Pre-Submission Review for Economics Papers

Economics reviewers often ask:

• what is the precise economic question?
• what is the paper's counterfactual?
• does the identification strategy support the claim?
• are assumptions visible and defensible?
• do the main tables and figures answer the stated question?
• are robustness checks informative rather than decorative?
• does the paper explain its contribution relative to the active economics literature?
• are data, code, and documentation ready for the transparency expectations of the target journal?
• is the journal target realistic for the contribution size and evidence type?

The paper has to earn trust in the design before the interpretation can carry much weight.

In our pre-submission review work, economics manuscripts most often fail because the empirical result is interesting but the identification claim is stronger than the design can support.

Counterfactual gap: the paper names a treatment, shock, or policy change but never makes the comparison group logic fully convincing.

Mechanism blur: the result is consistent with several channels, while the discussion treats one channel as established.

Robustness clutter: many checks are included, but the key identifying assumption is still not tested or explained.

Table-to-claim mismatch: the abstract claims a broad policy effect, while the main tables support a narrower descriptive or local result.

Replication weakness: code, raw data access, derived data, or documentation would not let another researcher reproduce the manuscript's core outputs.

A useful review should identify the first objection an economics referee would write down.

AEA journal materials make data and code availability a serious publication issue. The AEA Data and Code Availability Policy says accepted papers must provide the data, code, and documentation needed to reproduce results, with documented exceptions for constraints such as confidential data. AER: Insights also tells authors that submissions must comply with the AEA policy.

QJE author instructions point authors to a clear manuscript order and supplementary-data labeling. AEA style guidance also treats JEL codes, short abstracts, registration statements for randomized controlled trials where applicable, and data-source citations as part of the economics publishing package.

Those signals matter before submission. A paper can be intellectually promising and still look unready if the evidence, code, JEL framing, appendix, and data statement are not aligned.

Send the manuscript, target journal, working paper version if one exists, data dictionary, code repository or archive, README, main tables and figures, appendix, pre-analysis plan or registry if relevant, robustness files, model appendix, and any referee comments from prior submissions.

If data cannot be shared publicly, include the access pathway, license constraints, synthetic or intermediate files if available, and the exact language you plan to use in the data availability statement.

A useful economics pre-submission review should include:

• identification verdict
• theory or mechanism critique
• data and measurement check
• robustness and sensitivity review
• replication package readiness note
• contribution and literature-positioning critique
• journal-lane recommendation
• submit, revise, retarget, or diagnose deeper call

The review should not only say "add robustness." It should name the specific identifying assumption, model implication, or table-to-claim gap that blocks submission.

Before submission, authors often need to:

• rewrite the abstract around the strongest supported claim
• make the counterfactual explicit
• separate causal, descriptive, and theoretical claims
• move distracting robustness checks to the appendix
• add the robustness check that tests the main assumption
• document variable construction and sample restrictions
• clean the code and README enough for reproduction
• retarget from a general-interest journal to a field journal, or from a field journal to a stronger specialty venue

These fixes make the paper easier for an editor to evaluate quickly.

An applied micro paper needs identification clarity, policy context, and robustness that maps to the design. A theory paper needs assumptions, propositions, intuition, and examples that show why the model changes the reader's understanding. A macro paper needs model discipline, calibration or estimation transparency, and connection to aggregate evidence. An experimental paper needs design validity, preregistration where relevant, balance, attrition, and external-validity restraint. An econometrics paper needs a clear problem class, assumptions, proof readability, simulation evidence, and applied value.

The AI manuscript review can flag whether the blocking risk is identification, contribution, replication, or journal fit.

Use this page when the core contribution is economic inference, policy evaluation, development, labor, macro, IO, public economics, or econometric method. Use finance review when the manuscript's submission risk depends on finance-specific theory, data, and audiences: returns, pricing factors, corporate finance decisions, disclosure, banks, investors, market liquidity, or risk.

That distinction keeps the buyer's problem clear.

Do not submit an economics paper if the paper's strongest claim depends on a comparison the manuscript has not defended. Reviewers can disagree about taste, but they will converge quickly around an identification gap.

Also pause if the replication package is an afterthought. A clean paper with a broken code archive creates avoidable doubt. Before submission, the data statement, README, code order, table outputs, and figure outputs should tell the same story as the manuscript. If proprietary or confidential data are involved, the access limits should be precise instead of vague.