How and When to Use the Political Cycle to Identify Advertising Effects

54 Pages Posted: 20 Jun 2019 Last revised: 7 Aug 2019

See all articles by Sarah Moshary

Sarah Moshary

University of Chicago - Booth School of Business; eBay Research Labs

Bradley Shapiro

University of Chicago - Booth School of Business

Jihong Song

Princeton University - Department of Economics

Date Written: August 5, 2019

Abstract

A central challenge in estimating the causal effect of TV advertising on demand is finding quasi-random variation in advertising. Political advertising in the US has been proposed as a plausible instrumental variable because political spending on television has skyrocketed in recent elections, topping $4 billion in 2016. We take a multi-category approach to assessing how and where this instrument is valid and useful. We characterize the conditions under which political cycles theoretically identify the causal effect of TV advertising on demand, highlight potential threats to the exclusion restriction and monotonicity condition, and suggest a specification to address the most serious concerns. To characterize "where'' the approach might be most useful, we test the strength of the first stage of the political ad instrument, using both a single instrument and also optimal instruments obtained by machine learning. For the majority of commercial advertising categories, our findings suggest that researchers should consider using weak-instrument robust inference, as first-stage F-statistics are less than 10 for at least 202 of 274 product categories. Political advertising has the largest first-stage F-statistic for categories that typically advertise exclusively locally, such as automobile dealerships and restaurants. Failure to use the suggested specification leads to results that suggest violations of exclusion and monotonicity in a significant number of categories. Finally, we conduct a case study of the auto industry. Despite a very strong first stage, the IV estimate for this category is imprecise and includes zero.

Keywords: Advertising, Advertising Effectiveness, Political Advertising, Causal Effects, Instrumental Variables

JEL Classification: L10, L11, M31, M37, C26, C23, C81

Suggested Citation

Moshary, Sarah and Shapiro, Bradley and Song, Jihong, How and When to Use the Political Cycle to Identify Advertising Effects (August 5, 2019). Available at SSRN: https://ssrn.com/abstract=3404343 or http://dx.doi.org/10.2139/ssrn.3404343

Sarah Moshary

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

eBay Research Labs ( email )

2065 Hamilton Avenue
San Jose, CA
United States

Bradley Shapiro (Contact Author)

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

HOME PAGE: http://faculty.chicagobooth.edu/bradley.shapiro/

Jihong Song

Princeton University - Department of Economics ( email )

Princeton, NJ 08544-1021
United States

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