An Analysis of the Correlation between GDP and the Primary Industry, Secondary Industry and Tertiary Industry in China

2020 ◽  
Vol 09 (02) ◽  
pp. 163-171
Author(s):  
仲阳 刘
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Junjun Ye ◽  
Jijian Wang ◽  
Yangzhou Zhang

This paper attempts to evaluate the transformation and upgrading (T&U) levels of the three industries in 11 prefectures of Zhejiang Province, China, since 2016. Taking the provincial T&U levels of the three industries as the benchmark, the three industries in each prefecture were analyzed by shift-share method (SSM). The main results are as follows: In terms of primary industry, none of the 11 prefectures had structural advantage (structural shifts < 0), but 3 had regional competitiveness (competitiveness shifts > 0); in terms of secondary industry, none of the 11 prefectures had structural advantage (structural shifts < 0), but 5 had regional competitiveness (competitiveness shifts > 0); in terms of tertiary industry, all of the 11 prefectures had structural advantage (structural shifts > 0), and 6 had regional competitiveness (competitiveness shifts > 0); Shaoxing was competitive in all three industries, ranking the first in the competitiveness of every industry; Huzhou, Quzhou, and Jinhua were not competitive in tertiary industry. The research provides a new yardstick of industrial T&U level and lays the decision-making basis for local governments in Zhejiang to formulate industrial T&U policies.


2011 ◽  
Vol 63-64 ◽  
pp. 682-685
Author(s):  
Jia Mu Niu

In recent years, the economy grows rapidly in Jilin province, and people’s life improves steadily, but at the same time, people has to face a sever employment situation. The changes on trend and characteristics of employment elasticity become flexible and fuzzy to predict with the development of society. By using linear regression methodology, employment situation of Jilin province is analyzed by taking primary industry employment elasticity, secondary industry employment elasticity, and tertiary industry employment elasticity into account. The calculation results show that three strata of industry employment elasticity has an increasing trend, and the total elasticity of employment is mainly driven by the second and tertiary industries.


2011 ◽  
Vol 55-57 ◽  
pp. 709-712
Author(s):  
Shu Hui Liu ◽  
Wu Wei Li

Based on the statistical data during the period from 2000 to 2008 released by Henan Statistical Bureau in China, this paper applied the grey relational analysis to analyze the relationship between industrial structure including primary industry, secondary industry, tertiary industry and economic growth in Henan province in China. After detailed research, some results have been concluded for Henan province, the first of which is the relationship between industrial structure and economic growth during the period from 2000 to 2008 is very close, and the primary industry is the most important causation that brings about economic growth, the second of which is that tertiary industry played lager important significance than secondary industry during the economic growth in Henan province in China. Research results could provide valuable information for policy makers in government in their efforts to make appropriate economic polices.


2014 ◽  
Vol 962-965 ◽  
pp. 1400-1403
Author(s):  
Xiao Lin Hao ◽  
Ji Dong Wu ◽  
Ning Li

This study has carried out the economic impact of output by industry in Beijing, making meteorological factors as a productivity input with capital, and labor. It has showed that the industry Output is combined with precipitation and temperature. For example, whenever the temperature increased by 1%, the primary industry output will be increased by about 2.99% and whenever the precipitation increased by 1%, the tertiary industry output will be increased by about 0.10%. The climate change has different effect on the secondary industry and the tertiary industry, both of which are more serious than the primary industry in Beijing.


2013 ◽  
Vol 401-403 ◽  
pp. 2187-2190
Author(s):  
Shu Ru Liu ◽  
Yi Zhang

Nowadays, Real estate is playing a significant role in economic growth in China currently, and has been closely linked with different industries in the national economy. Taking Shan ?xi Province as an example and adopting the Grey Relevance Analysis Approach mentioned in Grey Theory, this article analyzes the relevance between the real estate and three industry sub-industries in secondary industry and tertiary industry. It shows that the relevance goes up between the real estate and the primary industry, secondary industry, and tertiary industry, the real estate has made great contribution to the whole economy in Shan ?xi Province, and it has a promising market as well.


