Blockchain and Investment: An Austrian Approach

Abstract: Investment is a function of expected profit, which involves calculation of the cost of trust. Blockchain technology is a new institutional technology (Davidson et al 2018) that industrialises trust (Berg et al 2018). We therefore expect that the adoption of blockchain technology into the economy will affect investment and capital structure. Using a broad Austrian economic approach, we examine how blockchain technology will affect the cost of trust, patterns of investment, and economic institutions.

Working paper available at SSRN.

1 Introduction

Austrian economics is characterised by a methodological focus on individual subjective choice in markets as the shaping force of economic outcomes. It suggests the idea that economic freedom is a necessary precondition for political freedom. Unsurprisingly, then, many of the pioneers of Bitcoin and blockchain technologies, such as Satoshi Nakamoto, Vitalik Buterin, and Roger Ver, as well as cypherpunks and cryptoanarchists such as Timothy May and Nick Szabo, have professed to having been significantly influenced by Austrian economics and in particular, by Ludwig Mises (1980 [1912]) who emphasised the importance of hard money and the primacy of economic freedom for political freedom (see e.g., Graf 2013, Šurda 2014, Ammous 2018).¹ Yet the ‘Austrian-ness’ of bitcoin (i.e. cryptocurrencies as private money cf. Hayek (1990 [1976]) viz. White 2015, Luther 2016a, Luther and Olson, 2015) can obscure the ‘Austrian-ness’ of blockchain.

Blockchain is a new institutional technology of distributed and decentralised ledgers for recording social facts such as identity, licensing, registries, property ownership and transfers, contracts, information and data. Since Nakamoto (2008) invented the blockchain as a mechanism to keep track of the digital money bitcoin, economic analysis of blockchain has drawn on a range of approaches and analytic frameworks including: game theory and mechanism design (so-called cryptoeconomics); monetary theory (Luther and Olson 2015; White 2015); microeconomics and industrial organisation (e.g. Böhme et al. 2015, Catalini and Gans 2018); institutional economics (e.g. Davidson et al. 2018); and political economy, among others.

We argue that a broader and more integrated Austrian economics account of blockchain as a technology (and not just of cryptocurrencies as private digital money) can yield important new insights into the dynamics of a market economy with new technologies of trust. Specifically, we show why capital structure will be affected by blockchain technology through reduced hazards of opportunism in contracting. An integrated Austrian approach also shows how blockchain innovation will affect the institutional boundaries between firms and markets, and the economic relationships between individuals and governments.

We proceed as follows. Section 2 reviews Austrian monetary theory exploring hard money, private money, and banking. Section 3 explores capital and capital structure. Section 4 investigates the consequences of malinvestment and bubbles. Section 5 discusses private governance, exploring how blockchain platforms can furnish fullstack institutional infrastructure. Section 6 concludes that blockchain is a technology for self-sovereignty.

2 Money

Austrian economic analysis of the viability of cryptocurrencies builds on Menger’s (2009 [1892]) account of the origin of money from trade (Szabo 2002). Money emerges from individual decisions to accept particular items in exchange as money because of mutual convergence of expectation that others will also accept it (Radford 1945; Jones 1976). In the Austrian account, the origin of money is an evolutionary competitive process over certain selection dimensions, including qualities of divisibility, acceptance, portability, scarcity, stability, tamper-resistance and permanence. These qualities facilitate money properties including as a medium of exchange, store of value, and unit of account (Harwick 2018).

When cryptocurrencies have some, or all, of these properties they can function as money. Bitcoin did not evolve in use, but rather was deliberately designed as a private digital money (Dwyer 2015) – specifically a ‘peer-to-peer electronic cash system’ (Nakamoto 2008). Cryptocurrencies, as digital money secured using blockchain technology, in this sense is the latest phase in the evolution of money (Albright 2014; Davidson and Block 2015; Luther and Olson 2015; Luther 2016b).

