Wednesday, April 12, 2017

"Six Patterns Behind the US Productivity Slowdown "

From the Conversable Economist, April 7:
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....
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