Contribution Framing (jbf-contribution-framing)

When to trigger

• The result is statistically solid but the paper does not say why JBF readers should care
• The introduction sounds like a data exercise rather than a finance contribution
• You need a concise editor-facing pitch or cover-letter paragraph

Contribution formula

A strong JBF contribution connects four elements:

1. Finance problem: the unresolved question in banking, intermediation,

markets, corporate finance, investments, or regulation.

1. Friction or mechanism: information, agency, liquidity, risk, capital,

market power, regulation, search, or behavioral channel.

1. Credible evidence or model: the design that lets the paper isolate the

mechanism.

1. Implication: how the result changes understanding of financial institutions,

investors, firms, or policy.

Contribution types

• Mechanism contribution: identifies how a finance friction operates.
• Measurement contribution: creates a better measure and proves it changes inference.
• Policy contribution: evaluates regulation or supervisory change with credible variation.
• Institutional contribution: reveals bank/intermediary behavior that theory had not pinned down.
• Theory-to-evidence contribution: connects a formal model to a newly tested implication.

Editor-facing paragraph

We study [finance question] using [setting/design]. The key challenge is
[identification or measurement problem]. We address it by [variation/data/model],
and find [headline result with magnitude]. The paper contributes to JBF by
showing [mechanism/implication] for [banking/intermediation/markets/regulation].

Anti-patterns

• Claiming contribution only because the setting is new
• Listing three literatures but not saying what each learns
• Over-selling policy relevance when the design identifies only a local effect
• Burying the magnitude until late in the paper

Subfield framing ladder

Match the pitch to the JBF subfield the referee will come from:

Worked framing pass (illustrative)

Hypothetical draft: staggered state adoption of digital collateral registries and small-business lending, with DealScan-style loan-level data.

• Raw pitch: "We use new registry data to study lending." That fails the stress test — it is data, not mechanism.
• Reframed: "Collateral frictions limit small-business credit; registry adoption cuts verification costs. Spreads on affected loans fall by an illustrative 18 basis points (about 7% of the sample-mean spread) and the collateralized share rises 5 percentage points, with no movement for large syndicated borrowers."
• The JBF hook: a collateral-information mechanism in intermediation, a magnitude in basis points, and a boundary condition (no effect where information frictions were already low).

Referee pushback on contribution claims

• "This is a known result in a new country." → Name the institutional feature (deposit-insurance design, supervisory regime, creditor rights) that changes the prediction, or reroute.
• "The policy implication overreaches." → Bound it: identified for treated banks near the threshold, not for system-wide Basel calibration.
• "Why JBF rather than a policy outlet?" → Anchor in an intermediation friction and the literature delta, not the policy narrative alone.

Calibration anchor

Accepted JBF empirical papers typically state the question, design, headline magnitude, and contribution within the first two pages, with one paragraph per literature delta (a stylized pattern, not a journal rule).

JBF contribution stress test

Before submission, answer these in the introduction, not only in the cover letter:

• Which financial decision-maker learns from the result: banks, borrowers, investors, regulators,

boards, managers, intermediaries, or markets?

• What friction or institutional feature makes the result non-obvious?
• Which magnitude changes interpretation, and in what units?
• What competing finance explanation has been ruled out or bounded?
• Where does the result travel, and where does it not?

If the answer is "we have better data," route back to jbf-literature-positioning and jbf-data-analysis. Better data become a contribution only after they identify a finance mechanism or revise a known result.

Output format

[One-sentence contribution] ...
[Mechanism] ...
[Why JBF] ...
[Magnitude] ...
[Boundary conditions] ...
[Next step] jbf-writing-style