KNT Presentation Notes

Conclusion motivation empirical model experimental

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Unformatted text preview: tion Empirical model Experimental design Reduced-form results Model estimation Example of (valence) marginal prior Kendall, Nannicini & Trebbi (2014): “How Do Voters Respond to Information?” Conclusion Motivation Empirical model Experimental design Reduced-form results Model estimation Conclusion Joint distributions: a copula-based approach In…nite ways to get joint (bivariate) distribution from univariate marginals We use copulas, introduced by Sklar (1959), which are tools for modeling dependence of several random variables We focus on copula families with only one dependence parameter ( ): Independence between P & V ) = 0 Farlie-Gumbel-Morgensen (FGM) copula (weak dependence) Frank copula (strong dependence) For each family, we estimate from vote data by ML (jointly with all other parameters). Vuong LR tests can directly assess assumptions on the copula Assumption Dependence of subjective belief distributions is constant across time Kendall, Nannicini & Trebbi (2014): “How Do Voters Respond to Information?” Motivation Empirical model Experimental design Reduced-form results Model estimation Italian local politics 101 Since 1993, direct election of mayors: FPTP, runo¤ in cities above 15,000 Mayors are crucial players in local politics High-salience elections Usual campaigning tools: Public rallies &...
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