Fused Lasso as Non-Crossing Quantile Regression

39 Pages Posted: 19 Jul 2024

See all articles by Tibor Szendrei

Tibor Szendrei

National Institute of Economic and Social Research (NIESR); Heriot-Watt University

Arnab Bhattacharjee

Heriot-Watt University; National Institute of Economic and Social Research (NIESR)

Mark Schaffer

Heriot-Watt University; IZA Institute of Labor Economics

Abstract

Quantile crossing has been a challenge for quantile regression, leading to research in how to obtain monotonically increasing quantile estimates. While important contributions, these papers do not provide insight into how enforcing monotonicity influences the estimated coefficients. This paper fills this gap and shows that non-crossing constraints are a type of fused-shrinkage. The proposed estimator has good fit and (fused) variable selection properties: it can reliably identify quantile varying parameters. We investigate the 'heat-or-eat' dilemma and show that prepayment has a non-linear impact on households' consumption choices. In a growth-at-risk application the estimator has the best forecast performance.

Keywords: fused-shrinkage, quantile regression, non-crossing constraints, LASSO

JEL Classification: C21

Suggested Citation

Szendrei, Tibor and Bhattacharjee, Arnab and Schaffer, Mark, Fused Lasso as Non-Crossing Quantile Regression. IZA Discussion Paper No. 17149, Available at SSRN: https://ssrn.com/abstract=4898329 or http://dx.doi.org/10.2139/ssrn.4898329

Tibor Szendrei (Contact Author)

National Institute of Economic and Social Research (NIESR) ( email )

2 Dean Trench Street
Smith Square
London, SW1P 3HE
United Kingdom

Heriot-Watt University ( email )

Arnab Bhattacharjee

Heriot-Watt University ( email )

National Institute of Economic and Social Research (NIESR) ( email )

Mark Schaffer

Heriot-Watt University ( email )

Riccarton
Edinburgh EH14 4AS, Scotland EH14 1AS
United Kingdom

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

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