Measuring Productivity in the Context of Technological Change by Diane Coyle 3

WORK IN THE AGE OF DATA BBVA OPENMIND DATA, IDEAS, AND PROPOSALS ON DIGITAL ECONOMY AND THE WORLD OF WORK BBVAOPENMIND.COM Work in the Age of Data 2 Measuring Productivity in the Context of Technological Change by Diane Coyle 3 Productivity matters because over the long run it is the measure of how much more effectively a society can turn its available resources into valued goods and services. Stated in this general way, it is the ultimate indicator of progress; and, indeed, productivity growth at “modern” rates significant- ly above zero began with the Industrial Revolution. However, measuring productivity is not straightforward, and linking its behavior to the underlying drivers still less so. Since the mid-2000s there has been Measuring Productivity a slowdown in trend productivity growth in many OECD economies, often described as the “productivity puzzle” precisely be- in the Context of cause its causes are not understood—and particularly because the pace of innovation in fields including digital, biomedicine, and Technological Change materials appears to be at last as rapid as ever (fig. 1). The standard approach is “growth accounting,” the attribution of real terms of Diane Coyle GDP growth to growth in measured inputs of capital and labor and a residual, known as multifactor or total factor productivity (TFP) growth.1 TFP is where technological progress, innovations enabling more output for the same inputs, ought to show up. However, the measured residual also includes the effects of failing to measure all inputs well, or omitting some of them. Over time the measurement of capital and labor inputs has become more sophisticat- ed, with adjustments for the skill level of workers, for example, or the introduction of some types of intangible capital. These im- Technological change is making it harder to provements chip away at the unexplained interpret disappointing productivity figures in residual, which Moses Abramovitz famous- 2 many economies. Although there are likely to ly labeled “the measure of our ignorance.” be many contributory factors, such as post- For example, a recent literature has identi- fied the importance of management quality financial crisis debt overhang and demographic for productivity at the firm level.3 If it were change, technological change complicates the possible to include an aggregate measure interpretation of the evidence in two ways. One of national management quality in the is the delay between companies adopting new growth accounting exercises, as a form of technologies and their impact on productivity intangible capital, this would reduce mea- because of the organizational or management sured TFP. changes and the complementary investments Its residual character thus makes TFP that are also needed. The other is the mismatch somewhat unintuitive. A more intuitive, between how official GDP and productivity and more easily measured, alternative is la- figures are defined and the character of the bor productivity. This is simply real GDP per hour worked. It also makes it easier to see digital economy, such as zero price, advertising- the role of technology, as embodied in capi- funded services, or the switch to cloud tal equipment. For example, a construction computing. A more fundamental question is worker becomes more productive not by whether “productivity” is a useful concept in digging faster with a shovel or taking few- economies consisting to such a large extent of er rest breaks, but by having a mechanical services and intangibles. digger to work with instead. So we should Work in the Age of Data 4 Since the mid-2000s there expect periods of technological change to and bookshops are full of warnings about has been a slowdown in manifest themselves in faster labor produc- the likely effect of the next wave of robotics productivity growth in many tivity growth as well as faster TFP growth. on jobs, but there is absolutely no sign yet OECD economies, a trend However, whichever is selected, pro- of the robot apocalypse as that would cer- often described as the ductivity measures now pose a puzzle. Al- tainly have boosted the labor productivity “productivity puzzle” though the pace of innovation continues, on figures. the face of it, to be very rapid, all measures There are three potential explanations for The technological innovations of productivity growth have slowed signifi- this paradox. of the first half of the 20th cantly, particularly since the mid-2000s. In One prominent perspective is that it the UK, where the slowdown has been par- is more apparent than real, and that, in century had profoundly ticularly marked, the level of labor produc- fact, there has been far less technological more important economic tivity is about one-fifth lower than it would innovation than the hype would lead us to consequences than today’s be had the pre-crisis trend continued. But believe. Robert Gordon is a forceful advo- incremental improvements in labor productivity growth has slowed ev- cate