scholarly journals Impact of Private Investment, Economic Growth and Financial Development on Environmental Degradation: Evidence from Pakistan

2021 ◽  
Vol 7 (1) ◽  
pp. 13-24
Author(s):  
Shabana Parveen ◽  
Bibi Aisha Sadiqa ◽  
Sher Ali ◽  
Farrah Yasmin
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Linear Regression ◽  
Regression Model ◽  
Co2 Emissions ◽  
Financial Development ◽  
Environmental Degradation ◽  
Linear Regression Model ◽  
Private Investment ◽  
The Impact

Private investment plays an important role in the process of economic growth and also impact natural environment of a country. The main purpose of the present study is to empirically analyze the impact of private investment and other macro economic variables on environmental degradation of Pakistan. For the purpose, time series data is collected for the years  1975 to 2017. The study used Linear regression model for analyzing the impact of private investment, energy consumption, financial development and economic growth on environmental degradation. Augmented Dickey Fuller (ADF) test and Phillips Perron (PP) test is used for identifying the unit root of the variables; first with an intercept then, with an intercept and a linear deterministic trend. Akaike Information Criterion (AIC) is used for selection of optimum lag whereas Johansen cointegration test is adopted for analyzing  long run association in the variables. The results of linear regression model show that energy consumption and economic growth have a positive and statistically significant impact on CO2 emissions whereas the impact of private investment on CO2 emissions is negative. It means that in Pakistan, private investment is environment friendly. Based on study results, it is recommended that  when formulating policies for economic growth and development,  motivation should be given to private inverters in order to increase private investment.

The impact of financial development, economic growth and energy consumption on environmental degradation

2015 ◽  
Vol 26 (5) ◽  
pp. 666-682 ◽  
Author(s):  
Madhu Sehrawat ◽  
A K Giri ◽  
Geetilaxmi Mohapatra
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Financial Development ◽  
Environmental Degradation ◽  
Series Data ◽  
Development Economic ◽  
Content Type ◽  
Indian Economy ◽  
Long Run ◽  
The Impact

Purpose – The purpose of this paper is to investigate the impact of financial development, economic growth and energy consumption on environment degradation for Indian economy by using the time series data for the period 1971-2011. Design/methodology/approach – The stationary properties of the variables are checked by ADF, DF-GLS, PP and Ng-Perron unit root tests. The long-run relationship is examined by implementing the Autoregressive Distributed Lag bounds testing approach to co-integration and error correction method (ECM) is applied to examine the short-run dynamics. The direction of the causality is checked by VECM framework and variance decomposition is used to predict exogenous shocks of the variables. Findings – The empirical evidence confirms the existence of long-run relationship among the variables. Financial development appears to increase environmental degradation in India. The main contributors to environmental degradation are: economic growth, energy consumption financial development and urbanization. The results also lend support to the existence of environmental Kuznets curves for Indian economy. Research limitations/implications – The present study suggests that environmental degradation can be reduced at the cost of economic growth or energy efficient technologies should be encouraged to enhance the domestic product with the help of financial sector by improving environmental friendly technologies from advanced economies. Originality/value – This paper proposes to make a contribution to the existing literature through examining the relationship between financial development and environmental degradation in Indian economy during 1971-2011 by employing modern econometric techniques.

scholarly journals The Impact of the COVID-19 Pandemic on Electricity Consumption and Economic Growth in Romania

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2394
Author(s):  
Georgeta Soava ◽  
Anca Mehedintu ◽  
Mihaela Sterpu ◽  
Eugenia Grecu
Keyword(s):  
Economic Growth ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Negative Impact ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Electric Energy Consumption ◽  
The One ◽  
The Impact

