macroforecast

Pandas-first macro forecasting workflow tools.

The current documentation is organized around the callable-first package structure. Start with the map below before opening individual API pages.

What To Check First

If you want to check…	Open first	Then open
Current package structure	Documentation Map	Workflow Contract, Public Python API
Package-wide defaults	Meta	Forecasting for runner policy usage.
Whether old runtime features are covered	Legacy Callable Coverage	Reference Verification
Data and preprocessing behavior	Data	FRED Datasets, Preprocessing
Paper replication settings	Replication	Reference Verification, Forecasting
Forecast runner behavior	Workflow Contract	Window, Forecasting
Models and parameter search	Models	Model Selection
Evaluation and tests	Evaluation	Metrics, Tests
Interpretation, output, and reporting	Interpretation	Output, Reporting

Main Sections

Section	Purpose
Documentation Map	One-page routing guide for what to inspect.
FRED Datasets	Dataset guide for FRED-MD, FRED-QD, FRED-SD, and combined loaders.
Replication	Paper-level reconstructed settings and notebook-style replication guides.
Reference	Current workflow reference pages grouped by package responsibility.
Legacy Callable Coverage	Migration audit from old runtime surfaces to current callable modules.
Reference Verification	Formula/reference anchors and verification-suite expansion rules.

• FRED Datasets
  • FRED-MD
  • FRED-QD
  • FRED-SD
  • FRED-MD + FRED-SD
  • FRED-QD + FRED-SD
  • Loader Boundary
  • Frequency Rule Of Thumb
  • Conversion Warnings
  • Dataset Docs Status
  • Official URLs
• Replication
  • Macroeconomic Data Transformations Matter
  • Macroeconomic Data Transformations Matter: Package-Only Notebook
• Reference
  • First Review Path
  • Workflow Groups
  • Orientation
  • Custom Hooks
  • Package Configuration
  • Data Pipeline
  • Feature Pipeline
  • Forecast Pipeline
  • Evaluation and Testing
  • Explanation and Delivery