Financial bubbles are not accidents. They are, according to Byrne Hobart and Tobias Huber, the primary mechanism through which societies finance bets too risky for ordinary capital circuits. This is the central thesis of Boom, published in 2025, and it challenges post-2008 crisis orthodoxy with a historical rigor one would not have expected from such a subject. The book arrives at the right moment: as American venture capital finances a wave of AI agents at an unprecedented pace, the question of whether European regulation is wisdom or a handicap has never been more concrete.
The Essentials
- Hobart and Huber argue that speculative bubbles have historically financed transformative infrastructure that rational capital would never have financed alone.
- Post-2008 macroprudential regulation aims to limit excess risk and credit, with variable effects depending on instruments and countries, but also on the space for radical experimentation that accompanied them.
- The AI agent market, driven by American venture capital, grows at 44-45% per year. Global market forecasts for this sector point to $53 billion by 2030, contemporary proof that speculative capital continues to finance transformative technologies in loosely regulated zones.
- Europe, more tightly regulated, struggles to grow its radical startups at the same pace.
- Boom poses the question of whether one can institutionalize the right to radical experimentation without reproducing the fragility of 2008.
Who are Hobart and Huber, and where does this book come from
Byrne Hobart is an American financial analyst and author of The Diff, an influential newsletter on markets, technology, and long-form economic thought. Tobias Huber is a German researcher specializing in the philosophy of technology and the history of financial systems. Their collaboration is improbable on paper—a market practitioner and a philosopher of technique—and that is precisely what makes Boom interesting. The book reads neither like a libertarian pro-market pamphlet nor like an academic critique of financial capitalism. It reads like an inquiry.
The underlying argument: from the Erie Canal to the transcontinental railroad, from the internet boom to American fracking, various breakthroughs, both public and private, have been associated with dynamics that the authors compare to those of financial bubbles. Investors lost money. Societies gained infrastructure.
The Central Argument: The Bubble as Involuntary Public Good
Hobart and Huber do not defend bubbles for their own sake. They document a precise mechanism.
Rational capital—pension funds, banks, insurers—demands predictable revenue streams and valuable assets. It finances well the expansion of what already exists. It finances poorly what does not yet exist, whose value depends on network externalities and infrastructure effects that only materialize at scale and over the long term. The American railroad of the nineteenth century was worth little if the West was not populated. It was worth a great deal if millions of people settled there.
No rational investor could evaluate this bet. The bubble financed it anyway.
What the authors call “public tolerance for failure” is the condition for this financing. When society accepts that investors lose fortunes on failed bets, it indirectly subsidizes the bets that succeed. The dot-com bubble destroyed billions. It also contributed to overinvestment in certain telecommunications infrastructure, while the main Internet protocols came largely from earlier public programs.
Carlota Perez, a Venezuelan-British economist whose work on technological revolutions is authoritative, had already described this mechanism in Technological Revolutions and Financial Capital (2002). Hobart and Huber acknowledge her explicitly. Where Perez analyzed the cycle descriptively, Boom adopts a normative stance: if this mechanism is productive, the deliberate reduction of leverage after 2008 deserves to be justified.
2008 as a Turning Point: When Prudence has a Hidden Cost
The post-crisis response to the Lehman Brothers collapse was a massive overhaul of financial regulation. Basel III, Dodd-Frank, strengthened capital ratios, reduced leverage on bank balance sheets: the goal was to make the system more resilient. It became so. But Hobart and Huber show that this resilience has a price that does not appear in prudential balance sheets.
Less leverage means less risk-taking, thus less radical experimentation. According to the authors, the 2010s were a decade of productivity stagnation in advanced economies, not because ideas were lacking, but because the capital capable of financing long-term bets had become scarce.
Tyler Cowen, an American economist whose work on secular stagnation is a reference, had posed the same diagnosis in The Great Stagnation (2011), attributing the slowdown to the exhaustion of technological “low-hanging fruit.” Hobart and Huber propose a complementary reading: the fruit was not exhausted; the capital capable of picking it was missing.
The argument becomes uncomfortable here. Post-2008 regulation had a long-term cost in terms of experimentation, and this cost has never been seriously accounted for in economic policy trade-offs.
The Contemporary Case: AI Agents as a Productive Bubble Unfolding
American venture capital is today the primary financing circuit for AI agents, systems capable of acting autonomously in complex environments. The market for these agents grows at 44-45% per year and is projected at $53 billion in the United States by 2030, according to data provided. This growth rate corresponds to no short-term profitability model. Most companies financed in this sector lose money. Some will continue to lose it for years.
Hobart and Huber would likely read this as a sign of health, not pathology. Venture capital plays here the role that railroad bonds played in the nineteenth century: it finances a bet on future infrastructure whose value depends on network effects that will only materialize after millions of users have adopted it.
The contrast with Europe is striking and documented in our analysis of the EU Chips Act. Europe invests in semiconductors, has world-class universities, and produces leading AI researchers. But European AI growth financing remains limited compared to the United States, and retention of AI researchers depends on several factors. Stricter regulation, on data protection, labor law, and stock market rules, is not the sole explanation. But it is an explanation.
