With the advent of generative artificial intelligence (GenAI), the scope of AI has increased dramatically, but its effect on labour productivity remains uncertain. Some innovations raise labour productivity growth as adoption spreads but the effect fades when the market is saturated. In contrast, two types of innovation — general purpose technologies (GPTs) and inventions in the method of invention (IMIs) — have long-lasting effects on productivity growth. GPTs (1) are widely adopted, (2) spur knock-on innovations, and (3) show continual improvement, refreshing the innovation cycle. IMIs increase the efficiency of the research and development process via improvements to observation, analysis, communication, and organization. We conclude there is suggestive evidence that GenAI is both a GPT and an IMI, a sign that its adoption will lead to higher labour productivity growth in the future.
Read articleAbout this issue
This milestone 50th issue of the International Productivity Monitor brings together six contributions exploring artificial intelligence, intangible capital, manufacturing productivity, health care measurement, and the high cost of living.
Issue highlights
GenAI could become a general-purpose technology and a new method of invention, creating sustained productivity gains
U.S. productivity growth may be understated by up to 1.6 percentage points annually due to intangible investment measurement issues
The broad-based slowdown in U.S. manufacturing productivity --- which occurred despite rising R&D spending --- suggests that ideas are getting harder to find
Despite major advances in technology, productivity growth has slowed across advanced economies. Brynjolfsson, Rock and Syverson (2021) argued that, due to the large intangible investments associated with digitalization, total factor productivity (TFP) growth may be underestimated and be higher after the investment boom. The resulting gap between standard and revised measures produces a J-shaped pattern, the “productivity J-curve”.
Building on this work, we examine productivity estimates for five advanced economies: France, Germany, Japan, the United Kingdom and the United States. Using the estimated coefficients on intangibles (research and development, software, and organizational capital) in the value functions of listed firms over 2006–2020, we find that TFP underestimation caused by large intangible investments was largely unique to the United States, and was much smaller in Europe and Japan. This result is consistent with the recent productivity rebound in the U.S. and reinforces the call for investment in innovation in Europe and Japan.
Read articleWhy did U.S. manufacturing productivity stop growing after 2010? Productivity growth actually disappeared, from an annual rate of +3.3 per cent during 1987–2010 to -0.3 per cent from 2010 to 2023. This article shifts attention from 2010 as the start of the productivity growth slowdown to a decade earlier when output stopped growing. This cessation of output growth in 2000 is attributed to the invasion of imports that closed domestic plants, destroyed jobs, and squeezed profits.
After 2000, a chain of causation followed that ultimately undermined productivity growth — from falling capacity utilization, to lower investment in fixed capital and research and development, and an erosion of innovation. Beyond the import invasion, the disappearance of productivity growth is also attributed to a general phenomenon of diminishing returns to innovation, the feeble influence of robots, government regulations that distorted investment, and a shrinking supply of skilled labour in the face of increasing skill demands.
Read articleU.S. manufacturing labour productivity growth fell from roughly 3.5 per cent per year over 1987–2007 to near zero over 2010–2022. Growth in total factor productivity (TFP) also fell to near zero over the same period. This article examines the sources of that slowdown by decomposing manufacturing productivity growth into contributions from leader and follower firms within frontier and laggard industries. We find that the slowdown is broad-based: both for labour productivity and TFP, productivity growth declined among both leaders and followers, across alternative weighting methods, and multiple industry groupings. Standard models of economic growth treat research and development (R&D) as the primary channel through which firms generate productivity growth.
The broad-based nature of the slowdown raises the question of whether the translation of R&D expenditures into productivity gains has weakened. We estimate an R&D production function at both the industry and firm levels and find that the elasticity of productivity with respect to R&D is consistently larger in the earlier period than in the full sample, even as R&D expenditure has risen across firms and industries. These results suggest that the slowdown reflects declining research productivity rather than reduced innovation effort.
Read articleUnderstanding health care productivity is critical, as the sector accounts for about 17 per cent of U.S. gross domestic product. However, official statistics likely understate productivity growth by failing to capture improvements in medical technology and treatment quality. The Health Care Satellite Account (HCSA), developed by the U.S. Bureau of Economic Analysis, addresses this gap by measuring spending by medical condition, enabling more meaningful output measurement. We present a simple framework that combines the HCSA with population health data to adjust prices and output for quality improvements. Output is defined as marginal health gains rather than service counts, consistent with prior recommendations.
This approach approximates more comprehensive methods while remaining tractable. Our results suggest substantial quality-adjusted productivity growth that is largely masked in official statistics, implying a downward bias of about 1.5 percentage points per year, with a range from 0 to over 5 percentage points. Productivity gains may be larger in other high-income countries, where life expectancy has increased more and spending has grown more slowly.
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This commentary examines persistent concerns about the cost of living among Canadians, a phenomenon also observed across many developed economies. Despite macroeconomic indicators showing that household income has generally grown faster than prices in recent years, approximately 60 per cent of Canadians identify the cost of living as a primary concern.
Drawing on polling data, economic statistics, and policy literature, the analysis identifies housing affordability, slowing real income growth, and social media–driven financial perceptions as key drivers. The commentary concludes that policy responses should prioritize housing supply, productivity growth, and stronger worker bargaining power to ensure that economic gains translate into improved household welfare.
