Advanced Analytics
Deep-dive correlation analysis and economic shock transmission networks
Basis
Annual observations
Method
Pearson correlation (r)
Sources
World Bank WDI · IMF WEO
Refresh Cycle
Nightly ingest, cached 1h
Indicator Correlation Matrix
Pearson correlation analysis showing relationships between key economic indicators. Positive correlations (green) indicate variables move together; negative (red) indicates inverse movements. Pairs without enough overlapping years are shown as "—".
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Economic Shock Transmission Network
Scenario model showing how external and domestic shocks would propagate through sectors to economic outcomes. Flow width represents estimated impact magnitude.
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Use Cases
Policy Maker Use
Identify which events create strongest economic impacts through specific sectors, enabling targeted policy interventions.
Risk Manager Use
Understand correlation structure for portfolio diversification and hedge strategy design. Anticipate second-order effects.
Economist Use
Validate theoretical models against empirical correlation patterns and shock transmission magnitudes.
Technical Details
Correlation Matrix Methodology:
- Method: Pearson correlation coefficient (r)
- Basis: annual observations, pairs aligned on shared years
- Data Source: World Bank WDI + IMF WEO (Bangladesh, actuals only)
- Excluded: IMF projection years, and pairs with fewer than 8 shared years
- Caching: 1-hour TTL
Sankey Transmission Network:
- Type: editorial scenario model, not measured telemetry
- Structure: economic events → sector channels → economic outcomes
- Weights: analyst elasticity estimates on a 0-100 scale
- Use: relative comparison of transmission channels, not forecasting
AI Economic Analysis
GeminiAsk Gemini to analyze correlations, identify transmission channels, or generate policy insights.
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