Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

This paper discusses techniques that will improve panel data estimation in the hospitality and tourism literature.

中文翻译：

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用于酒店和旅游研究的更通用的面板数据模型

目的

本文介绍了更高级的面板数据规范，这些规范将利用异质性并允许误差项中的任意形式的自相关和异方差。

设计/方法/方法

与 Assaf 和 Tsionas (2019a, 2019b) 一致，本文在 Mundlak 设备的基础上提出了面板数据模型，以允许随机斜率系数以及时间斜率系数。本文允许任意异方差和自相关，从而减轻可能的模型错误指定。本文在贝叶斯框架中开发和估计模型。本文的方法可以推广到许多非线性模型，包括有限因变量模型。

发现

本文比较了几个竞争模型，例如经典的面板数据模型，这些模型仅具有坚定的效果。本文还研究了标准差在 Mundlak 装置中形成企业效应和时间效应的作用。本文清楚地表明，我们的框架引入了最佳的灵活性和模型拟合。

研究限制/影响

本文说明了使用更灵活的模型（即特定单位和时变系数）在该领域未来估计面板数据的重要性。

原创性/价值

本文讨论了将改善酒店和旅游文献中的面板数据估计的技术。