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Verena Halsmayer on Managing Growth in Miniature: Solow’s Model as an Artifact

New Books Network

Mon Nov 24 2025

Summary

Podcast Summary: Verena Halsmayer on Managing Growth in Miniature: Solow’s Model as an Artifact

Podcast: New Books Network – Peoples and Things
Host: Lee Vinsel
Guest: Verena Halsmayer
Date: November 24, 2025

Episode Overview

This episode explores Verena Halsmayer's award-winning book, Managing Growth in Miniature: Solow’s Model as an Artifact. Halsmayer, a postdoctoral scholar at the University of Vienna, discusses the iconic Solow growth model and its role not just as a theory but as a practical tool and a product of its scientific and institutional milieu. The conversation delves into how economic reasoning, especially around growth and technological change, emerged, stabilized, and spread through the work of Robert Solow and his peers. Halsmayer emphasizes the cultural, material, and practical dimensions of economic modeling and traces the afterlives and ironies of the Solow model in policy, teaching, and development.

Key Discussion Points and Insights

The Book’s Intent and Approach

Understanding Economic Reasoning as Practice
- Halsmayer aims “to better understand economic reasoning,” focusing not just on economy theories or ideas, but on how these are rooted in “historically specific and culturally framed practice that is done with specific tools” ([04:43]).
- She brings a historian of science perspective, considering modeling and measurement as practices, not simply abstract ideas.
Importance of the Solow Model
- The Solow growth model is credited with explaining economic growth and the importance of technological progress. However, Halsmayer interrogates what "explaining growth" and "technological progress" actually mean in the context of economic reasoning ([08:49]).
- The Solow model formalized a certain style of economic reasoning—mathematical modeling—that became dominant between the 1930s and 1960s ([06:21]).

What Is the Solow Growth Model?

Model Features
- Presents a “self-sustaining economic equilibrium” via a simple mathematical formula—a frictionless world assuming full employment, perfect competition, and perfect foresight ([08:49]).
- Key finding: population growth and capital investment alone can't account for growth rates; the residual is attributed to technological change ([08:49–13:16]).
The “Solow Residual”
- When the model is deployed empirically, the gap between input and output growth becomes the “Solow residual” or “Total Factor Productivity” (TFP)—labeled technological progress, though it captures everything not explained by the model, including “social, political, cultural factors, and measurement errors” ([14:52–15:43]).
- Memorable moment: “Technology was just the label put on the residual, on the rest.” — Verena Halsmayer ([15:06])

Models as Tools and Practices

Method and Theoretical Framing
- Halsmayer draws from philosophers and historians such as Mary Morgan, Marcel Boumans, and Harold Moss, looking at models as artifacts and practices ([17:12]).
- Her approach moves beyond “doctrine” to investigate "specific intellectual cultures, social worlds...research and teaching, institutional and material conditions" ([24:37], [25:41]).
Teaching and Disciplinary Norms
- The Solow model is not just a research tool but a teaching device: “if you want to be an economist, this is how you do it” ([27:00]).
- Robert Solow at MIT was seen as “the teacher,” emphasizing collegiality and open workshop culture ([27:20]).

Performativity, Policy, and the Life of Models

Performativity vs. Interventionist Knowledge
- While related to performativity literature (i.e., models shaping reality), Halsmayer is more focused on “how the problem of growth was constituted through the model,” and the model’s unintended afterlives ([29:37]).
- Models can develop a life of their own, sometimes leading to regret among their creators ([31:01]).
Interventionist Knowledge
- Halsmayer co-edited a special issue on “interventionist knowledge,” examining how social science tools informed post-war policy across states, businesses, and organizations ([32:00–33:43]).
- One of the ironies: models or knowledge devices are often used in ways “other than intended, led to different outcomes than expected, or was simply ignored” ([33:43]).

