The key to reviving productivity, part I

“… it is only the rise of technology, and not the rise of modern political ideas as such, which has refuted the old and terrible truth that only violence and rule over others could make some men free.” — Hannah Arendt, On Revolution


Productivity is one of the most important long-term drivers of economic prosperity. However, for the past several decades, it has been declining across the world. The key to reverse this downwards trend is innovation.

In order to call a product, service or process an innovation, it must eventually make the employment of natural resources more efficient, i.e. it must increase productivity. It does so through creating new jobs, new industries, new supply lines, new fields of knowledge, new ways of exploring the world around us and so on.

The more an innovation is dispersed into the market, the more productivity increases. This means that the subsequent growth will be less driven by debt, which will make it more sustainable. It also means that, as technological change reaches more people and businesses, living standards rise. In other words, innovation not only improves how resource efficiency of an economy but it pays for itself and much more.

An upgrade, or an invention for that matter, while it brings some level of novelty to the market, it may not result in a more efficient employment of natural resources. There is in fact a chance that an update or an invention may ultimately lead to an inefficient use of natural resources if it does not create a large enough economic benefit to pay for itself.

The start of the Industrial Revolution in England officially marked the world’s departure from the Malthusian trap that gripped societies for most of human history. This was possible thanks to innovations in a number of key fields, including energy and transportation.

Additionally, over the course of the 20th century, we’ve seen a series of advancements in the fields of healthcare, education and information processing that helped create the world we know today.

The role of innovation, which Hannah Arendt calls technology in the above opening statement, has played and continues to play a pivotal role in driving economic growth and development.

Investors seeking attractive returns over the long-term should consider backing ventures that aim to solve the productivity puzzle, i.e. that aim to innovate. By doing so, they will have a direct stake in the engines of productivity that will fuel the economy of tomorrow.

Working more for less

Over the long-term, productivity is the main driver of economic prosperity. Therefore, it is a worrying sign that productivity has trended lower for decades across several key economies.

Weak productivity diminishes the prospect for an improvement of future living standards. In other words, it paves the way towards poverty. As the charts below illustrate, the downwards trend in productivity was in motion even before the financial crisis.

Another way of measuring productivity is the multifactor productivity (or total factor productivity — TFP). Even on this measure, productivity has been weakening in recent decades.

Meanwhile, the labour utilization rate (which is defined as the number of hours worked by person employed) has gone up. The charts below illustrate this for the UK and the USA. Note that the number of hours worked is not per capita.

This happens at a time when we have some of the lowest unemployment rates ever to be recorded, suggesting that monetary policy has little-to-no impact in actually revitalising the economy; its power is to stimulate consumption based on credit.

As the OECD recently reported, most of the jobs created since the financial crisis have been in low productivity sectors. Additionally, in certain economies, such as Belgium, Finland and Italy, there has been a net destruction of jobs in sectors with above average labour productivity.

Therefore, we have a) low labour productivity (i.e. workers are producing less per hour worked), b) an increase in labour utilisation rate (i.e. people are working more hours) and c) some of the lowest unemployment rates on record (i.e. more people than ever are likely doing a) and b)).

Furthermore, real wages have been dire throughout much of this economic “recovery”. This means that the living standards for a lot of people have declined.

In part responsible for the decline in productivity is the changing condition of demographics across the world. Global fertility rate is now on a clear downwards trajectory and is expected to decline further in the years ahead. Indeed, as Max Roser pointed out “one of the big lessons from the demographic history of countries is that population explosions are temporary”.

A smaller population means that a) the workforce is shrinking and b) a huge driver of demand (the number of consumers) is also diminishing. All else being equal, these are deflationary forces.

On top of this, a number of core economies are facing ageing population. Globally speaking, 2018 was the first year ever when there were more people over 64 than children younger than five.

Ageing populations and fewer people joining the workforce means lower participation rates going forward (you can see details about this development for Europe here, for USA here, for the UK here and for Asia and the rest of the world here).

