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The Eurovision Song Contest is one of the worldwide biggest live media events and the world’s leading broadcast of an international music competition. The countries of the European Broadcasting Union participate by sending an artist (or a group of artists) to the contest and both expert juries and the television audience of all participating countries vote in a special ranking and points system to determine the eventual winner. A substantial list of cultural economics papers empirically analyzed the voting behavior of juries (consisting of music industry professionals) and audiences to identify voting biases because of cultural and political influences on the voting bodies. Due to limited data availability, this literature suffered from having to treat the national juries as a black box even though they are composed of individuals with different demographic characteristics (age, gender, etc.) and expert backgrounds (industry managers, musicians, composers, music journalists, etc.). Our analysis benefits from utilizing new data about each individual member of the jury including their role within the jury (e.g., the chairperson) as well as about their individual votes in the ESC. Therefore, for the first time, we can disentangle the voting behavior of the juries and track the voting behavior of individual jury members. Based upon a rich dataset including personal characteristics (gender, age, career/professional background, nationality, cultural heritage, etc.) of both jury members (voters) and performing artists in the contest (voting objects), we analyze whether the increasing similarity between voter (jury member) and voting object (contest performer) correlates with upward biases in terms of awarded points. In doing so, we employ the concept of Mahalanobis distance to measure similarity and employ modern econometric regression methods to derive our results. Inter alia, we identify conditions under which the similarity of jury members with contestants leads to a pro-bias in voting (across different countries). Interestingly, the professional background of jury members also significantly influences the individual voting bias, for instance, experts with classical music backgrounds display significantly less bias than presenters of radio or television programs or music journalists. Altogether, our analysis allows us to look beyond the hitherto dominating “country X is biased for/against country Y” conclusions and track voting biases on an individual level, based on personal characteristics.
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