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.”