Also, in some countries, such as the USA, the UK and Japan, more elders than before are delaying retirement and working for longer. This diminishes the employment prospects of young people, which further adds pressure on labour productivity.

Overall however, we are faced with the following demographic dynamic: shrinking populations mean smaller pools of human capital; older people staying in employment for longer than it was the case for previous generations means that jobs for younger people are fewer; due to low fertility rates, a number of key economies will likely have more retirees than people working.

All of these factors are coming together to create a challenging backdrop for productivity and therefore, for economic prosperity — going forward, a smaller, less productive workforce will be responsible for economic progress (growth as well as development) while servicing growing liabilities (which include healthcare claims and funding of pension schemes).

If productivity stagnates or declines, economic progress can only happen if the inputs (labour, capital and energy) are used more intensively or in larger quantities.

You can increase productivity by either working harder or working smarter. The former means more hours at the office and delayed retirements (although it is questionable if this makes workers more productive). The latter requires innovation.

Innovation, productivity and progress

The great span of human history — from the arrival of anatomically modern man to Confucius, Plato, Aristotle, Michelangelo, Shakespeare, Beethoven, and all the way to Jane Austen indeed — was lived in societies caught in the Malthusian trap”. Then, something that happened during the years of the Industrial Revolution changed this paradigm.

That something was technological change, or innovation.

“Simply put, innovation can lead to higher productivity, meaning that the same input generates a greater output. As productivity rises, more goods and services are produced — in other words, the economy grows.” wrote the ECB recently.

In a society characterized by limited demographic growth and a finite pool of natural resources, we either maintain or increase production for the same or a smaller quantity of resources (i.e. we become more productive) or we maintain or increase production by consuming more resources. The key to productivity is innovation.

However, “[the] benefits of [a GPT] start small while the technology is immature and not widely used, grow to be quite big as the GPT improves and propagates, then taper off as the improvement — and especially the propagation — die down. When multiple GPTs appear at the same time, or in a steady sequence, we sustain high rates of growth over a long period. But if there’s a big gap between major innovations, economic growth will eventually peter out”. Here “GPT” stands for General Purpose Technologies.

This “petering out” can be seen in the growth dynamic that prevails today in major economies: economic growth while productivity is stagnating or declining and debt is climbing, especially in parts of the corporate and public sectors.

Therefore, there is a real need for solutions that boost productivity, i.e. for innovations.

As Alasdair Nairn writes in Engines that move markets, technological change…has been the driving force behind productivity growth, the creator of new products and the facilitator that has opened up new markets for existing products.”.

Capital allocators who back ventures which seek to innovate will have a direct stake in the engines of future economic growth. Obviously, financial rewards for backing new technologies are not guaranteed. However, this is a risk which, if diversified (either to exposure to multiple potential breakthroughs and other, more mundane and less correlated assets), can reward investors handsomely.

Looking back at history, we can see the areas which have had the biggest impact in accelerating economic progress, especially those that helped us break from the centuries-long Malthusian pattern.

These innovations happened in five key areas: energy, healthcare, infrastructure (including transport), education and information technology.

Please note that the list below is non-exhaustive – it builts on the following work: Economic Transformations: General Purpose Technologies and Long Term Economic Growth by Richard G. Lipsey, Kenneth I. Carlaw and Clifford T. Bekar, The Impacts of Technological Invention on Economic Growth – A Review of the Literature by Andrew Reamer and Energy capture, technological change, and economic growth: an evolutionary perspective by Victor Court.

There is no coincidence that the biggest innovations have been concentrated in these fields  —  they all improve exergy (productivity), either directly or indirectly.

For example, writing enables clearer and more precise communication which leads to more efficient execution of processes and less waste; the university is essentially a network of ideas and a place to explore new ways of thinking (i.e. of doing things better), which is crucial for any innovation to occur; tapping into cheap oil and other fossil fuels enabled productive economic activity on a scale unseen before.

Indeed, it is within these key areas that we need to strive to innovate today.

