Showing papers on "Cointegration published in 2022"

Mitigating Emissions in India: Accounting for the Role of Real Income, Renewable Energy Consumption and Investment in Energy

Abstract: Accomplishing environmental sustainability has become a global initiative whilst addressing climate change and its effects. Thus, there is a necessity for innovation on part of economies as they seek energy for sustainable development. Thus, we explore the case of India a highly industrialized and heavy emitter of carbon emission. To this end, this study explores the effect of renewable energy, non-renewable, economic growth, and investment in the energy sector on CO2 emission in the Indian economy. Canonical Cointegration Regression (CCR), Fully Modified Least Squares (FMOLS) and Dynamic Least Squares (DOLS) were used to access the long-run elasticity of the variables as well as Granger Causality analysis to detect the direction of causality relationship among the highlighted variables. Empirical regression shows a negative relation between CO2 emission and renewable energy. Thus, suggesting that renewable energy serves as a panacea for sustainable development in the face of economic growth trajectory. However, there was a positive relationship between CO2 emission and both non-renewable and real GDP growth. On the Granger analysis, we observe a one-way causality among renewable energy consumption and CO2 emission, economic development, and energy investment. These outcomes have far-reaching policy direction of environmental sustainability target in Indian economy.

How Do Renewable Energy, Economic Growth and Natural Resources Rent Affect Environmental Sustainability in a Globalized Economy? Evidence From Colombia Based on the Gradual Shift Causality Approach

Abstract: Undoubtedly, fossil fuel energy consumption causes global warming. The question at the core is whether or not we want to quit energy consumption? The obvious answer to this question is “no.” Therefore, the necessity for innovation is curial to attain green energy and sustainable growth. This research specifically focused on Colombia, which represents the aforementioned threats to a large extent as the trajectory of economic expansion is characterized by significant CO2 emissions in Colombia. In this regard, we examine the association between globalization, renewable energy, natural resources rent, economic growth, and CO2 emissions from 1970 to 2017. The cointegration test confirmed a long association between the considered variables. This study employed the Fully Modified Ordinary Least Squares, Dynamic Ordinary Least Squares, and Autoregressive Distributed Lag estimators for the long-run analysis. The long-run empirical results uncovered growth-induced emissions in Colombia. The result illustrated that the path of development is unsustainable in Columbia. In contrast, globalization and renewable energy demonstrated a favorable contribution to environmental quality. The outcomes of the Gradual Shift Causality indicated that globalization, natural resource rent, and economic growth Granger cause CO2 emissions. The findings highlight the need to enact well-coordinated measures to reduce environmental deterioration in Colombia. Colombia must aggressively promote the development of renewable energy and also foster a better viable environment for renewable energy investment to mitigate environmental damage caused by economic growth.

Does environmental, social, and governance performance move together with corporate green innovation in China?

Abstract: This research investigates the bidirectional cointegration relationship between environmental, social, and governance (ESG) performance and corporate green innovation with a panel of 770 Chinese listed firms during the 2011–2020. We find that there exists a long-run bidirectional comovement between ESG performance and corporate green innovation output. ESG performance exerts a short-run and long-run causal link with green innovation output. The panel cointegration test and VECM estimation also support that ESG performance moves together with green innovation output for clean industries, while ESG performance only presents a long-run relationship to green invention patents output for pollution industries. Our findings offer important value for policymakers and enterprises to propose an effective strategy to stimulate green innovation and improve ESG score.

Linking institutional quality to environmental sustainability

Abstract: This study investigates the influence of democracy, autocracy, and globalization on carbon dioxide (CO2) emissions in 69 developing countries from 1990 to 2018. We used the unit root approaches to scrutinize the level of stationarity and recognize that all concern variables were unified at first difference. Pedroni and the Kao cointegration methodologies were employed for the detection of long-run cointegration, and the conclusions discovered the presence of long-run relationships among variables. Furthermore, this study applied a fully modified ordinary least square (FMOLS) approach to estimate the long-run elasticity/coefficients. The outcomes showed that democracy and renewable energy significantly overcome the pressure on the environment. However, financial development and globalization significantly increase environmental damage. Besides, the findings of an interaction term between democracy and globalization significantly reduce the pollution level, and the dampening effect of autocracy and globalization does a similar effect on environmental damage. Besides, an Inverted U-shaped environmental Kuznets curve (EKC) hypothesis was verified across the developing world. Additionally, the Feedback hypothesis is discovered between autocracy, democracy, and CO2 emissions. However, the growth hypothesis is revealed from CO2 emissions and globalization to democracy. Finally, this study also suggests some valuable policy suggestions to the governments/policymakers in general/specific regarding the developing world for endorsing their environmental sustainability.

Role of Environmental Degradation, Institutional Quality, and Government Health Expenditures for Human Health: Evidence From Emerging Seven Countries

Abstract: The current study investigates the association of various economic, non-economic, governance, and environmental indicators on human health for seven emerging economies. Covering the period from 2000Q1 to 2018Q1, this study uses various panel data approaches for empirical estimations. The data is found first-order stationary. Besides, the panel slope is heterogeneous and cross-sectional dependence is present. Further, the cointegration association is found valid among the variables. Therefore, panel quantile regression is used to determine the long-run impact of each explanatory variable on human health at four quantiles (Q25, Q50, Q75, and Q90). The estimated results asserted that economic growth, government health expenditure, and human capital significantly reduce human health disasters like malaria incidences and cases. At the same time, greenhouse gas emissions and regulatory quality are significantly and positively correlated to human health issues in emerging economies. Moreover, mixed (unidirectional and bidirectional) causal associations exist between the variables. This study also provides relevant policy implications based on the empirical results, providing a path for regulating various economic, environmental, and governance sectors. Effective policy implementation and preventive measures can reduce the spread of diseases and mortality rates due to Malaria.

