E0230: Productivity Dispersion Map Framework
A decision-ready template derived from the framework.
Name variants
- English
- E0230: Productivity Dispersion Map Framework
- Katakana
- マップフレームワーク
- Kanji
- 生産性分散
Quality / Updated / Source / COI
- Quality
- Reviewed
- Updated
- Source
- Citations & Trust
- COI
- none
Context
Context: choosing productivity policy mix often exposes disagreements about TFP growth, firm dispersion, and capital deepening and the reliability of R and D intensity, diffusion lags, and infrastructure. Without a shared frame, the frontier focus vs diffusion remains implicit and accountability erodes across reviews. A structured record is needed to keep decisions consistent as market conditions change.
Options
- Option A: Keep the current approach to minimize disruption while accepting limited improvement.
- Option B: Pilot a phased change, validate against agreed metrics, and scale once thresholds are met.
- Option C: Redesign the approach end to end to pursue larger gains with higher execution risk.
Decision
Decision: Choose Option B. Validate TFP growth, firm dispersion, and capital deepening early, confirm R and D intensity, diffusion lags, and infrastructure assumptions, and pause if the frontier focus vs diffusion no longer holds. Document owners, constraints, and review dates.
Rationale
Rationale: Option B balances frontier focus vs diffusion while preserving flexibility. It tests whether TFP growth, firm dispersion, and capital deepening respond as expected to changes in R and D intensity, diffusion lags, and infrastructure before committing to a full rollout. This reduces the risk of locking in a costly path based on weak evidence and improves governance confidence.
Risks
- Weak data quality can hide shifts in TFP growth, firm dispersion, and capital deepening and delay corrective action.
- Slow execution can magnify the downside of frontier focus vs diffusion and reduce credibility in reviews.
Next
Next: Assign owners for TFP growth, firm dispersion, and capital deepening and R and D intensity, diffusion lags, and infrastructure, finalize baseline values, and publish the trigger thresholds. Schedule the first review checkpoint and define stop conditions so the decision can be revised quickly.