An Empirical Research on the Relationship between Foreign Direct Investment and Carbon Dioxide Emission Intensity of China

2013 ◽  
Vol 807-809 ◽  
pp. 951-957 ◽  
Author(s):  
Xiao Yan Ren ◽  
Shui Li Yang
Keyword(s):  
Co2 Emissions ◽  
Direct Investment ◽  
Carbon Dioxide Emission ◽  
Granger Causality Test ◽  
Causality Test ◽  
Correction Model ◽  
Test Error ◽  
Emissions Intensity ◽  
The Relationship

In this paper, the method of carbon emissions coefficient is used to have measured the total amount of CO2 emissions and to have calculated the CO2 emissions intensity of China from 1995-2010. The relationship between FDI and CO2 emissions intensity of China is also analyzed in the paper by means of cointegration test, error correction model and granger causality test. The results indicate that there is a long-term relationship between FDI and CO2 emissions intensity of China. Furthermore, the growth of FDI makes effect on CO2 emissions intensity of China, but CO2 emissions intensity of China doesnt make effect on the growth of FDI conversely.

scholarly journals Short And Long Term Effects Of Tourism Gdp Performance In Malaysia

2021 ◽  
pp. 1333-1341
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Vector Error Correction Model ◽  
Causality Test ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Stationary Test ◽  
The Relationship

This study applies observational investigation and concentrates on two primary variables which foreign direct investment and tourism. Information from 1991 to 2019 was gathered from World Bank to focus the relationship among the variables. The tests used to decipher this result are Stationary Test, Co-integration Test, Vector Error Correction Model and Granger Causality test. First, the Stationary Test focused on the Augmented Dickey Fuller (ADF) test was measuring about the time series data’s stationary property. Next, the method used to assess the existence of the relationship between two foreign direct investment variables and tourism is the Co-integrated Test. The Vector Error Correction Model (VECM) includes a bug fix model that should focus on the core behavior of that model. VECM specifies a simulated model that changes simultaneously towards its long-term estimates. It shows that disequilibrium disease will join in to make it work longer. VECM similarly observed the relationship between the variables over time. Finally, the Granger Causality Test was performed to look at the causal relationship between the two variables which is the relationship between foreign direct investment and tourism

scholarly journals Macroeconomic Variables and Foreign Direct Investment Inflows in Turkey

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
Saliha Meftah ◽  
Abdelkader Nassour
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Short Term ◽  
Causality Test ◽  
Correction Model ◽  
Vector Error Correction ◽  
Macroeconomic Variables ◽  
Vector Error ◽  
Causality Relationship

Foreign direct investment (FDI) is an essential factor in the development of a country. This study aims to examine what factors influence foreign direct investment. By using the vector error correction model, the research shows that there is a long-term causality relationship between exchange rates and inflation with FDI. However, in the short term, there are no variables that affect FDI. Besides, the Granger causality test shows causality in the direction of GDP and FDI, while other variables do not have causality. This research has implications for policymakers to pay attention to macroeconomic variables in increasing the flow of foreign direct investment.

scholarly journals Bootstrap ARDL Test on the Relationship among Trade, FDI and CO2 Emissions: Based on the Experience of BRICS Countries

2019 ◽  
Author(s):  
Fumei He ◽  
Ke-Chiun Chang ◽  
Min Li ◽  
Xueping Li ◽  
Fangjhy Li
Keyword(s):  
Foreign Direct Investment ◽  
Causal Relationship ◽  
Co2 Emissions ◽  
Direct Investment ◽  
Export Trade ◽  
Short Term ◽  
Brics Countries ◽  
The Relationship ◽  
Cointegration Relationship

We used the Bootstrap ARDL method to test the relationship between the export trades, FDI and CO2 emissions of the BRICS countries. We found that China's foreign direct investment and the lag one period of CO2 emissions have a cointegration on exports. South Africa's foreign direct investment and CO2 emissions have a cointegration relationship with the lag one period of exports, and South Africa's the lag one period of exports and foreign direct investment have a cointegration relationship with the lag one period of CO2 emissions. But whether it is China or South Africa, these three variables have no causal relationship in the long-term. Among the variables of other BRICS countries, Russia is the only country showed degenerate case #1 in McNown et al. mentioned in their paper. When we examined short-term causality, we found that CO2 emissions and export trade showed a reverse causal relationship, while FDI and carbon emissions were not so obvious. Export trade has a positive causal relationship with FDI. Those variables are different from different situations and different countries.

scholarly journals Does Chinese FDI, Climate Change, and CO2 Emissions Stimulate Agricultural Productivity? An Empirical Evidence from Pakistan

