Measuring robot quality: Slowing improvement is a possibility

Ippei Fujiwara, Ryo Kimoto, Shigenori Shiratsuka, Toyoichiro Shirota 19 May 2022



As the introduction of robots into the workplace increases, there is a growing concern over whether robots will cause human jobs to disappear. In response to this societal fear, academics have tackled this issue from both theoretical and empirical angles (e.g. Acemoglu and Restrepo 2017, Baldwin 2019, Dauth et al. 2017, Michaels and Graetz 2015).

However, to date, no study has specifically investigated the rate of technological progress, namely, the quality improvement of robots. For any attempt to predict how robots will affect the macroeconomy, in recognition of society’s existing anxiety, it is vital to understand the progress of robot production and the quality improvement path of robots. If the pace of quality improvement in robots slows down or has already diminished, fear regarding robots taking human jobs away may dissipate. In a new paper (Fujiwara et al. 2021), we aim to fill in this gap.

Our study uses two novel datasets – Production and Shipments of Manipulators and Robots collected by the Japan Robot Association and the Corporate Goods Price Index from the Bank of Japan – to measure the amount of progress made in improving robot quality in Japan between 1990 and 2018. First, we construct quality-unadjusted robot price indices using the Production and Shipments of Manipulators and Robots dataset and three techniques: index number, stochastic, and structural approaches. We then measure quality per robot by dividing this quality unadjusted price index by the Corporate Goods Price Index, an industrial robot price index that is quality-adjusted.

Figure 1 showsa the evolution of quality per robot estimated using the three approaches. Despite different approaches being used, there is no significant difference in trends. The pace of quality improvement per robot has slowed or decreased significantly since 2010. The rate of quality improvement per robot in the 2010s was around three percentage points per annum lower than in the 2000s.

Figure 1

a) Index number approach     

b) Stochastic approach


c) Structural approach


Note: All measures are in logarithmic scale and normalised to zero in 1990.

The result of the decline in the rate of quality improvement of robots may be in line with the findings of the recent studies by economists at the IMF and Federal Reserve such as Byrne and Pinto (2015) and Lian et al. (2019), which point to a decline in investment-specific technological progress, i.e. a slowdown in the pace of decline in the relative price of capital goods to consumer goods. The main conclusion also implies that the hypothesis that ‘ideas are getting harder to find’, advocated by Bloom et al. (2020), may apply to robot production.

As the estimates are based on various assumptions, the results should be treated with a certain degree of caution. Micro-level data for prices and product characteristics for individual robots are needed for more rigorous quality adjustments. Furthermore, this analysis does not capture the expansion of the range of robot applications due to advances in software, including algorithms and other factors. Measuring service flows from such intangible capital remains an issue for future studies.


Acemoglu, D and P Restrepo (2017), “Robots and jobs: Evidence from the US”,, 10 April.

Baldwin, R (2019), “Globalisation, automation and the history of work: Looking back to understand the future”,, 31 January.

Bloom, N, C I Jones, J V Reenen and M Webb (2020), “Are Ideas Getting Harder to Find?", American Economic Review 110(4): 1104-1144.

Byrne, D and E Pinto (2015), “The Recent Slowdown in High-tech Equipment Price Declines and Some Implications for Business Investment and Labor Productivity”, FEDS Notes.

Dauth, W, S Findeisen, J Südekum and N Woessner (2017), “The rise of robots in the German labour market”,, 19 September.

Fujiwara, I, R Kimoto, S Shiratsuka and T Shirota (2021), “Measuring Robot Quality: Has Quality Improvement Slowed Down?", CEPR Discussion Papers 16556.

Lian, W, N Novta, E Pugacheva, Y Timmer and P Topalova (2019), “The price of capital goods: A driver of investment under threat”,, 7 June.

Michaels, G and G Graetz (2015), “Estimating the impact of robots on productivity and employment”,, 18 March.



Topics:  Productivity and Innovation

Tags:  robots, skill biased technological change, job displacement, Japan, automation

Professor of Macroeconomics, Keio University and Australian National University; CEPR Research Fellow

PhD student, Pennsylvania State University

Professor, Faculty of Economics, Keio University

Associate Professor, Aoyama Gakuin University


CEPR Policy Research