Defining innovation

According to Joseph Schumpeter innovation is a “process of industrial mutation, that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one”. Another, less poetic and more pragmatic, definition, comes from the Oslo Manual: “an innovation is the implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organisational method in business practices, workplace organisation or external relations.”

In one word therefore, we can say that innovation is change. Importantly, this change is “not a linear, formulaic process of isolated actors but rather a messy, chaotic, and uncertain one of substantial interactions”.

Innovation is however different to an upgrade or an invention. In order to call a product, service or process an innovation, it must eventually make the employment of natural resources more efficient, i.e. it must increase productivity.

In addition to this, it must also bring to market something new which, as that novelty is more and more dispersed, it transforms the socio-economic order. This can mean the creation of new or better quality jobs, new industries, new supply lines, new fields of knowledge, new ways of exploring the world around us and so on.

An upgrade, or an invention for that matter, while it brings some level of novelty to the market, it may not result in a more efficient employment of natural resources.

An invention is a new product, service or process that may not improve productivity at all and that it may not be distributed into the market. There are plenty of useless inventions in human history.

Meanwhile, an upgrade is not just a new addition but it requires making an improvement to a product, service or process that is already on the market. There is in fact a chance that an update or an invention may ultimately lead to an inefficient use of natural resources if it does not create a large enough economic benefit to pay for itself. A

Also, the changes that an update or an invention makes to the structure of the economy are not revolutionary (or impactful enough), as opposed to those caused by an innovation, which tend to be.

Nevertheless, the link between innovations, inventions and upgrades is an incredibly strong and strange one in the sense that it is not always clear if and how an invention or upgrade will turn out to be an innovation.

Indeed, an innovation may be the result of multiple inventions and upgrades made over time, which are eventually put together in the right way or at the right time.

This is akin to saying that the “early computer”, or the Babbage machine, was an invention and so were the James Ritty’s cash register and the Colossus (arguably the world’s first electronic computer). Almost all of these different novelties, with the exception of the Babbage machine which was never finished, made a process more efficient.

However, they did not result in structural changes to the economy because they never reached the market scale needed for that or because there weren’t capable of creating an industry around them. That said, they did lay the foundations of Intel’s work on the memory chip and on Microsoft’s development of the Windows operating system which, in turn, created the personal computer – this was an innovation because it made processing information substantially more cost-efficient and it helped create and evolve the IT industry.

Now that we have a definition to work with  —  innovation is change caused by a new product, service or process which, as it becomes distributed more widely into the market, it improves productivity while also transforming the structure of the socio-economic order  —  how do we measure it and over what period?

Measuring innovation

Based on Ray Dalio’s work on productivity, the exergy economic model to which I was introduced to by the work done by the MacroStrategy Partnership, as well as based on the research conducted by Erik Brynjolfsson and Andrew McAfee and, separately, by R. G. Lipsey, K. I. Carlaw and C. T. Bekar, there are certain enablers (measures of input) of technological change and qualifiers (measures of output) of that change.

Enablers of innovation:

1. The right mix of cultural values…

2. …that transpire in a flexible regulatory and legal system

3. Access to necessary resources, such as raw materials

4. Investment / funding

Qualifiers for change to be innovation:

1. The new product, service or process results in a more exergy efficient (i.e. productive) economy over a multi-year period

2. The novelty changes the structure of the economy — be it by creating new jobs, new industries, new supply lines, new fields of knowledge, new ways of exploring and / or experiencing the world around us etc

3. For 1. and 2. to happen, the novelty must be dispersed within the economy.

The practice of innovation accounting is still in its infancy and understandably so, as our civilisation has never had to account for so much tangible and intangible “stuff” being responsible for our progress. An interesting side note: the exercise of measuring innovation is a job for experts in the field of complex systems, as much as it is for economists.

To see why, take for example the following thought exercise: a song inspires someone to write a book, which further inspires another person to try new things that eventually leads to an invention which, in time is “lucky” enough to be commercialised and dispersed into the market, becoming an innovation.

