Fast estimation algorithms to implement the Quantile Regression with Selection estimator and the multiplicative Bootstrap for inference. This estimator can be used to estimate models that feature sample selection and heterogeneous effects in cross-sectional data. For more details, see Arellano and Bonhomme (2017)
Overview: This package computes the Quantile Regression with Selection (QRS) estimator proposed by Arellano and Bonhomme (2017). Instead of using the algorithm originally proposed by those authors, it is based on a faster algorithm that attains a smaller computation time through the use of preprocessing techniques and quantile grid reduction. Installation: Provide instructions for installation via CRAN or GitHub if the package is not yet on CRAN.[...] Usage: A simple example is included in the package under the name example.r. It applies the estimation algorithm to obtain the estimates of the QRS estimator with the Mroz87 data set. License: GNU. Citation: The working paper version of the article can be accessed at https://arxiv.org/abs/2402.16693. Cite as Pereda-Fernández, S. (2024). Fast Algorithms for Quantile Regression with Selection. arXiv preprint arXiv:2402.16693.