Car methods

Research Design & Methods (car-methods)

When to trigger

• The design may not deliver the inference the question needs (identification, internal validity, equilibrium logic)
• An archival causal claim rests on an endogenous regressor with no strategy
• An experiment's manipulation may not isolate the theorized construct
• The study involves human participants and ethics-approval verification is unprepared
• A reviewer says "the design cannot support this claim"

Match the design to the question (CAR is method-agnostic)

CAR welcomes any appropriate method; the bar is fit and rigor, not a preferred method. Pick the design that earns the claim:

Claim	Design that earns it
Capital-market/contracting effect of reporting	Panel archival with fixed effects + an identification strategy
Causal effect of an information feature on judgment	Controlled experiment (lab/online/professional subjects)
Existence/optimality of an equilibrium or contract	Analytical model: primitives, equilibrium concept, proofs
Mechanism inside firms, audits, or standard-setting	Field study / interviews with an explicit coding protocol
A new construct's measurement and external validity	Survey with a validated instrument; or multi-method

A two-study design (e.g., an experiment isolating the mechanism behind an archival association) is a recognized CAR strength.

Design against the threats CAR reviewers probe

• Identification (archival). Anticipate omitted variables, reverse causality, and selection; plan a strategy (natural experiment, difference-in-differences with a credible parallel-trends argument, instrument, entropy balancing/matching, firm/year fixed effects) and state the assumptions each requires.
• Internal validity (experimental). Design manipulation and attention checks; randomize; pre-specify the predicted mediator; rule out demand effects and confounds; justify the participant pool (student, online, or professional) for the inference.
• Model discipline (analytical). Justify each assumption and the equilibrium concept; show which results are robust to relaxing assumptions.

CAR-specific design requirements

• Ethics-approval verification (mandatory). For any research involving human participants — experiments, interviews, surveys, including secondary human-participant data — you must obtain and upload institutional REB/IRB clearance, an REB-issued exemption, or a senior-administrator letter where no review board exists. A bare assertion is not accepted, and failure is grounds for withdrawal by the EIC. Plan this before data collection.
• Instrument capture. Surveys/experiments must submit the full research instrument with the manuscript (Data Integrity policy, item 1).
• Proprietary/field data. If you use proprietary organizational data, plan a credible means of verifying the data source/site on editor request and disclose any non-disclosure restrictions (policy item 2).

Execution bridge (StatsPAI / Stata MCP)

For the empirical / causal lane, estimate and audit rather than only specify. Full map: execution-with-mcp. CAR is archival/empirical accounting; the DiD / IV / RDD chain serves its causal designs around reporting and regulation.

• detect_design → recommend → fit with as_handle=true → audit_result to enumerate the checks the design owes.
• Panel / 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 and romano_wolf for the many-outcome family-wise correction reviewers expect.

Match the toolchain to the reviewer pool, and report the effect size the venue wants. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.

Checklist

• Design can support each prediction (identification / internal validity / equilibrium logic)
• (Archival) endogeneity strategy specified with its assumptions
• (Experimental) manipulation/attention checks, randomization, predicted mediator, pool justified
• (Analytical) assumptions and equilibrium concept justified; robustness mapped
• Ethics-approval verification secured for any human participants
• Full instrument prepared; proprietary-data verification/NDA plan in place

Anti-patterns

• Cross-sectional causal claims from one-period archival correlations with no strategy.
• Confounded manipulations that move more than the theorized construct.
• Assumption-driven results (analytical) never tested for robustness.
• Treating ethics approval as a formality — CAR requires documented verification, not a statement.

Output format

【Design】panel-archival / experiment / analytical / field / survey / multi-method
【Inference fit】each prediction supportable? notes ...
【Identification / internal validity / equilibrium】strategy + assumptions ...
【Ethics】REB/IRB clearance, exemption, or senior-admin letter secured?
【Instrument & proprietary data】full instrument; verification/NDA plan ...
【Next step】car-data-analysis