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Data Review Checklist for Empirical Economics

Data quality determines the credibility of empirical research. No econometric method can fix fundamentally flawed data. This checklist provides a systematic approach to reviewing data used in economics research -- whether you are checking your own work, reviewing a coauthor's data preparation, or assessing the data quality in a paper you are refereeing.

In the cataloguereviewMIT
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Provenance

Project
E2ER bundled skills
Maintained by
E2ER contributors
Licence
MIT
Source file
bhanneke/E2ER-project/blob/orgsci-mvp/skills/files/review/data-quality.md
Identifier
e2er/review/data-quality

Use it

Ships with every installation of E2ER.

Cite this skill
Persistent identifiers planned
@software{e2ercontributors2026datareviewchecklistforem,
  title   = {Data Review Checklist for Empirical Economics},
  author  = {E2ER contributors},
  year    = {2026},
  note    = {E2ER skill. Persistent identifier planned},
  url     = {https://github.com/bhanneke/E2ER-project/blob/orgsci-mvp/skills/files/review/data-quality.md}
}
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Description

Data model
Discipline
Economics
Method family
Empirical (quantitative)
Design
not specified
Research stage
Review
Contributors
E2ER contributors (Software, Methodology)
Usage
used in 2 templates · 1 published study · loaded by 1 specialist · Examples: 3 example studies
Source
E2ER repository · skills/files · @3b91f0e
Record
skill:e2er/review/data-quality · JSON

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More review skills in E2ER bundled skills