As the world evolves and tools to study human behaviour become more sophisticated, traditional economic models are becoming increasingly outmoded.
Why neo-classical economics is limited
Many people working in the field of neo-economics and finance sincerely believe they’re engaging in a scientific process.
Neo-economics uses increasingly sophisticated mathematical frameworks and formulas to study issues such as supply, demand and scarcity. Its core assumption is that people are rational in their decision-making.
This has led many practitioners to believe that resource allocation and transactional exchange can be codified in known rules.
However, if we were to accept that economies – and the people that drive them - are like machines, it follows that we’d view economic problems as essentially mathematical problems. This would mean that managing the economy and maintaining a general equilibrium would be a question of devising statistical equations. Any deviations from our equilibrium would be slight frictions or bumps in the road that neo-economists would seek to remove.
The problem is that these frictions that disrupt the smooth operation of the neo-economists’ machines are us - human beings.
Neo-economics is a sophisticated discipline and it does offer one way to approach problems of scarcity. However, unlike physics or engineering, it is not a science. Nor does it apply any scientific method or principle with any rigour.
This is one reason why most neo-classical economic models are unable to describe reality accurately or convincingly.
How did we get here?
Looking back to the 19th century and the development of classical economics, the most prominent figures of the day were, by background, lawyers, journalists and clergymen. People such as David Hume, John Stuart Mill and David Ricardo were intellectuals who regarded human behaviour as integral to economics.
In the early part of the 20th century and the emergence of increasingly sophisticated capital markets, academics began to formalise the study of economics. They introduced tools developed by mathematicians and physicists. However, in the pursuit of scientific credibility, these economic models adopted assumptions that any student of human behaviour would dismiss as utterly unreasonable.
Which is why, even now, the ability of economics to predict major events is questionable. Since World War Two, mainstream economic commentators, including the IMF and the World Bank, have missed almost every major crisis and crash to afflict every major economy.
The hidden assumptions of neo-classical economics
Central to economists’ models of individual behaviour is the concept of utility and the associated belief that satisfaction is the prime driver of an individual’s choices.
Furthermore, to make the mathematics in their models easy to work with, neo-classical economists assume that:
- We inhabit a world of individual, economic actors;
- These actors engage in rational transactions to maximise utility; and
- Collectively, these transactions satisfy the actors’ preferences in an environment of perfect information and complete trust.
As anyone who works at the coalface of their organisation will recognise, this scenario occurs extremely rarely, if ever, in the real world. A consequence of this is that when people’s economic behaviour changes and creates new challenges for an organisation or a society, the economists’ response is to throw money at it. A former Director General of CERN, the European Organisation for Nuclear Research, noted, ‘When I ask economists how to solve a problem, their only answers are fining people or bribing people’.
In short, neo-classical economics represents an extremely narrow understanding of people and organisations. Across business in general, and finance in particular, it has become a substitute for an adequate understanding of human behaviour.
And it has reached a point where many organisations are designing services and experiences for this figurative, uber-rational human. The species even has a name: homo economicus.
How homo economicus works
Most people regard the human brain as an advanced supercomputer. They see their senses as advanced receptors that absorb inputs from the world - and their conscious mind as the processor of these inputs. Once processed, the information is used to make rational decisions.
However, significant work by neuroscientists and cognitive psychologists shows that this notion of our capability to observe a fixed reality is largely a delusion.
Broadband input v narrowband processing
Staying with the supercomputer analogy, neuroscientists estimate that our senses, mainly our eyes, take in around 11 megabytes of information per second. Our conscious mind is able to cope with approximately 60 kilobytes per second.
So, we absorb information via broadband, yet process it using narrowband.
The result is a constant battle between precision and efficiency. To cope with the overwhelming sensory input, the brain seeks to compress and dump data and correct what it sees are errors.
The upshot of this is that, most of the time, we see with our brains, not our eyes. We build mental models from our experiences of how the world should work, and use these to fill gaps and take short-cuts.
So, rather than believe what we see, we see what we believe. In fact, behavioural economists have identified over 100 biases or psychological errors that humans are prone to when making decisions. We look at the top seven of these in our article ‘Decision-making biases identified by behavioural economics’.
System 1 vs system 2
The brain is the most metabolically expensive tissue in the human body. It takes up just 3% of tissue mass yet accounts for around 20% of the body’s energy consumption.
In the battle between precision and efficiency, human evolution determined that efforts to boost decision-making precision outweighed the benefits in most situations. However, in our modern, information-filled world, this model consistently produces cognitive errors.
The prominent behavioural economist Daniel Kahneman has popularised the notion of the brains having these two modes of thinking:
- System 1 – fast, automatic processing that reacts swiftly to danger. Driven by simplicity, it’s prone to blind spots and systematic biases; and
- System 2 – slow, deliberate cognitive processing for solving intricate challenges such as mathematical equations. It performs poorly when overwhelmed.
Cognitive psychologist Jonathan Haidt notes that the relation between these two systems of thinking is that of a rider (System 2) on an obstinate elephant (System 1).
The rider believes it is directing the elephant, however this is a fallacy. It is, in fact retrospectively rationalising the direction the elephant has decided on.
Another consequence of this relationship is that most of us don’t have introspective access to the areas of our brains where preferences are formed and decisions are made.
Most cognitive errors occur because System 1 is in charge when we believe System 2 should be in charge.
Behavioural economics - an alternative approach
Because the outcomes of the neo-classical economics boil down to fining or bribing people, the model limits itself to just one of the many levers that we can use to change people’s behaviour: self-interest.
Behavioural economists, by contrast, use knowledge from other fields which have studied humans in real depth. They employ tools developed in behavioural psychology, evolutionary biology and neuroscience.
Behavioural economists also take a very different view of organisations to that of neo-classical economists. They believe organisations are complex, dynamic systems that are highly sensitive to relatively small changes when applied in the right places. Accordingly, they believe that to assess an organisation by applying methods drawn from Newtonian mechanics is deeply misguided.
Ultimately, behavioural economists recognise that living, thinking creatures and manufactured, programmed objects behave very differently.
Or as the essayist, scholar, statistician and former trader and risk analyst, Nassim Nicholas Taleb so memorably put it, ‘a cat is not a washing machine’.
Conclusion
Since the early part of the 20th century, the neo-classical economic model has been the basis for forecasting global economic activity. Organisations have used it to design products and services and governments have used it to shape economies. However, a major flaw of neo-classical economics is its assumption that human behaviour is rational. For this reason, the more reliable behavioural economics uses tools developed in fields such as behavioural psychology, evolutionary biology and neuroscience.