Determinants of tourism industry in selected European countries: a smooth partial least squares approach

Various events, such as the global economic crisis, have seriously hampered long-term stable tourism processes with a particular relevance to international visits. In this study, we use the smooth paths of partial least squares (PLS; more specifically its PLS-SVD algorithm) and principal component analysis (PCA) dependent on a time parameter to descriptively examine the multivariate connections of tourism and economic growth during the periods close to the crisis. A novel approach regarding the paths of leading singular values and corresponding singular vectors and describing the maximum covariance strength reveals many practical outputs as time lags and mutual connections between sets of data. From the base of Central European countries analysed here, only Switzerland shows a significant tourism lagged situation, where the results provide relative perceptive conditions to non-residents with stable conditions for domestic tourism. Our findings show great evidence of similar behaviour in the Austria, Slovenia and Poland group as well as the Czech Republic and Slovakia group. Also the Czech Republic and Slovakia are potentially very sensitive to non-resident visits. Germany reveals its strong interconnection to the European economy. On the other hand, in the case of Hungary, simultaneous changes in income and consumer prices form ideal conditions for tourism.