18 Jan 2018
China’s rise was epochal but much of the impact was narrowly confined and has broadened only recently. Technology is challenging us much more fundamentally than China’s economic ascent, confronting many of the ideas we see as foundational. Technology is genuinely disruptive.
When I speak to businesses, the conversation almost always circles a few central concerns: the frenetic pace of change, a diminished ability to sustain price increases, and the need to think more inventively about how to create value and generate returns in the face of new competitive entrants - often from outside their sector.
"Recognition that the tech shock may be more disruptive than the China shock is dawning but the awakening seems to be very slow.”
Yet economic-focussed discussions still rely on learnings from previous cycles, using traditional frameworks and well-worn tools. The tech shock surely requires a more-thorough assessment of those approaches and tools.
If we compare the China shock to the tech shock, the challenge is stark. Recognition that the tech shock may be more disruptive than the China shock is dawning but the awakening seems to be very slow.
It’s difficult to envisage what the Asia Pacific region would look like today without the influence of China’s rise over the past few decades.
It is the world’s largest trading nation and second-largest economy. It now accounts for a quarter of global industrial production (up from 5 per cent 30 years ago), half of global crude steel production and the largest portion of tourism spending.
The main adjustment costs of China’s rise have fallen on the larger economies, such as the US and the UK. In particular, the global manufacturing sector has been dramatically reshaped. NBER research from Autor, Dorn and Hanson suggests while China’s rise cost jobs in US manufacturing, “there is little evidence for substantial offsetting employment gains” elsewhere.
China’s rise has meant the global economy has been much stronger, particularly in the last decade. Chinese tourists have been an important source of revenue for many countries ($US260 billion globally in 2016).
Chinese FDI has been crucial for an increasing number of (particularly less developed) economies. Commodity prices and commodity demand have been stronger for the last two decades, and manufactured goods prices have been soft, benefitting consumers of those products.
Smaller, more open economies have been in a better position to benefit from the positive influences across commodities, tourism and FDI. In fact, for many, the overall impact of China’s rise has been positive.
Economies which have been underweight manufacturing and overweight natural resources have particularly benefitted.
So while China’s rise has not been costless, the adjustment costs have been mostly borne by manufacturing, while the benefits have spread quite widely.
The lion’s share of China’s economic impact has fallen on manufacturing and natural resources. Technology’s disruption is much broader. Transport, education, banking and finance, media, entertainment, retail and professional services are all being reshaped under its influence.
Outside some sectors – such as government and construction – it seems virtually all industries in advanced economies are affected.
This latest wave of digital innovation seems to be radically broader than the use of robotics and technology which has been steadily changing manufacturing and commodities over the past century.
The aggregate direct impact of these forces is macro in scale. We have written previously on the impact technology seems to be having on wages and business investment and also the implications for economic policy. But technology also has implications for the nexus between economic and social policy.
In contrast to China – where by virtue of its addition to aggregate demand and the sectors where it has had a positive external impact – technology has fewer obvious winners in a macroeconomic sense, at least initially.
In an analogue environment, economic growth requires and depends on business fixed investment involving both labour and materials. In a digital environment, the link between growth and the demand for labour and materials is weaker – potentially, much weaker. Many of the new digital-based entrants to the economy are:
Revenue is being generated but it's not taking the same scale of physical capital investment we are used to.
As well as adding capacity cheaply, new entrants force incumbents to narrow margins to retain customers, meaning their influence is directly deflationary.
Technology has also changed the price transparency around products which were never particularly transparent.
As such, technology is much closer to a pure (positive) productivity shock. Higher productivity is ultimately the only driver of higher living standards but these gains may only emerge over time.
Brynjolfsson, Rock and Syverson argue, for instance, it took around three decades for manufacturing to reshape itself around the new technologies associated with electric power, as opposed to trying to add it into existing processes. The latter can help cut costs, but the former is genuinely transformational.
The technology shock is also impacting most forcefully when there are other headwinds in the global economy. These include higher debt levels limiting future growth, the emergence of a negative demographic dividend and lower average credit growth because of more prudent banking regimes.
For some countries, China’s rise was a net benefit precisely because China strengthened the global economy. Technology is impacting when the global economy is already more fragile, which makes the adjustment harder to take.
