IO accepts quantitative, formal, and qualitative IR work but is demanding about each. The design must
credibly connect the IR theory (io-theory-building) to evidence at or across the international
level, and rule out the strongest rival international explanation. This skill is mode-aware: pick the
section that matches your work.
io-literature-positioning
io-transparency-and-data-policy).For the single strongest rival international explanation, write one sentence: "If the rival were true rather than my argument, the international data/cases would look like ___; instead they look like ___." If you cannot, the design does not yet identify the IR contribution.
Claim: ratifying an international monitoring treaty raises later compliance. The naive cross-section confounds the effect with selection into membership — states that mean to comply ratify. An IO-credible design exploits variation in ratification timing: among eventual ratifiers, treat the staggered timing as identification with a modern staggered DID/event-study estimator (not naive TWFE) and report pre-trends. The adjudication sentence: if selection drove compliance, the gain would appear before ratification; instead it appears only after and tracks monitoring intensity. A sensitivity check then asks how strong an unobserved confounder must be to overturn it (say, twice the observed regime-type effect — illustrative). Timing-based identification, a rival-ruling counterfactual, and a sensitivity bound convert an association into an IR causal claim at IO.
| Threat | Where it appears | Design answer |
|---|---|---|
| Selection into treaty/alliance/IO membership | compliance, cooperation studies | ratification-timing, instrument, or selection model + sensitivity |
| Dyadic / network non-independence | any dyad-level outcome | multiway/dyadic-robust SEs or AME/latent-space models |
Estimate and audit the design, don't only describe it. Full map:
execution-with-mcp. International Organization is IR — country/dyad panels with difficult identification; foreground the source of variation and robustness to alternative explanations.
detect_design → recommend → fit with as_handle=true → audit_result.callaway_santanna / sun_abraham +
bacon_decomposition + honest_did_from_result); IV (effective_f_test +
anderson_rubin_ci); RDD (rdrobust + mccrary_test).romano_wolf for many-outcome
family-wise control, and mediate for mediation (not naive controlling-away).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.
【Mode】quant-causal / qualitative / experiment / formal-empirical
【Level of analysis】unit + why it matches the IR theory
【Estimand or claim】what is being identified/shown
【Key assumption(s)】and how each is defended (incl. dyadic/TSCS dependence)
【Rival ruled out】the adjudication sentence
【Robustness/sensitivity / proof appendix】planned
【Next】io-data-analysis
../../resources/external_tools.md — dyadic/network/gravity packages and CAQDAS for qualitative IR../../resources/official-source-map.md — formal-proof and quantitative-result verification policy