Optimal Time-Inconsistent Beliefs: Misplanning, Procrastination, and Commitment
Bibliographic record
Abstract
We develop a structural theory of beliefs and behavior that relaxes the assumption of time consistency in beliefs. Our theory is based on the trade-off between optimism, which raises anticipatory utility, and objectivity, which promotes efficient actions. We present it in the context of allocating work on a project over time, develop testable implications to contrast it with models assuming time-inconsistent preferences, and compare its predictions to existing evidence on behavior and beliefs. Our predictions are that (i) optimal beliefs are optimistic and time inconsistent; (ii) people optimally exhibit the planning fallacy; (iii) incentives for rapid task completion make beliefs more optimistic and worsen work smoothing, whereas incentives for accurate duration prediction make beliefs less optimistic and improve work smoothing; (iv) without a commitment device, beliefs become less optimistic over time; and (v) in the presence of a commitment device, beliefs may become more optimistic over time, and people optimally exhibit preference for commitment. This paper was accepted by Neng Wang, finance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".