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Rating Forecasts for Television Programs

Author

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  • Denny Meyer
  • Rob J. Hyndman

Abstract

This paper investigates the effect of aggregation and non-linearity in relation to television rating forecasts. Several linear models for aggregated and disaggregated television viewing have appeared in the literature. The current analysis extends this work using an empirical approach. We compare the accuracy of population rating models, segment rating models and individual viewing behaviour models. Linear and non-linear models are fitted using regression, decision trees and neural networks, with a two-stage procedure being used to model network choice and viewing time for the individual viewing behaviour model. The most accurate forecast results are obtained from the non-linear segment rating models.

Suggested Citation

  • Denny Meyer & Rob J. Hyndman, 2005. "Rating Forecasts for Television Programs," Monash Econometrics and Business Statistics Working Papers 1/05, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2005-1
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    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2005/wp1-05.pdf
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    References listed on IDEAS

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    3. Srinivas K. Reddy & Jay E. Aronson & Antonie Stam, 1998. "SPOT: Scheduling Programs Optimally for Television," Management Science, INFORMS, vol. 44(1), pages 83-102, January.
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    5. Shumway, C. Richard & Davis, George C., 2001. "Does consistent aggregation really matter?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 45(2), pages 1-34.
    6. Chan, Ngai Hang, 1999. "The Et Interview: Professor George C. Tiao," Econometric Theory, Cambridge University Press, vol. 15(03), pages 389-424, June.
    7. Swann, P. & Tavakoli, M., 1994. "An econometric analysis of television viewing and the welfare economics of introducing an additional channel in the UK," Information Economics and Policy, Elsevier, vol. 6(1), pages 25-51, March.
    8. Clive Granger & Tae-Hwy Lee, 1999. "The effect of aggregation on nonlinearity," Econometric Reviews, Taylor & Francis Journals, vol. 18(3), pages 259-269.
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    Cited by:

    1. Keita Kinjo & Takeshi Ebina, 2015. "State-Dependent Choice Model for TV Programs with Externality: Analysis of Viewing Behavior," Journal of Media Economics, Taylor & Francis Journals, vol. 28(1), pages 20-40, March.

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    More about this item

    Keywords

    Decision Trees; Disaggregation; Discrete Choice Models; Neural Networks; Rating Benchmarks;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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