scholarly journals The Influence of Collaborative Innovation Among Technology ,Institution and Finance on China’s Economic Growth

This paper constructs a model of collaborative innovation among technology, institution and financeto measure the synergy degree of 29 provinces and cities. Official provincial-level panel data from 2011-2017for 29 provinces are utilized. We find that there is a great difference in the synergy degree among differentregions because of the uneven distribution of financial resources in the region. Then the synergy degree of 29provinces and cities in China is regarded as an important variable in the fixed-effects model. The primaryfinding is that the degree of collaborative innovation among technology, institution and finance can positivelyaffect China’s economic growth. If the degree of collaborative innovation increase by 1%, and the GDP percapita will also increase by about 0.009%-0.016%. However, the domestic loan index of real estate enterpriseshas a negative impact on the per capita GDP. Then we get the conclusion that collaborative innovation will beeffective for China’s high-quality economic growth and suggest that government should use macro control toreduce capital’s preference for real estate investment especially by strengthening direct financial innovation tosupport technological innovation.

Author(s):  
Viktoriia Ahapova

The present article investigates the link between economic growth, namely GDP per capita, and the media activity represented with the indicator of the press freedom alongside other factors such as infrastructure, institutional conditions, and foreign direct investments. A panel of 179 countries was used for the period from 2000 to 2015. In particular, we run two panel data analysis models, fixed effects and random effects models, and examined their output with Hausman’s specification test, which pointed the fixed effects model as more efficient for the presented data set. However due to the presence of serial correlation, heteroskedastic, and cross-panel dependence, a Prais-Winsten regression with panel corrected standard errors (PCSE) was implemented. The comparative analysis of models of four country groups, divided by GNI per capita, was conducted. Both statistically significant correlation coefficients and models’ output provided evidence of an association between economic growth and the press activity.


Author(s):  
Hicham Boussalham

This study attempts to assess the impact of corruption on economic growth in the Mediterranean countries, during the period from 1998 to 2007. Econometric analysis using panel regression has been adopted to test this effect. Individual effects models such as random effects model and fixed effects model were applied to the study sample of 160 observations, and to choose the suitable model, we implemented several tests. For our analysis, we used a basic model that includes the dependent variable GDP per capita as a factor of economic growth and the corruption perception index as the independent variable concerned. Then we completed the model with several standardized macroeconomic control variables mentioned above and applied the individual effects models. The outcomes illustrate that corruption has a negative impact on the selected Mediterranean countries’ economic growth.


2020 ◽  
Vol 6 ◽  
pp. 237802311989832
Author(s):  
Daniel Driscoll

The most common counterargument to taxing carbon emissions is that the policy has a negative impact on economic growth. The author tests the validity of this argument by visualizing the enactment of carbon prices on gross domestic product per capita from 1979 to 2018 and presenting a formal fixed-effects regression analysis of panel data. No connection is found between carbon price implementation and diminished economic growth. This outcome is primarily due to policy design and the general nature of economic growth. The author concludes that this counterargument to enacting carbon prices exists only because of misunderstandings of economic growth and ideology.


Author(s):  
Hicham Boussalham

This study attempts to assess the impact of corruption on economic growth in the Mediterranean countries, during the period from 1998 to 2007. Econometric analysis using panel regression has been adopted to test this effect. Individual effects models such as random effects model and fixed effects model were applied to the study sample of 160 observations, and to choose the suitable model, we implemented several tests. For our analysis, we used a basic model that includes the dependent variable GDP per capita as a factor of economic growth and the corruption perception index as the independent variable concerned. Then we completed the model with several standardized macroeconomic control variables mentioned above and applied the individual effects models. The outcomes illustrate that corruption has a negative impact on the selected Mediterranean countries’ economic growth.