This paper analyzes the impact of the COVID-19 pandemic on economic growth and electricity consumption and investigates the hypothesis of the influence of this consumption on the gross domestic product (GDP) for Romania. Using time series on monthly electricity consumption and quarterly GDP and a multi-linear regression model, we performed an analysis of the evolution of these indicators for 2007–2020, a comparison between their behavior during the financial crisis vs. COVID-19 crisis, and empirically explore the relationships between GDP and electricity consumption or some of its components. The results of the analysis confirm that the shock of declining activity due to the COVID-19 pandemic had a severe negative impact on electric energy consumption and GDP in the first half of 2020, followed by a slight recovery. By using a linear regression model, long-term relationships between GDP and domestic and non-household electricity consumptions were found. The empirically estimated elasticity coefficients confirm the more important impact of non-household electricity consumption on GDP compared to the one of domestic electricity consumption. In the context of the COVID-19 pandemic, the results of the study could be useful for optimizing energy and economic growth policies at the national and European levels.

scholarly journals Assessing the Impact of Factors Driving Global Carbon Dioxide Emissions

2019 ◽  
pp. 1-15
Author(s):  
Redwan Ahmed ◽  
Gabriela Sabau ◽  
Morteza Haghiri
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Financial Development ◽  
Carbon Dioxide Emissions ◽  
Well Being ◽  
Testing Procedures ◽  
Cointegration Tests ◽  
Growth Energy ◽  
The Impact

The aim of this study is to empirically investigate the causal relationship between global CO2 emissions and six of their potentially contributing factors (i.e., economic growth, energy consumption, population, trade openness, financial development and corruption), by using a panel data collected from 65 countries during 1995 to 2013. We developed a dynamic model and used a four-step testing procedures (i.e., panel unit root tests, panel cointegration tests, long-run estimates, i.e. FMOLS estimates and a Granger causality test). The results showed that the most important factors driving global CO2 emissions were economic growth, energy consumption, corruption and financial development. It is recommended that countries develop their own CO2 reducing policies by designing an appropriate combination/mix of policy tools, such as regulation, economic, voluntary and educational/ informational instruments to address their environmental pollution. Countries could consider all dimensions of well-being when they measure their economic development. Imposing pollution taxes on fossil fuel based energy supplies, developing emissions standards, strengthening anti-corruption strategies and educating people about the adverse effects of CO2 emissions on the natural environment and human health are potential policy measures.

scholarly journals Modelling Energy Consumption, Carbon Dioxide Emissions and Economic Growth Nexus in Ethiopia: Evidence from Cointegration and Causality Analysis

2018 ◽  
Vol 6 (6) ◽  
pp. 699 ◽  
Author(s):  
Shemelis Kebede Hundie
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Financial Development ◽  
Environmental Sustainability ◽  
Carbon Dioxide Emissions ◽  
Positive Impact ◽  
Trade Openness ◽  
Causality Analysis ◽  
The Impact

Policy makers need to know the relationship among energy use, economic growth and environmental quality in order to formulate rigorous policy for economic growth and environmental sustainability. This study analyzes the nexus among energy consumption, affluence, financial development, trade openness, urbanization, population and CO2 emissions in Ethiopia using data from 1970–2014. The ARDL cointegration results show that cointegration exists among the variables. Energy consumption, population, trade openness and economic growth have positive impact on CO2 in the long-run while economic growth squared reduces CO2 emissions which confirms that the EKC hypothesis holds in Ethiopia. In the short-run urbanization and energy consumption intensify environmental degradation. Toda-Yamamoto granger causality results indicate the bi-directional causality between energy consumption and CO2 emissions, CO2 emissions and urbanization. Financial development, population and urbanization cause economic growth while economic growth causes CO2 emissions. Causality runs from energy consumption to financial development, urbanization and population which in turn cause economic growth. From the result, CO2 emissions extenuation policy in Ethiopia should focus on environmentally friendly growth, enhancing consumption of cleaner energy, incorporating the impact of population, urbanization, trade and financial development.

