Abstract
In this study, we analyze the development experience of eco-tourism in different regions of china to find the common regional convergence which is checked with ADF test and co-integration relations. In our results, we could contribute as theoretical foundation for regional development of eco- tourism in China. Meanwhile, the research result of convergence of regional eco-agricultural tourism in China could also contribute as the theoretical foundation for the policymaker.
Highlights
The research on the development of eco-tourism has become more popular in recent years
There are two means to apply theories said above to research on eco- tourism: one is Income return of eco-tourism based on cross section data, the other one is analysis based on time series data
The convergence and common trend of economy growth in and between different regions can be determined by equation 4 by Johansson and the definition by Bernard and Durlarf, through calculating the characteristics root of a matrix in different cyclamate number
Summary
The research on the development of eco-tourism has become more popular in recent years. There are two means to apply theories said above to research on eco- tourism: one is Income return of eco-tourism based on cross section data (including panel data), the other one is analysis based on time series data. The former is to judge whether the ecoagricultural tourism of different countries (regions) converges (including absolute convergence and relative convergence) based on income return ratio of ecoagricultural tourism with growth rate of eco-agricultural tourism the DV, Income of eco-agricultural tourism and other CV the IV. This study applies time series method, which was adapted by Bernard and Durlarf to research on economy growth, to study the convergence of regional eco-tourism in China. Miller and Russek (2000) have a research of the co integration and error correction models: the temporal causality between government taxes and spending. Dickey and Fuller (2001) have a research of the likelihood ratio statistics for autoregressive time series with a unit root. Johansen and Juselius (2002) analyze the maximum likelihood estimation and inference on co integration with application to the demand for money. Hall (2004) give the testing for a unit root in time series with pretest data-based model selection. Johansen (2007) give a statistical analysis of co integration faction, journal of economic dynamics and control. Li and Zi (2009) study the comprehensive analysis of the relationship between ecotourism and regional sustainable development in China
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