Difference between revisions of "Won and Jang (2012)"

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1. Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare 2. Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)? 3. Harmony of interest assumption between authors and publishers (creators and producers/investors) 4. Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption) 5. Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media)

A. Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right) B. Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction) C. Mass digitisation/orphan works (non-use; extended collective licensing) D. Licensing and Business models (collecting societies; meta data; exchanges/hubs; windowing; crossborder availability) E. Fair remuneration (levies; copyright contracts) F. Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness)

Source Details

Won and Jang (2012)
Title: Nonlinear income inequality effect on software piracy
Author(s): Won, S. J., Jang, J.
Year: 2012
Citation: Won, S. J., & Jang, J. (2009). Nonlinear income inequality effect on software piracy. Available at SSRN 1478907.
Link(s): Open Access
Key Related Studies:
Discipline:
Linked by:
About the Data
Data Description: Data set included 40 countries from 2003 to 2007 with 106 observations. The piracy rate was employed by the rate reported by the Business Software Alliance (BSA) consultants International Data Corporation (IDC).

The explanatory variables include the degree of economic inequality and four control variables which are: national income, judicial efficiency, individualism, and internet broadband subscribers.

  • Income information was obtained through the World Income Inequality Database V2.0c (WIID2) established by the World Institute for Development Economics Research of the United Nations University (UNU-WIDER).
  • Gross National Income data was extracted from the World Bank’s World Development Indicators (WDI) database.
  • The Rule of Law provided the indicator for judicial efficiency from the World Governance Indicator Project developed by the World Bank.
  • Individualism was measured by adopting an index by social psychologist Geert Hofstede.
  • The percentage population of Fixed Broadband Subscribers was measured from data of the World Telecommunication/Information and Communication Technologies (ICT) Indicators (WTII) which are established by International Telecommunications Union (ITU).
Data Type: Primary and Secondary data
Secondary Data Sources:
Data Collection Methods:
Data Analysis Methods:
Industry(ies):
Country(ies):
Cross Country Study?: Yes
Comparative Study?: No
Literature review?:
Government or policy study?:
Time Period(s) of Collection:
  • Prior to 2007
Funder(s):
  • Not stated

Abstract

We examine the relationship between income inequality and piracy rates in the presence of network effects. By the constructions of a theoretical framework, we are able to explain the relationship between income distributions and software piracy rates. Our research suggests that the proportion of the population with positive net benefits from piracy increases with income inequality at a diminishing rate, and then eventually decreases. We provide empirical evidence for this inverted U-shaped relationship between income inequality and piracy rates, while controlling for income, judicial efficiency, and fixed broadband subscribers. Our theoretical and empirical results imply that lax anti-piracy policies would make software producers better off (i.e., higher software sales because of network effects) in countries whose income inequality is moderate, but worse off in countries whose income inequality is severe. Therefore, policies against piracy should be strategically designed considering the non-linear effects of income inequality.

Main Results of the Study

  • National income has a negative and statistically significant effect on piracy rates across eight regression models. Nations with higher income levels exhibit smaller piracy rates, after controlling for indirect income effects, judicial efficiency, and fixed broadband subscribers.
  • The percent of the population of fixed broadband subscribers is negatively associated with piracy rate across all models, but the coefficients are only statistically significant in some models.
  • Results indicate that the percentage of the population of fixed broadband subscribers had a negative effect on piracy rate and this result is significant in several models. However, this result is inconsistent with the existing studies that consider the internet as a piracy enhancing tool.


Policy Implications as Stated By Author

  • Firms would be better off to allow a certain level of piracy in countries that have moderate income inequality since harsh policies against piracy may unduly shrink a potential network growth.
  • In contrast, in countries which have severe income inequality, allowing piracy gives little benefit to software publishers because most computer users are in the upper class.
  • Therefore, lax anti-piracy policy may reduce the cost of pirated software use without increasing the total software users. This suggests that preventative policies against piracy need to be strategically established considering the level of income inequality of each nation.


Coverage of Study

Coverage of Fundamental Issues
Issue Included within Study
Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare
Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)?
Harmony of interest assumption between authors and publishers (creators and producers/investors)
Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption)
Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media)
Green-tick.png
Coverage of Evidence Based Policies
Issue Included within Study
Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right)
Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction)
Mass digitisation/orphan works (non-use; extended collective licensing)
Licensing and Business models (collecting societies; meta data; exchanges/hubs; windowing; crossborder availability)
Green-tick.png
Fair remuneration (levies; copyright contracts)
Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness)
Green-tick.png

Datasets

Sample size: 40
Level of aggregation: Country
Period of material under study: 2003-2007


Sample size: 4
Level of aggregation: Years
Period of material under study: 2003-2007


Sample size: 106
Level of aggregation: Observations
Period of material under study: 2003-2007