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This paper aims to examine the relationship between tourism development and income inequality, closely linked to the Sustainable Development Goals, for the case of a large sample of 83 countries (and subsamples) over the period 1990–2019.

This study uses rigorous dynamic panel data analysis, namely, a Panel Vector Autoregressive Error Correction model, which takes into account both dynamic and endogenous relationships in the tourism-inequality nexus.

The results provide strong support that tourism development has an income inequality reducing effect (albeit relatively small with a reported elasticity of 0.05). Subsamples analysis reveals that the impact of tourism on income inequality varies and is relatively larger in developing economies and those tourist-dependent economies, as compared to developed economies. In fact, it is reported that a 1% increase in tourism development reduces income inequality by 0.46% for developing and 0.56% for tourist-dependent economies as compared to only 0.02% in developed economies. It is further observed that tourism may affect income inequality indirectly via economic growth.

This paper attempts to supplement the dearth literature on the tourism-inequality nexus by analyzing subsamples from a large data set while also using a dynamic panel data framework. The potential indirect effect of tourism on inequality via the economic growth channel is also explored.

该研究采用了严格的动态面板数据分析, 即面板向量自回归误差修正模型（PVEM）, 该模型考虑到了旅游业不平等关系中的动态和内生关系。

本文以1990–2019年期间83个国家（及其子样本）的大样本为例, 研究旅游业发展与收入不平等之间的关系。

本研究结果证明, 旅游业发展具有减少收入差距的作用（尽管相对较小, 报告的弹性为0.05）。子样本分析显示, 与发达经济体相比, 旅游业对收入不平等的影响在发展中经济体和那些依赖游客的经济体中存在差异且相对较大。事实上, 据报道, 旅游业发展每增加1%, 发展中经济体的收入差距就会缩小0.46%, 依赖旅游的经济体会缩小0.56%, 而发达经济体的差距仅缩小0.02%。本研究进一步观察到, 旅游业可能通过经济增长间接影响收入差距。

本文试图通过分析大型数据集的子样本, 同时采用动态面板数据框架, 来补充关于旅游与不平等关系的文献的不足。本文还探讨了旅游业通过经济增长渠道对不平等的潜在间接影响。

El estudio emplea un riguroso análisis dinámico de datos de panel, concretamente un modelo de corrección de errores autorregresivo vectorial de panel (PVEM), que tiene en cuenta tanto las relaciones dinámicas como las endógenas en el nexo turismo-desigualdad

Este documento examina la relación entre el desarrollo del turismo y la desigualdad de ingresos, estrechamente vinculada a los Objetivos de Desarrollo Sostenible, para el caso de una amplia muestra de 83 países (y submuestras) durante el periodo 1990-2019.

Los resultados apoyan firmemente que el desarrollo turístico tiene un efecto reductor de la desigualdad de ingresos (aunque relativamente pequeño, con una elasticidad declarada de 0,05). El análisis de submuestras revela que el impacto del turismo en la desigualdad de ingresos varía y es relativamente mayor en las economías en desarrollo y en aquellas economías dependientes del turismo, en comparación con las economías desarrolladas. De hecho, se informa de que un aumento del 1% en el desarrollo del turismo reduce la desigualdad de ingresos en un 0,46% en las economías en desarrollo y en un 0,56% en las economías dependientes del turismo, frente a sólo un 0,02% en las economías desarrolladas. Se observa además que el turismo puede afectar indirectamente a la desigualdad de ingresos a través del crecimiento económico.

El artículo intenta complementar la escasa bibliografía sobre el nexo entre turismo y desigualdad analizando submuestras de un gran conjunto de datos y empleando un marco dinámico de datos de panel. También se explora el posible efecto indirecto del turismo sobre la desigualdad a través del canal del crecimiento económico.

Mauritius’s residential real estate sector has undergone an increase in foreign investment over the past decades. This study aims to establish if the increasing level of foreign real estate investments (FREI) has increased land demand and land prices. The study also aims to depict whether the relation between FREI and land prices prevails at an aggregate and/ or a regional level.

Data from 26 regions, classified as urban, rural and coastal is collected on an annual basis over the period 2000 to 2019, and a dynamic panel regression framework, namely, an autoregressive distributed lag model, is used to take into account the dynamic nature of land price modeling.

The findings show that, at the aggregate level, in the long-term, FREI does not have a significant influence on land prices, while in the short term, a positive significant relationship is noted between the two variables. A regional breakdown of the data into urban, rural and coastal was done. In the long term, only in coastal regions, a positive significant link was observed, whereas in urban and rural regions FREI did not influence land prices. In the short term, the positive link subsists in the coastal regions, and in rural regions also land prices are positively affected by FREI.

Unlike other studies which have used quite general measures of FREI, the present research has focused on FREI mainly undertaken in the residential real estate market and how these have affected residential land prices. This study also contributes to research on the determinants of land prices which is relatively scarce compared to research on housing prices.

This study aims to investigate the effect of immigration on housing prices in Australia both at the national and regional levels.

Data for eight Australian states on a quarterly basis from 2004–2017 is used. To study the possible dynamic and endogenous relationship between housing prices and immigration, a panel vector autoregressive error correction model (PVECM) is adopted.

Analysis of the results indicates that in the short run immigration positively and significantly affects housing prices, whereas in the long run no significant relationship was observed between the two variables. From the regional breakdown and analysis, it is discerned that in some states there is a significant and positive effect of immigration on residential real estate prices in the long run. Causality analysis confirms that the direction of causation is from immigration to housing prices.

The study illustrates that immigration and interstate migration, as well as high salaries, have been causing a rise in housing demand and subsequently housing prices. To monitor exceedingly high housing prices, local authorities should be controlling migration and salary levels.

Past research studies had highlighted the importance of native interstate migration in explaining the nexus between immigration – housing prices. In this study, it has been empirically verified how immigration has been affecting the locational decisions of natives and subsequently how this has been affecting housing prices.