Study on the Non-linear Effect of Tourism Industry Agglomeration on Economic Growth in China——Based on Inter-provincial Panel Data

2021 ◽  
Vol 7 (6) ◽  
pp. 6213-6221
Author(s):  
Lin Li
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Threshold Value ◽  
Tourism Industry ◽  
Linear Effect ◽  
Industry Agglomeration ◽  
Non Linear Effect ◽  
Non Linear ◽  
Level Of Economic Development

Objectives: There are few studies on the non-linear effect of tourism industry agglomeration on economic growth. Based on this, this paper uses the panel data of provinces in 2007-2017 to analyze the spatial characteristics of China's tourism industry agglomeration, and uses the threshold regression model to analyze the role of China's tourism industry agglomeration in promoting economic growth. The results show that: China's tourism industry shows obvious characteristics of spatial agglomeration. The provinces with high degree of industrial agglomeration are mainly Beijing, Shanghai, Yunnan, Guangdong, Guizhou, Sichuan and Shanxi; The non-linear effect of China's tourism industry agglomeration on economic growth is significant. When the level of economic development is less than the threshold value of 10.552, tourism industry agglomeration promotes economic growth. When the level of economic development is greater than the threshold value of 10.552, the impact of tourism industry agglomeration on economic growth is negative. Williamson hypothesis of China's tourism industry agglomeration is established.

scholarly journals Do Carbon Emissions and Economic Growth Decouple in China? An Empirical Analysis Based on Provincial Panel Data

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2411 ◽  
Author(s):  
Yu Hao ◽  
Zirui Huang ◽  
Haitao Wu
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Carbon Emissions ◽  
Environmental Kuznets Curve ◽  
Kuznets Curve ◽  
Ekc Hypothesis ◽  
Capita Gross Domestic Product ◽  
Level Of Economic Development ◽  
The Relationship

Global warming has emerged as a serious threat to humans and sustainable development. China is under increasing pressure to curb its carbon emissions as the world’s largest emitter of carbon dioxide. By combining the Tapio decoupling model and the environmental Kuznets curve (EKC) framework, this paper explores the relationship between China’s carbon emissions and economic growth. Based on panel data of 29 provinces from 2007 to 2016, this paper quantitatively estimates the nexus of carbon emissions and economic development for the whole nation and the decoupling status of individual provinces. There is empirical evidence for the conventional EKC hypothesis, showing that the relationship between carbon emissions and per capita gross domestic product (GDP) is an inverted U shape and that the inflection point will not be attained soon. Moreover, following the estimation results of the Tapio decoupling model, there were significant differences between individual provinces in decoupling status. As a result, differentiated and targeted environmental regulations and policies regarding energy consumption and carbon emissions should be reasonably formulated for different provinces and regions based on the corresponding level of economic development and decoupling status.

scholarly journals Testing Non-linear Effect of Urbanization on Economic Growth in China — Based on the Aspect of Financial Deepening

2015 ◽  
Vol 65 (s2) ◽  
pp. 17-33
Author(s):  
Xinguang Li ◽  
Ridong Hu
Keyword(s):  
Economic Growth ◽  
Dynamic Change ◽  
Smooth Transition ◽  
Growth Effect ◽  
Financial Deepening ◽  
Relevant Variable ◽  
Linear Effect ◽  
Linear Feature ◽  
Non Linear Effect ◽  
Non Linear

Smooth Transition Regression Model (STR) is applied to analyze the non-linear effect of urbanization on economic growth in this study. By collecting relevant variable data in 1978–2012, financial deepening is selected as the transition variable to construct the STR Model which could reflect the dynamic change of urbanizational economic growth effect. The result shows that urbanizational economic growth effect should present the characteristics of threshold and could be described with non-linear Smooth Transition Model (LSTR1). Meanwhile, the urbanizational economic growth effect should reveal asymmetry, in which the research findings show contemporary financial deepening (FISt) as a factor. Specifically, the linear feature appears when the FISt is lower than 0.3792 (before 1990), while it reveals non-linearity when the FISt exceeds 0.3792 (after 1990), and the non-linearity becomes the major factor in the urbanizational economic growth effect after 1990.