Two key properties of bitcoin, by design, are hardness and uncensorability. Bitcoin is designed to mimic gold, with a fixed and declining schedule of money growth, and to have absolute tamper-resistance (Ammous 2016, 2018). These conjoint properties insulate cryptocurrencies as a store of value from political interference. When citizens can choose to make payments or transfer value through cryptocurrencies (see Hendrickson and Luther 2017) or store value in crypto-assets, this limits the ability of a government to control economic behaviour through control of the monetary unit (e.g. validating payments or capital controls), and nor can a government confiscate private property by devaluing the monetary unit (i.e. printing money or monetising public debt, resulting in an inflation tax). Cryptocurrencies thus limit government interference and arbitrary exercise of power in an economy (see Hendrickson and Luther 2019; Luther 2019).

The benefits of private competitive money supply have long been argued by Austrian economists. Hayek (1990 [1976]) addressed the case for the denationalisation of money, or the end to the government monopoly on the supply of currency and of the benefits to competitive supply, arguing that competition disciplines government abuse of money through inflation or weakening through contestability (but see Luther 2013 for a counter argument). A similar competitive efficiency argument extends to banking and finance, known as ‘free banking’ (Selgin and White 1987; Selgin 1988; White 2015). So-called Initial Coin Offerings (ICOs) are a further evolution of private distributed finance. Overall, the Austrian account of money (and banking) furnishes a coherent analysis of the design, emergence and viability of cryptocurrencies.

3 Capital

In Austrian capital theory the intertemporal structure of capital is an equilibrium consequence of entrepreneurial actions responding to changed incentives through the interest rate, or the cost of capital (Garrison 2001). Change in the market interest rate whether caused by changed time preference, or by monetary or fiscal policy – will induce a shift in the intertemporal structure of capital, with a lower interest rate inducing a longer period of production.² This mechanism connecting money and capital markets offers a theory of business cycles in which an artificial boom (caused by monetary or fiscal policy) inevitably leads to a bust through an intertemporal capital reallocation mechanism (Boettke 2018).

Austrian capital theory is economic analysis of the consequence that production takes time. Intertemporal coordination of capital is usually theorised from the Austrian perspective in terms of coordination of expectations under uncertainty, causing unstable investment (Shackle 1972; Loasby 1999; Potts 2000). However, the same insight can also be re-framed as a contracting-under-uncertainty problem, including expectations that complementary investments will be made and that contracts will be honoured. From this perspective, an Austrian economic analysis of blockchain begins by recognising that contracts occur in time to interlink capital structures of production. The cost of capital is the interest rate (equilibrium in money markets), and the cost of contracts is the cost of trust (Demsetz 1968; Novak et al. 2018), which we can think of as equilibrium in ‘governance markets’. A sequence of capital using activities implies a sequence of interlinked contracts and governance, and so the equilibrium form of these contracts will depend on the cost of trust. Austrian capital theory can in this way be extended to incorporate blockchain.

Production takes time. Production in time takes trust. Capital and trust are inputs into production. Larger capital structures require more secure property rights and institutional trust. Longer capital structures require greater trust owing to increased complexity of contracting. Changes in the cost of trust in consequences of new technologies of trust – e.g. blockchain, which industrialises trust (Berg et al. 2020) – will therefore affect capital structure the same way as changes in interest rates.

The total cost of capital structure in a modified ‘Hayekian triangle’³ is therefore composed of a finance cost of capital – the interest rate \(i\) – and a contracting cost – the cost of trust \(t\) – such that total cost \(=i+t\). As such, a reduction in the cost of trust (owing to an improvement in the technology of trust) will have the same effect on equilibrium capital structure as a fall in the interest rate. The relative effects of a reduction in the cost of trust vis-à-vis a fall in the interest rate is an empirical question that we do not address here. Five key economic effects follow from this insight.

First, trust is a co-factor determining equilibrium capital structure, along with the interest rate. A fall in the cost of trust \(t\), therefore, will have the same effect on capital structure (and consumption) as a fall in interest rates \(i\) : both cause an increase in ’roundaboutness’, thereby increasing consumption in the long run. The innovation and adoption of blockchain technology to reduce the cost of trust is therefore predicted, ceteris paribus, to induce a lower equilibrium interest rate.⁴

Second, trust has value. Following Menger’s Law (the theory of imputation in which the anticipated value of an end attaches itself to the means capable of achieving that end) the economic value of outputs from increased roundaboutness in capital will be bid into investment in technologies to lower the cost of trust. The economic value of blockchain technology is a monotonic function of the productive value of longer, more roundabout, more heterogenous capital structure.

