Bubbles As Innovation Accelerators
Why we need more speculative manias.
Given the unprecedented valuations of some tech companies and the low-volatility regime, which until recently dominated global financial markets, concerns about financial bubbles and crashes have intensified. Bubbles and their subsequent busts are predominately considered to be negative phenomena: they are often described as financially wasteful, economically inefficient, and socially destructive. Indeed, almost $6 trillion evaporated after the dotcom-collapse in the early 2000s, and the global economic system crashed when the financial bubble burst in 2008.
The standard view in the economics and finance literature holds that speculative financial bubbles form when unrealistic expectations about future cash flows decouple prices temporally from fundamental valuations. On this view — which was popularized by an early 19th-century study on crowd psychology— bubbles are the financial expression of “popular delusions” and the “madness of crowds.” Fueled by underlying self-reinforcing feedback-loops of imitation and herding behavior, prices elevate until a crash drives them back to fundamental values. As unrealistic and excessively optimistic expectations about the future fail, bubbles are considered to have socially and economically destructive effects. And, indeed, they are persistent and inevitable phenomena: from the Dutch tulip mania in 1637 and the South Sea Bubble of 1720, through the great crash of October 1929, Black Monday of 1987, and the financial crisis of 2007, speculative bubbles and market crashes invariably punctuate our history.
Yet not all bubbles are necessarily wealth- and value-destroying events. Rather, the formation of certain bubbles can be understood as an important process for innovation in various domains. As some financial bubbles deploy the financial capital necessary to fund disruptive technologies at the frontier of innovation, they are, thus, capable of accelerating breakthroughs in science, technology, and engineering. By generating positive feedback cycles of excessive enthusiasm and investments — which are essential for bootstrapping various social and technological enterprises — bubbles can be socially and economically net-beneficial. In other words, without the innovative spillover-effects of financial bubbles, many technological innovations or large-scale societal projects might never have happened.
Bubbles deploy the financial capital necessary to fund disruptive technologies at the frontier of innovation.
The complex networks of social interactions between enthusiastic supporters have catalyzed the formation of many large-scale scientific or technological projects, such as the Human Genome Project and the Apollo Program.* Characterized as manifestations of collective over-enthusiasm, they constitute an important element in the dynamics that give rise to great scientific discoveries and radical technological innovations. It is, therefore, not surprising that financial bubbles and speculative manias have been at the core of the technological revolutions that have fundamentally transformed our economic, social, and technological systems over the last centuries.
Bubbles and Technological Revolutions
What can we learn from the history of bubbles — as necessary elements in innovation — that could help us to anticipate, understand, and catalyze them better? Historically, it is singularly important to recognize their role in technological revolutions. In her now classic work on technological change, the socio-economist and historian Carlota Perez has identified five distinct technological revolutions, which she has called “great surges of development.” She defines a “great surge” as the process by which a technological revolution propagates across the economy and society. Emerging technologies — which might consolidate in what Perez calls a “techno-economic paradigm” — evolve around new infrastructures, energy sources, and materials. These major technological disruptions have led to the emergence of new interrelated constellations of technologies. The industrial revolution, for example, resulted in the mechanization of factories and the development of water power in the late 18th century. The second surge, which erupted in 1829, was based on steam and railways. The third revolved around steel, electricity and chemical, industrial, and electrical engineering, which, then, intensified, due to trans-continental railways and intra-continental steamships, international trade and globalization. All these new technologies and infrastructural networks emerged from the wreckage of speculative bubbles.
As Perez has shown, each technological disruption is triggered by a financial bubble, which allocates excessive capital to emerging technologies. Perez has identified a regular pattern of technology-diffusions. There is an “installation” phase in which a bubble drives the installation of the new technology. This is followed by the collapse of the bubble or a crash, to which Perez refers to as the “turning point.” After this transitional phase — which occurred, for example, after the first British railway mania in the 1840s, or, more recently, after the dotcom-bubble — a second phase is unleashed: the “deployment” phase, which diffuses the new technology across economies, industries and societies. The economic exhaustion of the technological revolution and excessive financial capital, which searches for new investment opportunities, can, then, give rise to the next technological revolution.