PENGARUH PEMBANGUNAN INFRASTRUKTUR TERHADAP PDRB DI PROVINSI INDONESIA

Wahana ◽  
2019 ◽  
Vol 22 (1) ◽  
pp. 15-27
Author(s):  
Suripto Suripto ◽  
Eva Dwi Lestari
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Infrastructure Investment ◽  
Water Infrastructure ◽  
Infrastructure Development ◽  
Road Infrastructure ◽  
Health Infrastructure ◽  
Spatial Coverage ◽  
The Government

Economic growth is one indicator to measure  the success of economic development in a country. Economic development is closely related to infrastructure. Infrastructure development will have an impact on economic growth both directly and indirectly. Therefore, the role of the government in determining infrastructure development policies is very important to increase economic growth in Indonesia. The purpose of this study is to determine the effect of infrastructure on economic growth in Indonesia including road infrastructure, electricity infrastructure, investment, water infrastructure, education infrastructure and health infrastructure in Indonesia in 2015-2017.The analytical tool used in this study is panel data regression with the approach of Fixed Effect Model. The spatial coverage of this study is all provinces in Indonesia, namely 34 provinces, with a series of data from 2015 to 2017 with a total of 102 observations. The data used is secondary data obtained from BPS Indonesia.The results of the study show that (1) the road infrastructure variables have a negative and not significant effect on GDRP. (2) electrical infrastructure variables have a negative and not significant effect on GDRP. (3) investment variables have a positive and significant effect on GDRP. (4) water infrastructure variables have a positive and not significant effect on GDRP. (5) educational infrastructure variables have a positive and not significant effect on GDRP. (6) health infrastructure variables have a positive and significant effect on GDRP. Keywords: development, infrastructure, investment, GDRP, panel data

Growth and Social Capital: Empirical Analysis of the Relationship

2019 ◽  
pp. 128-134
Author(s):  
Ksenia V. Bagmet
Keyword(s):  
Economic Growth ◽  
Social Capital ◽  
Economic Development ◽  
Social Development ◽  
Empirical Analysis ◽  
Panel Data Analysis ◽  
Well Being ◽  
Developed Countries ◽  
International Institute ◽  
Level Of Economic Development

The article provides an empirical test of the hypothesis of the influence of the level of economic development of the country on the level of development of its social capital based on panel data analysis. In this study, the Indices of Social Development elaborated by the International Institute of Social Studies under World Bank support are used as an indicators of social capital development as they best meet the requirements for complexity (include six integrated indicators of Civic Activism, Clubs and Associations, Intergroup Cohesion, Interpersonal Safety and Trust, Gender Equality, Inclusion of Minorities), comprehensiveness of measurement, sustainability. In order to provide an empirical analysis, we built a panel that includes data for 20 countries divided into four groups according to the level of economic development. The first G7 countries (France, Germany, Italy, United Kingdom); the second group is the economically developed countries, EU members and Turkey, the third group is the new EU member states (Estonia, Latvia, Lithuania, Romania); to the fourth group – post-Soviet republics (Armenia, Georgia, Russian Federation, Ukraine). The analysis shows that the parameters of economic development of countries cannot be completely excluded from the determinants of social capital. Indicators show that the slowdown in economic growth leads to greater cohesion among people in communities, social control over the efficiency of distribution and use of funds, and enforcement of property rights. The level of tolerance to racial diversity and the likelihood of negative externalities will depend on the change in the rate of economic growth. Also, increasing the well-being of people will have a positive impact on the level of citizens’ personal safety, reducing the level of crime, increasing trust. Key words: social capital, economic growth, determinant, indice of social development.

scholarly journals Tourism Industry and Economic Growth Nexus in Beijing, China

Economies ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 25 ◽  
Author(s):  
Yang Songling ◽  
Muhammad Ishtiaq ◽  
Bui Thi Thanh
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Strong Support ◽  
Growth Index ◽  
Strong Relationship ◽  
Tourism Industry ◽  
Var Model ◽  
Long Run ◽  
The Relationship ◽  
Beijing China

In the developing economy, tourism is the most visible and steadiest growing facade. Tourism is considered one of the rapidly increasing elements for economic development from the last two decades. Therefore, the proposed study used vector autoregression (VAR) model, error correction model (ECM), and the Granger causality to check the relationship between the tourism industry and economic growth based on the data of the Beijing municipal bureau of statistics from 1994 to 2015. Gross domestic product (GDP) is used as a replacement variable for the economic growth index, while internal tourism revenue is used as a tourism industry indicator. The study supports the tourism-led growth hypothesis proposed in the existing literature in a different survey of tourism and economic development. The results show that there is a strong relationship in the tourism industry and economic growth in the context of Beijing, and at the same time, tourism creates a more significant increase in long run local real economic accomplishments. The results of the VAR model confirm that in the long run, Beijing’s economic growth is affected by domestic tourism, while the ECM model shows unidirectional results in the short term. Similarly, there is a one-way causal relationship between the tourism industry and economic growth in Beijing, China. The empirical results are in strong support of the concept that tourism causes growth.

scholarly journals Non-linear effect of different humidity types on scrub typhus occurrence in endemic provinces, Thailand

Heliyon ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e06095
Author(s):  
Bhophkrit Bhopdhornangkul ◽  
Aronrag Cooper Meeyai ◽  
Waranya Wongwit ◽  
Yanin Limpanont ◽  
Sopon Iamsirithaworn ◽  
...  
Keyword(s):  
Scrub Typhus ◽  
Linear Effect ◽  
Non Linear Effect ◽  
Non Linear
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