2020 ◽  
Vol 12 (18) ◽  
pp. 7485 ◽  
Author(s):  
Shakeel Ahmad ◽  
Muhammad Tariq ◽  
Touseef Hussain ◽  
Qasir Abbas ◽  
Hamidullah Elham ◽  
...  
Keyword(s):  
Climate Change ◽  
Co2 Emissions ◽  
Agricultural Production ◽  
Direct Investment ◽  
Granger Causality Test ◽  
Test Results ◽  
Causality Test ◽  
Agriculture Sector ◽  
Long Run ◽  
Short Run

Pakistan’s agricultural sector growth is dwindling from the last several years due to insufficient foreign direct investment (FDI) and a drastic climate change-induced raise in temperature, which are severely affecting agricultural production. The FDI has paramount importance for the economy of developing countries as well as the improvement of agricultural production. Based on the time series data from 1984 to 2017, this paper aims to highlight the present situation of the agriculture sector of Pakistan and empirically analyze the short-run and long-run impact of Chinese foreign direct investment (CFDI), climate change, and CO2 emissions on agricultural productivity and causality among the variables. The Autoregressive Distributed Lag Model (ARDL) model and Granger Causality test were employed to find out the long-run, short-run, and causal relationships among the variables of interest. Furthermore, we have employed the Error Correction Model (ECM) to know the convergence of the equilibrium path. The bound test results verified the existence of a long-run association, and the empirical findings confirmed that Chinese FDI has a significant and positive impact, while climate change and CO2 emissions has negative impact on the agricultural growth of Pakistan both in the short-run and long-run. Granger Causality test results revealed that variables of interest exhibit bi-directional and uni-directional causality. The sector-wise flow of FDI reveals that the agriculture sector of Pakistan has comparatively received a less amount of FDI than other sectors of the economy. Based on the findings, it was suggested to the Government of Pakistan and policymakers to induce more FDI in the agriculture sector. Such policies would be helpful for the progress of the agriculture sector as well as for the economic growth of Pakistan.

scholarly journals The nexus between foreign direct investment and environmental sustainability in North Africa

2018 ◽  
Vol 9 (1) ◽  
pp. 57-68
Author(s):  
Marwa Lazreg ◽  
Ezzeddine Zouari
Keyword(s):  
Foreign Direct Investment ◽  
Granger Causality ◽  
Co2 Emissions ◽  
Direct Investment ◽  
Granger Causality Test ◽  
North African ◽  
African Countries ◽  
Causality Test ◽  
The North ◽  
North African Countries

This paper provides a study of the relationship between sustainable development and foreign direct investment (FDI) from an empirical point of view in the case of the North African countries during the period from 1985 to 2005. We use the cointegration test, the FMOLS (Fully Modified Ordinary Least Squares) model and the Granger causality test to examine this relationship. According to the empirical results, we confirm the existence of a cointegration relationship between the different series studied in this paper. Based on the cointegration test we can use the error correction model. Also, to test the effect of FDI on sustainable development in the North African countries, we make an estimate by FMOLS method. We found that the foreign direct investment has a positive impact on CO2 emissions. Also, the Granger Causality test confirms the presence of a bidirectional relationship between FDI and CO2 emissions (Carbon dioxide). That is to say, the FDI can cause CO2 emissions and CO2 emissions can cause FDI based on the Granger causality.

scholarly journals The Role of Foreign Direct Investment Inflows in Economic Growth in Malaysia

2021 ◽  
Vol 4 (2) ◽  
pp. g11-17
Author(s):  
Tien Siew
Keyword(s):  
Economic Growth ◽  
Unit Root ◽  
Direct Investment ◽  
Unit Root Test ◽  
Granger Causality Test ◽  
Least Square ◽  
Causality Test ◽  
Fdi Inflows ◽  
Ordinary Least Square ◽  
The Relationship

The purpose of this study is to investigate the relationship between the inflows of Foreign Direct Investment (FDI) and economic growth in Malaysia. The sample collected for this empirical study covered 30 years of data from 1991 to 2020. The secondary data was collected annually and a total of 30 observations were taken for each variable. Ordinary Least Square (OLS) regression, unit root test, several diagnostic tests and Granger causality test were used in this research to investigate the relationship between FDI inflows and economic growth. Eviews 11 was used to analyze the time series data throughout all the tests. The result showed that the inflows of FDI has a significant negative relationship with economic growth and there is no causal relationship between FDI and Gross Domestic Product (GDP). Keywords: Economic growth, FDI inflows, Granger Causality Test, Ordinary Least Square regression, Unit Root Test

scholarly journals Research on Influencing Factors of Tourism Income in Qinghai Province-Based on error correction model and Granger causality test

