Using regional data encompassing 155 Nomenclature of Territorial Units for Statistics (NUTS) regions across the EU-28 member states, we estimate the effect of tourist arrivals (total, domestic, and foreign) on regional growth over 2000-2018. Our empirical strategy tackles three data properties that cripple common econometric approaches: cross-section dependence, nonstationarity, and the endogeneity of the regressors. In addition to “pooled” models that assume common parameters across regions, we run “heterogeneous” models where parameters are allowed to differ between regions. Results of the pooled estimations show that domestic and total tourism inflows have positively and significantly contributed to growth, and the positive effect of foreign tourism is statistically discernible in regions that are mainly destinations for foreign tourists. Findings based on region-specific regressions reveal that the average impact on regional growth of tourist inflows is positive and significant, and large regional disparities in terms of the growth impact of domestic/foreign tourism exist.

我们使用包含欧盟28个成员国中155个国家统计单位（NUTS）区域命名法的区域数据，我们估算了2000-2018年期间游客入境（全部，国内和国外）对区域增长的影响。我们的经验策略解决了削弱普通计量经济学方法的三个数据属性：截面相关性，非平稳性和回归变量的内生性。除了假定跨区域使用通用参数的“池”模型之外，我们还运行“异构”模型，其中允许区域之间的参数不同。汇总估算结果表明，国内和总体旅游业流入对经济增长具有积极和显着的贡献，在主要是外国游客目的地的地区，外国旅游业的积极影响在统计上是可辨别的。