These bubbles, which have seeded major technological innovations and disruptions, share a central dynamic: the funding of these new technologies, energy sources, or networks decouples from expectations of economic return and, correspondingly, alter the risk profiles of the economic agents participating in a speculative mania. Irrespective of quantifiable financial returns and economic values, bubbles mobilize the financial capital needed to develop new transformative technologies. As the venture capitalist and economist William Janeway has shown, bubbles are necessarily wasteful as technological innovations require “inefficient” trial-and-error experimentation.
Contrary to the assumptions of neo-classical economics — in which rational, that is, utility-maximizing agents allocate scarce resources on the basis of perfect information — the excessive risk-taking, which financial bubbles incentivize, is critical for the discovery and commercialization of techno-scientific breakthroughs. These bubble-fueled investments are often not justified on the basis of traditional cost-benefit analyses. In other words, speculative capital drives these innovation-accelerating bubbles, which provide usable commercial infrastructural networks and technologies, even after the bubble has burst. In contrast to the orthodox view of bubbles as market failures and symptoms of economic irrationality — which is still deeply entrenched in mainstream academic economics —some speculative bubbles need to be re-conceptualized as important decentralized economic mechanisms that coordinate the large-scale capital allocation process, which the search for the next breakthrough requires. Although they can destroy value and inflict pain on individual investors, such bubbles can nevertheless be net beneficial for society as they enable the exploration of new economic spaces. In other words, the overall long-term benefits can outweigh the short-term costs of innovation-enabling bubbles and busts.
Socio-Political Bubbles
Bubbles extend beyond the domains of financial markets or technological innovations. As Didier Sornette and his research group have shown, bubbles are generic phenomena that occur in society at large. Similarly to financial bubbles, the essential ingredients are socio-behavioral mechanisms, such as herding or imitation, and exuberant over-optimism and unrealistic expectations. Such “social bubbles” have been the driving force for many large-scale political, scientific, and societal projects. Sornette and his collaborators have, for example, examined the Apollo program as well as the Human Genome project as they embody the essential characteristics of such bubbles. Identically to the economically productive ones that have fostered technological revolutions and major scientific breakthroughs, social bubbles can be characterized in terms of a reduction of collective risk-aversion. Standard risk-benefit analyses are disregarded, which results in extraordinary risk-taking in the face of radical economic and technological uncertainty.
Driven by political factors, such as the space race with the Soviet Union, as well as scientific curiosity, the Apollo program provides an interesting illustration of a massive social bubble. Still one of the costliest projects that have ever been undertaken by the United States at peacetime, it massively accelerated technological innovation and scientific advances. Fueled by self-reinforcing collective over-enthusiasm, massive financial, political and individual risks were taken to “put a man on the moon.” While the collective enthusiasm and public and political support peaked with the first moon landing in 1969 — which was then viewed as the first step in the colonization of space — the bubble subsequently burst as political and public support for the program decreased. Nevertheless, while the cost of the program might have been disproportional to the returns, some returns may still be exploited in the future.
Another example of a social bubble documented by Sornette and his collaborators is the Human Genome project. Initiated and funded by government agencies to sequence the human genome, it became a hyped large-scale scientific project, which was fueled by scientific and financial interests. Intense competition between the public and private sector catalyzed the anticipation and results that generated extraordinary over-enthusiasm and media interest that further attracted even more financial and scientific investments, which, in turn, resulted in a proliferation of genomic start-ups. This network of self-reinforcing feedbacks between different actors — such as scientists, government agencies, entrepreneurs, and venture capitalists — generated a massive social bubble, which inflated expectations about medical and commercial applications of the Human Genome project. However, the scientific understanding of genes and the commercialization of some of the underlying technologies have not advanced as anticipated. Still, the Human Genome project accelerated the falling of sequencing costs and generated incremental advances in scientific understanding and technological innovation. We are, however, still in the early phases of the project’s potential long term impact on society.
