Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
While standard theory assumes rational, optimizing agents under full information, the latter is rarely found in reality. Information has to be acquired and processed—both involving costs. In rational-inattentiveness models agents update their information set only when the benefit outweighs the information cost. We test the rational-inattentiveness model in a controlled laboratory environment. Our design is a forecasting task with costly information and a clear cost–benefit structure. While we find numerous deviations from the model predictions on the individual level, the aggregate results are consistent with rational-inattentiveness and sticky information models rejecting simpler behavioral heuristics.