Beyond the economic impacts, technology is challenging a number of our ideas and analytical frameworks. The following isn’t an exhaustive list. We may even be listing some issues prematurely; nevertheless the scale of the challenge seems clear.
The year 2016 was one of political surprises: Brexit, Trump and even the Philippines’ presidential election shocked virtually all establishment forecasters.
Apparent economic success did not seem to prevent political change. There is an economic underlay driving these results but by giving voice to those previously without one, social media may have fundamentally changed things.
In recent research Robert J Shiller argued “the human brain has always been highly tuned towards narratives, whether factual or not, to justify ongoing actions, even such basic actions as spending and investing”.
Social media platforms and 24/7 news cycles are allowing these narratives to flourish in a way we have never seen.
Andy Haldane highlighted recent research using Facebook data which showed, independently of local factors and conditions, the views of (economically and geographically distant) friends can materially change people’s views of the housing market.
Managing ‘truth’ in these narratives is, of course, a critical issue, with which we are only beginning to wrestle.
Seven of the world’s top-10 companies are from the technology sector and all are either from China or the US. China is the only country to have put up firewalls around its domestic internet, email, social media and technology systems - so it doesn’t seem like a coincidence China has managed to hold out against the enormous market power of the US platform companies.
This raises the question of whether the only way to compete with those huge companies (which have a head start in the technology space), is to quarantine domestic technology sectors.
If technology companies genuinely demonstrate positive returns to scale – and hence can come to hold dominant positions across industries – then expect more discussion about how other countries can create their own champions, even if few countries offer the scale potential of China.
This issue is also intersecting with national security. With strategic issues rising in prominence globally, technology’s ubiquity in modern economies suggests it is taking on some of the characteristics of a national defence industry.
For instance, the Foreign Investment Risk Review Modernization Act, 2017 focusses on foreign acquisitions in the US which threaten US technological and industrial leadership.
• The nature of work
The division and specialisation of labour is a foundational precept of economics. It has been a major driver of advances in living standards over the last three centuries. Henry Ford’s production line vehicles a century ago are perhaps the classic example.
With machine learning and artificial intelligence being increasingly applied to complex human tasks, Yuval Noah Harari points out the specialisation of labour is making it easier for algorithms to replace humans.
The narrower the range of tasks performed by a human, the more amenable those tasks are to being replaced by technology. Does it follow, then, that creating more generalist and broader roles is a way to stay ahead of the latest wave of technological change?
In this sense, if technology makes us generalists again, it might be good news. Technology, in effect, seems to be increasing the range of outputs possible for each individual. Consider how smart phones have allowed us to quickly perform a broader range of functions.
Some businesses (such as retail) are now allowing consumers to undertake more of the tasks the business used to perform. It also seems possible this ‘reallocation’ of tasks from businesses to consumers may explain some of the current productivity puzzle.
The bottom line is we may be seeing a reshaping of the fundamental nature of work. Rather than dividing it into smaller pieces, this technology wave may be a force for aggregation.
• Banking and insurance
Banking and insurance have historically relied on ‘risk pooling’ – grouping customers into different risk buckets. Under this approach, there is some segmentation between insurance policyholders or lending customers but it is typically quite broad.
With insurance for instance, flooding, cyclones, tornados or crime risks might be criteria for segmentation. In banking this may be the loan-to-valuation ratio of a loan or the geographic region or industry of a business. Technology allows much more granular segmentation of these markets.
Technologies becoming increasingly feasible include vehicles which allow your insurance company to track how you drive or data which will allow banks to actually see how close you run your cash buffers down before each payday.
Even consumer access to their own bank data will give individuals the ability to convince banks and insurance companies they are a better credit risk than the pool.
Andrew Cornell suggests Open Banking in the UK or Comprehensive Credit Reporting in Australia raises significant issues. It will improve the information available to lenders but also makes it more difficult for borrowers to escape the financial consequences of past mistakes or difficult periods in their lives.
It also raises the prospect a greater number of borrowers will have restricted access to the financial system. Data and analysis tools are likely to result in a more efficient allocation of credit but financial inclusion is very likely to suffer.
