Chart Turnover and Sales in the Recorded Music Industry: 1990–2005
Chart turnover and sales in the recorded music industry are examined before and during the growth of the Internet as a music source. Chart turnover is measured as the monthly turnover in Billboard’s Top 200 albums chart. Monthly data on expenditures and price indices for music and related goods, as well as demographic and income data, are used in a multivariate structural time series analysis that allows the capture of an unobserved component. We find that turnover positively affects sales, but also that sales are affected positively by an unobserved component that declines in magnitude after 2000.
KeywordsChart turnover Music industry Unobserved component
JEL ClassificationL82 L86
Unable to display preview. Download preview PDF.
- Alexander P. J. (2009) The music recording industry. In: Brock J. W. (eds) The structure of american industry (12th ed.). Pearson, Upper Saddle RiverGoogle Scholar
- Anderson C. (2006) The long tail: Why the future of business is selling less of more. Hyperion, New YorkGoogle Scholar
- Brynjolfsson, E., Hu, Y. J., & Simester, D. (2007). Goodbye pareto principle, hello long tail: The effect of search costs on the concentration of product sales. Retreived from Social Sciences Research Network website: http://ssrn.com/abstract=953587.
- Caves R. E. (1998) Industrial organization and new findings on the turnover and mobility of firms. Journal of Economic Literature 36(4): 1947–1982Google Scholar
- Dixit A. K., Stiglitz J. E. (1977) Monopolistic competition and optimum product diversity. American Economic Review 67(3): 297–308Google Scholar
- Fader, P. S. (2000). Expert report. A&M Records, Inc. v. Napster, Inc., 114 F. Supp. 2d 896.Google Scholar
- Fleder, D., & Kartik, H. (2007). Blockbuster culture’s next rise or fall: The impact of recommender systems on sales diversity. Retrieved from Social Sciences Research Network website: http://ssrn.com/abstract=955984.
- Harvey A. C. (1989) Forecasting structural time series models and the kalman filter. Cambridge University Press, CambridgeGoogle Scholar
- Koopman S. J., Harvey A. C., Doornik J. A., Shephard N. (2007) STAMP 8.0: Structural time series analyser, modeller and predictor. Timberlake Consultants, LondonGoogle Scholar
- Lee W. (2010) Music’s sales slump persists. The Tennessean 106(10): A1Google Scholar
- Rosen S. (1981) The economics of superstars. American Economic Review 71(5): 845–858Google Scholar
- Ryan J., Hughes M. (2006) Breaking the decision chain: The fate of creativity in the age of self-production. In: Ayers M. D. (eds) Cybersounds. Peter Lang, New York, pp 239–253Google Scholar
- Scherer F. M. (1980) Industrial market structure and industrial performance (2nd ed.). Houghton Mifflin, BostonGoogle Scholar
- Sterne J. (2006) On the future of music. In: Ayers M. D. (eds) Cybersounds. Peter Lang, New York, pp 256–263Google Scholar
- Varian H. R. (2000) Buying, sharing, and renting information goods. The Journal of Industrial Economics 48(4): 473–488Google Scholar