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Perceived pollution and inbound tourism for Shanghai: a panel VAR approach

ABSTRACT Although there exists sizeable literature studying the impact of tourists’ risk perceptions, less attention has been devoted to studying the difference between the impact of measured and perceived risks. We apply a panel vector autoregression (PVAR) to a dataset of inbound tourism in Shanghai, China to study the dynamic relationship between pollution and tourism. Particularly, we distinguish between measured pollution level and perceived pollution (measured by Google Trends search data) to test which one has the larger impact on tourists’ decisions. Our results show that pollution (measured or perceived) can be a powerful deterrent to potential international tourists.