Dynamic impacts of economic growth, energy use, urbanization, agricultural productivity, and forested area on carbon emissions: new insights from Kazakhstan

Abstract: • Improving environmental quality through reducing emissions is the central pillar of climate change mitigation and achieving sustainable development goals. • The empirical results indicate that increased economic growth, energy use, and urbanization lead to environmental degradation while agricultural productivity and forested area improve the environment quality in Kazakhstan. • Several unit root tests (ADF, DF-GLS, and P-P), cointegration tests (ARDL bounds test, Johansen test, and Engle-Granger test), and cointegration regression models (DOLS, FMOLS, CCR), and diagnostic tests have been utilized to confirm the accuracy of the results. • This is a pioneering attempt to reveal the dynamic impacts of urbanization, agricultural productivity, and forested area on CO 2 emissions in Kazakhstan. • This study provides recommendations for designing effective policies related to the low-carbon economy, promoting renewable energy use, sustainable urban development, climate-smart agriculture, and sustainable forest management that would reduce emissions as well as the negative impacts of global climate change. The study aims to investigate the dynamic impacts of economic growth, energy use, urbanization, agricultural productivity, and forested area on carbon dioxide (CO 2 ) emissions in Kazakhstan. Time series data from 1996 to 2020 were utilized by employing the Dynamic Ordinary Least Squares (DOLS) approach. The Autoregressive Distributed Lag (ARDL) bounds test revealed evidence of cointegration among the variables in the long run which has been verified by the Johansen cointegration test and Engle-Granger cointegration test. The empirical findings revealed that a 1% increase in economic growth, energy use, and urbanization cause an increase in CO 2 emissions by 0.14%, 0.81%, and 1.28% in Kazakhstan. Conversely, a 1% increase in agricultural productivity and the forested area may lead to CO 2 emissions reduction by 0.34% and 2.59%, respectively in the long run. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and canonical cointegrating regression (CCR). In addition, the pairwise Granger causality test was utilized to capture the causal linkage between the variables. This article put forward policy recommendations in the areas of low-carbon economy, renewable energy, sustainable urban development, climate-smart agriculture, Graphical Abstract .

Enhancing environmental quality in the United States by linking biomass energy consumption and load capacity factor

Abstract: This study analyzes the impact of biomass energy, financial development, and economic growth on environmental quality using the novel Fourier autoregressive distributed lag (ARDL) approach on annual data for the period 1965–2018 in the United States (USA). The study analyzes the impact of related variables on the load capacity factor (LCF) as well as on indicators of environmental degradation such as carbon dioxide emissions and ecological footprint. The LCF is one of the most comprehensive environmental indicators to date, encompassing both biocapacity and ecological footprint. In this regard, this study contributes to the environmental economics literature by examining, for the first time, the impact of biomass energy on the LCF. The results of the cointegration test show that there is only a long-run relationship between the LCF and the independent variables. According to the Fourier ARDL results, biomass energy improves the environmental quality, while financial development has no effect on the LCF. Moreover, the increase in per capita income reduces the LCF. Furthermore, since the income elasticity is larger in the long run than in the short-run, the environmental Kuznets curve is validated. Therefore, the United States government should encourage the use of biomass and investment in this form of energy.

Re-visiting the Environmental Kuznets curve for ASEAN: A comparison between ecological footprint and carbon dioxide emissions

Abstract: The relationship between macroeconomic factors and environmental pollution has been widely researched during the last two decades. The Environmental Kuznets Curve (EKC) has been investigated in a number of nations. However, the empirical research concentrating on evaluating two different environmental proxies for ASEAN (Association of Southeast Asian) countries has not been done earlier. Furthermore, the majority of studies considered first-generation econometric approaches since they fail to account for cross-sectional dependency in their estimation. For this intention, the study used the second generation: CADF and CIPS unit root tests, Westerlund cointegration test, fully modified ordinary least square (FMOLS) and Pooled Mean Group (PMG) to reinvestigate the EKC hypothesis in ASEAN nations between 1991 and 2016, examining two EKC specifications and comparing the validity of the EKC for consumption-based emissions (CO 2 emission) and footprint-based emissions (ecological footprint). The empirical findings indicate that: (i) when using the EF, ‘the inverted U-shaped hypothesis’ is valid in ASEAN; on the contrary, when using the CO 2 emissions, the ‘inverted U-shaped hypothesis’ is not valid in these countries; (ii) Non-renewable energy (NREC) has a significantly positive effect on EF and CO 2 emissions whereas renewable energy consumption (REC) decreases environmental pollution in these countries; (iii) Unidirectional causality is reported between economic growth and environmental degradation while a bidirectional relationship is found between NREC and EF. A Significant policy recommendation is highlighted for ASEAN countries to encourage the consumption of renewable energy to lower CO 2 emissions in the future and more efforts are needed to maintain the environmental sustainability. • This study investigates the validity of the EKC hypothesis using two different indicators of environmental quality: ecological footprint (EF) and CO 2 emissions for ASEAN. • The findings show that the EKC hypothesis is valid for the EF proxy. • The EKC hypothesis does not hold for the CO 2 emission. • Negative effects of the renewable and positive effects of non-renewable energy are found.