Fused LASSO as Non-Crossing Quantile Regression

Tibor Szendrei; Arnab Bhattacharjee; Mark E. Schaffer

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arXiv · 2403.14036

Fused LASSO as Non-Crossing Quantile Regression

Tibor Szendrei·Arnab Bhattacharjee·Mark E. Schaffer

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Abstract

Growth-at-Risk is vital for empirical macroeconomics but is often suspect to quantile crossing due to data limitations. While existing literature addresses this through post-processing of the fitted quantiles, these methods do not correct the estimated coefficients. We advocate for imposing non-crossing constraints during estimation and demonstrate their equivalence to fused LASSO with quantile-specific shrinkage parameters. By re-examining Growth-at-Risk through an interquantile shrinkage lens, we achieve improved left-tail forecasts and better identification of variables that drive quantile variation. We show that these improvements have ramifications for policy tools such as Expected Shortfall and Quantile Local Projections.

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BibTeX RIS

Tibor Szendrei, Arnab Bhattacharjee, Mark E. Schaffer. 2024-03-20. Fused LASSO as Non-Crossing Quantile Regression. https://arxiv.org/abs/2403.14036

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