Abstract

ABSTRACTThe literature on gravity equations has recently shown that flows between two countries are not merely impacted by their structural bilateral determinants but also affected by their relative accessibility vis-à-vis other countries. The idea can be extended to tourism analysis: bilateral tourism flows are not only determined by factors affecting the attractiveness of the destination country but also depend on the attractiveness of alternative destinations. This effect can be termed ‘multilateral resistance to tourism’ (MRT) and embodied in cross-sectional correlation across the main tourism determinants. In this paper, we show that the standard estimation techniques applied in tourism analysis fail to properly account for the MRT, yielding biased estimates and nonstationary residuals. We cast the gravity model into the common factor framework and employ the common correlated effects (CCE) estimator to obtain unbiased estimates of some standard determinants of tourism flows in the context of 35 OECD members during 1995–2015. Our CCE results show that the impact of a number of regressors becomes negligible and insignificant, highlighting their role as vectors of cross-section dependence. Our findings stress the need for analyzing the data to detect the magnitude of the cross-sectional dependence and, when the latter is omnipresent, employing MRT-robust estimations.

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