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Abstract:
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Preferences for popular music genres can be measured based on consumer sales and listening habits and critics' opinions. We analyze data from 1974 to 2016 from the Billboard Hot 100 charts and the Village Voice Pazz and Jop critics poll. We model yearly counts of appearances in these lists for 10 music genres with two multinomial logit models, using various demographic, social, and industry variables as predictors. Since the counts are correlated over time, we use a partial likelihood approach to fit the models. Our models provide strong fits to the observed genre proportions and illuminate trends in the popularity of genres over the sampled years, such as the rise of country music and the decline of rock music in consumer preferences, and the rise of rap/hip-hop in popularity among both consumers and critics. We forecast the genre proportions (for consumers and critics) for several years into the future with ARIMA models fit to the series of transformed model-predicted probabilities. We model over time the association between consumer and critics' preferences using Cramer's V and forecast how this association might trend in the future.
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