The Book's Structure and Solo’s Place in the Story

Halsmayer intentionally avoids a hero biography of Solow, focusing sparsely on him as a person ([34:17–35:50]).
Tracking the model’s place among “parallel constructions”—Solow’s became dominant, but she resists simplifying into hero/villain narratives ([35:45], [38:09]).

The Model’s Flexibility and Political Afterlives

Interpretive Ambiguity
- The Solow model’s very abstractness and simplicity made it widely adaptable—and ambiguous. It “could be interpreted in a variety of different ways,” making it a vehicle for both state-driven and market-driven policy ([49:13–53:50]).
- Quote: “A model is ambiguous enough that you can kind of project your uses and desires...and use it for your ends.” — Lee Vinsel ([53:27])
Policy Device and Knowledge Infrastructures
- The model became embedded in macroeconomic forecasting, planning models, and policy evaluation even as the details changed ([54:36–57:41]).
- “It’s not only about the acceptance of a specific theory...but really about the hegemony of a specific kind of problematization through the tools and infrastructures of knowledge.” — Verena Halsmayer ([57:41])
Political Ironies
- Salo’s model is sometimes directly associated with neoliberalism, but in fact, its politics are “far from obvious”—it has served many different projects and worldviews ([67:53–69:07]).
- Halsmayer’s focus: “It’s the politics of the knowledge” ([68:21]).

The Model and Technology Studies

Computerization and Modeling
- Halsmayer addresses the crossover between economics and computing—Solow’s is a “sweet, sweet exercise in comparison” to computationally more complex input-output models ([62:18–63:21]).
- She traces empirical labor: transforming raw industrial data into usable model form ([63:52–64:42]).
- Shift: From rich, discursive documentation of empirical problems (e.g., NBER) to the dominant style of mathematical abstraction with little methodological transparency ([64:44]).

Current and Future Work

From Economic Planning to Alternative Planning
- Halsmayer is now researching “alternative economic planning,” specifically the Lucas Plan (1975–82), an industrial worker initiative for socially useful production in the UK ([74:23–76:34]).
- Focus: How knowledge, calculation, and participatory planning technologies moved across domains, aiming to show that alternative forms of organizing production could also be economically viable.

Notable Quotes & Memorable Moments

On Economic Models as Practice:
“I think what is most important to me was to not think of economists’ knowledge as a set of theories or ideas, but rather as a practice, like historically specific and culturally framed practice that is done with specific tools.” — Verena Halsmayer ([04:43])
On the Solow Residual:
“Technology was just the label put on the residual, on the rest.” — Verena Halsmayer ([15:06])
On Teaching the Model:
“If you want to be an economist, this is how you do it.” — Verena Halsmayer ([27:00])
On Interpretive Flexibility:
“A model is ambiguous enough that you can kind of project your uses and desires...and use it for your ends.” — Lee Vinsel ([53:27])
On Political Complexity of the Model:
“It is one additional small-scale storyline of market thinking that maybe tones down a little the break of the 1970s in that it focuses on the tenacity and resilience of governmental knowledge infrastructures… the sources of neoliberal governance are not only the ideas of the big names…” — Verena Halsmayer ([69:07])
On Ongoing Measurement Debates:
“You can see the computer age everywhere but in the productivity statistics.” — (After Solow’s famous quip, cited at [72:27])

Important Timestamps

[04:43] — Verena summarizes the book’s purpose and approach to economic reasoning.
[08:49–13:16] — Explaining the Solow Model and Solow Residual.
[14:52–15:43] — What “technology” actually means in the model.
[17:12] — Influence of historians of science and philosophy, rubric of “models as artifacts.”
[27:00] — The Solow model’s role in teaching economics.
[29:37–33:43] — Models, performativity, and interventionist knowledge.
[34:17–35:50] — Decision not to make the book a biography of Solow.
[49:13–53:50] — Ambiguity of the model, “carrier” for divergent political could-be’s.
[57:41] — The persistence of knowledge infrastructures and models.
[67:53–69:07] — Ironies, politics, and the model’s adoption.
[74:23–76:34] — Halsmayer introduces her research into the Lucas Plan and alternative planning.