Third, this analysis extends to consumption, which can also be conceived intertemporally. Blockchain technology facilitates use of tokens and smart contracts to control consumption through smart money (controlling forward options of consumption through programmable tokens, programmable internet money, or directed money). This implies a consumption path to Austrian capital theory too, where changes in the technology of smart money affect the time structure or pattern of consumption, just as changes in the technology of trust affect the pattern of production via changes in the cost of contracting. Directed money (smart money) changes consumption by enabling longer or more controlled consumption spending (as controlled by downstream parties to contracts). These might be welfare agencies, insurance companies, corporate accounts, or any locus of a payment transfer using money with additional functions (such as transparency and surveillance, controls, multisig permissioning, or voting), which in effect increases the ’roundaboutness of consumption’.

Fourth, this implies the existence of an endogenous cause of macroeconomic fluctuations due to changes in the cost of trust, such as might be caused by institutional technologies (Davidson et al. 2018) such as the emergence of nation states, implicit social contracts (McCloskey 2010), improvements in courts, and the invention of blockchains as platforms for high-trust economic coordination. To the extent that changes in the cost of trust can be positive or negative (viz. negative shocks, as increases in the cost of trust, owing to effects such as corruption) we can hypothesise the existence of ‘trust cycles’ in economic history, as the analogue of business cycles. Such a framework provides a foundation for an Austrian approach to development economics based around the costs of contracting and investment.

Fifth, a manifestation of longer and more complex capital structure are global supply chains made of multiple independent economic organisations (i.e. distinct legal, accounting and administrative entities) linked together through contractual relations. Falling cost of trust therefore predicts both less vertical integration in industrial supply chains and increased contractual linkages (Williamson 1985; Berg et al. 2019b), as well as increased globalisation in trade specialisation. This predicts an increase in complexity and scale of global interlinked production. A further implication operating inside organisations (as for instance with the emergence of decentralised autonomous organisations, or DAOs, see Werbach 2018) is that the lowered cost of contracting through smart contracts can be applied to the Austrian theory of the firm as an organisational bundle of heterogenous capital (i.e. resources, capabilities) (Foss 1994, 1993, Boudreaux and Holcombe 1989).

Capital is an economic mechanism to transform foregone consumption now (i.e. savings and investment) into greater future consumption. Economic growth theory (beginning with Solow 1956) measures capital as a stock (K), with equilibrium K balancing depreciation and investment flows. Unlike Austrian capital theory, the mainstream model removes capital from time (ODriscoll and Rizzo 1985), and therefore from hazards of opportunism, problems of coordination, and costs of contracting. But in an equilibrium model of capital in time (Hayek 1941; Lachmann 1956), changing time preferences changes interest rates which changes the incentives to entrepreneurial investment in longer or shorter capital structures (viz. more roundabout production, more heterogeneous capital).

Longer capital structures require more coordination (particularly of complementary investment), expose greater hazards of opportunism, depend more on security of property rights, and require more contracting and other governance mechanisms (Williamson 1985). Therefore, just as a change in the interest rate in the loanable funds market affects equilibrium capital structure, so too will a change in the cost of trust also affect equilibrium capital structure.

Longer, more complex capital structures therefore require greater investment not only in a stock of capital $(\mathrm{K})$ but also in the quality of governance mechanisms and institutions to facilitate more complex contracting over longer time horizons. Institutional technologies such as blockchain lower the cost of contracting by removing scope for opportunism and the need for costly real time monitoring and auditing, thereby enabling commercial promises to work better (Catalini and Gans 2017, Berg et al. 2020).

A general theory of long-run economic dynamics therefore requires a model of capital and institutional technology as an integration of Austrian capital theory (Garrison 2001) and institutional cryptoeconomics (Davidson et al. 2018).

4 Investment

Austrian capital theory, like endogenous growth theory (Romer 1990), is based on microeconomic foundations in which ‘there is no such thing as free growth’ (Garrison 2005). Economic growth is obtained by investment that foregoes current consumption in return for higher future consumption. Investment in technological change, including investment in human capital or new knowledge, is in this sense conceptually equivalent to an intertemporal reallocation of capital toward early stage production.

