Date of Award


Document Type

Open Access

Degree Name

Bachelor of Arts



First Advisor

Harlan Holt




bitcoin, regression theory


Virtual currencies emerged in 2009 as alternatives to traditional methods of payment, offering faster transaction speeds and increased privacy. The prime example of these currencies is Bitcoin. Prior literature in the past five years has generally predicted that bitcoin would fail to supplant an existing widely traded currency, but the volatility of the currency has been decreasing since then. I test Dowd and Greenaway’s (1993) currency acceptance model using recent data on Bitcoin, including Bitcoin volatility. This paper will show whether Bitcoin's ability to act as a store of value and its level of price volatility affect the number of people that will accept it as a currency. Confidence in existing currencies may be weakening, and thus, analyzing the relationship between volatility and currency acceptance is significant in understanding the future behavior of currencies. I will employ a time-series vector autoregression to determine the effects of the number of vendors that accept Bitcoin, the volatility of the Bitcoin, the volatility of the dollar, and the volatility of the Euro on both Bitcoin volatility and the number of vendors that accept Bitcoin. I will also run Newey-West regressions to determine the effects of each volatility on the number of vendors.