Abstract
Studying white-collar crime presents challenges due to definitional disputes, variation in units of analysis, lack of data, and the use of proxy measures. This study employed multilevel meta-analytic methods to shed light on these issues. A total of 602 effect sizes using occupational or corporate crime as the dependent variable were included ( N = 54,205 individuals and 6,425 corporations), with predictor domains reflecting individual and organizational characteristics. Deterrence and positive personal traits showed the largest significant bivariate and multivariate effect sizes, respectively. Moderator analyses suggest that effects are largely stable regardless of whether the dependent variable reflects behavioral intentions or actual behavior, or cross-sectional or longitudinal designs are used.
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