Tuesday, November 2, 2021, 11:45 am – 1:00 pm
This paper experimentally documents the relevance of cognitive uncertainty for understanding and predicting intertemporal choice. First, cognitive uncertainty sheds light on various decision anomalies that are typically conceptualized using non-standard discount functions, including extreme short-run impatience; per-period impatience that decreases in the length of the delay; and transitivity violations in the form of subadditive discounting. Second, model estimations suggest that accounting for cognitive uncertainty leads to large improvements in model fit. Third, we show that measuring cognitive uncertainty yields insights for both choice architecture and predicting the context-dependence of (im)patience.