Hope for J-Shaped Productivity Growth

This article summarizes the December 2020 Finance & economics report by The Economist. The report collects research to support the idea that the pandemic could stimulate productivity growth. The report builds up to this productivity growth opportunity thesis slowly and systematically as follows:

By way of introduction, “[p]roductivity is the magic elixir of economic growth” because it “is the ultimate source of long-run increases in income.” Productivity growth is defined generally as producing more from available resources.

However, economists generally do not have a full understanding of productivity growth but have established some drivers. For example, labor productivity growth (more output per worker per hour) is driven by raising education levels, increasing capital investments per worker, and adoption of innovations. Total factor productivity growth (more output per total inputs) on the other hand, is driven by “the reallocation of scarce resources from low-productivity firms and places to high-productivity ones”, technological progress, and business model evolution.

From a historical perspective, productivity growth has occurred in surprising, seesawing bursts. For example, “[t]he brutal years of the 1930s were followed by the most extraordinary economic boom in history.” But then “productivity growth decelerated sharply in the 1970s from scorchingly high rates in the post-war decades.” Then, “[a] burst of higher productivity growth in the rich world, led by America, unfolded from the mid-1990s into the early 2000s.” This growth is attributable to the technological efficiencies wrought by computerization in many industries. Specifically, “improvements in manufacturing techniques, better inventory management and rationalisation of logistics and production processes made possible by the digitisation of firm records and the deployment of clever software.”

Emerging markets also saw productivity growth in this time period but not as much from the technological revolution of computerization, but from more mundane, but more profound factors. Specifically, their productivity growth was brough on by “high levels of investment and an expansion of trade which brought more sophisticated techniques and technologies to the developing-economy participants in global supply chains.”

However, the financial crisis caused a “broad-based and stubbornly persistent slowdown in productivity growth” in more than 70% of the economists around the world and that has persisted largely to this day.

Forebodingly for the present day, “[a]ccording to research by the World Bank, countries struck by pandemic outbreaks in the 21st century (not including covid) experienced a marked decline in labour productivity of 9% after three years relative to unaffected countries.”

The productivity growth funk that we have found ourselves in (and face going forward) has been difficult to explain. “The World Bank reckons slowing trade growth and fewer opportunities to adopt and adapt new technology from richer countries may have helped depress productivity advances in the emerging world. Across all economies, sluggish investment in the aftermath of the global financial crisis looks a culprit: a particular problem in places with ageing and shrinking workforces. Yet while these headwinds surely matter, the bigger question is why new technologies like improved robotics, cloud computing and artificial intelligence have not prompted more investment and higher productivity growth.”

To explain this recent lack of productivity growth, economists have largely settled on three hypotheses, one of which holds promise for expectations of productivity growth.

The first hypothesis is that recent technological developments have not been as transformative as past advances. However, this is questionable because technological advances have been ongoing and are increasingly used (see remote working and remote operational technologies).

The second hypothesis, made famous by Larry Summers (former Treasury Secretary and former President of Harvard University), is that weak demand and weak spending by the government and consumers have reduced investment on the supply side.

The third and most hopeful hypothesis has been recently developed by Erik Brynjolfsson and Daniel Rock, of MIT, and Chad Syverson, of the University of Chicago. Brynjolfsson et al. developed the hypothesis of the “productivity J-curve” that both explains the recently underwhelming productivity growth despite all the recent technological advancements and predicts exploding productivity growth in the foreseeable future.

Specifically, Brynjolfsson et al. propose that [a]s new technologies are first adopted, firms shift resources towards investment in intangibles: developing new business processes. This shift in resources means that firm output suffers in a way that cannot be fully explained by shifts in the measured use of labour and tangible capital, and which is thus interpreted as a decline in productivity growth. Later, as intangible investments bear fruit, measured productivity surges because output rockets upward in a manner unexplained by measured inputs of labour and tangible capital.”

The J-Curve can be observed in the 1990’s when computer technologies developed in the 70’s and 80s started to be used productively by industry.

The Economist contends that “the pandemic quickened the pace of technology adoption” and points to “[a] survey of global firms conducted by the World Economic Forum this year[, which] found that more than 80% of employers intend to accelerate plans to digitise their processes and provide more opportunities for remote work, while 50% plan to accelerate automation of production tasks.”

These investments could be the ingredients for future rapid propductivity growth, especially in the services sector. For example, “the boost to distance education and telemedicine delivered by the pandemic could help drive a period of growth in services trade, and the achievement of economies of scale in sectors which have long proved resistant to productivity-boosting measure.”

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