Innovation is equivalent in its effect on capital structure to a change in the loanable funds market caused by a lower interest rate (i.e. a change in intertemporal preferences). Economic growth is associated with the production process becoming more indirect, more ’roundabout’, or more complex (Potts 2000).⁵ The use of the price mechanism to handle the increased information becomes more important as the capital structure of the economy evolves in complexity. This is why markets matter more as an economy grows.

In Austrian Business Cycle theory (Hayek 1935) an artificial boom can occur because of malinvestment, which occurs when the ex ante investment allocation of capital across time into a particular structure of heterogenous capital does not match with ex post consumer preferences for ultimate consumption goods. This can arise because of entrepreneurial uncertainty about consumer demands and failures of information owing to missing or distorted markets. Austrian economists, however, tend to emphasise that a key cause of such distortions are policy interventions. A boom-bust cycle will therefore occur when policy-distorted interest rates induce malinvestment by shifting the intertemporal pattern of consumption and the capital structure of production (Garrison 2001).⁶

In this model, artificial policy shifts and monetary inflation cause expectational uncertainty about capital structure and prices (Lachmann 1956), hindering entrepreneurial action and economic coordination. However, a boom-bust cycle can cause innovation when coupled with entrepreneurial alertness (Kirzner 1973) to innovation discovery during the bust (Holcombe 2003, Potts 2004).

Consider a speculative mania caused by artificial policy action (such as easy credit conditions or generous public support for a new technology, e.g. green technologies) or by media-induced hype of the prospects of a new technology (e.g. artificial intelligence or blockchain, at the time of writing). Early investors rush in, induced by easy credit conditions and low opportunity cost of start-up operations.

Assume that in the first phase of the boom-bust cycle everything fails for standard malinvestment reasons. However, observe that the boom-bust process generates a lot of new economic information about out-of-equilibria conditions surrounding the new technological prospect (including information about production costs and market demand, new business models, and institutional barriers). This information forms a common-pool resource that can be usefully mined by a second wave of entrepreneurs (Allen and Potts 2016; Potts 2019).⁷

Boom-bust cycles in this way prime entrepreneurial discovery by incentivising exploration of out-of-equilibria conditions which is an information input into subsequent entrepreneurial plans. A boom-bust process in effect subsidises entrepreneurial discovery costs into the theory of the market process. Malinvestment in this way creates a non-contractual intertemporal externality in information as input into entrepreneurial discovery. The boom can produce information about experiments that can be gathered and recycled by entrepreneurs during the bust phase, when real cost of resources is cheaper (see also Hausmann and Rodrik 2003).

This thesis has several striking implications. First, bubbles may be important mechanisms for long-run economic growth because of their role in facilitating out-of-equilibrium information search and discovery (Potts 2004). This ‘real bubbles’ model endogenises innovation as the discovery of value while leaving technological change as the discovery of new physical properties in the world exogenous (Arthur 2009) due to the costs of entrepreneurial information discovery occurring in out-of-equilibrium conditions.

Second, the type of boom or bubble matters owing to its prospective yield of new information. A housing bubble, for instance will generate less new information than, say, a frontier technology bubble owing to the novelty of the search space. Generic asset bubbles are therefore of low yield and will often be substantially costly to society, whereas a technology bubble will more likely be net positive because of the new information about entrepreneurial opportunities it generates.

Third, the boom is necessary to generate information as out-of-equilibria search, but the bust is also necessary to release resources for entrepreneurial re-use. Relatedly, governance and coordination will often be required to efficiently assemble information into entrepreneurial opportunities (Allen and Potts 2016; Potts 2019). This implies low expected value in rational public planning of technological innovation. Instead, the main public policy function of innovation policy should be to promote a bubble and then to disseminate information and learnings from it (Bakhshi et al. 2011) in order to create a resource for entrepreneurial discovery.

Fourth, we can therefore distinguish between first-wave Schumpeterian entrepreneurship (boom), when public funding or loose-money dominates, and secondwave Kirznerian entrepreneurship (bust), when venture capital dominates. This integrates entrepreneurial discovery of value to real business cycles phases.