2019 ◽  
Vol 14 (2) ◽  
pp. 77-82
Author(s):  
Nurhayani Nurhayani

The aims of this research are to determine the economic growth in Jambi Province and the factors that influence it. The variables of this research are economic growth, investment, primary industry sector investment, secondary industry sector investment, and tertiary industry sector investment as research variables. The research model is multiple linear analysis to determine the effect of primary, secondary and tertiary sector industry investment on economic growth in Jambi Province. Based on the regression result, only the research variable of realization of primary industry sector investment, which significantly influences economic growth in Jambi Province. While investment in secondary and tertiary industry sectors did not significantly affect economic growth in Jambi Province.


2014 ◽  
Vol 519-520 ◽  
pp. 1500-1503
Author(s):  
Zai Tang Wang ◽  
Na Wang

This paper simulates the changes of the industries output after the business tax changing to the value added tax by using a general equilibrium model. The result show that, without burdening the tax of the tertiary industry, the VAT pilot reform can enhance the development of the primary , secondary and tertiary industry. It promotes the development of the primary and secondary industry obviously, but no significant influence for the primary industry.


2016 ◽  
Vol 8 (7) ◽  
pp. 294
Author(s):  
Jia-li Cai

<p>Finance is the core of modern economy, which plays an important role of allocating the resources and regulating the economy. The input-output table of China in 2007 and 2010 will be integrated into a simple form which includes primary industry, secondary industry, tertiary industry and the financial industry in this paper. Through the analysis on the direct dependency, complete dependency, spread effect and intermediate input rate and output rate, this paper investigates the relevancy between China’s financial industry and three major industries. It is concluded that although China’s financial industry develops rapidly, its status and role in the national economy is not outstanding. And this paper gives some suggestions for the development of the national economy, including developing the tertiary industry, promoting the structure upgrade of secondary industry and speeding up the cultivation of financial talents to promote the development of the financial industry.</p>


2021 ◽  
Vol 11 (1) ◽  
pp. 7
Author(s):  
Erjie Hu ◽  
Di Hu ◽  
Handong He

Innovation is a key factor for a country’s overall national strength and core competitiveness. The spatial pattern of innovation reflects the regional differences of innovation development, which can provide guidance for the regional allocation of innovation resources. Most studies on the spatial pattern of innovation are at urban and above spatial scale, but studies at urban internal scale are insufficient. The precision and index of the spatial pattern of innovation in the city needs to be improved. This study proposes to divide spatial units based on geographic coordinates of patents, designs the innovation capability and innovation structure index of a spatial unit and their calculation methods, and then reveals the spatial patterns of innovation and their evolutionary characteristics in Shenzhen during 2000–2018. The results show that: (1) The pattern of innovation capacity of secondary industry exhibited a pronounced spatial spillover effect with a positive spatial correlation. The innovation capacity and innovation structure index of the secondary industry evolved in a similar manner; i.e., they gradually extended from the southwest area to the north over time, forming a tree-like distribution pattern with the central part of the southwest area as the “root” and the northwest and northeast areas as the “canopy”. (2) The pattern of innovation capacity of tertiary industry also had a significant spatial spillover effect with a positive spatial correlation. There were differences between the evolutions of innovation capacity and innovation structure index of tertiary industry. Specifically, its innovation capacity presented a triangular spatial distribution pattern with three groups in the central and eastern parts of the southwest area and the south-eastern part of the northwest area as the vertices, while its innovative structure showed a radial spatial distribution pattern with the southwestern part of the southwest area as the source and a gradually sparse distribution toward the northeast. (3) There were differences between the evolution modes of secondary and tertiary industries. Areas with high innovation capacity in the secondary industry tended to be more balanced, while areas with high innovation capacity in the tertiary industry did not necessarily have a balanced innovation structure. Through the method designed in this paper, the spatial pattern of urban innovation can be more precise and comprehensive revealed, and provide useful references for the development of urban innovation.


2014 ◽  
Vol 962-965 ◽  
pp. 2165-2169
Author(s):  
Feng Yun Wang ◽  
Bing Hua Chen ◽  
Jin Ru Fan

This paper studies the causal relationship between energy consumption and economic growth in Beijing by using econometric method from 1980 to 2012, and then establishes the model between the energy consumption of three industries and economic growth to study the influence of the secondary industry and tertiary industry energy consumption on economic growth in Beijing. Finally, we put forward counter measures and suggestions on sustainable development of Beijing's economy and energy industry.


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