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:
- Finance problem: the unresolved question in banking, intermediation,
markets, corporate finance, investments, or regulation.
- Friction or mechanism: information, agency, liquidity, risk, capital,
market power, regulation, search, or behavioral channel.
- Credible evidence or model: the design that lets the paper isolate the
mechanism.
- 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:
| Subfield |
What counts as the marginal contribution |
Framing trap |
| Bank capital / liquidity regulation |
Quantifying a Basel-style margin (CET1, LCR, NSFR) on lending or risk-taking with credible variation |
Restating "capital affects lending" without a new margin or mechanism |
| Credit risk / default modeling |
Out-of-sample gain over standard benchmarks plus an economic story for the gain |
Pure horse-race accuracy with no intermediation insight |
| Bank performance / financial stability |
A risk-taking or stability channel (Z-score, NPLs, tail risk) theory had not pinned down |
Cross-country correlations sold as causal stability lessons |
| Market microstructure / liquidity |
An institutional friction that changes measured liquidity or price discovery |
Generic asset-pricing result with banks as labels |
| Fintech / sustainable finance |
Evidence the new technology or ESG margin changes credit allocation or risk pricing |
Novelty of the setting standing in for a finance mechanism |
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
1---2name: jbf-contribution-framing3description: Use when sharpening the contribution claim for a Journal of Banking & Finance paper so the manuscript explains why the result matters for banking, financial intermediation, markets, regulation, or corporate finance.4---56# Contribution Framing (jbf-contribution-framing)78## When to trigger910- The result is statistically solid but the paper does not say why JBF readers should care11- The introduction sounds like a data exercise rather than a finance contribution12- You need a concise editor-facing pitch or cover-letter paragraph1314## Contribution formula1516A strong JBF contribution connects four elements:17181. **Finance problem**: the unresolved question in banking, intermediation,19 markets, corporate finance, investments, or regulation.202. **Friction or mechanism**: information, agency, liquidity, risk, capital,21 market power, regulation, search, or behavioral channel.223. **Credible evidence or model**: the design that lets the paper isolate the23 mechanism.244. **Implication**: how the result changes understanding of financial institutions,25 investors, firms, or policy.2627## Contribution types2829- **Mechanism contribution**: identifies how a finance friction operates.30- **Measurement contribution**: creates a better measure and proves it changes inference.31- **Policy contribution**: evaluates regulation or supervisory change with credible variation.32- **Institutional contribution**: reveals bank/intermediary behavior that theory had not pinned down.33- **Theory-to-evidence contribution**: connects a formal model to a newly tested implication.3435## Editor-facing paragraph3637```text38We study [finance question] using [setting/design]. The key challenge is39[identification or measurement problem]. We address it by [variation/data/model],40and find [headline result with magnitude]. The paper contributes to JBF by41showing [mechanism/implication] for [banking/intermediation/markets/regulation].42```4344## Anti-patterns4546- Claiming contribution only because the setting is new47- Listing three literatures but not saying what each learns48- Over-selling policy relevance when the design identifies only a local effect49- Burying the magnitude until late in the paper5051## Subfield framing ladder5253Match the pitch to the JBF subfield the referee will come from:5455| Subfield | What counts as the marginal contribution | Framing trap |56| --- | --- | --- |57| Bank capital / liquidity regulation | Quantifying a Basel-style margin (CET1, LCR, NSFR) on lending or risk-taking with credible variation | Restating "capital affects lending" without a new margin or mechanism |58| Credit risk / default modeling | Out-of-sample gain over standard benchmarks plus an economic story for the gain | Pure horse-race accuracy with no intermediation insight |59| Bank performance / financial stability | A risk-taking or stability channel (Z-score, NPLs, tail risk) theory had not pinned down | Cross-country correlations sold as causal stability lessons |60| Market microstructure / liquidity | An institutional friction that changes measured liquidity or price discovery | Generic asset-pricing result with banks as labels |61| Fintech / sustainable finance | Evidence the new technology or ESG margin changes credit allocation or risk pricing | Novelty of the setting standing in for a finance mechanism |6263## Worked framing pass (illustrative)6465Hypothetical draft: staggered state adoption of digital collateral registries and small-business lending, with DealScan-style loan-level data.6667- Raw pitch: "We use new registry data to study lending." That fails the stress test — it is data, not mechanism.68- 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."69- 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).7071## Referee pushback on contribution claims7273- "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.74- "The policy implication overreaches." → Bound it: identified for treated banks near the threshold, not for system-wide Basel calibration.75- "Why JBF rather than a policy outlet?" → Anchor in an intermediation friction and the literature delta, not the policy narrative alone.7677## Calibration anchor7879Accepted 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).8081## JBF contribution stress test8283Before submission, answer these in the introduction, not only in the cover letter:8485- Which financial decision-maker learns from the result: banks, borrowers, investors, regulators,86 boards, managers, intermediaries, or markets?87- What friction or institutional feature makes the result non-obvious?88- Which magnitude changes interpretation, and in what units?89- What competing finance explanation has been ruled out or bounded?90- Where does the result travel, and where does it not?9192If the answer is "we have better data," route back to `jbf-literature-positioning` and `jbf-data-analysis`.93Better data become a contribution only after they identify a finance mechanism or revise a known result.9495## Output format9697```text98[One-sentence contribution] ...99[Mechanism] ...100[Why JBF] ...101[Magnitude] ...102[Boundary conditions] ...103[Next step] jbf-writing-style104```
brycewang-stanford