Cited by 47Decision-Making and Behavioral EconomicsExperimental Behavioral Economics StudiesFinancial Literacy, Pension, Retirement Analysis

Stereotypes and false consensus: How financial professionals predict risk preferences

Roth, Benjamin, Voskort, Andrea·2014·Journal of Economic Behavior & Organization

Integrity signals

Registry

Crossref · 10.1016/j.jebo.2014.05.006

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Roth, B., & Voskort, A.
Affiliations
Heidelberg University (DE)
Corresponding author
Roth, Benjamin
Venue
Journal of Economic Behavior & Organization
Publisher
Elsevier BV
Published
2014-11
Volume
107
Pages
553-565
ISSN
0167-2681 (ISSN-L)
OpenAlex
W1972732878
Cited by
47
References
5
Citations by year
2026: 2 · 2025: 1 · 2024: 7 · 2023: 7 · 2022: 4 · 2021: 6 · 2020: 4 · 2019: 3 · 2018: 3 · 2017: 4 · 2016: 5 · 2014: 1
FWCI
3.04
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Economic Behavior & Organization (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
  • Social Sciences › Safety Research › Experimental Behavioral Economics Studies
  • Social Sciences › Business, Management and Accounting › Accounting › Financial Literacy, Pension, Retirement Analysis
Keywords
risk preferences, risk-taking, stereotypes, false consensus effect, prediction of others' behavior, financial professionals, students, demographic data, self-assessment, prediction accuracy

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