majiayu000 AI Economist Skill
A unified tool for central bank policy analysis and real-time GDP nowcasting for the US and Canada.
Features
🏦 Policy Oracle (Taylor Rule Engine)
- Multi-Model Gap Estimation: Calculates output gaps using Okun's Law (Labor), HP Filter (Statistical), and Capacity Utilization (Industrial).
- Non-Linear Taylor Rule: Implements asymmetric central bank preferences for high inflation scenarios.
- Bayesian Inference: Provides statistical confidence intervals for the model-implied policy rates.
- Visual Analytics: Generates sensitivity charts showing policy rate requirements across different macro scenarios.
🚀 GDP Nowcast (GDPCastNow)
- Quant Bridge Model: Extracts latent macro factors using SVD/PCA from high-frequency indicators (Industrial Production, Retail Sales, Payrolls, etc.).
- AI Sentiment Correction: Scrapes news RSS feeds and official flash estimates (StatCan) to adjust quantitative forecasts with real-time sentiment.
- Official Integration: Direct scraping of StatCan "Daily" reports for the most recent economic outlooks.
Usage
1. Requirements
Ensure you have the dependencies installed:
pip install -r requirements.txt
2. Execution
Run the unified CLI entry point:
Analyze Policy Rates (Taylor Rule):
python main.py policy --country US
python main.py policy --country Canada
Run GDP Nowcast:
python main.py gdp --country US
python main.py gdp --country Canada
Configuration
The tool uses FRED (Federal Reserve Economic Data) for most macro indicators. An API key is required.
- Environment Variable:
FRED_API_KEY - Default: A fallback key is provided in the code but using your own is recommended.
Powered by Antigravity AI