Vinsamlegast notið þetta auðkenni þegar þið vitnið til verksins eða tengið í það: http://hdl.handle.net/1946/18234
This thesis aims to explore whether digital crypto-currencies such as Bitcoin can be considered money from the perspective of the Austrian school of economics. It begins by describing the functions and design of the Bitcoin system in detail. Other innovations that either build on or improve Bitcoin will be explained as well. The functions of money are then defined from the origins of money, providing a categorical approach toward a comparison between Bitcoin and incumbent money. The risks and complications of Bitcoin will be discussed in this thesis with an emphasis on the role of policymakers. One of the main reasons why Bitcoin has yet to be regarded as money in a traditional narrow sense is the barrier generated by network effects, in particular, the presence of excess inertia. Other risks and complications that are present within the context of this thesis will also be discussed.
A significant part of the criticism of Bitcoin as a medium of exchange that comes from the Austrian school arises because Bitcoin does not seem to follow the regression theorem Mises put forth to explain the emergence of money. An attempt will be made to reform the regression theorem so it accounts for digital innovations such as Bitcoin, if proven unsuccessful, another perspective is offered in which Bitcoin does not violate the theorem. When the complication of the regression theorem is solved, it is possible to address whether Bitcoin is money or just a secondary medium of exchange.
From an Austrian perspective, Bitcoin is not money, however, an argument will be made that Bitcoin is an imperfect form of memory, one which fits somewhere in between commodity money and fiat money, a synthetic commodity money. The possibility of Bitcoin substitutes to incite an expansion of the money supply will also be analysed from an Austrian perspective.
Subject: Regression theorem, Bitcoin, Austrian economics, Synthetic commodity money, Network effects