A couple of recent reports review the evidence about the productivity slowdown. Gustavo Adler, Romain Duval, Davide Furceri, Sinem Kiliç Çelik, Ksenia Koloskova, and Marcos Poplawski-Ribeiro have written an IMF Discussion Note called \”Gone with the Headwinds: Global
Productivity (April 2017, SDN/17/04). Over at the McKinsey Global Institute, James Manyika, Jaana Remes, Jan Mischke, and Mekala Krishnan have written a Discussion Paper on \”The Productivity Puzzle: A Closer Look at the United States\” (March 2017). Both reports offer an overview of the productivity slowdown, along with discussion of possible causes and policy recommendations.
At least for me, the underlying causes of the productivity slowdown, which has now been going on for more than a decade, are not yet clear. Thus, my approach is to compile a bunch of patterns and try turn them over in my mind, trying to figure out a sensible way in which they fit together. In a similar spirit, the authors of the McKinsey report write:
\”We identify six characteristics that provide further insight into the productivity growth slowdown: declining value-added growth, a shift in employment toward lower productivity sectors, a relatively small number of sectors experiencing jumps in productivity, weak capital intensity growth across all types of capital, uneven rates of digitization across sectors (especially the large and often relatively low-productivity ones), and slowing business dynamism.\”
Here\’s some additional description of these six factors: of course, the McKinsey report has more detail.
1) Productivity is output divided by a measure of inputs, like labor hours worked. Changes in the growth rate of productivity can be driven by either the numerator or the denominator. The most recent productivity slowdown seems to be a numerator problem.
\”Looking closely at productivity growth, we find differences in the role the denominator, hours-worked growth, and the numerator, value-added growth, have played in recent years. For example, the period between 1995 and 2004 is considered an era of high growth with annual productivity growth averaging about 3 percent. However, we have found two distinct periods within this decade. The first is from 1995 to 2000 when productivity growth spiked, driven primarily by an increase in growth of real value-added output. Value-added output growth for the total economy, which averaged 3.4 percent annually from 1991 to 1995, increased to 4 percent from 1995 to 2000, a period of booming consumer and IT spending. As a result, productivity growth increased from 1.4 percent to 2.0 percent. The subsequent era of 2001 to 2004 was a period of continued high productivity growth, averaging 3.6 percent a year. However, the underlying driver was a decline in hours-worked growth, which fell to negative 0.2 percent partly as a result of the tech crash and the restructuring wave in manufacturing of the early 2000s. So while these two periods are typically treated as a single period of booming productivity growth, we prefer to separate them as the implications for investment, industry evolution, and job expansion are very different. …
\”What is striking about productivity growth after the recession ended in 2009 has been low value-added output growth compared with past periods.32 Growth in real value-added output has declined to 2.2 percent between 2009 and 2014. This compares to growth of roughly 3 to 4 percent in prior time periods.\”
2) A shift of the economy to sectors with slower productivity growth \”reduced productivity growth by 0.2 percentage points every year for the private business sector between 1987 and 2014, as employment transitioned from high-productivity manufacturing sectors to lower-productivity sectors such as health care and administrative and support services.\”
Of course, this raises a question about how well the \”output\” of these service sector jobs are measured: for example, perhaps certain jobs in health care care do more to improve health than they did 30 years ago, but that benefit is probably not well-captured in the economic statistics.
\”The productivity boom of 1995 to 2000 was characterized by an exceptional combination of sectors experiencing a productivity acceleration: large employment sectors such as retail and wholesale experienced accelerating productivity at the same time as rapid productivity growth was occurring in sectors such as computer and electronic products. … During the boom, the number of accelerating sectors for many years was above 20 out of 60 sectors analyzed, in some years making up as much as 30 to 40 percent of total hours worked. In 1995, for example, these included sectors such as retail trade, wholesale trade, finance, and computer and electronic products. Recently only six sectors recorded significant productivity growth acceleration, and those sectors made up only 2 to 7 percent of total hours worked, and 5 to 8 percent of value added. These sectors included oil and gas extraction, petroleum and coal manufacturing, and transportation.\”
4) The slowdown of productivity growth has been accompanied by a slowdown in investment.
\”In the period from 1995 to 2004, there was a boom in capital intensity growth across most assets, particularly in information capital and software. This period is associated with high labor productivity growth. What is striking is that the most recent period, 2009 to 2014, coincides with both exceptionally low productivity growth and low capital intensity growth across all types of assets. Thus, this period has not only been exceptional due to the lack of accelerating productivity sectors, but the low pace at which capital services per hour worked has been rising, across all forms of capital.\”
A slowdown across all types of suggests that the underlying causes are not about a certain kind of technology or industry, but rather are broader in scope.
5) Many low-productivity sectors also lag in digitalization, which tends to be associated with higher productivity.
\”[W]e calculate that the US economy is realizing only about 18 percent of its digital potential with large sectors lagging behind. Our use of the term digitization and our measurement of it encompasses: the digitization of assets, including infrastructure, connected machines, data, and data platforms; the digitization of operations, including processes, payments and business models, customer and supply chain interactions; and the digitization of the workforce, including worker use of digital tools, digitally-skilled workers, and new digital jobs and roles. While the information and communication technology, media, financial services, and professional services sectors are rapidly digitizing, other sectors such as education and health care are not … Indeed, the largest sectors by output and employment, and often those with relatively low productivity growth, tend to be the ones lagging in digitization. … Frontier sectors today have four times the level of digitization of frontier sectors 20 years ago. Yet the rest of the economy continues to significantly lag behind even historical digitization levels of frontier sectors; their level of digitization is only 60 percent that of leading sectors 20 years ago.\”
6) The US economy seems to be less dynamic, in the sense that it is doing a less good job of reallocating jobs and capital away from slower-growth sectors and toward higher-growth sectors.
\”Productivity growth can increase if the share of employment and output in more productive firms increases even while employment and output fall in less productive firms. However, Decker and coauthors find that such a reallocation is happening to a lesser extent in the post-2000 period, particularly in the high-tech sector, with implications for overall productivity growth. Beyond the decline in overall dynamism, there is evidence that the gaps between high- and low-performing companies are widening. Analysis by the OECD finds growing divergence in productivity levels of global frontier firms relative to others since 2001, which the OECD interprets as a symptom of slower productivity diffusion. According to their analysis, frontier firms have continued to raise their productivity levels. This suggests it is a lack of diffusion of best practices that is driving the slowdown in productivity growth, rather than a lack of innovation of the productivity frontier. …
\”Likewise, digital trends vary widely across firms. Companies are using digital tools to raise the bar in operational efficiency, customer engagement, innovation, and workforce productivity. But they vary widely in how they are pursuing such opportunities, which could be driving large differences in productivity across firms. A McKinsey survey of 150 large companies evaluated respondents on 18 practices related to digital strategy, capabilities, and culture to arrive at a metric called the “Digital Quotient”. The distribution curve of this quotient reveals a striking gap between the digital leaders and laggards. Putting the above findings together would suggest that while the productivity gap between firms has been widening, the reallocation of labor from less to more productive firms has waned.\”