Title: Joint Quantile Shrinkage: A State-Space Approach toward Non-Crossing Bayesian Quantile Models

Authors 
David Kohns - Aalto University
Tibor Szendrei - National Institute of Economic and Social Research

Abstract:

Crossing of fitted conditional quantiles is a prevalent problem for quantile regression models. We propose a new Bayesian modelling framework that penalises multiple quantile regression functions toward the desired non-crossing space. We achieve this by estimating multiple quantiles jointly with a prior on variation across quantiles, a fused shrinkage prior with quantile adaptivity. The posterior is derived from a decision-theoretic general Bayes perspective, whose form yields a natural state-space interpretation aligned with Time-Varying Parameter (TVP) models. Taken together our approach leads to a Quantile-Varying Parameter (QVP) model, for which we develop efficient sampling algorithms. We demonstrate that our proposed modelling framework provides superior parameter recovery and predictive performance compared to competing Bayesian and frequentist quantile regression estimators in simulated experiments and a real-data application to multivariate quantile estimation in macroeconomics.

The public research seminars of the Department of Economics and Finance (DEF) at Tallinn University of Technology  usually take place on the second and fourth Wednesdays of the month both in onsite and online format, unless announced otherwise. The seminar will last one hour, presentation will last approximately 45 minutes followed by 15 minutes of discussion. The seminars are held in English. Questions about the seminar can be sent to the seminar coordinator Karsten Staehr karsten.staehr@taltech.ee