Macroeconomics Could Benefit From Complexity

In chaos versus complexity, Greg Fisher states (my emphasis):

Dynamic networks – or complex systems – are very different to the systems studied in Chaos Theory.  They contain a number of constituent parts (“agents”) that interact with and adapt to each other over time.  Perhaps the most important feature of complex systems, which is a key differentiator from chaotic systems, is the concept of emergence.  Emergence “breaks” the idea of determinism because it means the outcome of some interaction can be inherently unpredictable.  In large systems, macro features often emerge that cannot be traced back to any particular event or agent.

To understand the concept of emergence further, we can look at water.  We know the qualities of oxygen atoms and we know the qualities of hydrogen atoms, so presumably we can determine the qualities of H20, water?  Actually we cannot.  Really, however freakishly this might sound, we cannot.  It turns out that we are familiar with the qualities of water only because we have observed them empirically.  The properties of water are emergent.  If any reader wished to delve further in to this, I would recommend Stuart Kauffman’s book Re-Inventing the Sacred.  In this book, Kauffman wrote that

“it is something of a quiet scandal that physicists have largely given up trying to reason ‘upward’ from the ultimate physical laws to larger-scale events in the universe”

The reason for the inability to reason ‘upwards’ from hydrogen and oxygen to water is because the properties of water are emergent and therefore indeterminable from the properties of the constituent atoms.

First of all, I’ve read Kauffman’s book and would personally recommend it to anyone interested in physics, complexity and/or emergence. Second, the difference between chaos and complexity, although it may appear subtle, highlights a critical concern for the study and modeling of complex systems. The macro economy is one of these complex systems in which “the outcome of some interaction can be inherently unpredictable.”
Peter Lewin moves this discussion into the realm of economic modeling with his (Complex?) Thoughts on Heterogeneity and Complexity; Quality and Quantity (my emphasis):

Returning to the theme of the relationship between quantity and quality, quantitative modeling works when both the independent and dependent variables are meaningful, identifiable quantifiable categories that can be causally related. The model ‘works’ then in the sense of providing quantitative predictions. The inputs and outputs can be described in quantitative terms. But, when the outcome of the process described by the model is a new (novel) category of things, no such quantitative prediction is possible. Ambiguity in the type and number of categories in any system destroys the ability to meaningfully describe that system exclusively in terms of quantities. We have a sense then of the effects of heterogeneity. Variation applies to quantitative range. Heterogeneity (variety) applies to qualitative (categorical) range. Diversity incorporates both, but they are significantly different. Heterogeneity may not be necessary for complexity, but heterogeneity does militate in its favor. For example, compound interaction between quantitative variables (categories) can be an important characteristic of complex systems, but complex systems are likely to result from substantial heterogeneity, especially where heterogeneity is open-ended, in the sense that the set of all possible categories of things is unknown and unknowable.  

Heterogeneity rules out aggregation, which, in turn, rules out quantitative prediction and control, but certainly does not rule out the type of ‘pattern prediction’ of which Hayek spoke. In fact, erroneously treating heterogeneous capital as though it were a quantifiable magnitude has led to misunderstandings and policy-errors, such as the those associated with the connection between investment and interest rates - errors that could have been avoided with a better understanding of capital heterogeneity and its effects. The capital-structure is complex, but it is intelligible. We can understand and describe in qualitative (abstract) terms how it works and render judgment on economic policies that affect it. And, as a result of Hayek’s insights into complex phenomena, we have an enhanced appreciation of what is involved.

Economics is slowly moving in the direction of recognizing that heterogeneity not only exists in the real world, but is critical to understanding how the system works. Unfortunately, we are not yet at the point where most economists accept the inherent inability to quantitatively forecast macroeconomic outcomes and render accurate policy proposals from those conclusions. Many physicists now accept the consequences of and are incorporating complexity into models of various systems. Economics and economic policy would benefit greatly from moving in the same direction.  

Network Models Can Restore Emergence in Economics

Currently active on my kindle is Positive Linking: How Networks Can Revolutionise the World
by Paul Ormerod. For a brief background of how I came upon this subject, my most recent interest in economics began a couple years back when I began reading classic works of Hayek and Keynes, among others. Probably surprising to many, I found the work of both these giants in the field to offer timeless insights about the macroeconomy that had seemingly been lost leading up to the financial crisis. More specifically, I was curious about the broader ideas of uncertainty and emergence that each touches on, though in different manners. Allowing my reading selections to follow a random path, I stumbled upon books in theoretical and particle physics discussing those intriguing subjects in the context of chaos theory and network effects. Ormerod’s book, among other things, is trying to encourage mainstream economics to re-incorporate these lost ideals from the past with new lessons from physics and other social sciences.

