Cited by 124Auction Theory and ApplicationsExperimental Behavioral Economics StudiesMerger and Competition Analysis

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Information Disclosure as a Matching Mechanism: Theory and Evidence from a Field Experiment

Tadelis, Steven, Zettelmeyer, Florian·2015·American Economic Review

Abstract

Market outcomes depend on the quality of information available to its participants. We measure the effect of information disclosure on market outcomes using a large-scale field experiment that randomly discloses quality information in wholesale automobile auctions. We argue that buyers in this market are horizontally differentiated across cars that are vertically ranked by quality. This implies that information disclosure helps match heterogeneous buyers to cars of varying quality, causing both good and bad news to increase competition and revenues. The data confirm these hypotheses. These findings have implications for the design of other markets, including e-commerce, procurement auctions, and labor markets. (JEL C93, D44, D82, L15)

Overview

Integrity signals

Registry

Crossref · 10.1257/aer.20110753

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

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

Verification

Claims the paper makes

This paper’s full text isn’t openly available, 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?

  • Information disclosure helps in matching heterogeneous buyers to sellers of varying quality.

    “Tadelis and Zettelmeyer (2015) shows that information disclosure helps in matching heterogeneous buyers to sellers of varying quality.”

    From Two-Sided Adverse Selection and Bilateral Reviews in Sharing Economy (2019) · cites this paper as Tadelis and Zettelmeyer (2015)

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 16

  1. 10.1111/j.1756-2171.2011.00131.x · DOI
  2. 10.1007/s00199-006-0177-4 · DOI
  3. 10.1111/joie.12048 · DOI
  4. 10.2307/1251005 · DOI
  5. 10.1016/j.euroecorev.2007.07.003 · DOI
  6. 10.1086/261891 · DOI
  7. 10.2307/1073080 · DOI
  8. 10.1086/466995 · DOI
  9. 10.1016/S0165-4101(01)00018-0 · DOI · Paper page
  10. 10.1162/003355303321675428 · DOI
  11. 10.1257/aer.96.3.756 · DOI
  12. 10.1257/aer.101.4.1535 · DOI
  13. 10.2307/3003562 · DOI · Paper page
  14. 10.2307/1911865 · DOI
  15. 10.1287/mnsc.1090.0998 · DOI
  16. 10.2307/2951695 · DOI

Cited by

Sorted by citations

Metadata

Authors
Tadelis, S., & Zettelmeyer, F.
Affiliations
  • National Bureau of Economic Research (US)
  • Northwestern University (US)
Venue
American Economic Review
Published
2015-02-01
Volume
105
Issue
2
Pages
886-905
ISSN
0002-8282 (ISSN-L)
OpenAlex
W2118997265
Cited by
124
References
1
Citations by year
2026: 10 · 2025: 9 · 2024: 10 · 2023: 10 · 2022: 12 · 2021: 8 · 2020: 12 · 2019: 13 · 2018: 11 · 2017: 8 · 2016: 6 · 2015: 6
FWCI
12.91
Type
journal article
Language
en
Open access
closed
Locations
  • American Economic Review (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Auction Theory and Applications
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Experimental Behavioral Economics Studies
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Merger and Competition Analysis
Keywords
information disclosure, matching mechanisms, consumer heterogeneity, product quality, competition, auction revenue, market design, e-commerce, labor market, procurement auctions

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