Solving the productivity puzzle

SAN FRANCISCO – For years, one of the big puzzles in economics has been accounting for declining productivity growth in the United States and other advanced economies. Economists have proposed a wide variety of explanations, ranging from inaccurate measurement to “secular stagnation” to questioning whether recent technological innovations are productive.

But the solution to the puzzle seems to lie in understanding economic interactions, rather than identifying a single culprit. And on that score, we may be getting to the bottom of why productivity growth has slowed.

Examining the decade since the 2008 financial crisis – a period remarkable for the sharp deterioration in productivity growth across many advanced economies – we identify three outstanding features: historically low growth in capital intensity, digitization, and a weak demand recovery. Together these features help explain why annual productivity growth dropped 80%, on average, between 2010 and 2014, to 0.5%, from 2.4% a decade earlier.

Start with historically weak capital-intensity growth, an indication of the access labor has to machinery, tools, and equipment. Growth in this average toolkit for workers has slowed – and has even turned negative in the US.

In the 2000-2004 period, capital intensity in the US grew at a compound annual rate of 3.6%. In the 2010-2014 period, it declined at a compound annual rate of 0.4%, the weakest performance in the postwar period. A breakdown of the components of labor productivity shows that slowing capital-intensity growth contributed about half or more of the decline in productivity growth in many countries, including the US.

By digitization, we mean digital technology – such as cloud computing, e-commerce, mobile Internet, artificial intelligence, machine learning, and the Internet of Things (IoT) – that is moving beyond process optimization and transforming business models, altering value chains, and blurring lines across industries. What differentiates this latest wave from the 1990s boom in information and communications technology (ICT) is the breadth and diversity of innovations: new products and features (for example, digital books and live location tracking), new ways to deliver them (for example, streaming video), and new business models (for example, Uber and TaskRabbit).

However, there are also similarities, particularly regarding the effect on productivity growth. The ICT revolution was visible everywhere, the economist Robert Solow famously noted, except in the productivity statistics. The Solow Paradox, as it was known (after the economist), was eventually resolved when a few sectors – technology, retail, and wholesale – ignited a productivity boom in the US. Today, we may be in round two of the Solow Paradox: while digital technologies can be seen everywhere, they have yet to fuel productivity growth.

MGI research has shown that sectors that are highly digitized in terms of assets, usage, and worker enablement – such as the tech sector, media, and financial services – have high productivity. But these sectors are relatively small in terms of share of GDP and employment, whereas large sectors such as health care and retail are much less digitized and also tend to have low productivity.

The last feature that stands out in this period of historically slow productivity growth is weak demand. We know from corporate decision-makers that demand is crucial for investment. For example, an MGI survey conducted last year found that 47% of companies increasing their investment budgets were doing so because of an increase in demand or demand expectations.

Across industries, the slow recovery in demand following the financial crisis was a key factor holding back investment. The crisis increased uncertainty about the future direction in consumer and investment demand. The decision to invest and boost productivity was correctly deferred. When demand started to recover, many industries had excess capacity and room to expand and hire without needing to invest in new equipment or structures. That led to historically low capital-intensity growth – the single biggest factor behind anemic productivity growth – in the 2010-2014 period.

James Manyika is Chairman of the McKinsey Global Institute and a senior partner in McKinsey & Company’s San Francisco Office.

Myron Scholes, a Nobel laureate in economics.
Copyright: Project Syndicate.

 

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