We study a model of electoral accountability and selection (EAS) in which voters with heterogeneous horizontal preferences pay limited attention to the incumbent's performance using personalized news aggregators . Extreme voters' aggregators exhibit an own-party bias, which hampers their abilities to discern good and bad performances. While this effect alone could undermine EAS, there is a countervailing effect stemming from partisan disagreements, which make the centrist voter pivotal and could potentially enhance EAS. Overall, increasing mass polarization and shrinking attention spans have ambiguous effects on EAS, whereas correlating voters' news signals unambiguously improves EAS and voter welfare.
We study a model of electoral accountability and selection (EAS) in which heterogeneous voters can aggregate the incumbent's performance data into personalized signals through paying limited attention . Extreme voters' signals exhibit an own-party bias, which hampers their abilities to discern good and bad performances. While this effect alone would undermine EAS, there is a countervailing effect stemming from partisan disagreements, which make the centrist voter pivotal and could potentially enhance EAS. Overall, increasing mass polarization and shrinking attention spans have ambiguous effects on EAS, whereas correlating voters' signals unambiguously improves EAS and voter welfare.
R
voters with heterogeneous horizontal preferences pay limited attention to
heterogeneous voters can aggregate
R
using personalized news aggregators
data into personalized signals through paying limited attention
R
aggregators
signals
R
could
would
D
news