INTERNATIONAL DETERMINANTS OF SOFTWARE PIRACY Jacob Aaron

67 Pages·2011·0.27 MB·English

INTERNATIONAL DETERMINANTS OF SOFTWARE PIRACY

Jacob Aaron Boyce
B.A., California State University, Sacramento, 2008

THESIS

Submitted in partial satisfaction of
the requirements for the degree of

MASTER OF ARTS

in

ECONOMICS

at

CALIFORNIA STATE UNIVERSITY, SACRAMENTO

SPRING
2011
© 2011

Jacob Aaron Boyce
ALL RIGHTS RESERVED
ii
INTERNATIONAL DETERMINANTS OF SOFTWARE PIRACY

A Thesis

by

Jacob Aaron Boyce

Approved by:

____________________________, Committee Chair
Jonathan Kaplan

____________________________, Second Reader
Craig Gallet

Date:________________________
iii
Student: Jacob Aaron Boyce

I certify that this student has met the requirements for format contained in the University
format manual, and that this thesis is suitable for shelving in the Library and credit is to
be awarded for the thesis.

____________________________, Department Chair _______________
Mark Siegler Date

Department of Economics
iv
Abstract
of
INTERNATIONAL DETERMINANTS OF SOFTWARE PIRACY
by
Jacob Aaron Boyce

As life becomes increasingly more digital, copying and distributing lossless copies of
copyrighted material is quicker and simpler than ever. For the owners and producers of
copyrighted material, there are very real implications for easier reproduction of their
works. With the rise of the Internet and broadband Internet worldwide, does this
increased connectivity lead to increased rates of software piracy? I approach this
question with unbalanced panel data consisting of 105 nations during the time period of
2006-2009, allowing for control of unknown and immeasurable characteristics among
nations. The results find that increased broadband Internet penetration rates lead to
increased piracy rates.

____________________________, Committee Chair
Jonathan Kaplan

____________________________
Date
v
TABLE OF CONTENTS
Page
List of Tables .................................................................................................................... vii 
List of Figures .................................................................................................................. viii
Chapter

1. INTRODUCTION ..........................................................................................................1 
2. LITERATURE REVIEW ...............................................................................................5 
2.1. Theoretical Analysis ................................................................................................. 5 
2.2. Cross-sectional Regression Analysis ....................................................................... 9 
2.3. Panel Data Analysis ............................................................................................... 18 
2.4. Conclusion .............................................................................................................. 20 
3. DATA SUMMARY ......................................................................................................22 
3.1. Summary Statistics ................................................................................................. 22 
3.2. Proposed Regression Analysis and Expected Results ............................................ 35 
4. EMPIRICAL ANALYSIS ............................................................................................37 
4.1 Ordinary Least Squares Regression ........................................................................ 37 
4.2 OLS Results Interpretation ...................................................................................... 40 
4.3 Panel Regression ..................................................................................................... 42 
4.4 Panel Regression Interpretation .............................................................................. 48 
5. CONCLUSION .............................................................................................................51 
Appendix. Data Sources ...................................................................................................55 
References ..........................................................................................................................56 
vi
LIST OF TABLES
Page

3.1. Descriptive Statistics ..................................................................................................22 
3.2. Correlogram ................................................................................................................29 
4.1. Ordinary Least Squares Regression Results ...............................................................38 
4.2. Fixed Effects and Random Effects Regression Results ..............................................44 
4.3. Fixed Effects Regression Results (Continued) ...........................................................47 

vii
LIST OF FIGURES
Page

3.1. Scatter Plot with Fitted Line for Piracy Rate and Broadband Penetration Rate ........ 30 
3.2. Scatter Plot with Fitted Line for Piracy Rate and Internet Penetration Rate ..............31 
3.3. Scatter Plot with Fitted Line for Piracy Rate and ln(rGDP) .......................................31 
3.4. Scatter Plot with Fitted Line for Piracy Rate and IPR ................................................32 
3.5. Scatter Plot with Fitted Line for Piracy Rate and HDI ...............................................33 
3.6. Scatter Plot with Fitted Line for Piracy Rate and Gini ...............................................33 
3.7. Scatter Plot with Fitted Line for Piracy Rate and ROL ..............................................34 
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1

Chapter 1
INTRODUCTION
Each year, our world becomes increasingly more advanced and digital
technologies permit faster distribution and more exact copies of original works to be
distributed with ease. Piracy of copyrighted works has been a longstanding issue, even
before the advances of modern computers. Prior to computers, piracy was done through
analog means such as making a recording of a cassette tape, making a copy of a VHS
video, or recording a live concert using a hidden tape recorder. Today, people access
many forms of media with computers. Computers can now display electronic books, play
music, movies, and run games and software applications as well. Within the last two
decades not only have these media forms become ever more present on computers but the
Internet has also experienced a surge in growth. Initially, the Internet surge was just dial-
up connections but in the past ten years, broadband Internet access and usage has seen
huge growth worldwide as well, growing from 394 million users or six percent of the
world’s population in 2000 to nearly 2.1 billion or 30 percent of the world’s population in
2010 according to the International Telecommunications Union.1
Though there are many types of piracy that may occur today, the focus of this
thesis is on business software application piracy. The Business Software Alliance (BSA)
publishes a yearly worldwide report of business software piracy rates. This thesis uses
the data published in the BSA report to study the causes of piracy.

1 A listing of data sources and the Internet address to locate the data are included in the appendix at the end
of this thesis.
2

The rate of software piracy may have a large variety of determinants. Among the
determinants may be social, political, economic, and technological variables.
Specifically, this thesis seeks to examine the relationship between expanded use and
availability of the Internet and broadband Internet to the rate of piracy.
Previous literature has primarily employed cross-sectional data sets and chosen an
assortment of social, political, economic and technological variables to find determinants
of piracy rates. Departing from the prior literature, this thesis employs panel data
analysis to control for unique characteristics across countries and time rather than cross-
sectional data chosen for just a single year.
Secondly, the objective is to determine the relationship between Internet and
broadband Internet penetration rates and the rates of piracy, whereas earlier research has
not had as narrow a focus but instead attempted to identify broad structural models for
determining piracy rates. The breadth of the variables chosen in this prior research is
critical to the decision of other researchers to choose cross-sectional data instead of panel
data. Many of the political and social variables do not change much over time and thus
are included in the fixed effects in a panel regression.
As previously mentioned, a panel of data is used to create a model using fixed
effects. The use of country fixed effects allows for control of immeasurable and
unknown variables which are fixed in time but vary across countries. By also allowing
for fixed effects across time, differences from year to year that occur across all countries
can be controlled. The fixed effects model allows for fewer variables to be chosen as
explanatory variables because the fixed effects account for factors that change very