While a great deal of literature explores the implications of introducing robots into the workplace for the labor market, there are still some studies that measure the quality of robots over time. This column uses data from the Japan Robot Association and the Bank of Japan to document significant declines in robot quality improvement in Japan over the past decade. The difference in robot quality growth rate between 2000 and 2010 is large, at about -3 percentage points per year.
With the rise of robots in the workplace, there is growing concern about whether robots will lose their jobs. In response to these social fears, educators have addressed this problem both theoretically and empirically (e.g. Acemoglu and Restrepo 2017, Baldwin 2019, Dauth et al. 2017, Michaels and Graetz 2015).
To date, however, no study has specifically investigated the rate of technological progress, such as the improvement of robotic quality. For any attempt to predict how robots will affect the macro-economy, it is essential to understand the progress of robot production and the way to improve the quality of robots, in recognition of the existing concerns of society. If the pace of robotic quality improvement slows down or has already slowed down, the fear of robots taking away human work can be allayed. In a new paper (Fujiwara et al. 2021), we aim to fill this gap.
Our research uses two innovative datasets to measure the amount of progress that has been made in improving the quality of robots in Japan between 1990 and 2018 – the production and shipment of manipulators and robots collected by the Japan Robot Association and the price index of corporate products from the Bank of Japan. First, we produce and run manipulators and robot datasets and create value-for-money robot price indices using three techniques: index numbers, stochastic and structural methods. We then measure the quality of each robot by the Corporate Product Price Index, an industrial robot price index that divides this quality-consistent quality by an unmatched price index.
Figure 1 shows the evolution of values per robot estimated using three methods. Despite the use of different approaches, there is no significant difference in trends. The pace of quality improvement per robot has slowed down or decreased significantly since 2010. The quality improvement per robot in the 2010s was about three percentage points lower annually than in 2000.
A) Index number system
B) Stochastic method
C) Structural method
Note:: All measurements were normalized to the logarithmic scale and in 1990 to zero.
The results of the reduction in the rate of development of robotic standards may be consistent with the results of recent studies by economists at the IMF and the Federal Reserve, such as Byrne and Pinto (2015) and Lian et al. (2019), which points to a decline in investment-specific technological advances, i.e., the slowdown in the relative value of capital goods with consumer goods. The main conclusion also implies that the hypothesis that ‘ideas are becoming harder to find’ has been supported by Bloom et al. (2020), may apply to robot production.
Since the estimates are based on different assumptions, the results should be considered with a certain degree of caution. Micro-level data for pricing and individual robot product features are required for more stringent quality adjustments. Furthermore, due to the advances in software, including algorithms and other factors, this analysis does not capture the breadth of robotic applications. The flow of measurement services from such obscure capital remains a problem for future studies.
Acemoglu, D and P Restrepo (2017), “Robots and Jobs: Evidence from the United States”, VoxEU.org, 10 April.
Baldwin, R (2019), “Globalization, Automation and the History of Work: Looking Back to Understand the Future”, VoxEU.org, 31 January.
Bloom, N., CI Jones, JV Rinen and M. Webb (2020), “Getting Ideas Harder?”, American Economic Review 110 (4): 1104-1144.
Byrne, D & E Pinto (2015), “Recent downturn in high-tech equipment prices and some implications for business investment and labor productivity”, notes FEDS.
Dauth, W, S Findeisen, J Südekum and N Woessner (2017), “The Rise of Robots in the German Labor Market”, VoxEU.org, 19 September.
Fujiwara, I, R Kimoto, S Shiratsuka and T Shirota (2021), “Measuring Robot Quality: Decreased Quality Improvement?”, CEPR Discussion Paper 16556.
Lian, W, N Novta, E Pugacheva, Y Timmer and P Topalova (2019), “The Value of Capital Products: The Driver of Investing in Threats”, VoxEU.org, 7 June.
Michaels, G and G Graetz (2015), “Estimating the Impact of Robots on Productivity and Employment”, VoxEU.org, 18 March.