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The workhorse probabilistic voting model implies that as the socio-demographic match between a voter and a candidate increases, so too does that candidate’s lack of responsiveness the voter’s opinion. Despite this counter-intuitive result, the lack of data on candidate demographics prevents any testing of the underlying model vis-à-vis voter and candidate representativeness. We construct a new longitudinal dataset containing both candidate and voter demographics, and ideal points across congressional elections. We use this to show how responsive every congressional candidate is to the voters who share (and don’t share) their demographics. We estimate how congruence between candidate and voter demographics affect the weight put upon the voters’ ideal points, directly getting at the underlying prediction about voter and candidate behavior. We use these results to test whether the traditional formal prediction is realized, or whether formal models need to be adjusted.