Individual skill
jbes-literature-positioning
Use when positioning a Journal of Business & Economic Statistics (JBES) methods paper against prior econometric and statistical methods. Stakes what is new relative to the existing toolkit; it does not write a standalone literature survey.
Journal-of-Business-and-Economic-Statistics-Skills/skills/jbes-literature-positioning/SKILL.md
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# Literature Positioning (jbes-literature-positioning)
## When to trigger
- A referee will ask "how is this different from method X already in the literature?"
- The contribution relative to the closest existing estimator/test/algorithm is fuzzy
- You are unsure whether your improvement is incremental or genuinely new
- You need to map your method onto the right strand (time series, panel, GMM, ML, Bayesian, etc.)
## Why positioning is the methods-paper crux at JBES
JBES referees are method experts: they judge a paper first by **what it adds to the existing toolkit**. Because the journal explicitly welcomes **adaptation of methods from machine learning and data science** alongside classical econometrics, your closest competitors may live in **two literatures at once** — the statistics/ML method you adapt *and* the econometric problem you apply it to. Position against **both**. The contribution must be stated as a delta against named prior methods, not as a freestanding survey: which assumptions you relax, which rates you improve, which computational barrier you remove, or which empirical setting prior methods cannot handle.
## Positioning protocol