals have evolved to display certain traits. The male peacock, for example, has a wonderful plume of tail feathers for which he uses to attract mates. The larger his plume, the more attractive he becomes but at a price: he is more visible to predators. This form of tradeoff is seen throughout the animal kingdom, but there is a correlation with increased expression and increased vulnerability to predators. As can be easily identified, there are more animals with nominal characteristics within any given population and increasingly less as phenotype characteristics become more flamboyant. The quantity of phenotypes that make an animal attractive to mates decreases as the resulting characteristics make the more easily seen by predators.

In the physical sciences, the law of diminishing returns can be seen through the processes of chemical reactions and limiting reagents. In the process of creating a fire, three factors are needed: heat, fuel, and oxygen; however, in a contained environment, an increase in any one of these could lead suboptimal reaction if the other factors are held ceteris paribus. If there is too much fuel for the fire to consume, then the oxygen in the environment becomes the limiting reagent: the reactant that is used up first in a chemical reaction and determines the amount of product that can be formed in a reaction. If the oxygen in the environment becomes too abundant, the fire will begin to burn faster. The chemical reaction may happen so quickly all the fuel becomes used and there is leftover oxygen. If the heat in this scenario becomes too high, the risk of changing the reaction from a fire to combustion increases. The law of diminishing returns is a priori to economic and societal systems.

Tilson, William. “Societal Actions as Outcomes of an Endogenous System: Economic Theory and Policy: Autonomous or Caused?” Working Paper, 2019.

Bridging the physical and social sciences

Throughout the past, biology has borrowed much from economics. I think it’s time that economics begins to take back some ground. I’d argue that economics and biology have more in common than you’d think. We both deal with agents who are constrained in their environments and are subject to larger systems whose rules may not be fully known. Agents, animals, cells, and DNA all have similarities in how they engage with the world. 1) They’re subject to the law of demand: price and quantity demanded of any good and service are inversely related to each other. 2) They must follow diminishing marginal returns. 3) They all abide in a world of emergent behaviors and outcomes; some of these may take hundreds or more generations to manifest themselves.

Given these constraints, it can be followed that outcomes of this system can be described by other outcomes of the same system. Most notably, there should be patterns of behavior and design that transcends the individual agents within the system, no matter how large or small they might be. From this point, I think that the sciences, both social and physical, should be able to share methods and ideas. I think many of the truths in our would can be found at the intersection of these ideas.

In my current research, I’m looking to create a synthesis between the rules provided by evolutionary biology and the human action from the micro scale to the macro phenomenon. Many of these patterns will reside in the meso-level, a place in between micro and macro. Note that the feedback loops will reside at all levels of the system.

I’m going to take a moment here, while I am in class to give my impression on Charlie Plott’s fundamental equation. In it, he says

preferences * institutions * physical possibilities = outcomes.

Is there anything wrong with this attempt to constrain the outcomes of human actions? I would say yes. The biggest issue resides in an engineer-like observation of human action. This equation steps outside the system, when it actually unable to do so. Furthermore, all of these are self-reinforcing or self-removing. The equation is entirely endogenous at both the system level and the agent level. In a Robinson Crusoe situation, at least on of these variables need not exist. Additionally, where does choice and subsequently action occur? In this line of thinking, there is little room for the adaptation that happens in reality.

On a side note, I recently listened to a podcast on the ideas purported by Glen Weyl where he claims that the study of economics has a difficult time explaining increasing returns to scale. Much of human social behavior exhibits this, not to mention digital technologies. Does economics explain this? I’ll link to another blog on this later.

Farms or Cities: A Chicken and Egg Problem

I am only a few pages into Jane Jacobs’ book The Economy of Cities and she posits something I have yet to hear in any of my time learning economics or philosophy: cities are not made possible by the agricultural economy but agricultural economies are made possible by the economies of cities. I think most of the profession, and many farmers, would argue against that thought. To them, cities must arise out of the foundations of agrarian economies. For the first cities, that is certainly true. What about later cities?

If it wasn’t for cities, there could be no expansion of farming technologies. There could be no global exchange of produce. Without cities, farms would have fewer people to which they could sell their goods.  I am not against farming; in fact, I think transitioning to many more, smaller farms instead of the mega-factory farms would be a net good to our society. However, this does not detract from the case presented by Jacobs; farms need cities to advance their trade and keep it viable.

But let’s face it, cities are unable to produce enough food to keep their own fed. They rely on massive harvests from farms the world over. Vertical farming has recently become a fad, but upon closer inspection, vertical farms can only produce leafy greens and vegetables with low-caloric value. A city cannot be sustained on vertical farms, nor can a farm be maintained over multiple generations without plenty of customers.

I don’t think Jacobs is entirely correct in her assumption. Cities need farms and farms need cities. There is a feedback loop here. Farms feed innovation and human interaction in cites; this, in turn, brings innovation back to the farm and allows it to profit from these interactions. The city is then able to have increased interaction due to increased production from the farms.

One issue that arises is that massive fixed costs undertaken by some farmers attempting to compete with larger farms who are able to dilute the costs across their investments. For the average non-factory farmer, this level of capital expense may be unsustainable. What does competition look like in the farming industry? I imagine the margins are tight.