Spatial-temporal impacts of tourism economy

This study aims to propose a spatial-temporal geographically weighted regression model to estimate tourists' consumption caused by tourism infrastructure improvement. A Bayesian geographically weighted regression model with time series correlations are proposed. In this study, northern part of Nagano prefecture is selected as a study area, where is a popular sightseeing spot because of winter sports, trekking and eco-tourism. In the proposed model, tourists' consumption per tourist is explained by indices relating tourism infrastructure improvement, seasonal distribution of the number of tourists. Model estimation results show the followings. Estimation results of model parameters indicate that tourism consumption in the previous year and investment on commerce and industry are strongly correlated with tourism consumption. It is also shown that hyper parameter on error term effects over estimate of model parameter.