Written with AI: The 2025 book by Marc Fasteau and Ian Fletcher Industrial Policy for the United States: Winning the Competition for Good Jobs and High-Value Industries, notes: “A major problem with mainstream economics, once one gets past recitations of free-market theology and looks at the actual scholarship, is that it is only good at understanding things that are well suited to mathematical modeling, such as price setting in freely competitive markets. It has weak insight into organization, management, corporate strategy, R&D, engineering, workforce development, the origins of technology, product design, policymaking by governments, and the strategies nations use to compete. None of these reduce to equations well, but they are central to how modern firms, governments, and thus economies function. Even some fields that do mathematize well, such as finance and international trade, are prone to oversimplifications that lead to false conclusions.”
Fasteau and Fletcher are not just attacking the results of mainstream economics; they are attacking its tools. Their argument is that the field’s obsession with “mathiness”—using complex equations to model simple, idealized behaviors—has effectively lobotomized its ability to understand the messy, non-linear realities of industrial power.
Several recent essays and papers wrestle with these exact themes:
1. “The Wrong Kind of Maths” by Tim Harford (October 2025)
In this essay, Harford explores the “unreasonable ineffectiveness of mathematics in economics.” He echoes the book’s claim that mainstream models are “Newtonian”—excellent at calculating the trajectory of a falling apple (or a price point in a competitive market) but useless at understanding the “biological” complexity of a firm’s R&D strategy or a nation’s geopolitical maneuvering. He argues that because things like “engineering” or “workforce development” cannot be reduced to a clean $y = f(x)$ function, they are treated as “exogenous shocks” rather than the core of the economy.
2. “Model-First Culture and the Social Ontology Gap” by Tony Lawson (2025)
Lawson, a long-time critic of mathematical formalism, published a series of interviews and papers in late 2025 that align perfectly with the book’s critique. He argues that the “mainstream” has a “model-first” culture where, if a phenomenon (like corporate strategy or policymaking) doesn’t fit into a mathematical model, the economist concludes the phenomenon is “unscientific” or unimportant. Lawson refers to this as “social ontology”—the study of what the social world is actually made of—and claims economics has replaced reality with a “mathematical fantasy world.”
3. “The Everything-Bagel Liberalism and the Physics of Building” by Ezra Klein and Derek Thompson (2025)
While more of a policy essay (linked to their 2025 book Abundance), this piece wrestles with the “R&D and engineering” gap. They argue that the US government and mainstream economists have spent decades focusing on the “demand side” (subsidies, taxes, and money) because it is easy to model. Meanwhile, they have ignored the “supply side”—the actual physics of how you build a semiconductor plant or train a precision machinist—because those “non-mathematical” frictions (regulations, management, tacit knowledge) don’t look good in an equation.
4. “Mathiness in the Era of Industrial Rivalry” – Various Authors (2024-2025)
Following Paul Romer’s earlier critiques, several papers in the Journal of Institutional Economics (2025) have picked up the “Industrial Policy” mantle. They argue that:
Finance and Trade: These are “mathematized” to a fault, leading to the “false conclusions” Fasteau and Fletcher mention (e.g., the idea that capital flows are always efficient).
The Competitiveness Gap: They suggest that nations like China and Germany succeed because their policymakers don’t use “mathiness” as a shield; they use “management” and “workforce strategy” as their primary tools.Fasteau and Fletcher’s book is effectively the “manifesto” for a new alliance of thinkers who want to move past the free-market theology and replace it with what they call “advantageous industry” analysis. They suggest that if you can’t model a nation’s ability to build a rocket or a vaccine, your “economic science” is actually just a high-status form of ignorance.
Lawson identifies a persistent, widespread hostility toward methodological analysis within mainstream economics. He argues that this is not accidental but serves a specific institutional function:
The Shield of Ignorance: Mainstream economists discourage methodology—often explicitly and boldly—to prevent the discipline from identifying obstacles to an “emancipated” economics.
Preventing Criticism: This aversion serves to block criticism of the heavy emphasis on mathematical modeling and to stifle the development of alternative approaches.
The “Selection” Defense: Elite figures like Frank Hahn argued that economics foundations “look after themselves” through a selection process where “good” foundations prosper and “bad” ones wither, effectively telling young economists to give no thought at all to methodology.
Mathematical Modeling as Ideology
Lawson suggests that the obsession with math is not a neutral scientific choice but a form of ideology.
The Cultural Belief: There is a widespread, almost faith-based cultural belief that for a field to be “scientific,” it must take a mathematical form.
Irrelevance as a Feature: Lawson argues this ideology contributes to the irrelevance of mainstream economics but serves to sustain the status quo by deflecting criticism away from the underlying economic system.
The “Closed System” Problem: He asserts that mathematical modeling is fundamentally ill-suited to social analysis because it requires “closures” (isolated atoms in a closed system), whereas social reality is “open” and contingent.
The “Nudge” and Behavioral Pivot
Lawson provides a sharp ontological critique of this Nudge group:
Old vs. New Behavioralism: While “old” behavioral economics (like Herbert Simon’s) was more grounded, “new” behavioral economics is largely a deductivist modeling endeavor.
Maintaining the Atomistic Assumption: In most cases, these “modern” behavioral models still assume atomistic agents who maximize preference relations using standard equilibrium concepts. They consider more “realistic” effects but still assume optimizing agents, essentially staying within the neoclassical paradigm.
The Nature of Heterodoxy
Finally, Lawson defines the real essence of the “heterodox” opposition as an ontological conception rather than just a policy disagreement. While the mainstream project relies on mathematical-deductive methods that assume isolated atoms, heterodox traditions (like Post-Keynesianism or Institutionalism) focus on openness, internal relationality, and social structures
