About MacroLab
MacroLab makes the big picture clear.
Markets move on stories as much as statistics. News, filings, earnings calls, central-bank speeches, and other text streams shape expectations long before they fully settle into conventional macro releases. MacroLab is built to make those narrative shifts easier to read, trace, and use.
Rather than presenting another black-box score, MacroLab focuses on explainable macro signals: what appears to be moving, why it may be moving, and which underlying sources help explain the change.
Why MacroLab exists
Most macro workflows still force people into one of two bad choices. Either they absorb an overwhelming amount of text manually, or they rely on opaque indicators that hide the reasoning behind the output.
MacroLab sits between those extremes. It is designed for people who want a clearer view of the cycle without giving up traceability. The aim is not just to summarize the world, but to connect changing narratives to growth, inflation, uncertainty, and financial conditions in a way that can be inspected and challenged.
What MacroLab is
MacroLab is a platform for publishing and exploring macro research outputs from separate upstream projects. It brings together forecast dashboards, uncertainty series, and standalone research artifacts in a single interface.
It acts as:
- a distribution layer for macro forecasting and monitoring projects
- a research interface for exploring signals and supporting context
- a place to compare current views with historical series and published material
- a modular home for external artifacts that live outside the core application
MacroLab is not the modeling pipeline itself. The upstream research systems remain in their own projects. MacroLab is the layer where their outputs become legible, explorable, and shareable.
How it works
MacroLab is built around a simple separation of concerns.
Upstream projects process text streams and macro data in their own pipelines. MacroLab reads the resulting outputs and presents them in a consistent interface: current signals, historical context, supporting articles, uncertainty views, and published artifacts.
That separation matters. It keeps the research systems modular while making the user-facing experience more coherent. It also makes it easier to host more than one kind of macro project without forcing everything into a single product shape.
What you can explore
MacroLab is designed to support multiple project types rather than a single monolithic dashboard.
Forecast dashboards
Projects such as The Narrater surface current macro views, historical prediction context, and supporting material tied to business-cycle interpretation.
Uncertainty dashboards
Projects such as Components of Uncertainty make it easier to inspect topic-based measures of uncertainty and how they evolve over time.
Published artifacts
Some projects are better shipped as standalone web apps. MacroLab can host and organize those published artifacts while keeping them connected to the broader research environment.
What makes it different
- Explainability over mystery. MacroLab is built around interpretable signals, not presentation-only dashboards.
- Narrative-aware by design. It treats text as a first-class macro input rather than background color.
- Multi-project from the start. Forecasts, uncertainty tools, and independent artifacts can live side by side.
- Separation of concerns. Modeling pipelines stay in their own projects; MacroLab focuses on presentation, access, and feedback.
- Auditability as a product feature. Signals should be traceable back to supporting context, not detached from it.
Principles
MacroLab should feel rigorous, not theatrical. The product is strongest when it is clear about what it knows, what it is inferring, and what remains uncertain.
- Clarity: reduce complexity without hiding it
- Traceability: connect outputs back to underlying evidence
- Modularity: let different research projects plug into a common interface
- Restraint: avoid pretending to have more precision than the signal supports
- Feedback: treat user responses as inputs to future research rather than simple engagement metrics
Current status
MacroLab is an evolving research platform. Some parts are already usable as public-facing dashboards and artifacts, while other components remain in preview and are still being refined.
That status is intentional. The goal is to ship real interfaces early, learn from how they are used, and improve them as the surrounding research matures.
Why this matters
Macro analysis does not happen in spreadsheets alone. It happens in language, interpretation, disagreement, and changing expectations. A useful macro platform should reflect that reality.
MacroLab is an effort to make macro research more legible, more explainable, and easier to explore. If you want to understand not just what the signal says, but why it says it, this is the right place to start.