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README.md
In FARS: Factor-Augmented Regression Scenarios
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:
- (i) Extract global and block-specific factors using a flexible multilevel factor structure.
- (ii) Compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings.
- (iii) Estimate factor-augmented quantile regressions.
- (iv) Recover full predictive densities from these quantile forecasts.
- (v) 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
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FARS documentation built on Aug. 8, 2025, 7:33 p.m.
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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:
- (i) Extract global and block-specific factors using a flexible multilevel factor structure.
- (ii) Compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings.
- (iii) Estimate factor-augmented quantile regressions.
- (iv) Recover full predictive densities from these quantile forecasts.
- (v) 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
Try the FARS package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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