Rejected from Journal of Econometrics? Where to Submit Next

The journal's current scope includes identification, estimation, testing, decision, and prediction issues in theoretical and applied econometrics. A rejection can therefore concern several different contracts. Do not collapse all of them into “not novel enough.”

Diagnose whether the rejection is theoretical, applied, or audience-driven.

A desk rejection usually signals contribution size, scope, audience, positioning, or an obvious mismatch between theory and application. It does not certify that proofs or code are correct. A method developed mainly to answer one substantive question may be stronger in an applied outlet than after being inflated into a general econometric contribution.

A post-review rejection is portable evidence. Referees may expose failed identification, unstated regularity conditions, incorrect rates, nonuniform asymptotics, a fragile bootstrap, weak-instrument behavior, simulation tuning, selective designs, empirical specification search, or irreproducible tables. Those defects will reappear in the same specialist community.

A transfer offer, if present, should be evaluated as logistics. The receiving journal independently judges the paper. Confirm whether reports transfer and whether the revised version can be uploaded before review.

Econometric Theory

Best for: papers whose durable contribution is a rigorous advance in the probabilistic or statistical foundations of econometric modeling, estimation, prediction, testing, or inference. Modern work involving high-dimensional data, computation, machine learning, and interdisciplinary theory can fit when the theorem is central.

Think twice if: the proof issue remains unresolved or the contribution depends mainly on one empirical application. Verify every condition, rate, limit, and dependency, and explain what the result adds to econometric theory rather than simply moving the same manuscript.

Journal of Applied Econometrics

Best for: innovative quantitative economic research applying existing or new econometric techniques to substantive problems in measurement, estimation, testing, forecasting, or policy. The official scope emphasizes economic content, interpretation, transferable techniques, and replicability.

Think twice if: the application is decorative or the data and specialized programs cannot be made reproducible through an appropriate archive or controlled route. Show what an economist learns or decides differently because of the method.

The Econometrics Journal

Best for: fresh theoretical or applied econometrics where the contribution has direct or potential application value. It can fit a concise leading-case result without requiring exhaustive generality, provided the manuscript clearly identifies the problem and value.

Think twice if: the paper cannot meet the journal's streamlined submission requirements or still needs an open-ended major-revision program. Its official process emphasizes quick screening, review, revision, and dissemination, so scope and presentation discipline matter.

Journal of Business & Economic Statistics

Best for: statistical methodology, computation, forecasting, causal inference, time series, panel methods, or data-science work with substantive applications in business, economics, or finance. It is coherent when statistical readers and applied researchers both benefit.

Think twice if: the method is only a field-specific adjustment with little statistical contribution, or the empirical application does not test the method's practical value. Align the paper with current scope and demonstrate robustness beyond one favorable dataset.

Econometrics and Statistics

Best for: methodological research connecting econometric questions with modern statistics, including model selection, dependence, panels, measurement error, Bayesian methods, time series, computation, and high-dimensional inference. It can fit work whose audience crosses traditional journal boundaries.

Think twice if: the manuscript is a narrowly applied economic study without a transferable methods result, or a formal theorem with no econometric motivation. State the interface contribution and evaluate it under realistic data-generating processes.

Quantitative Economics

Best for: high-quality theoretical or empirical work whose quantitative contribution matters across economic fields. A paper with a strong economic question and a method essential to answering it may fit better than one presented as a specialist technique alone.

Think twice if: the manuscript remains a narrow estimator extension or the economic consequence is small. The Econometric Society venue is not an easier substitute for Journal of Econometrics; broad interest, rigor, and contribution must be visible.

Create an assumption-to-setting map. For each formal condition, list the economic interpretation, observed diagnostic, plausible violation, consequence of failure, and whether a weaker result survives. This is more useful than adding another paragraph that calls assumptions standard.

