A Theory of Optimum Cryptocurrency Scope
2019, Economics of Innovation and New Technology
https://doi.org/10.1080/10438599.2019.1687395Abstract
Robert Mundell (1961) framed the fixed-versus-flexible exchange rate controversy in a novel way when he focused attention on currency areas and the ingredients necessary for a group of nations to form an optimal currency area (OCA). This paper proposes an analogous theory for cryptocurrencies, called optimal currency scope (OCS), and explains the conditions necessary for an OCS to exist. In contrast to an OCA, which is defined by its non-overlapping geographic areas, an OCS is defined by its multiple-overlapping attributes and the needs they solve, which we call scope. Scopes are not geographic and have fuzzy boundaries; so, the possibility of competing currencies in a single scope needs to be considered. The central issues surrounding an OCS are the optimal number and magnitude of currency attributes, rather than whether nations should adopt fixed versus fluctuating exchange rates. Similar to the findings since Mundell first introduced his OCA Theory, we find that the optimum number of cryptocurrency attributes and, therefore, the optimal number of cryptocurrencies must be determined empirically rather than theoretically. A copy of the published version of this article may be downloaded at https://www-tandfonline-com.ezproxy.babson.edu/eprint/WDQSCQGCXEHXUQ4S5AFT/full?target=10.1080/10438599.2019.1687395.
Key takeaways
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- The concept of optimal currency scope (OCS) extends Mundell's optimal currency area (OCA) theory to cryptocurrencies.
- OCS focuses on overlapping attributes of currencies, contrasting with the geographic nature of OCA.
- Determining the optimal number of cryptocurrency attributes requires empirical analysis, not just theoretical reasoning.
- Scopes in OCS have fuzzy boundaries, accommodating the coexistence of multiple currencies within a single scope.
- The paper emphasizes the necessity of solving specific needs through currency attributes in cryptocurrency ecosystems.