Read articleEditors' Overview
The publication of the 50th issue of the International Productivity Monitor (IPM) marks an important milestone for the journal. Since its founding 25 years ago, the IPM has now published 350 articles by academics and policy practitioners from around the world. The journal’s success reflects the leadership and dedication of Andrew Sharpe. His founding role and long-standing stewardship as Managing Editor established the IPM as a respected forum for international knowledge exchange on productivity issues. We look forward to building on the strong foundation he established.
To inform the journal’s future direction, we conducted a survey of IPM contributors and readers. Respondents rated the journal highly, citing as key strengths its focus, empirical rigor, policy relevance, and international perspective. The survey also identified opportunities to further expand the journal’s reach and impact, while preserving its core strengths. These opportunities include several new initiatives that are underway, such as enhancing the dissemination of findings through accompanying blogs, webinars, and podcasts, improving data accessibility, and modernizing the journal’s design and website.
This 50th issue contains six contributions covering five broad themes: artificial intelligence, intangible capital, manufacturing productivity, health care measurement, and the high cost of living. Martin Baily, David Byrne, Aidan Kane and Paul Soto open the issue with a wide-ranging review article that examines the potential for generative artificial intelligence (GenAI) to provide a sustained productivity boost. They argue that GenAI exhibits characteristics of both a general-purpose technology and an invention in the method of invention. Based on the available evidence, they conclude that GenAI could generate lasting future productivity gains through widespread diffusion, complementary innovations, and more efficient research and development. However, the authors also warn that productivity gains from AI may be delayed or limited by slow adoption, organisational hurdles, and risks of overinvestment.
The second article, by Ahmed Bounfour, Kazuma Edamura, Takayuki Ishikawa, Tsutomu Miyagawa, Alberto Nonnis and Konomi Tonogi, analyzes the productivity “J-curve” — the idea that large investments in intangible assets associated with digitalization may result in official statistics underestimating total factor productivity (TFP) early in the investment boom. Examining empirical evidence for five advanced economies, they find that J-curve effects are largely unique to the U.S. and have been much smaller in Europe and Japan. Their estimates highlight the role of software investments in the United States and suggest that standard U.S. TFP growth measures may be underestimated by up to 1.6 percentage points annually. The authors conclude by calling for more aggressive investment in digital innovation in Europe and Japan.
The next two articles, originating from a CSLS session at the 2026 American Economic Association Annual Meeting, examine why U.S. manufacturing productivity growth slowed so dramatically, falling from an annual rate of 3.3 per cent during 1987-2010 to -0.3 per cent during 2010-2023.
Robert Gordon and Kenneth Ryu argue that the disappearance of productivity growth after 2010 can be traced back a decade earlier, and partly attributed to the surge in U.S. manufacturing imports that began around 2000 — roughly the time when China joined the World Trade Organization. They show that increased U.S. manufacturing imports came not only from China, but also from other lower-wage economies such as Mexico. They find these imports ultimately weakened domestic manufacturing production, capacity utilization, profitability, investment and innovation activities. Beyond import competition, the authors also point to diminishing returns to innovation, regulatory distortions, and a shortage of skilled labour as contributing factors.
Danial Lashkari and Jeremy Pearce further examine the sources of the slowdown by decomposing U.S. manufacturing productivity growth into contributions from leader and follower firms within frontier and laggard industries. They demonstrate that the slowdown was broad-based. It occurred across productivity measures, using multiple industry groupings, and for both leaders and follower firms. The broad-based nature of the slowdown raises the question of whether the translation of research and development (R&D) expenditures into productivity gains has weakened, as suggested by Gordon and Ryu. The authors estimate an R&D production function at the industry and firm levels and find that the elasticity of productivity with respect to R&D is consistently larger in the earlier period than in the full sample period, even as R&D expenditure rose across firms and industries. These results suggest that the slowdown reflects declining research productivity rather than reduced innovation effort and are consistent with the “ideas getting harder to find” hypothesis.
The fifth article, by Calvin Ackley, Abe Dunn, Eli Liebman and John Romley, seeks to better understand health care productivity in the United States. Productivity is a critical issue for a sector that accounts for 17 per cent of U.S. GDP. However, official statistics likely understate productivity growth by failing to capture improvements in medical technology and treatment quality. The U.S. Bureau of Economic Analysis has developed a Health Care Satellite Account (HCSA) to try to address this gap by measuring spending by medical condition, thus moving from an input to an output-based measurement in health care. The authors present a framework that combines the HCSA with population health data to adjust output prices for quality improvements. In this framework, “output” is defined as marginal health gains rather than traditional service counts or hours worked. Their results suggest substantial quality-adjusted productivity growth that is largely absent in official statistics. They speculate that health care productivity gains might be even larger in other high-income countries, where life expectancy has increased more than in the United States while health care spending has grown more slowly.
The 50th issue concludes with a commentary by Claude Lavoie that studies persistent concerns about the high cost of living among Canadians. The issue is pervasive, despite macroeconomic indicators showing that household income growth has generally outpaced inflation in recent years. Drawing on polling data, economic statistics, and policy literature, the author identifies housing affordability, slowing real income growth, and social media–driven financial perceptions as key drivers. The commentary argues that policy responses should prioritize housing supply, productivity growth, and stronger worker bargaining power to help ensure that economic gains translate into improved household welfare.