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A Note on Cryptocurrencies and Currency Competition

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  • Almosova, Anna

Abstract

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.

Suggested Citation

  • Almosova, Anna, 2018. "A Note on Cryptocurrencies and Currency Competition," IRTG 1792 Discussion Papers 2018-006, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  • Handle: RePEc:zbw:irtgdp:2018006
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    References listed on IDEAS

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    1. Fernández-Villaverde, Jesús & Sanches, Daniel, 2019. "Can currency competition work?," Journal of Monetary Economics, Elsevier, vol. 106(C), pages 1-15.
    2. Berentsen, Aleksander, 2006. "On the private provision of fiat currency," European Economic Review, Elsevier, vol. 50(7), pages 1683-1698, October.
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    6. Marimon, Ramon & Nicolini, Juan Pablo & Teles, Pedro, 2012. "Money is an experience good: Competition and trust in the private provision of money," Journal of Monetary Economics, Elsevier, vol. 59(8), pages 815-825.
    7. Klein, Benjamin, 1974. "The Competitive Supply of Money," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 6(4), pages 423-453, November.
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    Cited by:

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    4. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Packham, Natalie & Woebbeking, Fabian, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," IRTG 1792 Discussion Papers 2018-034, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
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    7. Xiaojia Bao & Qingliang Fan, 2020. "The impact of temperature on gaming productivity: evidence from online games," Empirical Economics, Springer, vol. 58(2), pages 835-867, February.
    8. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    9. Kuczmaszewska, Anna & Yan, Ji Gao, 2018. "On complete convergence in Marcinkiewicz-Zygmund type SLLN for random variables," IRTG 1792 Discussion Papers 2018-041, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Packham, Natalie, 2018. "Optimal contracts under competition when uncertainty from adverse selection and moral hazard are present," IRTG 1792 Discussion Papers 2018-033, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    15. Wang, Honglin & Yu, Fan & Zhou, Yinggang, 2018. "Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach," IRTG 1792 Discussion Papers 2018-051, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    16. Yan, Ji Gao, 2018. "Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables," IRTG 1792 Discussion Papers 2018-040, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    17. Max Fuchs, 2022. "CBDC as Competitor for Bank Deposits and Cryptocurrencies," MAGKS Papers on Economics 202210, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    18. Kalkbrener, Michael & Packham, Natalie, 2018. "Correlation Under Stress In Normal Variance Mixture Models," IRTG 1792 Discussion Papers 2018-035, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    19. Guizhou Wang & Kjell Hausken, 2022. "Competition between Variable–Supply and Fixed–Supply Currencies," Economies, MDPI, vol. 10(11), pages 1-20, October.
    20. Burda, Michael C., 2021. "Valuing cryptocurrencies: Three easy pieces," IRTG 1792 Discussion Papers 2021-011, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    21. Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    22. Guo, Shaojun & Li, Dong & Li, Muyi, 2018. "Strict Stationarity Testing and GLAD Estimation of Double Autoregressive Models," IRTG 1792 Discussion Papers 2018-049, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    23. Koziuk, Andzhey & Spokoiny, Vladimir, 2018. "Toolbox: Gaussian comparison on Eucledian balls," IRTG 1792 Discussion Papers 2018-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

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    More about this item

    Keywords

    Currency competition; Cryptocurrency; Inflation; Blockchain;
    All these keywords.

    JEL classification:

    • E40 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - General
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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