Estimation and inference in semiparametric quantile factor models

Shujie Ma (), Oliver Linton and Jiti Gao

No 8/17, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: We propose an estimation methodology for a semiparametric quantile factor panel model. We provide tools for inference that are robust to the existence of moments and to the form of weak cross-sectional dependence in the idiosyncratic error term. We apply our method to CRSP daily data.

Keywords: cross-sectional dependence; Fama-French model; inference; sieve estimation. (search for similar items in EconPapers)
JEL-codes: C14 C21 C23 G12 (search for similar items in EconPapers)
Pages: 47
Date: 2017
New Economics Papers: this item is included in nep-ecm and nep-ore
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Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Estimation and inference in semiparametric quantile factor models (2021)
Working Paper: Estimation and Inference in Semiparametric Quantile Factor Models (2019)
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