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Global Software Piracy, Technology and Property Rights Institutions
- Published: 22 April 2020
- Volume 12 , pages 1036–1063, ( 2021 )
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- Simplice A. Asongu 1
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This study extends the literature on fighting software piracy by investigating how Intellectual Property Rights (IPRs) regimes interact with technology to mitigate software piracy when existing levels of piracy are considered. Two technology metrics (internet penetration rate and number of PC users) and six IPR mechanisms (constitution, IPR law, main IP laws, WIPO Treaties, bilateral treaties and multilateral treaties) are used in the empirical analysis. The statistical evidence is based on (i) a panel of 99 countries for the period 1994–2010 and (ii) interactive contemporary and non-contemporary quantile regressions. The findings show that the relevance of IPR channels in the fight against software piracy is noticeably contingent on the existing levels of technology embodied in the pirated software. There is a twofold policy interest for involving modern estimation techniques such as interactive quantile regressions. First, it uncovers that the impact of IPR systems on software piracy may differ depending on the nature of technologies used. Second, the success of initiatives to combat software piracy is contingent on existing levels of the piracy problem. Therefore, policies should be designed differently across nations with high, intermediate and low levels of software piracy.
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With respect to this strand of the literature, more strict IPR regimes are adopted as nations make the transition from ‘developing countries’ to ‘developed countries’. Such tight IPR regimes are likely to, inter alia: (i) boost innovation and technology transfer (Lee and Mansfield 1996 ); (ii) favour exports (Maskus and Penubarti 1995 ); and (iii) enhance investment by multinational corporations (see Mansfield 1994 ; Seyoum 1996 ).
Throughout this study, the terms ‘piracy’ and ‘software piracy’ are employed interchangeably.
The countries are presented in panel B of Table 8 in the Appendix.
SIIA stands for Software and Information Industry Association.
Data from the BSA primarily measures commercial software piracy. For more insights into the reliability of the piracy data, the interested reader can refer to inter alia: Traphagan and Griffith ( 1998 ) and Png ( 2008 ).
The adopted software piracy data has been used extensively in the literature on piracy (Marron and Steel 2000 ; Goel and Nelson 2009 ; Andrés 2006a ; Banerjee et al. 2005 ).
The interested reader can refer to an example (e.g. Indonesia) for more insights into how the data is collected: http://www.wipo.int/wipolex/en/profile.jsp?code=ID .
http://www.wipo.int/wipolex/en/
For ease of presentation and purpose of simplicity, the quantile estimator is disclosed without subscripts in Eq. ( 1 ).
The term ‘broad’ is employed to emphasise the fact that this study cannot be directly compared with Asongu ( 2015 ) because the latter is (i) focused exclusively on Africa: (ii) based on mean values of software piracy and (iii) is modelled with non-interactive specifications.
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Asongu, S.A. Global Software Piracy, Technology and Property Rights Institutions. J Knowl Econ 12 , 1036–1063 (2021). https://doi.org/10.1007/s13132-020-00653-1
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Received : 19 April 2019
Accepted : 29 March 2020
Published : 22 April 2020
Issue Date : September 2021
DOI : https://doi.org/10.1007/s13132-020-00653-1
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