Accounting treatments — disclosure choices, conservatism, auditor selection, tax positions, standard adoption — are rarely random, so RAST referees expect a credible identification strategy, not kitchen-sink controls. Pick the design that breaks the endogeneity for your accounting setting.
| Identification threat / setting | Design |
|---|---|
| Regulation / standard adoption with a clean date (e.g., a reporting mandate) | Difference-in-differences; event study around the adoption date |
| Staggered adoption across firms/states/countries | Staggered DiD with modern estimators (avoid naive TWFE bias) |
| Endogenous accounting/auditor/tax choice | Instrumental variables / 2SLS with a defensible exclusion |
| A threshold rule (covenant, index inclusion, size or regulatory cutoff) | Regression discontinuity |
| Selection on observables | Matching (PSM/entropy) as a complement, not the main claim |
| A plausibly exogenous shock to the information environment | Natural experiment; pre-trends shown |
| Information content of an accounting signal | Short-window event study with a clean benchmark and confound check |
State the estimating equation, the unit and level, the fixed effects (firm, year, industry-year), and the identifying variation explicitly. The design section must make a skeptic believe the variation is as-good-as-random conditional on controls. RAST's first-round-decision culture means a weak design is more likely to draw a reject than a "fix it in revision."
For contested accounting constructs (discretionary accruals, earnings quality, disclosure indices, audit quality, information asymmetry), the proxy choice is a design decision. Pre-commit a primary measure with precedent and plan the alternative proxies you will use to show the result is not proxy-driven (carried out in revacc-data-analysis). A clean design on a fragile proxy still fails.
For the empirical / causal lane, estimate and audit rather than only specify. Full
map: execution-with-mcp. RAST is empirical accounting; emphasize identification of disclosure / governance effects and the multiple-testing haircut for mined associations.
detect_design → recommend → fit with as_handle=true → audit_result to
enumerate the checks the design owes.callaway_santanna / sun_abraham + bacon_decomposition
honest_did_from_result. IV: effective_f_test + anderson_rubin_ci. RDD:
rdrobust + mccrary_test.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.
【Lane】archival / analytical / experimental
【Setting & identifying variation】...
【Design】DiD / staggered-DiD / IV / RDD / event study / experiment / model
【Spec】equation; unit/level; fixed effects; clustering plan
【Construct】primary proxy + alternatives planned
【Identification defense】pre-trends / exclusion / discontinuity / randomization ...
【Data provenance】sources + vintages + screens noted
【Next skill】revacc-data-analysis