Working Paper: CEPR ID: DP18430
Authors: Sarah Auster; Christian Kellner
Abstract: We study the effect of ambiguity on timing decisions. An agent faces a stopping problem with an uncertain stopping payoff and a stochastic time limit. The agent is unsure about the correct model quantifying the uncertainty and seeks to maximize her payoff guarantee over a set of plausible models. As time passes and the agent updates, the worst-case model used to evaluate a given strategy can change, creating a problem of dynamic inconsistency. We characterize the stopping behavior in this environment and show that, while the agent's myopic incentives are fragile to small changes in the set of considered models, the best consistent plan from which no future self has incentives to deviate is robust.
Keywords: stopping problem; ambiguity; consistent planning
JEL Codes: C61; D81; D83
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Model uncertainty (D81) | DM's stopping payoff (J33) |
| Model uncertainty (D81) | DM's time limit (C41) |
| DM's sophistication (myopic vs. forward-looking) (D84) | DM's timing decisions (C41) |
| Updates to the worst-case model (C51) | Optimal stopping times (C41) |
| Updating beliefs (D83) | Changes in worst-case model (C69) |
| Changes in worst-case model (C69) | Dynamic inconsistency in stopping behavior (D15) |
| Myopic DM (D91) | Deviation from optimal plans (L21) |
| Forward-looking DM (E17) | Consistent plan development (O20) |
| Forward-looking DM (E17) | Mitigation of risks of premature stopping (C41) |