Analysis of Impact Factors of China's Carbon Dioxide Emissions

2012 ◽  
Vol 616-618 ◽  
pp. 1111-1114
Author(s):  
Xiao Yu Ma ◽  
Qiang Yi Li ◽  
Adili Tuergong
Keyword(s):  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Positive Impact ◽  
Dynamic Panel Data ◽  
Impact Factors ◽  
Dynamic Panel ◽  
Consumption Structure ◽  
Current Period ◽  
Per Capita ◽  
The Impact

This paper estimates the quantity of CO2 emissions in 30 provinces of China covering the year from 1999 to 2010, combining static and dynamic panel data model.Meanwhile, we use instruments to control the endogeny of the two models, analyzing the impact factors of China's CO2 emissions comprehensively and objectively. The result shows that a inverted U-shaped relationship is found between per capita GDP and CO2 emissions per capita .And it means that the Environmental Kuznets Hypothesis is verified in China.And energy consumption structure, industrial structure and urbanization have a positive impact on China's CO2 emissions. The CO2 emissions of last period have a crucial impact on the emissions of current period.

scholarly journals Real exchange rate undervaluation and sectoral growth in South Africa

2018 ◽  
Vol 9 (4) ◽  
pp. 462-476
Author(s):  
Brian Tavonga Mazorodze ◽  
Dev D. Tewari
Keyword(s):  
South Africa ◽  
Exchange Rate ◽  
Panel Data ◽  
Real Exchange Rate ◽  
Positive Impact ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
Content Type ◽  
Sectoral Growth ◽  
The Impact

PurposeThe purpose of this paper is to establish the empirical link between real exchange rate (RER) undervaluation and sectoral growth in South Africa between 1984 and 2014.Design/methodology/approachThe study employs a dynamic panel data approach estimated by the system generalised method of moments technique in a bid to control for endogeneity.FindingsThe authors find a significant positive impact of undervaluation on sectoral growth which increases with capital accumulation. Also, the authors confirm that undervaluation promotes sectoral growth up to a point where further increases in undervaluation retards growth.Practical implicationsThe results confirm the importance of policies that keep the domestic currency weaker to foster sectoral growth.Originality/valueThe originality of this paper lies in establishing the impact of exchange rate undervaluation on growth at a sector level in the context of South Africa using a dynamic panel data approach.

Value-added intellectual capital and financial performance: evidence from Mauritian companies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reena Bhattu-Babajee ◽  
Boopen Seetanah
Keyword(s):  
Financial Performance ◽  
Intellectual Capital ◽  
Positive Impact ◽  
Value Added ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
Content Type ◽  
Data Framework ◽  
Long Run ◽  
The Impact

PurposeThe purpose of this paper is to empirically assess the impact of value-added intellectual capital (VAIC) on the financial performance (FP) of companies in Mauritius.Design/methodology/approachThe research uses a dynamic panel vector error correction model (PVECM) which simultaneously allows for endogeneity and causality issues among the variables used.FindingsThe results show that VAIC enhances corporate FP, with a reported lower effect in the short run as compared to the long run. Other important determinants of firm’s performance are asset turnover, capital turnover and firm’s size. Leverage, on the other hand, is observed to be performance reducing in nature. FP of the companies is also a significant determinant of VAIC, implying reverse causal effects exist between the two variables of interest, namely, VAIC and FP.Research limitations/implicationsThe study can be enhanced by doing an industry-specific comparison of the impact of VAIC on FP for more insights.Practical implicationsIt is recommended that managers pay more attention to the role of firms’ stock of tangible and intangible assets, as this has a positive impact on firms’ FP. Also, the results may help to increase awareness of the importance of effective intellectual capital (IC) management within an organization. More so, as demonstrated by Ståhle et al. (2011), VAIC indicates the efficiency of the company’s labor and capital investments within firms in Mauritius. This study may, therefore, enable Mauritian firms to measure their IC efficiency and develop policies to promote and improve upon their intellectual potential to enhance firm’s performance.Originality/valueThe main theoretical contribution of this paper relates to the assessment and conceptualization of the bi-directional relationship between VAIC and FP. It confirmed that there are self-reinforcing feedback effects between VAIC and FP. Methodologically speaking, this paper investigates the VAIC–FP nexus in a dynamic setting using a dynamic panel data framework, namely, a PVECM which also allows for additional insights into the short- and long-run effects.

