Disentangling the Effects of Ad Tone on Voter Turnout and Candidate Choice in Presidential Elections

We study the effects of positive and negative advertising in presidential elections. We develop a model to disentangle these effects on voter turnout and candidate choice. The central empirical challenges are highly correlated and endogenous advertising quantities that are measured with error. To address these challenges, we construct a large set of potential instruments, including interactions with incumbency that we demonstrate provide the critical identifying variation, and apply machine learning causal inference methods. Using data from the 2000 and 2004 U.S. presidential elections, we find that positive and negative ads play fundamentally different roles. Negative ads are more effective at driving relative candidate shares, whereas positive ads stimulate turnout. These results indicate that a candidate geographically targeting tone trades off local relative share gains and local increases in turnout for localities with a strong base. Counterfactual simulations indicate that ad tone alone can impact the outcome of close elections. Our analysis also provides potential explanations as to why past studies have produced mixed findings on both ad tone and turnout effects.