Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Using data on more than 125 countries, this article attempts to add to the research linking corruption and the shadow economy by examining the effect of variability (uncertainty) in one white-collar crime on the prevalence of the other. Measuring variability alternately via a 3-year and a 5-year moving SD, the following main points emerge from the econometric analysis that accounts for bi-directional causality. First, with shadow economy as the dependent variable, shadow economy and corruption are substitutes, and greater variability in corruption increases the shadow economy. Second, the effect of corruption variability is stronger in the short run than the long run. Third, with corruption as the dependent variable, corruption and shadow economy again turn out to be substitutes. Fourth, the effect of shadow economy variability has no statistically significant influence on corruption. Fifth, the findings are somewhat sensitive to an alternate measure of the shadow economy that covers a longer period.