How do we account for the value of that song or of that book? For the inspiration of the songwriter or of the book author? Should these elements be considered as inputs into this innovation? I would answer “yes, they should”. But how do we measure a) their own inputs and b) their contribution.

The World Economic Forum compiled 31 indexes, survey and reports that aim to measure innovation. The issue with these trackers, as Peter Thiele pointed out, is that they are either too focused on inputs and don’t account enough for the broader outputs of innovation or they use too narrow measures of innovation all together.

Thiele stressed that “ideally, an index of innovation would capture both the outcomes — the extraordinary new value — and the various inputs — the extraordinary new ways — that are combined to produce the outcomes.”

Here is a solution to this problem. This is inspired by the work of Andy Lees from MacroStrategy as well as by Ray Dalio’s perspective on productivity.

We already seem to have several “innovation input” metrics — for example, patent activity, R&D spending, investment in intangibles (excluding goodwill and advertising) by companies and venture capital activity. The bigger challenge is to measure “innovation output”, i.e. the broader outcome that Thiele refers to.

I suggest that we measured it by the overall change in labour productivity and capital stock. The latter condition is added as a “safety” measure (just to confirm the trend in labour productivity). The idea here is that if something increases productivity, we can afford to save (invest) and build capital stock.

Therefore, if we have output growth but stagnating or declining capital stock, especially in an environment of low productivity, then it must mean that, overall, resources are not allocated efficiently, i.e. that whatever novelty we create is not paying for itself, let alone boosting productivity. Data for the charts below comes from the World Bank.

At first it looks like the growth we have witnessed during the current economic recovery has been depleting capital stock, which includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings.

This suggests that a) the growth hasn’t been driven by productivity and that b) there hasn’t been enough investment to sustain, let alone build capital stock. That said, some emerging economies, such as China seem to have been adding to their capital stock as their GDP increased.

Although in recent years the Chinese economy seems to have followed the same path of capital stock consumption like most of the developed world has. Also, the sustainability of China’s capital stock is increasingly under scrutiny as “ghost” cities and “bridges to nowhere” have been reported by some commentators.

However, it is perhaps inaccurate to only focus on formation of fixed assets, especially given the heavy knowledge-based economic “model” that has been spreading across the world. So let’s look at some figures on investment in intangibles, which also coincide with some of the “innovation input” measures mentioned by Peter Thiele.

We can see that across various regions of the world, investing in / funding of potential innovation (i.e. R&D spending) has been roughly flat for the past 20 years, when measured as a percentage of GDP. The noticeable outliers are China which grew its gross R&D spending from 0.6% of GDP in 1996 to 2.1% in 2016 and Israel which has been maintaining its gross R&D spending above 3.5% of GDP since 2000.

However, the picture is a bit more optimistic when we separate the private sector’s R&D spending. The chart below shows that the private sector has continued to look for ways of creating new products, services or processes that may very well turn out to be innovations in time. Also, in light of Ray Dalio’s commentary on the ongoing dispute between China and the US, I separate the data for the US and China from the rest of the world.

Another encouraging sign is the amount of patents that have been granted, which has been on an upwards trend for the past 30 years. True — not all those granted patents are novelties that will boost productivity and transform our society and economy. Some patents may actually be detrimental to such progress as they can act as roadblocks to innovation.

To me however, the upwards trend in patent application and patent grants is a proxy for the fact that people continue to look for new ways of doing things or for new things all together — this search is essential for innovation.

Below we look at the total patent granted (the red line in the above chart) broken down by technology “area”.

I used my own judgment to categorise 36 areas into 6 (the five key ones discussed above plus one which includes our entertainment and comfort). The categorisation has been done based on guidance from the World Intellectual Property Organisation’s Concept of a Technology Classification for Country Comparisons, which is where the data comes from. The period before the 21 century includes data between 1980–1999. Similarly, the period since the 21 century includes data between 2000–2017.

