An Empirical Study on the Relationship between Chinese Tourism Development and Economic Growth:A Case Study of Huangshan City
Huo Shou-hua
Abstract
Huo Shou-hua
Abstract
This paper analyzes the dynamic relationship between tourism development and economic growth of Huangshan City,based on ADF test,co-integration test and Granger causality test.A vector error correction model is established to study the long-term stable relationship.The results indicate that there are a long-term equilibrium relationship between economic growth and development of tourism industry.With domestic tourism increased by 1%,the growth of GDP increases about 0.45%;with inbound tourism increased by 1%,the growth of GDP increases 0.056%.The one-way Granger causality existes among domestic tourism,inbound tourism income and economic growth.In conclusion,Huangshan City should attach great importance to the tourism development and increase tourism investment.Moreover,the government should put forward a long-term strategy about balancing the tourism development and economic growth.
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This paper analyzes the dynamic relationship between tourism development and economic growth of Huangshan City,based on ADF test,co-integration test and Granger causality test.A vector error correction model is established to study the long-term stable relationship.The results indicate that there are a long-term equilibrium relationship between economic growth and development of tourism industry.With domestic tourism increased by 1%,the growth of GDP increases about 0.45%;with inbound tourism increased by 1%,the growth of GDP increases 0.056%.The one-way Granger causality existes among domestic tourism,inbound tourism income and economic growth.In conclusion,Huangshan City should attach great importance to the tourism development and increase tourism investment.Moreover,the government should put forward a long-term strategy about balancing the tourism development and economic growth.
Key concepts: Tourism, Granger causality, Error correction model, Economics, Investment (military), Government (linguistics), Empirical research, Vector autoregression