Arbeitspapier

A Note on Cryptocurrencies and Currency Competition

The recent development of private cryptocurrencies has created a need to extend existing models of private currency provision and currency competition. The outcome of cryptocurrency competition should be analyzed in a model which incorporates important features of the modern cryptocurrencies. In this paper I focus on two such features. First, cryptocurrencies operate according to a protocol - a blockchain - and are, therefore, free from the time-inconsistency problem. Second, the operation of the blockchain costs real resources. I use the Lagos-Wright search theoretic monetary model augmented with privately issued currencies as in Fernandez-Villaverde and Sanches (2016) and extend it by linear costs of private currency circulation. I show that in contrast to Fernandez-Villaverde and Sanches (2016) cryptocurrency competition 1) does not deliver price stability and 2) puts downward pressure on the ination in the public currency only when the costs private currency circulation (mining costs) are suciently low.

Sprache
Englisch

Erschienen in
Series: IRTG 1792 Discussion Paper ; No. 2018-006

Klassifikation
Wirtschaft
Money and Interest Rates: General
Monetary Systems; Standards; Regimes; Government and the Monetary System; Payment Systems
Monetary Policy, Central Banking, and the Supply of Money and Credit: General
Central Banks and Their Policies
Thema
Currency competition
Cryptocurrency
Inflation
Blockchain

Ereignis
Geistige Schöpfung
(wer)
Almosova, Anna
Ereignis
Veröffentlichung
(wer)
Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
(wo)
Berlin
(wann)
2018

Handle
Letzte Aktualisierung
10.03.2025, 11:45 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Almosova, Anna
  • Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"

Entstanden

  • 2018

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