Growing Adoption Rates of ICT have Counterbalanced the
Productivity Slowdown in Advanced Economies
By Mun S. Ho, Koji Nomura, Jon D. Samuels1
May 8, 2024
Debates about the economic policy response to stagnating productivity growth in advanced economies
start with identifying the proximate causes of the slowdown, which is no easy task, and targeting policy
to those causes. Sayed and Gordon (2019) argued that “decelerating technical change, rather than slowing
investment, was the primary driving force in the transatlantic slowdown.” Another VoxEU column “Reevaluating the sources of the recent productivity slowdown” (Winkler, Koutroumpis, Lafond, & Goldin,
2021) concludes that technological change “remains a key factor behind current macroeconomic trends
and underpins the observed slowdown through various dimensions,” with additional contributions from
slower growth of capital per worker, slower growth of global trade and changes in “allocative efficiency.”
At the policy level, the 2024 Economic Report of the President of the United States (Council of Economic
Advisors, 2024) contains 126 mentions of productivity.2 Chapter 7 of the report is entirely devoted to
Artificial Intelligence, discussing economic and regulatory policy to measure, evaluate, and manage the
emerging technology.
This column focuses on technological change via the lens of total factor productivity (TFP) growth, which
was also identified as a key measure of innovation by the U.S. Department of Commerce (Advisory
Committee on Measuring Innovation in the 21st Century Economy, 2008). We developed a detailed
cross-country dataset to measure the industry sources of economic growth in the U.S. and Japan using
“modern growth accounting” (Inklaar, Van Ark, & Fernald, 2022). These accounts carefully define
comprehensive outputs and inputs in constant quality (or composition adjusted) units that are matched
to appropriate price deflators (e.g. including land inputs, imputing consumer durable capital services,
using quality adjusted prices for computers and other high-tech devices). Mismeasurement is a serious
concern in growth accounting as discussed by Winkler et al. (2021), but the dataset that we have
developed incorporates the most detailed and comprehensive data that we are aware of.
Here we summarize two conclusions about technological change over the 1955-2019 period reported in
(Ho, Nomura, & Samuels, 2023). Our first finding is that the slowdown in productivity growth in the
Computer sector explains a significant portion of the aggregate productivity slowdowns in both
countries. The “Computer” sector contains many of the high-tech devices that drive investment in ICT
(Information and Communications Technology), including computer and peripheral equipment
manufacturing, communications equipment manufacturing, and semiconductor manufacturing.
1
The views expressed in this paper are solely those of the authors and not necessarily that of the U.S. Bureau of
Economic Analysis (BEA), the U.S. Department of Commerce.
2
Just a simple word count of “productivity” within the report.
Figure 1 shows the contribution of productivity growth in the Computer sector to aggregate total factor
productivity growth in the U.S. and Japan (this is the “standard” contribution and is essentially the
Domar weight multiplied by TFP growth in each industry). The horizontal dotted lines represent the
averages over sub-periods. The peak contribution was during 1995-2004 in both countries and there is a
very clear step-down pattern in the contribution of TFP growth in the computer sector since then.
Toward the end of this period, the contribution of the computer sector resembled what it was before
the late 1960s when Moore’s Law took hold. Between the 1995-2004 and 2004-2019 sub-periods,
aggregate TFP growth decelerated by 0.52pp in the U.S. and by 0.22pp in Japan. In the U.S., the
slowdown in TFP growth in the computer sector accounted for 0.30 of these 0.52pp and in Japan it
accounted for 0.27pp of the aggregate productivity slowdown. That is, the slowdown in computer sector
productivity growth accounted for more than half of the aggregate TFP slowdown in the U.S. and for the
entire slowdown in Japan. We emphasize that Computer is a small sector in both countries, its share to
total value-added never exceeded 2.3% in either country. The notion that the deceleration in ICT TFP is
an important factor is not new to the productivity studies community, but the magnitudes that we
measure, and the methods that we used that are consistent with the framework of the national
accounts, provides strong evidence on the disproportionate importance of the production of ICT to
productivity growth in advanced economies.
The second conclusion from our research is new and concerns how TFP growth affects the cost of capital
and thus the price of aggregate output. The cost-of-capital mechanism is intuitive: productivity growth
in ICT drives down the price of investment in ICT and thus the cost of capital of any sector that invests in
ICT. Since use of ICT capital has been growing steadily over time, this effect has been growing over time
and counterbalances some of the deceleration in the direct contribution of TFP growth in ICT to
aggregate TFP growth shown in Fig. 1. (The magnitude of this “cost-of-capital effect” involves the TFP
growth rate in ICT, the weight of ICT in the capital input of each sector, and the share of capital input in
total inputs.) Figure 2 shows the economy-wide impact of this cost-of-capital mechanism relative to the
standard contributions of Computer TFP. The sub-period averages of this ratio are rising over time in
both countries. The key conclusion is that this effect has been growing in importance since the mid
1990’s, coinciding with the increasing adoption of ICT that was initiated with the acceleration of
semiconductor technology growth and the resultant rapid fall in ICT prices (Jorgenson, 2001). In broad
terms, ongoing technological progress in the computer sector has made using ICT capital in production
cheaper (relative to what prices would have been without this technological progress), and this falling
cost has allowed producers across all industries to charge lower prices for their goods and services.
Our two findings reinforce the close attention paid to developments in the ICT producing sectors when
analyzing the sources of aggregate economic growth. One, productivity in these sectors is of
disproportionate importance to aggregate productivity growth in advanced economies, and two, these
innovations carry over to industries that make use of computing technology. While the first has
decelerated, the second has accelerated since the mid-1990s. Importantly, the use of ICT technology is
much more widespread across industries and countries than its production, so that aggregate economic
gains from ICT adoption across the world economy may soon (or already may) outpace the standard
measured contribution of ICT productivity to aggregate productivity growth. The relationship between
emerging technologies and measured productivity growth is of keen interest to those studying the
sources of, and prospects for, economic growth. For example, there are discussions of how general
purpose technologies require complementary investments and new processes and thus cause a
productivity J-curve (Brynjolfsson, Rock, & Syverson, 2021). Whether we will observe a large, delayed
response for productivity, or not, we have demonstrated that the impact of existing technologies is
significantly broader than previously identified. There is an ongoing economic impact of past computer
sector productivity growth via high ICT adoption today that should be recognized in a more refined
dynamic accounting of the sources of growth.
1.00
0.80
Percentage points
0.60
0.40
0.20
0.00
-0.20
-0.40
1955
U.S.
(period average)
1965
1975
1985
1995
Japan
(period average)
2005
2015
Figure 1: Contribution of TFP Growth of the Computer sector to aggregate TFP Growth. The contribution is defined as the
Domar-weighted industry TFP growth rate.
0.80
Ratio of contributions
0.70
U.S.
(period average)
Japan
(period average)
0.60
0.50
0.40
0.30
0.20
0.10
0.00
1955
1965
1975
1985
1995
2005
2015
Figure 2: Contribution of the cost-of-capital effect relative to the direct TFP effect of ICT on aggregate TFP.
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