1. Contribution statement: specify the obstacle, result, and capability unlocked. Separate theorem novelty from empirical importance.
2. Identification: prove what is learned from observables under stated assumptions before discussing estimators or algorithms.
3. Assumptions: organize primitive and high-level conditions, provide examples and counterexamples, and identify which results use each condition.
4. Proof audit: map theorem dependencies, verify edge cases and limit operations, test notation consistency, and obtain an independent line-by-line read of contested arguments.
5. Finite-sample designs: include favorable, calibrated, and adversarial settings. Vary signal, dependence, dimensionality, misspecification, tuning, and sample size.
6. Baselines: implement strong current methods with comparable information, tuning budgets, initialization, and convergence criteria.
7. Inference: report coverage, size, power, bias, variance, interval length, and failure or nonconvergence, not one preferred metric.
8. Empirical application: show how estimates, uncertainty, rankings, forecasts, counterfactuals, or policy conclusions change and why the change is credible.
9. Reproducibility: rebuild every table and figure from a clean environment; archive code, seeds, package versions, data access, and execution instructions.
10. Claims and discussion: distinguish pointwise from uniform results, asymptotic from finite-sample guarantees, and demonstrated settings from conjectured extensions.

Audit the theory-to-application chain before choosing another journal.

Use a transfer only when the receiving journal matches the revised center and the administrative savings are meaningful. Verify the current author instructions, submission fee if any, report handling, and ability to replace files. A transfer suggestion is not editorial endorsement.

Appeal when a specific factual or procedural error is decisive: a claimed counterexample violates the theorem's stated domain, a report overlooks an uploaded appendix, or the process applied the wrong article category. State the error, evidence, and possible effect. Do not turn an appeal into a second cover letter arguing that the paper is important.

Submit fresh when the revision changes the audience or contribution. While an appeal or transfer remains active, do not submit the manuscript to another journal and do not conduct simultaneous or parallel submission. Preserve version history and disclose related papers and data as required.

In our pre-submission review work with Journal of Econometrics manuscripts, four patterns repeatedly determine the next route. They are qualitative editorial observations, not a claim about private decisions or acceptance probabilities.

Pattern 1: estimation begins before identification ends

In Journal of Econometrics candidates, the paper often proposes an estimator and reports asymptotics without first showing which parameter is uniquely determined by observed data under the maintained structure. We trace observables, latent variables, restrictions, support, normalization, and target parameters. We test alternative data-generating processes that produce the same observables. When identification is partial or local, we rewrite the estimand and inference contract before evaluating the estimator.

Pattern 2: a high-level assumption hides the economic burden

Another Journal of Econometrics pattern calls an eigenvalue, mixing, smoothness, sparsity, rank, or separation condition standard even when the empirical setting makes it doubtful. We map each condition to data and economic behavior, identify diagnostics, and study violations. A theorem can be valid while the application is not. That distinction often routes a paper toward theory or forces a more credible applied design.

Pattern 3: simulations select the method's home field

Parameter values, error distributions, initialization, tuning, or competing implementations favor the proposed method. We add calibrated designs from the application, weak-signal and boundary cases, misspecification, dependence, and nonconvergence reporting. We rerun baselines under comparable tuning and compute. The revised evidence may support a narrower but defensible claim.

Pattern 4: the empirical illustration never changes the answer

The new procedure produces a slightly different standard error or coefficient, but the manuscript does not show what substantive inference, forecast, ranking, or decision changes. We trace the method through every empirical table and figure and identify the conclusion it enables. If none changes, the paper is theory-led; if the economic result is central, the paper needs a deeper applied contract.

These checks reach equations, proofs, assumptions, simulations, data construction, code, tables, appendix, and abstract. A new journal name cannot repair them. Routing becomes credible when the strongest validated contribution and the intended reader finally align.

Choose a destination only when the revised abstract can state the econometric obstacle, result, assumptions, finite-sample evidence, empirical value, and boundary without hand-waving. Confirm every decision-letter issue is fixed, bounded, or answered with evidence and verify the destination's current scope immediately before submission.

For this page, read final Search Console data after 14 complete days. At 21 complete days, keep, revise, consolidate, or stop based on indexation, exact-query ownership, impressions, clicks, and qualified /ai-review starts. A published page is an experiment, not a traffic result.