In the context of blockchain and cryptocurrencies, our defence of the information benefits of malinvestment for entrepreneurial discovery implies that technology-targeted loose money focused about a particular technological opportunity can be valuable by facilitating costly discovery of information about profit opportunities pertaining to that technology or business idea. This is the effect of an initial coin offering (ICO), which creates a private money for an idea, enabling a bubble (if one does form) to be contained within the space of the cryptocurrency. Hard money cryptocurrencies are protection against government debasement of money, and its distorting effect on the price mechanism, but ICO bubbles, or sector-specific bubbles are powerful focusing mechanisms of low opportunity cost exploration for the discovery of information about entrepreneurial opportunities.

5 Governance

5.1 Markets and macro order

Austrian economics engaged in two of the major intellectual disputes in twentieth century economics: with John Maynard Keynes on the nature of business cycles; and with Oscar Lange and Abba Lerner on the possibility of socialist calculation. It was widely perceived to have lost the argument in each instance.

In consequence, the theoretical focus of Austrian economics shifted from a macro focus on decentralised coordination in the market system (namely, the disputed territories it was perceived to have lost) and toward analytic focus on the microeconomics of particular markets or processes, and to political economy analysis of collective action problems, public choice (Buchanan and Tullock 1962), and rules and law (e.g. Hayek 1960, 1973). The macro-theoretical focus on whole-economy coordination of Austrian analysis thus fractured into microeconomic domains of information economics, organisational theory, industrial organisation, law and economics, New Institutional Economics, constitutional economics, and political economy, all eventually absorbing (albeit somewhat imperfectly) into the mainstream of economic analysis.

But the subsequent history of the world refutes the outcomes of the scholarly battles of the time, finding the Austrian economists right about both the nature of business cycles and the impossibility of socialist calculation. Yet history is written by the victors and a further consequence of the mid-century Austrian defeat was the analytic framing of subsequent theoretical discussion. For instance, the Keynesian and Neoclassical framing of business cycles and growth dynamics emphasises a causal logic of demand-side versus supply-side analysis (e.g. Nelson and Plosser 1982). However, the Austrian argument was about the primacy of particular factor markets in macroeconomic coordination, emphasising the role of capital markets (Mises 1980 [1912], Hayek 1935, 1941) over labour markets (e.g. Friedman 1968, 1977; Phelps 1968). In consequence, Austrian economists retreated to a “there’s no such thing as macro” line. Furthermore, basic questions about the nature of the market system and whether left to itself it would tend toward order or disorder was also reframed as a story about the domain of equilibrium theorising (along with analytical corollaries about bounded rationality, imperfect or asymmetric information, mechanism design, and so on).⁸ Evolutionary and complexity economics (e.g. Nelson and Winter 1982, Potts 2000) subsequently arose to develop non-equilibrium theoretical models of complex dynamical systems. However, the Austrian framing also proposes a different understanding of the consequences of decentralised decision making in market economies (Hayek 1945), locating the propagation mechanism of disequilibrium dynamics in capital markets and problems of knowledge coordination (see Fig. 1 below).⁹

Yet had the Austrian economists won those debates at the time, consider what might have happened. We can posit that, first of all, the Austrian framing of the basic economic problem as inquiry into the origins and nature of decentralised economic coordination in market economies would have persisted. And second, institutional economics and economic analysis of governance would have been clearly seen as part of the same inquiry. Hayek versus Keynes was about which factor market was coordinating the macroeconomy (capital or labour), and Mises-Hayek versus Lange-Lerner was about whether market economies produced macro coordination. But had Mises and Hayek won those debates, the next question would have gone beyond factor market substitution questions of macro dynamics (which became the entire story in mainstream analysis) but rather in the direction pointed to by Lachmann (1956) and Shackle (1972) (see Lavoie 1986, Loasby 1999) with respect to the evolution of institutional mechanisms (or innovation in institutional technologies) to govern decentralised orders. This brings us to the significance of blockchain and distributed ledger technologies for decentralised economic coordination (see Fig. 2 below).

Figure. 1: Macroeconomic Issues as Understood by Which Factor Market Coordinates the Economy

The defeat of Austrian economics has resulted in a lacuna in modern economics with respect to interest in institutional technologies of macroeconomic coordination in a decentralised order. Economic analysis became stuck in the domain of the HayekLange debate about decentralised versus centralised market orders and in the context of factor markets and relative factor costs, without consideration of further institutional competition and innovation in the production of governance. What we have missed is analysis of institutional substitution possibilities for the supply of decentralised coordination for private orders.

