Rights statement: This is the author’s version of a work that was accepted for publication in Tourism 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 Tourism Management, 75, 2019 DOI: 10.1016/j.tourman.2019.06.012
Accepted author manuscript, 545 KB, PDF document
Available under license: CC BY-NC-ND
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Bayesian dynamic panel models for tourism research
AU - Assaf, A. George
AU - Tsionas, Mike G.
N1 - This is the author’s version of a work that was accepted for publication in Tourism 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 Tourism Management, 75, 2019 DOI: 10.1016/j.tourman.2019.06.012
PY - 2019/12/10
Y1 - 2019/12/10
N2 - This paper describes several innovative dynamic panel data models that allow variations in slope coefficients both across time and cross-sectional units. We replace time variation with a dynamic (autoregressive) component and introduce several variations of the so-called Mundlak device in which random intercepts are linear function of the average values of the regressors. We develop all models in a Bayesian framework, and test their performance using an interesting application on the impact of advertising on firm sales. We provide technical details of all these models and present tools to compare their performance in a Bayesian framework. Moreover, model averaging and posterior model pools are presented to gain more insight into the relationship between advertising and sales.
AB - This paper describes several innovative dynamic panel data models that allow variations in slope coefficients both across time and cross-sectional units. We replace time variation with a dynamic (autoregressive) component and introduce several variations of the so-called Mundlak device in which random intercepts are linear function of the average values of the regressors. We develop all models in a Bayesian framework, and test their performance using an interesting application on the impact of advertising on firm sales. We provide technical details of all these models and present tools to compare their performance in a Bayesian framework. Moreover, model averaging and posterior model pools are presented to gain more insight into the relationship between advertising and sales.
U2 - 10.1016/j.tourman.2019.06.012
DO - 10.1016/j.tourman.2019.06.012
M3 - Journal article
VL - 75
SP - 582
EP - 594
JO - Tourism Management
JF - Tourism Management
SN - 0261-5177
ER -