Multiple Linear Regression Model Based Research on Relationship between Energy Consumption and Economic Growth

2011 ◽  
Vol 361-363 ◽  
pp. 1296-1299
Author(s):  
Ke Liu ◽  
Xiao Liu Shen ◽  
Yi Mo Ji
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Research Method ◽  
Multiple Linear Regression Model ◽  
Effect Factor ◽  
Policy Optimization

This paper selects energy consumption and annual GDP data of Beijing from the year of 1990 to 2009 as a sample, and adopted the research method of combining the quality and quantity, theory and empirical research, and we also employed the multiple linear regression model to analyze the effect of energy consumption to economic growth and the sensitivity of each effect factor. We wish this paper could provide a support to the future economic growth and policy optimization of energy and industry development of Beijing from theory to data.

scholarly journals A Causal Nexus of Energy Consumption, Private Investment, Economic Growth and Environmental Degradation: Evidence from Pakistan

2020 ◽  
Vol 6 (2) ◽  
pp. 367-376
Author(s):  
Shabana Parveen ◽  
Hazrat Ali ◽  
Habib Elahi Sahibzada ◽  
Sohail Farooq
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Granger Causality ◽  
Co2 Emissions ◽  
Environmental Degradation ◽  
Private Investment ◽  
Granger Causality Test ◽  
Var Model ◽  
Causality Test ◽  
Policy Makers

The importance of private investment in the growth process of a country cannot be denied, however, its relationship with environmental degradation has not got much attention from researchers yet. The present study is an attempt to divert the attention of researchers and policy makers to the association with private investment and environmental degradation.  The time series data was used from 1975 to 2017. The data was taken from WDI. To analyze the causal link among environmental degradation, private investment, energy consumption and economic growth, Vector Autoregressive (VAR) model is used. Granger causality test is employed for knowing the course of causality in the variables. The results of the VAR model suggest that if an innovation of one standard deviation occurs from outside, it takes about 12 years for CO2 emissions, 9 years for private investment, 10 years for energy consumption and about 8years for economic growth to adjust. Moreover, the results show that most of the variation in all variables is explained by their own. Granger causality test identifies four unilateral causalities in the variables running from CO2 emissions to economic growth while the consumption of energy to CO2 emissions, energy consumption to economic growth while  from economic growth to private investment. The study recommends policy makers to make environmental friendly policies regarding consumption of energy, private investment and also economic growth.

scholarly journals Analysis of the correlation between the Gross Domestic Product and the final consumption of electricity

2020 ◽  
Vol 14 (1) ◽  
pp. 59-73
Author(s):  
Liviu Valentin Vlăducu
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Linear Regression ◽  
Gross Domestic Product ◽  
Regression Model ◽  
Linear Regression Model ◽  
Electricity Consumption ◽  
Domestic Product ◽  
Efficiency Measures ◽  
The Moment

AbstractWhile the economy has shown clear signs of recovery, in quantitative terms, after the moment of the global crisis, energy production has returned to the level before the crisis, only since 2011. In this context, this paperwork aims to carry out an analysis on the existence of a correlation between the Gross Domestic Product registered in Romania and the final annual consumption of electricity. The databases used involve the data recorded for the period 2000-2018. Over time, in the specialty literature, there have been two approaches regarding the link between the economic growth and the energy consumption, respectively an approach starts from the idea that in order for economic growth to occur, energy consumption must increase, and another promotes the idea that economic growth can reduce energy consumption, by applying energy efficiency measures. To perform the analysis, a simple linear regression model was initially used in which we considered the Gross Domestic Product as a dependent variable and the Electricity Consumption as an explanatory factor (independent variable). Subsequently, analysing the results, a quadratic linear regression model was used to test the hypothesis of a more complex link between the two indicators. Following the tests performed on the two chosen variables, the Gross Domestic Product of Romania and the Final Electricity Consumption, can be argued that the energy intensity of the economy increases as economic growth reaches a certain threshold. After that threshold, economic growth is associated with the relative decrease in energy consumption.

