Corruption, Income and Piracy. An empirical analysis

Bekir Insaf ()
Additional contact information
Bekir Insaf: Department of Economy, University of Sousse, Sousse, Tunisia

Review of Law & Economics, 2017, vol. 13, issue 2, 25

Abstract: This paper subjects the piracy-corruption relationship to a detailed empirical examination. A distinction is drawn between the direct impact of corruption on piracy and the indirect impact which operates through corruption’s impact on per capita income and the resultant impact of income on piracy. Using data for 100 countries covering the period 1996–2010, both direct and indirect impacts of corruption on software piracy are estimated. Corruption is estimated to have a positive direct effect on the piracy rate. The indirect effect is found to be negative and smaller in absolute value than the direct effect for the majority of the sample income range. As a result, the total effect of corruption on software piracy is positive except for the lower income countries in the sample.

Keywords: income; panel data analysis; piracy; corruption (search for similar items in EconPapers)
JEL-codes: O34 O38 Q53 Q58 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/rle-2013-0005 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:rlecon:v:13:y:2017:i:2:p:25:n:1

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/rle/html

DOI: 10.1515/rle-2013-0005

Access Statistics for this article

Review of Law & Economics is currently edited by Francesco Parisi

More articles in Review of Law & Economics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().