Boom, Bust, and Bitcoin: Bitcoin-Bubbles as Innovation Accelerators

Abstract

Bitcoin represents one of the most interesting technological breakthroughs and socio-economic experiments of the last decades. In this paper, we examine the role of speculative bubbles in the process of Bitcoin’s technological adoption by analyzing its social dynamics. We trace Bitcoin’s genesis and dissect the nature of its techno-economic innovation. In particular, we present an analysis of the techno-economic feedback loops that drive Bitcoin’s price and network effects. Based on our analysis of Bitcoin, we test and further refine the Social Bubble Hypothesis, which holds that bubbles constitute an essential component in the process of technological innovation. We argue that a hierarchy of repeating and exponentially increasing series of bubbles and hype cycles, which has occurred over the past decade since its inception, has bootstrapped Bitcoin into existence.

Keywords:

• bitcoin
• money
• cryptocurrencies
• financial bubbles
• technological innovation
• economic growth
• reflexivity

JEL Classification Codes:

• O33
• O43
• G12

Notes

1 In this article, we follow the convention to use uppercase “B” to refer to the Bitcoin network and lowercase “b” to the protocol-native cryptocurrency.

2 For a sample of the academic literature, see Narayanan et al. 2016; Narayanan and Clark 2017; Chohan 2017; Wheatley et al. 2019; and Gerlach, Demos, and Sornette 2019. However, most of the relevant analyses, on which we will rely, have occurred outside traditional academic journals on blogs or social networks, such as Medium, Reddit, Twitter, or Telegram.

3 What makes Bitcoin a particularly illuminating object for analysis is that its unique technological genesis subverts the conventional innovation process, thereby challenging fundamental economic assumptions about the importance of basic science, the role of public R&D, or the interactions between government-directed policies, private industry and market forces, and publicly-funded universities and research labs, which have begun to replace the obsolete linear model of innovation (see Leydesdorff and Etzkowitz 1998; Leydesdorff and Meyer 2003; and Stokes 1997). For a critique of the linear model of innovation in which scientific insights—that flow irreversibly from basic research to applied science and emerging technologies—translate into economic growth, see Kealey (1996). While its design incorporates pre-existing components, the invention of Bitcoin resulted not from a set of deliberate innovation policies or a specific academic research program. On the contrary, the open-sourced, crowd-funded, and non-academic development of the technology—which was created by a pseudonymous programmer—occurred outside traditional institutional boundaries. While analyzing the socio-economic and academic institutions that predate but shaped the technology’s enigmatic development in more depth would contribute to a holistic understanding of the Bitcoin phenomenon, such an analysis is beyond the scope of this article. While we provide an overview of Bitcoin’s pre-history in the next section, we focus here on the period that started in 2008 with the release of the white paper. For literature on the institutional and evolutionary dynamics underlying technological innovation that might be instructive in this context, see, for example, Mansfield 1968; Nelson and Winter 1982; Metcalfe 1998; Dosi 2000; Witt 2002; Geroski 2003.

4 This section draws on the exceedingly thorough review of Bitcoin’s academic pre-history by Narayanan and Clark (2017).

5 While it is tempting to construe proof-of-work as an algorithmic reformulation of the labor theory of value—which postulates that value is determined by labor or the cost of production—”work” in Bitcoin’s system is derived not from political economy but from computer science. The work to be proven—that is, transaction validations and cryptocurrency issuance performed by CPUs—is probabilistic and not deterministic in nature. In other words, no amount of computational effort guarantees a reward. Rather, the successful solution of a cryptographic puzzle is a low-probability outcome, which miners try to achieve in repeating trial-and-error-processes (see Land 2020). More generally, an adequate economic framework for understanding the process of bitcoin’s monetization is not the Marxist labor theory of value—elements of which can be already identified in Aristotle, Adam Smith, or David Ricardo—but the Austrian monetary economics developed by Carl Menger, Ludwig Van Mises, or F.A. Hayek. For an application of Austrian economics to Bitcoin, see Ammous (2018).

6 In a 2009 post on the P2P Foundation message board, Nakamoto states: “A lot of people automatically dismiss e-currency as a lost cause because of all the companies that failed since the 1990’s. I hope it’s obvious it was only the centrally controlled nature of those systems that doomed them. I think this is the first time we’re trying a decentralized, non-trust-based system” (Nakamoto 2009).