Do low gasoline prices cause more traffic fatalities in the 50 states of the USA? The importance of other factors

2019 ◽  
Vol 46 (3) ◽  
pp. 777-795
Author(s):  
Shawkat Hammoudeh ◽  
Seong-Min Yoon ◽  
Ali Kutan
Keyword(s):  
Panel Data ◽  
Alcohol Consumption ◽  
Dynamic Panel Data ◽  
Gasoline Prices ◽  
Dynamic Panel ◽  
Content Type ◽  
The Usa ◽  
The Media ◽  
Per Capita ◽  
The Impact

Purpose Motivated by the news media and a lack of comprehensive research on the USA, the purpose of this paper is to examine the relationship between changes in road fatalities and gasoline prices, per capita disposable personal income, alcohol consumption per adult, blood alcohol concentration (BAC) limits and gender. Design/methodology/approach This study employs both static and dynamic panel data models, making use of annual data over the 2000–2013 period collected from the 50 states of the USA and the consistent system GMM estimators of the parameters, to estimate the impact of these variables on fatalities per 100,000 persons and per 100,000 vehicles. Findings The results highlight the importance of gasoline prices in determining the level of road fatalities, underscoring that a 10 percent decrease in gasoline prices leads to a 248 increase in the total number of road fatalities, but with many more injuries. Increases in the female-to-total driver ratio have a greater significant positive impact on road fatalities where a 10 percent increase in this ratio increases road fatalities by 1,008 deaths. Increases in registered vehicles per capita also increase the number of fatalities. Other variables such as alcohol consumption per adult and BAC limits are not as important. Policy implications are also provided. Research limitations/implications The results of this study highlight the importance of gasoline prices in determining the number of road fatalities. This factor can be an effective policy measure by which policymakers can offset increases in fatalities due to further drastic declines in future gasoline prices. But the effects of the gasoline prices in determining the number of road fatalities are not as strong as the media would lead us to believe. The media ignores the impact of other factors on fatalities, which results in an overestimation of the impact of gasoline prices. Originality/value This study uses the panel data of 50 US states and the dynamic panel data model. In addition to gasoline price effects on the road fatalities, this study also considers other factors such as gender, gasoline taxes, per capita disposable personal income, per capita alcohol consumption, BAC limits and number of registered vehicles.

scholarly journals Impact of Population Growth on Economic Growth in Africa: A Dynamic Panel Data Approach (1980 -2015)

2018 ◽  
Vol 6 (4) ◽  
Author(s):  
Amade Peter ◽  
Ibrahim H. Bakari
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Population Growth ◽  
Negative Impact ◽  
Positive Impact ◽  
Dynamic Panel Data ◽  
African Countries ◽  
Dynamic Panel ◽  
System Gmm ◽  
The Impact

This study examines the impact of population growth on the economic growth of African countries using panel data approach from 1980 -2015. The impact of population growth on economic growth is still largely controversial at national and regional levels. The study used annual secondary data of fifty three (53) African countries sourced from the World Development Indicators database. Data were collected for economic growth, proxied by GDP, population growth, fertility rate, crude death rate and inflation rate. The data were analyzed using descriptive statistics, as well as dynamic panel models of difference and system GMM. The results of the difference and system GMM suggest that population growth exerts a positive impact on economic growth of Africa while fertility has a negative impact on economic growth of Africa. The paper concludes and recommends that population growth impacts positively on economic growth and thus African countries should adopt and implement pragmatic policy measures that will enhance the productivity of its population so as to reap more demographic dividends.

scholarly journals Bank revenue diversification: its impact on risk and return in Brazilian banks

2019 ◽  
Vol 30 (79) ◽  
pp. 91-106
Author(s):  
Jorge H. L. Ferreira ◽  
Francisco A. M. Zanini ◽  
Tiago W. Alves
Keyword(s):  
Method Of Moments ◽  
Positive Impact ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Bank Performance ◽  
Revenue Diversification ◽  
Dynamic Panel ◽  
Risk And Return ◽  
The Subject ◽  
The Impact

ABSTRACT The present study aims to determine the impact of bank revenue diversification on Brazilian banks’ risk and return. This strategy has been adopted by banks in several countries, including Brazil. In 2003, noninterest income accounted for 17.80% of the operating revenue of the banks analyzed, and in 2014, this share increased to 27.40%. While many studies have addressed the subject in American, European and Asian banks, it still has not been approached in a sample of Brazilian banks. Since the banking industry is a key variable for the financial system’s stability, it is important to study the factors that affect banks’ risk and return. We analyzed the sample for the period from 2003 to 2014, using dynamic panel data GMM (Generalized Method of Moments) to address endogeneity, heteroscedasticity and autocorrelation problems. Our main results show that noninterest income has a major role in the performance of the banks studied; our analysis of financial intermediation activities showed that loan operations produced better results than trading. Moreover, confirming the hypotheses proposed, noninterest income showed a generally positive impact on return and risk adjusted return for the banks studied. However, against our expectation, noninterest income showed a positive relationship with the risk of these banks (although not statistically significant). It is worth highlighting the control variables, i.e., real interest rate, GDP and bank growth, which were relevant in determining bank performance.

scholarly journals Study on Influencing Factors of Carbon Emissions from Energy Consumption of Shandong Province of China from 1995 to 2012

