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Ignorance Is Bias: The Effect of Latino Losers on Models of Latino Representation
Author(s) -
Juenke Eric Gonzalez
Publication year - 2014
Publication title -
american journal of political science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.347
H-Index - 170
eISSN - 1540-5907
pISSN - 0092-5853
DOI - 10.1111/ajps.12092
Subject(s) - representation (politics) , legislature , political science , ignorance , ballot , selection bias , selection (genetic algorithm) , majority rule , econometrics , social psychology , psychology , voting , computer science , economics , statistics , mathematics , politics , artificial intelligence , law
Nearly every aggregate study of minority legislative representation has observed outcomes of elections (officeholders), rather than the supply of minority candidates. Because of this, scholars have left a large amount of important data, the election losers, out of their models of minority representation. The evidence presented in this article demonstrates that voters in the United States cannot choose minority officeholders because there are rarely minority candidates on the ballot. I use state legislative candidate data from Carsey et al. ([Carsey, Thomas M., 2008]) and Klarner et al. ([Klarner, Carl E., 2012]) to test models of Latino representation that correct for first‐stage selection bias. Once candidate self‐selection is taken into account, the probability of electing a Latino increases enormously. I then use data from 2010 to make out‐of‐sample predictions, which clearly favor the conditional model. Thus, our current understanding of Latino representation is significantly biased by ignoring the first stage of an election, a candidate's decision to run.