An analysis of the prosperity of China's marine economy

PurposeChina's marine economy occupies an important position within the national economy, and its contribution thereto is constantly improving. The overall operation of the marine economy shows positive developmental trends with potential for further growth. The purpose of this research is to analyse the prosperity of China's marine economy, reveal trends therein and forecast the likely turning point in its operation.Design/methodology/approachBased on the periodicity and fluctuation of China's marine economy development, China's marine economic prosperity indicator system is established from five perspectives. On this basis, China's marine economic operation prosperity index can be synthesised and calculated, then a dynamic factor model is constructed. Using the filtering method to calculate China's marine economic operational Stock–Watson index, Markov switching has been used to determine the trend to transition. Furthermore, China's current marine economic prosperity is evaluated through analysis of influencing factors and correlation analysis.FindingsThe analysis shows that, from 2017 to 2019, the operation of the marine economy is relatively stable, and the prosperity index supports this finding; meanwhile it also exposes problems in China's marine economy, such as an unbalanced industrial structure, low marine economic benefits and insufficient capacity for sustainable development.Originality/valueThrough the analysis of the prosperity of China's marine economy, the authors reveal the trends in China's marine economy and forecast its likely future turning point.

A Prosperity Index Model of Regional Tourism Industry Based on Composite Index

In recent years, the ice and snow tourism industry has developed rapidly, which plays an important role in boosting regional economy. The prosperity index of the ice and snow tourism industry was compiled, and the early warning model of the ice and snow tourism industry in Heilongjiang Province of China was built, which was taken as a comprehensive scale to observe the fluctuation of the ice and snow tourism industry. Combined with the current economic situation, the composite index, the situation of the industry and the turning point of the industry cycle volatility are analyzed, to determine the situation and trend of the industry volatility. This can provide reference for the policy formulation of the ice and snow tourism industry in Heilongjiang province and the micro-management of tourism companies.

A Study on the Prosperity Index and Cycle Measurement of China Air Cargo Transport

The business cycle of the Air cargo in China is investigated in this paper. Both the composite indicator (CI) and the diffusion indicator (DI) are derived and the benchmark date is determined. The composite index is synthesized by 10 indicators using correlation analysis and the method of NBER. Then the spectral method is adopted in use of the CI to identify the the major cycle of air cargo in China. By the CI, there is a major cycle with the length of 3,6 years. The major cycle of air cargo in China keeps pace with the the global trade fluctuation. The cycle of air cargo of China is compared with the United States, and the railway cargo of China. The author finds out that the major cycle of the air cargo is basically consistent with the USA in the same period. Combined with the prosperity index, it illustrates that the growth of air cargo in China will reach a peak in around 2021-2022, considering the growth of global trade and the leading prosperity index.

Research on electric power development and economic growth in Hebei Province based on business cycle analysis

With the improvement of China’s electrification level, the relationship between electricity power consumption and social economy development is getting closer. Under this background, in this paper, the business cycle analysis method is applied to the electricity power industry in Hebei Province, and the link between electric power generation and economic development is determined through the prosperity index. First of all, the steps and methods of business cycle analysis were introduced, and the time-difference grey correlation method considering the consistency of time series to screen indicators was put forward, thus to reduce the number of indicators. Next, Hebei Province was taken as an example, and its monthly data related to power generation and economic growth in the 10 years from 2009 to 2018 to was selected to build the business cycle indicator system, at last the composite prosperity index of Hebei Province in electric power industry was calculated. This research results manifest that it is feasible to apply the business cycle analysis to the power industry.