TheMarketForIdeas

Financial crises are often explained as failures of markets, regulation, or monetary policy. More often than not, however, they begin as failures of judgment.

That may sound obvious. Yet modern societies continue to place extraordinary faith in expert opinion, particularly when uncertainty is high. Investors seek forecasts. Governments seek guidance. Central banks seek credibility. The assumption is that more expertise leads to better decisions.

History suggests a more complicated reality.

Long before behavioural economics, before forecasting models and risk-management algorithms, Mark Twain identified a problem that remains central to modern finance:

“The trouble with the world is not that people know too little; it’s that they know so many things that just aren’t so.”

Few observations capture the history of economic forecasting more accurately.

Consider some of the most influential mistakes of the past century.

In the late 1920s, prominent economists and financial commentators argued that a new era of prosperity had arrived. The stock market crash that followed exposed the fragility of those assumptions.

In the decades before the inflationary turmoil of the 1970s, many policymakers believed they had discovered a stable relationship between inflation and unemployment. They had not.

In 1998, Long-Term Capital Management employed Nobel Prize-winning ideas, sophisticated quantitative models, and some of the brightest minds in finance. It still collapsed.

In the years leading up to 2008, rating agencies assigned AAA ratings to securities backed by increasingly questionable mortgages. Investors interpreted those ratings as objective assessments of risk. In retrospect, they were expressions of confidence built upon assumptions that turned out to be dangerously incomplete.

What’s striking about these episodes isn’t the lack of expertise. Expertise was abundant.

The problem was that expertise often produced a false sense of certainty.

Twain understood something that institutions frequently forget: intelligent people are perfectly capable of believing implausible things, especially when those beliefs are widely shared.

“We are discreet sheep; we wait to see how the drove is going, and then go with the drove.”

Today we would describe this as herding behaviour. Economists study it. Psychologists model it. Regulators worry about it.

Yet the underlying mechanism is simple enough. Human beings are social creatures. We take comfort from agreement. We derive reassurance from the fact that other intelligent people appear to share our conclusions.

Unfortunately, consensus and correctness are not the same thing.

Indeed, financial history suggests that the two often diverge at precisely the moments that matter most.

Before the housing bubble burst, there was broad agreement that national property prices could not decline significantly. Before the dot-com crash, there was widespread belief that a new economic era had arrived. Before inflation returned after the pandemic, there was broad agreement that price pressures would prove temporary.

The details change.

The pattern doesn’t.

One reason is institutional.

Forecasting isn’t just an intellectual exercise – it’s shaped by professional incentives. Economists, analysts, rating agencies, and policymakers operate within organisations that reward credibility, reputation, and career stability.

Under such conditions, being wrong alongside everyone else is often safer than being wrong alone.

An economist who issues a forecast close to the consensus may ultimately prove inaccurate, but the reputational consequences are limited if most of the profession made the same mistake.

An economist who challenges the consensus risks looking foolish long before events reveal whether the warning was justified.

The result is a quiet but powerful pressure to conform.

Twain recognised this tendency in political life.

“Nothing is so ignorant as a man’s vote when he has not heard both sides.”

The observation applies equally well to financial markets. Systems become fragile when alternative views disappear. Once dissent is treated as eccentricity rather than analysis, institutions lose their ability to identify emerging risks.

This is one reason why major crises often appear obvious in hindsight. The information was usually available. The warning signs often existed. What was missing was not knowledge but willingness to question prevailing assumptions.

Nassim Nicholas Taleb built much of his work around this insight. Black Swans do not emerge from nowhere. They emerge from environments in which people have become excessively confident in their models, forecasts, and explanations.

Twain would likely have understood the point immediately.

He was deeply suspicious of certainty.

Not knowledge. Not expertise. Certainty.

That distinction matters.

Modern economies depend on specialised knowledge. Financial systems could not function without analysts, economists, statisticians, and risk managers. The lesson is not that experts are unnecessary.

The lesson is simply that experts are human.

They are vulnerable to fashion, incentives, groupthink, and intellectual overconfidence in much the same way as everyone else.

Perhaps that is why one of Twain’s most quoted observations remains surprisingly relevant:

“Whenever you find yourself on the side of the majority, it is time to pause and reflect.”

This is not an argument against consensus. Most of the time, consensus is useful.

It is, however, an argument against treating consensus as evidence.

The most dangerous words in finance are rarely “nobody knows.”

More often, they are “everybody knows.”

Because that is usually the moment when risk stops being visible and starts becoming systemic.

The failure of experts is therefore not a failure of intelligence. It is a failure of humility.

And in economics, as in life, humility is often a more valuable safeguard than confidence.

Photo source: Mahoney Fotos @ pexels.com.