Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Abstract We adopt the posterior-based approach to study dynamic discrete choice problems under rational inattention. We provide necessary and sufficient conditions to characterize the solution for general uniformly posterior-separable cost functions. We propose an efficient algorithm to solve these conditions and apply our model to explain phenomena such as perceptual distance, status quo bias, confirmation bias, and belief polarization. A key condition for our approach to work is the concavity of the difference between the generalized entropy of the current posterior and the discounted generalized entropy of the prior beliefs about the future states.