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name: aejpol-referee-strategy description: Use when anticipating how AEJ: Economic Policy referees and editors will read a manuscript, before submission or before an R&R, to pre-empt the objections that sink policy-evaluation papers. Maps likely pushback to fixes and calibrates expectations; it does not write the response letter (see aejpol-rebuttal) or fix the identification.

Referee Strategy — Reading the Manuscript as an AEJ: Policy Referee (aejpol-referee-strategy)

When to trigger

• Before submitting: you want to find the objections a referee will raise first
• Deciding whether the paper is ready or needs another round of work
• Calibrating expectations about the AEA single-blind process and timeline
• Triaging which weaknesses to fix vs. disclose before submission

How AEJ: Policy referees read

AEJ: Policy reviews are single-blind through the AEA system (referees see the authors; authors do not see referees), refereed by economists who expect both credible causal evidence and a policy-relevant welfare reading. A referee typically tests four things in order; a paper dies at the first one it fails:

1. Is it a policy paper of broad interest? (the aejpol-topic-selection test) — a clean estimate with no policy lever or welfare reading invites a "better suited to a field journal / AEJ: Applied" rejection.
2. Is the causal claim credible? (the aejpol-identification test) — staggered TWFE, asserted parallel trends, a weak instrument, or an over-generalized RDD are the usual kill shots.
3. Does the welfare/policy reading follow? (the aejpol-theory-model test) — a hand-waved "this is welfare-improving" or a sufficient-statistic formula whose assumptions are violated.
4. Is it robust and reproducible? (the aejpol-robustness / aejpol-replication-package tests).

Pre-empting the predictable objections

| Likely referee objection | Pre-emption to build before submitting | |---|---| | "This isn't a policy paper / not broad-interest" | Lead with the policy question + welfare stake; state the cost-benefit reading in the abstract | | "Staggered TWFE is biased here" | Heterogeneity-robust DID + Bacon decomposition + flat leads, in the main paper | | "Parallel trends is assumed, not shown" | Event-study leads + honest-DID bounds | | "Exclusion restriction is not credible" | Institutional + theoretical defense + falsification | | "The welfare claim is hand-waved" | Explicit sufficient-statistic / MVPF / cost-benefit derivation | | "External validity is unclear" | Heterogeneity by setting; explicit scope of the policy lesson | | "Effect is significant but tiny / not policy-relevant" | Benchmark the magnitude against budget / status quo | | "Not reproducible / data unavailable" | AEA-compliant package + restricted-data access path ready |

Calibrating expectations

• AEA review is thorough; expect a small number of detailed referee reports and an editor letter. Plan for an R&R rather than a clean accept.
• Decide in advance which objections you will fix (identification, robustness) vs. bound and disclose (external validity, a calibrated welfare parameter). Disclosing a limitation precisely is stronger than hiding it.

Checklist

• [ ] The "is this a policy paper?" objection is pre-empted on page one
• [ ] The single most likely identification objection has a main-text answer (not relegated to the appendix)
• [ ] The welfare reading is derived, not asserted
• [ ] Each predictable objection is mapped to an exhibit or paragraph that answers it
• [ ] Limitations you cannot fix are bounded and disclosed precisely
• [ ] Reproducibility is ready before the editor asks

Anti-patterns

• Submitting hoping referees will not notice the staggered-TWFE / pre-trends problem
• Hiding a known limitation instead of bounding and disclosing it
• A welfare claim with no derivation, trusting the referee to grant it
• Putting the decisive robustness check only in an online appendix the referee may skip
• Mis-calibrating to a generic-journal process and ignoring AEA single-blind norms

Worked vignette (illustrative)

An education-policy paper using a funding-formula RDD anticipates three objections: (1) "local estimate only" → states the estimand and argues the threshold population is the marginal policy population; (2) "manipulation at the cutoff" → CJM density test + donut RDD; (3) "no welfare reading" → translates the test-score effect into a cost-per-standard-deviation and compares to class-size policies. All three answers are in the main text, so no referee can raise them as fatal.

Output format

【Broad-interest verdict】would a referee call this a policy paper? [Y/N + fix]
【Top identification objection】+ main-text pre-emption
【Welfare-reading objection】derived or hand-waved? + fix
【Objection→answer map】[objection → exhibit/paragraph]
【Fix vs. disclose list】what to fix now / what to bound and disclose
【Next step】aejpol-submission (if ready) or back to the named skill