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A Note on Detecting Dividing Lines in Turnout: Spatial Dependence and Heterogeneity in the 2012 US Presidential Election

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  • Nadia Fiorino
  • Nicola Pontarollo
  • Roberto Ricciuti

Abstract

US voters have been moving apart in the last twenty years. This paper analyzes how their voting participation has partitioned by looking at US counties in the 2012 Presidential elections. To tackle this question, we propose a methodology that jointly addresses spatial autocorrelation of the dependent variable and splits the sample according to the non-linearity in the covariates. We find that in different groups of US counties, obtained through a spatial lag regression tree procedure, some variables have different statistical significance (or lack of it), and sometimes different signs. This heterogeneity – which is a manifestation of the complexity of the political behavior - is obfuscated by traditional methods that extrapolate a single average relationship between the variables.

Suggested Citation

  • Nadia Fiorino & Nicola Pontarollo & Roberto Ricciuti, 2020. "A Note on Detecting Dividing Lines in Turnout: Spatial Dependence and Heterogeneity in the 2012 US Presidential Election," CESifo Working Paper Series 8167, CESifo.
    • Handle: RePEc:ces:ceswps:_8167
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    More about this item

    Keywords

    turnout; spatial dependence; heterogeneity;
    All these keywords.

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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