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.

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