Fused LASSO as Non-Crossing Quantile Regression

Tibor Szendrei, Arnab Bhattacharjee and Mark Schaffer ()

Papers from arXiv.org

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.

Date: 2024-03, Revised 2025-04
New Economics Papers: this item is included in nep-ecm
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http://arxiv.org/pdf/2403.14036 Latest version (application/pdf)

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Working Paper: Fused LASSO as Non-crossing Quantile Regression (2024)
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