The microeconomics of cryptocurrencies
The proposal for the digital currency Bitcoin was released in 2008 (Nakamoto 2008). Since then, its viability has been continuously questioned, with many predicting its demise. So far, such predictions are moot. At its peak in the end of 2017, one bitcoin was worth just below $20,000, then it dropped to $3400 a year later, and bounced back to $9,000 in spring 2020. This is despite the fact that Bitcoin is not backed by any real asset nor any governmental claims (such as the ability to use it to settle tax debts). As a consequence, Bitcoin’s resilience has increasingly become a topic of interest among economists.
While macroeconomists look to it as a potential study of monetary theory, microeconomists have been interested in Bitcoin due to the seemingly robust nature of an otherwise highly decentralized network without any clear owner.
Bitcoin was initially proposed in a white paper by Nakamoto (2008) and came into existence on 3 January 2009. Nakamoto’s contribution was providing the answer to a long-standing question in the cryptography community (and to a lesser extent among libertarians) which is the question of whether it is possible to design a fully decentralized digital currency.
Having a decentralized cash system means that individuals may engage in ‘monetary transactions’ without involving any third party (like cash, which can be given by a buyer directly to a seller) and without any authority that would, for instance, conduct monetary policy. In the technological jargon, transactions in such a system are called peer-to-peer.
Until the advent of Bitcoin, the problem did not have any obvious solution. By being electronic, the “coins” can, in principle, easily be copied and thus used several times. That is, one faces the risk of double-spending. The double-spending problem can theoretically be avoided if, at any time, there is a consensus among all participants about which coin was spent, and by whom.
However, such real-time consensus in peer-to-peer systems is known to be impossible, according to Fischer et al.’s (1985) ‘FLP theorem’, one of the most important theorems in computer science. In a practical sense, this means that one needs what is called a ‘Byzantine fault tolerant system’,i.e. a system that allows for temporary disagreements as well as a protocol to handle such disagreements.
The challenge is that Byzantine fault tolerant systems are vulnerable to the possibility of double-spending attacks, for it is not possible to distinguish genuine Byzantine faults from double-spending. By understanding the role of incentives, Nakamoto found a way to drastically increase the cost of attempting to double spend. Thus, for many, Nakamoto’s contribution was a breakthrough, explaining why it was met with vast enthusiasm and spurred further development.
Over the past five to ten years, the literature on the blockchain and cryptocurrencies has branched out in many directions, including initial coin offerings, smart contracts, governance, macroeconomic impacts, stable coins substitution, central bank digital currencies and, of course, an entire branch of computer science.
In Halaburda et al. (2020), we offer a survey that focuses on the developing microeconomics literature through the lenses of the standard division of economics: supply and demand (of Bitcoin), price, and competition.
The supply side of the market essentially depends on miners (the agents who validate and record transactions) and their incentives. Here we discuss the literature that formally examines issues related to equilibrium when miners are strategic. Recognizing that miners are driven by economic incentives sheds a different light on the prescriptions of software protocols. For example, the economic literature quickly established that
Nakamoto’s ‘longest chain rule’ — a protocol to restore consensus among miners in case of disagreement — is incentive compatible in equilibrium. However, the literature also found other equilibria, which do not offer the same level of robustness of the system.
Moreover, the economic lens allows us to recognize proof-of-work mining, the mechanism used by Bitcoin to minimize potential disagreements, as a well-analysed type of contest (Tullock contest). Using the properties of Tullock’s contests allows us to derive limits to the decentralization of mining under proof-of-work protocols. Finally, we discuss the literature which shows that achieving consensus is an equilibrium.
As the most crucial issue regarding blockchain stability is the double-spending issue, there is a significant literature on whether the Bitcoin system sufficiently thwarts incentives to double-spend. Here, we employ the formal model developed by Eric Budish (2018), which examines both (i) the mining competition and (ii) incentive compatibility. It also provides the basis for discussing extensions, like proof-of-work versus proof-of-stake, an energy-frugal alternative to proof-of-work.1 We include this aspect as well in the formal analysis.
Turning to the demand side of the market, we examine the reasons why people use — or don’t use — Bitcoin. The interactions between supply and demand impact Bitcoin’s price, which has also been the subject of multiple studies.
Finally, we study competition between cryptocurrencies, which is an increasingly relevant topic as the market capitalization of all cryptocurrencies grew at a stunning rate in the past few years. In February 2014, the market capitalization of all cryptocurrencies was approximately $14 billion. In January 2018, near Bitcoin’s peak, the total market capitalization reached $825 billion. As of July 2020, total market capitalization was approximately $275 billion, and Bitcoin’s price was slightly above $9,000. Thus, despite the spectacular decline in Bitcoin’s price from its peak (amounting to more than $19,000), the total market capitalization of all cryptocurrencies is still ten times as large as it was in 2014.
One particular topic of interest in this area is competition in the market of cryptocurrency exchanges. Over time, this market has evolved from essentially a monopoly in 2011 (Mt. Gox served more than 80% of the market) to an oligopoly in 2014 (three firms held 84% of the market share), and finally to a much more competitive market (in August 2019, the top three firms held just 13% of the market).
While broad trends and understanding have emerged, it is also clear that the cryptocurrency ecosystem continues to evolve, and its precise place within the broader economy has yet to be established. Hence, more research will be needed. Hopefully, this survey will help establish a base for such future research.
Budish, E (2018), “The economic limits of bitcoin and the blockchain”, mimeo, University of Chicago Booth School of Business.
Dwork, C and M Naor (1992), “Pricing via processing or combatting junk mail”, Annual International Cryptology Conference, Springer, pp 139-147.
Fischer, M J, N A Lynch and M S Paterson (1985), “Impossibility of distributed consensus with one faulty process”, Journal of the ACM (JACM) 32(2):374-382.
Gans, J S and N Gandal (2019), “More (or less) economic limits of the blockchain”, NBER Working Paper.
Halaburda, H, G Haeringer, J Gans and N Gandal (2020), “The Microeconomics of Cryptocurrencies”, NBER Working Paper No. 27477.
Nakamoto, S (2008), “Bitcoin: A peer-to-peer electronic cash system”.
1 Gans and Gandal (2019) examine the double-spending issue in the case of proof-of-stake.