Chapter The Price of Uncertainty in Present-Biased Planning
CollectionEuropean Research Council (ERC)
The tendency to overestimate immediate utility is a common cognitive bias. As a result people behave inconsistently over time and fail to reach long-term goals. Behavioral economics tries to help affected individuals by implementing external incentives. However, designing robust incentives is often difficult due to imperfect knowledge of the parameter β ∈ (0, 1] quantifying a person’s present bias. Using the graphical model of Kleinberg and Oren , we approach this problem from an algorithmic perspective. Based on the assumption that the only information about β is its membership in some set B ⊂ (0, 1], we distinguish between two models of uncertainty: one in which β is fixed and one in which it varies over time. As our main result we show that the conceptual loss of effi- ciency incurred by incentives in the form of penalty fees is at most 2 in the former and 1 + max B/ min B in the latter model. We also give asymptotically matching lower bounds and approximation algorithms.
Keywordsbehavioral economics; incentive design; heterogeneous agents; approximation algorithms; variable present bias; penalty fees; behavioral economics; incentive design; heterogeneous agents; approximation algorithms; variable present bias; penalty fees; Alice and Bob; Decision problem; Graph theory; Graphical model; NP (complexity); Time complexity; Upper and lower bounds
Publication date and place2017
Computing & information technology