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Campaign Advertising and Election Outcomes: Quasi-Natural Experiment Evidence from Gubernatorial Elections in Brazil

Author

Listed:
  • Bernardo S. da Silveira

    (Department of Economic, New York University)

  • João Manoel Pinho de Mello

    (Department of Economics, PUC-Rio)

Abstract

Whether campaign advertising influences election outcomes is an open question; a paradox given the amount spent on campaigning in general and TV advertising in particular. We argue that such “absence of documentation” is due to the focus of the empirical literature on the United States, in which the allocation of campaign spending and advertising is decentralized. We explore a quasinatural experiment that enables us to mitigate the omitted variables and reverse causality problems caused by decentralized allocation. In Brazil, gubernatorial elections work in a two-round system. In the first round, candidates’ TV time shares are determined by their coalitions’ share of seats in the National Parliament. In the second round, TV time is split equally between the first-round winner and runner-up. Using differences between rounds as a source of variation, we find a large causal effect of TV advertising on election outcomes.

Suggested Citation

  • Bernardo S. da Silveira & João Manoel Pinho de Mello, 2007. "Campaign Advertising and Election Outcomes: Quasi-Natural Experiment Evidence from Gubernatorial Elections in Brazil," Textos para discussão 550, Department of Economics PUC-Rio (Brazil), revised May 2010.
    • Handle: RePEc:rio:texdis:550
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    References listed on IDEAS

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    More about this item

    Keywords

    TV Advertising; Campaign Spending; Election Outcomes; Endogeneity; Quasi-Natural Experiments;
    All these keywords.

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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