7 For technical treatments of Bitcoin, see Antonopoulos (2014); Song (2019).

8 As the bust of the bitcoin bubble in 2018 has shown, the positive feedback loop underlying bitcoin’s rise can revert into a dynamic that results in accelerating price and devaluations accompanied respectively by increases and decreases in hash power, which, in turn, reduce network activity and security.

9 In contrast to earlier Internet protocols, such as TCP/IP or SMTP, which were difficult to monetize, Bitcoin directly motivates early adopters to adopt and hype the network.

10 Contrary to the view that Bitcoin’s underlying blockchain is the true technological innovation, we argue that the intertwined reflexive feedback loops that govern the protocol’s design and incentive structure represent Bitcoin’s novelty. Consequently, as it follows from our analysis, bitcoin, the cryptocurrency, cannot be separated from its underlying distributed ledger-technology as this would disrupt the intricate incentive system embedded in the network. Bitcoin commentator Joe Coin aptly captures the novelty of Bitcoin’s design in a cogent blog post from 2015: “Given the crucial requirement to preserve decentralization, the problem Satoshi had to solve while designing Bitcoin was how to incentivize network participants to expend resources transmitting, validating, and storing transactions. The first step in solving that is the simple acknowledgement that it must provide them something of economic value in return […] The incentive had to be created and exist entirely within the network itself […] any instance of a blockchain and its underlying tokens are inextricably bound together. The token provides the fuel for the blockchain to operate, and the blockchain provides consensus on who owns which tokens. No amount of engineering can separate them” (Coin 2015).

11 An embryonic version of this idea can already be identified in Schumpeter’s concept of “creative destruction.” In 1910, he wrote that “to produce […] means to combine materials and forces within our reach […]. To produce other things, or the same things by a different method, means to combine these materials and forces differently.” Schumpeter identified creative destruction as a “source of energy within the economic system which would of itself disrupt any equilibrium that might be attained” (see Schumpeter 1934). Creative destruction precisely refers to a combinatorial process in which novelty gets continually created by combining existing elements, which, in turn, constantly disrupt the established economic order. Later research on innovation dynamics expanded on the Schumpeterian conception of technological evolution as a recursive process whereby the recombination of existing elements generates novel or improved technologies (see Usher 1954; Kauffman 1993; Fleming 2001; McNerney et al. 2011; Tria et al. 2014; Youn et al. 2015; Fink and Reeves 2019).

12 “Discovery,” “invention,” and “innovation” represent elementary components of technological progress and economic growth. Whereas the separation of vertical or “zero-to-one” and horizontal or “1-to-n” innovations echoes the distinction between radical or “disruptive” and incremental innovations (see Christensen 1997), Cauwels and Sornette (2022) grade discovery, invention, and innovation hierarchically in terms of the risk, uncertainty, and novelty involved in each process.

13 Interestingly, for theologist and philosopher René Girard, the original sin in Christianity lies in the “mimetic desire” of humans to imitate each other, which, ultimately, results in violence. On a Girardian reading, then, the emergence of altcoins, and the tribal rivalry and conflict these competing cryptocurrencies triggered, could be explained by the mimetic desire to copy the singularity of Bitcoin’s design and successful implementation (see Hobart and Huber 2019). For a quantitative application of Girard’s mimetic theory that models the mimetic contagion driving speculative bubbles, see Orléan (1989b).

14 For a discussion on “sound money” in Austrian Economics, see Ammous (2018).

15 For example, cryptographer Ralph Merkle, who invented Merkle Trees—a data structure that Bitcoin employs—compares the protocol to an organism: “[…]. Bitcoin is the first example of a new form of life. It lives and breathes on the internet. It lives because it can pay people to keep it alive. It lives because it performs a useful service that people will pay it to perform. It lives because anyone, anywhere, can run a copy of its code. It lives because all the running copies are constantly talking to each other. It lives because if any one copy is corrupted it is discarded, quickly and without any fuss or muss. It lives because it is radically transparent: anyone can see its code and see exactly what it does. It can’t be changed. It can’t be argued with. It can’t be tampered with. It can’t be corrupted. It can’t be stopped. It can’t even be interrupted […]. But as long as there are people who want to use it, it’s very hard to kill, or corrupt, or stop, or interrupt” (see Merkle 2016).

