Rating Forecasts for Television Programs

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Rating Forecasts for Television Programs

Author Info

Denny Meyer
Rob J. Hyndman ()

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Rob 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.

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Publisher Info
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

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Find related papers by JEL classification:
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
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
M37 - Business Administration and Business Economics; Marketing; Accounting - - Marketing and Advertising - - - Advertising

This paper has been announced in the following NEP Reports:

NEP-ALL-2005-04-03 (All new papers)
NEP-CUL-2005-04-03 (Cultural Economics)
NEP-ECM-2005-04-03 (Econometrics)

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

Clive Granger & Tae-Hwy Lee, 1999. "The effect of aggregation on nonlinearity," Econometric Reviews, Taylor and Francis Journals, vol. 18(3), pages 259-269. [Downloadable!] (restricted)
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. [Downloadable!]
Tobias, Justin & Zellner, Arnold, 2004. "A Note on Aggregation, Disaggregation and Forecasting Performance," Staff General Research Papers 12024, Iowa State University, Department of Economics.
Other versions:
- Zellner, Arnold & Tobias, Justin, 2005. "A Note on Aggregation, Disaggregation and Forecasting Performance," Staff General Research Papers 12371, Iowa State University, Department of Economics.
- Zellner, Arnold & Tobias, Justin, 1998. "A note on aggregation, disaggregation and forecasting performance," CUDARE Working Paper Series 869, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
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. [Downloadable!] (restricted)

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