Johan Norberg, in his recent work on the geography of human potential (Peak Human), examines whether cultural optimism is a condition of radical innovation or merely its symptom. His thesis of “decline by choice” suggests that societies that accept stagnation have decided it, even unconsciously. Applied to Europe, it suggests that regulation that reduces the space for experimentation may reflect a set of institutional and cultural choices.
The Book’s Blind Spots: What Hobart and Huber Don’t Say
Boom is a stimulating book. It is also a book that chooses its battles.
First blind spot: not all bubbles produce transformative infrastructure. The subprime bubble of 2008 produced overvalued houses in abandoned suburbs and a crisis that destroyed millions of jobs. Japan’s credit bubble of the 1980s left a lost decade. Hobart and Huber tend to select bubbles that turned out well. The argument would be more robust if it integrated an analysis of the conditions that differentiate a productive bubble from one that is simply destructive.
Second blind spot: the question of profit capture. When the internet bubble financed fiber optic cable, the infrastructure remained. But the profits of the following decade were captured by a few large platforms, to the detriment of broader competition. This phenomenon, documented by Thomas Philippon in The Great Reversal, shows that the collective benefit of a bubble can coexist with a concentration of gains that widens inequality. Our analysis on the relationship between capital and labor documents that in several economies, inequality and the share of capital income have risen since the 1980s, and the speculative cycle contributes to this.
Third blind spot: the book is primarily American in its examples and sensibility. The argument does not travel well into contexts where financial institutions are different, where the relationship to risk is culturally distinct, or where market failures run deeper. South Korea, for example, produced global technology champions without an ecosystem of venture capital comparable to Silicon Valley’s, through other institutional and state mechanisms.
Institutionalizing the Right to Experimentation by 2030-2040
Boom raises, without fully answering, the central question for the next decade: designing institutions that preserve the space for radical experimentation without reproducing the systemic fragility of 2008 remains an open problem.
The post-crisis response prioritized the reduction of systemic risk, with possible economic trade-offs but without declared acceptance of stagnation. The next decade compels exploration of other trade-offs, because AI, energy, and biotechnology may require large-scale financing, sometimes difficult to mobilize with very prudent capital.
Several avenues exist, though none has yet been proven at scale. The first is institutional separation: dedicated investment vehicles for radical experimentation, capitalized publicly or by institutional investors with a long mandate, would function as controlled bubbles, with the risk of loss explicitly accepted. Bpifrance in France or DARPA in the United States play partly this role. But their scope remains limited against the sums at stake in the AI wave.
The second avenue is regulatory: creating zones of risk tolerance, broadened regulatory sandboxes, where companies can experiment with business models or technologies without being subject to the full prudential framework. The United Kingdom attempted this in fintech after 2016, with mixed but real results.
The third avenue, harder to institutionalize, is cultural: rebuilding social tolerance for entrepreneurial failure, what Norberg associates with the cultural optimism of growth societies. Europe punishes failure more severely than the United States in its bankruptcy codes, financing systems, and in the signals its universities send to researchers who want to start companies.
None of these avenues solves the problem of profit capture. A zone of radical experimentation financed publicly or semi-publicly can produce transformative infrastructure whose profits are then privatized. This is a recurring model: the internet benefited from initial public investments, GPS is an American public infrastructure used commercially by private companies, and mRNA vaccine technologies benefited from substantial public investments before and during the pandemic, then were commercialized notably by private companies. Mazzucato has documented this meticulously. The dilemma is not choosing between experimentation and stability.
It is knowing who benefits from experimentation when it succeeds.
The signal to watch through 2030 is simple: economies that manage to maintain a space for radical experimentation while avoiding a systemic crisis will produce decisive data on the viability of the dilemma. For now, experience remains limited. Boom poses the question with more force than its predecessors. That is already a great deal.
What Makes This Book Valuable
Boom addresses readers thinking through the economics of innovation, financial regulation policy, and the reasons why some societies produce technological breakthroughs while others do not. Financial economics researchers will find the argumentation poorly formalized; readers seeking a clear thesis, solidly supported by history and sufficiently challenging to demand a response, will find what they seek here.
What you find that you do not read elsewhere: a serious and documented defense of the idea that conditions favoring bubbles can also favor transformative innovation. Most economists admit this idea in theory. Few develop it with the historical scope that Boom gives it.
The book leaves questions open. That is a strength.
Bibliographic Information
Title: Boom: Bubbles & the End of Stagnation Authors: Byrne Hobart, Tobias Huber Date of publication: 2025
Sources
- Tom Tunguz, “10 Best Books of 2025”: https://tomtunguz.com/10-best-books-of-2025/
- Johan Norberg, Peak Human: The New Geography of Human Potential, https://anderseninstitute.org/the-state-of-capitalism-with-luigi-zingales/
- Carlota Perez, Technological Revolutions and Financial Capital (2002), Cambridge University Press
- Thomas Philippon, The Great Reversal (2019), Harvard University Press
- Tyler Cowen, The Great Stagnation (2011), Dutton
