15/11/18: The 'New Normal' is a Road to another Tech Sector Bust

The VC land of wonders and waste is awash with cash, thanks to a decade-long loose liquidity pumping across the markets by the Central Banks. Just as in the prior iterations of the same (the Dot.Com Bubble and the pre-GFC assets binge), the outrun will be the same as it was before: a crash.

TechCrunch reports that (https://techcrunch.com/2018/11/11/age-of-the-unicorn/):

• Over the last 5 years, the number of 'unicorns' - startups with valuations in excess of USD1 billion - has grown from 39 to 376 - almost a ten-fold increase
• The rate of 'unicorns' emergence is accelerating: in 11 months through November 1, 2018, we've added 81 new 'unicorns' to the roster, which means there is now a new 'unicorn' company launched every four days
• Mega-deals for start ups - funding rounds in excess of USD100 million - are also on the rise, with their frequency up ten-fold on five years ago. "Back in 2013, there were only about four mega rounds a month, but now there are forty mega rounds a month based..." Thus, "starting from 2015, public market IPO has for the first time no longer been the major funding source for unicorn size companies."

As the chart above shows, there has been a power-law acceleration in the trend since mid-2017 and it is now clearly topping the asymptote.

Two countries dominate the 'unicorns' league: China (with 149 count) and the U.S. (with 146 count). Which implies two things: 

• Given the close links between the PBOC policies, Chinese Government investment strategies and supports, and China's counts of 'unicorns', majority of these start ups are heavily dependent on debt, and political good will. They are sitting ducks for ESG risks and are extremely exposed to political and policy uncertainty.
• The U.S. 'unicorns' are completely dependent on the markets ability to cycle cash from corporate and financial sectors debt and private equity into start ups funding, and M&As. There is zero rational valuation happening in this sub-sector.

A dramatic shift in risks from tangible tangible technologies (including strongly patentable innovation or defensible market shares) of the likes of Apple and Google toward less tangible, highly price and income elastic SaaS types of product offers is reflecting the massive buildup in valuations risks. This too is reflected in the article, albeit the authors fail to spot the implications. TechCrunch conclusion is perhaps even more alarming that the stats they present. "Mega rounds are the new normal; staying private longer is the new normal; and the global composition of the unicorn club is the new normal." We've heard exactly the same arguments at the tail end of the Dot.Com boom about the absurdly over-valued early internet age companies. We've heard exactly the same arguments about the real estate sector prior to 2008. We've heard exactly the same arguments about tulip bulbs in Amsterdam some centuries ago too. 

'The new normal' is the old road to a bust.

13/3/18: Another Brick in the Secular Stagnation Wall

Another brick in the Secular Stagnation Wall: global productivity growth has now collapsed in all major groups of economies:

And the short-lived blip to the upside over the late 2014 in the advanced economies is now... well, short-lived.

30/9/17: Technological Revolution is Fizzling Out, as Ideas Get Harder to Find

Nicholas Bloom, Charles Jones, John Van Reenen, and Michael Webb’s latest paper has just landed in my mailbox and it is an interesting one. Titled “Are Ideas Getting Harder to Find?” (September 2017, NBER Working Paper No. w23782. http://www.nber.org/papers/w23782.pdf) the paper asks a hugely important question related to the supply side of the secular stagnation thesis that I have been writing about for some years now (see explainer here: http://trueeconomics.blogspot.com/2015/07/7615-secular-stagnation-double-threat.html and you can search my blog for key words “secular stagnation” to see a large number of papers and data points on the matter). Specifically, the new paper addresses the question of whether technological innovations are becoming more efficient - or put differently, if there is any evidence of productivity growth in innovation.

The reason this topic is important is two-fold. Firstly, as authors note: “In many growth models, economic growth arises from people creating ideas, and the long-run growth rate is the product of two terms: the effective number of researchers and their research productivity.” But, secondly, the issue is important because we have been talking in recent years about self-perpetuating virtuous cycles of innovation:

• Clusters of innovation engendering more innovation;
• Growth in ‘knowledge capital’ or ‘knowledge economies’ becoming self-sustaining; and
• Expansion of AI and other ‘learning’ fields leading to exponential growth in knowledge (remember, even the Big Data was supposed to trigger this).

So what do the authors find?

“We present a wide range of evidence from various industries, products, and firms showing that research effort is rising substantially while research productivity is declining sharply.” In other words, there is no evidence of self-sustained improvements in research productivity or in the knowledge economies.

Worse, there is a diminishing marginal returns in technology, just as there is the same for every industry or sector of the economy: “A good example is Moore's Law. The number of researchers required today to achieve the famous doubling every two years of the density of computer chips is more than 18 times larger than the number required in the early 1970s. Across a broad range of case studies at various levels of (dis)aggregation, we find that ideas — and in particular the exponential growth they imply — are getting harder and harder to find. Exponential growth results from the large increases in research effort that offset its declining productivity.”

We are on the extensive margin when it comes to knowledge creation and innovation, which - to put it differently - makes ‘innovation-based economies’ equivalent to ‘coal mining’ ones: to achieve the next unit of growth these economies require an ever increasing input of resources.

Computers are not the only sector where the authors find this bleak reality. “We consider detailed microeconomic evidence on idea production functions, focusing on places where we can get the best measures of both the output of ideas and the inputs used to produce them. In addition to Moore’s Law, our case studies include agricultural productivity (corn, soybeans, cotton, and wheat) and medical innovations. Research productivity for seed yields declines at about 5% per year. We find a similar rate of decline when studying the mortality improvements associated with cancer and heart disease.” And more: “We find substantial heterogeneity across firms, but research productivity is declining in more than 85% of our sample. Averaging across firms, research productivity declines at a rate of around 10% per year.”

This is really bad news. In recent years, we have seen declines in labor productivity and capital productivity, and TFP (the residual measuring technological productivity). Now, knowledge productivity is falling too. There is literally no input into production function one can think of that can be measured and is not showing a decline in productivity.

The ugly facts presented in the paper reach across the entire U.S. economy: “Perhaps research productivity is declining sharply within every particular case that we look at and yet not declining for the economy as a whole. While existing varieties run into diminishing returns, perhaps new varieties are always being invented to stave this off. We consider this possibility by taking it to the extreme. Suppose each variety has a productivity that cannot be improved at all, and instead aggregate growth proceeds entirely by inventing new varieties. To examine this case, we consider research productivity for the economy as a whole. We once again find that it is declining sharply: aggregate growth rates are relatively stable over time, while the number of researchers has risen enormously. In fact, this is simply another way of looking at the original point of Jones (1995), and for this reason, we present this application first to illustrate our methodology. We find that research productivity for the aggregate U.S. economy has declined by a factor of 41 since the 1930s, an average decrease of more than 5% per year.”

This evidence further confirms the supply side of the secular stagnation thesis. Technological revolution has been slowing down over recent decades (not recent years) and we are clearly past the peak of the TFP growth of the 1940s, and the local peak of the 1990s (the ‘fourth wave’ of technological revolution).

Update June 7, 2018: A new version of the paper is available at https://web.stanford.edu/~chadj/IdeaPF.pdf.