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2015
DOI: 10.22151/ela.1.1.2
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Lack of Preferences, Political Trust and Education Levels: Alternative Explanations for Invalid Votes in Brazilian Elections

Abstract: This paper explores the causes of invalid voting in Brazilian elections. Given that invalid ballot rates tend to be higher where voting is compulsory, the correlates of invalid votes in those countries deserve attention. In this regard, Brazil provides an ideal case for analysing the issue. Brazil not only has the largest electorate of all democracies with compulsory voting laws, but it has also introduced electronic ballots, what has been responsible for a considerable decline in the invalid vote rates. Using… Show more

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Cited by 1 publication
(4 citation statements)
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“…Despite that, the aggregate research continues to dominate the field. We counted 26 aggregate-level studies employing regression models of the determinants of invalid voting (Ackaert et al 2011; Aldashev and Mastrobuoni 2013; Cisneros 2013; Cisneros and Freigedo 2014; Cohen 2018; Damore et al 2012; Dejaeghere and Vanhoutte 2016; Fatke and Heinsohn 2017; Galatas 2008; Gendźwiłł 2015; Herron 2011a; Hooghe et al 2009; Kimball and Kropf 2005; Kouba and Lysek 2016; McAllister and Makkai 1993; Nihuys 2014; Pachón et al 2017; Pion 2010; Power and Garand 2007; Power and Roberts 1995; Reynolds and Steenbergen 2006; Rosenthal and Sen 1973; Singh 2017; Socia and Brown 2014; Superti 2015; Uggla 2008), while 11 studies utilize data from individual survey responses (Arbache et al 2014; Borba 2008; Carlin 2006; Cisneros 2016; Cohen 2017; Hill and Rutledge-Prior 2016; Hooghe et al 2009; Katz and Levin 2016; Moral 2016; Singh 2017; Solvak and Vassil 2015). Two studies combine both (Driscoll and Nelson 2014; Hill and Rutledge-Prior 2016).…”
Section: Methodological Strategies and Substantive Resultsmentioning
confidence: 99%
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“…Despite that, the aggregate research continues to dominate the field. We counted 26 aggregate-level studies employing regression models of the determinants of invalid voting (Ackaert et al 2011; Aldashev and Mastrobuoni 2013; Cisneros 2013; Cisneros and Freigedo 2014; Cohen 2018; Damore et al 2012; Dejaeghere and Vanhoutte 2016; Fatke and Heinsohn 2017; Galatas 2008; Gendźwiłł 2015; Herron 2011a; Hooghe et al 2009; Kimball and Kropf 2005; Kouba and Lysek 2016; McAllister and Makkai 1993; Nihuys 2014; Pachón et al 2017; Pion 2010; Power and Garand 2007; Power and Roberts 1995; Reynolds and Steenbergen 2006; Rosenthal and Sen 1973; Singh 2017; Socia and Brown 2014; Superti 2015; Uggla 2008), while 11 studies utilize data from individual survey responses (Arbache et al 2014; Borba 2008; Carlin 2006; Cisneros 2016; Cohen 2017; Hill and Rutledge-Prior 2016; Hooghe et al 2009; Katz and Levin 2016; Moral 2016; Singh 2017; Solvak and Vassil 2015). Two studies combine both (Driscoll and Nelson 2014; Hill and Rutledge-Prior 2016).…”
Section: Methodological Strategies and Substantive Resultsmentioning
confidence: 99%
“…We were able to identify only 13 such systematic analyses. Nine of them use single national data sets (Arbache et al 2014; Borba 2008; Carlin 2006; Driscoll and Nelson 2014; Hill and Rutledge-Prior 2016; Hooghe et al 2009; Katz and Levin 2016; McAllister and White 2008; Stiefbold 1965), while four exploit the recent availability of cross-national comparative surveys (Cohen 2017; Moral 2016; Singh 2017; Solvak and Vassil 2015). This is an important addition because aggregate-level studies can only imperfectly model relationships that posit individual-level causal mechanisms due to ecological inference problems.…”
Section: Methodological Strategies and Substantive Resultsmentioning
confidence: 99%
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