The DOI matches its Crossref record.
Impetuous Youngsters and Jaded Old-Timers: Acquiring a Reputation for Learning
Open accessAbstract
This paper examines individual decision making when decisions reflect on people's ability to learn. We address this problem in the context of a manager making investment decisions on a project over time. We show that in an effort to appear as a fast learner, the manager will exaggerate his own information; but ultimately, he becomes too conservative, being unwilling to change his investments on the basis of new information. Our results arise purely from learning about competence rather than concavity or convexity of the rewards functions. We relate our results to the existing psychology literature concerning cognitive dissonance reduction.
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Citations
Cited by
The Provision of Incentives in Firms
Prendergast, C. (1999) · Journal of Economic Literature · doi:10.1257/jel.37.1.7 · Cited by 3,338
Self-citationOttaviani, M., & Sørensen, P. N. (2006) · Journal of Economic Theory · doi:10.1016/j.jet.2004.08.005 · Cited by 180
Metadata
- Authors
- Prendergast, C., & Stole, L.
- Venue
- Journal of Political Economy
- Publisher
- University of Chicago Press
- Published
- 1996-12
- Volume
- 104
- Issue
- 6
- Pages
- 1105-1134
- ISSN
- 0022-3808 (ISSN-L)
- 1537-534X
- OpenAlex
- W2095996041
- Cited by
- 715
- References
- 0
- FWCI
- 6.26
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Impetuous Youngsters and Jaded Old-Timers: Acquiring a Reputation for Learning. https://app.cochat.ai/papers/10.1086/262055
- The paper
- Prendergast, C., & Stole, L. (1996). Impetuous Youngsters and Jaded Old-Timers: Acquiring a Reputation for Learning. Journal of Political Economy. https://doi.org/10.1086/262055
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