The Nexus between Financial Development, Economic Growth and Energy Consumption in India: A VECM Technique

2020 ◽  
pp. 602-612
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Financial Development ◽  
Consumer Price Index ◽  
Development Economic ◽  
Energy Prices ◽  
Vector Error Correction ◽  
Percent Increase ◽  
Growth Energy ◽  
The Impact

The demand for energy consumption requires efficient financial development in terms of bank credit. Therefore, this study examines the nexus between Financial Development, Economic Growth, Energy Prices and Energy Consumption in India, utilizing Vector Error Correction Model (VECM) technique to determine the nature of short and long term relationships from 2010 to 2019. The estimation of results indicates that a one percent increase in bank credits to private sector results in 0.10 percent increase in energy consumption and 0.28 percent increase in energy consumption responses to 1 percent increase in economic growth. It is also observed that the impact of energy price proxied by consumer price index is statistically significant with a negative sign indicating the consistency with the theory.

scholarly journals Economic Development, CO2 Emissions and Energy Use Nexus-Evidence from the Danube Region Countries

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3165
Author(s):  
Eva Litavcová ◽  
Jana Chovancová
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Carbon Emissions ◽  
Bounds Testing ◽  
Mutual Cooperation ◽  
Long Run ◽  
Short Run ◽  
Danube Region ◽  
The Impact

The aim of this study is to examine the empirical cointegration, long-run and short-run dynamics and causal relationships between carbon emissions, energy consumption and economic growth in 14 Danube region countries over the period of 1990–2019. The autoregressive distributed lag (ARDL) bounds testing methodology was applied for each of the examined variables as a dependent variable. Limited by the length of the time series, we excluded two countries from the analysis and obtained valid results for the others for 26 of 36 ARDL models. The ARDL bounds reliably confirmed long-run cointegration between carbon emissions, energy consumption and economic growth in Austria, Czechia, Slovakia, and Slovenia. Economic growth and energy consumption have a significant impact on carbon emissions in the long-run in all of these four countries; in the short-run, the impact of economic growth is significant in Austria. Likewise, when examining cointegration between energy consumption, carbon emissions, and economic growth in the short-run, a significant contribution of CO2 emissions on energy consumptions for seven countries was found as a result of nine valid models. The results contribute to the information base essential for making responsible and informed decisions by policymakers and other stakeholders in individual countries. Moreover, they can serve as a platform for mutual cooperation and cohesion among countries in this region.

Cognition predicts days-alive-out-of-hospital after LVAD implantation

2021 ◽  
pp. 039139882110184
Author(s):  
Marykay A Pavol ◽  
Amelia K Boehme ◽  
Melana Yuzefpolskaya ◽  
Mathew S Maurer ◽  
Jesus Casida ◽  
...  
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Left Ventricular ◽  
Motor Speed ◽  
Ventricular Assist ◽  
Hospitalization Rates ◽  
Left Ventricular Assist ◽  
Patient Groups ◽  
The Impact

Objective: Cognition influences hospitalization rates for a variety of patient groups but this association has not been examined in heart failure (HF) patients undergoing left ventricular assist device (LVAD) implantation. We used cognition to predict days-alive-out-of-hospital (DAOH) in patients after LVAD surgery. Methods: We retrospectively identified 59 HF patients with cognitive assessment prior to LVAD. Cognitive tests of attention, memory, language, and visual motor speed were averaged into one score. DAOH was converted to a percentage based on total days from LVAD surgery to either heart transplant or 900 days post-LVAD. Variables significantly associated with DAOH in univariate analyses were included in a linear regression model to predict DAOH. Results: A linear regression model including LVAD type (continuous or pulsatile flow) and cognition significantly predicted DAOH (F(2,54) = 6.44, p = 0.003, R2 = .19). Inspection of each variable revealed that cognition was a significant predictor in the model (β = .11, SE = .04, p = 0.007) but LVAD type was not ( p = 0.08). Conclusions: Cognitive performance assessed prior to LVAD implantation predicted how much time patients spent out of the hospital following surgery. Further studies are warranted to identify the impact of pre-LVAD cognition on post-LVAD hospitalization.

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