FARS: Factor Augmented Regression Scenarios in R

Gian Pietro Enzo Bellocca, Ignacio Garrón Vedia, Carlos Rodriguez Caballero and Esther Ruiz Ortega

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: In the context of macroeconomic/financial time series, the FARS package provides a framework in R for the construction of conditional densities of the variable of interest based on the factor-augmented quantile regressions (FA-QRs) methodology. Within this context, the factors used to estimate the quantiles are extracted from a multi-level dynamic factor model with potential overlapping group-specific factors, while the densities are obtained by matching the estimated quantiles to a Skewed-Student density. The package also allows the construction of measures of risk as well as designing economic scenarios for the conditional densities. In particular, the package enables users to: (i) extract global and group-specific factors using a flexible multi-level factor structure and compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings; (ii) obtain estimates of the parameters of the FA-QRs together with their standard deviations, and recover full predictive conditional densities from estimated quantiles; (iii) obtain risk measures based on extreme quantiles of the conditional densities; and (iv) estimate the conditional density and the corresponding extreme quantiles when the factors are stressed.

Keywords: Multilevel; factor; model; Stressed; factors; Scenario; analysis; R (search for similar items in EconPapers)
Date: 2025-10-13
New Economics Papers: this item is included in nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://e-archivo.uc3m.es/rest/api/core/bitstreams ... ae66b330ec10/content (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:48180

Access Statistics for this paper

More papers in DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística
Bibliographic data for series maintained by Ana Poveda ().