Fig. 2 Domain of Analysis of Decentralised Orders.

Blockchain or distributed ledger technology are institutional technologies of governance that supply decentralised coordination of identity management, record-keeping, registries, asset-transfer, payments and contracting. This suite of new institutional technologies is fumishing new ways of privately supplying economic coordination through money, property rights, and organisation through private provision of platform governance rules and mechanism for exchange and contracting (Davidson et al. 2018, Berg et al. 2019b). What we are now observing is not only the de-nationalisation of money (viz. Hayek 1990 [1976]), but a far broader de-nationalization of ledgers and therefore the basis of identity management, property rights, law, and record-keeping and social permissioning (e.g. licensing, credentialing, registries). The arrival of blockchain technology is beginning to usher in new domains of economic competition beyond the margins of factor market competition (e.g. substitution of capital for labour, in the context of centralised provision of the services of ‘order’) but to competition in the provision of order itself (e.g. self-sovereign identity, cryptocurrencies, smart contracts, decentralised exchanges, decentralised autonomous organisations, blockchain interoperability, and so on).

5.2 The trust engine

An Austrian macro view of blockchain therefore provides critical analytic purchase on a new understanding of the role of institutions in the dynamics of market economies. The central insight is this: market dynamics are ultimately built on the manufacture of trust, and decentralised market dynamics have historically relied on the centralised manufacture of trust. Adam Smith wrote that the division of labour is limited by the extent of the market, pointing to the mechanism (specialisation) by which market growth creates wealth. Our key insight is that the technologies of the manufacture of trust are a limit on the extent of the market. These institutional technologies began with the ability of a sovereign to furnish order (North and Weingast 1989, Olson 1993). Notably, these are centralised institutional technologies that circumscribe the domain within which the costs of trust between agents fall sufficiently to make trade, exchange, contracting and other forms of economic cooperation in the joint production of value worthwhile. But blockchain technology is an ‘existence proof’ of the possibility of decentralised provision of the institutional conditions for trade and exchange, which is to say of the manufacture of trust to facilitate economic coordination.¹⁰

The foundational engine of history is the manufacture of trust to enable economic cooperation (Gambetta 1988, Zak and Knack 2001, Nooteboom 2002, Bachmann and Zaheer 2006, Schneider 2012). Examples of trust engines, or of new mechanisms of trust upon which economies are built, are codes of law, nation states, constitutional governance, hierarchical organisations, and most recently blockchain, which is a new architecture of trust (Werbach 2018). Trust mechanisms enable markets to be created and when these mechanisms fail the result is missing markets and therefore missing opportunities for value creation through cooperation.

A blockchain is a three-sided market that enables two parties to trust information pertaining to mutual exchange or cooperation, and therefore to make promises without exposing themselves to hazards of opportunism, because a third party has performed work (Berg et al. 2020). A proof-of-work blockchain in this way converts energy intensive computation into economically valuable trust.

The limit of the market is bound by the manufacture of trust. Each technology of trust, or mechanism to engender trust, will therefore have a corresponding upper bound on the scale and scope of particular markets or other forms of economic cooperation that can be built upon them. The basic economic equation is that the cost of the trust mechanism must be less than the value of the trade that takes place. The trust mechanism can only consume up to the value of the surplus generated by economic cooperation under facilitated trust. Economic institutions facilitate not only mutual coordination (à la Schelling 1960) but do so in a way that economies on the cost of trust.

This creates economic competition to invent and implement institutional mechanisms or technologies that manufacture trust as an input into economic cooperation. Furthermore, entrepreneurship over institutions to create trust will create value to be captured by the creator of the platform (whether a government, or a governance mechanism.) The limit of an economy is therefore ultimately given by the extent of markets or other opportunities for economic cooperation that can be created with given trust technologies. A ‘trust technology’ can be modelled as a regular production function with resource inputs and with diminishing returns to cooperation through eventual discovery of all possible trades and capital etc., thus exhausting the zone of surplus between benefits of cooperation and cost of trust, and as opportunities to exploit the environment of cooperation incentivised by trust manufacturing institutions are revealed (Kreps 1990).