2021 ◽  
Vol 275 ◽  
pp. 02032
Author(s):  
Yi Chen ◽  
Jingqi Liu ◽  
Songkui Yin
Keyword(s):  
Error Correction ◽  
Granger Causality ◽  
Influencing Factors ◽  
Granger Causality Test ◽  
Error Correction Model ◽  
Causality Test ◽  
Correction Model ◽  
Qinghai Province ◽  
Tourism Revenue

As an important growth point of Qinghai’s economic development, tourism has become increasingly prominent in its contribution to the development of the national economy and has become one of the most dynamic industries in the province. Based on the relevant data from 2001 to 2018, this paper explores the influencing factors of tourism revenue in Qinghai Province by constructing an error correction model and combining Granger causality test. The research results show that there is a significant correlation between the total number of tourist visits, per capita GDP and traffic conditions, and the growth of tourism income in Qinghai Province. Among them, every 1% increase in the total number of tourist arrivals drives an average increase of 1.566% in tourism revenue; and the short-term elasticity of tourism revenue to the total number of tourist arrivals is slightly greater than the long-term elasticity.

scholarly journals Tourism and Poverty Reduction in Mexico: An ARDL Cointegration Approach

2019 ◽  
Vol 11 (3) ◽  
pp. 845 ◽  
Author(s):  
Jorge Garza-Rodriguez
Keyword(s):  
Poverty Reduction ◽  
Structural Break ◽  
Household Consumption ◽  
International Tourism ◽  
Causality Test ◽  
Correction Model ◽  
Per Capita ◽  
One Year ◽  
The Relationship

The objective of this paper was to investigate, with respect to the case of Mexico, the relationship between international tourism and the magnitude of poverty during the period of 1980–2017, through the use of an autoregressive distributed lags (ARDL) cointegration model with a structural break. The econometric results obtained in this paper indicate that there is a long-term relationship between international tourism and the reduction of poverty. It was found that for every 1% increase in international tourism, household consumption per capita increases 0.46% (and, therefore, poverty decreases). In the short term, it was found that a 1% increase in international tourism leads to a 0.11 % increase in household consumption per capita (a decrease in poverty). The coefficient of the error correction model indicates that 23.9% of any movement into disequilibrium is corrected within one year. To corroborate these results, a Toda–Yamamoto Granger causality test was carried out, indicating a unidirectional causality relationship from international tourism towards the reduction of poverty.

scholarly journals Another Look into the Relationship between Economic Growth, Carbon Emissions, Agriculture and Urbanization in Thailand: A Frequency Domain Analysis

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5132
Author(s):  
Mário Nuno Mata ◽  
Seun Damola Oladipupo ◽  
Rjoub Husam ◽  
Joaquim António Ferrão ◽  
Mehmet Altuntaş ◽  
...  
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Frequency Domain ◽  
Co2 Emissions ◽  
Frequency Domain Analysis ◽  
Causal Connection ◽  
Causality Test ◽  
Macroeconomic Indicators ◽  
The Relationship

This empirical study assesses the effect of CO2 emissions, urbanization, energy consumption, and agriculture on Thailand’s economic growth using a dataset between 1970 and 2018. The ARDL and the frequency domain causality (FDC) approaches were applied to assess these interconnections. The outcome of the bounds test suggested a long-term association among the variables of investigation. The ARDL outcomes reveal that urbanization, agriculture, energy consumption, and CO2 emissions positively trigger Thailand’s economic growth. Additionally, the frequency domain causality test was used to detect a causal connection between the series. The main benefit of this technique is that it can detect a causal connection between series at different frequencies. To the understanding of the authors, this is the first study in the case of Thailand that will apply the FDC approach to capture the causal linkage between GDP and the regressors. The outcomes of the causality test suggested that CO2 emissions, urbanization, energy consumption, and agriculture can predict Thailand’s economic growth in the long term. These outcomes have far-reaching implications for economic performance and Thailand’s macroeconomic indicators.

scholarly journals Foreign Direct Investment (FDI), Trade and Its Contribution to the Proposed Logistics Hub in Jamaica

2015 ◽  
Vol 2 (4) ◽  
pp. 44-48
Author(s):  
Kimberly Racquel Elizabeth Chin
Keyword(s):  
Foreign Direct Investment ◽  
Granger Causality ◽  
Direct Investment ◽  
Mining Industry ◽  
Granger Causality Test ◽  
Causality Test ◽  
Independent Variables ◽  
Causality Relationship ◽  
The Government ◽  
The Relationship

In order to objectively analyze contribution of logistic operations to Jamaica’s Foreign Direct Investment (FDI), we perform the Granger causality test. This test was used to determine the relationship among Gross Domestic Product (as a dependent variable) and Government Income, Trade, FDI inflow and the Exchange rate (as independent variables). The Granger causality test produced evidence of a bidirectional causality relationship which suggests that FDI’s influence on efficiency lies in the government relaxing its dependency on the mining industry for economic growth. fdi logistics

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