Difference between revisions of "Andrés (2006b)"
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− | |Name of Study=Andrés ( | + | |Name of Study=Andrés (2006) |
− | |Cross-country= | + | |Author=Andrés, A.R. |
− | |Comparative= | + | |Title=Software piracy and income inequality |
+ | |Year=2006 | ||
+ | |Full Citation=Andrés, A. R. (2006). Software piracy and income inequality. Applied Economics Letters, 13(2), 101-105. | ||
+ | |Abstract=This paper investigates the extent to which income inequality influences national piracy rates across a sample of 34 countries. Economic inequality seems to have a negative significant effect on national rates of piracy. Consistent with previous studies, we also find that judicial efficiency affects piracy rates. Additionally, research results show that income and education are not important determinants of piracy rates. | ||
+ | |Authentic Link=https://www.researchgate.net/profile/Antonio_Andres/publication/24068355_Software_piracy_and_income_inequality/links/00b4952b703cb4c24b000000.pdf | ||
+ | |Link=https://www.researchgate.net/profile/Antonio_Andres/publication/24068355_Software_piracy_and_income_inequality/links/00b4952b703cb4c24b000000.pdf | ||
+ | |Reference=Husted (2000); Gopal and Sanders (1997); | ||
+ | |Plain Text Proposition=This study shows that income inequality appears to have a negative and significant effect on piracy rates, and hence supporting Husted’s result (2000). The regression results also reveal that the efficiency of the judicial system is an important factor when explaining cross-national variations in piracy rates. No significant association was found between | ||
+ | income, education and piracy rates. Overall, the results are in line with previous empirical research. | ||
+ | |FundamentalIssue=5. Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media), 1. Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare, | ||
+ | |EvidenceBasedPolicy=D. Licensing and Business models (collecting societies; meta data; exchanges/hubs; windowing; crossborder availability), F. Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness), | ||
+ | |Discipline=K42: Illegal Behavior and the Enforcement of Law, L82: Entertainment • Media, O34: Intellectual Property and Intellectual Capital | ||
+ | |Intervention-Response=The authors find that higher levels of judicial efficiency are associated with lower software piracy rates. Only the law variable seems to impact on piracy rates. The coefficient on rule of law is negative and statistically significant. This finding suggests that the efficiency of the legal system might act a deterrent factor of piracy behaviour, hence supporting previous findings (Holm, 2003). | ||
+ | |Description of Data=This study uses data on income inequality from the World Income Inequality Database (WIID, 2000). It also uses data on software piracy published by the International Planning Research Corporation (IPRC) for the Business Software Alliance (BSA) and Software Information Industry Association (SIIA) (IPRC, 2003). | ||
+ | |Data Type=Secondary data | ||
+ | |Data Source=International Planning Research Corporation; World Income Inequality Database; Business Software Alliance; | ||
+ | |Method of Collection=Quantitative Collection Methods, Survey Research (quantitative; e.g. sales/income reporting), Quantitative data/text mining | ||
+ | |Method of Analysis=Quantitative Analysis Methods, Cluster analysis, Descriptive statistics (counting; means reporting; cross-tabulation), Correlation and Association | ||
+ | |Industry=Software publishing (including video games); Creative, arts and entertainment; | ||
+ | |Country=Australia; Brazil; Canada; Chile; China; Colombia; Denmark; Dominican Republic; Finland; France; Honduras; Hong Kong; Hungary; India; Indonesia; Israel; Italy; Mauritius; Mexico; Netherlands; Norway; Pakistan; Peru; Philippines; Poland; Portugal; Singapore; South Africa; Spain; Sweden; Thailand; Turkey; United Kingdom; Zimbabwe; | ||
+ | |Cross-country=Yes | ||
+ | |Comparative=Yes | ||
|Government or policy=No | |Government or policy=No | ||
|Literature review=No | |Literature review=No |
Revision as of 17:07, 21 October 2016
Contents
Source Details
Andrés (2006) | |
Title: | Software piracy and income inequality |
Author(s): | Andrés, A.R. |
Year: | 2006 |
Citation: | Andrés, A. R. (2006). Software piracy and income inequality. Applied Economics Letters, 13(2), 101-105. |
Link(s): | Definitive , Open Access |
Key Related Studies: | |
Discipline: | |
Linked by: |
About the Data | |
Data Description: | This study uses data on income inequality from the World Income Inequality Database (WIID, 2000). It also uses data on software piracy published by the International Planning Research Corporation (IPRC) for the Business Software Alliance (BSA) and Software Information Industry Association (SIIA) (IPRC, 2003). |
Data Type: | Secondary data |
Secondary Data Sources: | |
Data Collection Methods: | |
Data Analysis Methods: | |
Industry(ies): | |
Country(ies): | |
Cross Country Study?: | Yes |
Comparative Study?: | Yes |
Literature review?: | No |
Government or policy study?: | No |
Time Period(s) of Collection: | |
Funder(s): |
Abstract
This paper investigates the extent to which income inequality influences national piracy rates across a sample of 34 countries. Economic inequality seems to have a negative significant effect on national rates of piracy. Consistent with previous studies, we also find that judicial efficiency affects piracy rates. Additionally, research results show that income and education are not important determinants of piracy rates.
Main Results of the Study
This study shows that income inequality appears to have a negative and significant effect on piracy rates, and hence supporting Husted’s result (2000). The regression results also reveal that the efficiency of the judicial system is an important factor when explaining cross-national variations in piracy rates. No significant association was found between income, education and piracy rates. Overall, the results are in line with previous empirical research.
Policy Implications as Stated By Author
The authors find that higher levels of judicial efficiency are associated with lower software piracy rates. Only the law variable seems to impact on piracy rates. The coefficient on rule of law is negative and statistically significant. This finding suggests that the efficiency of the legal system might act a deterrent factor of piracy behaviour, hence supporting previous findings (Holm, 2003).