of this view. In his book The Rise and digital entertainment or the erywhere across the OECD. Fall of American Growth he argues that digitalization of services Any complex phenomenon will have the technological innovations of the early a number of contributory factors, and in to mid-twentieth century, such as indoor this case the drawn-out effects of the finan- plumbing, electricity, or the initial com- cial crisis on firms’ investment spending, munications technologies of telegraph, decreasing competition in key economic telephone, and radio, had profoundly more sectors, or adverse demographic change in important economic consequences than the OECD countries are all plausible parts today’s incremental improvements in dig- of the productivity story.4 Still, there is a ital entertainment or the digitalization of striking paradox in the combination of existing services and products. While Gor- seemingly rapid innovation in a number of don has a narrow focus in terms of today’s technological fields—advanced materials, frontier technologies, his argument has biomedicine, green energy, autonomous had some support from recent estimates vehicles, small satellites, the “Fourth In- of a sharp decline in research productivity.5 dustrial Revolution” in manufacturing— It is not only Moore’s Law that is showing and dismal productivity figures. The media signs of running out of steam; the number 1975 1980 1985 1990 1995 2000 2005 2010 2015 8 6 4 2 0 -2 Annual % Change Year France Netherlands Fig. 1. Labor productivity growth 1970–2018, selected countries Germany Spain (Source: https://stats.oecd.org) Italy United Kingdom Japan United States Measuring Productivity in the Context of Technological Change by Diane Coyle 5 of researchers in the United States is more tions and hence the GDP and productivity in 5G communications. In recent work on than twenty times greater now than in the statistics. Economic historian Paul David the importance of intangible investments 1930s, and yet there has been a long-run provided a canonical example of the long such as business process redesign, new trend decline in TFP growth for some forty delays between innovation and productivity business models, or additional investments years now. outcomes in his 1999 study of the adoption in human capital for the use of technologies Not surprisingly, given the range of in- of electricity in the early twentieth century. such as artificial intelligence, Erik Bryn- novations reported currently, the technol- Not only was new infrastructure needed for jolfsson and his colleagues characterize this ogy community is dismissive of the claim distribution networks; as David pointed out, as a “productivity J curve,” whereby innova- that the pace of change is slowing. It is hard crystallizing the benefits of electricity also tion leads to lower productivity before any to evaluate the claim that there are severely required major investments such as new improvements are observed.9 Some of the diminishing returns to new ideas. Part of low-level factory buildings configured for current much-hyped innovations, such as the impact of new technologies may never assembly lines in place of old mills built AI and machine learning systems, or the be measured or measurable. For instance, over several stories around their steam en- Internet of Things, are anyway not yet as if today’s renewable energy technologies gines’ drive shafts. Additionally, getting the widely deployed in business as headlines enable the decarbonization of electricity full benefit of the assembly line required in- would suggest so it remains to be seen if generation, this will represent a profound- novations in management techniques and they will live up to expectations. Others— ly important innovation that will never be workflow organization. In that case the lag such as computing, discussed below—are captured in GDP or productivity measure- between original innovations and full pro- widely used, however. ment because the carbon externalities are ductivity impact was some fifty years.6 The final possible explanation concerns not included. A discovery like the use of Research on the initial wave of the dig- the difficulty in measuring productivity. mini-aspirin doses—a cheap and old com- ital revolution also highlighted the impor- This line of explanation also has its skep- pound—to help prevent cardiovascular tance of management and organizational tics. A number of studies have explored the illness will extend many lives but hardly change, leading to either delays, or even potential for measurement error and con- affects the growth statistics at all. failure on the part of some firms to gain cluded that, if anything, the measurement In general, GDP as a value-added mea- any productivity benefit from their invest- difficulties were even greater before the sure does not reflect well innovations that ments in information and communication mid-2000s, so this argument deepens the improve the efficiency of production pro- technology equipment.

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