We can see that there has been a lot of effort in searching for new ways of doing things in 4 out of the 5 key areas of innovation. Therefore, we may be in one of the “waves” of lower productivity  —  a period of time during which innovations are spawning but haven’t yet been dispersed into the economy (i.e. they haven’t reached enough or the right hands to boost overall labour productivity).

Another “tracker” of innovation which is not quantifiable (and I would argue it should not be) but which is observable from real world interactions is how open is our society to philosophy — the word philosophy, at its roots, means φιλοσοφία, or “love for wisdom”. So how do we gauge this?

We can observe if people are encouraged to think and speak freely, encouraged to explore ideas, even if they make no sense at first and if they are provided with the necessary political space to do so.

I say political space and not just any space because, as the Romans realised, we are free only in the political space (that is what the SPQR acronym stands for). We should never underestimate the power of ideas for it is the driving force behind most of the charts in this paper. As bodybuilder Kay Green said, “thoughts become things”.

Now to the question regarding the timeframe of innovation measurement.

In my view, due to the uncertain nature of innovation (i.e. being a kind of change), measuring its impact over the long term is better than doing it over the short term. This is to avoid concluding that something is an innovation because it sparked productivity for a month, a quarter or a year after which its impact faded.

Having a multi-year timeframe is therefore more likely to enable us to measure it more accurately, especially when we consider that so many innovations in history did not have an immediate impact on the economy.

This is because innovation comes in waves: “consider what I call the portable-power era — the time of the diffusion of technologies such as the electric motor and the internal-combustion engine. This era starts around 1890 and ends in the mid-1930s. For the first 25 years of this era, productivity growth was quite slow: less than 1.5 percent per year. Then starting around 1915, growth sped up to around 3 percent per year and stayed there for a decade. Then things slowed again through the mid-1930s. So you have a 25-year slow period while the technology was diffusing, a 10-year acceleration, and then another slowdown”.

Therefore, a time frame of minimum a decade is recommended.

Finally, we have to address the issue of distribution of technological change. Take a look at the chart below.

The above data comes from the UK’s Office for Budget Responsibility. I added the circles to show that labour productivity, based on the 10-year rolling average growth rate, hasn’t been so low since the late 1880s and that it reached an all-time peak in the 1970s.

Since then it has been continuously declining. Before 1880s, innovations in the area of energy processing (for example, James Watt’s steam engine in 1769) and in area of transport infrastructure (such as the railway system and Stephenson’s Rocket locomotive in 1829) boosted productivity levels from 1860s through to the early 1880s as these technologies became more widely adopted across the country.

Similarly, before 1970s the computer technology started to improve (with the first computer, PDP-1, on the US market in 1960 for about 1/10 of the previous versions’ price), the first nuclear reactor was connected to the grid in 1956 and the idea of trade liberalisation started to become more popular across the developed world in the years following WWII (which helped spread ideas and technologies that were previously confined solely to certain countries). Also, during the years of the Cold War (1946–1989) there was a constant arms race to develop new technologies.

The key message is that productivity seems to come in waves, depending on when and how technological change (innovation) is dispersed.

However, going forward, if we want to innovate further and improve productivity growth, we need to be mindful of the “energy cycle” as well.

There comes a point when in order to get to the “next level” of economic development (e.g. quantum computers, global quality healthcare, faster transportation, less pollution and so on), the boost to productivity needed to create all of this will come only if we tap into a cheap and very abundant (more abundant than the finite oil resources) form of energy that enables all of this to happen. See my previous paper for more details on this.

The decline in productivity that we’ve seen in recent decades, coupled with the fall in capital formation suggests that either the new technologies created over the past 10 years or so haven’t been innovations or there are some other things out there that prevent them from doing their job of boosting productivity and transforming our economy for the better.

In part II of this report, we will look at some of the factors that can block innovation, as well as what this macro backdrop may mean for investors’ capital allocation decisions.

Categories: Economics

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