Productivity might be desirable, but is it really measurable?
Notwithstanding the recent volatility in equities, economists have tended toward a degree of buoyancy in recent months. The International Monetary Fund (IMF) and the Organization for Economic Cooperation and Development (OECD) see world GDP increasing by 3.7% this year, which would make 2017 and 2018 the strongest two growth years since 2010-11.
Moreover, the IMF has forecast average unemployment across the Group of Seven advanced economies to dip below 5% for the first time since the 1970s. And all of this is happening with inflation fairly well in hand.
There is one measure by which the global economy continues on an arc of flattering to deceive, however, and that is productivity. For a number of years, there has been an expectation of productivity gains flowing through from disruptive technologies – and in part it’s this expectation of “jam tomorrow” that explains the clamor for stocks in tech firms still apparently chary of demonstrating profitability.
Such flow-throughs have not happened, leading to periodic hand-wringing from analysts about a slowdown that has afflicted both manufacturing and service industries across all types of economies – advanced, emerging and developing. A recent Reuters report on a slight third-quarter uptick in Britain’s numbers noted, wryly, that the country had also just endured its worst decade of productivity growth since the 1820s, when it was “emerging from the Napoleonic Wars.”
Higher productivity means companies producing more goods or services for less, either in terms of labor or capital. It is considered key to rising living standards as it allows firms to pay higher wages without having to raise prices.
One can see how this dynamic has played out in China in recent decades. In the wake of Deng Xiaoping’s “reform and opening-up” policies, by the early years of this century Chinese industry was well on its way to dominating global supply chains in everything from clothing to electronics. From almost a standing start, productivity exploded. As the Chinese economy has advanced, however, the returns for each new unit of input have tapered off. Now, with costs rising and China’s labor force shrinking as a consequence of its long-standing one-child policy, its productivity faces the slowing trajectory already familiar to so-called “mature” economies.
In part it’s the expectation of ‘jam tomorrow’ that explains the clamor for stocks in tech firms still apparently chary of demonstrating profitability
That the vagaries of productivity are little understood in those economies will offer scant reassurance to dirigiste policymakers in Beijing. In the United States, where productivity grew by a modest 1.2% last year, despite an annualized fall of 0.1% in the fourth quarter, long-term deceleration has been a cause of angst for years. Even so, owing perhaps to the flexibility of its labor market, the US scores well by comparison with other advanced economies, including Germany. Britain fares worse than either, but marginally better than Japan, which happens to have the lowest unemployment rate of any G7 economy.
What’s clear is that slight movements up or down in hours worked will have an impact on productivity data – as they did in the aforementioned British Q3 uptick. UK employment currently hovers at a 42-year-low of 4.3%, but in the three months from July to September the pace of hiring slowed and the number of hours worked dropped by 0.5%, even as the British economy grew by 0.4%. Bingo: output per hour grew 0.9% for the quarter, recovering from a 0.1% drop in the previous one. Observers have noted that France achieves marginally higher productivity than Britain – but with unemployment trending north of 9% throughout 2017.
Perhaps only an economist could argue that the route to more productivity lies in less employment. There is certainly a case to be made for not feeling compelled to work oneself to death, however. In Japan (low productivity, low unemployment), that case is being made, even as people are also being enjoined to work until they’re 70, to combat labor shortages. Conversely, in France (broadly similar productivity, high unemployment), Emmanuel Macron wants to take apart labor laws that limit the French working week to 35 hours.
In France, some people do work more than 35 hours, of course – and are paid overtime at a higher-than-normal hourly rate. In many other economies, overtime payments are an alien concept. Country-by-country comparisons of productivity should, perhaps, better reflect such variations. After all, if “only a small portion of overtime goes into the pay slip,” as in Japan, then productivity calculations are surely unreliable.
IMF and OECD reports are rarely bereft of entreaties on governments and central banks to enact productivity-enhancing structural reforms. Discounting the possibility that humanity has exhausted its potential for such advances, there remains another challenge that they tend to soft-pedal, however, and it is a profound one: How, in an era in which advanced economies are increasingly service-oriented and artificial intelligence is gaining purchase, do you go about identifying, let alone quantifying, economic activity?
It’s straightforward enough to measure factory output, or even the labor costs saved by self-serve kiosks at McDonald’s. But software programs don’t work hours. Who or what tracks and records data-encrypted financial trades on fintech platforms, or the one-click insurance policy you just bought? And what is the value added by jobs based entirely around publishing things on social media?
Neal Soss, a former assistant to then US Federal Reserve chairman Paul Volcker, recently told The Wall Street Journal: “As far as I’m concerned productivity is a miracle.” One problem with miracles: You can never be entirely sure they’re not a mirage.