Economics: on the chopping block

Hayek’s 1974 “mea culpa”

Human understanding of economics isn’t great.?

Despite some pivotal moments and important insights, modern economics has failed to effectively describe or explain the empirical reality, or predict macro events.???

In 1974, the economist Friedrich August von Hayek was awarded the Nobel Prize in Economics. His customary laureate lecture was shockingly titled: “The Pretence of Knowledge ”. In a scathing address, Hayek laid out a detailed indictment of his profession, its arrogance and systemic failures. Remember, the time is December 1974 -?the deepest point of the 1973-75 recession. Inflation in the US is above 11% and in the UK above 16%.

He starts off quite strong:?

“The particular occasion of this lecture, combined with the chief practical problem which economists have to face today, have made the choice of its topic almost inevitable. On the one hand the still recent establishment of the Nobel Memorial Prize in Economic Science marks a significant step in the process by which, in the opinion of the general public, Economics has been conceded some of the dignity and prestige of the physical sciences. On the other hand, the economists are at this moment called upon to say how to extricate the free world from the serious threat of accelerating inflation which, it must be admitted, has been brought about by policies which the majority of economists recommended and even urged governments to pursue. We have indeed at the moment little cause for pride: as a profession we have made a mess of things.”

Hayek points out a systemic source of failure - the concede that economics is on par with hard sciences. He claims that social sciences, including economics, are Complex Systems [he does not directly refer to this field, but he implies it]. Complexity entails a large number of variables and sensitivity to boundary conditions, i.e., small changes in input can shift a complex system from one equilibrium to another (e.g., growth to recession). Since in 1974 there was no way to even identify all the affecting variables, let alone measure them, economists simply ignored them. Here’s how Hayek put it:??

“This means that to entrust to science – or to deliberate control according to scientific principles – more than scientific method can achieve may have deplorable effects.”

[Indeed, Asimov’s Psychohistory, although conceived in the 1950s, is still in our future (perhaps closer than it may seem), and in 1974 would definitely seem unattainable.]?

Lastly, Hayek calls out himself and his peers for arrogance, in an astounding “mea culpa”:

“If we are to safeguard the reputation of science, and to prevent the arrogation of knowledge based on a superficial similarity of procedure with that of the physical sciences, much effort will have to be directed toward debunking such arrogations, some of which have by now become the vested interests of established university departments. We cannot be grateful enough to such modern philosophers of science as Sir Karl Popper for giving us a test by which we can distinguish between what we may accept as scientific and what not – a test which I am sure some doctrines now widely accepted as scientific would not pass.”

The allusion to Popper is savage! He is rejecting the attribution of science to economics [which is ironic given the full name of the prize he had just won: the Nobel Memorial Prize in Economic Sciences.] Moreover, he implies that economics is unfalsifiable and therefore comparable to astrology. Eek.?

The lecture ends on an ominous note:?

“[man] will have to learn that in this, as in all other fields where essential complexity of an organized kind prevails, he cannot acquire the full knowledge which would make mastery of the events possible. He will therefore have to use what knowledge he can achieve, not to shape the results as the craftsman shapes his handiwork [!], but rather to cultivate a growth by providing the appropriate environment, in the manner in which the gardener does this for his plants… The recognition of the insuperable limits to his knowledge ought indeed to teach the student of society a lesson of humility which should guard him against becoming an accomplice in men’s fatal striving to control society – a striving which makes him not only a tyrant over his fellows, but which may well make him the destroyer of a civilization…”

Damn!

Nobody ever got fired for not predicting a recession

Where were we? Ah yes, our deficient understanding of economics. In 2001 Prakash Loungani, an economist from the International Monetary Fund, published a survey of the accuracy of economic forecasts in the 1990s. He reached two main conclusions. The first was a severe lack of diversity in the predictions. The second was that they were consistently wrong, or as he wrote: “The record of failure to predict recessions is virtually unblemished.”

In 2014 the Financial Times published a piece titled: “An astonishing record – of complete failure ”. In it, they follow up on the work of Loungani, now with a colleague, Hites Ahir. The key facts reported are as follows:?

• In the wake of the 2007-8 financial Loungani and Ahir surveyed 77 countries.
• By 2009, 49 were in recession.
• In a report published in April 2008 - with the financial crisis, a fully established fact - economists had not predicted a single one of these recessions. Not a single one. This is not about being myopic. The crisis was in full swing.?
• This unanimous position of “no recession on the horizon” was unchanged by September 2008.
• A year later, in September 2009, while 49 countries were already in recession, economists predicted (I kid you not) 54 out of 49.
• Same thing happened in 2011-12, with zero recession predictions in the spring of 2011, two recessions predicted by September 2011, and 15 actually happening in 2012.??
• Comparing these predictions from the private sector to those made by multinational organizations such as the IMF showed no significant difference. They were similarly bad.?

