scholarly journals Analisis pengaruh investasi industri sektor primer, sektor sekunder dan sektor tersier terhadap pertumbuhan ekonomi di Provinsi Jambi

2019 ◽  
Vol 14 (2) ◽  
pp. 77-82
Author(s):  
Nurhayani Nurhayani
Keyword(s):  
Economic Growth ◽  
Regression Result ◽  
Research Model ◽  
Primary Industry ◽  
Tertiary Sector ◽  
Tertiary Industry ◽  
Industry Sector ◽  
Secondary Industry ◽  
Industry Investment ◽  
Industry Sectors

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.

scholarly journals The Impacts of Globalization on Inequality in the Post-COVID-19 World: Evidence From China

2021 ◽  
Vol 9 ◽  
Author(s):  
Tsun Se Cheong ◽  
Yanrui Wu ◽  
Michal Wojewodzki ◽  
Ning Ma
Keyword(s):  
International Trade ◽  
Income Inequality ◽  
Empirical Studies ◽  
County Level ◽  
Primary Industry ◽  
Industry Sector ◽  
Secondary Industry ◽  
Per Se ◽  
Industry Sectors ◽  
The Impact

Empirical studies suggest that globalization (FDI and international trade) has been greatly affected by the COVID-19 and related anti-pandemic measures imposed by governments worldwide. This paper investigates the impact of globalization on intra-provincial income inequality in China and the data is based on the county level. The findings reveal that FDI is negatively associated with intra-provincial inequality, intra-provincial inequality increases as the primary industry sector (agriculture) declines. The result also finds that the increase in inequality stems not from the development in the tertiary or secondary industry sectors per se, but the unevenness in the distribution of these sectors.

Research on Relationship between Industrial Structure and Economic Growth: Evidence from Henan Province in China

2011 ◽  
Vol 55-57 ◽  
pp. 709-712
Author(s):  
Shu Hui Liu ◽  
Wu Wei Li
Keyword(s):  
Economic Growth ◽  
Industrial Structure ◽  
Henan Province ◽  
Primary Industry ◽  
Policy Makers ◽  
Tertiary Industry ◽  
Secondary Industry ◽  
Grey Relational ◽  
The Relationship ◽  
Important Significance

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.

On the Relationship between Economic Growth and Energy Consumption in Beijing

2014 ◽  
Vol 962-965 ◽  
pp. 2165-2169
Author(s):  
Feng Yun Wang ◽  
Bing Hua Chen ◽  
Jin Ru Fan
Keyword(s):  
Economic Growth ◽  
Sustainable Development ◽  
Energy Consumption ◽  
Causal Relationship ◽  
Energy Industry ◽  
Counter Measures ◽  
Tertiary Industry ◽  
Secondary Industry ◽  
The Relationship

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.

scholarly journals Analysis on Transformation and Upgrading Levels of Three Industries in 11 Prefectures of Zhejiang Based on Shift-Share Method

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Junjun Ye ◽  
Jijian Wang ◽  
Yangzhou Zhang
Keyword(s):  
Decision Making ◽  
Local Governments ◽  
Zhejiang Province ◽  
Primary Industry ◽  
Regional Competitiveness ◽  
Tertiary Industry ◽  
Secondary Industry ◽  
Structural Shifts

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.

Analysis on the Employment Elasticity Change Factors Based on Linear Regression Methodology

2011 ◽  
Vol 63-64 ◽  
pp. 682-685
Author(s):  
Jia Mu Niu
Keyword(s):  
Linear Regression ◽  
Jilin Province ◽  
Primary Industry ◽  
Tertiary Industry ◽  
Change Factors ◽  
Employment Situation ◽  
Increasing Trend ◽  
Calculation Results ◽  
Employment Elasticity ◽  
Secondary Industry

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.

Impact of Climate Change on Regional Economy

2014 ◽  
Vol 962-965 ◽  
pp. 1400-1403
Author(s):  
Xiao Lin Hao ◽  
Ji Dong Wu ◽  
Ning Li
Keyword(s):  
Climate Change ◽  
Economic Impact ◽  
Regional Economy ◽  
Meteorological Factors ◽  
Primary Industry ◽  
Impact Of Climate Change ◽  
Tertiary Industry ◽  
Industry Output ◽  
Secondary Industry ◽  
Precipitation And Temperature

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.

The Real Estate Industry and Three Industry Correlation Empirical Analysis, Shan’xi Province

2013 ◽  
Vol 401-403 ◽  
pp. 2187-2190
Author(s):  
Shu Ru Liu ◽  
Yi Zhang
Keyword(s):  
Real Estate ◽  
Grey Theory ◽  
Real Estate Industry ◽  
Great Contribution ◽  
Primary Industry ◽  
The Real ◽  
The Real Estate ◽  
Tertiary Industry ◽  
Relevance Analysis ◽  
Secondary Industry

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.

The Resource Configuration Effect’s Simulation Calculations of the VAT Pilot Reform Based on the CGE Model

2014 ◽  
Vol 519-520 ◽  
pp. 1500-1503
Author(s):  
Zai Tang Wang ◽  
Na Wang
Keyword(s):  
Significant Influence ◽  
Equilibrium Model ◽  
Value Added ◽  
Cge Model ◽  
Primary Industry ◽  
Resource Configuration ◽  
Tertiary Industry ◽  
Result Show ◽  
Secondary Industry ◽  
Business Tax

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.

scholarly journals The Drivers of Structural Changes

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Jianfang Liu
Keyword(s):  
Economic Growth ◽  
Structural Transformation ◽  
Structural Adjustment ◽  
Structural Changes ◽  
Public Expenditure ◽  
Driving Mechanism ◽  
Primary Industry ◽  
Labor Share ◽  
Secondary Industry ◽  
Fourth Wave

Structural change is an important feature in the process of economic growth. Most economies in the process of economic growth have appeared similar structural adjustment. The primary industry labor share declines; the tertiary industry labor share increases; the secondary industry labor share presents an inverted u-shaped change. This paper aims to analyze the driving mechanism of structural transformation from the perspectives of supply, demand, input and output, international trade and government public expenditure, and finally make a prospect for future structural transformation research from the perspectives of producer heterogeneity and consumer heterogeneity as well as the fourth wave of technological change — artificial intelligence.

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