Now, these bubbles share an essential dynamic as they are driven by excessive public, political, and financial expectations about future outcomes, which are not justified by fundamental valuation or standard cost-benefit-analyses. But is this collective over-enthusiasm just a manifestation of crowd irrationality? While expectations are often massively elevated, it seems misleading to label these phases of collective exuberance as purely irrational.
Innovative Exuberance
As the dotcom bubble illustrates, the fundamental expectations or beliefs behind the bubble can be rationally justified. The intuition that the Internet will radically transform our economic and societal structures was ultimately correct. While investing in startups such as Pets.com was a painful experience for some investors — $300 million evaporated when the company folded after the collapse of the dotcom bubble — companies such as Google and Amazon emerged from the debris. Although, it now seems to be the result of irrational exuberance — as Robert Shiller’s book, which was published at the peak of the internet bubble, suggests — new accounting methods, such as net present value or so-called “real-option” valuations of companies, have helped to rationalize dotcom investments. By extending option theory to companies, investors were able to assess future investments in intangible assets and the value of future opportunities. It follows from real-option theory that the greater the uncertainty, the more valuable the options may be. Investments in dotcom startups could, thus, be rationalized as they had a risk/reward-profile similar to an asymmetric call option.
Similarly, the current unprecedented valuations of tech unicorns might seem irrational. However, when considering another feature of tech companies — network effects and the economics of increasing returns that are characteristic of Silicon Valley — the valuations of some of these companies might be rationally justified. As with Google and search, Facebook and social media, or Uber and ridesharing, often one company might eventually control the entire market. While is it unclear whether network effects will continue to dominate, the potential scalability and increasing returns help rationalize some of the current unicorn valuations. In other words, while the expectations and enthusiasm that drive bubbles might be inflated, it does not necessarily render the extraordinary investments or commitments, which are a defining feature of such bubbles, irrational. Rather, such bubbles could be characterized as phases of innovative exuberance, which, in some cases, enable the development and deployment of disruptive new technologies.
Financial Crashes, Economic Stagnation, and Technological Acceleration: Productive vs. Unproductive Bubbles
But how can we distinguish between productive bubbles — which are necessary components in the process of innovation — and unproductive bubbles, which destroy value and destabilize entire financial systems? As Janeway has shown, bubbles can be separated and categorized along two different dimensions. One dimension is defined by the object of speculation. Charles Kindleberger, in his important Manias, Panics and Crashes, mapped out the spectrum of assets that have historically been the objects of speculation, such as tulip bulbs and railroads, real estate, commodities, stocks, and bonds. More recently financial derivatives, such as credit-default swaps, options, exchange-traded-funds, and cryptocurrencies have all been the focus of excessive speculation. The other dimension, which Janeway identifies, is the locus of speculation, that is, the economic space where the speculation occurs. Often, speculative activity in credit markets generates bubbles that are highly destructive. As they infect the economy, these destructive bubbles can increase the systemic instability of the financial and economic system as it was the case during the credit bubble of 2004–2007. On the contrary, the dotcom bubble, for example — or, more recently, the crypto-bubble — was confined to the capital or alternative markets, and did not spill over into the broader economy. While destructive for some investors, the dotcom bubble, ultimately, provided the technological foundation of the Internet and its emerging cyber-economy.
Now, what distinguishes innovation-accelerating bubbles from speculative phases that yield, at best, incremental gains, and are, at worst, destructive? Historically, the five major technological revolutions, which disrupted the economic, institutional, and political structure of society, resulted in extraordinary increases in productivity. In other words, the bubbles, which fueled these socio-technological revolutions, have been transformative engines for economic growth and productivity, which enabled the propagation of the underlying technological innovation across the entire economic system. Not only have they all fundamentally transformed existing industries and infrastructures, but they also created radically new economic spaces to be explored and exploited. These massive technological disruptions — which can be aptly characterized by a process of Schumpeterian “creative destruction” — all generated novel interrelated sets of new technologies, which, in turn, have catalyzed further innovations, infrastructures, and industries.