Aside from Ormerod, there are numerous others simultaneously working to construct new models of the economy that include these areas of research. One of those is Steve Bannister, at Naked Keynesianism, who offers this conclusion to a critique of the Lucas critique:

I propose two things to restore the dominating importance of emergent macro properties on economic behavior. One is a recommitment to econometric modelling. Ever increasing data and increasingly better tools will continually improve modelling and forecasting results.

The other is a methodology that is vastly underused in economics, but widely used in various other sciences: network system analysis based on the mathematical theory of graphs. These methods lets us directly measure and model emergent dynamic behaviors from groups, like the individuals in an economy. No added up methodological individualism required; no agent-based model needed. Observe, model, and predict directly at the macro level.

While I believe empirical models, properly done, are fundamental to understanding and policy, network models provide us with a dynamic theory, emergent macro behaviors, that  support our correct Keynesian beliefs that it is the macro foundations of micro behavior that matter, not the other Lucasian way around.  

Points of Public Interest

1. Why Limiting Itemized Deductions (Still) Makes Sense - My former professor, Diane Lim Rogers, offers her support for a proposal to limit itemized deductions to a 15 percent rate. This policy will simultaneously increase the progressive nature of income taxes, substantially reduce total tax expenditures and raise revenue.
2. The Fed Is Misleading Congress About Europe - Warren Mosler, a founding member of Modern Monetary Theory, argues that the Fed’s dollar swap lines are unsecured lending and should therefore be the responsibility of Congress.
3. Philip Pilkington: Is QE/ZIRP Killing Demand? - Pilkington describes the counterproductive efforts of Fed policy. Milton Friedman also believed ZIRP (zero interest rate policy) would restrict demand as I outlined in Deflationary Monetary Policy.
4. The Liberalism of Classical Liberalism - Peter Boettke tries to correct some typical misrepresentations of classical liberalism with a good dose of historical background.
5. Show Me the Daylight 'twixt Sanction and Tariff - Samuel Wilson considers recent trade sanctions against Iran and China, and why the two are viewed in different lights by Americans.
6. The Future of Economics - Steve Keen, a leading post-Keynesian, makes a case for incorporating disequilibrium, dynamic modeling and emergent properties into the core of future economics.
7. The European Crisis Deepen - Peter Boone and Simon Johnson, former IMF Chief, explain why current optimism is likely unwarranted and how the realistic end may include a break-up of the Eurozone.

Quote of the Week

...is from Russell Robert’s 2009 book  The Price of Everything: A Parable of Possibility and Prosperity

“Genetic mutation is random. Natural selection accepts the good changes and rejects the bad ones. Economic evolution isn’t random. Changes in products aren’t random. The knowledge and innovation come from entrepreneurs trying to anticipate what people want and what will survive in the marketplace. That makes it more focused than biological evolution. And you get progress, not just survival.”

In this novel, Roberts masterfully portrays the emergent order of our world and economics through a dialogue between a student and teacher. The story is very compelling and inspiring for anyone with visions of becoming a teacher. A great read for anyone with even a remote interest in economics.

Points of Public Interest

1. Money, credit and inflation - Sean Corrigan explains the difference between money and credit, highlighting the different nature of banks and individuals in creating credit. An often forgotten aspect of our current monetary system is that individual banks can create credit (which can turn into money) irrespective of Fed or Treasury policy. This unique ability generates the potential for inflationary and deflationary forces in the money supply outside of the federal government’s control.
2. Death by Wealth Tax - Richard Epstein argues against the proposal for a wealth tax on assets.
3. Trials and Errors: Why Science Is Failing Us - Jonah Lehrer details some failings in medicine stemming from the incorrect, basic “assumption—that understanding a system’s constituent parts means we also understand the causes within the system.” As Lehrer notes, centuries ago David Hume recognized a human desire to view the appearance of causation as an actual fact, rather than “fiction that helps us make sense of facts.” (HT: Russ Roberts)
4. Debt, Deficits, and Modern Monetary Theory - Bill Mitchell, a founding member of Modern Monetary Theory (MMT), outlines the difference between MMT and mainstream economics. These differing conceptions about public debts and very important to the public policy battles in the news today. (HT: Neil Wilson)
5. Peter Boettke on Austrian Economics - “Austrians want to talk about things like dispersed knowledge, heterogeneity, uncertainty – not just risk, but real uncertainty – and institutions, how institutions arise to allow us to cope with our ignorance and our uncertainty and to ameliorate the frictions that exist in the world.” Peter Boettke discusses contributions of Austrian economics and five books to read on the subject.