jibs-data-analysis

Research

Use when running and reporting the empirical analysis for a Journal of International Business Studies (JIBS) manuscript — cross-national measurement equivalence, common-method-variance checks, the right multilevel/dynamic-panel estimator, endogeneity and dynamic-endogeneity identification, and robustness aligned to the JIBS methods-editorial canon. Executes and reports; it does not design the study (jibs-methods) or frame the contribution (jibs-contribution-framing).

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Data Analysis & Cross-National Validity (jibs-data-analysis)

When to trigger

Cross-country or multilevel data are collected and it is time to estimate and report
You are unsure your estimator matches nesting (individuals in firms in countries) or a process design
Reviewers will probe measurement equivalence, CMV, or (dynamic) endogeneity
A reviewer cites a JIBS "From the Editors" methods editorial against your analysis

Establish cross-national measurement equivalence first

At JIBS, because constructs travel across countries and cultures, measurement equivalence is a first-order review concern, not an afterthought. Before testing hypotheses:

Reliability & CFA. Report reliability (alpha/composite reliability) and a confirmatory factor analysis with fit (CFI, TLI, RMSEA, SRMR).
Measurement invariance. Run multi-group CFA and report configural → metric → scalar invariance across countries; if scalar fails, report partial invariance or the alignment method and discuss what cross-country comparisons remain defensible.
Construct & discriminant validity. AVE per construct; AVE > inter-construct squared correlations (or HTMT). Report the correlation matrix with reliabilities on the diagonal.
Aggregation (multilevel). Justify any aggregation to the country/firm level with ICC(1), ICC(2), and r_wg(j).
Qualitative designs. Where the design is case-based, "validity" becomes trustworthiness — a transparent data structure, an audit trail, and representative cross-case quotations.

Match the estimator to the cross-country/multilevel design

Data structure / claim	Estimator
Individuals/firms nested in countries	Multilevel / HLM (random intercepts/slopes); country-level Xs
Latent constructs across groups, mediation	Multi-group / multilevel SEM
Internationalization as a path-dependent process	Dynamic panel (system/diff GMM), firm FE, lagged DVs
Cross-border entry-mode / location choice	Logit/probit/multinomial; conditional/mixed logit
Cross-country count/limited DV	Poisson/negative binomial; Tobit/Heckman as fits

Cluster standard errors to the country (or country-year) structure.

Common-method variance (CMV) — an active JIBS gatekeeper

JIBS routinely asks survey/same-respondent papers that appear to suffer from CMV to run validity checks and resubmit. A Harman single-factor test alone is not sufficient. Report the designed separations first (from jibs-methods), then statistical evidence: a marker-variable approach, an unmeasured latent method factor (CFA), or showing interaction/cross-level effects survive (these are hard to inflate by CMV). Cite the JIBS "From the Editors" CMV editorial.

Endogeneity and "dynamic endogeneity"

For internationalization-as-process designs, address dynamic endogeneity explicitly: past strategy, performance, and unobserved firm heterogeneity co-evolve. Execute the identification planned at design (instruments and first-stage strength, dynamic-panel GMM with instrument-count and Hansen/AR(2) diagnostics, DiD/natural experiment, or selection models) and discuss the assumptions. Reviewers anchor this to the JIBS endogeneity/dynamic-endogeneity editorials.

Reporting & robustness

Mediation: bias-corrected bootstrap CIs (e.g., 5,000 resamples); conditional indirect effects for moderated mediation.
Moderation/cross-level interactions: report the coefficient and plot simple slopes; report incremental variance.
Effect sizes: report magnitudes, not only p-values (a JIBS p-value editorial cautions against p-value worship).
Robustness: alternative country samples (drop influential countries), alternative distance measures, alternative specifications; sensitivity to endogeneity assumptions.

Execution bridge (StatsPAI / Stata MCP)

Run the battery, don't just enumerate it. Full map: execution-with-mcp. JIBS is international business — cross-country panels with confounded institutions; emphasize fixed effects, clustering, and endogeneity of location / entry choices.

Many outcomes / specifications: romano_wolf (step-down FWER) or benjamini_hochberg — report the adjusted threshold.
OVB sensitivity: oster_delta / sensemakr.
Inference: wild_cluster_bootstrap (few clusters), twoway_cluster / conley; multilevel data → cluster at the right level.
Re-fit off one handle: audit_result(result_id) lists the missing checks and the exact suggest_function for each.
Exhibits: etable / did_summary_to_latex from the handle — no retyped numbers.

Keep the decisive checks in the body and the exhaustive battery in the appendix. See the executed chain in the JF execution walkthrough.

Output format

【Measurement】reliability/CFA fit; invariance configural/metric/scalar (or partial/alignment) ...
【Estimator】multilevel / multilevel-SEM / dynamic-panel GMM / choice model; SE clustered by country ...
【CMV evidence】designed separation + marker/latent-method test (beyond Harman) ...
【Endogeneity / dynamic endogeneity】strategy executed; diagnostics; assumptions ...
【Mediation/Moderation】bootstrap CIs / simple slopes / incremental variance ...
【Robustness】country-drop, alt distance, alt specs ...
【FTE editorial alignment】 ...
【Next step】jibs-contribution-framing

Anti-patterns

Pooling countries without testing measurement invariance.
Single-factor (Harman) test as the sole CMV defense.
OLS on country-nested data, ignoring non-independence.
Internationalization-process regressions with no dynamic-endogeneity treatment.
Reporting p-values with no effect sizes or practical magnitude.
Treating cultural/institutional distance as a black-box covariate.