Determinants of worldwide software piracy losses
Abstract
This paper studies the determinants of software piracy losses along five major macroeconomic dimensions: Technological, Educational, Institutional, Access to Information and Labor force. The study was conducted based on a large dataset available from 1995 to 2010 and comprising 81 countries.
As for the Technological dimension, more patents by residents increases piracy losses while the effect of R&D is the opposite (decreases piracy losses). In terms of the Educational dimension, the results show that more spending on education increase the piracy losses but, at the same time, more schooling years have the contrary effect. Concerning the Institutional dimension, nations with less corruption have lower piracy levels. Regarding the Access to Information, it seems that access to Internet diminishes the losses while the share of Internet broadband subscriptions has no effect. The results also show that, regarding the Labor dimension, employment in services has a deterrent effect while labor force with higher education and youth unemployment increases piracy losses.
First published online 20 October 2015
Keyword : piracy losses, software piracy, copyright, system GMM
How to Cite
Gomes, N. D., Cerqueira, P. A., & Alçada-Almeida, L. (2018). Determinants of worldwide software piracy losses. Technological and Economic Development of Economy, 24(1), 48–66. https://doi.org/10.3846/20294913.2015.1074128
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Mishra, A.; Akman, I.; Yazici, A. 2007. Organizational software piracy: an empirical assessment, Behaviour & Information Technology 26(5): 437–444. http://dx.doi.org/10.1080/01449290500483577
Poddar, S. 2005. Why software piracy rates differ – a theoretical analysis. National University of Singapore, Department of Economics.
Roodman, D. 2009a. How to do xtabond2: an introduction to difference and system GMM in Stata, Stata Journal 9(1): 86–136.
Roodman, D. 2009b. A note on the theme of too many instruments, Oxford Bulletin of Economics and Statistics 71(1): 135–158. http://dx.doi.org/10.1111/j.1468-0084.2008.00542.x
Siponen M.; Vance, A.; Willison, R. 2012. New insights into the problem of software piracy: the effects of neutralization, shame, and moral beliefs, Information & Management 49(7–8): 334–341. http://dx.doi.org/10.1016/j.im.2012.06.004
Soto, M. 2009. System GMM estimation with a small sample: Barcelona Graduate School of Economics.
van Kranenburg, H.; Hogenbirk, A. 2005. Multimedia, entertainment, and business software copyright piracy: a cross-national study, Journal of Media Economics 18(2): 109–129. http://dx.doi.org/10.1207/s15327736me1802_3
Akbulut, I. 2014. Exploration of the antecedents of digital piracy through a structural equation model, Computers & Education 78: 294–305. http://dx.doi.org/10.1016/j.compedu.2014.06.016
Andrés, A. R. 2006a. The relationship between copyright software protection and piracy: evidence from Europe, European Journal of Law and Economics 21(1): 29–51. http://dx.doi.org/10.1007/s10657-006-5670-5
Andrés, A. R. 2006b. Software piracy and income inequality, Applied Economics Letters 13(2): 101–105. http://dx.doi.org/10.1080/13504850500390374
Andrés, A. R.; Asongu, S. 2013. Fighting software piracy: which governance tools matter in Africa?, Journal of Business Ethics 118(3): 667–682. http://dx.doi.org/10.1007/s10551-013-1620-7
Andrés, A. R.; Goel, R. K. 2011. Corruption and software piracy: a comparative perspective, Policy & Internet 3(3): 1–22. http://dx.doi.org/10.2202/1944-2866.1088
Andrés, A. R.; Goel, R. K. 2012. Does software piracy affect economic growth? Evidence across countries, Journal of Policy Modeling 34(2): 284–295. http://dx.doi.org/10.1016/j.jpolmod.2011.08.014
Arellano, M.; Bond, S. 1991. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations, The Review of Economic Studies 58(2): 277–297. http://dx.doi.org/10.2307/2297968
Arellano, M.; Bover, O. 1995. Another look at the instrumental variable estimation of error-components models, Journal of Econometrics 68(1): 29–51. http://dx.doi.org/10.1016/0304-4076(94)01642-D
Asongu, S. 2012. Fighting software piracy in Africa: how do legal origins and IPRs protection channels matter?, Journal of the Knowledge Economy, 1–22. http://dx.doi.org/10.1007/s13132-012-0137-0
Baltagi, B. 2008. Econometric analysis of panel data. 4th ed. John Wiley & Sons.
