Abstract:

Tourism development is one of the most important parts of the economic growth and it is one of the fastest-growing economic activities in the world. Tourism contributes to economic growth through the following direct and indirect channels. First，tourists’spending generates direct revenues to tourism-related businesses such as airlines，travel agents，hotels，shops，restaurants，and other tourist facilities. Secondly，the direct tourism revenues generate additional income for the firms that supply materials and services to the tourism characteristic businesses. Thirdly，the direct and indirect incomes will further radiate through all sectors of the destination generating the induced effects within the economy. According to World Travel and Tourism Council ( WTTC) ，the tourism sector directly contributed USD2229. 8 billion ( 3. 0% of total GDP) to global GDP and directly supported more than 107 million jobs ( 3. 6% of total employment) in 2015. As we include the “wider impacts”( ie the indirect and induced impacts) of Travel ＆ Tourism on the economy，the total contribution to GDP was USD7170. 3 billion ( 9. 8% of GDP) and total employment supported by the industry was 9. 5% of total employment，which is more than 283 million jobs in 2015. In terms of tourism economic benefits in China，the total contribution of the tourism sector to the GDP in China was CNY5366. 4 billion ( 7. 9% of GDP) ，and the total contribution to employment was 8. 4% of total employment ( 65 million jobs) . Tourism has been considered as a possible source of economic growth for many destinations by a number of studies． The ever increasing international arrivals and the income generated from tourism have contributed to job creation，poverty alleviation，environmental protection，and mutual understanding of different cultures across the globe. As the third largest country in the world，China has everything that a tourist destination can offer. The country’s rich cultural and natural heritage，pristine mountains，extensive river valleys，lakes，beaches，cuisines，art and crafts and above all，very warm and hospitable people attracted millions of tourists every year from all over the word. During the past decade，international and domestic tourism in China has surpassed its neighbors in both international arrivals and receipts and became the top destination in Asia and the Pacific. The proliferation of empirical studies，testing whether economic growth is tourism driven，such as the hypothesis of tourism-led economic growth ( TLEG) in nowadays considered as a key area of research within tourism economics. As we know，time series data are often sampled at different frequencies，e. g. monthly tourism demand， quarterly GDP，etc. While，the traditional time series causality tests are designed for single-frequency data. Temporal aggregations are always used to change the high-frequency variables into the common lowest frequency. Some research indicated that the traditional temporal aggregated Granger causality test model with stock ( or skipped) sampling may suffer from spuriously hidden or generated causality. In this paper，we investigate the linkage between the growth of inbound tourism arrivals ( inbound tourism reception) and real GDP growth rate in the case of China with mixed frequency Granger causality test to deal with an important，yet obvious overlooked problem，the spurious effect caused by the temporal aggregation，to remedy the power and size of Granger causality test. The majority of the previous studies have ignored the spurious effect of the Granger causality caused by the temporal aggregation. In addition，the sample size，as well as the study period also affected the reliability of the Granger causality test. The mixed frequency Granger Causality tests can address these limitations of the previous studies，and the simulation and empirical study show that it can exploit all data available whatever their sampling frequencies are and，achieves higher local asymptotic power than the existing single-frequency tests． Moreover，the rolling and recursive mixed frequency Granger causality test is used to further ensure the stability of the test when the sample is small and covers abnormal fluctuations caused by one-off events. The empirical results of mixed-frequency Granger causality tests have shown that there are some differences as we use inbound tourism arrival and tourism reception as the proxy variables for tourism demand，in which the growth of inbound tourism arrivals can lead economic growth in short-run，while inbound tourism revenue does not Granger cause economic growth. The hypothesis that economic growth drive inbound tourism revenue increase is approved，while the null hypothesis that of the economic growth doesn't Granger-cause inbound tourist arrivals couldn’t rejected significally. In addition，time-varying mixed frequency Granger causality test results show the relationship between inbound tourism demand and economic growth changes significantly with different sample sizes and different stages of economic development. To summarize，the results of the mixed-frequency Granger causality tests is more powerful than the traditional low-frequency methods.

Key Words: inbound tourism; economic growth; mixed frequency model; Granger causality test