Quantile regression in varying coefficient models

Abstract This paper deals with the estimation of conditional quantiles in varying coefficient models by estimating the coefficients. Varying coefficient models are among popular models that have been proposed to alleviate the curse of dimensionality. Previous works on varying coefficient models deal with conditional means directly or indirectly. However, quantiles themselves can be defined without moment conditions and plotting several conditional quantiles would give us more understanding of the data than plotting just the conditional mean. Particularly, we estimate the conditional median by estimating varying coefficients by local L 1 regression.

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