More broadly, technology is shifting the mix of investment towards intangibles. Consider what this implies for the allocation of credit to the business sector.
Typically, investment in long-lived assets has, in some significant part, been funded by borrowing. Tangible investment (ie investment in something which in general terms takes steel and cement to produce) can be used to secure lending because it is, itself, securable. This type of investment often has some secondary market value.
Intangible investment, however, is much harder to secure. How do you ensure software is not reused or relocated? And its secondary market value is questionable.
What is the secondary market value of something with a marginal cost of almost zero? Haskel and Westlake write about the rise of intangible investment and some of the challenges it brings.
At the very least, a financial system with debt financing at its heart seems relatively poorly placed to fund this sort of investment, compared to a system where equity financing is pre-eminent.
• Economic structure and the nature of growth
Beyond all this, some mundane but important challenges to economic precepts are surfacing. Technology is changing the underlying structure of economies. One idea (which has a long history) is thinking about the tradable versus the non-tradable sector.
Many countries even publish CPI data on the basis of this delineation. The basic premise is the prices of non-tradable products are domestically determined while prices for tradable products are determined with greater reference to global markets.
But on what basis can we determine which sectors are now tradable versus non-tradable? Cloud-based solutions are allowing professional service firms to easily globalise their operations.
Postal services are being disintermediated by global players who benefit more directly from the package shipping boom coinciding with the disruption of retail. Media has become progressively global as digital distribution has increased.
This effect is already substantial. In Australia, the proportion of traded goods prices changing in any quarter has risen to a record high of 45 per cent.
This is similar to when the goods and services tax was introduced in 2000 and a range of other taxes removed; a period of enormous discrete change in a very wide range of prices. It seems much of the economy is now tradable in some way or another.
Where does this leave us?
This technology revolution seems to be genuinely and persistently disruptive. It is challenging the economic structure and the nature of economic cycles. Wages, inflation and business investment are all behaving differently in the current cycle.
Perhaps most importantly, it challenges our precepts and is forcing us to reassess some of our fundamental analytical tools.
There is a particular risk some of the smaller Asia Pacific economies which benefitted disproportionality from China’s rise may not appreciate how epochal the technology shift is.
These positive flow-ons may well mean the costs of China’s rise still aren’t appreciated in those economies, like they may be in the US or the UK.
In particular, there seems to be a tendency to treat current changes as a once-off. In the past year alone we have seen claims inflation would be materially higher: if mobile phone charges were excluded from the US consumer price index; if package holidays were excluded from the German CPI; or if used-car prices were excluded from the NZ CPI.
Fundamentalism (conviction in principles rather than outcomes) is unlikely to help us through this period. Governments, in particular, seem to be struggling with this.
We should resist the temptation to treat surprises as isolated events and instead focus on the lessons we can take forward. We need to be particularly flexible and open in our thinking.
Political stability is the natural victim of this setup. The political surprises of 2016 have given way to a more jaundiced view of politics. In many ways, the consensus has tended to be less surprised because, to an extent, we expect instability, polarisation and equivocation.
As we re-explore issues like protectionism, the nature of work and how to distribute gains more evenly, this expectation seems likely to become even more entrenched.
The modest global growth environment we expect over the next couple of years is unlikely to be strong enough to remove the sense of angst generated by the structural shifts. Voters will remain demanding.
As disruption is felt across economies, business models, ideas and politics, how can we expect businesses to undertake long duration investment? There seems to be a meaningful risk traditional business investment will remain sub-par, further challenging the economic cycle.
Fundamentally, there is an existential question in the nature of technology: how are we going to know what we know? The reality is observation changes the observed, a phenomenon evidenced across economics, psychology, physics and other disciplines.
People change their behaviour when they know they are being observed or measured. The challenge with the ‘observer effect’ is so much of the digital age rests on measuring people and behaviour. The ability to measure is not going away.
In fact, it seems it will only become more pervasive. How we assess and judge the significance of the information we receive is the next realm likely to face significant disruption.
Richard Yetsenga is chief economist at ANZ
This story originally appeared as a Blue Lens piece from ANZ Research
The views and opinions expressed in this communication are those of the author and may not necessarily state or reflect those of ANZ.
18 Jan 2018
07 Feb 2018