Jde Identification Strategy

---
name: jde-identification-strategy
description: Use when the causal identification strategy is the bottleneck for a Journal of Development Economics (JDE) manuscript — RCT/field experiment, DID, IV, RDD in low- and middle-income settings. Stress-tests the design against development-economics empirical norms before tables are drafted.
---

# Identification Strategy (jde-identification-strategy)

## When to trigger

- The empirical core is OLS + controls with an undefended causal claim
- A DID uses two-way fixed effects (TWFE) on staggered timing without modern estimators
- An IV's first stage is weak or the exclusion restriction is unargued
- An RCT lacks a pre-analysis plan, balance, or attrition analysis
- You are unsure your design clears the JDE causal bar

## The JDE identification bar

Development economics has been a leader in the **credibility revolution**, and JDE referees apply a demanding identification standard while respecting that field settings are messy. The implicit credibility ranking (strong → weaker):

1. **RCT / field experiment** with a registered pre-analysis plan, balance, and attrition handling — the modal credible design in modern development micro
2. **Sharp/fuzzy RDD** at a clean program or eligibility threshold (common in targeted transfer and education programs)
3. **DID / event study** off a credibly exogenous policy or shock, using modern estimators
4. **IV** with a strong first stage and a defended, institutionally-grounded exclusion restriction
5. **Selection-on-observables / matching** — acceptable only as a complement, rarely the spine

A **theoretical** paper is judged on the development relevance and rigor of its mechanism, not on a research design. A paper with **novel, hard-to-assemble data** answering a first-order development question can carry reduced-form evidence — but the question and the data discipline must be exceptional.

JDE also runs a permanent **pre-results review / Registered Reports** track: a prospective design (hypotheses, procedures, statistical analysis plan, **power analysis**, pilot data if applicable) can be reviewed and accepted in principle *before* results exist. If your design is prospective, build it to that standard — it both strengthens identification and unlocks that route (see jde-review-process).

## Branch paths

### RCT / field experiment (the development workhorse)
- Pre-registered PAP (AEA RCT Registry / OSF); report deviations honestly.
- **Power / MDE** justified at the level of randomization; clustered designs need cluster-level power.
- Balance table; attrition analysis with **Lee bounds** if differential.
- **Inference at the unit of randomization** (cluster); few clusters → wild-cluster bootstrap or randomization inference.
- Multiple-hypothesis adjustment across outcomes/subgroups (Romano–Wolf / Westfall–Young).
- External validity: what does this population and context teach beyond the site?

### DID / event study
- Staggered adoption → move beyond TWFE (Callaway–Sant'Anna, Sun–Abraham, de Chaisemartin–D'Haultfœuille); report a Goodman-Bacon decomposition.
- Clean event-study plot with leads; pre-period coefficients near zero.

### IV
- Strong first-stage F; with weak instruments use Anderson–Rubin / weak-IV-robust sets.
- Exclusion argued in three registers: theory, institutional detail, falsification.
- Report reduced form and OLS alongside; discuss the LATE/complier interpretation.

### RDD
- McCrary / Cattaneo–Jansson–Ma density test for manipulation at the cutoff.
- Optimal bandwidth (Calonico–Cattaneo–Titiunik) plus bandwidth robustness; bias-corrected CIs.
- Covariate smoothness and placebo cutoffs.

## Anti-patterns

- TWFE on staggered treatment with no discussion of heterogeneity bias
- An RCT with no PAP, no power calculation, and unexamined differential attrition
- Inference not clustered at the randomization level
- Overclaiming a single-site LATE as a universal development parameter

## Output format

```
【Design】RCT / RDD / DID / IV / theory / descriptive
【Identifying variation】one sentence
【Diagnostics done】[PAP, balance, attrition/Lee bounds, density, first-stage F, pre-trends, ...]
【Diagnostics missing】[...]
【Inference】clustering level + few-cluster handling + MHT
【Interpretation】LATE / ATE / external validity note
【Pre-results route?】[Y/N]
【Next step】jde-data-analysis
```