Prior to the COVID-19 crisis, considerable attention focused on the long-term productivity slowdown observed across countries. This was referred to as the productivity paradox, as the productivity slowdown occurred at a time of significant technological change. The focus on productivity is expected to resurface and gain prominence, once the recovery from the COVID-19 crisis is fully underway.
The increasing diffusion of digital technologies in the 2000s was expected to spark a new wave of productivity growth, similar to those seen in the past, e.g. as a result of electrification (from the mid-1880s) and, to a lesser extent, ICT investments (in the 1990s). However, this has not, yet, materialised, raising a number of still largely open questions, ranging from the potential lagged effects of these new technologies, to structural factors, right through to measurement.
Indeed, a number of views have been put forward to address the paradox:
The transformative nature and scale of today’s technological breakthroughs pale into insignificance compared with those that took place in the past. The benefits from electricity, internal combustion engines, the invention of telephone and radio, spread out through the economy over many years. Recent innovations, such as ICT, although also revolutionary, have shown more rapid adoption and a shorter-lived impact on productivity and economic growth (Cowen, 2011; Gordon, 2012).
The pace of technological progress has not slowed but adoption requires parallel innovation in organisational structures and business models. The next wave of productivity growth driven by technology breakthroughs in artificial intelligence, robotics, the Internet of Things, Big Data, 3D printing, nanotechnology and biotechnology, may lag the innovations and take time to be fully deployed (Brynjolfsson and McAfee, 2011; Baily, Manyika and Gupta, 2013).
A breakdown of the diffusion machine. Some studies suggest that an important explanation for the productivity slowdown is the slowing pace at which innovations spread from the most globally advanced firms to the rest of the economy (OECD, 2015; Andrews, Criscuolo and Gal, 2016). More recent work has analysed the drivers of differences in firms’ ability to achieve productivity gains focusing, in particular, on managerial quality and workers’ skills. Preliminary evidence suggests that low managerial quality and the lack of ICT skills curb the adoption of digital technologies and the rate of diffusion (Andrews, Nicoletti and Timiliotis, 2018), and that more productive firms tend to employ a larger share of skilled employees and operate with a larger share of managerial roles (OECD, 2019).
Other structural changes. Another factor that may explain the longer-term decline in productivity growth across (developed) economies is the long-term shift from manufacturing to services, in particular the shift to lower productivity personal services. Demographic changes and more service orientated consumption patterns, notably from ageing populations, may exacerbate this effect. Nevertheless, a number of converging studies conclude that the impact of this phenomenon is limited so far (Barnett et al., 2014; Kierzenkowski et al., 2018; Riley et al., 2018; Sorbe et al. 2018, Mourougane and Kim, 2020).
Measurement. Several measurement challenges can limit the analysis of recent productivity trends. Many of these challenges concern longstanding issues relating to the measurement of factors of production and output, and especially the distinction between price and volume changes. New forms of doing business, driven in particular by digitalisation and the sharing economy, as well as the increasing importance of knowledge-based assets, have added new measurement challenges and exacerbated the long-standing ones. While the jury remains out on the underlying causes, a growing body of evidence has suggested that measurement, or rather “mismeasurement”, is not the cause (Syverson, 2017; Byrne, Fernald and Reinsdorf, 2016; Ahmad and Schreyer, 2016; Ahmad, Ribarsky and Reinsdorf, 2017).