Spillovers from Mass Advertising: An Identification Strategy

摘要

Increasingly, firms have the ability to make high-quality, microlevel predictions of demand for their products, which improves their ability to target advertising. In spite of this, firms may choose to target advertising at a higher level of aggregation than their predictions allow to benefit from the significant discounts that often accompany mass advertising purchases. We argue that firms making such a choice generate "advertising spillovers" that are quasi-random and can be used to identify the response to advertising. These advertising spillovers occur when local levels of advertising are higher or lower than locally optimal because of the influence of other markets or individuals on the mass advertising decision. We formalize the supply-side conditions that incentivize firms to generate these spillovers as part of their optimization strategy, present an empirical strategy for exploiting these conditions, and apply the strategy to multiple product categories and brands. Estimates from this "spillover strategy" agree with recent literature that suggests many standard approaches to estimating the response to advertising may produce biased results because of unobservables; our estimates also suggest that some recent empirical strategies, such as the DMA-border strategy, can produce biased estimates for seasonal products.