Final Thoughts

This episode offers a richly layered exploration of how economic thinking is shaped, taught, and institutionalized, using the Solow growth model as a lens. Halsmayer’s work complicates the triumphalist or villainous readings of economics’ “great men” and their models by highlighting the practices, ambiguities, and unforeseen consequences in the long afterlife of a paradigm. The conversation is interspersed with personal and professional anecdotes, careful attention to the materiality of knowledge, and a humility regarding the ongoing limits of economic measurement—a perfect listen for anyone interested in economics, science studies, or the politics of expertise.

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Transcript

A (0:00)

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A (8:49)

Okay, so most commonly I would say the model is credited with explaining economic growth and illuminating the importance of technological progress and innovation. And it was actually one of the goals when I started this to just very basic, investigate what does that mean? What does explaining growth and illuminating the importance of technological progress mean in the context of this kind of reasoning? When you look at this model, it features a self sustaining economic equilibrium. So it is expressed in the form of a linear differential equation. And just in a nutshell, it's about growth, growth of output, of national income. It's the same in this model, determined by output and saving. So labor is given outside the model and capital always adapts flexibly. So we have output, we have capital and labor, the both the two inputs and both of them in this equilibrium are fully employed. So we have the assumption there is full employment, we have the assumption of perfect compet repetition and we have the assumption of perfect foresight. So every future development is known in the present. And then the basic. So this is a very curious world, right? I mean there's no questions of power, there is no land, no energy, there is no environmental depletion. It's just a smooth, very smoothly working mathematical world. There's only one good. There is no uncertainty, no risk. It's really this frictionless cosmos. And what the model then it was published in 1956 in this dominant version by Robert Solow. And the argument of the paper is then population growth and capital investment are not enough to increase this equilibrium growth rate. It can only be changed through additional factors such as technological change. So the thing is, and this was really fascinating for me that contemporary economists, they said this is not about a new idea of growth or it's not about like there were already works talking about the importance of technological progress for growth. That was nothing new. But what was new was the form of the model in the sense that it provided a very neat and simple like for those who could deal with the mathematics mechanism to think about growth in this very specific mathematical world. So to me it seemed then that this model equipped the post war vocabulary of growth, development and productivity with a very essential efficient image of a manageable mechanism that would lead toward an ever more prosperous future like manageable growth.

B (44:55)

Yeah, no, that. It was very helpful for me because I got onto this stuff. Well, I mean, first of all, I should have Made clear earlier. Maybe I shouldn't. This gets very incestuous, but. But Erik Hountschel's father, David Hounschel, is my doctoral advisor. That's how I met Eric in the first place. And David had me read. I don't know if you ever bumped into this thing. There's Nathan Rosenberg, this economist, but a kind of historically interested economist for sure. Fascinating guy on the economics of technology. I think it's like around 70 or so. He puts together a. Basically a kind of edited. It could be like a textbook on the economics of technology. I can't remember the title off the top of my head, but I have it in a very prominent place in my office. And it has. I'm pretty sure it has Salow's 57 article Technical Change in the Aggregate Production Function in it. So, I mean, David had kind of reared me in that stuff. Right. It was part of my training that this was going on in the late 50s. And like, this is like it comes out in the innovation delusion. All my stuff on innovation. People don't realize that I was like trained into this way of thinking, like very early on. But it was only later, once I discovered Gordon and these other people writing about the economics of technology, that I really went. Went back and read that 57 article closely. And I think for me, I just assumed you totally have disabused me of this notion. But I just saw it as a kind of ex nilo thing that it was like a total invention. I think one of the things I really like about your chapter is that it shows. It's like it's fitting into these much. There's all kinds of growth accounting and other people have models of this stuff. It's something that people are doing at that moment. Right. And he fits into a much broader thing. And then again, I think you kind of said it earlier, but it was like the. You know, the beauty or parsimony maybe that allowed it to travel beyond in ways that those other ones.

