Building a Practical Macro Regime Research Lab with FRED

Most macroeconomic analysis lives at one of two extremes:

• High-level commentary that’s hard to test or operationalize
• Academic or institutional research that’s powerful, but opaque and inaccessible

This project sits somewhere in the middle.

I wanted a clear, repeatable, and modular way to explore macroeconomic regimes using publicly available FRED data — something that supports learning, experimentation, and practical monitoring without pretending to predict the economy.

That’s what this repository is. Here’s a link to GitHub.

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What This Project Is

This repo is a macro research lab built on FRED data, organized as a progression of notebooks and a small reusable Python core.

At a high level, it answers questions like:

• How do growth, inflation, and policy interact over time?
• How can we classify macro “regimes” in a transparent way?
• What do key indicators tend to do around regime transitions?
• How can this analysis be turned into something practical and monitorable?

The goal is not forecasting perfection — it’s structure, clarity, and reuse.

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How the Project Is Structured

Modular Core (macro_utils)

All reusable logic lives in a small utility layer:

• Transformations (YoY, MoM, z-scores)
• Regime classification (growth, inflation, policy)
• Event studies (pre/post windows around transitions)
• Plotting helpers and exports

This keeps notebooks readable and prevents copy-paste sprawl.

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Notebook Progression

The notebooks are intentionally sequential:

• Notebook 01 – FRED Quickstart
  Pulling and organizing raw macro data
• Notebook 02 – Transformations That Matter
  YoY, MoM, normalization, and why levels vs changes matter
• Notebook 03 – Macro Relationships
  Correlations, lead/lag behavior, and basic exploratory analysis
• Notebook 04 – Regimes & Signals
  Classifying growth, inflation, and policy regimes
• Notebook 05 – Research Templates
  Reusable analytical patterns (rolling stats, conditionals, summaries)
• Notebook 06v1 – Macro Research Dashboard
  A first integrated view of regimes, distributions, and event studies
• Notebook 06v2 – Fully Built Macro Research Pipeline
  A comprehensive, end-to-end research workflow
• Notebook 07 – Regime Transitions & Practical Monitoring
  Transition detection, pre/post analysis, and lightweight monitoring outputs

If you only look at two notebooks, 06v2 and 07 are the culmination.

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What This Is Not

This project is deliberately not:

• A trading system
• A forecasting engine
• A claim that regimes are “true” or optimal

Instead, it’s a research scaffold — something you can build on, critique, or adapt to your own framework.

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Why I Built This

I wanted:

• A way to think clearly about macro regimes
• A repeatable research workflow instead of one-off charts
• A clean separation between data, logic, and analysis
• Something I could extend later (dashboards, alerts, alternative regime definitions)

This repo reflects how I actually explore macro questions — not how I’d present them in a polished report.

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What’s Next

This project is intentionally scoped as Part I.

A future Part II may explore:

• Alternative regime definitions
• Bayesian or probabilistic framing
• Dashboard integrations
• Live updates and monitoring
• Deeper links between macro regimes and asset behavior

For now, this repo stands as a complete, working macro research lab.