Individual skill
jmcb-empirical-design
Use when bank/central-bank data construction, measurement, or sample design is the bottleneck for a Journal of Money, Credit and Banking (JMCB) manuscript. Hardens how the dataset is built and measured so the identification can do its job; it does not re-argue the causal strategy or write prose.
Journal-of-Money-Credit-and-Banking-Skills/skills/jmcb-empirical-design/SKILL.md
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- design Derived category
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# Empirical Design (jmcb-empirical-design)
## When to trigger
- The dataset is assembled from Call Reports, Y-9C, supervisory, credit-register, or central-bank sources and the construction is under-documented
- The key variable (a "monetary shock," a "bank capital ratio," a "credit-supply" measure) is a constructed object whose definition matters for the result
- Sample period, window, or frequency choices are not motivated and could be driving the finding
- Restricted-access bank/central-bank data are involved and the access path is unstated
- A referee questioned whether the measurement, not the mechanism, produces the result
## The JMCB measurement bar
JMCB carries a deep replication heritage — the journal's own 1980s–2000s Data Archive episodes (Dewald–Thursby–Anderson; the 2006 "Got Replicability?" audit) made it acutely aware that monetary/banking results often hinge on how series are spliced, deflated, and aligned. So referees scrutinize **construction and timing**: how a series is seasonally adjusted, how regulatory definitions changed mid-sample, how a bank merger reshapes a panel, and whether the announcement window for a monetary surprise is defensible. The standard is that a reader could rebuild the central variables from the description.
