Research Design (wp-research-design)

World Politics asks every article to "be explicit about its research design and use appropriate methods," and applies separate expectations to quantitative and qualitative work. Because the journal values arguments that travel across cases, the design must connect a portable argument (wp-theory-building) to evidence in a way that rules out the strongest cross-case rival. This skill is mode-aware: pick the section that matches your work.

When to trigger

• Specifying case selection, identification, or experimental design for a cross-case question
• A reviewer questioned causal claims, case choice, external validity, or a confound
• Justifying why your design adjudicates the rival account from wp-literature-positioning

Comparative-historical & case-based (a World Politics staple)

• Case selection by design logic — typical, deviant, most/least-likely, paired/structured-focused comparison, or set-theoretic (QCA). Say what each case is a case of and why the comparison identifies the argument. Convenience is not a design.
• Process tracing with explicit tests (hoop, smoking-gun, straw-in-the-wind); state what evidence would have disconfirmed the argument in each case.
• Travel. Show the comparison licenses a claim beyond the cases studied (scope conditions), not just a within-case story.

Quantitative / cross-national

• Identification first. State the estimand and the assumptions that license a causal reading (parallel trends, exclusion, continuity, ignorability). Defend them; don't assert them.
• TSCS realities. With time-series-cross-section data, address serial correlation, unit effects, and cross-sectional dependence (panel-corrected SEs, Driscoll–Kraay); avoid naive TWFE on staggered treatment — use modern estimators.
• Designs: DID/event study, IV (first-stage strength, exclusion, weak-IV-robust inference), RDD, matching/weighting with balance + sensitivity; survival models for onset/duration.
• Inference: cluster at the right level (often country); sensitivity to unobserved confounding.

Experiments & formal-empirical

• Experiments: preregister design and primary analyses; report power/MDE; address attrition and ethics (APSA Principles — see wp-review-process/wp-submission). State the generalization claim across contexts honestly.
• Formal-empirical: make the empirical test follow from the model's comparative statics, and distinguish predictions unique to your model from those shared with rivals.

The adjudication test (World Politics–specific)

For the single strongest rival explanation, write one sentence: "If the rival were true rather than my argument, the cases/data would look like ___; instead they look like ___." If you cannot, the design does not yet identify a contribution that travels.

Execution bridge (StatsPAI / Stata MCP)

Estimate and audit the design, don't only describe it. Full map: execution-with-mcp. World Politics is comparative/IR with a strong qualitative tradition; apply the chain below to its quantitative-causal lane and say so when work is case-based.

• detect_design → recommend → fit with as_handle=true → audit_result.
• Observational causal claims: staggered DiD (callaway_santanna / sun_abraham + bacon_decomposition + honest_did_from_result); IV (effective_f_test + anderson_rubin_ci); RDD (rdrobust + mccrary_test).
• Experiments: randomization-based inference, romano_wolf for many-outcome family-wise control, and mediate for mediation (not naive controlling-away).
• Sensitivity: oster_delta / sensemakr for observational claims.

Report the effect size in interpretable units; route the full battery to the appendix/supplement. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.

Anti-patterns

• Convenience case selection dressed up as theory-driven; selecting on the dependent variable
• Naive TWFE on staggered treatment; ignoring serial correlation / cross-sectional dependence in TSCS
• "Causal" language on a design that only supports cross-case association
• A within-case story over-generalized with no scope conditions
• A design that cannot distinguish your argument from the leading alternative

Design-objection patterns and the venue-specific fix

World Politics judges each tradition on its own terms and prizes designs built to adjudicate, so design objections cluster predictably across the comparative and IR styles it publishes.

Worked micro-example (illustrative)

A hypothetical comparative study asks whether electoral autocracies are more war-prone than closed ones. A weak version selects three war-fighting electoral autocracies and infers a tendency — a selection-on-the-outcome flaw a referee will name immediately.

Mode:      comparative-historical, structured-focused comparison
Estimand:  conflict propensity, electoral vs closed autocracy, holding capacity fixed
Selection: 2 electoral + 2 closed autocracies matched on GDP/region; varies on the OUTCOME
Adjudication: if the rival "capacity, not regime type" held, the matched closed cases would
  fight as often; instead the electoral cases initiate ~2x more disputes (illustrative).
Travel:    scope condition — holds where elections raise audience costs, not where they are sham

The redesign varies on the outcome and writes the adjudication sentence, so the comparison can identify a contribution that travels. (Counts and ratios illustrative; confirm design expectations against current guidelines.)

Output format

【Mode】comparative-historical / quant cross-national / qualitative / experiment / formal-empirical
【Estimand or claim】what is being identified/shown, and across which cases
【Case selection / key assumption(s)】and how each is defended
【Rival ruled out】the adjudication sentence
【Robustness/sensitivity】planned checks
【Next】wp-data-analysis

Supplementary resources

• ../../resources/external_tools.md — identification/TSCS packages, QCA, and CAQDAS for qualitative work
• ../../resources/official-source-map.md — reviewer-guideline expectations for design and methods