Because existing trust mechanisms eventually run into diminishing returns, a growing economy requires ongoing innovation in the development of new trust engines. A key insight of Austrian economics is to understand why innovation in trust engines and mechanisms must push in the direction of further decentralisation of the institutional foundations of an economic order, and therefore to understand the significance of blockchain and the technological capabilities it brings to distributed governance.

6 Technologies of self-sovereignty

Austrian economics offers a general analytic framework to understand the evolutionary significance of blockchain or distributed ledger technology for long-run economic dynamics. We began by noting that the cyberpunks who first developed cryptocurrencies clearly saw a decentralised digital private money as a technology solution to the perceived corruption of government money and modern institutional finance (Nakamoto 2008). This insight was based on an explicit understanding of the origin of money and its role in an economy that is foundational to the Austrian School of economics (Menger 2009 [1892], Szabo 2002). However, the point we have argued in this paper is that the Austrian economics of blockchain offers a broader domain of analysis than the Austrian economics of bitcoin and rests not on Austrian monetary theory but rather on Austrian capital theory (Hayek 1935, 1941). Blockchain is an institutional technology (Davidson et al. 2018) of decentralised private capital infrastructure (Berg et al. 2019a) to facilitate trade and exchange through the manufacture of trust (Berg et al. 2019b).

The basic insight can be expressed in the idea of technologies of self-sovereignty. A peer-to-peer electronic payments technology is a self-sovereign money that does not rely on the permission of the state to work, but enables trust in value transfer between individuals. Self-sovereign identity is the ability of individual people (or machines) to assert verifiable claims about themselves that enable trusted interactions and contracting, including transferring money or making contracts. Smart contracts (Szabo 1997) are an ability to contract without hazards of opportunism caused by the need to trust third party monitoring and enforcement. Self-sovereign blockchains are the ability of private individuals to provide registries of data, identity, mappings, claims and other administrative inputs into economic organisation and coordination without the need for a trusted centralised state to provide this foundational institutional layer.

Blockchain is an institutional innovation that industrialises the manufacture of trust. Blockchains manufacture trust in a distributed and decentralised way, pushing consumer sovereignty deeper into the institutional foundations of an economic order. The effect of this is to erode the power of centralised control over the administrative infrastructure of a market economy in recording economic facts such as property rights, ownership and contracts. In this sense, blockchain is a technology of freedom (Allen et al. forthcoming).

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Footnotes

1. See, e.g. https://medium.com/@hayekian/how-bitcoin-spreads-austrian-economics-and-thus-worldwide-intellectual-revolution-9df49929725d ↩︎
2. What Menger called ‘higher-order goods’, Böhm-Bawerk (1889) called ’roundaboutness’, Hayek (1931) called ‘stages of production’, and Lachmann (1956) called ‘heterogenous capital’. ↩︎
3. “Hayek greatly simplified the Austrian vision of a capital-using economy by modelling the economy’s production activities as a sequence of inputs and a point of output.” (Garrison 2001, p. 2). ↩︎
4. Obviously, this prediction depends upon factor elasticities and bargaining outcomes as to where rents are captured, i.e. whether by consumers through lower prices (income effects dominate) or by other factors as increased rents (substitution effects dominate). ↩︎
5. This accords with Adam Smith’s (1776) idea of the origin of wealth arising from the market process of an increased division of labour and division of knowledge. ↩︎
6. Sustainable economic growth in long run consumption is only possible through an exogenous increase in technology (e.g. real business cycle theory, Nelson and Plosser 1982) or change in intertemporal preference that induces longer capital structure. ↩︎
7. viz. “The early bird gets the worm, but the second mouse gets the cheese.” ↩︎
8. Equilibrium theorising arrived mid-century with the formal turn in economic analysis ushered in by Paul Samuelson, Arrow-Debreu, et al. (see Mirowski 1989). This provided the context for generalised theoretical and empirical analysis of departures from equilibrium in terms of bounded rationality, imperfect information, competitive frictions, etc. ↩︎
9. And some Post-Keynesian analysis, building on Keynes (1936: ch 12) (e.g. Shackle 1978, Loasby 1999). ↩︎
10. This was the analytic direction Austrian economics was heading before its mid-century defeat pulled focus away from analysis of decentralised orders. ↩︎