# Jeg Identification Strategy > Use when the inferential backbone of a Journal of Economic Growth (JEG) manuscript needs stress-testing — empirical papers via causal/econometric identification for growth, theory papers via assumptions, results, proof exposition, and generality. Forks by paper type, as a specialist growth and dynamic-macroeconomics outlet requires. - Skill: `thedixitjain/jeg-identification-strategy` (Agent Skill) - Install (CLI): `npx skillmds add thedixitjain/jeg-identification-strategy` - Raw SKILL.md: https://api.skillmd.com/api/skills/thedixitjain/jeg-identification-strategy/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: thedixitjain (https://skillmd.com/u/thedixitjain) - Updated: 2026-09-08 - Page: https://skillmd.com/skills/thedixitjain/jeg-identification-strategy --- # Identification & Argument Strategy (jeg-identification-strategy) ## When to trigger - An empirical growth claim rests on a cross-country regression with endogenous regressors - A theoretical result depends on an assumption you have not justified or tested for tightness - You are unsure whether your inferential backbone clears a growth-specialist bar JEG publishes both theory and empirics, so this skill has **two tracks**. Pick the one matching your paper; quantitative/calibrated papers use both. ## Track E — Empirical identification (causal design for growth) Growth empirics carry a hard endogeneity problem: most candidate determinants (institutions, human capital, finance, openness) are co-determined with income. The bar: ### Cross-country / dynamic-panel growth - If you run growth-on-determinant regressions, confront **reverse causality and omitted deep determinants** explicitly. A bare OLS or static panel will not convince. - Dynamic-panel **system GMM** (Arellano-Bond / Blundell-Bond) is common, but it is a trap if abused: **cap and report the instrument count**, report the **Hansen-J** over-identification test and **AR(2)** serial-correlation test, and show results are not driven by instrument proliferation. - Convergence claims: distinguish β- from σ-convergence and address Galton's-fallacy / measurement-error critiques. ### Clean causal shock (where one exists) - Where a credibly exogenous shock to a growth determinant exists, use a sharp design: **IV** (strong first stage, defended exclusion restriction in theory + institutions + falsification), **DID/event study** (modern estimators, not naive TWFE on staggered timing; pre-trends), or **RDD** (density and bandwidth diagnostics). - Few-country / few-cluster inference: use wild-cluster bootstrap or randomization inference; do not lean on asymptotic t-stats with a handful of clusters. - State the estimand (ATT / LATE / local effect) and its external validity for the growth question. ## Track T — Theoretical argument (assumptions, results, generality) For a theory paper the "identification" object is the **logical structure**, not a research design. - **Assumptions**: list them explicitly; mark which are substantive (drive the result) vs technical (for tractability). Justify each economically and flag knife-edge conditions. - **Results**: state propositions/theorems precisely with their hypotheses; give existence, uniqueness, and stability of the relevant steady state or balanced-growth path, and check transversality. - **Proof exposition**: put intuition in the text and full proofs in an appendix; make each step auditable. A growth-theory referee will reproduce the algebra. - **Generality**: show how far the result reaches — which assumptions can be relaxed, what breaks if you do, and which comparative statics / testable predictions survive. Generality is the contribution's reach. ## Execution bridge (StatsPAI / Stata MCP) Estimate and audit the design, don't only describe it. Full map: [`execution-with-mcp`](../../../shared-resources/empirical-methods/execution-with-mcp.md). JEG (growth) uses cross-country and long-run panels with deep endogeneity; foreground identification and robustness to alternatives. - `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 control. - **Sensitivity:** `oster_delta` / `sensemakr` for observational claims. Report the magnitude in interpretable units; route the full battery to the appendix. A run end-to-end (synthetic data, real returns) is in the [JF execution walkthrough](../../../Journal-of-Finance-Skills/resources/worked-examples/02-execution-walkthrough.md). ## Anti-patterns - (E) System GMM with hundreds of instruments and no Hansen-J / AR(2) reported. - (E) Naive TWFE on staggered growth-policy timing; OLS cross-country causal claims with no design. - (T) A "general" theorem that silently depends on a knife-edge parameter restriction. - (T) Proofs that assert rather than derive existence/uniqueness/stability. - Either track claiming more than the argument supports. ## Persistence-design defenses (Track E extension) Historical-persistence and deep-determinants papers face a now-standard referee script at this journal; pre-empt all four lines before submission: - **Spatial autocorrelation**: report Conley standard errors at several distance cutoffs alongside clustered SEs, and show the headline estimate survives the widest defensible cutoff. - **Spurious spatial fit**: run placebo treatments drawn from spatially correlated noise and report where the true coefficient falls in that placebo distribution. - **Overused instruments**: if your instrument (terrain, climate, disease ecology, a historical shock) has already served other outcomes in print, defend exclusion against *each* published channel it explains — not in the abstract. - **Mechanism opacity**: a reduced-form persistence coefficient is a starting fact, not an answer; bring intermediate-period outcomes or a decomposition that traces how the past reaches the present. A persistence paper that clears only the first two is an economic-history note; clearing all four is what makes it a growth paper. ## Output format ``` 【Track】E (empirical) / T (theory) / both 【E: design】GMM-panel / IV / DID / RDD + key diagnostics (Hansen-J, AR(2), first-stage F, pre-trends) 【E: inference】clustering / few-country handling; estimand + external validity 【T: assumptions】substantive vs technical; knife-edge flags 【T: results】existence / uniqueness / stability / transversality checked? 【T: generality】what can be relaxed; surviving predictions 【Next skill】jeg-data-analysis ``` --- **Source:** [`brycewang-stanford/Awesome-Journal-Skills`](https://github.com/brycewang-stanford/Awesome-Journal-Skills) → `Journal-of-Economic-Growth-Skills/skills/jeg-identification-strategy/SKILL.md`