A spatial econometric approach to model the growth of tourism flows to China cities

Abstract

The main purpose of this research is to investigate and estimate the spillover effects in inbound and domestic tourism flows to 341 cities in mainland China. The key determinants of tourism flows are also studied in the spatial econometric model. Past tourism flow research which did not apply spatial econometric models tended to have biased results as the spillover effects which exist in tourism flows were not taken into consideration. To the best of the author's knowledge, this study represents one of the first attempts to analyze the spatial interaction between city (tourist) destinations. In the first step of empirical study, the spatial distribution of inbound and domestic tourism flows and their growth rates are investigated using exploratory spatial data analysis. The global Moran's I statistics for inbound and domestic tourism flows reveal strong positive and significant spatial autocorrelation, and the autocorrelation increases with time. This suggests that the city with a large number of tourist arrivals has a propensity to be clustered close to other cities with large numbers of tourist arrivals. Furthermore, the Moran significance maps indicate four significant inbound tourism hot-spot areas in 1999 and 2006. These are the Beijing-Tianjin cluster, the Yangtze River Delta cluster, the Fujian coast cluster and the Pearl River Delta cluster. As for domestic tourism flows, five hot-spot areas are discovered of which three tend to persist in significance over time. These three include the Beijing-Tianjin cluster, the Shandong Peninsula cluster and the Yangtze River Delta cluster. Apart from persistent hot-spot areas for domestic tourism, the Pearl River Delta cluster was significant in 2002, while the Chengdu cluster was significant in 2006. To capture the spillover effects in tourism flows and identify factors contributing to the unevenly distributed tourism flows, various spatial econometric models are estimated. The results confirm the existence of spillover effects in both inbound and domestic tourism flows, and suggest that infrastructure factors, tourist attractions and the SARS outbreak are significant determinants of inbound and domestic tourism flows. In addition, while the degree of openness to inbound tourists is important for inbound tourism flows, city's income is the key to enhancing domestic tourism flows. A comparison between the estimated coefficients obtained from the inbound tourism flow model and the domestic model indicates that the spillover effects in inbound tourism flows are larger, and infrastructure elasticities are higher for inbound tourism flows compared to domestic flows. This suggests that inbound tourists are more demanding, for example, with regards to hotels, land transportation, telecommunication facilities and airports. As for the regional differences in tourism growth, the results reveal that the spillover effects for inbound tourism flows are strongest in Eastern cities while for domestic flows they are more significant in Western cities. Finally, various infrastructure elasticities are higher for Eastern and Central cities in comparison to those for Western cities, suggesting that tourists have lower expectation with regards to infrastructure needs when traveling to Western cities in mainland China.