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FARS: Factor Augmented Regression Scenarios in R

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  • Bellocca, Gian Pietro Enzo
  • Garrón Vedia, Ignacio
  • Rodríguez Caballero, Carlos Vladimir
  • Ruiz Ortega, Esther

Abstract

In the context of macroeconomic/financial time series, the FARS package provides a comprehensive framework in R for the construction of conditional densities of the variable of interest based on the factor-augmented quantile regressions (FA-QRs) methodology, with the factors extracted from multi-level dynamic factor models (ML-DFMs) with potential overlapping group-specific factors. Furthermore, the package also allows the construction of measures of risk as well as modeling and designing economic scenarios based on the conditional densities. In particular, the package enables users to: (i) extract global and group-specific factors using a flexible multi-level factor structure; (ii) compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings; (iii) obtain estimates of the parameters of the FA-QRs together with their standard deviations; (iv) recover full predictive conditional densities from estimated quantiles; (v) obtain risk measures based on extreme quantile

Suggested Citation

  • Bellocca, Gian Pietro Enzo & Garrón Vedia, Ignacio & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2025. "FARS: Factor Augmented Regression Scenarios in R," DES - Working Papers. Statistics and Econometrics. WS 48180, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:48180
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    References listed on IDEAS

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    1. Mevik, Björn-Helge & Wehrens, Ron, 2007. "The pls Package: Principal Component and Partial Least Squares Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 18(i02).
    2. Tomohiro Ando & Ruey S. Tsay, 2011. "Quantile regression models with factor‐augmented predictors and information criterion," Econometrics Journal, Royal Economic Society, vol. 14, pages 1-24, February.
    3. Rodríguez-Caballero, Carlos Vladimir & Caporin, Massimiliano, 2019. "A multilevel factor approach for the analysis of CDS commonality and risk contribution," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
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