jpe-identification

Identification & Economic Interpretation (jpe-identification)

When to trigger

• The empirical core is OLS + controls with no defended causal claim
• Staggered DID estimated with TWFE without addressing heterogeneity-bias critiques
• IV with a weak first stage or a thin exclusion argument
• Structural estimation where the source of parameter identification is not spelled out
• A clean causal effect exists but its economic interpretation is not pinned down

The JPE bar: credible identification AND economic meaning

JPE accepts both reduced-form and structural work, but the bar has two parts that must both clear:

1. Credible identification — the estimate isolates the causal/structural object you claim.
2. Economic interpretation — the estimate maps onto a parameter or margin that economic theory cares about. A credibly identified effect with no economic meaning is a half-paper here.

Reduced-form work should connect to a model or mechanism (see jpe-theory-model); structural work must make its identification transparent. Atheoretical correlation mining is the classic JPE desk-reject signal — and at JPE the desk screen is a co-editor (Chicago-centered board led by Esteban Rossi-Hansberg) and the submission fee is non-refundable, so an undisciplined design is a costly miss. JPE's price-theory heritage (e.g., Becker's "Crime and Punishment," JPE 1968) means the economic mechanism behind a clean estimate matters as much as the estimate. If the contribution is a deep quantitative-macro identification, consider whether JPE Macroeconomics is the better venue than the flagship.

Design priority (strong → acceptable)

The right design is dictated by the economics, not by fashion. As a rough ordering of what travels well at JPE:

1. Structural estimation tied to a model — when the question is about a deep parameter, welfare, or counterfactuals; identification of parameters argued explicitly.
2. Quasi-experiment (DID, RDD, event study) that maps to a model prediction — reduced form whose coefficient has a stated economic interpretation.
3. Strong IV with a theory-grounded exclusion restriction — first-stage strength plus an economic story for exogeneity and exclusion.
4. RCT / lab evidence interpreted through a mechanism.
5. OLS with a serious endogeneity discussion — acceptable in theory-empirics or descriptive-with-model papers, not as the sole causal claim.

Branch paths

Branch A — DID / event study

• Staggered timing? Diagnose negative-weighting with Goodman-Bacon; estimate with a heterogeneity-robust estimator (Callaway–Sant'Anna, Sun–Abraham, de Chaisemartin–D'Haultfœuille, or Borusyak–Jaravel–Spiess).
• Pre-trends: show the event-study plot; do not lean only on a joint pre-trend test (low power) — argue economically why pre-trends are flat.
• Map the coefficient to a model object: what does the ATT mean economically?
• Placebo: randomize treatment timing/units; report the distribution.

Branch B — IV

• First-stage strength: report effective F (Montiel Olea–Pflueger); if weak, use Anderson–Rubin / weak-IV-robust CIs.
• Exclusion: defend in three registers — theory, institutional detail, and a placebo/over-identification check.
• Report the reduced form, not just 2SLS.
• State the LATE interpretation: whose behavior does the instrument move, and is that the population the economics is about?

Branch C — RDD

• McCrary / rddensity manipulation test.
• Optimal bandwidth (Calonico–Cattaneo–Titiunik) plus ≥3 bandwidth-robustness checks; bias-corrected CIs.
• Covariate smoothness at the cutoff; placebo cutoffs.

Branch D — Structural estimation

• State the model's microfoundations and the moments/variation that identify each parameter (a "what identifies what" paragraph is expected).
• External validation: do estimated parameters match independent evidence or untargeted moments?
• Provide counterfactuals and welfare, and show sensitivity to key assumptions.

Checklist

• Identifying assumption stated in one sentence and defended economically
• Design-appropriate diagnostics done (pre-trends / first-stage F / manipulation test / parameter identification)
• Placebo or falsification test reported
• Standard errors clustered at the level of treatment assignment, justified
• The estimated object is given an explicit economic interpretation
• Reduced-form work connects to a model or mechanism; structural work makes identification transparent
• Selection / general-equilibrium threats to interpretation acknowledged

Anti-patterns

• TWFE on staggered treatment with no discussion of heterogeneity bias
• A precisely identified effect with no statement of what it means for economics
• IV exclusion asserted ("we argue the instrument is exogenous") without evidence
• Structural estimates with no "what identifies what" discussion — the model becomes a black box
• Clustering at the wrong level to manufacture significance
• Ignoring that the partial effect may be offset in general equilibrium

Output format

【Design】structural / DID / IV / RDD / event study / other
【Identifying assumption】one sentence
【Economic interpretation of the estimate】...
【Diagnostics done】[pre-trends, first-stage F, manipulation, param-ID, ...]
【Diagnostics missing】[...]
【Clustering level】... (justification)
【GE / selection caveats】...
【Next】jpe-theory-model (if mechanism not yet formalized) or jpe-robustness