USF St. Petersburg campus Honors Program Theses (Undergraduate)


Jesse S. Daw

First Advisor

Suzanne Dieringer, M.A. in Economics, Visiting Professor, College of Business


University of South Florida St. Petersburg

Document Type


Date Available

May 2014

Publication Date


Date Issued

April 2014


The development of the internet has brought about a profound shift in the music industry for both record labels and the artists they represent. This shift has come as a result of modem capabilities for music to be hosted online and available to be downloaded by consumers over the internet. These innovations have allowed record labels and independent musicians to sell their music through a new and convenient medium, and services provided by companies such as ITunes and Amazon have introduced more options for consumers purchasing music. However, the ability to access music over the internet has created a new type of criminal who can easily steal or "pirate" music that has been openly shared by others on online file sharing networks. The purpose of this study is to identify variables that affect consumer demand for illegally downloaded music. In pursuit of this goal, a logit regression model will be used with maximum likelihood estimation to test multiple variables that are expected to affect demand. The variables that will be tested are: age, gender, grade point average, race, annual income bracket, use of streaming services, convenience of illegal downloads, perceived moral obligations, price of music relative to income, and low perceived risk of legal ramifications. By using a logit model to determine how these variables affect the likelihood that consumers will download music illegally, it will become clear how each variable weighs into the consumer decision making process and affects their demand for illegal music downloads.


A thesis submitted in partial fulfillment of the requirements of the University Honors Program, University of South Florida St. Petersburg.

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Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.