Quantile Factor Models

54 Pages Posted: 20 Feb 2018

See all articles by Liang Chen

Liang Chen

Shanghai University of Finance and Economics - School of Economics

Juan Dolado

European University Institute

Jesús Gonzalo

Universidad Carlos III de Madrid - Department of Statistics and Econometrics; Aarhus University - Department of Economics and Business Economics

Date Written: February 2018

Abstract

In contrast to Approximate Factor Models (AFM), our proposed Quantile Factor Models (QFM) allow for unobserved common factors shifting some parts of the distribution other than the means of observed variables in large panel datasets. When such extra factors exist, the standard estimation tools for AFM fail to extract them and their quantile factor loadings (QFL). Two alternative approaches are developed to estimate consistently the whole factor structure of QFM: (i) a two-step estimation procedure which is only valid when the same factors shift the means and the quantiles; and (ii) an iterative procedure which is able to extract (potentially) quantile-dependent factors and their QFL at a given quantile even when both sets of factors differ. Simulation results confirm that our QFM estimation approaches perform reasonably well in finite samples, while four empirical applications provide evidence that extra factors shifting quantiles could be relevant in practice.

Suggested Citation

Chen, Liang and Dolado, Juan and Gonzalo Muñoz, Jesús, Quantile Factor Models (February 2018). CEPR Discussion Paper No. DP12716, Available at SSRN: https://ssrn.com/abstract=3126210

Liang Chen (Contact Author)

Shanghai University of Finance and Economics - School of Economics ( email )

777 Guoding Road
Shanghai, 200433
China

Juan Dolado

European University Institute ( email )

Villa Schifanoia
133 via Bocaccio
Firenze (Florence), Tuscany 50014
Italy

Jesús Gonzalo Muñoz

Universidad Carlos III de Madrid - Department of Statistics and Econometrics ( email )

c/ Madrid 126
Getafe (Madrid), 28903
Spain
34 + 91 624 9853 (Phone)
34 + 91 624 9849 (Fax)

Aarhus University - Department of Economics and Business Economics

Fuglesangs Allé 4
Aarhus V
Denmark

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