Summary, metrics and ratings, and Manager's comments on Evaluation of “Artificial Intelligence and Economic Growth” by Aghion et al.
Evaluation 1 of “Artificial Intelligence and Economic Growth” by Seth Benzell
90% CI: (70,90)
Quality scale rating
“On a ‘scale of journals’, what ‘quality of journal’ should this be published in?: Note: 0= lowest/none, 5= highest/best”
90% CI: (3.5, 5.0)
See here for a more detailed breakdown of the evaluators’ ratings and predictions.
Manager’s note (David Reinstein): I converted math and Greek letters into latex format, mainly to demonstrate this capacity. I made no other changes.*
Thanks to the Unjournal for their invitation to review “Artificial Intelligence and Economic Growth”. In this essay the authors have three announced goals: Help set an agenda for research on the impact of AI on growth, refine research questions on the subject, and summarise and recontextualize key previous findings with an emphasis on Baumol’s cost disease. This is an ambitious task, but the authors largely succeed!
In the first four sections of the paper, the authors do a wonderful job of outlining a general neoclassical model of automation. They explain how the key parameters of the model determine the impact of automation. They distinguish between two types of economic singularity, and show how the more extreme variety emerges naturally from some parameterizations of their model – something which I believe is an important innovation of this paper (including above Nordhaus (2015) a direct antecedent paper). These models stimulate the reading researcher to ask how these parameters could be estimated, opening a door to applied economists to contribute to the macroeconomic question of growth and AI. After this, section 5 is a bit of a disappointment. It lists several additional economic phenomena that might be caused by AI and automation, and occasionally ties these ideas back to economic growth, but in a less organised way without the assistance of a model. The essay closes with empirical evidence on capital shares and automation, which was adequate for the time empirically, but is somewhat lacking in its interpretation of the data.
Let me start by going into detail about what I liked about the first several sections, including some complementary thoughts it inspired in me. Then I’ll explain what I consider the main factor omitted in these sections: the impact of automation and AI on saving and investment. I’ll close with some thoughts on the limitations of sections 5 and 6, and how they might be improved.
Section 2 of the paper lays out a general, neoclassical, model of automation, drawing on Zeira (1998) and Acemoglu and Restrepo (2016). The key equations are clearly presented. The authors highlight Baumol’s "cost disease" -- the phenomenon that an increase in output of one sector of the economy will make goods in a complementary sector more expensive -- as a key phenomenon to be understood for projecting AI and automation-led growth. '
The authors do a great job of highlighting the importance of “
The authors explain several special cases of their model, to explain how other parameters balance against each other as well. They focus on the role of “
Sections 3 and 4 go farther beyond the current state of the literature, introducing AI as an input to technology production functions and considering versions of an economic singularity. Section 3's formalization is clear, but I might have appreciated a note from the author that other approaches to modelling "AI in the idea production function" might be better -- whereas I think the model in section 2 is more solidly paradigmatic. The key parameter here turns out to be "
In section 4, the authors lay out what I think are the best taxonomy of economic singularities I've seen (I think the best alternative that would have been in the literature at the time would have been Nordhaus 2015's). While these are somewhat extreme scenarios, they immediately ground themselves by showing how a type I case is the natural result of the oldest economic model of automation -- the AK growth model. I would make the connection between the AK growth model and the "
I really appreciated these sections, and feel they do a generally good job at agenda setting for both theorists and applied researchers. For applied researchers, I think the way the paper identifies "
For the theorist, the mind swims with possible extensions to and variations on the approaches presented. Obviously a paper like this can't cover or even suggest every possibility. One might imagine variations of a growth model that allows for "
Still I do think that the authors fall down in not focusing more heavily on the role of saving in the model. Throughout the paper, the saving rate in the model is assumed to be constant — a hypothesis that isn't well grounded in either a representative agent model (which achieves a constant interest rate in the long run) or an OLG model (in which saving will be a function of many other considerations). I think this is an important oversight for a document that wants to set the agenda.
I’ll admit I’m a bit of a partisan for this issue, having considered it in (Benzell et. al. 2015) and (Benzell et. al. 2022). In the first paper, we show how in OLG models automation technologies can actually lower output and welfare for future generations. The reason is that savings are made by the young out of their labor incomes, for consumption in their retirements. When automation accumulates, the share of income going to young and laboring savers decreases, and the share going to old spenders increases. This reduces the amount which is saved and reinvested. In certain cases, the reduced saving effect is large enough to more than offset the productivity growth effect of automation. The possibility that a new technology could lower long-run output is not admitted for in the authors' model – ruling out certain conceptually coherent scenarios such as the one imagined in Asimov’s “The Caves of Steel” – where highly productive AGIs and automation exists, but a low saving and reinvestment rate by a socialist government keeps society impoverished.
More generally, the exogenous saving framework pursued by the authors doesn't allow for any inter-generational analysis of the impact of automation. On a more practical level, interpreting the decrease in the global interest rate as telling us something about automation (for example, see the recent "cite") needs to account for global demographic and distributional factors that have created a "global saving glut" (cite). In (Benzell et. al. 2021), we find that even a rate of automation at 5x the historical rate would fail to overcome this headwind and increase interest rates.
This brings me to the final section of the paper, on the evidence to date on automation and capital shares. Karabarbounis and Neiman (2014) is correctly taken as the starting point, and I think the discussion is ok for the time overall. My main quibble is with the characterization of Autor et. al. (2017) and Barkai (2017). These are presented as 'alternative theories of capital share's increase' but they're more like alternate theories of what
Acemoğlu, D., & Restrepo, P. (2016). The race between machines and humans: Implications for growth, factor shares and jobs.
Autor, D., Dorn, D., Katz, L. F., Patterson, C., & Van Reenen, J. (2020). The fall of the labor share and the rise of superstar firms. The Quarterly Journal of Economics, 135(2), 645-709.
Barkai, S. (2020). Declining labor and capital shares. The Journal of Finance, 75(5), 2421-2463.
Barkai, S., & Benzell, S. G. (2018). 70 years of US corporate profits (No. 277). Working Paper.
Benzell, S. G., Brynjolfsson, E., & Saint-Jacques, G. (2022b). Digital Abundance Meets Scarce Architects: Implications for Wages, Interest Rates, and Growth.
Benzell, S. G., Kotlikoff, L. J., LaGarda, G., & Sachs, J. D. (2015). Robots are us: Some economics of human replacement (No. w20941). National Bureau of Economic Research.
Benzell, S. G., Kotlikoff, L. J., LaGarda, G., & Ye, V. Y. (2021). Simulating Endogenous Global Automation (No. w29220). National Bureau of Economic Research.
De Loecker, J., Eeckhout, J., & Unger, G. (2020). The rise of market power and the macroeconomic implications. The Quarterly Journal of Economics, 135(2), 561-644.
Karabarbounis, L., & Neiman, B. (2014). The global decline of the labor share. The Quarterly journal of economics, 129(1), 61-103.
Nordhaus, W. D. (2015). Are we approaching an economic singularity? information technology and the future of economic growth (No. w21547). National Bureau of Economic Research.
Zeira, J. (1998). Workers, machines, and economic growth. The Quarterly Journal of Economics, 113(4), 1091-1117.
How long have you been in this field?
I started my PhD in Economics in 2012. I became interested in the impact of automation on economic growth shortly after, so about 10 years.
How many proposals and papers have you evaluated?
I have reviewed about 30 papers. I’d say about ⅓ to ½ of these are broadly on the subject of automation.