It is more than eight years since the beginning of the global financial crisis. Although the world economy came back from the abyss, it never fully recovered. Now, latest data from across the world suggests that we may be tethering at the edge of another downturn. So why have negative interest rates, dirt-cheap commodities and waves of central bank liquidity failed to restore sustained growth?

There are a number of interrelated factors that have been blamed: excess capacity, savings glut, demographics, indebtedness and so on. However, a large part of the blame must lie with policymakers and professional economists who have systematically failed to anticipate breakdowns but continue to advocate measures that have already been proved ineffective.

This line of thinking inevitably manifests itself in large-scale Computable General Equilibrium (CGE) models. Almost all policymaking institutions spend enormous resources building them. This is inexplicable given that CGE models have never been able to predict a major economic event. The problem is that economies are not Victorian machines and no amount of refining the CGE framework will get us better results.

The Dog & the Frisbee

An alternative framework is to rethink economies as Complex Adaptive Systems (CAS), which are made up of large numbers of independent agents that are constantly interacting with each other and evolving. Examples include ecological systems, cities, financial markets, the English language and, arguably, Hinduism. Note that CASs do not follow the Newtonian logic of CGE and have no inherent tendency to gravitate to a stable equilibrium. They also suffer from the Law of Unintended Consequences and can respond to the same stimulus in multiple ways. This means that managing such systems is less about pre-planning and more about constant monitoring, feedback and flexible adjustment.

Let me contrast the CAS and CGE frameworks through an example popularised by Andrew Haldane of the Bank of England. Say, a man is throwing a Frisbee for his dog to catch. If the dog was a CGE proponent, it would model the shape of the Frisbee, the man’s muscle strength, wind speed, gravity and so on. Even if the dog is a genius, however, it would probably still fail to catch the Frisbee because there are just too many moving parts to model.

In reality, the average dog has no problem catching the Frisbee because all it does is closely watch the flying object and constantly adjust its own position, i.e., monitor, feedback, adapt. This is the CAS approach.

Transparency & Flexibility

So, how would this apply to the current economic predicament? First of all, let us be clear that there is no such thing as an ‘equilibrium’ growth rate to which the world economy naturally gravitates. Similarly, all periods of economic growth in history have been accompanied by large global imbalances. A return to so-called balance is not obviously a good thing. There is also no ‘neutral’ interest rate to which the US Federal Reserve need revert. So, the Fed should act on the best available data and not be swayed by some preconceived notion of normality.

Second, it is far from obvious that even ‘helicopter money’ would revive demand. Recipients of such cash injections are just as likely to save it as spend it (especially when deflation is increasing the value of cash holdings).

Instead, the increase in the central bank’s liabilities could have many unintended consequences that could come back to bite at an inconvenient time in the future. Third, central banks and other regulators need to take a very different approach towards regulating the financial system. Conventional thinking is that increasing regulation always reduces the vulnerability to crises. However, banks were heavily regulated even before 2007 and that did not prevent the crisis.

Why should ever more regulations help? The imposition of increasingly cumbersome rules is making financial systems inflexible and less transparent. The CAS approach would suggest that this makes the banking system more vulnerable, not less.

Indeed, the new complicated Basel-related regulations are likely to have unintended consequences that may cause the next crisis. It’s better to have simple regulations combined with active supervision. Policymakers must realise that regulation and supervision are different things, and there is a trade-off between them. To conclude, the key implication of the CAS framework is that a complex world cannot be managed by increasing complexity but through simplicity and flexibility. Since there is no equilibrium, it’s all about triggering virtuous cycles and then managing the distortions that necessarily accompany them.