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    Rights statement: This is the author’s version of a work that was accepted for publication in International Journal of Hospitality Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Hospitality Management, 72, 2018 DOI: 10.1016/j.ijhm.2018.01.009

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Changing The Basics: Toward More Use of Quantile Regressions in Hospitality and Tourism Research

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Changing The Basics: Toward More Use of Quantile Regressions in Hospitality and Tourism Research. / Assaf, A. George; Tsionas, Mike.
In: International Journal of Hospitality Management, Vol. 72, 06.2018, p. 140-144.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Assaf AG, Tsionas M. Changing The Basics: Toward More Use of Quantile Regressions in Hospitality and Tourism Research. International Journal of Hospitality Management. 2018 Jun;72:140-144. Epub 2018 Feb 3. doi: 10.1016/j.ijhm.2018.01.009

Author

Assaf, A. George ; Tsionas, Mike. / Changing The Basics : Toward More Use of Quantile Regressions in Hospitality and Tourism Research. In: International Journal of Hospitality Management. 2018 ; Vol. 72. pp. 140-144.

Bibtex

@article{515e0291b3e84f03b1b14d2f481765f9,
title = "Changing The Basics: Toward More Use of Quantile Regressions in Hospitality and Tourism Research",
abstract = "The aim of this paper is to encourage more use of Quantile Regressions (QRs) in hospitality and tourism research. More importantly, we focus on the Bayesian estimation of QRs and discuss its advantages over traditional estimation techniques. We also discuss a Bayesian QR model that accounts for heteroscedasticity. We illustrate the performance of the two models using an interesting application on corporate social responsibility and firm value.",
keywords = "Quantile Regressions, Heteroscedasticity, Bayesian Estimation",
author = "Assaf, {A. George} and Mike Tsionas",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in International Journal of Hospitality Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Hospitality Management, 72, 2018 DOI: 10.1016/j.ijhm.2018.01.009",
year = "2018",
month = jun,
doi = "10.1016/j.ijhm.2018.01.009",
language = "English",
volume = "72",
pages = "140--144",
journal = "International Journal of Hospitality Management",
issn = "0278-4319",
publisher = "Elsevier Limited",

}

RIS

TY - JOUR

T1 - Changing The Basics

T2 - Toward More Use of Quantile Regressions in Hospitality and Tourism Research

AU - Assaf, A. George

AU - Tsionas, Mike

N1 - This is the author’s version of a work that was accepted for publication in International Journal of Hospitality Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Hospitality Management, 72, 2018 DOI: 10.1016/j.ijhm.2018.01.009

PY - 2018/6

Y1 - 2018/6

N2 - The aim of this paper is to encourage more use of Quantile Regressions (QRs) in hospitality and tourism research. More importantly, we focus on the Bayesian estimation of QRs and discuss its advantages over traditional estimation techniques. We also discuss a Bayesian QR model that accounts for heteroscedasticity. We illustrate the performance of the two models using an interesting application on corporate social responsibility and firm value.

AB - The aim of this paper is to encourage more use of Quantile Regressions (QRs) in hospitality and tourism research. More importantly, we focus on the Bayesian estimation of QRs and discuss its advantages over traditional estimation techniques. We also discuss a Bayesian QR model that accounts for heteroscedasticity. We illustrate the performance of the two models using an interesting application on corporate social responsibility and firm value.

KW - Quantile Regressions

KW - Heteroscedasticity

KW - Bayesian Estimation

U2 - 10.1016/j.ijhm.2018.01.009

DO - 10.1016/j.ijhm.2018.01.009

M3 - Journal article

VL - 72

SP - 140

EP - 144

JO - International Journal of Hospitality Management

JF - International Journal of Hospitality Management

SN - 0278-4319

ER -