Banerjee, D.; Khalid, A. M.; Sturm, J. E. 2005. Socio-economic development and software piracy. An empirical assessment, Applied Economics 37(18): 2091–2097. http://dx.doi.org/10.1080/00036840500293276
Barro, R. J. 2013. Education and economic growth, Annals of Economics and Finance 14(2): 301–328.
Barro, R. J.; Lee, J. W. 2013. A new data set of educational attainment in the world, 1950–2010, Journal of Development Economics 104(0): 184–198. http://dx.doi.org/10.1016/j.jdeveco.2012.10.001
Blundell, R.; Bond, S. 1998. Initial conditions and moment restrictions in dynamic panel data models, Journal of Econometrics 87(1): 115–143. http://dx.doi.org/10.1016/S0304-4076(98)00009-8
Boyce, J. A. 2011. International determinants of software piracy: Master’s thesis [online]. California State University [cited 30 January 2013]. Available from Internet: http://hdl.handle.net/10211.9/1087
BSA. 2012. Shadow market: 2011 BSA Global Software Piracy Study. Business Software Alliance.
Chen, C. C.; Chen, C. P.; Yeh, C. Y. 2010. Determinants of software piracy: evidence from far East countries, Journal of International and Global Economic Studies 3(2).
Cho, H.; Chung, S.; Filippova, A. 2015. Perceptions of social norms surrounding digital piracy: the effect of social projection and communication exposure on injunctive and descriptive social norms, Computers in Human Behavior 48: 506–515. http://dx.doi.org/10.1016/j.chb.2015.02.018
Fishbein, M.; Ajzen, I. 1975. Belief, attitude, intention and behavior: an introduction to theory and research. Boston: Addison Wesley.
Goel, R. K.; Nelson, M. 2009. Determinants of software piracy: economics, institutions, and technology, The Journal of Technology Transfer 34(6): 637–658. http://dx.doi.org/10.1007/s10961-009-9119-1
Goel, R. K.; Nelson, M. A. 2012. Shadow economy and international software piracy, Applied Financial Economics 22(23): 1951–1959. http://dx.doi.org/10.1080/09603107.2012.690848
Hansen, L. P. 1982. Large sample properties of generalized method of moments estimators, Econometrica 50(4): 1029–1054. http://dx.doi.org/10.2307/1912775
Judson, R. A.; Owen, A. L. 1999. Estimating dynamic panel data models: a guide for macroeconomists, Economics Letters 65(1): 9–15. http://dx.doi.org/10.1016/S0165-1765(99)00130-5
Knack, S.; Keefer, P. 1995. Institutions and economic performance: cross-country tests using alternative institutional measures, Economics & Politics 7(3): 207–227. http://dx.doi.org/10.1111/j.1468-0343.1995.tb00111.x
MacDonald, L. E.; Fougere, K. T. 2003. Software piracy: a study of the extent of coverage in introductory MIS textbooks, Journal of Information Systems Education 13(4).
Marron, D. B.; Steel, D. G. 2000. Which countries protect intellectual property? The case of software piracy, Economic Inquiry 38(2): 159–174. http://dx.doi.org/10.1111/j.1465-7295.2000.tb00011.x
Mishra, A.; Akman, I.; Yazici, A. 2007. Organizational software piracy: an empirical assessment, Behaviour & Information Technology 26(5): 437–444. http://dx.doi.org/10.1080/01449290500483577
Poddar, S. 2005. Why software piracy rates differ – a theoretical analysis. National University of Singapore, Department of Economics.
Roodman, D. 2009a. How to do xtabond2: an introduction to difference and system GMM in Stata, Stata Journal 9(1): 86–136.
Roodman, D. 2009b. A note on the theme of too many instruments, Oxford Bulletin of Economics and Statistics 71(1): 135–158. http://dx.doi.org/10.1111/j.1468-0084.2008.00542.x
Siponen M.; Vance, A.; Willison, R. 2012. New insights into the problem of software piracy: the effects of neutralization, shame, and moral beliefs, Information & Management 49(7–8): 334–341. http://dx.doi.org/10.1016/j.im.2012.06.004
Soto, M. 2009. System GMM estimation with a small sample: Barcelona Graduate School of Economics.
van Kranenburg, H.; Hogenbirk, A. 2005. Multimedia, entertainment, and business software copyright piracy: a cross-national study, Journal of Media Economics 18(2): 109–129. http://dx.doi.org/10.1207/s15327736me1802_3