Aggregation, Heterogeneous Autoregression and Volatility of Daily International Tourist Arrivals and Exchange Rates

Abstract

Tourism is a major source of service receipts. The two leading tourism countries for Taiwan are Japan and USA. Daily data from 1/1/1990 to 31/12/2008 are used to model tourist arrivals from the world, USA and Japan to Taiwan, as well as their associated volatility. Inclusion of the exchange rate allows approximate daily price effects to be captured. The Heterogeneous Autoregressive (HAR) model is used to approximate long memory properties in daily exchange rates and international tourist arrivals, test whether alternative short and long run estimates of conditional volatility are sensitive to the approximate long memory in the conditional mean, examine asymmetry and leverage in volatility, and examine the effects of temporal and spatial aggregation. Asymmetry (though not leverage) is found for several alternative HAR models. For policy purposes, the empirical results suggest that an arbitrary choice of data frequency or spatial aggregation will not lead to robust findings.