Predicting advertising volumes: A structural time series approach
Ralf Dewenter and
Ulrich Heimeshoff
No 228, DICE Discussion Papers from Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE)
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.
Keywords: advertising volumes; cyclical behavior; AR-processes; structural time series models (search for similar items in EconPapers)
Date: 2016
New Economics Papers: this item is included in nep-mkt
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:dicedp:228
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