The DOI matches its Crossref record.
Assessing Punitive Damages (With Notes on Cognition and Valuation in Law)
Open accessAbstract
A. Two GoalsThis Article has two goals.The first is to investigate the sources of arbitrariness and unpredictability in punitive damage awards.On the basis of responses from 899 jury-eligible citizens, we estimate the results of deliberations consisting of all white juries, all African-American juries, all female juries, all male juries, all wealthy juries, all poor juries, and juries of widely diverse degrees of age and education.Our principal conclusions, stated briefly,' are that at least in the personal injury cases studied here, people's moral judgments are remarkably widely shared, but that people have a great deal of difficulty in mapping such judgments onto an unbounded scale of dollars.Shared moral judgments but erratic, unpredictable, and arbitrary awards, possibly even meaningless awards, are a potential product of this difficulty.Since participants in law are frequently asked to map their judgments onto an unbounded dollar scale, this problem relates not only to punitive damage reform but also to a number of other positive and normative questions now faced by the legal system, including the law governing awards for pain and suffering, libel, sexual harassment and other civil rights violations, intentional infliction of emotional distress, administrative penalties, and contingent valuation.In addition to identifying serious problems in current practices and suggesting possible reforms, our study points in the direction of a large and potentially fruitful research agenda.Our second goal involves what might be called the behavioral analysis of law.In the past three decades, a great deal of progress has come from the application of a certain understanding of economics to legal problems.Within economics and psychology, but outside law, that understanding has been under sustained attack.Within social science generally, the attack has produced insights that supplement, and sometimes undermine, those versions of economics that have undergirded economic analysis of law.These insights very much bear on law.Our study is thus an effort to contribute to the behavioral analysis of law, a field at its inception but showing signs of considerable growth. 2 Our findings also help show what might be missing, impractical, or 1.A technical version of the survey and study, accompanied with more detailed statistical analysis, is reported in Daniel Kahneman, David Schkade, & Cass R. Sunstein, Shared Outrage and Erratic Awards: The Psychology of Punitive Damages, 16 J.RISK & UNCERTAINTY (forthcoming Apr.1998).This Article provides a nontechnical summary of our findings and develops, as the technical paper does not, the implications of our findings for law and legal reform.2.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
The Theory of Dyadic Morality: Reinventing Moral Judgment by Redefining Harm
Schein, C., & Gray, K. (2018) · Personality and Social Psychology Review · doi:10.1177/1088868317698288 · Cited by 659
Music, Pandas, and Muggers: On the Affective Psychology of Value.
Hsee, C. K., & Rottenstreich, Y. (2004) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.133.1.23 · Cited by 654
Tetlock, P. E. (2002) · Psychological Review · doi:10.1037//0033-295x.109.3.451 · Cited by 632
Judicial Influence: A Citation Analysis of Federal Courts of Appeals Judges
Landes, W. M., Lessig, L., & Solimine, M. E. (1998) · The Journal of Legal Studies · doi:10.1086/468022 · Cited by 373
The Long-Run Growth in Obesity as a Function of Technological Change
Posner, R. A., & Philipson, T. J. (1999) · SSRN Electronic Journal · doi:10.2139/ssrn.167008 · Cited by 254
Metadata
- Authors
- Sunstein, C. R., Kahneman, D., & Schkade, D.
- Venue
- The Yale Law Journal
- Publisher
- JSTOR
- Published
- 1998-05
- Volume
- 107
- Issue
- 7
- Pages
- 2071
- ISSN
- 0044-0094 (ISSN-L)
- OpenAlex
- W1641607344
- Cited by
- 264
- References
- 0
- FWCI
- 63.83
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Assessing Punitive Damages (With Notes on Cognition and Valuation in Law). https://app.cochat.ai/papers/10.2307/797417
- The paper
- Sunstein, C. R., Kahneman, D., & Schkade, D. (1998). Assessing Punitive Damages (With Notes on Cognition and Valuation in Law). The Yale Law Journal. https://doi.org/10.2307/797417
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.