Quantile Regression Analysis of Censored Data with Selection An Application to Willingness-to-Pay Data

Victor Champonnois (), Olivier Chanel and Costin Protopopescu ()
Additional contact information
Victor Champonnois: Aix-Marseille Univ, CNRS, AMSE, Marseille, France., https://www.amse-aixmarseille.fr/en
Costin Protopopescu: Aix-Marseille Univ, CNRS, AMSE, Marseille, France., https://www.amse-aixmarseille.fr/en/members/protopopescu

No 2214, AMSE Working Papers from Aix-Marseille School of Economics, France

Abstract: Recurring statistical issues such as censoring, selection and heteroskedasticity often impact the analysis of observational data. We investigate the potential advantages of models based on quantile regression (QR) for addressing these issues, with a particular focus on willingness to pay-type data. We gather analytical arguments showing how QR can tackle these issues. We show by means of a Monte Carlo experiment how censored QR (CQR)-based methods perform compared to standard models. We empirically contrast four models on flood risk data. Our findings confirm that selection-censored models based on QR are useful for simultaneously tackling issues often present in observational data.

Keywords: Censored Quantile Regression; Contingent Valuation; Flood; Monte Carlo Experiment; Quantile Regression; Selection Model; Willingness to Pay (search for similar items in EconPapers)
JEL-codes: C15 C21 C9 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2022-07
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-env
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.amse-aixmarseille.fr/sites/default/fil ... /wp_2022_-_nr_14.pdf (application/pdf)

Related works:
Working Paper: Quantile Regression Analysis of Censored Data with Selection An Application to Willingness-to-Pay Data (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aim:wpaimx:2214

Access Statistics for this paper

More papers in AMSE Working Papers from Aix-Marseille School of Economics, France AMU-AMSE - 5-9 Boulevard Maurice Bourdet, CS 50498 - 13205 Marseille Cedex 1. Contact information at EDIRC.
Bibliographic data for series maintained by Gregory Cornu ().