I have thought for some time that standard economic models used in forecasting, which necessarily are based on historical data – usually from the post WWII period,  can no longer accurately describe the new economy we see evolving today. In particular, there is the paradox that the rate of productivity improvement over the last 15 years or so (as conventionally measured) has been well below prior levels and yet we are experiencing transformations of whole industries due to rapid adoption of new technologies, which logically should mean higher levels of productivity.

This productivity issue has been the subject of a lot of recent reports from commentators such as Bill Gross, John Mauldin, A. Gary Shilling, the OECD, and, recently, CIBC’s Benjamin Tal (Productivity Growth-A Reality or Illusion? June 12, 2017). This is because overall economic growth has been slow and the standard assumption is that growth in GDP = increase in employment plus increase in productivity (real output per hour worked). If employment is not going to increase very much due to demographics, then growth in the economy will depend upon productivity gains (that, in turn, will require more business capital investment).

In fact, the proper calculation is to multiply the two factors rather than add them. “Economic output is the product of two factors: total hours worked times productivity of the workforce.” That quote comes from an excellent new piece of research by Michael Mandel and Bret Swanson writing on behalf of The Technology CEO Council in the USA, entitled The Coming Productivity Boom.

I mention this formula for estimating growth because I believe it falsely implies direct causation, that it is possible to calculate the increase in GDP that would result from additional workers (labour input) by multiplying their hours worked by the productivity figure for the whole economy. Similarly, it is assumed that new capital investment in plant and equipment (capital input) would increase the productivity of existing workers. But, in reality, the definition of productivity makes it a derivative ratio – there is no causality. If more people join the labour force, their economic output will depend on what sort of jobs they end up doing – you cannot simply apply the same productivity factor to everyone. And if a manufacturer invests new capital to buy robots, causing economic output to rise, the productivity calculation will show an increase in output per hour worked by humans even though the vast majority of them did not make any improvement in their rate of production. In fact, productivity will increase even more if the robots replace human workers, which would reduce the total number of hours worked (the denominator of the productivity ratio). This would make remaining employees appear more productive even though individual output for most workers would not have changed.

If we reject the standard economic growth model and look at productivity as just a derivative calculation that compares output (real GDP) to only one of its inputs (labour), we can understand today’s complex economy much better. Benjamin Tal accomplished this in his latest report where he identified “the rising share of the service economy” as an important factor in the slowing of total productivity growth. It is common sense that a person’s income is largely a function of their economic output. Service sector jobs are usually lower-paid. As the service sector grows while manufacturing shrinks in terms of relative economic share, productivity is reduced, all else being equal. Another factor contributing to increased service sector share of the economy is globalization and offshoring. U. S. President Trump often points to high-paying jobs in manufacturing that have gone overseas thus reducing the manufacturing component of GDP. This also implies less domestic capital spending on plant and equipment, resulting in lower than expected productivity gains.      

But Mandel and Swanson suggest another approach to the productivity puzzle that leads them to a more optimistic conclusion about future growth. They divide the private sector economy into two parts - digital industries and physical industries - based on the nature of their end products. Digital industries account for about 30% of total private sector output and 25% of the workforce. These industries have been investing heavily and have boosted productivity, with investment “more than doubling from $173 billion to $352 billion” over the last 20 years. In contrast, physical industries have invested only 19% more “from $127 billion to $151 billion”. The authors strongly believe that new technologies are increasingly being adopted by the physical industries where there is huge opportunity for productivity improvement. One large sector in this regard is healthcare. Transportation and distribution are also likely to experience rapid change. I have already written about the transformation we are witnessing in these industries (December 2016 The World Is Changing…..Are You Ready?).

There are some industry leaders (called “frontier firms” in an OECD study) that are well ahead in adopting new methods that boost productivity, reduce costs, and provide new services to consumers (like Amazon, Google, Facebook, priceline.com, etc.). They will force their competitors to do the same, simply in order to survive. The same is true geographically - some countries have leapt ahead in implementing transformational technology (e.g. India with advanced personal ID coding and internet-based financial and government services) that will spread to other regions. Matthew Tracey and Joachim Fels of Pimco call this “diffusion” in their essay Productivity: A surprise Upside Risk to the Global Economy where they suggest that greater productivity gains are possible, resulting in a higher rate of global growth.

Why does any of this matter to investors? Because the revolution in technology is gradually separating businesses into two camps - leaders (early adopters) and those who are being left behind. In a roaring bull market where pretty much everything goes up, you can simply own a passive index fund. In contrast, stock selection in today’s market has never been more important, in my view. As I argued last December, we need to make sure we are putting our money with industry leaders in the new economy – businesses with a future - while avoiding legacy businesses that are failing to make necessary adjustments and business models that may no longer be viable in the future economy. We can never do without standard economic models derived from analysis of past data, but it is risky to rely solely on them and expect history to repeat while disregarding the way synergistic adaptation of new technologies is changing the world. The new information / digital economy is quite different from the previous manufacturing-based economy, just as the industrial revolution transformed the agricultural era that preceded it. We have moved from farmers driving oxen, to production lines using machines, to brains leveraged by computers.

Which brings us to Harry Potter. Consider that J. K. Rowling created Harry Potter with very little capital investment in education, equipment (some pencils and a pad of paper), or office facilities (she wrote in cafes), yet this single creative genius built a business that, according to Wikipedia, now exceeds $15 billion! That certainly would skew the productivity calculation for the U.K. economy. How can you measure the capacity utilization of someone’s imagination?  Just as James Watt developed the commercial steam engine in 1781 that sparked the industrial revolution, we could claim that J. K. Rowling led the U.K.’s charge into the age of ideas. Harry Potter is a great example of a business with a future as this media content will continue to be viewed by millions of people around the world using various digital devices for many years to come.

 

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