16 Bitcoin’s diffusion occurred primarily online on social media, mailing lists, and blog posts. For example, Bitcoin’s infectiousness has spread with various “memes,” which acts as a unit for carrying and transmitting Bitcoin-related ideas and symbols. An example of Bitcoin’s mimetic model of technology diffusion is the “Hodl”-meme, which—resulting from a misspelling of the word “hold”—motivates bitcoin holders to resist the urge to sell in response to market fluctuations. Consequently, analysts at Barclays developed an epidemiological model of Bitcoin’s diffusion that models bitcoin as a “virus” that “infects” the population adopting the cryptocurrency technology.

17 In Perez’s classic conceptual model of technology diffusion, this phase might correspond to what she identifies as the “turning point.” In her model, each technological disruption is triggered by a financial bubble, which allocates excessive capital to emerging technologies. Perez has extracted a regular generic pattern of technology-diffusion from historical case studies. She identifies 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 she 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 (see Perez 2003).

18 For price data, see Wheatley et al. (2019).

19 Mencius Moldbug, a pseudonym for technology entrepreneur and computer scientist Curtis Yarvin, embodies the spirit of the bubble dynamics of bitcoin, with his Bubble Theory of Money (BTM), which holds that, given its fundamentally social nature, money can be likened to a bubble. He writes: “Bitcoin is money and Bitcoin is a bubble, The BTM asserts that money and a bubble are the same thing. Both are anomalously overvalued assets. Both obtain their anomalous value from the fact that many people have bought the asset, without any intention to use it, but only to exchange it for some other asset at a later date. The two can be distinguished only in hindsight. If it popped, it was a bubble. If not, money—so far” (see Moldbug 2013; Law 2006). This reasoning should be distinguished from the standard theory of money, which considers it as an IOU and thus as credit (Becke and Sornette 2017), and the fact that credit growth is unstable and has led historically to boom-bust cycles over the last 5000 years (Graeber 2012). In the creation of bitcoins, there is indeed no credit mechanism. The BTM is also reminiscent of the theory of value considered as a convention, developed by the French economist André Orléan (1987 and 1989a).

20 “Hodling” represents the speculative adoption of bitcoin as it implies a speculative bet on future gains in value. Thus, adoption is here defined as an increase in “hodling”—that is, the accumulation and holding of bitcoin.

21 The expectation that the halvening results in an increase of “hodlers” and higher prices assumes that scarcity drives bitcoin’s value. In this view, the halvening represents a supply “shock” that increases bitcoin’s relative scarcity. While the supply cap of 21 million bitcoins is algorithmically fixed, relative supply and the bitcoins in circulation decrease. Furthermore, due to the change in the supply schedule, the market needs to absorb fewer bitcoins, which miners are selling to cover their capital expenditures. Gradually, miner compensation will transition to transaction fees. A popular model that is used to model bitcoin’s scarcity-based value is the so-called Stock-to-Flow model. It models the price of Bitcoin based on the “stock-to-flow ratio,” which was initially used to value gold and other raw materials. By relating the “stock”—i.e., the quantity issued–to the “flow”—i.e., the annual issued quantity–the model derives a prediction of a bitcoin price post-halvening of $55,000 to $100,000 (which would correspond to a market cap of more than $1 trillion) (see Plan B 2019).

22 Bitcoin could only be invented once. Given its singular nature, it has been argued that Bitcoin cannot be replaced by another cryptocurrency. Hal Finney, for example, stated that every subsequent version of the protocol designed to substitute Bitcoin would be self-invalidating. A hypothetical Bitcoin successor would undermine its own viability and credibility as “an investor” would not “know that it won’t happen again” (Finney 2011). In this view, the adoption of Bitcoin follows a binary logic: either Bitcoin succeeds or Bitcoin and all other forks or cryptocurrencies will fail as well.

Additional information

Notes on contributors

Tobias A. Huber

Tobias A. Hubber is at ETH Zurich, in the Department of Management, Technology and Economics, Switzerland. Didier Sornette is also at ETH Zurich, in the Department of Management, Technology and Economics, Switzerland, as well as Tokyo Tech World Research Hub Initiative, Institute of Innovative Research, Tokyo Institute of Technology, and the Institute of Risk Analysis, Prediction and Management, Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, China.

Didier Sornette

Tobias A. Hubber is at ETH Zurich, in the Department of Management, Technology and Economics, Switzerland. Didier Sornette is also at ETH Zurich, in the Department of Management, Technology and Economics, Switzerland, as well as Tokyo Tech World Research Hub Initiative, Institute of Innovative Research, Tokyo Institute of Technology, and the Institute of Risk Analysis, Prediction and Management, Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, China.