Sep 2026· Working paper (Federal Reserve Bank of Cleveland)· 0 citations
TL;DR
It is found that AI is complementary to the high-skill–equipment composite and that the AI weight in production remains small, and the estimated model implies different effects of alternative AI shocks.
Abstract
We model artificial intelligence (AI) as a distinct capital input in a nested CES aggregate production function that extends work done by Krusell et al. (2000) and embed it in a dynamic general equilibrium economy. By bringing the model to the data, we estimate the degree to which AI either substitutes for or complements the other production inputs at the aggregate level. We find that AI is complementary to the high-skill–equipment composite and that the AI weight in production remains small. We then use the model to study how this complementarity shapes the macroeconomic and distributional effects of AI capital accumulation. The estimated model implies different effects of alternative AI shocks. A rise in the AI usage share is contractionary as it increases reliance on a scarce complementary input. A fall in AI prices is expansionary due to the lower cost of accumulating AI capital. A tax on AI capital income raises limited revenue while the AI capital stock remains small, but can finance welfare-improving transfers as the AI price falls. A large-scale universal basic income (UBI) funded jointly by a consumption tax slows AI investment with welfare gains for low-skill workers at the expense of losses for high-skill workers and entrepreneurs. On the measurement side, we construct a quality-adjusted AI price index from hedonic regressions and build a corresponding AI capital stock.
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Christina Anderl, G. Caporale· CESifo working papers· 0 citations
Abstract This paper constructs a multi-sector general equilibrium model to analyze the impact of artificial intelligence (AI) on structural transformation, by examining the complementary and substitutive relationships between AI and high- and low-skilled labor, as well as the differences in labor skill intensity across...
Wei Jiang, Xing-Da Chen, Shi-Cheng Ni· China Finance and Economic R...· 0 citations
This paper investigates the aggregate impact of Artificial Intelligence (AI) technology on labor productivity, exploiting patent data in OECD countries during 2000-2017. We first document that after accelerating in 2000, the issuance of AI technology related patents has more than tripled by 2017 and OECD countries held...
It is shown that countries have narrowed gaps in capital and schooling more readily than gaps in productivity, and the Intelligence Divide is therefore not simply about access to AI, but about the capacity to turn knowledge into productivity.
P. Imam, Jonathan R. W. Temple· IMF Working Papers· 0 citations
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