Nonparametric mixed exponentially weighted moving average-moving average control chart.

This research designed a distribution-free mixed exponentially weighted moving average-moving average (EWMA-MA) control chart based on signed-rank statistic to effectively identify changes in the process location. The EWMA-MA charting statistic assigns more weight to information obtained from the recent samples and exponentially decreasing weights to information accumulated from all other past samples. The run-length profile of the proposed chart is obtained by employing Monte Carlo simulation techniques.

Energy consumption and innovation-environmental degradation nexus in BRICS countries: new evidence from NARDL approach using carbon dioxide and nitrous oxide emissions.

The BRICS nations-Brazil, Russia, India, China, and South Africa-have grown significantly in importance over the past few decades, playing a vital role in the development and growth of the global economy. This expansion has not been without cost, either, since these countries' concern over environmental deterioration has risen sharply. Both researchers and decision-makers have focused a lot of attention on the connection between economic growth and ecological sustainability.

The determinants of carbon emissions in Belt and Road Initiative countries: analyzing the interactive role of information and communication technologies.

Belt and Road Initiative (BRI) countries have benefited greatly from the intelligent growth of the green economy made possible by the widespread adoption of internet and mobile phone technologies. In addition, renewable energy consumption endorses sustainable development. Therefore, the purpose of this research is to determine if the use of information and communication technology (ICT) and renewable energy consumption has an effect on sustainable development in BRI countries, while using the augmented mean group (AMG) model, AMG robustness test, and panel Dumitrescu-Hurlin causality test to get robust results.

The nexus between government spending, economic growth, and tourism under climate change: testing the CEM model for the USA.

This study examines the impact of government spending, income, and tourism consumption on CO emissions in the 50 US states through a novel theoretical model derived from the Armey Curve model and the Environmental Kuznets Curve hypothesis. The findings of this research are essential for policymakers to develop effective strategies for mitigating environmental pollution. Utilizing panel cointegration analysis, the study provides valuable insights into whether continued increases in government spending contribute to higher pollution levels.

Interconnecting sustainable development goals 7 and 13: the role of renewable energy innovations towards combating the climate change.

This research examines the trends in environmental footprints through energy innovations, digital trade, economic freedom, and environmental regulation from the context of G7 economies. Quarterly observations from 1998-2020 have been utilized for the advanced-panel model entitled Method of Moments Quantile Regression (MMQR). The initial findings confirm slope heterogeneity, interdependence between the cross-sectional units, stationarity properties, and panel cointegration.

Impact of COVID-19 on China's business and economic conditions: the importance of quantile asymmetries.

China has remained a growth engine for the global economy for the last several years. In this study, we assess the impact of COVID-19 on China's business and economic conditions; employing the quantile-on-quantile (QQ) regression and the quantile causality approaches. These econometrics batteries suit our research postulation, as they are capable to delineate underlying asymmetries across the whole distribution, based on which we can infer whether the response of China's business and economic conditions towards COVID-19 is heterogenous or homogenous.

Are economic growth and environmental pollution a dilemma?

For the first time, this study introduces-proposes using the Armey curve hypothesis (ACH) for testing the environmental Kuznets curve hypothesis (EKCH) in the relevant literature. The rationale for this new proposed methodology is that both hypotheses are expected to have similar inverted U-shaped curves. Hence, we combine the aforementioned hypotheses to obtain a single composite model.

Impact of COVID-19 and economic policy uncertainty on China's stock market returns: evidence from quantile-on-quantile and causality-in-quantiles approaches.

COVID-19 unexpectedly ensnared the entire world and wreaked havoc on global economic and financial systems. The stock market is sensitive to black swan events, and the COVID-19 disaster was no exception. Against this backdrop, this study explores the impact of COVID-19 and economic policy uncertainty (EPU) on Chinese stock markets' returns for the period spanning January 23, 2020 to August 04, 2021.

Research Methods in a Multinational Business Environment and Implications for Capital Formation: Application of Cross-Sectional Autoregressive Distributed Lag Methods.

We explore whether foreign direct investment outflows augment or obstruct public or private capital in developing countries by decomposing domestic capital into private and public capital. While developed countries are the primary source of foreign direct investment outflows (FDIOs), developing economies have become the primary source of FDIO over the past 30 years. We apply cross-sectional autoregressive distributed lag (CS-ARDL) methods to overcome the issue of endogeneity and cross-sectional dependency in our dataset.

"Does Institutional Quality, Natural Resources, Globalization, and Renewable Energy Contribute to Environmental Pollution in China? Role of Financialization".

Our study explores the impact of financialization on carbon emissions by utilizing diverse financialization proxies, particularly for China. We examine the impact of financialization, institutional quality, globalization, natural resources, trade openness, and renewable and nonrenewable energy consumption on environmental pollution over the period 1996-2017 by utilizing dynamic autoregressive distributed lag (ARDL) simulations. The empirical findings of the study indicate that institutional quality, trade, globalization, natural resources, and renewable energy consumption significantly decrease environmental pollution in the long run, while foreign direct investment and financialization have neutral effects on carbon emissions.

The role of economic policy uncertainty in the energy-environment nexus for China: Evidence from the novel dynamic simulations method.

Even though a great number of researches have explored the determinants of carbon emissions, the impact of economic policy uncertainty (EPU) on the environment has not been fully investigated in the energy-environment literature. Since recent studies show a strong relationship between the external environment and uncertainty, the present study for the first time in the literature aims to explore the function of EPU in the energy-environment nexus for China by using the novel bounds testing with dynamic simulations. The empirical results indicate that increases in the real income and energy intensity contribute to environmental pollution while increases in renewable energy lower the level of emissions.

Investigating household sector's non-renewables, biomass energy consumption and carbon emissions for Pakistan.

Concerns over the observed rising trend towards carbon emissions and the resulting adverse effects of climate change on human activities are the main challenges facing human beings. This study examines household sector's non-renewables and biomass energy consumption magnitude and how much carbon is emitted from non-renewable and biomass energy in Pakistan by using the PSLM 2018-2019 survey. In addition, using STIRPAT model, this study investigates the effect of income, household size, and clean energy on non-renewables and biomass energy choices of the household sector.

Globalization, sustainable development, and variation in cost of power plant technologies: A perspective of developing economies.

This study evaluates the sustainable power plant cost in the outlook of global power plant efficiency to reduce fossil fuel dependency and greenhouse gas emissions. For this purpose, the Global Change Assessment Model (GCAM) applied for conducting the cost assessment of power zone technologies for all principal electricity generation. This study considers the characteristics of essential factors (cement, price of resources, possible increases in employees, and metals) that affect costs.

The impacts of different proxies for financialization on carbon emissions in top-ten emitter countries.

The nexus of financialization and carbon emissions has been widely discussed in the literature. A vast body of literature that estimates the impact of financialization on carbon emissions proxies financialization with either domestic credit or market capitalization. However, these representatives do not fully respond to the complicated nature of financial development.

The relationship between urbanization, technology innovation, trade openness, and CO emissions: evidence from a panel of Asian countries.

This paper explores the dynamic relationship between CO emissions, urbanization, trade openness, and technology innovation based on the panel data of 13 Asian countries over the period of 1985-2019. The STIRPAT model is used as a framework for the analysis. For estimation purpose, panel cointegration and FMOLS techniques are utilized.