More General Panel Data Models for Hospitality and Tourism Research

A. George Assaf*, Mike G. Tsionas, Florian Kock

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


This paper introduces more advanced panel data specifications that would exploit heterogeneity and allow for arbitrary forms of autocorrelation and heteroskedasticity in the error terms.

In line with Assaf and Tsionas (2019a, 2019b), this paper builds on the Mundlak device to propose panel data models to allow for random slope coefficients, as well as time slope coefficients. This paper allows for arbitrary heteroskedasticity and autocorrelation, thus mitigating possible model misspecification. This paper develops and estimates the model in a Bayesian framework. This paper’s methods can be generalized to many nonlinear models including limited dependent variable models.

This paper compares several competing models such as a classical panel data model, which has only firm effects. This paper also examines the role of standard deviations in the formation of firm effects and time effects in the Mundlak device. This paper clearly shows that our framework introduces the best flexibility and model fit.

Research limitations/implications
This paper illustrates the importance of using more flexible models (i.e. unit-specific and time-varying coefficients) for future estimation of panel data in the field.

This paper discusses techniques that will improve panel data estimation in the hospitality and tourism literature.
Original languageEnglish
JournalInternational Journal of Contemporary Hospitality Management
Issue number11
Pages (from-to)4142-4156
Number of pages15
Publication statusPublished - 2022

Bibliographical note

Published online: 13 June 2022.


  • Heterogeneity
  • Panel data models
  • Bayesian
  • Mundlak

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