jme-skills

Plugin jme-skills from marketplace awesome-journal-skills in brycewang-stanford/Awesome-Journal-Skills. Commands read from the repo's manifest — 1 month ago.

Skills (12)

• jme-contribution-framing

  Use when sharpening the "what is new and why it matters for macro/policy" claim of a Journal of Monetary Economics (JME) manuscript — turning a result into a first-order monetary-economics contribution that clears a single-blind, two-referee, "up or out" process.

• jme-data-analysis

  Use when building or stress-testing the empirical/quantitative analysis for a Journal of Monetary Economics (JME) manuscript — VAR/SVAR, local projections, DSGE estimation, moment matching, IRFs, and FEVDs — to monetary-economics and macroeconomics norms. Covers estimation choices, inference, and ro

• jme-identification-strategy

  Use when the identification of a monetary or macro shock (or a structural mechanism) is the bottleneck for a Journal of Monetary Economics (JME) manuscript — high-frequency surprises, narrative shocks, proxy/SVAR, local projections, sign restrictions, and model-based identification. Stress-tests the

• jme-literature-positioning

  Use when positioning a Journal of Monetary Economics (JME) manuscript against the monetary-economics and macroeconomics frontier — staking the contribution against monetary-policy, business-cycle, DSGE, intermediation, and expectations literatures without writing a standalone survey.

• jme-rebuttal

  Use after a Journal of Monetary Economics (JME) revise-and-resubmit to plan the response letter and revision — given JME's distinctive "up or out" rule (the resubmission ends in acceptance or rejection, no second R&R) and the ~50% publication-likelihood signal an R&R carries.

• jme-replication-and-data-policy

  Use when assembling the supplementary-materials / replication deposit for a Journal of Monetary Economics (JME) manuscript — depositing data, code (Dynare/MATLAB/Stata/R), and appendices on ScienceDirect / Mendeley Data per JME's supplemental-materials policy, plus the Elsevier generative-AI declara

• jme-review-process

  Use when you need to understand how the Journal of Monetary Economics (JME) review process actually works — single anonymized (single-blind) review with at least two reviewers, the distinctive "up or out" first-revision rule, the ~50% publication-likelihood threshold for an R&R, suggested referees,

• jme-submission

  Use when running the final pre-submission preflight for the Journal of Monetary Economics (JME) via Elsevier Editorial Manager — the US$350 (US$200 PhD) up-front fee, single-anonymized review, the 40-page / ≤10 tables-and-figures cap, 100-word abstract, line numbers, author-date references, JEL code

• jme-tables-figures

  Use when designing the main-text exhibits of a Journal of Monetary Economics (JME) manuscript under the strict 40-page / no-more-than-10-tables-and-figures-combined cap — impulse-response plots, FEVDs, moment tables — and deciding what to push to the online supplementary appendix.

• jme-topic-selection

  Use when assessing whether a research question fits the Journal of Monetary Economics (JME) — monetary theory and policy, central banking, business cycles, growth, financial intermediation, fiscal interactions, and expectations — before investing in a model or estimation. Checks scope fit and the po

• jme-workflow

  Use when deciding which jme-* sub-skill to invoke next, or when sequencing manuscript work from topic selection through the "up or out" rebuttal for a Journal of Monetary Economics (JME) submission. Routes — it does not replace — the specialized skills.

• jme-writing-style

  Use when applying Journal of Monetary Economics (JME) house style — the 100-word abstract that may not begin with "This paper" or "We", author-date references with journal titles spelled out, double-spaced 12-point formatting with line numbers, footnotes not endnotes, up to five keywords, and at lea

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