Robust filtering with quantile regression

João Borges Assunção; Pedro Afonso Fernandes

Robust filtering with quantile regression

Research output: Working paper

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Abstract

This working paper proposes a new, practical method to compute the non-linear Mosheiov-Raveh (MR) filter using least absolute deviations (LAD) instead of the linear programming approach proposed by these two authors. This paper is embodied with an implementation in the R programming language of the proposed method which facilitates the computation of the MR filter in current applications to produce a robust estimate, namely, of the GDP trend growth. This technique may be appropriate to deal with non linear time series or structural changes.

Original language	English
Number of pages	17
Publication status	Published - 21 Feb 2022

Keywords

Business cycles
Non linear time series
Robust filtering
Software

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47725977Final published version, 379 KBLicence: Unspecified

http://hdl.handle.net/10400.14/38332Licence: Unspecified

CUBE: Católica Lisbon Research Unit in Business and Economics
Machado, F. (PI), Aranda, A. M. (Researcher), Costa, A. I. D. A. (Researcher), Martins, A. P. (Researcher), Bernard, A. (Researcher), Fidalgo, A. (Researcher), Reis, C. (Researcher), Abecassis-Moedas, C. (Researcher), Santos, C. (Researcher), Tran, D. (Researcher), Fernandes, D. (Researcher), Bonfim, D. (Researcher), Schliephake, E. (Researcher), Kalogirou, F. (Researcher), Reis, F. (Researcher), Santos, F. (Researcher), Machado, F. (Researcher), Sguera, F. (Researcher), Cerqueiro, G. (Researcher), Reis, H. (Researcher), Barreto, I. (Researcher), Silva, J. (Researcher), Salvado, J. C. (Researcher), Neves, J. C. D. (Researcher), Gijsbrechts, J. (Researcher), Stahl, J. (Researcher), Guedes, J. C. (Researcher), Faias, J. (Researcher), Wagner, L. (Researcher), Correia, I. (Researcher), Saldanha, M. F. (Researcher), Fontes, J. C. (Researcher), Modesto, L. (Researcher), Meira, M. (Researcher), Matos, M. G. D. (Researcher), Gouveia, M. (Researcher), Kozeniauskas, N. (Researcher), Bertani, N. (Researcher), Couzoff, P. (Researcher), Barroso, P. (Researcher), Encarnação, P. (Researcher), Raposo, P. (Researcher), Teles, P. (Researcher), Bastos, W. (Researcher), Bohnsack, R. (Researcher), Vale, R. C. D. (Researcher), Ferreira, R. (Researcher), Lloyd-Braga, T. (Researcher), Ramus, T. (Researcher), Colaço, V. H. (Researcher), Cavicchini, A. (Researcher), Parada, P. (Researcher), Pieters, R. (Researcher), Pinto, F. S. (Researcher), Colaço, V. H. (Researcher) & Venter, Z. (Researcher)
1/01/20 → 31/12/25
Project: Research

Cite this

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title = "Robust filtering with quantile regression",

abstract = "This working paper proposes a new, practical method to compute the non-linear Mosheiov-Raveh (MR) filter using least absolute deviations (LAD) instead of the linear programming approach proposed by these two authors. This paper is embodied with an implementation in the R programming language of the proposed method which facilitates the computation of the MR filter in current applications to produce a robust estimate, namely, of the GDP trend growth. This technique may be appropriate to deal with non linear time series or structural changes.",

keywords = "Business cycles, Non linear time series, Robust filtering, Software",

author = "Assun{\c c}{\~a}o, \{Jo{\~a}o Borges\} and Fernandes, \{Pedro Afonso\}",

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AU - Fernandes, Pedro Afonso

PY - 2022/2/21

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KW - Non linear time series

KW - Robust filtering

KW - Software

M3 - Working paper

BT - Robust filtering with quantile regression

ER -

Robust filtering with quantile regression

Abstract

Keywords

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Projects

CUBE: Católica Lisbon Research Unit in Business and Economics

Cite this