SUMMARY
Our study investigates the proper role of income in predicting national software piracy rates. We run regressions isolating various measures of income, including GDP per capita and median household income and variations thereof, to predict national software piracy rates. Then we also run multivariate regressions incorporating GDP and other non-income predictors such as corruption in a manner consistent with previous studies. This topic is of importance due to the multi-billion dollar losses incurred globally each year due to pirating. Our results show that a square root version of median household income is the best measure of national income and consistent with what economic theory predicts.