2021 ◽  
Vol 9 ◽  
Author(s):  
Min Zhong ◽  
Peng Wang ◽  
Ming Ji ◽  
Xi-Hao Zeng ◽  
Hong-Xiang Wei

This paper aimed to identify the relationship between the pressure to reach economic growth targets and residents' health by applying a panel fixed effects model, a Sobel-Goodman mediation effects test and a regulatory effects model to the inland provinces of China. The empirical results verify that the pressure to reach economic growth targets in these regions reduces the level of residents' health. Moreover, the effect in developing regions is significantly stronger than that in developed regions, and the effect in the northern region is significantly stronger than that in the southern region. The mediation effects test found that the pressure to reach economic growth targets has led to an upsurge in PM2.5 concentration and an increase in the output of industrial solid waste, thereby threatening residents' health. The regulatory effects model highlights that enhancing public awareness could weaken the negative impact of the pressure to reach economic growth targets on residents' health, while the expansion of industrial production will aggravate the negative impact. In the process of economic growth, the government should set reasonable economic growth targets, pay attention to the construction of the environmental protection legal system, implement energy- conservation and emission reduction measures and increase public awareness of environmental protection to ensure residents' health.


2016 ◽  
Vol 21 (5) ◽  
pp. 626-648 ◽  
Author(s):  
Souha El Khanji ◽  
John Hudson

AbstractOur study examines the effect of water utilization together with the effect of water quality on economic growth across countries. We constructed a panel of 177 countries covering the period of 1960–2009. We analyse two dependent variables, gross domestic product per capita and the average of five years of growth. The analysis is conducted using a fixed effects model and fixed effects with instrumental variables. We find that although water utilization affects growth, water quality also proves to be highly significant and affects growth in both the short and long run to a greater degree than water quantity.


Author(s):  
Hicham Boussalham

This study attempts to assess the impact of corruption on economic growth in the Mediterranean countries, during the period from 1998 to 2007. Econometric analysis using panel regression has been adopted to test this effect. Individual effects models such as random effects model and fixed effects model were applied to the study sample of 160 observations, and to choose the suitable model, we implemented several tests. For our analysis, we used a basic model that includes the dependent variable GDP per capita as a factor of economic growth and the corruption perception index as the independent variable concerned. Then we completed the model with several standardized macroeconomic control variables mentioned above and applied the individual effects models. The outcomes illustrate that corruption has a negative impact on the selected Mediterranean countries’ economic growth.


2021 ◽  
Vol 16 (1) ◽  
pp. 130-151
Author(s):  
Fernanda Andrade de Xavier ◽  
Aparna P. Lolayekar ◽  
Pranab Mukhopadhyay

We study the effect of revenue decentralization (RD) and expenditure decentralization (ED) on sub-national growth in India from 1981–1982 to 2015–2016 for 14 large (non-special-category) states. Our study provides evidence that both RD and ED play a defining role in India’s sub-national growth in this three-and-a-half-decade period. We use a panel data model with fixed effects (FE) and Driscoll and Kraay standard errors that control for heteroscedasticity, autocorrelation and cross-sectional dependence. To test for causality between growth and decentralization, we use the Granger non-causality test. The regression analysis is supplemented with the distribution dynamics approach. We find that: (a) While decentralization Granger-caused economic growth, the reverse causality effect of growth on decentralization was not significant; (b) Economic growth increased significantly after liberalization; (c) Decentralization, capital expenditure and social expenditure had significant positive impacts on economic growth; and (d) States that had high levels of decentralization also had high levels of per capita income, while states that had low decentralization also exhibited low per capita income.


Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4762
Author(s):  
Daniela Nicoleta Sahlian ◽  
Adriana Florina Popa ◽  
Raluca Florentina Creţu

The aim of our study was to analyze whether the increase in the use of renewable energy can help GDP growth. The research carried out shows that renewable energy has the ability to decrease or neutralize the negative impact of greenhouse gases (GHG), but also to maintain economic growth. We focused our analysis on the EU-28 as we know that the EU Commission’s aim, in the near future, is to join forces to reduce the GHG used and move to renewable sources. We used a panel analysis with data between 2000 and 2019 from all Member States, and our results showed that their economic growth is influenced positively by the production of renewable energy, the GHG per capita, and the GHG intensity per GDP.


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