In contrast to these innovative bubbles, which are boosting economic growth and productivity, the financially destructive bubbles, which have punctuated the global financial markets since the late 1970s, have been accelerated by the hyper-financialization of the economy and large-scale monetary-policy-driven market interventions. As the aftermath of the financial crisis of 2007/2008 has shown, explosive debt and leverage magnified the bursting of the bubble, which had higher-order systemic effects and large-scale unintended consequences — such as the socialization of its costs and increased income disparities — from which the global capitalist system has not recovered. Moreover, historically unprecedented monetary-policy experimentations and competitive devaluations engineered by global central banks have destroyed the informational content of price-signals and warped the cost of risk. Coupled with the virtualization of finance that resulted in ever-increasing abstractions and complexities, the extraordinary suppression of volatility, which resulted from the globally-coordinated central-bank response to the 2007-meltdown, has, over the last decade, given rise to various financial bubbles, which have materialized across different markets and asset classes.
Largely driven by lower risk premia and artificially-inflated valuations, these bubbles, however, have failed to unleash economic productivity and technological innovation. Artificial central-bank liquidity and share-buybacks — an estimated $3.8 trillion since 2009 — for example, have provided a price-insensitive automatic bid underneath the market, which resulted in the institutionalization of “buy-the-dip”-strategies and the emergence of a “short-volatility complex,” which consists of volatility-suppressing financial engineering strategies.** However, recent surges of volatility in global financial markets — which have been triggered by the tightening of monetary policy and resulted in systematic deleveraging across strategies, reduced “liquidity-volatility-flows,” and a re-pricing of risk assets — are indicating that the systemic instability of the global financial and economic system has increased even further.
Due to this fundamental economic regime shift, which has been stimulated by an illusionary belief in eternal economic growth and automatic technological progress, financing of radical breakthroughs and discoveries has shifted from hyper-ambitious large-scale projects to short-term and exit-driven investments that extract mainly incremental gains. Of course, there have been recent technological innovations and scientific advances. Yet, they have not been comparable to the innovations that revolutionized science and technology over the past two centuries. However, as venture investor Peter Thiel writes:
“The actual truth is that there are many more secrets left to find, but they will yield only to relentless searchers. There is more to do in science, medicine, engineering, and in technology of all kinds. We are within reach not just of marginal goals set at the competitive edge of today’s conventional disciplines, but of ambitions so great that even the boldest minds of the Scientific Revolution hesitated to announce them directly. We could cure cancer, dementia, and all the diseases of age and metabolic decay. We can find new ways to generate energy that free the world from conflict over fossil fuels. We can invent faster ways to travel from place to place over the surface of the planet; we can even learn how to escape it entirely and settle new frontiers. But we will never learn any of these secrets unless we demand to know them and force ourselves to look.”
In this sense, we can think of bubbles as financial instruments that underwrite the relentless search for these “secrets,” which — when uncovered— yield enormous scientific, technological, and economic benefits. Now, as the clean-tech bubble of the last decade exemplifies, this search-process can, of course, be unproductive. Due to a variety of technological, political, and regulatory factors, the clean-tech bubble, which burst in 2007, for example, seemed to have so far mainly resulted in incremental innovations. However, energy — alongside money, intelligence, life, or space — represents one of the critical domains that contain the seeds for future financial bubbles, which might be capable of unlocking radical techno-scientific breakthroughs. More specifically, the ever-increasing applications and extensions of neural network techniques, novel system-designs in nuclear energy, or the emergence of bitcoin as a decentralized alternative to the legacy financial system might trigger new waves of technological innovation and economic productivity.
