A0635
Title: Comparing flexible modelling approaches: The varying-thresholds model versus quantile regression
Authors: Niccolo Ducci - Agenzia delle Entrate (Italy)
Leonardo Grilli - University of Florence (Italy)
Marta Pittavino - Ca Foscari University of Venice (Italy) [presenting]
Abstract: The varying-thresholds model (VTM) is a novel methodology proposed by a prior study, capable of estimating the whole conditional distribution of a response variable in a regression setting. It can be used for continuous, ordinal, and count responses. The focus is on conditional quantiles and prediction intervals estimated through VTM, which are compared with those of quantile regression. The comparison is based on a set of data-generating models to assess the performance of the two methodologies regarding the coverage and width of prediction intervals. The simulation study encompasses settings with several functional forms and types of errors. In addition, a discrete version of the continuous ranked probability score is proposed as a tool to choose the best link function for the binary models used in the fitting of VTM. In summary, the varying-thresholds model is a flexible methodology that can be broadly applied with light assumptions; it is advantageous over quantile regression when the conditional quantile function is misspecified.