A (53:50)

Is that would be one part. Yes. So it could become a carrier of. Of more market fundamentalist views that Solo was comfortable with and an exemplar for the belief in the omnipotence of markets. But then there is also still another side, like when you look at it as a. Like, not as a set of ideas or theories to trace how the model turns into a part of what, for instance, Daniel Hirschman or Elizabeth Pop Berman have called policy devices. So this links to the performativity literature, but not in the sense that we look at market devices, but policy devices or the epistemic infrastructures of policy making. And here, of course, you said it before in terms of R and D measurements, but also more generally like the neoclassical growth model just, just took part and further pushed the trend to subject policy to an economic evaluation. And this is maybe still quite known. What I found, what I found really interested is that when I started to trace a few ways the model went, there were less invisible, less visible ways. For instance, in economic planning, like as part of these large scale macro econometric forecasting and planning models, which were some kind of of decision support systems in the field of macroeconomic planning. So it was still a very technical notion of planning. It was basically the organization and intellectual foundation for policy making. So it was not about larger political programs for planning. And also here, even if you couldn't see, these models had integrated a neoclassical growth model to talk about the long run and to say which kind of policies should be chosen if the goal was to have this and that growth rate by the year 1980, something like that. It was also again about imagining possible future worlds and to play the what happens if game and tracing ways how to achieve them through macroeconomic management. So this was another way the model got implemented in policy making. And the thing that ties in with the special issue that you mentioned before is that the model infrastructures that evolved from the interventionism of the 1950s and 60s, they remain rather stable. So I mean of course this is something where case studies have to be made. But this technique of forecasting translates well into the 1970s and way beyond. So either alongside newer techniques such as DSGE models, but also if these macroeconomic forecasting models were adapted and became more detailed, the foundational architecture still remained relatively stable. So this would be like one argument how it's not only about the acceptance of a specific theory or the adoption of a specific technique, but really about the hegemony of a specific kind of problematization through the tools and infrastructures of knowledge.

B (65:34)

And best fit is. Is still kind of. I can't remember. What is it? Oh, God. It has to do with inference. It's best fit. Yeah. Yeah. I mean, is this still very common in, like, business school? Kind of more positivist research in business schools are still doing. Talking about best fit a lot as a kind of. I'm sorry that I'm just having a brain fart at the moment. My business school friends are going to be ashamed of me. Okay, so. And I do have business school friends. You know, I know it disappoints people, but. So. Okay, so I want to talk to you about. Second, about politics and ironies. And so I thought you put it pretty well that in the history of economic thought, we have heroes and villains, and we have a lot written in that mode, both of those modes. And who the heroes and villains are, of course, depends on where you sit in the world. Like, if you're a member of the libertarian Mercatus center at George Mason University, then Hayek and Friedman and all these characters are like, they're the best. But if you're, I don't know, Morawski or Melinda Cooper or any number of other folks, then, like, you know, it's the neoliberal thought collective, and there's that whole literature. But I see you as kind of, you know, I see you. You have a chapter or a chapter, not a section on politics in your introduction that I thought was really nice. And it starts off with this kind of very bold quotation, just saying, like, that Salo's model is neoliberalism. You know, it's just like a declaration. I can't remember who you're quoting. But then. Then you kind of deconstruct that and pull it apart and say, you know, Salo's politics are not that obvious. He's kind of. He's kind of complicated and doesn't fit anywhere neatly. And it also reminds me of kind of like Eric's work on Paul Lazarusfeld, the sociologist, also not somewhere you can just kind of pin down. And so I wanted to talk to you about that, about the kind of attention to. And we can call it ironies that's what, you know, I think that's how we thought about it in the interventionist knowledge special issue. But yeah, I mean, I think you hear what I'm saying?