Now, at the core of the historical technological revolutions mentioned above was an all-pervasive low-cost input, often new materials or energy sources combined with novel products, processes, and infrastructures. Artificial intelligence or bitcoin, for instance, share the conceptual features that can be identified in previous innovation waves — they are emerging as clusters of interlocking technologies and organizing principles that might not only transform existing sectors and industries but could power novel economic systems. An essential element of innovation-accelerating bubbles crystallizes in these domains: a compelling core narrative about how the underlying technologies can radically transform our existing technological, economic, and societal structures. Although these technologies follow their specific boom and bust patterns — as the “crypto mania” and past “AI-winter”*** illustrate — we can, nevertheless, identify a kernel of plausible visions underneath the hyperinflated claims, promises, and expectations, which, as past speculative frenzies have shown, often get validated in the future. Recent advances in AI or the spread of bitcoin, for example, have given rise to futuristic narratives, which envision a future that is radically different from a stagnating present.**** Whether the realization of these visions will be dystopian or utopian in nature depends, ultimately, on human agency — the choices we make in the present historical moment will influence the trajectory on which the future will unfold. If history is any guide, it seems that we need more, not less, financial bubbles, which are capable of igniting the next phase of techno-scientific progress and accelerating its transformative civilizational effects.
Notes
*The bubble-dynamics, which underlie the Appolo Program or the Human Genome Project, can be identified in other large-scale technological, scientific, and political projects. The “war on cancer,” which President Richard Nixon officially declared in 1971, or more recently, the Human Connectome Project, which was initiated to map the functional and anatomical connectivity of the human brain, provide other examples. Naturally, the capital intensity of such hyper-ambitious projects has attracted criticisms, which question the feasibility of their scientific and technological implementation or promised socio-economic value. John Horgan, who articulated the infamous End-of-Science-Hypothesis, argued, for example, that the complexity and intractability of a given research challenge may represent, ultimately, an economic profit-opportunity for science. Citing biology’s failure to solve cancer and the scientific quest for immortality, he suggests that the scientific “inability to solve certain important problems” might open novel sources of research funding. Given that military and defense-related research & development has been an important vector of technological innovation over the past century, climate change has emerged as a substitute for the Second World War, and more specifically, the Cold War, which were crucial to secure research funding. In this sense, climate change could be characterized as one of the largest social and political bubbles of our time.
**Hedge fund manager and volatility philosopher Christopher Cole estimates that implicit and explicit short volatility-strategies account for around $60 billion and $1.4 trillion, respectively (see, for example, his article “Volatility and the Alchemy of Risk”)
*** The exponential growth in computation, GPUs, storage, datasets, user demand, high levels of R&D, and massive VC and state-sponsored investments could indicate the formation of a new AI bubble that might be followed by another “AI-winter.” However, on Perez’ cyclical model of technological innovation, AI simply represents an instantiation of the more extensive IT-technological revolution. Consequently, the bursting of previous AI bubbles, such as the one in the 1980s, could have already marked the “turning point” or phase of readjustment. Back then, over-inflated expectations crashed when cheap UNIX workstations triggered the fall of over-priced expert systems running on LISP and the Dreyfus brothers published their Mind over Machine, which undermined some of the pretentious and flawed assumptions of the first generation of AI research. As the ambiguity surrounding the classification of different AI-bubbles indicates, cyclical or wave theories of innovation—which generalize across large historical time-frames (around half a century in Perez’ framework) — have often limited power to diagnose, explain, and predict phenomena occurring at smaller time-scales.
****Counter-intuitive to the common-sense experience of accelerated socio-technological change, a few contemporary thinkers, such as Peter Thiel, Tyler Cowen, or Robert Gordon, have diagnosed our age with a lack of radical technological innovation and economic progress — or, as Sci-Fi author Neil Stephenson has called it, “innovation starvation.”
This article has been updated in January 2019.