Why are economists so bad at predicting recessions? Well, as stated above, there is the issue of complexity and methodology. However, those would not account for such a consistent failure rate. Cognitive bias, would. In this case, it’s Loss Aversion. The term was coined by Kahneman and Tversky (1979). It is the human tendency to prefer avoiding loss over gaining identical profit. The blindness to recessions is an example of loss aversion happening on two separate levels. The first relates to the people asking for the prediction. For example government officials, politicians and leaders, and in a way the general public. Our aversion to loss is so deep that we would naturally doubt such predictions. This leads to the second instance of the bias which relates to incentive. We prefer a “no recession on the horizon” prediction over one that predicts prosperity, [and surely over one that actually predicts a recession.] Therefore, predicting a negative future (e.g., recession) and getting it wrong, is more likely to discredit an economist’s reputation. In short, you are far less likely to be fired over predicting growth and getting it wrong.?

We are but simple creatures.?

Milking a male-goat over a sieve

Classical Economics is commonly attributed to Adam Smith [An Inquiry into the Nature and Causes of the Wealth of Nations (1776)]. It is based on the assumption of rationality. Adam Smith is considered the progenitor of the Rational Choice Theory. This has been the case for nearly 200 years. The first “attack” on the rational choice theory came in 1957, by Herbert Simon, when he coined the term ‘bounded rationality’. Simon suggested we replace the perfect rationality assumptions with a different set of assumptions. One that is bound by human cognitive limitations. These new assumptions take into account access to information, or partial information, computational resources available for evaluation and analysis and other normative behaviors. Nevertheless, Simon does not challenge the fundamental rational choice. He continues to assume that under these limitations, the individual would still make rational choices.

The first real assault on the core of Rational Choice Theory, as well as on Bounded Rationality, came in the 1970s with the seminal work Tversky and Kahneman, the fathers of behavioral economics. Their work was, first and foremost, empirical. They demonstrated, if not proved, that rationality in human behavior is not a reasonable assumption. In recent years, especially after Kahnman’s 2002 Nobel, behavioral economics became a popular phenomenon. Gladwell’s The Tipping Point (2000), Levitt’s Freakonomics (2005), Ariely’s Predictably Irrational (2008), Kahneman’s Thinking, Fast and Slow (2011), and many more best sellers exemplify the popularity of Behavioral Economics with the general public.?

This should have been enough. In July 2007, Dan Ariely published an article in the HBR, titled: “The End of Rational Economics ”. In it he suggests that behavioral economics is changing economics from the bottom up. Businesses are adopting methodologies and tools from this new science. As optimistic as he may be in that piece, academia tends to be slower in unclenching its dogmas. Try searching for behavioral economics departments in top schools and universities. They exist, but are not easy to find. Prominent universities have yet to update their drop-down website menus. Look at the list of the Federal Reserve chairman, all with backgrounds in classical economics and law. The IMF is pretty much the same thing. In ranking behavioral economists are as rare as gems. Research.Com publishes a list of ‘Best Economics and Finance Scientists’. In 2023, the first notable behavioral economist is George Loewenstein at number 39. The number one ranked in the Best Social Sciences and Humanities Scientists list is our Herbert Simon. Need we say more??

We spent 200 years under the assumption of rationality. 200 years in which economists and scholars invested time, attention and sometimes whole countries’ resources under the seemingly unassailable assumption of rationality. And then we debunked it. Any attempt to calculate the cost of that mistake is dizzying. No matter. We now know better. We can change course and correct, right? Well, it has been nearly half a century and very little has changed.?

Traditional economics is dug in

The rule of traditional economics over every aspect of our lives and the resistance to naming a “successor” should not come as a surprise. Thomas Kuhn coined the term paradigm shift in its modern meaning [in his fantastic book: The Structure of Scientific Revolutions (1962)] and supplied us with two necessary conditions for a revolution. The first is the accumulation of a lot of evidence that contradicts the existing paradigm. The more entrenched the current paradigm, the more evidence must be supplied. The second is an alternative paradigm to replace the old. behavioral economics has the potential to expand to all the domains currently occupied by traditional economics. Nevertheless, it is not there yet, and therefore, does not meet the second condition. Meeting the first condition, despite all that we have laid out, and some, is also a challenge. The captains of industry, the czars of government, the Dumbledores of academia, all reign over massive infrastructure that represents vast stakes, invested over many centuries. Letting go of this edifice, broken as it may be, will take some doing.?

Decentralized Economics [DeEcon?] - A New Hope

We’ve made a three prong shaming of economics. 1) The deficiency in the integration of tools and methodologies that can handle complex systems. 2) The extremely strong bias against loss predictions. 3) The misplaced assumption of rationality, or at least the marginalization of theories that reject that assumption.?

So? What now? We believe there’s reason for hope.

Let’s start with complexity. Luckily quite a few things have changed since 1974. State of the art AI technology today can manipulate and evaluate over a trillion parameters. Rumors about Chat GPT4’s 100 trillion parameters are probably exaggerated. Nevertheless, Chat GPT3 is confirmed to handle 175 billion parameters and the 10 trillion mark has been crossed [see M6].

Applying these technologies for modeling economies and market dynamics, on a global scale, is attainable. Moreover, applying machines to this task, including model design [or evolution], would insulate us from bias. This can be programmed in a way that would also solve the rationality issue. The lack of rationality in human choices can be organized as biases and treated like any other parameter.?

The question is what is the best environment to start building a new empirical science of economics.?

We are suggesting that blockchain based metaverses can offer the best environment.

More on this, next time.