Functional coefficient quantile regression model with time-varying loadings

Date

2023-01-01

Author

Atak Atalık, Alev
Montes-Rojas, Gabriel
Olmo, Jose

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This paper proposes a functional coefficient quantile regression model with heterogeneous and time-varying regression coefficients and factor loadings. Estimation of the model coefficients is done in two stages. First, we estimate the unobserved common factors from a linear factor model with exogenous covariates. Second, we plug-in an affine transformation of the estimated common factors to obtain the functional coefficient quantile regression model. The quantile parameter estimators are consistent and asymptotically normal. The application of this model to the quantile process of a cross-section of U.S. firms’ excess returns confirms the predictive ability of firm-specific covariates and the good performance of the local estimator of the heterogeneous and time- varying quantile coefficients.

URI

https://www.tandfonline.com/doi/full/10.1080/15140326.2023.2167151
https://hdl.handle.net/11511/102220

Journal

JOURNAL OF APPLIED ECONOMICS

DOI

https://doi.org/10.1080/15140326.2023.2167151

Collections

Department of Economics, Article

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Citation Formats

A. Atak Atalık, G. Montes-Rojas, and J. Olmo, “Functional coefficient quantile regression model with time-varying loadings,” JOURNAL OF APPLIED ECONOMICS, vol. 26, pp. 1–39, 2023, Accessed: 00, 2023. [Online]. Available: https://www.tandfonline.com/doi/full/10.1080/15140326.2023.2167151.