Bubble, bubble toil and trouble?

Increasingly, people are talking about a bubble in artificial intelligence (AI). This sounds ominous, but it has not stopped the stock market from moving higher.

There are many other commentators who are better placed to discuss the economic, social and geopolitical implications of AI, as well as the limitations and risks. Here we will simply explore the general characteristics of investment bubbles to see what applies to the current moment.

Chart 1: Google searches for “AI Bubble”

Source: Google

Each bubble is unique, but there are commonalities. There is usually a narrative of why some exciting new technological or social development will lead to ever rising prices. Economics Nobel laureate Robert Shiller described this as a process where price increases raise investor enthusiasm, which spreads by “psychological contagion from person to person, in the process amplifying stories that might justify the price increases and bringing in a larger and larger class of investors.”

There is the expectation of riches based on price movements, not underlying fundamentals. Economist Charles Kindleberger, author of a classic book on the theme, Manias, Panics and Crashes, describes a bubble as “a sharp rise in price of an asset or a range of assets in a continuous process, with the initial rise generating expectations of further rises and attracting speculators interested in profits from trading in the asset rather than its use of earning capacity.”

Inevitably, people believe there is a new paradigm that render old ways of analysing investments irrelevant. One will hear a variation of the phrase “this time is different”. This is also the title of another classic book on financial crises by Carmen Reinhart and Ken Rogoff, while Sir John Templeton called it the four most dangerous words in investing. Warren Buffet’s five most dangerous words in business, “everybody else is doing it” also applies.

A final characteristic of bubbles is that even with the above checklist – rapid price increases driven by expectation more than reality, euphoric narratives, and the drawing in of ever more participants – they are very hard to spot in real time. It is usually only after the fact that we can definitively say something was a bubble. When it is still blowing up, even hardened sceptics must admit that there is a possibility that things will work out.

In the real world
Another general principle is that investment bubbles usually have a financial and a real economy dimension. The more pronounced the real-world dimension, the greater the fall-out after the crash.

A purely financial bubble will obviously hurt investors when it pops, but the broader impact is muted. Bitcoin is probably unique in having experienced several bubbles and crashes in its short existence, but because Bitcoin has limited connection with the real world, its price slumps did not have a big impact on the economy.

At the other end of the spectrum, however, are real estate bubbles, for instance Japan in the 1980s, the US and Spain in the early 2000s and China in the late 2010s. These bubbles distort the real economy, since an ever-greater share of activity becomes devoted to property. Other more productive sectors might lag behind as capital is redirected into the sector and people quit their jobs to become real estate agents or full-time landlords. It works for a while, but when the bubble bursts, the capital and labour attached to the real estate must be put to work elsewhere.

More damaging is the debt. Developers and homebuyers rely on loans which they must still repay even when property prices fall. Banks then end up with a sharp increase in non-performing loans. The 2008 sub-prime crisis was made worse by the fact that the debt was sliced and diced and spread throughout the global financial system, such that no one had a full picture of the massive vulnerabilities that had accumulated. When a property bubble bursts, in other words, balance sheets are impaired across the economy and painful deleveraging acts as a drag on economic growth for years.

The upside of down
Bubbles do have one positive side effect, however. They often leave behind cheap and plentiful infrastructure that would not have otherwise existed. The initial investors get wiped out, but others can buy the assets at cents on the dollar. One example is the 1800s railway bubbles. The railway was a truly transformative industry at the time, but people got overexcited. Investors bid up share prices of railway companies, who in turn laid tracks in all directions, without having to think too carefully whether they would earn a return. With all this overbuilding, many lines couldn’t be profitable and the bubbles burst.

However, afterwards, the tracks were still there, and since the new buyers paid little, they could generate a return in the decades ahead. In that sense, the railway bubble could be viewed as a social good as the first investors “subsidised” cheap railways for subsequent generations through their losses. The internet and telecoms bubble of the 1990s similarly resulted in thousands of miles of broadband fibre that could never generate a return. However, after the bubble burst and the expense of building out the fibre networks was written off, there was a platform for the internet and eventually, social media, to really take off.

It is the 1990s internet and telecom bubble that is the obvious parallel the current AI enthusiasm, but the lessons from the railway bubble of 1800s and the canal bubble of 1700s also apply. The so-called dotcom bubble was based on the belief that the internet would change everything. This belief was not wrong, just a bit early. More importantly, however, people were prepared to pay anything for exposure to internet companies. Considerations of cash flow, costs and profitability went out the window. The cash flows that were visible to investors were also exaggerated by the fact that the software companies bought from the hardware companies and vice versa. Money was circulating within the system, but the money from outside, from the end customer, was often in short supply.

Click here to read more...