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Rating Forecasts for Television Programs

  • Denny Meyer
  • Rob J. Hyndman

    ()

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.

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File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2005/wp1-05.pdf
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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 1/05.

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Length: 15 pages
Date of creation: Mar 2005
Date of revision:
Handle: RePEc:msh:ebswps:2005-1
Contact details of provider: Postal: PO Box 11E, Monash University, Victoria 3800, Australia
Phone: +61-3-9905-2489
Fax: +61-3-9905-5474
Web page: http://www.buseco.monash.edu.au/depts/ebs/
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  1. Tobias, Justin & Zellner, Arnold, 2000. "A Note on Aggregation, Disaggregation and Forecasting Performance," Staff General Research Papers 12024, Iowa State University, Department of Economics.
  2. Shumway, C. Richard & Davis, George C., 2000. "Does Consistent Aggregation Really Matter?," Ag Econ Series 12966, Washington State University, School of Economic Sciences.
  3. 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.
  4. Chan, Ngai Hang, 1999. "The Et Interview: Professor George C. Tiao," Econometric Theory, Cambridge University Press, vol. 15(03), pages 389-424, June.
  5. Fred S. Zufryden, 1973. "Media Scheduling: A Stochastic Dynamic Model Approach," Management Science, INFORMS, vol. 19(12), pages 1395-1406, August.
  6. Clive Granger & Tae-Hwy Lee, 1999. "The effect of aggregation on nonlinearity," Econometric Reviews, Taylor & Francis Journals, vol. 18(3), pages 259-269.
  7. K. Lee & M. H. Pesaran & R. G. Pierse, 1988. "Aggregation Bias and Labor Demand Equations for the U.K. Economy," UCLA Economics Working Papers 492, UCLA Department of Economics.
  8. 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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