The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Internet Job Search and Unemployment Durations
Abstract
Using the December 1998 and August 2000 CPS Computer and Internet Supplements matched with subsequent CPS files, we ask which types of unemployed workers looked for work on line and whether Internet searchers became reemployed more quickly. In our data, Internet searchers have observed characteristics that are typically associated with shorter unemployment spells, and do spend less time unemployed. This unemployment differential is however eliminated and in some cases reversed when we hold observable characteristics constant. We conclude that either Internet job search is ineffective in reducing unemployment durations, or Internet job searchers are negatively selected on unobservables.
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
Cites
Unemployment Insurance and Unemployment Spells
Meyer, B. D. (1990) · Econometrica · doi:10.2307/2938349 · Cited by 1,178
Cited by
Goldfarb, A., & Tucker, C. (2019) · Journal of Economic Literature · doi:10.1257/jel.20171452 · Cited by 2,744
The Individual Experience of Unemployment
Wanberg, C. R. (2012) · Annual Review of Psychology · doi:10.1146/annurev-psych-120710-100500 · Cited by 664
Does internet development improve green total factor energy efficiency? Evidence from China
Wu, H., Hao, Y., Ren, S., Yang, X., & Xie, G. (2021) · Energy Policy · doi:10.1016/j.enpol.2021.112247 · Cited by 540
Is Internet Job Search Still Ineffective?
Kuhn, P., & Mansour, H. (2014) · The Economic Journal · doi:10.1111/ecoj.12119 · Cited by 386
Self-citationImperfect Competition in the Labor Market
Alan, M. (2011) · Handbook of Labor Economics · doi:10.1016/s0169-7218(11)02409-9 · Cited by 329
Metadata
- Authors
- Kuhn, P., & Skuterud, M.
- Venue
- American Economic Review
- Publisher
- American Economic Association
- Published
- 2004-02-01
- Volume
- 94
- Issue
- 1
- Pages
- 218-232
- ISSN
- 0002-8282 (ISSN-L)
- OpenAlex
- W3123267736
- Cited by
- 364
- References
- 1
- FWCI
- 29.24
- Type
- journal article
- Language
- en
- Open access
- closed
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: Internet Job Search and Unemployment Durations. https://app.cochat.ai/papers/10.1257/000282804322970779
- The paper
- Kuhn, P., & Skuterud, M. (2004). Internet Job Search and Unemployment Durations. American Economic Review. https://doi.org/10.1257/000282804322970779
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.
