| name | wp-research-design |
| description | Use when defending the research design of a World Politics manuscript — comparative-historical and case selection, quantitative cross-national identification, qualitative process tracing, experiments, or formal-empirical linkage for cross-case questions. World Politics expects explicit research design and appropriate methods, judged on each tradition's own terms. Strengthens the design; it does not write code. |
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.
| Referee objection | The fix this skill drives |
|---|
| "Case selection unjustified" | State what each case is a case of and the design logic (typical / deviant / most–least-likely / paired); convenience is not a design |
| "Selecting on the dependent variable" | Add variation on the outcome, or reframe as a scope-condition study with disconfirming cases |
| "Causal language on associational design" | Match the verb to the warrant; reserve causal claims for designs that identify them |
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
