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FARS - Factor-Augmented Regression Scenarios

The FARS package provides a comprehensive framework in R for modeling and forecasting economic scenarios based on the multi-level dynamic factor model (MLDFM). The package enables users to:

• 1. Extract global and block-specific factors using a flexible multilevel factor structure.
• 2. Compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings.
• 3. Estimate factor-augmented quantile regressions.
• 4. Recover full predictive densities from these quantile forecasts.
• 22. Estimate the density when the factors are stressed.

Installation and Usage

For detailed usage and examples, including stress testing, quantile regression, and more, please refer to the FARS Vignette. The Vignette example is based on: González-Rivera, G., Rodríguez-Caballero, C. V., & Ruiz, E. (2024). Expecting the unexpected: Stressed scenarios for economic growth. Journal of Applied Econometrics, 39(5), 926–942. https://doi.org/10.1002/jae.3060

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.