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jiekun Song ◽  
Qing Song ◽  
Dong Zhang ◽  
Youyou Lu ◽  
Long Luan
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Industrial Structure ◽  
Shandong Province ◽  
Stirpat Model ◽  
Per Capita Gdp ◽  
Consumption Structure ◽  
Per Capita ◽  
The Impact ◽  
Consumption Intensity

Carbon emissions from energy consumption of Shandong province from 1995 to 2012 are calculated. Three zero-residual decomposition models (LMDI, MRCI and Shapley value models) are introduced for decomposing carbon emissions. Based on the results, Kendall coordination coefficient method is employed for testing their compatibility, and an optimal weighted combination decomposition model is constructed for improving the objectivity of decomposition. STIRPAT model is applied to evaluate the impact of each factor on carbon emissions. The results show that, using 1995 as the base year, the cumulative effects of population, per capita GDP, energy consumption intensity, and energy consumption structure of Shandong province in 2012 are positive, while the cumulative effect of industrial structure is negative. Per capita GDP is the largest driver of the increasing carbon emissions and has a great impact on carbon emissions; energy consumption intensity is a weak driver and has certain impact on carbon emissions; population plays a weak driving role, but it has the most significant impact on carbon emissions; energy consumption structure is a weak driver of the increasing carbon emissions and has a weak impact on carbon emissions; industrial structure has played a weak inhibitory role, and its impact on carbon emissions is great.

scholarly journals An Examination of Green Credit Promoting Carbon Dioxide Emissions Reduction: A Provincial Panel Analysis of China

2021 ◽  
Vol 13 (13) ◽  
pp. 7148
Author(s):  
Wenjie Zhang ◽  
Mingyong Hong ◽  
Juan Li ◽  
Fuhong Li
Keyword(s):  
Carbon Dioxide ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Emissions Reduction ◽  
Green Finance ◽  
Carbon Emissions Reduction ◽  
Negative Effect ◽  
Emissions Intensity ◽  
The Impact

The implementation of green finance is a powerful measure to promote global carbon emissions reduction that has been highly valued by academic circles in recent years. However, the role of green credit in carbon emissions reduction in China is still lacking testing. Using a set of panel data including 30 provinces and cities, this study focused on the impact of green credit on carbon dioxide emissions in China from 2006 to 2016. The empirical results indicated that green credit has a significantly negative effect on carbon dioxide emissions intensity. Furthermore, after the mechanism examination, we found that the promotion impacts of green credit on industrial structure upgrading and technological innovation are two effective channels to help reduce carbon dioxide emissions. Heterogeneity analysis found that there are regional differences in the effect of green credit. In the western and northeastern regions, the effect of green credit is invalid. Quantile regression results implied that the greater the carbon emissions intensity, the better the effect of green credit. Finally, a further discussion revealed there exists a nonlinear correlation between green credit and carbon dioxide emissions intensity. These findings suggest that the core measures to promote carbon emission reduction in China are to continue to expand the scale of green credit, increase the technology R&D investment of enterprises, and to vigorously develop the tertiary industry.

scholarly journals Impact of unemployment and income on entrepreneurship in post-apartheid South Africa: 1994–2015

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Darma Mahadea ◽  
Irrshad Kaseeram
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Employment Growth ◽  
Positive Impact ◽  
Early Stage ◽  
National Development ◽  
Entrepreneurial Activity ◽  
Per Capita Gdp ◽  
Per Capita ◽  
The Impact

Background: South Africa has made significant progress since the dawn of democracy in 1994. It registered positive economic growth rates and its real gross domestic product (GDP) per capita increased from R42 849 in 1994 to over R56 000 in 2015. However, employment growth lagged behind GDP growth, resulting in rising unemployment. Aim and setting: Entrepreneurship brings together labour and capital in generating income, output and employment. According to South Africa’s National Development Plan, employment growth would come mainly from small-firm entrepreneurship and economic growth. Accordingly, this article investigates the impact unemployment and per capita income have on early stage total entrepreneurship activity (TEA) in South Africa, using data covering the 1994–2015 period. Methods: The methodology used is the dynamic least squares regression. The article tests the assertion that economic growth, proxied by real per capita GDP income, promotes entrepreneurship and that high unemployment forces necessity entrepreneurship. Results: The regression results indicate that per capita real GDP, which increases with economic growth, has a highly significant, positive impact on entrepreneurial activity, while unemployment has a weaker effect. A 1% rise in real per capita GDP results in a 0.16% rise in TEA entrepreneurship, and a 1% rise in unemployment is associated with a 0.25% rise in TEA. Conclusion: There seems to be a strong pull factor, from income growth to entrepreneurship and a reasonable push from unemployment to entrepreneurship, as individuals without employment are forced to self-employment as a necessity, survival mechanism. Overall, a long-run co-integrating relationship seems plausible between unemployment, income and entrepreneurship in South Africa.

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