Abstract
Individuals vary in their attention to news. Building on theories of imperfect information, we propose a novel method to uncover the distribution of attention in surveys of consumers and professional forecasters. We develop a finite mixture model to cluster forecasts according to their attention, which is robust to forecast rounding and non-adjustment. Our results reveal substantial attention heterogeneity in survey data, showing that ignoring this heterogeneity can underestimate average inattention. By constructing a panel of individual attention measures, we provide new insights into the drivers of attention from within-individual variations. Finally, we discuss the theoretical implications of our findings.