QE publishes papers that apply quantitative methods to substantive economic questions, so the contribution should be framed as a quantitative answer, not as machinery. A QE-fit contribution sentence names three things: the question, the quantity you deliver (an estimate, a counterfactual, a welfare number, a measured fact), and the lesson that travels beyond the setting. Frame against the Econometric Society lens: if the only honest framing is "we propose a new estimator," the paper belongs at Econometrica; QE wants "using [method], we answer [question] and find [quantity], which implies [lesson]."
Match the framing to the paper type:
State plainly what the result does establish (the estimand, the population, the assumptions) and what it does not (external validity limits, identifying assumptions that could fail, computational approximations). Because QE forbids significance asterisks and asks for standard errors and coverage sets, frame the contribution with its uncertainty attached, not as a point claim.
The general-interest Econometric Society readership wants the payoff, not the plumbing. Grade a candidate contribution sentence against this table.
| Framing pattern | Coeditor reading | Verdict at QE |
|---|---|---|
| "We estimate [parameter] and find a welfare gain of [number]" | quantity-first, answer travels | strong fit |
| "We measure [object] previously assumed, getting [magnitude, s.e.]" | a fact the field lacked | strong fit |
| "We propose a new [estimator]" with a toy application | machinery, not an answer | Econometrica lane |
The most common desk-reject framing is the method-as-contribution sentence: a computational or inference device with no economic quantity attached. Re-anchor it on the number the method delivers.
A paper estimates a dynamic model of retirement timing and evaluates raising the early-claiming age. Machinery-first framing: "We solve a dynamic program with a nested fixed-point estimator." A QE-fit rewrite names question + quantity + lesson: "Raising the early eligibility age by two years cuts early claiming by 14 percentage points (s.e. 3) and raises lifetime benefits 6% on average, but the gains are regressive — a margin reduced-form work leaves unquantified." (Numbers illustrative.) The rewrite carries uncertainty, states the policy quantity, and flags the distributional lesson; the estimator becomes a credibility footnote, not the headline.
【One-sentence contribution】question + quantity + lesson
【Quantity type】estimate / counterfactual / welfare / measured fact (+ uncertainty)
【Scope — establishes】estimand / population / assumptions
【Scope — does NOT establish】[...]
【QE fit】answer-first, not method-first? [Y/N]
【Next step】qe-identification-strategy