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Predicting advertising volumes: A structural time series approach

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  • Dewenter, Ralf
  • Heimeshoff, Ulrich

Abstract

Media platforms typically operate in a two-sided market, where advertising space serves as a major source of revenues. However, advertising volumes are highly volatile over time and characterized by cyclical behavior. Firms' marketing expenditures in general are far from stable. Due to planning of future issues as well as financial planning, platforms have to forecast the demand for advertising space in their future issues. We use structural time series analysis to predict advertising volumes and compare the results with simple autoregressive models.

Suggested Citation

  • Dewenter, Ralf & Heimeshoff, Ulrich, 2016. "Predicting advertising volumes: A structural time series approach," DICE Discussion Papers 228, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    • Handle: RePEc:zbw:dicedp:228
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    References listed on IDEAS

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    Cited by:

    1. Céline Bonnet & Jan Philip Schain, 2020. "An Empirical Analysis Of Mergers: Efficiency Gains And Impact On Consumer Prices," Journal of Competition Law and Economics, Oxford University Press, vol. 16(1), pages 1-35.

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    Keywords

    advertising volumes; cyclical behavior; AR-processes; structural time series models;
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