Parametric Modeling of Quantile Regression Coefficient Functions With Longitudinal Data

@article{Frumento2020ParametricMO,
  title={Parametric Modeling of Quantile Regression Coefficient Functions With Longitudinal Data},
  author={Paolo Frumento and Matteo Bottai and Iv{\'a}n Fern{\'a}ndez-Val},
  journal={Journal of the American Statistical Association},
  year={2020},
  volume={116},
  pages={783 - 797}
}
Abstract In ordinary quantile regression, quantiles of different order are estimated one at a time. An alternative approach, which is referred to as quantile regression coefficients modeling (qrcm), is to model quantile regression coefficients as parametric functions of the order of the quantile. In this article, we describe how the paradigm can be applied to longitudinal data. We introduce a two-level quantile function, in which two different quantile regression models are used to describe the… Expand
Panel Quantile Regression with Time-Invariant Rank
I propose a quantile-based random coefficient panel data framework to study heterogeneous causal effects. The heterogeneity depends on unobservables, as opposed to heterogeneity for which we can addExpand

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